Hacker Noon

HackerNoon 本周精选项目：Yaeum、XColdPro 和 EquipmentStack

2026-05-29T15:00:42+00:00

Welcome to HackerNoon’s Projects of the Week, where we spotlight standout projects from the Proof of Usefulness Hackathon, HackerNoon’s competition designed to measure what actually matters: real utility over hype. \n \n Each week, we’ll highlight projects that demonstrate clear usefulness, technical execution, and real-world impact - backed by data, not buzzwords.

This week, we’re excited to share three projects that have proven their utility by solving concrete problems for real users: Yaeum, XColdPro, and EquipmentStack.

:::tip Want to see your own project spotlighted here?

Join the Proof of Usefulness Hackathon to get on our radar.

:::

Meet the Projects of The Week

Meet Yaeum

https://hackernoon.com/yaeum-earns-a-74-proof-of-usefulness-score-by-building-an-ai-powered-sentence-mining-and-grammar-analysis-tool-for-k-pop-and-k-drama-fans?embedable=true

Yaeum is an innovative language learning app that allows fans of K-pop and K-drama to learn Korean directly from their favorite content using generative AI and machine learning.

Search for a Korean song, drama, or movie, and Yaeum will provide an in-depth analysis of the text, sentence by sentence, and set up a personalized vocabulary list to make memorizing new words easy. To achieve this, Yaeum taps into several open sources third party apis and uses generative AI and machine learning to analyze the texts and provide grammatical explanations as well as vocabulary.

Proof of Usefulness score: +74 / 1000

:::tip See Yaeum’s full Proof of Usefulness report

Read their story on HackerNoon

:::

Meet XColdPro

https://hackernoon.com/xcoldpro-cold-wallet-storage-earns-a-52-proof-of-usefulness-score-by-building-hardware-agnostic-cold?embedable=true

XColdPro is a patent-pending, hardware-agnostic cold storage software designed to protect both cryptocurrency keys and the host machine holding them, solving critical issues around digital asset inheritance and OS-level threat defense.

XColdPro leverages Python and Electron to deliver a cross-platform experience, secured by robust AES-256-GCM encryption and PBKDF2 with 500K iterations. The tech stack is uniquely built to operate in a fully air-gapped, no-cloud environment, while utilizing scheduled task watchdog architecture and OS-level behavioral monitoring to seamlessly integrate threat intelligence.

Proof of Usefulness score: +52 / 1000

:::tip See XColdPro’s full Proof of Usefulness report

Read their story on HackerNoon

:::

Meet EquipmentStack

EquipmentStack is a newly launched, niche content platform focused on detailed athlete equipment specifications. The platform helps enthusiasts find exactly what the pros use, diving into the labor-intensive data gathering that earned them their recent Proof of Usefulness score.

To build and manage its extensive content repository, EquipmentStack utilized WordPress as its foundational technology. Choosing WordPress allowed it to rapidly deploy a custom, SEO-friendly site that is perfectly suited for managing a highly structured database of gear and athletes without unnecessary technical overhead.

While the project is in its infancy with no verifiable user traction yet, the live site demonstrates high-quality, labor-intensive data gathering that offers genuine utility to enthusiasts.

Proof of Usefulness score: +35 / 1000

:::tip See EquipmentStack’s full Proof of Usefulness report

Read their story on HackerNoon

:::

Want to submit your project to the Proof of Usefulness hackathon?

What is Proof of Usefulness?

It's our answer to a web drowning in vaporware and empty promises. We evaluate projects based on: \n ▪️ Real user adoption \n ▪️ Sustainable revenue \n ▪️ Technical stability \n ▪️ Genuine utility

Test your project’s usefulness and submit your report on Hackernoon before August 10, 2026, to compete for over $150,000 in cash prizes and software credits.

Projects score from -100 to +1000. Top scorers compete for $20K in cash and $130K+ in software credits.

You’ll be in good company. The hackathon is backed by teams who ship production software for a living - Bright Data, Neo4j, Storyblok, Algolia, and HackerNoon.

What happens when you submit:

1. Get your free Proof of Usefulness score instantly \n 2. Your submission becomes a HackerNoon article (published within days) \n 3. Compete for monthly prizes \n 4. All participants get rewards

Complete guide on how to submit here.

:::tip 👉 Submit Your Project Now!

:::

\ That’s all for now.

Until next time, Hackers!

得益于人工智能，基本面分析的价值得到了提升

2026-05-29T14:59:59+00:00

AI is not a great equalizer. It is a great amplifier. It amplifies what you already are — for better and for worse.

TypeScript 中的主成分分析（第 4 部分）：将 PCA 转化为可解释因子分析

2026-05-29T14:29:59+00:00

Now remember how PCA collapses data with 100 dimensions into a single dimension, wouldn't it be cool if this dimension was interpretable. For example, let's say the 100 columns were like stress, smoking frequency, alcohol ml etc etc.. you see where I am going with this, the final dimension would be something like cardiac arrest or premature demise. On that cheery note, let's figure out how PCA can actually be used to label this reduced dimension.

斯瓦蒂莉娜·巴里克如何利用人工智能重塑美国移民战略

2026-05-29T14:16:00+00:00

For most people, the US immigration system feels like a black box. You submit documents, you wait and you hope. The rules shift without warning. The timelines stretch. The costs climb. And if something goes wrong, figuring out why can take months and thousands of dollars in legal fees.

Swatilina Barik decided that did not have to be the case.

A seasoned practitioner with 10+ years of hands-on experience inside immigration strategy, Barik has spent considerable time watching the same problems repeat themselves. Applicants arriving underprepared. Petitions filed with gaps that could have been caught early. Strategies chosen not because they were the best fit but because they were the most familiar. She did not see a system that needed a few upgrades. She saw one that needed to be rethought entirely.

That rethinking led to Visa Architect.

A System Built for Complexity

US immigration is not a single pathway. It is a sprawling web of visa categories, eligibility criteria, processing timelines and adjudication patterns that shift depending on country of origin, employer size, job role and a dozen other variables. Navigating it well has always required deep expertise and deep expertise has always been expensive.

Visa Architect changes that equation. The platform uses artificial intelligence to do what the best immigration strategists do but at a scale and speed that was not previously possible. It analyzes an applicant's profile, maps it against relevant visa categories, identifies potential weaknesses in a petition before it is filed and models how different approaches might play out given current adjudication trends.

The result is not just faster processing. It is smarter decision-making from the very beginning of the immigration journey.

Why Experience in the Field Made the Difference

There is no shortage of technology companies trying to automate legal processes. What makes Barik's approach different is where she started. She did not come to immigration as an outsider looking to apply a general-purpose AI tool to a new market. She came as someone who had already spent years inside the system, learning what actually trips applications up and what actually gets them approved.

That practical knowledge is embedded in Visa Architect in ways that a purely data-driven approach would miss. The platform understands not just the rules but the context around the rules. It reflects the kind of judgment that experienced practitioners develop over years and makes it accessible to a much wider range of users.

Who Benefits and How

The impact of Visa Architect reaches across the immigration ecosystem.

For individual applicants, it means entering the process with a clearer picture of where they stand. They can understand which visa pathway is genuinely the strongest fit for their circumstances rather than defaulting to whatever their employer used for the last hire. They can see potential red flags in their documentation before a case officer does. They can make informed choices rather than hoping for the best.

For businesses, particularly smaller companies that lack dedicated immigration teams, it means access to a level of strategic analysis that was previously out of reach. A startup sponsoring its first international employee no longer has to navigate the process blind.

For immigration attorneys, Visa Architect is not a replacement. It is a resource. It handles the research-heavy analytical work that consumes hours of preparation time, freeing practitioners to focus on the judgment calls, the nuanced arguments and the client relationships where human expertise is irreplaceable.

A Broader Shift in How Immigration Works

What Barik is building points to something larger than a single platform. It reflects a fundamental shift in how AI can and should be applied to high-stakes professional fields.

For years the dominant approach was to automate simple tasks and leave complex ones to humans. What Visa Architect demonstrates is that AI built on deep domain knowledge can take on genuinely complex work, not by replacing human judgment but by expanding who has access to informed guidance in the first place.

The US immigration system is not going to get simpler. Policy changes, backlogs and evolving adjudication standards are a permanent feature of the landscape. But the tools people use to navigate that landscape are changing. Swatilina Barik is building some of the most important ones. \n

:::tip This story was distributed as a release by Sanya Kapoor under HackerNoon’s Business Blogging Program.

:::

《TechBeat》：什么是预测性软件质量？AI时代的软件运维（2026年5月29日）

2026-05-29T14:00:59+00:00

How are you, hacker? 🪐Want to know what's trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. ## What is Predictive Software Quality? Software Operations in the AI Era By @playerzero [ 8 Min read ] PlayerZero explains how predictive software quality helps enterprises prevent defects, reduce firefighting, and scale reliable software development with AI. Read More.

New Research on Cloud Database Cost and Migration Trends

By @scylladb [ 4 Min read ] New research reveals why companies ignore database risks until costs, latency, or outages force migrations—and what warning signs to watch. Read More.

AI in Ecosystem Design: Where It Helps and Where It Breaks

By @tsivarev [ 7 Min read ] Where AI helps in ecosystem design, where it fails, and why human judgment must stay in the loop for trust, grants, reputation, and governance. Read More.

Can Voice Deepfake Detection Keep Up With the 1600% Surge in Fraud Attacks?

By @modulate [ 10 Min read ] Deepfake vishing surged 1600% in 2025. Most detection tools analyze text, not audio — and miss what matters. Here's how voice-native detection actually works. Read More.

The Proxy Metric Engineers Get Wrong Every Time

By @webintelligencehub [ 7 Min read ] IP pool size is a marketing number. Learn which metrics matter when evaluating proxy providers, and what to look for on their websites before you spend a dollar Read More.

Why Your Newborn Already Knows Physics (And Why LLMs Still Can't)

By @zbruceli [ 21 Min read ] Inside the biological tricks that let three-pound brains outlearn trillion-parameter machines — and the radical new architectures trying to close the gap Read More.

AI Doesn't Exist, and Poop Proves It

By @akashi-ghost [ 11 Min read ] AI is not alien or fake intelligence. It is accumulated human thought, culture, code, bias, and memory reflected back through machines. Read More.

Why macOS Is Underrepresented in Public AI Research Datasets

By @macpaw [ 5 Min read ] MacPaw Research explains why macOS is severely underrepresented in public AI datasets and introduces GUIrilla, a framework for scalable Mac UI exploration. Read More.

Undefined Behavior: Ghosts in the Fog, or Boundaries of a Model?

By @arthurlazdin [ 6 Min read ] UB isn't a dark corner of C. It's what happens when a program steps outside its computational model — and the compiler, a perfect executor, follows the math. Read More.

I Gave Hermes Agent 5 Impossible Tasks

By @syedahmershah [ 8 Min read ] I put Nous Research's hot new Hermes Agent framework through 5 brutal, multi-step tasks to see if it actually self-improves or just fails silently. Read More.

Nobody Told Me Securing APIs Was My Problem in OutSystems

By @kumar96 [ 7 Min read ] Creating third-party integration is not a problem in OutSystems. It talks about web services, OAuth, and other security in APIs Read More.

5 Characters Who Need to Be in Mortal Kombat 3

By @joseh [ 4 Min read ] Kenshi and Kintaro are just a few of the characters that should be in Mortal Kombat 3. Read More.

Here's How You Can Stop N+1 Queries Forever

By @mattleads [ 15 Min read ] A practical, working demonstration of 7 advanced Doctrine ORM strategies to eliminate the N+1 query problem in Symfony applications. Read More.

The Death of the 2-Way Quote

By @bennydoda [ 5 Min read ] AI agents will move so fast in establishing decentralised ecosystems for trading that regulators won't know where to start Read More.

We're Solving the Wrong Problem for LLMs and AI Overall

By @notllmhallucination [ 12 Min read ] A review of context and memory issues in LLMs against the methods of AI startups to solve these in biological or biology-mimicking ways. Read More.

Navigating Claude Code: MCP Servers Worth Adding

By @efimovov_5guqm5 [ 7 Min read ] MCP servers connect Claude Code to external tools. Use scopes correctly, keep credentials in env vars, and run mcp-scan on every new server. Read More.

What Happens When You Build a System Monitor for 10 Months Between €3.80/h Shifts

By @huckler [ 7 Min read ] My system monitor with its own 9-layer AI between €3.8/h retail shifts. 55 GitHub stars, 260 downloads, 10 months solo. Here's everything it does. PC Workman. Read More.

The Next Stage of QA Evolution

By @qatech [ 7 Min read ] Learn how AI-generated code is shifting software QA toward continuous verification, agentic testing, and context-aware product quality systems. Read More.

AGENTS.md Was Built to Help Agents. I Use it to Catch Them.

By @vladlensk1y [ 4 Min read ] How I use AGENTS.md and a GitHub Action to catch low-effort AI-generated PRs before wasting maintainer review time. Read More.

7 of the Best SERP APIs for SEO and Market Research in 2026

By @apilayer [ 4 Min read ] Discover 7 of the best SERP APIs for SEO and market research in 2026. Read More. 🧑‍💻 What happened in your world this week? It's been said that writing can help consolidate technical knowledge, establish credibility, and contribute to emerging community standards. Feeling stuck? We got you covered ⬇️⬇️⬇️ ANSWER THESE GREATEST INTERVIEW QUESTIONS OF ALL TIME We hope you enjoy this worth of free reading material. Feel free to forward this email to a nerdy friend who'll love you for it. See you on Planet Internet! With love, The HackerNoon Team ✌️

396 篇博客文章，带你了解创业者

2026-05-29T14:00:46+00:00

Let's learn about Founders via these 396 free blog posts. They are ordered by HackerNoon reader engagement data. Visit the Learn Repo or LearnRepo.com to find the most read blog posts about any technology.

Where founders share what they learn on the go. Read founder-related content: everything from challenges, success stories, leadership tips, to experiments.

1. Behind the startup: Interview with Alexander Busarov on Fighting Counterfeiting in China

In this interview we speak with Alex Busarov the co-founder of Taelpay about Taelpay ecosystem a blockchain application developed by the team while operating in China. Tael consists of over 50,000 users in 500 cities, hundreds of products protected with NFC chips and blockchain, all in cooperation with a long list of participating companies like Rakuten, Nestlé, New Zealand Cherry Corp,and many more. The Tael ecosystem is anchored by the Tael token which acts as a reward, loyalty, and marketing incentive for participants in the ecosystem. Now lets delve straight into the interview!

2. How to Create a Habit Tracker in Notion

Why Even Track Your Habits?

3. 11 Non-Technical Startup Founders Who Built Great Tech Products

It might be surprising to some, but even non-technical startup founders have been behind great tech products like Tinder and AirBnB without the usual background

4. The Role of Change in a Pitch Deck Answering the "Why Now?" Question

A successful pitch starts with a well-thought-out pitch deck. And the "Why now" section is arguably one of the most important aspects of that deck.

5. Exit Strategies For Tech Entrepreneurs: Knowing When And How To Sell

An exit strategy is often developed at an early stage and outlined in a business plan so that investors understand how they will receive a return of investments

6. An Interview With Ilya Sutskever, Co-Founder of OpenAI

OpenAI cofounder and chief scientist Ilya Stuskever talks about ChatGPT and the promise of models like GPT-4

7. 5 Low-Investment Business Ideas You Can Start Online

Entrepreneurship definitely is one of the most misconceived terminologies of the era. It seems like a mountain of tasks to start a business. When we think of all the time, money, and risks involved, it’ just seems so inaccessible to a regular man or woman.

8. How Jay Wey Amassed Millions of Followers on TikTok while Maintaining a Full-Time Job

In this Slogging thread, we talk to Jay Wey the Co-founder of Ubiik and social media influencer behind jayandsharon.

9. How I started my IoT Company

A biological marvel, the human itself known as homo sapiens. In the Latin language, it stands for a wise man. A wise man that survived about 200,000 years of evolution and extinction. There are many perspectives towards its survival and today I would like to share my perspective, slightly vague but different. There is a concept of what drives you that has become popular within the last decade. Certain presumptions about the driving force are based upon raw emotional aspects such as passion and rage. I find to myself that these aspects are reactions to our stubbornness to keep on going on but the negative aspect is that these reactions are short-lived and eventually man settles with peace. I would like to share a certain experience in a short period of my life that has produced results beyond my expectations. It is a small story of how I created my IoT Device converted into a product and made a company out of it.

10. Top Ten Startup Ecosystems in the World 2019: Flat Earth Ahead

We skipped last year, but this year SparkLabs Group is back with our fourth rankings and report of the Top Ten Startup Ecosystems in the World.

11. Underrated Founder Traits: The Unspoken Variables in Startup Success

In the venture capital ecosystem, there's a persistent allure for formulas, models, and hard data that investors routinely rely upon…

12. How a Solo Developer Can Make $1,100,000 Per Month

It's possible for a solo developer to build a profitable microstartup to pay the bills and live life on their own terms.

13. [Startup Founder Interview] 10 Questions for Every Startup Founder

Startup founders, here's how to get featured on HackerNoon! This startup founder interview template is based on David Smooke’s ten founder questions.

[14. How Fitt Insider Started With

a Newsletter and Reached The Top of the Fitness Industry](https://hackernoon.com/how-fitt-insider-started-with-a-newsletter-and-reached-the-top-of-the-fitness-industry) When it comes to building a successful business, the journey of Anthony Vennare, co-founder of Fitt Insider, offers invaluable insights. From leveraging persona

15. Unlock the Secret to Startup Success by Mastering the Explore-Exploit Loop

Startups need to strike a balance between seeking new opportunities and maximizing the existing ones.

16. 10 Ukrainian Founders' Stories on Leading Web3 Businesses During the War and Bear Market

Ten stories of Ukrainian founders on leading Web3 companies during the war and bear market: relocation, working under sirens, distress, and raising capital.

17. Founder Interviews: Artem Petakov of Noom

What's Your Background, and How Did That Lead You to Your Current Role?

18. I Created a Mobile App That Turns People Into Giga Chads and Memes With AI

MeMemes is a mobile app that uses AI to transform people into over 30 famous meme images.

19. 5 Great Tools To Create an MVP Without Coding [Bonus Included]

How to build a start-up or product MVP without coding

20. Yusuf Sevim on Merging Reality and Digital Realms Through MetaTime

Yusuf Sevim discusses MetaTime's revolutionary journey to fuse the real and digital using cutting-edge blockchain tech, emphasizing speed and security.

21. Tech Made in Ukraine: The People Behind the Platforms We Use Every Day

Discover how Ukrainian tech talent is driving global innovation through success stories like GitLab, Revolut, Grammarly, Wise, and Moss.

22. The Most Important Skill of a Founder: Sales

After starting two companies, I’ve learned that sales is by far the most important skill for a founder.

23. How to Hack Awareness for Your Startup — Without Content Marketing

Startups usually focus on building their product first, and don’t even try to generate leads or interest until an MVP is ready. Some will just launch on ProductHunt hoping for some lead flow. But in the best case, they will get eyeballs for two days, and then no more leads come in. And building a lead flow is not that easy.

24. 👨‍💻 Developer Insights From Robin Thurston: Founder of MapMyFitness and CEO of Outside

Robin Thurston, Outside CEO, shares insights: seize opportunities, prioritize customers, embrace mobile tech, build reward mechanisms, impact society.

25. This is How I Won Pioneer, A Fully Remote Accelerator

This is a story about how I won ‘Pioneer’ and what I learned during this program. Pioneer is a fully remote accelerator and it’s a community where entrepreneurs/indie makers help each other improve their own businesses.

26. How a First Time CTO Can Choose the Right Techstack for Their Startup

If you are a developer who is still in school or freshly (drop) out of the college or you just have a couple of years of corporate experience and have decided to take on the entrepreneurial journey as a tech-(co)founder / CTO of a startup, this series will help you understand various aspects and the role you will have to play as a technology leader for the success of your startup.

27. The Attention Economy is Worth Billions of Dollars

The average consumer’s attention is now worth billions of dollars because that’s how much companies spend on their user acquisition efforts.

28. I Helped Build 5 Companies before 34 and This is The #1 Mistake First time Founders Make

The debate was deadlocked. Three members of my team at Kanary—the platform I’d built for brands to buy digital ad space—agreed with me, and three didn’t. It was 2013, and I’d spent the last year building Kanary as the company’s founder and CEO.

29. "The Timing Was Off!" — Strava Co-Founder Mark Gainey on Popularizing Fitness on the Internet

Mark Gainey talks about the early challenges of creating Strava and how him and his co-founder built a healthy, profitable business.

30. The Stripe Atlas Review: How we Started a US Company as Non-US Residents

Here’s our end-to-end experience: how we incorporated Rapidr, Inc., a C-Corp with Stripe Atlas, and got set up with a business bank account, mailing address.

31. 9 Startup Metrics For Tech Founders To Track

In this post, you will find nine essential metrics that you should know about and measure. Your KPIs can change as your startup grows.

32. How Didactic's Move to Crowdfunding Signals Opportunity for All

Didactic's crowdfunding will change the crowdfunding space.

33. The 40 Under 40 Fueling Spain's Startup Economy

This article explores the impressive achievements of these ambitious entrepreneurs and their innovative business ideas.

34. LLC vs. Corporation: What’s the Best Structure for Your Startup?

Source: Zuza Gałczyńska, Unsplash

When starting your own business, it may be challenging to choose between an LLC and a Corporation. Here is some information that may make the decision a little less taxing.

35. 15+ Awesome Stuff to Build and Sell With JavaScript (and Friends)

Learn fifteen+ types of projects you can turn in your next side hustle or full-time arrangement to leverage your JavaScript skills in a scalable way.

36. Introducing Notion to Entrepreneurs, Founders, and Startup Executives

This long-form article is an informal introduction to Notion for entrepreneurs, founders and startup executives. It covers the basics and explains what makes this company truly special. It’s a 17 minute read full of film and pop culture references because why not. Also, this is my first blog post on the internet.

37. State of Hacker Noon 2019-2020

Photo Credit, Giphy.com/HackerNoon, where we have 1.7M impressions since creating our account in October.

38. Startup 101: From Idea to Business Model

We all from time to time come across an idea for a Startup. A company that can be a million or billion or maybe trillion-dollar worth. A company that can be next Tesla or Amazon, but sadly, 99.99999% of us don’t take the next step. That idea remains just a fragment of our memory.

39. Founder Interviews: Stephen Tse of Harmony.one

A serial founder who sold a startup to Apple and worked on infrastructure projects at Google, Harmony.one founder & CEO Stephen Tse has raised an $18M seed round and assembled one of the top engineering teams to build a next-generation high-performance blockchain protocol.

40. Zoom's Nine Year Path to Overnight Success

Zoom has been in news a lot lately. It has gone from being an enterprise solution to a household name pretty fast.

41. Founders at Work: 150+ YCombinator Founders’ Stories

Jessica Livingston's book "Founders at work" (2007, 32 stories) inspired thousands of founders to start their startups.

42. Year in Review 2020: Profitable Side Project, Startup MVPs and more

My process in building things that can invent opportunities for our business and career

43. A Conversation With John McAfee From Underground London

What a character. This interview began with Zoom breaking and we when we started a new Zoom call, McAfee pretended to talk without making sounds just to fuck with me. Then we hit record:

44. What The Non-Technical Entrepreneur Needs To Know About Tech

You’re a non-technical entrepreneur and you have a business-driven vision for your startup. As an entrepreneur, you don’t need to be a technical expert. However, you do need to know the basic concepts because many tech decisions are business decisions.

45. Founder Interviews: Max Krohn of Keybase

What's your background, and what are you working on?

46. All the Tools You Need to Emulate the Experience of Being in a Physical Office

On managing remote teams and creating an atmosphere similar to your office: Recently, I did a webinar with TIE and fellow women founders on Managing remote teams. A lot of you asked for the extensive list of tools that I mentioned in the webinar. So, here it is!

47. "When You’re Humble and Have Humility - You Rise to the Top"

Michael Gaizutis is the Founder of RNO1 – Experience Design Agency for Tech & Web3 Brands of the Future.

48. The happy ending to my burnout story

Burnout is a scary thing. It creeps in when you least expect it. And it usually takes longer than usual for you to realize it’s even happening. Let’s back up a few months.

49. Testkube: K8s Native Testing Tool

More background information on the Cloud Native Testing Tool, Testkube.

50. How to Approach Strategic Planning When the Sky is Falling

Can you remember when you used to gather in person with your team to define your roadmap and reassess your company’s collective priorities? Every quarter, our team at Pillar VC convenes for a strategic planning session to decide how we’ll invest our time and energy in the months ahead; last week, we held this meeting for the first time over Zoom. While we’ve only been working remotely for a few weeks, it feels like the world around us has changed at lightning speed.

51. Nine Lessons I Learnt Over Nine Years Running A Company

I sent the following note to the Sift team today. I’m also sharing it here in case it’s useful to others.

52. Books to Billions: How Sachin and Binny Bansal Built Flipkart to 100+ Million Customers

It is hard to imagine that one small company can completely transform the way we shop. But that is exactly what Flipkart has done. In 2007, e-commerce was still considered a niche business and most Indians did their shopping offline. Internet was taking over the world and Steve Jobs had just launched the world’s first iPhone in 2007 which was about to disrupt the entire smartphone industry in the years to come.

53. "The Abandonment of Clean Algos is the Suicide of Mainstream Social Media" - Minds CEO Bill Ottman

Bill Ottman is the co-creator and CEO of Minds, a free and open source social network with crypto rewards. They continue to make waves as an alternative to the incumbent social network business model of surveillance capitalism. Bill has also been a guest on the Joe Rogan podcast. Today, he kindly took the time to answer some questions for Hacker Noon.

54. Going From Idea to Client in 6 Weeks [Here's What We Did]

In January 2020, we met with about 45 companies. This enabled us to refine our vision (3 pivots in that month), understand our go-to-market, and start to build a list of potential clients. Once we felt confident about the product, we entered into full implementation mode.

55. Reddit's Origin Story and Persistent Path to Product Market Fit

Welcome to the first edition of Product Stories. The first product that I have chosen is Reddit — a company that thousands of startups have tried to emulate but always failed to do so. Let’s look at why that is and what’s so special about Reddit.

56. Founder Interviews: Rousseau Kazi of Threads

What's your background?

57. Founder Interviews: Jeremy Burton of Wonolo

58. Dear Startup Founders: Beware of Your Minions!

So, my dear startup founders, do you know what your minions are doing while you aren't looking?

59. NFT Adoption in Modern Companies: An Interview With Evinco Winery DAO Co-Founder, Joy Pathak

A conversation with Joy Pathak, Evinco Winery DAO co-founder, about NFTs and how they are set to change the food and beverages industry.

60. Blending AI and Human Expertise: How Smith.ai CEO/Founder is Revolutionizing SMB Customer Engagement

Discover how Smith.ai combines AI and human expertise to revolutionize 24/7 customer engagement for SMBs, driving growth through advanced virtual receptionists.

61. What Are The Good, The Bad, And The Ugly Startup Lessons From Netflix’s Movie “The White Tiger”?

What is “The White Tiger?" If you’re asking startup founders, the answer is - not just another Netflix movie, but a unique collection of great business lessons.

62. Stepping Away From Operational Management

The headspace of the owner is key, especially when they're hands-on in running their business, putting their all into it

63. A Female CTO Shares Her Thorny Journey In the Male-Dominated Tech Industry

Colette Wyatt is a Chief Technology Officer at Evolve, an award-winning UK-based software house with an R&D Centre in Ukraine. She's also a Co-Founder and COO of e-bate, a revolutionary platform for rebates management, which attracted £950,000 last year from Mercia Asset Management, the MEIF Proof of Concept & Early Stage Fund, and part of the Midlands Engine Investment Fund.

64. Founder Interviews: Lingke Wang of Ethos

Lingke Wang and the Ethos team have recently raised over $46 million in order to simplify and modernize the archaic life insurance industry.

65. The Pirate Bay Is Still Alive: Words From One of the Co-Founders

Peter Kolmisoppi explains why The Pirate Bay is still alive and some websites aren't.

66. Understanding the Different Kinds of Founder Madness

The six Archetypes of Founder Madness: Imperial Individualist, Naively Confident, Strategic Contrarian, Frontier Explorer, Mad Scientist, and Global Catalyst.

67. Meet the Man Who Has Bought Over 500 Companies

Luke Sophinos tells the story of Mark Leonard.

68. Airtable: 26 Firms Offering Non-Dilutive Funding Options to Founders

Raise money without giving up a piece of your company

69. The 11 Pieces of Advice I Would Give to My Younger Self — Thoughts on Building 'The Information'

Ten years after founding The Information, the tech journalist–CEO contemplates everything she wishes she’d known from the start.

70. Promoted from Dev to Team Lead: 8 things they didn’t tell me

I was 24 years old. A baby.

71. The Future of Gathering Information Online

Please welcome our weekly sponsor Paperform to Hacker Noon! I stumbled upon Paperform when their founder Dean McPherson contributed a number of in the trenches startup founder stories, like Stop Thinking About Scaling — For Developers Working on Crazy New Startup Ideas, to Hacker Noon. Today, we’re going to catch up on the state of this startup — and find out what makes Dean & his cofounder Dionysia McPherson do what they do.

72. Community Commerce Is the Most Underrated Growth Strategy in Modern Marketing

Community commerce is transforming growth by turning customers into advocates. Learn how brands drive trust, retention, and revenue through community.

73. Founders and MMA Fighters are More Similar Than You Think

What if startup founders learning mixed martial arts - or mixed martial arts fighters found a startup. Takeaways of traversed startup journey and sports.

74. ChatGPT Can Transform the Way Businesses Approach Customer Service

Most organizations consider customer service an overhead while it is an opportunity. It allows you to drive continued value from the customer even after a sale.

75. Startup Interview with Alex Cojocaru, CEO of Licenseware

Licenseware is the first open app ecosystem for software license management. Reduce software costs and manage licensing risks, PAYIG, completely modular.

76. The Agony of a First Time Founder

First time founders build out of passion. They face a problem and try to solve for themselves, making assumptions that everyone has the same problem.

77. From Graduating College to Raising $1+ Million Dollars in 9 months

I was studying Mechanical Engineering in my final year at college in the UK when I joined my roommate and his friend in building an app called Cluttr they started developing in the Summer of 2017.

78. Eugene Lisovskiy, Level up Basket Founder: “Community Is the Core of Everything; It Inspires Growth”

Read for opinions on growing a robust community in any niche, adapting your product to the metaverse, the power of outsourcing and the future of AI.

79. The Future of No-Code: An Interview with Parker Thompson from No-Code Report 🚀

No-Code Report is a weekly no-code newsletter, built using no-code tools like Webflow, Airtable, and Zapier. Working at a no-code analytics firm, I wanted to learn about insights in the field more broadly, so I spoke with No-Code Report's founder, Parker Thompson, on the state of the industry and its future.

80. Growth Hacking Is Dead. Trust Is the New Growth Engine.

Growth hacking once drove startup traction, but customer trust now powers sustainable growth. Learn how trust, retention, and community drive startup success.

81. From Zero to Manic

I am 36 years old and have long felt disconnected from the world. Not so much the natural world — that I’ve been lovingly drawn to and constantly in awe of as far back as I can remember.

82. Seth Flora on Entrepreneurship, HackerNoon, and His Least Favorite Thing About the Internet

Seth Flora is the owner of LEO Digital Marketing. In his spare time, he helps founders create business plans, form strategies, and more.

83. How to Not Fail Your Next Startup

Over the past 7 years I have worked in large IT companies in the Russian Federation, EU, and in the USA. Here's what I wish I knew before I started each project

84. 5 Steps to Build a SaaS Product That Gets Funded

Roughly a decade ago I decided to move away from my corporate job in investment banking in London to pursue something I always knew I wanted: to become an entrepreneur.

85. Introducing S.A.M.: The Self-leadership Framework

TL;DR: A self-leader does everything that a leader should do, but for herself. She plans, motivates, listens, and cares for herself. She uses the S.A.M. framework to put her efforts into perspective by focussing on Skills, Attitude, and Mindfulness as the core of her self-leadership practice.

86. How Threads Raised A $10M+ Series A Led By Sequoia Capital

Four fundraising tips from Rousseau Kazi of Threads.com

87. How the Founder of “SaaS for Daycare” Raised a $4.2

For parents of toddlers and babies, finding the right daycare can be a huge challenge. Jessica Chang saw this as an opportunity.

88. Looking at the Startup Ecosystem: Fundraising Market Map

This map is a visual overview of every company that helps you get an investment for your startup, from pitch decks to captable management.

89. Founders Interviews: Will Martino of Kadena

90. Advice for Founders During Uncertain Times

Having been in the VC business for 22 years now, we have had the misfortune of living through at least two major downturns. While each has its own unique characteristics, there are a few lessons that may be relevant in responding to the latest crisis.

91. Why Should You Startup?

myPluto helps small teams, young entrepreneurs and ,aspiring product managers to navigate the development of their first product in a structured manner.

92. You Are Literally Hired, If You Have This One Skill

Here is how a role most people had never heard of became the career opportunity everyone's talking about.

93. You Suck at Setting Performance Metrics

One of the most common frustrations among business professionals is performance metrics. Performance metrics are how employers value the contributions made by their employees and how employees clarify the expectations of their employer. It’s a simple tool that when used with intentionality can be a powerful asset for a company, but when used wrong can be one of the fastest ways to lose top talent and discourage your workforce.

94. Founders, Do You Have a Plan for the End of the World?

Founders and CEOs have a lot of tasks and responsibilities. Coaching the team, becoming a mentor for newcomers, and preparing for the end of the world.

95. Tech Stack Decisions are Make-or-break for Startups

Choosing lean, scalable, and adaptable tools is the smart play.

96. This Editor Uses the Power of Storytelling to Help Diverse Tech Entrepreneurs Thrive

More than half of America’s cutting-edge companies valued at $1 billion or more were established by foreign-born founders.

97. Five Tips for Applying to YC 2021

Tips and resources for applying to Y Combinator

98. Breaking The Loop Of Trust While Dealing With Real-World-Data Between The Patients And Researchers

In this interview, we spoke to the company’s Co-CEO and Co-Founder, Ashwin Rathod about its innovation.

99. How To Use OKRs For Your High-Growth Startup

Airbyte, the open-source data integration platform, shares how they performed on their OKRs for Q1 2021, and what their new OKRs for Q2 2021 are.

100. WordPress is Entering its End-Stage Founder Period

Juan Gonzalez (@Kaelon @JuanDotCo) describes how WordPress, like every founder-led enterprise, is approaching a predictably dangerous period.

101. The 10 Top Places in Europe for New Startups to Apply for Tax Breaks

It’s been roughly two months now since the Coronavirus turned our lives upside down. From practising social distancing and getting used to a life confined within four walls. To constant washing of hands and wearing masks and other Personal Protective Equipment (PPE) just to buy a loaf of bread. All the while watching strangers, friends and loved ones getting sick, COVID-19 is truly something none of us saw coming — well besides Bill Gates.

102. Delivering Zero-Fee Trading Through Sheer Determination

Anyone familiar with our project, Digitex Futures, will know that it’s been a long and eventful journey to get here. But we’ve stayed the course. Even during the worst bear market imaginable when many other projects had to throw in the towel, we’ve managed to survive.

103. Antoni Zolciak, Aleph Zero's COO & CMO, talks about creating a public blockchain

Startup interview with Antoni Zolciak of Aleph Zero, a public blockchain with enhanced privacy features. We combine academic excellence with business know-how.

104. Bootstrapping Surge: Why 57% More Founders Are Self-Funding in 2025

Pilot's annual founder survey report found that a quarter of founders are self-funding.

105. I Lost $400k ARR and Tested Positive for Covid-19 on The Same Day

March 13, 2020. I’ll remember this day as Charcoal Grey Friday in honor of my Costco sweatpants (thanks mother-in-law) and it being the hardest day of my career at GrowthHit.

106. A Conversation with Genesis Mining CEO Marco Streng

Genesis Mining CEO Marco Streng studied mathematics at the Ludwig-Maximilian University of Munich before co-founding Genesis Mining in 2013 and becoming a passionate advocate for blockchain technology and cryptocurrency.

107. Why Startups May Fail to Get Funding in 2022

If you want to start your business but don't know where to get capital, you need to find out who the investors are and why they are ready to sponsor startups.

108. Founder Interviews: Francisco Homem de Mello of Qulture.Rocks

109. Marcus Cobb Overcame A Tornado (And A Pandemic) To Raise Capital

From raising money outside of Silicon Valley to pivoting after hitting a fundraising wall, to dealing with tornados and pandemics - Jammber founder Marcus Cobb shares his top tips for startup founders.

110. Top-5 lessons I learned during Apple Entrepreneur Camp

Apple Entrepreneur Camp taught key lessons—app inclusivity, user-centered approach, product page optimization, app review preparation, and user rewards.

111. How To Say "No" At Work Without Sounding Like A Jerk

“No” is often equated with being mean but “no” isn’t about shutting projects and people down. Here's how to say no in a corporate setting without sounding rude.

112. 7 Startup Safety Considerations for New Businesses

If you’re getting your startup up and running, then you know that it takes a lot of effort and time. It also takes a lot of resources. No matter the size of the business, you are investing resources in it, and we’re not just talking about financial resources. Startup owners are also prepared to invest their time, energy, and emotions in something they truly believe in.

113. ‘It Is Never Too Late to Learn, Grow, and Inspire’: Viktor Kochetov, CEO of Kyrrex

Startup interview with Viktor Kochetov, CEO of Kyrrex.

114. Building a Mental Health Startup: Insights from a Founder

People have a wide range of different "tools" that can give them cheap and fast relief of anxiety or other psychological conditions.

115. Everything I Learned (the Hard Way) as a First-Time AI SaaS Founder

A first-time CEO shares what went right, what went wrong, and the governance mistakes every startup founder should avoid before it’s too late.

116. Assembling the Avengers of Web3: How Andrew Masanto Brought Tech's Hottest Founding Team Together

Andrew Masanto is a two-time web3 unicorn founder, having started and popularized two of the top 100 cryptocurrencies (Hedera and Reserve).

117. With AI, Coders Have More Time for Creative Coding: Malik Drabla, Co-Founder Adrenaline

In this interview, we speak with Malik Drabla, the co-founder of Adrenaline - an AI project to help coders make the best of their code.

118. Overcoming Imposter Syndrome in the Technology Industry

Hacker Noon Non-Technical Founder Podcast- Episode 53 Zack Hurley

119. Five Things I Would Have Done Differently

I don’t have many regrets in my professional career. In fact, I have none. Regretting is useless and a waste of time.

120. Opening a Bank Account is Still A Hurdle for Crypto Startups

If you’re a crypto startup dealing with stubborn institutions, you’re not alone!

121. The Non-Technical Founder

I have been speaking to Coworking spaces, Incubators and Accelerators across London and it has become apparent that there is a common problem arising from non-technical startup founders. This transcends the culture, this impacts more than just female or minority-led startups.

122. Founder Interviews: David Karandish of Jane.ai

123. The Unusual Strategy This Entrepreneur Used To Raise Most of His Round Before It Even Started

A few years ago, Matthew Klein and his brother Andrew saw that the retail landscape was changing and that companies needed more agility than ever.

124. Fundraising: No One is Going to Do It For You

My "Tough Love" Talk To Founders Who Are Struggling To Raise Capital

125. Bringing Dishonest Crypto Journalists Lies to Light - The Story of Danny De Hek and Sultan Kassam

Bringing Dishonest Crypto Journalists Lies to Light - The Story of Danny De Hek and Sultan KassamBringing Dishonest Crypto Journalists Lies to Light - The Story

126. Behind Trust Wallet: A Glimpse into the World's Leading Multi-chain Crypto Wallet

Eowyn emphasizes security in the crypto realm amidst rising cybersecurity threats.

127. How to Build a Great Team

Marc Randolph goes over the importance of building a great team.

128. State of the Cryptomarket: An Interview With BankX CEO Lance Parker

The cryptomarket is melting. The cryptomarket meltdown is a result of the bearish sentiment in the market.

129. Lior Yaffe from Jelurida on How Covid-19 Uncovers the Flaws in Our Money System

"What I see is how the pandemic is exposing the inefficiency and inequality of the existing fiat system. Governments are printing money to bailout those who recklessly spent it during the good years. Banks lending government-backed money to those who don't need it instead of helping businesses in distress." - Lior Yaffe, Co-Founder, Jelrurida

130. Founder Interviews: James Wu and Allen Lu of AdaptiLab

Childhood friends James and Allen are making it easier for companies to build machine learning teams with AdaptiLab (Techstars Seattle ‘19).

131. The Systematic Guide to Finding a Co-Founder

You’re going to spend more time with your co-founder than with your spouse. This is why finding the right one is the one activity you CANNOT afford to rush. If you’re truly passionate about founding a company, you have only two options: compromise or keep on looking.

132. How a Bunch of Little Pitching Tweaks Helped This Founder Raise $4M For His Purchasing Software…

Serial entrepreneur Andrew Hoag had a huge frustration.

133. 10 Reasons Why Startup Fails

There are a number of prominent startup examples that have been very successful in the past few decades like Facebook, Instagram, and Airbnb among others. But from these stories of success, quite a number of failure stories are left untouched. According to an estimate 9 out of 10 startups end up failing. Entrepreneurs publish post mortem online and they are quite haunting. The reasons for failure may depend upon various factors like insufficient funding, incompetent team, and lack of motivation. I have compiled a list of 10 reasons which have been the cause of startup failures.

134. Tips for Building in Public as A Founder From Europe Eu

How building in public helped the growth of my startup.

135. Startup Interviews: Josh Aziz of TransferWise

What's your background, and what are you working on?

136. Understanding the Intricacies of Growth Marketing for Lean Startups

For most companies, growth marketing is the way of the future for leveraging data and agility to scale revenue and increase customer lifetime value.

137. Founder Interviews: Matt Creager of Manifold

Matt is the co-founder & VP of Marketing and Developer Relations at Manifold, the cloud-native marketplace company.

138. Han Solo — my journey from Google to founding Kalo

Why I left Google to found an AI startup funded by Techstars and Peter Thiel.

139. Startups: Why You Shouldn't Be Afraid to Launch a Project in a Bear Market

Despite the bear market startups should not turn off their projects in the crypto industry and Web 3.0. A few tips for projects on how to start in a bear market

140. How I learned Elixir and Launched a Product in 60 days

The concepts behind Erlang/OTP/Elixir make it a great fit for a tool like the one I was building

141. Saving Cryptocurrency from Scammers: Interview with Crypto Vigilante

I think the ICO run is past us. We will not see a crazy market like we did in 2017. Scammers are very sophisticated and are always coming up with new ways to scam.

142. Exploring AgriFi: An Exclusive Interview With Tórónet Co-founder Bolaji Akinboro

True to my conviction that blockchain's enormous disruptive potential can change the status quo, I recently sat down with Bolaji to explore AgriFi and Tórónet

143. Navigating the Risks and Opportunities of Starting an AI Company

The world of AI startups is rapidly expanding, with a multitude of new players and innovative solutions in various industries.

144. Unraveling Decentralized AI Computation & Web3 with Jet Liu, Product Director at Phoenix

A conversation with Jet Liu on how a combination of AI, Web3, and innovations in computation technology can help shape the future.

145. How To Pick The Best Tech Stack for your SaaS Startup

Choosing the right set of frameworks, database, front-end tools, back-end tools to build a long lasting tech stack for your SaaS

146. The Founder Playlist: Reflections on Really Good Advice from 45 CEOs

On the Importance of Building Healthy Co-Founder Relationships, Navigating Investor Meetings, and Investing in Your Mental Health as a Founder.

147. Daniel Quoc Dung Huynh, An Entrepreneur Advocating for Open-Source Privacy-Friendly AI

Daniel Quoc Dung Huynh, CEO and Co-founder of Mithril Security, is launching a startup to democratize privacy-by-design AI tools.

148. 10 Things Every Beginner Indie Hacker Should Know

10 Lessons I learned after making $1K as an Indie Hacker

149. 10 Things To Do Right Away Before Starting Your Product Journey

We all have different roles to fulfill during a product’s journey. Some of us are heavily invested on the sales and marketing side while others consider the technical decisions as their day to day job. While segregation of work is important as well as useful for founders, there are a lot of things that all founders need to learn to make sure they are ahead on the curve as they take continuous decisions for the product and its growth. Here are 10 things to do right away as you start your product journey.

150. The NodeJS Digital Transformation Guide for Non-Technical Founders

When it comes to selecting the right back-end technology. It can be confusing to evaluate your project needs and a versatile fit for your back-end development. However, NodeJS can be the best fit for your product. Thus, hire NodeJS developers to build the best business solution. Some of the crucial factors include whether you should look for offshore or onshore hiring.

151. Six Tips to Build Awareness for Your Tech Startup

You have built a tech startup to provide an outstanding solution, but it is not necessary that all the people will understand your idea in the beginning.

152. Surviving Coronavirus Pandemic: A Guide for Startups

Yes, we’re witnessing a crisis unfolding. Not only people get gripped by the coronavirus fear. It’s like a stroke for most businesses — some will recover, some won’t.

153. How Brazil’s Newly Elected Government Will Affect Its Bustling Startup Ecosystem

With a new political wind blowing through Brazil, we need to ask: What impact might Lula's election have on the buzzing startup ecosystem?

154. How to Win the UAE Market: Promotional Strategies for Small and Medium-sized Businesses

155. If You Want To Achieve A Goal Show Up Prepared

It is important to realize that we have the ability to manufacture our own fate when we want to. - Eric Haney, Delta Force operator

156. 11 Lessons I Learned as a Tech Founder

I’ve been a full-time founder for almost a year but have been into startup culture for most of my professional career as a software engineer (~4 years).

157. You Owe Your Team Prompt Layoffs and a New Plan

Right now, the start-up community is facing upheaval. Although shelter-in-place rules tend to affect some companies more than others and hopefully will be limited to the short-term, all of us will be in uncharted territory for the rest of the year, as we navigate chaotic capital markets and a possible recession.

158. Why Are So Many Startups Built Now Only To Sell Later?

Unsuccessful startups are all alike; every successful startup has succeeded in its own way.

159. Do You Have to Code to Be in Tech?

Software Development is a route that’s proved to be very popular in the last couple of years in tech. From HTML & CSS webinars to Ruby on Rails meet ups, you can’t escape the hype. But what if coding isn’t for you? What if you want to solve problems in Tech without writing code, is there a career out there for you?

160. Top 5 Methods of Running an Effective Cryptocurrency Exchange

Anti Danilevski, KickEX CEO and founder, talks about Top 5 Methods of Running an Effective Cryptocurrency Exchange based on his own experiences in the field.

161. Founder Interviews: Satyam Vaghani of Nutanix

What's your background, and what are you working on?

162. An Intro to D-Commerce with Geoffrey Frank

Geoffrey Frank is the founder of Myntist, a startup that combines e-commerce and d-commerce platforms into a digital hybrid ecosystem.

163. Ignore the Internet (and 3 More Lessons Learned Between $10 and $1,100)

In July, my brother and I launched our first software product after nearly 2 years of working full-time on our business. We hit a big milestone that month and generated our first $10 in software revenue.

164. The One Piece Of Advice All Founders Need To Hear

Lose the to-do list, there is only one thing you need to focus on

165. 15 Advanced Cybersecurity & Web 3.0 Executives

A new breed of tech visionaries has been instrumental in driving this change and helping to deliver Web 3.0 solutions to the masses.

166. How Sound.me Simplifies AI-Powered Influencer Marketing

Explore Sound.me's journey, an AI-driven influencer platform transforming influencer marketing with simplicity, accountability, and global reach.

167. How to Name Your Startup

I’ve always found naming things to be particularly challenging. That is because a bad name is way worse than a good name is good - naming your car the “No-Go” (as the Chevy Nova was in Spanish) is far worse than a decent name like the Passat is good. Naming is, unfortunately, a negative sum game.

168. Tokenisation of Real World Assets : An Interview With OpenTrade CEO David Sutter

David Sutter is the CEO of OpenTrade, an institutional lending platform that provides users access to a suite of on-chain credit products for tokenized real-wor

169. Growing From $0 to $10 in Revenue in 24 Months

I know what you’re thinking. “That title has to be a typo. No one could grow that fast!”. I’m here to tell you that if you work hard and pursue your dreams you too can make $10 in 2 years.

170. Adadot Founder Alex on Building a Analytics Tool and being Nominated For #Noonies 2022

I’m Alex and I’m the Founder at Adadot.

171. The New Frontier: Investing in Web 3.0's Cutting-Edge Technology

I am speaking with James Wo, the CEO and founder of the investment firm Digital Finance Group, to discuss promising sectors within Web 3.0 for investment.

172. Virtual Assets, Charity, and Humanity in 2023

Philcoin is the world’s first philanthropic blockchain super dApp, says founder Jerry Lopez.

173. Why Digital Marketing Isn't Working for Your Tech Startup

That are countless blog posts that extoll the benefits and power of digital marketing. There are even more that show you exactly how to do it.

174. Doers Vs No Doers: An Analytical Approach

To start with, this is a tricky topic, where I might find people in conflict with my perception but after all when isn’t conflict a promising act. Conflict by its meaning is a disagreement where one holds an entirely opposite perspective and surely does one defend it as if it was their very own life at stake. I think that is a beauty of it, perhaps lasting for a long time that is unexpected or usual. I would put it as my experience to suggest that I have seen people get excited and enthusiastic about doing something. It can be an idea or a project or anything that they either want to achieve in life or a common goal to which one puts an effort.

175. We Made a Twist and Learned a Lot: Navigating a Startup

Learn from our twist-filled journey and gain valuable insights. Find inspiration and guidance for your own pivotal path

176. How I Went From a Freelance Developer to a Product Founder, My 10 Year Journey

A short story of a workaholic engineer switching from a developer to a product founder in 10 years.

177. Meet the Writer: HackerNoon Contributor Zaheer Dodhia, CEO and Brand Hacker

Let's make the business world beautiful with brand designs.

178. Unity Communications Founder on Building the Company

Explore Patrick Brown's vision for Unity Communications, blending superior BPO services with his love for DJing.

179. Finally Going Full Remote? Here's Everything You Need to Know First

Remote work is booming largely because of the lockdown. But this way of working has been around for a long time - especially among knowledge workers. During the pandemic, a lot of companies tested remote working for the first time, and most of them do not plan to go back to the office even after the lockdown. However, some holes need to be patched and things taken care of before any founder jumps into remote working permanently.

180. Culture and Leadership in Startups: Lessons from the Founder

Lessons from a founder on shaping startup culture that scales — from hiring and leadership to trust, transparency, and building a team you’re proud of.

181. Founder Interviews: Joe Mahavuthivanij of Mythic Markets

182. Pre-PMF Startup: How To Do It Right

In the beginning of June 2020, we had enough cash to sustain ourselves for 2 years, and had decided to pivot. At the time, we weren’t sure if we needed to move away from our product, on which revenues were growing very slowly, or not. We spent 6 weeks in full exploration mode to identify what our next step was.

183. Cash Rules Everything Around Me [Writing Prompts For Startup Founders]

Are you a startup founder? Consider filling out these writing prompts so readers can get to know your company better, and it's a great way for others to learn.

184. The Day the CEO of Meta Stopped to Like My Vision

Never underestimate the power of sharing what you think. Write, publish, post. Technology is built that way — brick by brick, idea by idea.

185. Exclusive Interview With DEGA Founder and CEO Carlos Rene

In this interview, you are going to learn more about Carlos's blockchain career and DEGA, his brainchild.

186. How to Start, Run and Sell Your Billion-dollar Business

Timeless advice to profit from your passions, capitalize on your ideas and become a better human being.

187. 5 Reasons Why You Should Do Competitive Analysis Before Building A Product

5 reasons why you should do competitive analysis before building a product ? Using competitive analysis, startup founders can get a head on in product.

188. Podcast: Kate Dudzik on AI ethics, product-led data science and more!

One thing that has become clear in the last few years is that the soft parts of data science are becoming even more important. What do I mean by soft parts? I a

189. From Corporate Job to Solopreneurship — Insights From Running My Own Mentorship Business For a Year

Achieving a €260,000 with My Central European Software Engineering Leadership Venture.

190. Duelist King Nominated as Blockchain Game Dev of the Year

Nicole Nguyen is the co-founder of Duelist King, the first NFT game powered by Dual Launch via OccamRazer IDO and PancakeSwap IFO.

191. Founder Interviews: Michael Reitblat of Forter

Forter is the leading provider in e-commerce fraud prevention, protecting $130B in digital transactions annually.

192. The 10 Most Inspirational Quotes by Miki Agrawal

Miki Agrawal shares her most thoughtful and inspirational quotes about life, entrepreneurship, technology, and not letting the haters win.

193. Serenity Shield: A Pioneering Vision For Secure Data Storage, Recovery, and Transfer

Venket Naga, CEO of Serenity Shield, talks about his journey in tech, the inspiration behind the blockchain initiative and how it aims to redefine data security

194. Unlocking the Future of DeFi: How Dolomite is Redefining the Crypto Landscape!

Adam Knuckey, co-founder of Dolomite, shares the story of its inception, the challenges faced, and the vision for the future.

195. How To Build Products Like a Scientist

Every decision and step we take at a startup is based on some belief. Here's how to validate those beliefs and build products like a scientist ;)

196. Being a Student Founder Ain't Easy

Estimated Reading Time: 14 minutes

197. Building an API-Powered Platform

On this episode. Jon Dahl, CEO of Mux, and Thierry Schellenbach, CEO of Stream, talk to Amy Tom about starting their API-powered platform.

198. Minds Behind Money: Interview With VC Zachari Saltmer, Co-Founder of One Big Fund

In this interview, we catch up with Zachari Saltmer, Co-Founder of One Big Fund to discuss the state of VC funding, AI, and crypto.

199. The Illusion of Ideas

Why untested ideas remain illusions. Only through simplicity, speed, and real-world testing can you separate what’s real from what’s not.

200. An Inspiring Story of Sowemo Tech Company Founder

Sowemo Tech Private Limited Founded by Ketan Shrivastava and Surendra yadav in July 2019. Basically its a IT service company located in heart of India at Bhopal Madhya Pradesh. Its a long journey travelled by Ketan from 2012 When Ketan was in final year of engineering in 2012. He had idea of Talent Search Portal. At that time in Bhopal Engineering students have potentials But was not much aware about Angel investors.

201. Hiring Remote Tech Talent: Overcoming the Challenges, Maximizing the Benefits

Levin shares his views on hiring remote tech talent, the benefits and challenges of remote hiring, and strategies for finding and retaining remote talent.

202. How To Explore Your Startup Idea With ZERO Money

A couple years ago I was teaching a small course at Stanford about Entrepreneurship and I remember the number one question was how to raise money.

203. 8 Things a Co-founder Can Start Doing When Others Are Busy With Product Development

Find out what you need to do as a co-founder during product development when you have little to do but still need to contribute to the success of the startup.

204. Dalip Celbeqiri On Work and Motivation [Interview]

I had the chance to talk to the Facebook Video Expert Dalip Celbeqiri who is the "go-to-person" when it comes to creative marketing. You can catch him behind the scenes, usually brainstorming and creating master plans for viral content. Dalip is one of the founders and CEO for the company Following Media Inc. His team runs the marketing for some of the biggest brands like “DIY Simple“. His team currently holds the 2nd place for “most views on a Facebook video” with more than 4.5 billion minutes viewed in a year; 100% organically.

205. A Letter of Encouragement to the Female Founders of the Future

Surveys suggest that over a third of the world’s female entrepreneurs have experienced gender bias. Only about 6.4% companies have women CEOs.

206. The Noonification: Practical Introduction to Domain-Driven Design (7/22/2023)

7/22/2023: Top 5 stories on the Hackernoon homepage!

207. 8 Legal Documents Every Business Startup Needs

‘Caution’ is not exactly a word we associate with budding entrepreneurs and founders. Many of whom thrive on passion, uncertainty, and taking calculated risks. But before you turn that spark of a great idea into a reality, it’s wise to pause and consider if you’ve covered all your legal bases. To set yourself up for optimal success, it’s critical that each new venture is built on a solid legal foundation so you’re ready and prepared for the challenges and curveballs.

208. The Strong Game of Developer To Entrepreneur

The title of CEO/Founder seems cool but it's all about burning our hands and heads by Hustling. It's not like a general race where once you run quick and finish before anyone else and win the game. To be honest, entrepreneurship is like slowly moving with high efforts for success.

209. Food Tech Stories: How To Fail Food Delivery Startup

Based on this story: Trackin: Solo Founding a +$167,000/Month Food Startup

210. CEO of Lattice: First-Time Founder Misconceptions

Jack Altman, CEO of Lattice, goes over first-time founder misconceptions.

211. Machine Learning is Driving the Future

AdValorem Angel Syndicate drives the future with investment in machine learning.

212. 20 Questions for Yearly Employee Reviews

After scouring the internet and tapping into whatever it is I've learned about building teams and leveling up the purpose of work, I came up with 20 questions for the Hacker Noon team to reflect on the year behind and improve for the year ahead. Maybe they can help your startup or team too? So, I'm publishing them here.

213. How to Find and Message Investors on LinkedIn

Here's how to look for investors on LinkedIn, and what should be in the first email to get interested in your project.

214. 6 Lessons Learned Fundraising for Our Startup in Africa

After the announcement and news on raising our first external round of capital, several budding African entrepreneurs have reached out to me through various social media channels asking, "Tesh, please could you share some tips on how you did it?" Reflecting upon the same and the numerous congratulatory messages that came streaming in this past week made me think about the struggle of fundraising, and why it is indeed a great milestone for entrepreneurs. As much as the capital we have raised ($350k) for our startup, MarketForce 360, is very 'small' - compared to some counterparts across the globe - I have come to learn that less than 0.5% of startups globally get funded by either angel investors or VC's (venture capitalists). In Africa, the statistics are worse!

215. App-Hopping: The Silent Productivity Killer and Why the Future Belongs to Niche Ecosystems

Discover why app-hopping is a productivity killer and how Unified Niche Ecosystems reclaim 59 mins/day lost to digital fragmentation and Micro-SaaS failure.

216. 20 Questions for Yearly Employee Reviews

After scouring the internet and tapping into whatever is I've learned about building teams and leveling up the purpose of work, I came up with 20 questions for the Hacker Noon team to reflect on the year behind and improve for the year ahead. Maybe they can help your startup or team too? So, I'm publishing them here.

217. "You Have to Have Privacy, But to What Scale and Under Whose Control?" - Adel de Meyer

Recently I had a chance to chat with Adel de Meyer, entrepreneur and leader of DAPS coin, a fully anonymous staking coin and payment system. Her project recently published a new DAPS whitepaper and announced its web wallet.

218. Andrew Wilkinson: Lessons Learned Based on the Last 20 Years of Running Tiny

Here's a big list of things that don't seem to work, based on the last 20 years of running Tiny:

219. My 17 Years of Tech Experience In A Few Lines

I've been working in technology for the last 17 years, and I cannot help but admit that — as rewarding as this industry seems — it's a never-ending race with time, and the speed at which the disruptive becomes outdated is unparalleled.

220. From Chemical Engineering to Content Marketing: Black-in-Tech Interview with Emmanuel Nwaka

The Black in Tech Interview with Emmanuel Nwaka.

221. In Conversation with Stewart Kohl on What He Looks For in an Investment

Stewart Kohl is Co-Chief Executive Officer of The Riverside Company, a global private equity firm based in Cleveland, Ohio with offices across North America, Europe and the Asia-Pacific region. The Riverside Company has more than $7 billion in assets under management and oversees a global portfolio of more than 80 companies. Prior to joining Riverside in 1993, Kohl served as vice president of Citicorp Venture Capital and COO of the National Cooperative Business Association in Washington, D.C

222. How Perfectionism Helped Me and Worked Against Me

As a kid I always wanted to be the best at what I did: school, sports, games, you name it. I remember playing cards with friends and if I lost and somebody laughed, I would get very upset and disappointed.

223. Representing Your Virtual Self: An Interview With Leo Nilsson From Scapin'

Today, I am talking with Leo Nilsson, co-founder of a mobile chat app - Scapin'. Scapin' is designed for our virtual identities.

224. Saving 20+ Hours a Week: How Jamie I.F. Built AffiliateFinder.ai to Automate Affiliate Recruitment

Jamie I.F., Founder of AffiliateFinder.ai on Helping SaaS Teams Automate Affiliate Recruitment and Grow Faster

225. The Secret of Networking: How High-Tech Companies Expand Into New Markets

Maxim Lukyanov shares insights on how business developers and high tech companies attain noteworthy results through the secret and power of networking

226. Introducing HanafundMe.com: the Crowdfunding Platform for Women

Starting up business, if you are cash strapped, can be pretty tough. It is still workable, but the journey is longer. Having extra funds helps you sustain your business operations and makes it easier to scale for growth.

227. Post-Acquisition Lessons on Time & Energy Management: What I'd Do Differently as a Repeat Founder

I've often fantasized about time traveling to coach my younger self. This is the advice I'd give myself when I was launching my last startup.

228. Challenges, Benefits and How Businesses Can Adopt Blockchain

The blockchain is a distributed ledger that records transactions in a permanent and verifiable way.

229. 5 Productivity Hacks for Solo Founders

Let's be honest, starting a business can be challenging, but for many people (like me) - it's a lifelong dream. Although many people feel more comfortable starting a business with a co-founder - it's not always the best decision.

230. "Lack of Focus Can Derail Even the Best Plans" says Rhythm Systems CEO Patrick Thean

Patrick Thean is an award-winning serial entrepreneur who has started and exited multiple companies.

231. Meet a Simple API for PDF Docs

PDF API, fill, generate and e-sign PDFs

232. Top Startup Directories To Submit Your Business in 2021

Recently we decided to start trying harder to market our side project, Notifier.so - Get Notified when your business is mentioned on Reddit and more, and as part of that process we submitted it to a bunch of directory sites we found in an older article.

233. Top Management Tips for Startup Founders

Here are some top dos and don'ts for startup founders, alongside some management tips for startup founders from successful entrepreneurs.

234. [Interview] How Technology Is Reshaping Transportation: Trends and Challenges

Why will more people switch to cars as their choice of transportation? When will all vehicles become self-driving? I had the opportunity to sit down and talk about these issues in greater detail with Alexander Sapov, the CEO of GetTransfer.com, one of the biggest airport-to-city transfer providers.

235. Escape the Digital Grind: How Wellness Retreats Offer a Refreshing Break

A story on wellness retreats and their benefits in today's digital age. How technology takes a toll on us and what to do about it.

236. Meet the World Bank Exec Turned Startup Founder Who Raised $3 Million for Her Vietnamese Coffee…

While Debbie Wei Mullin was fundraising for her specialty Asian beverage company, Copper Cow Coffee, she encountered frequent skepticism about its appeal: “it’s a niche product.”

237. Food Tech Stories: How These Guys Built A Multi-Billion Dollar Family Business

Who doesn’t know Panda Express? It is a fast-food restaurant chain that offers American Chinese cuisine. With over 2,200 locations, it is a forward-runner in the Asian restaurant chain niche. The idea of Panda Express was born in the United States. First restaurants used to be located in shopping mall food courts, but the chain has been expanded since then. You can see Panda Express in universities, airports, military bases, amusement parks, and other places.

238. Bootstrapping, Fundraising Or Both? How A Gritty Approach Helped Allie Magyar Raise Capital

After years of running events for huge companies, Allie Magyar decided she was spending too much of her time hovering over a fax machine.

239. Build vs. Buy: The AI Martech Conundrum

Lomit Patel, Chief Growth Officer at Tynker, provides an overview of the pros and cons when building or buying an AI martech solution to capitlise on growth.

240. How to Excel When Hiring for Your Startup

Often, the problem lies not in hasty or incorrect hiring decisions but rather in the failure to correct a wrong decision promptly.

241. Story behind the Feelin App

Feelin | Share what you feel

242. How To Run a Tight Fundraising Process

Why you have to own your process from end-to-end

243. The Tyler Hochman Interview: Building a B2B Workforce Analytics Company

Interview with Tyler Hochman, CEO of FORE Enterprise.

244. Interview with Hyunkeun Yoon, COO of Karaoke Blockchain Platform, SOMESING

A self-starting entrepreneur with 13 years of experience in HR managing, Hyunkeun Yoon. SOMESING is another Blockchain project, which recently won at the Blockbattle Korea 2.

245. Richard Stallman: Everything You Need to Know About Him

Sarah Mei goes over Richard Stallman.

246. 2020 Founder Review: Product, Community and Challenges

Year Highlights for TAIKAI's Product, Community and Challenges.

247. Empowering Business Agility: An Interview with Fabian Veit, CEO at MAKE

Discover how MAKE Founder & CEO Fabian Veit drives innovation with visual no-code automation, empowering businesses to adapt, innovate, and outpace competition.

248. #FoundersConnect: Abdul Hassan, CEO & Founder of Mono, Backed by Ycombinator

FoundersConnect: Abdul Hassan, CEO & Founder of Mono, Backed by Ycombinator

249. Thrilled to be Recognized as a Trending Startup in Jaipur, India

Emizentech is recognized as one of the trending startups in Jaipur India in 2022 by Hackernoon.

250. The Entrepreneur's Balancing Act: Cultivating Success While Nurturing Life's Dimensions

Embark on an entrepreneurial journey while maintaining balance in health, finance, relationships, and spirituality. Thrive in all aspects of life! 🚀🌟

251. How To Create Personal Breakthroughs By Mastering EI: Interview With Matt Kursh

A recent nationwide survey aiming to better understand the “before and after” of emotions in relation to the COVID-19 pandemic has found that people’s #1 emotion now is anxiety, and before the outbreak, the #1 emotion was calm.

252. From Connected Cars to Mental Health: Ivan Mishanin's Journey as a Co-Founder and Tech Leader

How to build successful companies and what tech leader should look like in the AI era?

253. David Brunk On Revolutionizing Legal Trust Through Smart Contracts

In this exclusive interview, Brunk delved into the origin of DTrust, the benefits and risks associated with smart contract-based trusts

254. How I Quit My Job to Start My Online Business

I quit my job. I'm now unemployed. It feels great to finally be able to write this blog post.

255. Successful Founders Built Lives That Energize Rather Than Drain Them

Your home life isn't separate from your business. It's the foundation everything else is built on.

256. Thought Leadership and Startups: the Path is the Goal

Don’t aim to ‘become a thought leader’. It’s not about the label. But do strive to make a difference in your industry with thought leadership.

257. Top 7 Promising SaaS Entrepreneurs in 2021 You Should Not Miss

The article gives you an idea of how the top SaaS companies made progress and ranked themselves in the top list.

258. Mozilla Summer Startup Studio and MVP Lab

TLDR: See mozilla.org/builders for more details regarding our summer programs!

259. Top Reasons For Tech Startups Failure And What To Do To Avoid It

The millennials are too tired of 9 to 5 jobs and a monotonous lifestyle for a decade now. They have a good skill set and corporate experience, which pushes, them to open startups with the knowledge gained from their work environment. But does everyone see success in venturing startups, and what are the difficulties they face to be consistent in their entrepreneurial dreams? Let us see the top 10 reasons for tech startups fail and how we can recover and be ready with measures to overcome the failures:

260. Ilya Rouss: “Travel Trends to Watch: digital nomads, non-mainstream places, local economies growth”

When the travel industry will recover after the pandemic, what will the travel experience look like and how modern tech will influence it?

261. Redwerk Founder on How to Stand Out in a Crowded, AI-Assisted Software Development Market

Redwerk’s Founder shares how the company became a trusted tech partner for Fortune 500s, serving 773M users through custom software and digital transformation.

262. Todays 5 Ideas: 31.08.2020

A text editor where Pac-Man will start eating the text whenever you press backspace.

263. Here's Why We Invested in Turing — The Future of CPG Formulation

Iteration is the new innovation…

264. Why Your Product Is Scaling Faster Than Your Story Can Handle

When product scale outpaces narrative clarity, teams accumulate narrative debt. A systems view of why growth quietly breaks alignment first.

265. How to Build a Successful WEB3 Startup in Three Easy Steps (There Are No Easy Steps)

Building a successful WEB3 startup is more like trying to navigate a maze blindfolded while riding a unicycle and fighting wild feral hogs, but you can do it!

266. 4 Tips SaaS Founders can use to Optimize their Sales Funnel

This article will show you 4 tactics for optimizing your SaaS sales funnel

267. Tech founder, Why Haven't You Become a Designer Yet?

No, seriously, why not? It’s cool to be a designer, a creative person who DJs vinyl sets in a funky club at night and starts the morning with a double-filter coffee and a vegan croissant overlooking the sea to get inspired for the next advertising campaign. Not a bad stereotype, right?

268. 7 Reasons Why Your MVP may Never Launch

269. "Founder Bottleneck" Might Prevent Your Next Raise or Exit

Founder dependence isn’t just an operational bottleneck, it’s a risk multiplier that will kill any operator's chance of exiting a business.

270. Carina Ayden On Being an Environmentalist Founder Building Resilient Products

Carina Ayden, the founder of Unimaginable foods, shares her perspective on the sustainable lifestyle and becoming an environmentalist.

271. The Interpretation Gap: Why Capability Is Outpacing Trust, and Valuation Is Paying the Price

Advanced systems are scaling faster than markets can interpret them.

272. Women in Tech: Interview With Maja Roknic, CPO and Co-Founder at CulturePulse AI

CulturePulse's fearless female co-founder and CPO pushes the boundaries of product development in AI.

273. 5 Business Lessons from IBM Surveyed CEOs for a Post-Pandemic World

After the uncertainty of the year 2020, we have to admit: the new order came up from the chaos, and as a result, the business priorities were reconfigured too.

274. What to Know Before Joining an Accelerator

Starting a business is hard and requires making tough decisions. More than that, most startups struggle to find the necessary investment. This is why many startup founders seek to join an accelerator that will make the initial investment and provide quality mentor support.

275. 2 or 3 Under 20ish Awards⁠—Hacker Noon's #Noonies Nominees for 2019

Hacker Noon—where hackers start their afternoons, has partnered with Stream to present the first inaugural Noonies 2019: The Tech Industry's Greenest Awards. You can help Hacker Noon declare the best and worst of this year's tech scene by voting every day from today until August 16th!

276. Female Entrepreneur Miki Agrawal Champions Global Sustainability Initiatives With TUSHY

Miki Agrawal champions ongoing global sustainability and eco-friendly hygiene through her professional and personal life.

277. How Does One Trade Crypto in Canada and the USA?

By a deep study into the market systems before launch, the company pointed out shortcomings within the crypto industry.

278. Stop Thinking Big and Start Thinking About the Daily 1% Improvement

The only way to learn is by starting and doing things relentlessly. You should go deep into a chosen space, and don't worry about making big leaps.

279. Roles Of Support Are The New Normal

Are you being the best leader you can be? Is your leader effective? here are some useful tips on how to do better.

280. "Develop the Habit of Upgrading Yourself," Advises Muhammad Bilal

Muhammad Bilal (Pakistan) is a 5x 2020 Noonie Nominee for contributions to the Entrepreneurship, Founders, IoT, Life, and Life Lessons tag categories on Hacker Noon. In this interview, Muhammad shares personal perspectives regarding self-awareness, problem solving, and stagnation.

281. The Key to Succeeding With Founder-Led Sales

Sam Blond discusses founder-led sales.

282. Meet the Writer: HackerNoon Contributor Omer Rosenbaum, CTO and Co-Founder at Swimm.io

My name is Omer, I am the CTO and Co-Founder of Swimm, a devtool that helps developers and their teams manage knowledge about their codebase.

283. DeFi Today: In the Words of Builders in the Space

It might just be a sign of the times, and it definitely feels like so much has been said about DeFi already.

284. My College Startup Failed; This is What I Learned

College is a great place, you make new friends, try new things, and have no shortage of homework. During my freshman year at Iowa State, aside from doing normal college things, I spent my time learning as much as possible about how people have made technology solve problems for society and everything that goes into making these ideas a reality.

285. Four Tips for Capitalizing on Security Posture to Expedite Business Growth

Cybersecurity is often cited as a minefield for businesses, and while this cliche remains true, it has become slightly outdated.

286. 12 Product Design Principles While Working in Small Startups

If you are aware of the values of carrying out the Product Design Process, then you are halfway through the success!

287. What Happens When Purpose Is Assumed, Not Discovered

A cautionary tale of ambition, denial, and the costly consequences of building a startup without a clear problem to solve or customers to serve.

288. 7 Things Tech Entrepreneurs Should Know Before Starting a Business

To start your own business or a startup you don’t need to have a degree in business specialization or business experience. All you need is to know how business works and do proper business planning.

289. Making the Leap to Solopreneur

It was a big, scary decision to make—going from a conventional 9-to-5 desk job working in operations of a small company, to launching my own digital business where I work as a content manager and writer.

290. The Founders Survey Winners Are: Gmail, Mailchimp, Slack, Trello, Hubspot, Zoom and Custom Code

As Startups, we have a habit of moving fast. But in our haste, did we pick the right tools for the job?

291. Cassie Founder, Nicky Watson, Answers: 10 Questions for Every Startup Founder

Founder Nicky Watson shares insight into her company, Cassie, with HackerNoon's '10 Questions for Every Startup Founder' interview template.

292. Why Indie Products Differentiation Is Important And How To Achieve It

Analyzing how successful indie businesses are able to differentiate themselves.

293. Brutal Facts: Most Artists Can't Draw

Roy Simmons coined that phrase and I like it a lot. “Most artists can’t draw.”

294. 🎓 How I am Learning Sales as a Technical Founder

As a first time founder embarking on my (intended to be a VC-backed) startup journey 🚀, I quickly realized there are a lot of skills that I need as a founder that I didn’t have. I was comfortable with talking to customers & product development due to my engineering background but I massively struggle with copywriting, marketing, and the most important one — Sales 💸.

295. "The most important thing for any ad is to know your audience," - says George Thomas McCormick

George Thomas McCormick is the founder of SOAR: a full-funnel Facebook & Instagram marketing agency. SOAR's main offering is creating and running profitable Facebook and Instagram ad campaigns for its clients.

296. #FoundersConnect: Interview with Michael 'Trojan' Okoh - Co-founder and CTO, ThePeer

22-year old Founder of ThePeer, Michael Trojan Okoh, shares his story with me.

297. Lessons Learned From Successful Founders Building in Public

Valuable Lessons learned from 5 successful public building founders.

298. The 3 Traits I Never Compromise On When Hiring a Dream Team

A strategic framework for hiring high-potential talent — even if they lack experience. Based on real-life practice, behavioral psychology, and experience.

299. This CEO Got Bill Gates’ Attention—Now He’s Fueling AI with Memgraph’s Speedy Graph Tech

Dominik Tomicevic, founder and CEO of Memgraph answers ten questions for startup founders from HackerNoon Founder and CEO David Smooke.

300. 7 Stories To Learn About Davis Baer

Learn everything you need to know about Davis Baer via these 7 free HackerNoon stories.

301. How a Founder’s Passion Can Hinder Startup Success

It is common advice for founders to build only things they are passionate about. But, there's another side to that story.

302. $1.3M in Funding for Rural Colorado Founders via the Greater Colorado Pitch Series 2.0

This year, applicants to the Greater Colorado Pitch Series can apply for 4 different capital tracks and $1.3M in total investment is available.

303. The Productivity Trap Engineers Fall Into: Work That Never Ships

It looks like progress, it feels like progress. But nothing ships. This is avoidance in a very nice hoodie.

304. Journey with my startup so far

The many pivots of building a startup from a UK Founder

305. Meet the Writer: HackerNoon's Contributor Marianna Alshina, Chief Business Development Officer

Interview with Marianna Alshina, CBDO at Know Your Dosh for Hackernoon.

306. Experiment Loudly. Learn Quietly.

The fastest way to build predictable, sustainable growth is learning which signals deserve your focus and which are just noise.

307. 5 Most Important Tips Every Data Analyst Should Know

The 5 things every data analyst should know and why it is not Python, nor SQL

308. Andros Wong's Wonder is Providing DAOs with Technical Infrastructure

Wonder has one key concept and it is that “the future is collaborative”

309. Insights From the Co-Founder of Genopets: Building a Blockchain-Powered Gaming Platform

Join us as we sit down with Jay, the Co-Founder of Genopets, as he shares his journey in building a blockchain-powered gaming platform and the insights he gaine

310. Startup CEOs: Here’s Good News You Can Include in Your 2020 Board Deck

As you prepare for your board meetings, you might be struggling to find some good news to share with the board. Sure, it’s a mistake to go into a board meeting pretending everything is going well — board meetings are a valuable opportunity to share your startup’s challenges and get guidance from a panel of trusted advisors.

311. Beyond Excel and Google Sheets: Innovations in Handling Massive Spreadsheets Amidst the Big Data Rev

We spoke to Jason Hines, the Co-founder of Gigasheet, a big data spreadsheet platform…

312. How Founders Can Adapt to the New Normal

The ongoing pandemic has impacted not only our lives but also the global economy. COVID-19 will stay with us for months to come and it is unlikely that our world will ever look the same. This is the time to adapt.

313. How We Built Arengu — Story and Vision of Our Startup

Arengu was officially founded in May 2018, but we had to come a long way before finding our value as a company. Today, we'd like to share our road with you, so you can get inspired and learn from our story.

314. 5 Types Of Fear That Millions Of People Feel

Fear of missing out

315. Time Off Isn't An Issue: The Key Practices Helping Me Lead Remotely Right Now

I’ll not deny it. I love being in a physical office with coworkers. I love being around people with the same objectives and challenges. It gives me strength and motivation.

316. How Public Product Roadmap Help Us to Understand Our Users

To what extent do you allow your users and customers guide your development process? This is a question we have grappled with over the last year and, frankly, continue to debate passionately at our morning pow wow. But, today is the first time we have shipped a purely user-requested feature and it feels like a significant milestone.

317. When is The Right Time to Step Down as Your Startup's CEO?

Here's why you can't and shouldn't be your startup's CEO forever. Eventually, if you're lucky, it'll come time to let someone else manage your baby.

318. Interview: BrainCo CEO on The Future of Brain Machine Interface Tech

BrainCo is a tech company that is dedicated to developing Brain Machine Interface technology, and it is the first Chinese team chosen by Harvard Innovation Lab. Located in Somerville, MA, the company is adjacent to Harvard University and MIT.

319. The Dumbest Thing We Do as Startup Founders

The dumbest thing we do as startup founders is to not share equity with one another.

320. Interview with AnavClouds Founders: How To Build a Million Dollar Company

The founders of AnavClouds Software are both Salesforce professionals, doing well in their own spheres of work. They happened to meet through a common friend of theirs and started working together for some time. As the volumes grew they decided over a cup of steaming coffee that it was the right time to start a venture of their own, in 2016.

321. Building Armenia’s First Live Seafood Supply Chain: A Business Case in Market Creation

How I built Armenia’s first live seafood supply chain by combining custom systems, logistics, and smart business strategy.

322. Current Market Outlook: Insights for Seed Stage Founders

This short briefing note is prepared for founders who are considering, or are in the process of raising seed capital. The last few weeks have seen a significant shift in terms of the fundraising atmosphere, and investors’ appetite for risk.

323. The HackerNoon Newsletter: Dear Startup Founders: Beware of Your Minions! (10/16/2024)

10/16/2024: Top 5 stories on the HackerNoon homepage!

324. 10 Features For A Successful Community: An Open Letter

If you’re like us, you probably have some unread red-dot notifications in your Slack sidebar. Work-related, a few are from social groups or communities

325. The Best Way to Measure Real KPIs? - DON'T Add a Link to your Product

How many people will click to check out the website shouldn't matter when you are trying to validate a product.

326. Startup Wrappers Can Be Insanely Valuable

SaaS businesses (particularly ones for technical users) sometimes have to deal with a vocal outcry that their product “is just a wrapper around” something. The implication is that ‘a wrapper’ is inherently not valuable, and it’s impossible to build a great business around such a product. This logic is a product of lazy thinking and myopia; ‘wrappers’ can be insanely valuable.

327. Where The Heck Should You Incorporate A Remote-Based Company?

A hands-on guide for remote founders choosing where to incorporate. Real lessons, legal tips, and why Delaware keeps coming out on top.

328. Meet the Writer: Sergey Prilutskiy is The Co-founder of Blockchain Company, MixBytes

Short interview with Sergey Prilutskiy, developer, researcher, security specialist, co-founder of MixBytes company, and Hackernoon author.

329. The Zen of Building Financial Models: 9 Tips for Startup Founders

9 tips to improve your financial modeling game as a founder.

330. HackerNoon & The Wild West of Startups

Amy Tom chats with David Smooke (co-founder and CEO of HackerNoon) about his founder's journey with HackerNoon, and with Storm Farrell (Software Developer at Ha

331. How To Recruit, Train, and Retain Skilled UX Designers

A “ready” UX designer is a rare encounter in the wild. Designers usually do know how to make things pretty – but when it comes to the product logic and interactions design, few feel at ease. The inevitable solution is to hire people with a relevant background and upgrade them to real UXers: host lectures, give homework, provide practice opportunities.

332. The Most Dangerous Lie in Startups

Most founders skip a founder agreement because they trust each other. But when pressure hits - that missing structure becomes the root of chaos.

333. FourWeekMBA Founder Gennaro Cuofano On Heuristic Decision Making

Gennaro Cuofano (Italy) writes about digital business models, platforms, blockchain business models, and new ways of doing business, all the while managing the growth of a high-tech startup and a small sales team. In this interview: Decentralization, Scaling, and Building Your Own Platform.

334. Where Should Advisors Fit Into Your Business?

Do you need an advisor to help you through challenges? It’s another expense, not an immediate contribution to the top line. What to do?

335. How To Manage Your Business During Pandemic

In this Pandemic, Businessman is losing so much money they know it. If your elementary business base on offline, then their barely any chance of making money however If your business on online, then you can make some money because the e-commerce websites are helping out of there are services. I know some startup company their primarily based on online. One of my close friends, he shares some cold facts, how he manages his business in this pandemic.

336. Pivot via Repositioning

The restroom story

337. Here’s Everything I Learned Building a Blog to Teach Cybersecurity

It was in early 2025 that I initiated my own blog, OpenExploit.in, with one simple aim: to make cybersecurity easy to learn and available to all.

338. How We Scored $125 MRR and 497 Followers Pre-launch

Hey Hackernoon family! I havent contributed an article in a long time but I wanted to share how we grew our newsletter, Product Byte, to 497 subscribers and $150/mrr (6 paid members) before we even launched.

339. Tech Is Shaping the Airlines Business: Here's How

In this episode of "Flying into the Future: How Tech is Shaping the Airlines Business," Omri Hurwitz welcomes esteemed guest Nathaniel Felsher.

340. AI Meets Crypto: A Conversation With EmpyrX Founder And CEO Cam Sandifur

In this interview with Olayimika Oyebanji, Cam discussed EmpyrX and the importance of AI.

341. While Investors Scour for Homeruns, Founders Should Prioritize Getting on Base

If investors only know how to spot short-term, moonshot yields, is it possible that the overwhelming majority of successful startups get overlooked?

342. Using Efficient Knowledge Transfer to Increase Information's Half-Life: Remote Weekly #26 📝

Today, I want to talk to you about the life of information and how that fundamentally impacts remote working.

343. Discover the 'Cheat Codes' for the Difficult 'Game' of Giving Care

If the game is unbeatable, frustration takes over and the game is tossed aside.

344. The Unseen Areas Augur Your Future Failure

It is 1943 and you are Head of the United States Eighth Air Force. Your mission is to destroy Germany's ability to wage war and free up the skies for the Allied Forces. The problem is that your Bombers are being zapped out of the sky like mosquitos drawn into the fire in a summery night.

345. "As a founder, I am looking for risk-takers" #Noonies2021

I am scared that more and more people are captivated by networked systems (and their tricks) that push them to move faster but not to become better thinkers.

346. No Stanford Degree? No Problem. Here’s How to Win as an Underdog Founder

Startups love to talk about disruption, but when it comes to funding, the system still favors the familiar.

347. The HackerNoon Newsletter: Dear Startup Founders: Beware of Your Minions! (10/15/2024)

10/15/2024: Top 5 stories on the HackerNoon homepage!

348. “Four-Day Workweek? I Hate It.” Top Fintech Founder Max Faldin About Building a Remote-First Startup

Silverbird Founder Max Faldin about Building a Remote-First Startup

349. How We're Helping Black Founders Succeed with Launch Like a Mogul

Growing up and entering adulthood post-college, I always knew that I wanted to be in a position to help the Black community succeed and break barriers.

350. From a Mac Mini, Running Windows XP, to Streaming Giant: The Twitch Come-Up

A brief look at Twitch's humble beginnings, as well as pivotal decisions that turned their fortunes around.

351. How to Balance Investor Relations and Product Growth

Learn how to strategically align investor relations with product growth for sustainable business success and revenue optimization.

352. Fortuitapps Founder on Applying Imagination to Solving Problems And Noonies 2022 Nomination

Hey HackerNoon Readers! I’m Nicolas and I’m the founder of Fortuitapps.

353. A Statement From Hayden Adams - The Inventor of Uniswap

Hayden Adams on Uniswap.

354. Pioneering Personalized Learning: How TinyTap's Yogev Shelly Revolutionizes Childhood Education

Yogev Shelly is the founder and CEO of TinyTap. TinyTap is the world’s largest library of educational games for young learners.

355. The Highs and Lows of My First Real Startup, CoLaunchly

Discover the journey of launching CoLaunchly, its challenges, and insights on startup life, burnout, and growth

356. Success in Startupland Demands that You Stop Thinking and Start Doing

I’m normally a pretty big thinker. I like to analyze decisions and thoughts all the way out in the future and plan for all of the various contingencies. What happens if x goes wrong and then I’m in situation y? How will that affect a, b, and c? And I continue down the rabbit hole until I can’t see the light anymore.

357. From Fluorescent Lights to Sporting NFTs

It pays to be neurodiverse - Ben Appleby escaped school and followed his instincts - now he is a co founder of an exciting web3 sporting platform launching soon

358. 3 Best Tips To Attract Investors Being An Outsider

Unshackled Ventures founding partner Nitin Pachisia explains three ways he built a strong network during his fundraising journey.

359. Knowing When to Hard Pivot Might Be This Year's Most Valuable Skill

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360. The Food Truck: An Old Business Idea Worth Exploring?

Food trucks have been around for quite some time now, an idea sprung forth from an older necessity-driven idea, the chuckwagon. It is a simple proposition, really: instead of the public going to a restaurant or diner to eat, the food comes to them. One could consider it the older cousin of straight-to-your-door food delivery.

361. From Small Failures to Big Wins: An Interview With Marco Calamassi on Mindset

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362. What I Learn When I Failed a Project

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363. The Power of Saying "I Assume the Risk and Its Consequences"

I share how taking full responsibility for risks (without hiding my fear) has shaped my leadership, empowered my team, and strengthened our company culture.

364. When Startup Advice Backfires: Avoiding Common Pitfalls That Slow Your Growth

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365. How To Write a Manifesto

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366. 6 Lessons From YC Startup School Delhi SMB Meetup #1

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367. If Your Deck Confuses Smart People, It’s Not a Smart Deck

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368. #FoundersConnect: How Erika Brodnock, Founder of Kami, Uses Tech to Improve the Lives of Families

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369. Bernard Moon, 3x Noonies Nominee, Co-Founder of SparkLabs group AMA

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370. Matt Huang, Co-founder of Paradigm, Confirms That Paradigm Is Dedicated to Crypto

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371. Start with 3 Workflows, Not "AI Transformation"

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372. "Let the market decide what it wants," says Jeremy Britton, Co-founder and CFO of Bostoncoin

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373. How Running a Venture Capital Firm is Similar to Playing Basketball

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374. Pioneering Online Bookings: A Talk with Nachum Kligman, CEO of Book Like A Boss

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[375. When We Can Pitch Startups at Events

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376. What Is Bonjoro And How It Can Help You Make Money Off Cold Contacts

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377. 7 Tips for Co-founder Dating Success

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378. 'Digital Information is Easy to Manipulate': Göran Almgren, Co-founder Enigio

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379. How We Carved A Niche For An Rx Delivery Service

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380. Chris Orzechowski on Building 100+ Year Brands

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381. Perfecting The Art Of Investor Updates: How-to Guide And A Template

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382. The First Finance Hire You Make Will Either Save You or Confuse You

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383. Web3 Founder Survey: Product-Market Fit and Timing Are Most Existential Challenges

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384. 4 Reasons Why SaaS Will Benefit Your Business Big Time

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385. Your Perfect Deck: Why Your Audience Needs Direction, Not More Information

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386. Making VR Accessible: Lessons from Scaling a Startup to a Global Network

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387. Helping CEOs make Sense of the Modern IT 'Acronym Soup'

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388. To Trust or Not To Trust? That is the Question

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389. How to Filter Out Bad Startup Advice

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390. Ask Me How To Lose Your Company Without Losing Your Faith

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391. "Don't Listen To Other People", Interview with Leia Ruseva

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392. A PSA On Being the Average Of The 5 People You Spend The Most Time With

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393. "Have Faith, Be Open, Trust Yourself", Interview with Chris Castiglione

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394. #MyStartInTech: Interview With Guim Gonzalez, Founder & CEO of Xatet Technologies

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395. How Founders Ship Commitments Before They Ship Understanding

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396. Setbacks Suck—But This One Made My Web3 Startup Bulletproof

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Thank you for checking out the 396 most read blog posts about Founders on HackerNoon.

Visit the /Learn Repo to find the most read blog posts about any technology.

《时间旅行的谬误：为何回到过去会改变现在》

2026-05-29T13:00:43+00:00

Table of Links

I. Introduction

II. Pseudoscience

III. Unidentified Assumption

IV. False Assumption

V. Objection

VI. Conclusion and References

VI. CONCLUSION

When we assume that zero change to the past implies zero change to the present, we impose the information structure of the present universe onto its past structure – that is, we assume that everything will turn out the same, except for those events (and their chaotic interactions) that were changed in the past. Unfortunately for aspiring time travelers, this notion is false.

\ Traveling into the past logically requires changing the present, no matter how careful one is to avoid a temporal paradox. Hopes to travel into the past without changing the present, such as by avoiding any physical interaction within the past, are unfounded. Because all serious proposals for time travel into the past inherently assume Eq. 1, which has been shown false on a priori logical grounds, their treatment as scientific proposals are pseudoscientific.

\ [1] Pienaar, J.L., Ralph, T.C. and Myers, C.R., 2013. Open timelike curves violate Heisenberg’s uncertainty principle. Physical Review Letters, 110(6), p.060501.

\ [2] Godel, K., 1949. An example of a new type of cosmological solutions of Einstein’s field equations of gravitation. Reviews of Modern Physics, 21(3), p.447.

\ [3] Morris, M.S., Thorne, K.S. and Yurtsever, U., 1988. Wormholes, time machines, and the weak energy condition. Physical Review Letters, 61(13), p.1446.

\ [4] Deser, S. and Jackiw, R., 1992. Physical cosmic strings do not generate closed timelike curves. Physical Review Letters, 68(3), p.267.

\ [5] Deutsch, D., 1991. Quantum mechanics near closed timelike lines. Physical Review D, 44(10), p.3197.

\ [6] Hartle, J.B., 1994. Unitarity and causality in generalized quantum mechanics for nonchronal spacetimes. Physical Review D, 49(12), p.6543.

\ [7] Politzer, H.D., 1994. Path integrals, density matrices, and information flow with closed timelike curves. Physical Review D, 49(8), p.3981.

\ [8] Goldwirth, D.S., Perry, M.J., Piran, T. and Thorne, K.S., 1994. Quantum propagator for a nonrelativistic particle in the vicinity of a time machine. Physical Review D, 49(8), p.3951.

\ [9] Hawking, S., 2009. A brief history of time: from big bang to black holes. Random House.

\ [10] Hawking, S.W., 1992. Chronology protection conjecture. Physical Review D, 46(2), p.603.

\ [11] Thorne, K., 1995. Black Holes & Time Warps: Einstein’s Outrageous Legacy. WW Norton & Company.

\ [12] Popper, Karl, 1962. Conjectures and refutations. The growth of scientific knowledge, New York: Basic Books.

\ [13] Boekholt, T.C.N., Portegies Zwart, S.F. and Valtonen, M., 2020. Gargantuan chaotic gravitational threebody systems and their irreversibility to the Planck length. Monthly Notices of the Royal Astronomical Society, 493(3), pp.3932-3937.

:::info Author:

(1) Andrew Knight, J.D (aknight@alum.mit.edu)

:::

:::info This paper is available on arxiv under CC BY 4.0 license.

:::

使用 ML Ki 在 Android 上构建实时 OCR

2026-05-29T12:18:52+00:00

In early 2026, I'm sitting there, 8 PM, trying to get Tesseract OCR to work. JNI errors. Native library crashes. My APK is 52MB for some reason. I'm Googling "tesseract android crash armeabi" for the hundredth time.

Wednesday evening I deleted everything and tried ML Kit. Had it working by 10 PM. Felt like an idiot for not doing or trying this before.

I'm not here to trash Tesseract—it's powerful if you know what you're doing. But if you just need to scan some text (receipts, menus, documents, whatever), ML Kit is so much easier it's not even funny. Yeah, you're stuck with Google Play Services. But I've shipped 4 apps with it and exactly zero users have complained about that.

Here's What We're Building

Point camera. See text. That's it.

Everyone thinks the hard part is the actual OCR. Nope. ML Kit handles that fine. The real problems:

The camera fires at 60 fps. You process maybe 3.
Blurry frames everywhere (or maybe I just have shaky hands?)
CameraX lifecycle stuff that makes zero sense until you've leaked memory twice
Device rotation (my nemesis)

Built this flow four times now. Still find new ways to screw it up.

Why ML Kit Over Tesseract?

Let me show you what I'm talking about:

| Thing | Tesseract | ML Kit | |----|----|----| | Setup | NDK, native libs, 3hrs of Stack Overflow | One Gradle line | | APK Size | +30-50MB | +10MB (downloads on first run) | | Integration | JNI wrappers, pray it works | Works with CameraX out of box | | Crashes | Different ones per device | Pretty stable | | Handwriting | Bad but trainable | Completely useless | | When it breaks | You're on your own | Usually works |

Tesseract is better if you need custom training or weird fonts. For everything else? ML Kit.

Gradle Setup (The Easy Part)

dependencies {
    implementation("androidx.camera:camera-camera2:1.3.0")
    implementation("androidx.camera:camera-lifecycle:1.3.0")
    implementation("androidx.camera:camera-view:1.3.0")

    implementation("com.google.mlkit:text-recognition:16.0.0")
}

That text-recognition thing downloads ~10MB on first run. Found out when users on mobile data got mad at me. Now I show a warning.

Camera Setup (Where It Gets Real)

class OCRActivity : AppCompatActivity() {
    private lateinit var cameraExecutor: ExecutorService
    private lateinit var textRecognizer: TextRecognizer

    override fun onCreate(savedInstanceState: Bundle?) {
        super.onCreate(savedInstanceState)
        setContentView(R.layout.activity_ocr)

        textRecognizer = TextRecognition.getClient(TextRecognizerOptions.DEFAULT_OPTIONS)
        cameraExecutor = Executors.newSingleThreadExecutor()

        if (allPermissionsGranted()) {
            startCamera()
        } else {
            requestPermissions()
        }
    }

    private fun startCamera() {
        val cameraProviderFuture = ProcessCameraProvider.getInstance(this)

        cameraProviderFuture.addListener({
            val cameraProvider = cameraProviderFuture.get()

            val preview = Preview.Builder().build().also {
                it.setSurfaceProvider(viewFinder.surfaceProvider)
            }

            val imageAnalyzer = ImageAnalysis.Builder()
                .setBackpressureStrategy(ImageAnalysis.STRATEGY_KEEP_ONLY_LATEST)
                .build()
                .also {
                    it.setAnalyzer(cameraExecutor, TextAnalyzer(textRecognizer) { result ->
                        runOnUiThread { updateUI(result) }
                    })
                }

            try {
                cameraProvider.unbindAll()
                cameraProvider.bindToLifecycle(
                    this, 
                    CameraSelector.DEFAULT_BACK_CAMERA, 
                    preview, 
                    imageAnalyzer
                )
            } catch (e: Exception) {
                Log.e(TAG, "Camera binding failed", e)
            }
        }, ContextCompat.getMainExecutor(this))
    }
}

See that STRATEGY_KEEP_ONLY_LATEST? Let me explain why this matters.

The Frame Processing Problem

Here's what happens without it:

Camera: "Here's frame 1!"
You: *starts processing frame 1* (takes 200ms)
Camera: "Here's frame 2!"
Camera: "Here's frame 3!"
Camera: "Here's frame 4!"
You: *still processing frame 1*
User: *moves camera to look at something else*
You: *finally finishes frame 1, starts frame 2*
User: "Why is it showing text from 3 seconds ago?"

With KEEPONLYLATEST, it just throws away frames you can't keep up with. Wasteful? Sure. But it's the only way to stay in sync with what the user is actually looking at.

Processing Frames (The Important Stuff)

class TextAnalyzer(
    private val recognizer: TextRecognizer,
    private val onTextRecognized: (Text) -> Unit
) : ImageAnalysis.Analyzer {

    private var lastAnalyzedTimestamp = 0L
    private val throttleMs = 300L  // my magic number

    @androidx.camera.core.ExperimentalGetImage
    override fun analyze(imageProxy: ImageProxy) {
        val currentTimestamp = System.currentTimeMillis()

        // Skip if we processed a frame too recently
        if (currentTimestamp - lastAnalyzedTimestamp < throttleMs) {
            imageProxy.close()
            return
        }

        val mediaImage = imageProxy.image
        if (mediaImage != null) {
            val image = InputImage.fromMediaImage(
                mediaImage, 
                imageProxy.imageInfo.rotationDegrees
            )

            recognizer.process(image)
                .addOnSuccessListener { visionText ->
                    onTextRecognized(visionText)
                    lastAnalyzedTimestamp = currentTimestamp
                }
                .addOnFailureListener { e ->
                    Log.e(TAG, "OCR failed", e)
                }
                .addOnCompleteListener {
                    imageProxy.close()  // DO NOT FORGET THIS
                }
        } else {
            imageProxy.close()
        }
    }
}

About That 300ms Throttle

Tried different values:

100ms: Phone got hot, battery died fast
500ms: Felt laggy and unresponsive
300ms: Sweet spot

Also the processing time varies wildly:

"STOP" sign → 50ms
Restaurant menu → 400ms
Full page of text → sometimes 600ms

The imageProxy.close() Thing

Forget this and your camera freezes after 10 seconds. No error. No crash. Just frozen.

I debugged this for over an hour once. Logs showed nothing. Camera just stopped sending frames. Finally found a random Stack Overflow comment mentioning it. Close the proxy or CameraX stops working.

What You Actually Get

private fun updateUI(result: Text) {
    if (result.text.isBlank()) {
        textView.text = "Point at some text..."
        return
    }

    textView.text = result.text

    // Or if you need more control:
    for (block in result.textBlocks) {
        val blockText = block.text
        val bounds = block.boundingBox  // useful for drawing rectangles

        for (line in block.lines) {
            val lineText = line.text
            // line.confidence is ALWAYS null btw

            for (element in line.elements) {
                // individual words
            }
        }
    }
}

Quick rant: line.confidence is always null on the free on-device model. I spent 2 hours checking my code thinking it was broken. Nope. Just doesn't give confidence scores. Only the paid cloud API does that. Docs mention this but not anywhere obvious.

Things That WILL Break

Memory Leaks

My first version crashed every 40 seconds. Heap dumps, profilers, everything. Finally realized:

override fun onDestroy() {
    super.onDestroy()
    textRecognizer.close()  // forgot this
    cameraExecutor.shutdown()
}

ML Kit keeps models in memory. Big ones. Don't close the recognizer → activity recreates → leak the whole model. Few times and you OOM. Learned this the hard way.

Rotation Hell

I hardcoded rotation to 0 because I only tested portrait. Worked great! Friend tested landscape: "Dude, this is completely broken."

ML Kit was trying to read sideways text. Obviously terrible.

val image = InputImage.fromMediaImage(
    mediaImage,
    imageProxy.imageInfo.rotationDegrees  // just use this
)

Low Light = Bad Times

Tried everything: contrast adjustment, sharpening, noise reduction. Maybe 5% improvement. Not worth the complexity.

What worked:

"Please turn on more lights" message
Flashlight toggle
Higher exposure (but then motion blur)

Sometimes bad input = bad output. No code fix.

Device Performance

My Pixel 6: 80-120ms per frame \n Random Samsung from 2019: 300-500ms

Test on the worst device you can find. Your flagship lies to you.

Real World Use Cases

Extracting Specific Stuff

ML Kit gives you raw text. Want prices? Write a regex.

private fun extractPrice(text: String): String? {
    val pattern = """[$₹€£]\s*\d+(?:[.,]\d{2})?""".toRegex()
    return pattern.find(text)?.value
}

But watch out: ML Kit adds random spaces in numbers when image quality is bad.

"$49.99" → "$ 4 9 . 9 9"

private fun cleanPrice(text: String): String {
    return text.replace("""\s+""".toRegex(), "")
}

Spent an afternoon debugging this.

Document Scanning

For documents, I don't use live scanning. Different approach:

Take photo → crop → OCR once → let user edit

private fun processDocument(bitmap: Bitmap) {
    val image = InputImage.fromBitmap(bitmap, 0)

    recognizer.process(image)
        .addOnSuccessListener { visionText ->
            displayText(visionText.text)
        }
        .addOnFailureListener { e ->
            showError(e)
        }
}

Better because: no motion blur, proper framing, can preprocess.

Testing (The Annoying Part)

Can't really automate OCR testing well. What I do:

Keep a folder of problem images from production. Blurry receipts, tilted text, bad lighting. About 30 images now. Before shipping anything, run through all of them manually.

class OCRTest {
    fun testImage(resourceId: Int, expectedText: String) {
        val bitmap = BitmapFactory.decodeResource(resources, resourceId)
        val image = InputImage.fromBitmap(bitmap, 0)

        recognizer.process(image)
            .addOnSuccessListener { result ->
                assert(result.text.contains(expectedText))
            }
    }
}

Not elegant. Catches regressions though.

When ML Kit Fails

Real limitations:

Handwriting: Completely useless. Built a handwritten notes scanner. Gave up after a week. Need cloud Vision API or specialized service. On-device can't even handle cursive.

Complex layouts: Tables, newspapers, multi-column stuff—text comes back in random order. Receipt scanner that needed items next to prices? The ordering logic took longer than the OCR.

Damaged documents: Coffee stains, faded text, crumpled paper—doesn't work. Tesseract with preprocessing sometimes better but then back to NDK problems.

My translation app uses ML Kit for quick scans (fast, offline) but has "high quality mode" using cloud Vision API. Slower, costs money, way more accurate. Sometimes you compromise.

Wrap Up

Things I wish I knew before starting:

300ms throttle works
Close your resources
Test on crappy devices
Validate everything, OCR lies
Handwriting is impossible

\

If you need perfect accuracy (medical, financial stuff), use the cloud API or add a human review. For normal apps, on-device is fine.

This code is simplified. Real production needs architecture, error handling, all that. But it should save you a week of debugging.

Try ML Kit before Tesseract. Seriously.

停止侵权、停止行为并支付赔偿：版权流氓如何将法律威胁转化为商业模式

2026-05-29T08:44:50+00:00

There is an entire category of commercial enterprise whose business model consists of hunting down small website operators and locating images of questionable or marginal legal exposure.

These companies then threaten operators with financial demands that bear no rational relationship to any actual harm suffered, despite the fact that in the overwhelming majority of cases no meaningful financial harm or loss has occurred at all.

We are speaking, to be precise, about companies such as Visual Rights Group, Copyright Agent, and an ever-proliferating ecosystem of associated entities that have, through industrious deployment of automated web-scraping tools, transformed intellectual property law into an instrument not of protection, but of extraction.

\ The methodology is almost admirably brazen. Automated scrapers — software bots and humans with no particular editorial judgement and certainly no interest in proportionality — are directed at Google Images and analogous repositories, tasked with identifying images that appear elsewhere on the internet without what these organisations deem appropriate licensing documentation.

A match is found. A letter — carefully worded to skirt the line between stern notice and outright intimidation — lands in an inbox. The demand follows.

Five hundred dollars. Sometimes more. And here is the detail that should provoke not merely irritation but genuine outrage: that sum is not the cost of a licence.

That is not what it would cost you to legitimately acquire the right to use the image going forward. That is simply their fee. Their toll. Payable, they imply, in lieu of further unpleasantness. A licence, should you wish one, would presumably cost you additional money on top of this opening gambit.

"The image in question may be a stock photograph of a bowl of pasta. It may be a thumbnail no larger than a postage stamp. It is almost certainly not the reason anyone visited your website."

Let us consider, with appropriate seriousness, the actual nature of the infringement being alleged. In the vast majority of these cases, we are not talking about a competitor reproducing an award-winning image to sell competing merchandise.

We are not talking about a publication stripping a photographer's byline and profiting from their artistry.

We are talking about a small business, a community organisation, or an individual who placed an image on a webpage — often in good faith, often having sourced it from somewhere that looked entirely legitimate — and whose digital footprint was subsequently detected by a scraper with neither conscience nor context.

The image in question may be a stock photograph of a bowl of pasta. It may be a thumbnail no larger than a postage stamp. It may be a decorative illustration buried on a page that receives forty visitors per month.

It is almost certainly not the reason anyone visited your website. It has demonstrably not deprived the rights holder of a single sale. It has not diminished the commercial value of the image by one measurable cent. And yet: five hundred dollars, please, at your earliest convenience.

The legal architecture underpinning these operations is, one must concede, technically functional. Copyright law in most jurisdictions does not require proof of actual damage to support a claim.

Statutory damages exist precisely because proving commercial harm is difficult, and because the law seeks to deter infringement generally.

These are sensible principles in the context for which they were designed — protecting working artists and photographers from systematic commercial exploitation of their labour.

What they were manifestly not designed for is to provide a revenue model for companies that acquire large portfolios of images for the express purpose of finding unauthorised uses and monetising the threat of litigation. That is not rights protection. That is rent-seeking at industrial scale, dressed in the language of intellectual property.

The letters that arrive from these organisations are, it must be noted, carefully calibrated instruments of anxiety. They invoke copyright legislation.

They reference potential statutory penalties — figures considerably larger than their own demand, naturally, to ensure the demand looks like a bargain by comparison.

They set deadlines. They use the word "infringement" repeatedly. What they rarely do is engage meaningfully with the specific facts of the alleged use: the size of the image, the nature of the website, the commercial context, the lack of any identifiable damage. Those details are, for their purposes, inconvenient.

There is, in all of this, something particularly dispiriting about the targeting of small operators — the sole-trader who built their own website, the community group that runs a modest online presence, the small enterprise whose web presence was assembled by someone who downloaded an image from the first Google result that appeared.

These are not sophisticated infringers running profitable piracy operations. These are ordinary people who made an administrative error, or who were misled about the licensing status of an image, or who simply did not know.

And for that — for that modest, victimless, entirely human failure of diligence — they receive threatening correspondence and a demand for money that, to many of them, represents a week's income.

Not because they have injured anyone. Not because a photographer has been denied their fair return. But because a company has built a business model around the industrialisation of that threatening correspondence.

It would be one thing if these demands were proportionate: a polite notice, a request to remove the image, and perhaps a modest settlement reflecting actual administrative costs. That would be reasonable. That might even be legitimate.

But five hundred dollars as a floor, representing fees only, for a tiny and entirely inconsequential image use — that is not proportionate. That is predatory.

The recipients of these letters should be aware, of course, that many such claims are worth challenging, and that specialist legal advice is available and often worth seeking.

But they should also be aware that the entire enterprise is designed to make challenging such claims feel more costly and frightening than simply paying. That is not an accident. It is the architecture of the business model.

To the organisations engaged in this practice: one suspects you are aware of the reputational assessment held of you by the broader community. This column would simply add its voice to the record.

A Final — And Rather More Serious — Observation

It is, when one pauses to reflect on it, genuinely amusing that the considerable technological resources of these organisations are deployed in pursuit of thumbnail photographs and decorative stock imagery. The machinery of enforcement is aimed, with laser precision, at some of the smallest possible targets.

And the approach, when the letter arrives, is instructive. There is no courtesy notice. No email that says, politely: "We believe this image may be subject to copyright — you are welcome to remove it, or we can discuss a licence if you wish to continue using it."

That would be reasonable. That would be the conduct of an organisation genuinely interested in rights protection.

Instead, the correspondence arrives fully formed: a payment demand, often under a heading as brazen as "Possible Copyright Use," requesting a fee — frequently upwards of five hundred dollars — without any demonstration of financial damage, without evidence of lost licence revenue, without any attempt to quantify what harm has actually occurred.

Straight for the throat. The message is clear: this is not an invitation to resolve a problem. It is a toll.

Consider, too, the vintage of the alleged infringement. These organisations do not limit themselves to active, visible uses. Their scrapers and human oversight will locate an image buried on a page from 2023 — a post that receives no traffic, that no one reads, that has in all practical senses ceased to exist in any meaningful way.

The image they are demanding payment for may not even still appear on the rights holder's own website. It has harmed no one. It has displaced no sale. It sits in a digital archive that the world has entirely forgotten about. And yet: here is the invoice.

This matters because it exposes the exercise for what it is. If the concern were genuine rights protection — ensuring photographers and artists are fairly compensated for active commercial use of their work — the age and visibility of the use would be relevant.

An image generating zero impressions on an abandoned or (old news) page or Google images is not competing with a licensed alternative. It is not depriving anyone of revenue. It simply exists, quietly, in a corner of the internet, and it has been found by a bot.

Which makes it all the more striking that these same organisations appear entirely untroubled by something considerably more damaging happening at scale right now.

Automated tools and AI-assisted pipelines are systematically scraping original journalism from major news organisations — the interviews, the research, the editorial judgement that produces a news story — and republishing it, paraphrased just sufficiently to obscure the source.

An AI rewrite of copyrighted content is not a free pass. Rewriting does not extinguish the underlying copyright, and laundering a violation through a language model does not make it lawful.

This is the copyright harm that actually matters. Not a forgotten image on a page no one visits. The systematic stripping of original journalism — work that is expensive to produce and impossible to sustain if its economic foundation is scraped away at scale.

That is where the enforcement energy belongs. The fact that it isn't tells you everything about what this industry is actually for.

萨默街

2026-05-29T08:00:26+00:00

:::info Astounding Stories of Super-Science May 2001, by Astounding Stories is part of HackerNoon’s Book Blog Post series. You can jump to any chapter in this book here. A ROOM WITH A VIEW - Chapter XII - Twelfth Chapter

Astounding Stories of Super-Science May 2001: A ROOM WITH A VIEW - Chapter XII - Twelfth Chapter

\ By E. M. Forster

:::

\ It was a Saturday afternoon, gay and brilliant after abundant rains, and the spirit of youth dwelt in it, though the season was now autumn. All that was gracious triumphed. As the motorcars passed through Summer Street they raised only a little dust, and their stench was soon dispersed by the wind and replaced by the scent of the wet birches or of the pines. Mr. Beebe, at leisure for life’s amenities, leant over his Rectory gate. Freddy leant by him, smoking a pendant pipe.

“Suppose we go and hinder those new people opposite for a little.”

“M’m.”

“They might amuse you.”

Freddy, whom his fellow-creatures never amused, suggested that the new people might be feeling a bit busy, and so on, since they had only just moved in.

“I suggested we should hinder them,” said Mr. Beebe. “They are worth it.” Unlatching the gate, he sauntered over the triangular green to Cissie Villa. “Hullo!” he cried, shouting in at the open door, through which much squalor was visible.

A grave voice replied, “Hullo!”

“I’ve brought someone to see you.”

“I’ll be down in a minute.”

The passage was blocked by a wardrobe, which the removal men had failed to carry up the stairs. Mr. Beebe edged round it with difficulty. The sitting-room itself was blocked with books.

“Are these people great readers?” Freddy whispered. “Are they that sort?”

“I fancy they know how to read—a rare accomplishment. What have they got? Byron. Exactly. A Shropshire Lad. Never heard of it. The Way of All Flesh. Never heard of it. Gibbon. Hullo! dear George reads German. Um—um—Schopenhauer, Nietzsche, and so we go on. Well, I suppose your generation knows its own business, Honeychurch.”

“Mr. Beebe, look at that,” said Freddy in awestruck tones.

On the cornice of the wardrobe, the hand of an amateur had painted this inscription: “Mistrust all enterprises that require new clothes.”

“I know. Isn’t it jolly? I like that. I’m certain that’s the old man’s doing.”

“How very odd of him!”

“Surely you agree?”

But Freddy was his mother’s son and felt that one ought not to go on spoiling the furniture.

“Pictures!” the clergyman continued, scrambling about the room. “Giotto—they got that at Florence, I’ll be bound.”

“The same as Lucy’s got.”

“Oh, by-the-by, did Miss Honeychurch enjoy London?”

“She came back yesterday.”

“I suppose she had a good time?”

“Yes, very,” said Freddy, taking up a book. “She and Cecil are thicker than ever.”

“That’s good hearing.”

“I wish I wasn’t such a fool, Mr. Beebe.”

Mr. Beebe ignored the remark.

“Lucy used to be nearly as stupid as I am, but it’ll be very different now, mother thinks. She will read all kinds of books.”

“So will you.”

“Only medical books. Not books that you can talk about afterwards. Cecil is teaching Lucy Italian, and he says her playing is wonderful. There are all kinds of things in it that we have never noticed. Cecil says—”

“What on earth are those people doing upstairs? Emerson—we think we’ll come another time.”

George ran down-stairs and pushed them into the room without speaking.

“Let me introduce Mr. Honeychurch, a neighbour.”

Then Freddy hurled one of the thunderbolts of youth. Perhaps he was shy, perhaps he was friendly, or perhaps he thought that George’s face wanted washing. At all events he greeted him with, “How d’ye do? Come and have a bathe.”

“Oh, all right,” said George, impassive.

Mr. Beebe was highly entertained.

“‘How d’ye do? how d’ye do? Come and have a bathe,’” he chuckled. “That’s the best conversational opening I’ve ever heard. But I’m afraid it will only act between men. Can you picture a lady who has been introduced to another lady by a third lady opening civilities with ‘How do you do? Come and have a bathe’? And yet you will tell me that the sexes are equal.”

“I tell you that they shall be,” said Mr. Emerson, who had been slowly descending the stairs. “Good afternoon, Mr. Beebe. I tell you they shall be comrades, and George thinks the same.”

“We are to raise ladies to our level?” the clergyman inquired.

“The Garden of Eden,” pursued Mr. Emerson, still descending, “which you place in the past, is really yet to come. We shall enter it when we no longer despise our bodies.”

Mr. Beebe disclaimed placing the Garden of Eden anywhere.

“In this—not in other things—we men are ahead. We despise the body less than women do. But not until we are comrades shall we enter the garden.”

“I say, what about this bathe?” murmured Freddy, appalled at the mass of philosophy that was approaching him.

“I believed in a return to Nature once. But how can we return to Nature when we have never been with her? To-day, I believe that we must discover Nature. After many conquests we shall attain simplicity. It is our heritage.”

“Let me introduce Mr. Honeychurch, whose sister you will remember at Florence.”

“How do you do? Very glad to see you, and that you are taking George for a bathe. Very glad to hear that your sister is going to marry. Marriage is a duty. I am sure that she will be happy, for we know Mr. Vyse, too. He has been most kind. He met us by chance in the National Gallery, and arranged everything about this delightful house. Though I hope I have not vexed Sir Harry Otway. I have met so few Liberal landowners, and I was anxious to compare his attitude towards the game laws with the Conservative attitude. Ah, this wind! You do well to bathe. Yours is a glorious country, Honeychurch!”

“Not a bit!” mumbled Freddy. “I must—that is to say, I have to—have the pleasure of calling on you later on, my mother says, I hope.”

“Call, my lad? Who taught us that drawing-room twaddle? Call on your grandmother! Listen to the wind among the pines! Yours is a glorious country.”

Mr. Beebe came to the rescue.

“Mr. Emerson, he will call, I shall call; you or your son will return our calls before ten days have elapsed. I trust that you have realized about the ten days’ interval. It does not count that I helped you with the stair-eyes yesterday. It does not count that they are going to bathe this afternoon.”

“Yes, go and bathe, George. Why do you dawdle talking? Bring them back to tea. Bring back some milk, cakes, honey. The change will do you good. George has been working very hard at his office. I can’t believe he’s well.”

George bowed his head, dusty and sombre, exhaling the peculiar smell of one who has handled furniture.

“Do you really want this bathe?” Freddy asked him. “It is only a pond, don’t you know. I dare say you are used to something better.”

“Yes—I have said ‘Yes’ already.”

Mr. Beebe felt bound to assist his young friend, and led the way out of the house and into the pine-woods. How glorious it was! For a little time the voice of old Mr. Emerson pursued them dispensing good wishes and philosophy. It ceased, and they only heard the fair wind blowing the bracken and the trees. Mr. Beebe, who could be silent, but who could not bear silence, was compelled to chatter, since the expedition looked like a failure, and neither of his companions would utter a word. He spoke of Florence. George attended gravely, assenting or dissenting with slight but determined gestures that were as inexplicable as the motions of the tree-tops above their heads.

“And what a coincidence that you should meet Mr. Vyse! Did you realize that you would find all the Pension Bertolini down here?”

“I did not. Miss Lavish told me.”

“When I was a young man, I always meant to write a ‘History of Coincidence.’”

No enthusiasm.

“Though, as a matter of fact, coincidences are much rarer than we suppose. For example, it isn’t purely coincidentally that you are here now, when one comes to reflect.”

To his relief, George began to talk.

“It is. I have reflected. It is Fate. Everything is Fate. We are flung together by Fate, drawn apart by Fate—flung together, drawn apart. The twelve winds blow us—we settle nothing—”

“You have not reflected at all,” rapped the clergyman. “Let me give you a useful tip, Emerson: attribute nothing to Fate. Don’t say, ‘I didn’t do this,’ for you did it, ten to one. Now I’ll cross-question you. Where did you first meet Miss Honeychurch and myself?”

“Italy.”

“And where did you meet Mr. Vyse, who is going to marry Miss Honeychurch?”

“National Gallery.”

“Looking at Italian art. There you are, and yet you talk of coincidence and Fate. You naturally seek out things Italian, and so do we and our friends. This narrows the field immeasurably we meet again in it.”

“It is Fate that I am here,” persisted George. “But you can call it Italy if it makes you less unhappy.”

Mr. Beebe slid away from such heavy treatment of the subject. But he was infinitely tolerant of the young, and had no desire to snub George.

“And so for this and for other reasons my ‘History of Coincidence’ is still to write.”

Silence.

Wishing to round off the episode, he added; “We are all so glad that you have come.”

Silence.

“Here we are!” called Freddy.

“Oh, good!” exclaimed Mr. Beebe, mopping his brow.

“In there’s the pond. I wish it was bigger,” he added apologetically.

They climbed down a slippery bank of pine-needles. There lay the pond, set in its little alp of green—only a pond, but large enough to contain the human body, and pure enough to reflect the sky. On account of the rains, the waters had flooded the surrounding grass, which showed like a beautiful emerald path, tempting these feet towards the central pool.

“It’s distinctly successful, as ponds go,” said Mr. Beebe. “No apologies are necessary for the pond.”

George sat down where the ground was dry, and drearily unlaced his boots.

“Aren’t those masses of willow-herb splendid? I love willow-herb in seed. What’s the name of this aromatic plant?”

No one knew, or seemed to care.

“These abrupt changes of vegetation—this little spongeous tract of water plants, and on either side of it all the growths are tough or brittle—heather, bracken, hurts, pines. Very charming, very charming.”

“Mr. Beebe, aren’t you bathing?” called Freddy, as he stripped himself.

Mr. Beebe thought he was not.

“Water’s wonderful!” cried Freddy, prancing in.

“Water’s water,” murmured George. Wetting his hair first—a sure sign of apathy—he followed Freddy into the divine, as indifferent as if he were a statue and the pond a pail of soapsuds. It was necessary to use his muscles. It was necessary to keep clean. Mr. Beebe watched them, and watched the seeds of the willow-herb dance chorically above their heads.

“Apooshoo, apooshoo, apooshoo,” went Freddy, swimming for two strokes in either direction, and then becoming involved in reeds or mud.

“Is it worth it?” asked the other, Michelangelesque on the flooded margin.

The bank broke away, and he fell into the pool before he had weighed the question properly.

“Hee-poof—I’ve swallowed a pollywog, Mr. Beebe, water’s wonderful, water’s simply ripping.”

“Water’s not so bad,” said George, reappearing from his plunge, and sputtering at the sun.

“Water’s wonderful. Mr. Beebe, do.”

“Apooshoo, kouf.”

Mr. Beebe, who was hot, and who always acquiesced where possible, looked around him. He could detect no parishioners except the pine-trees, rising up steeply on all sides, and gesturing to each other against the blue. How glorious it was! The world of motor-cars and rural Deans receded inimitably. Water, sky, evergreens, a wind—these things not even the seasons can touch, and surely they lie beyond the intrusion of man?

“I may as well wash too”; and soon his garments made a third little pile on the sward, and he too asserted the wonder of the water.

It was ordinary water, nor was there very much of it, and, as Freddy said, it reminded one of swimming in a salad. The three gentlemen rotated in the pool breast high, after the fashion of the nymphs in Götterdämmerung. But either because the rains had given a freshness or because the sun was shedding a most glorious heat, or because two of the gentlemen were young in years and the third young in spirit—for some reason or other a change came over them, and they forgot Italy and Botany and Fate. They began to play. Mr. Beebe and Freddy splashed each other. A little deferentially, they splashed George. He was quiet: they feared they had offended him. Then all the forces of youth burst out. He smiled, flung himself at them, splashed them, ducked them, kicked them, muddied them, and drove them out of the pool.

“Race you round it, then,” cried Freddy, and they raced in the sunshine, and George took a short cut and dirtied his shins, and had to bathe a second time. Then Mr. Beebe consented to run—a memorable sight.

They ran to get dry, they bathed to get cool, they played at being Indians in the willow-herbs and in the bracken, they bathed to get clean. And all the time three little bundles lay discreetly on the sward, proclaiming:

“No. We are what matters. Without us shall no enterprise begin. To us shall all flesh turn in the end.”

“A try! A try!” yelled Freddy, snatching up George’s bundle and placing it beside an imaginary goal-post.

“Socker rules,” George retorted, scattering Freddy’s bundle with a kick.

“Goal!”

“Pass!”

“Take care my watch!” cried Mr. Beebe.

Clothes flew in all directions.

“Take care my hat! No, that’s enough, Freddy. Dress now. No, I say!”

But the two young men were delirious. Away they twinkled into the trees, Freddy with a clerical waistcoat under his arm, George with a wide-awake hat on his dripping hair.

“That’ll do!” shouted Mr. Beebe, remembering that after all he was in his own parish. Then his voice changed as if every pine-tree was a Rural Dean. “Hi! Steady on! I see people coming you fellows!”

Yells, and widening circles over the dappled earth.

“Hi! hi! Ladies!”

Neither George nor Freddy was truly refined. Still, they did not hear Mr. Beebe’s last warning or they would have avoided Mrs. Honeychurch, Cecil, and Lucy, who were walking down to call on old Mrs. Butterworth. Freddy dropped the waistcoat at their feet, and dashed into some bracken. George whooped in their faces, turned and scudded away down the path to the pond, still clad in Mr. Beebe’s hat.

“Gracious alive!” cried Mrs. Honeychurch. “Whoever were those unfortunate people? Oh, dears, look away! And poor Mr. Beebe, too! Whatever has happened?”

“Come this way immediately,” commanded Cecil, who always felt that he must lead women, though he knew not whither, and protect them, though he knew not against what. He led them now towards the bracken where Freddy sat concealed.

“Oh, poor Mr. Beebe! Was that his waistcoat we left in the path? Cecil, Mr. Beebe’s waistcoat—”

No business of ours, said Cecil, glancing at Lucy, who was all parasol and evidently “minded.”

“I fancy Mr. Beebe jumped back into the pond.”

“This way, please, Mrs. Honeychurch, this way.”

They followed him up the bank attempting the tense yet nonchalant expression that is suitable for ladies on such occasions.

“Well, I can’t help it,” said a voice close ahead, and Freddy reared a freckled face and a pair of snowy shoulders out of the fronds. “I can’t be trodden on, can I?”

“Good gracious me, dear; so it’s you! What miserable management! Why not have a comfortable bath at home, with hot and cold laid on?”

“Look here, mother, a fellow must wash, and a fellow’s got to dry, and if another fellow—”

“Dear, no doubt you’re right as usual, but you are in no position to argue. Come, Lucy.” They turned. “Oh, look—don’t look! Oh, poor Mr. Beebe! How unfortunate again—”

For Mr. Beebe was just crawling out of the pond, on whose surface garments of an intimate nature did float; while George, the world-weary George, shouted to Freddy that he had hooked a fish.

“And me, I’ve swallowed one,” answered he of the bracken. “I’ve swallowed a pollywog. It wriggleth in my tummy. I shall die—Emerson you beast, you’ve got on my bags.”

“Hush, dears,” said Mrs. Honeychurch, who found it impossible to remain shocked. “And do be sure you dry yourselves thoroughly first. All these colds come of not drying thoroughly.”

“Mother, do come away,” said Lucy. “Oh for goodness’ sake, do come.”

“Hullo!” cried George, so that again the ladies stopped.

He regarded himself as dressed. Barefoot, bare-chested, radiant and personable against the shadowy woods, he called:

“Hullo, Miss Honeychurch! Hullo!”

“Bow, Lucy; better bow. Whoever is it? I shall bow.”

Miss Honeychurch bowed.

That evening and all that night the water ran away. On the morrow the pool had shrunk to its old size and lost its glory. It had been a call to the blood and to the relaxed will, a passing benediction whose influence did not pass, a holiness, a spell, a momentary chalice for youth.

\ \

:::info About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books.

This book is part of the public domain. Astounding Stories. (2001). ASTOUNDING STORIES OF SUPER-SCIENCE, MAY, 2001. USA. Project Gutenberg. Release date: May 1, 2001, from https://www.gutenberg.org/cache/epub/2641/pg2641-images.html

This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org, located at https://www.gutenberg.org/policy/license.html.

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\ \

舒曼协议

2026-05-29T07:00:43+00:00

Astounding Stories of Super-Science May 2001: A ROOM WITH A VIEW - Chapter XI - In Mrs. Vyse’s Well-Appointed Flat

\ By E. M. Forster

:::

\ The Comic Muse, though able to look after her own interests, did not disdain the assistance of Mr. Vyse. His idea of bringing the Emersons to Windy Corner struck her as decidedly good, and she carried through the negotiations without a hitch. Sir Harry Otway signed the agreement, met Mr. Emerson, who was duly disillusioned. The Miss Alans were duly offended, and wrote a dignified letter to Lucy, whom they held responsible for the failure. Mr. Beebe planned pleasant moments for the new-comers, and told Mrs. Honeychurch that Freddy must call on them as soon as they arrived. Indeed, so ample was the Muse’s equipment that she permitted Mr. Harris, never a very robust criminal, to droop his head, to be forgotten, and to die.

Lucy—to descend from bright heaven to earth, whereon there are shadows because there are hills—Lucy was at first plunged into despair, but settled after a little thought that it did not matter the very least. Now that she was engaged, the Emersons would scarcely insult her and were welcome into the neighbourhood. And Cecil was welcome to bring whom he would into the neighbourhood. Therefore Cecil was welcome to bring the Emersons into the neighbourhood. But, as I say, this took a little thinking, and—so illogical are girls—the event remained rather greater and rather more dreadful than it should have done. She was glad that a visit to Mrs. Vyse now fell due; the tenants moved into Cissie Villa while she was safe in the London flat.

“Cecil—Cecil darling,” she whispered the evening she arrived, and crept into his arms.

Cecil, too, became demonstrative. He saw that the needful fire had been kindled in Lucy. At last she longed for attention, as a woman should, and looked up to him because he was a man.

“So you do love me, little thing?” he murmured.

“Oh, Cecil, I do, I do! I don’t know what I should do without you.”

Several days passed. Then she had a letter from Miss Bartlett. A coolness had sprung up between the two cousins, and they had not corresponded since they parted in August. The coolness dated from what Charlotte would call “the flight to Rome,” and in Rome it had increased amazingly. For the companion who is merely uncongenial in the mediaeval world becomes exasperating in the classical. Charlotte, unselfish in the Forum, would have tried a sweeter temper than Lucy’s, and once, in the Baths of Caracalla, they had doubted whether they could continue their tour. Lucy had said she would join the Vyses—Mrs. Vyse was an acquaintance of her mother, so there was no impropriety in the plan and Miss Bartlett had replied that she was quite used to being abandoned suddenly. Finally nothing happened; but the coolness remained, and, for Lucy, was even increased when she opened the letter and read as follows. It had been forwarded from Windy Corner.

“TUNBRIDGE WELLS, \n “September.

“DEAREST LUCIA,

“I have news of you at last! Miss Lavish has been bicycling in your parts, but was not sure whether a call would be welcome. Puncturing her tire near Summer Street, and it being mended while she sat very woebegone in that pretty churchyard, she saw to her astonishment, a door open opposite and the younger Emerson man come out. He said his father had just taken the house. He said he did not know that you lived in the neighbourhood (?). He never suggested giving Eleanor a cup of tea. Dear Lucy, I am much worried, and I advise you to make a clean breast of his past behaviour to your mother, Freddy, and Mr. Vyse, who will forbid him to enter the house, etc. That was a great misfortune, and I dare say you have told them already. Mr. Vyse is so sensitive. I remember how I used to get on his nerves at Rome. I am very sorry about it all, and should not feel easy unless I warned you.

“Believe me, \n “Your anxious and loving cousin, \n “CHARLOTTE.”

Lucy was much annoyed, and replied as follows:

“BEAUCHAMP MANSIONS, S.W.

“DEAR CHARLOTTE,

“Many thanks for your warning. When Mr. Emerson forgot himself on the mountain, you made me promise not to tell mother, because you said she would blame you for not being always with me. I have kept that promise, and cannot possibly tell her now. I have said both to her and Cecil that I met the Emersons at Florence, and that they are respectable people—which I do think—and the reason that he offered Miss Lavish no tea was probably that he had none himself. She should have tried at the Rectory. I cannot begin making a fuss at this stage. You must see that it would be too absurd. If the Emersons heard I had complained of them, they would think themselves of importance, which is exactly what they are not. I like the old father, and look forward to seeing him again. As for the son, I am sorry for him when we meet, rather than for myself. They are known to Cecil, who is very well and spoke of you the other day. We expect to be married in January.

“Miss Lavish cannot have told you much about me, for I am not at Windy Corner at all, but here. Please do not put ‘Private’ outside your envelope again. No one opens my letters.

“Yours affectionately, \n “L. M. HONEYCHURCH.”

Secrecy has this disadvantage: we lose the sense of proportion; we cannot tell whether our secret is important or not. Were Lucy and her cousin closeted with a great thing which would destroy Cecil’s life if he discovered it, or with a little thing which he would laugh at? Miss Bartlett suggested the former. Perhaps she was right. It had become a great thing now. Left to herself, Lucy would have told her mother and her lover ingenuously, and it would have remained a little thing. “Emerson, not Harris”; it was only that a few weeks ago. She tried to tell Cecil even now when they were laughing about some beautiful lady who had smitten his heart at school. But her body behaved so ridiculously that she stopped.

She and her secret stayed ten days longer in the deserted Metropolis visiting the scenes they were to know so well later on. It did her no harm, Cecil thought, to learn the framework of society, while society itself was absent on the golf-links or the moors. The weather was cool, and it did her no harm. In spite of the season, Mrs. Vyse managed to scrape together a dinner-party consisting entirely of the grandchildren of famous people. The food was poor, but the talk had a witty weariness that impressed the girl. One was tired of everything, it seemed. One launched into enthusiasms only to collapse gracefully, and pick oneself up amid sympathetic laughter. In this atmosphere the Pension Bertolini and Windy Corner appeared equally crude, and Lucy saw that her London career would estrange her a little from all that she had loved in the past.

The grandchildren asked her to play the piano.

She played Schumann. “Now some Beethoven” called Cecil, when the querulous beauty of the music had died. She shook her head and played Schumann again. The melody rose, unprofitably magical. It broke; it was resumed broken, not marching once from the cradle to the grave. The sadness of the incomplete—the sadness that is often Life, but should never be Art—throbbed in its disjected phrases, and made the nerves of the audience throb. Not thus had she played on the little draped piano at the Bertolini, and “Too much Schumann” was not the remark that Mr. Beebe had passed to himself when she returned.

When the guests were gone, and Lucy had gone to bed, Mrs. Vyse paced up and down the drawing-room, discussing her little party with her son. Mrs. Vyse was a nice woman, but her personality, like many another’s, had been swamped by London, for it needs a strong head to live among many people. The too vast orb of her fate had crushed her; and she had seen too many seasons, too many cities, too many men, for her abilities, and even with Cecil she was mechanical, and behaved as if he was not one son, but, so to speak, a filial crowd.

“Make Lucy one of us,” she said, looking round intelligently at the end of each sentence, and straining her lips apart until she spoke again. “Lucy is becoming wonderful—wonderful.”

“Her music always was wonderful.”

“Yes, but she is purging off the Honeychurch taint, most excellent Honeychurches, but you know what I mean. She is not always quoting servants, or asking one how the pudding is made.”

“Italy has done it.”

“Perhaps,” she murmured, thinking of the museum that represented Italy to her. “It is just possible. Cecil, mind you marry her next January. She is one of us already.”

“But her music!” he exclaimed. “The style of her! How she kept to Schumann when, like an idiot, I wanted Beethoven. Schumann was right for this evening. Schumann was the thing. Do you know, mother, I shall have our children educated just like Lucy. Bring them up among honest country folks for freshness, send them to Italy for subtlety, and then—not till then—let them come to London. I don’t believe in these London educations—” He broke off, remembering that he had had one himself, and concluded, “At all events, not for women.”

“Make her one of us,” repeated Mrs. Vyse, and processed to bed.

As she was dozing off, a cry—the cry of nightmare—rang from Lucy’s room. Lucy could ring for the maid if she liked but Mrs. Vyse thought it kind to go herself. She found the girl sitting upright with her hand on her cheek.

“I am so sorry, Mrs. Vyse—it is these dreams.”

“Bad dreams?”

“Just dreams.”

The elder lady smiled and kissed her, saying very distinctly: “You should have heard us talking about you, dear. He admires you more than ever. Dream of that.”

Lucy returned the kiss, still covering one cheek with her hand. Mrs. Vyse recessed to bed. Cecil, whom the cry had not awoke, snored. Darkness enveloped the flat.

\ \

:::info About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books.

:::

AI 魔术背后的奥秘：用通俗易懂的语言向你的经理解释 AI

2026-05-29T02:20:37+00:00

Maybe you already know what AI is. But then your manager, a friend, or your mom asks you to explain it, and suddenly it becomes harder than expected. This article is my attempt to explain AI in plain words — the way I would explain it to someone who does not care about tokens, weights, gradients, or architecture diagrams.

\ So, let me try.

\ We want to speed up our businesses with AI. We trust it to help with investments, strategy, hiring, writing, coding, operations, and decisions that may actually matter.

\ But do we really understand what AI is doing?

\ There are already many articles trying to explain AI “for dummies.”

\ Some become technical too quickly: tokens, weights, vectors, attention, parameters, gradients. Before the reader understands what AI is doing, they are already lost inside the machinery.

\ Others go in the opposite direction. They describe AI as something almost magical: a digital mind, a new intelligence, a machine that understands us.

\ Both versions miss something important.

\ AI is not magic.

But it is also not boring.

\ So, let me try a different path: a simple, not-too-deep explanation of what AI and Large Language Models (LLMs) are really doing, why they can feel intelligent, and why the basic trick behind them is still astonishing.

\ Take a seat and grab your coffee. AI may look like magic from the outside, but once you understand the machine behind it, the trick becomes surprisingly simple.

How the Trick Works

Imagine a system trained on millions, even billions, of texts. That is why we call it a Large Language Model, or LLM.

\ It repeatedly sees simple words like red, yellow, blue, green, pink, and orange near the word color. Every time it sees this kind of relationship — or pattern — the strengths of many connections slightly change. These learned strengths are what we call weights, and adjusting them is what we call training or learning. Over time, those weights make some word relationships stronger than others, such as the association between color and words like red, yellow, and blue.

\ Is AI recording everything it learns? Well, not exactly. It does not keep every sentence like a library. A better way to say it is that it keeps traces of relationships between words. If a sentence appears again and again, it has a bigger chance of being reproduced almost literally, like when we repeat a common idiom. But most of the time, the model is not copying. It is using learned relationships to predict what should come next.

\ But it also sees words like warm in different contexts. Sometimes, warm appears near color, as in “warm colors.” Other times it appears near weather, coffee, clothes, or tone. So, the model does not learn only one fixed meaning for warm. It learns that the surrounding context, including word order, distance, and nearby words, changes which relationships matter.

\ The same happens with phrases like “red car”, “blue car”, and “black car”. After seeing enough examples, the model learns a pattern: color-related words often appear next to object-related words like car, forming a small phrase that can be useful later when predicting an answer.

\ To add one technical term, this process is called AI training. Now, grab another sip of coffee, and let’s move on to the second half of the trick.

\ Imagine you have a fully trained AI chatbot right in front of you, and you start typing. That conversation becomes part of the chatbot’s context: everything the trained model can currently see and use as it shapes its answer. And yes, for once, the AI jargon is just a normal English word.

\ Then attention enters the picture.

\ Suppose you write:

My red car is fast.

\ The model does not process those words as isolated pieces. In that context, red and car become strongly connected.

\ Later, if you ask:

Which color is my car?

\ The model still does not “know” it is answering a question in the human sense. But words and symbols like which, color, is, my, and ? form a pattern that has often been followed by answer-like text during training.

\ The word car pulls attention toward the earlier phrase ”my red car is fast”. The word color makes color-related words more relevant. The word my helps connect the current phrase “my car” with the earlier phrase “my red car is fast.”

\ The word which and the symbol ? help shape the continuation toward an answer-like form, because it often appears in question-like patterns. Together, words and symbols like which, ?, is, and my also make an answer starting with your more likely, because in many question-answer patterns, my in the question becomes your in the answer.

\ So, when the model begins producing:

Your car is…

\ Many words related to color are possible, in general: blue, yellow, black, green, or red. But in this specific context, red has the strongest relationship to car, because the earlier sentence was: “My red car is fast.”

\ So, the model continues:

Your car is red.

\ That feels like understanding.

\ What we are really seeing is fluency. By predicting likely next words, the answer fits the question, follows the context, and sounds natural. That makes the chat feel like a fluent conversation, almost like understanding, even when the mechanism underneath is prediction.

\ But underneath, it is not magic. The model is using learned relationships, the current context, and attention to generate the most likely useful continuation.

\ It is a little like your phone’s predictive text on steroids — except the steroids are billions of parameters, massive training data, attention mechanisms, and a context window large enough to make language look like thought.

\ And this is the basic trick we need to understand before talking seriously about AI.

\ It is just a text predictor.

\ Or, more exactly, a token predictor. I know I promised not to talk about tokens, but it's time to break that rule. A token is simply a word, a number, a symbol, an emoji, or any fragment of text that carries meaning (like the suffix -ing, the plural -s or the symbol !).

\ To keep things simple, think of tokens as the basic building blocks of language for the model. In fact, there are AI models that can use audio or image fragments as tokens! So, from here on out, we'll be talking about tokens instead of words.

\ Well, now you know how it works.

\ That may sound simple, but this act of predicting the next token could mean much more than it first appears.

\ Grab another sip of coffee if you want to pause here.

\ If you’re still with me, let’s talk about math.

But What About Math?

You may say:

But AI knows math.

\ Well, maybe. But not necessarily in the way we do.

\ If a model has read billions of examples where the tokens 2, +, and 2 are followed by = 4, it does not need to understand numbers like a child counting apples on a table. It can learn the pattern:

2 + 2 = 4

\ The same happens with many simple equations, formulas, and procedures. The model has seen mathematical language written again and again: examples, exercises, proofs, explanations, mistakes, corrections, and step-by-step solutions.

\ So, when you ask a math question, the model may generate something that looks like reasoning because it has learned the shape of mathematical reasoning in text.

\ But this is also why LLMs can fail at math in surprising ways.

\ They are often very good at producing the form of a solution: the steps, the symbols, the explanation, the final sentence. But unless the model is connected to a calculator, code interpreter, or another verification tool, it is still generating the next likely token.

\ For familiar patterns, that works beautifully.

\ For unusual numbers, long calculations, or problems where one small error breaks the whole answer, the model may produce a confident but wrong result.

\ It is not because the model is “stupid.”

\ \ It is because fluency is not the same as calculation.

A calculator computes.

An LLM predicts text.

\ Sometimes, prediction is enough to reproduce the correct calculation. Sometimes, it is not.

\ That is why AI can explain math beautifully and still make basic arithmetic mistakes. It has learned how mathematical answers usually look, but it is not always executing mathematics as a dedicated calculator would.

\ So again, the known trick: next-token prediction.

\ But when the training data contains millions of examples of human mathematics, explanations, formulas, and solutions, predicting the next token can look a lot like knowing math.

\ Just that — and all that.

\ Of course, this is a simplification. In practice, many modern AI systems can connect to and use tools when a math problem needs real precision — much like we pick up a calculator when mental math is not enough. But that’s another story.

Just That — And All That

The next time you play with AI, remember this:

It is just a text predictor — technically, a token predictor.

But that sentence is more explosive than it sounds.

\ Just prediction of the next word? Yes. But prediction over the accumulated patterns of human culture is not small. The model is not asking what you would say next. It is asking what humanity, in all its writing, has tended to say next.

\ Every answer is shaped by an enormous history of how humans have described, argued, solved, imagined, explained, corrected, and misunderstood the world through language.

\ That is why “just a text predictor” is both true and misleading.

\ It is not a mind.

It is not magic.

\ But it is also not your phone’s autocomplete.

\ It is closer to an astonishing game: collaborating with the echo of everyone who wrote before you, one predicted word at a time.

\ A physicist’s next symbol. A poet’s next rhyme. A chef’s next ingredient. A programmer’s next line of code.

\ Just that — and all that.

\ It is amazing, isn’t it?

A Thought for the Next Coffee

But once you understand this, another thought appears.

\ We learned that AI is really just predicting the next token. Does that mean it can predict the future?

\ Your AI chat has not seen the future. It has absorbed patterns from what humans have already written, and it uses those patterns to predict what should come next. In a way, it does what humans have always done: it learns from the past to predict the future.

\ Most of the time, this works surprisingly well because most of life does rhyme with the past. Tomorrow you may wake up at 6:00 AM because you did it yesterday, last week, and for years before that. The next word, the next habit, the next answer, the next event — often, the past is a good guide.

\ Until it is not.

\ You may win the jackpot and never need that 6:00 AM alarm again.

\ The world may change. A new event may break the pattern. A new invention, crisis, discovery, regulation, war, behavior, or idea may appear where the old text has no reliable map.

\ That is where AI becomes less certain than it sounds.

\ It does not truly predict the future. It predicts from the past.

\ Most of the time, that is enough to look intelligent.

\ Sometimes, it is exactly why it fails.

\ But that is a thought for the next coffee.

If You Want Another Long Coffee

Now that you understand the basic trick behind LLMs, you may enjoy these pieces where I explore how the same idea plays out in real-world AI agents:

\ And yes, the same “just a next-token predictor” reality explains why context, memory architecture, and guardrails matter so much.

308 篇博客文章，带你了解创始人故事

2026-05-29T02:00:32+00:00

Let's learn about Founder Stories via these 308 free blog posts. They are ordered by HackerNoon reader engagement data. Visit the Learn Repo or LearnRepo.com to find the most read blog posts about any technology.

Founders, very often, solve problems that we don't know we have yet.

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Software development has improved 100x since the internet was invented, but how people report bugs has not changed since the 1990s.

121. Gumroad's 2020 Roadmap

I am excited to share this. One of the most fun parts about being CEO is spending (a lot of) time thinking about the grand future and then figuring out a set of reasonable steps to get there. This is the most creative bit of my job, and I love it.

122. The One Piece Of Advice All Founders Need To Hear

Lose the to-do list, there is only one thing you need to focus on

123. How Slack's Huddles Gave Us The Boost We Needed To Launch

Remote working makes it hard to have the spontaneity that offices can bring. Slack Huddles managed to bring that to one team's successful bid for ProductHunt

124. "I’m a big advocate of Web3 and an anarchist at heart," says FinTech Entrepreneur, Julie Plavnik

Julie is a content strategist and writer who helps Web3 projects rank higher on search engines by creating engaging, optimized content.

125. Tokenisation of Real World Assets : An Interview With OpenTrade CEO David Sutter

David Sutter is the CEO of OpenTrade, an institutional lending platform that provides users access to a suite of on-chain credit products for tokenized real-wor

126. Adadot Founder Alex on Building a Analytics Tool and being Nominated For #Noonies 2022

I’m Alex and I’m the Founder at Adadot.

127. Web3 Enables Users to Create and Own their Web Experience

Fetch.ai is an AI-powered blockchain that allows businesses and individuals to use multi-agent system-based solutions to solve complex problems or coordination.

128. ‘Being Naive Is a Feature, Not a Bug’: Abhinov Balagoni, CEO Pax Credit

A Chat with Abhinov Balagoni, Founder and CEO of Pax Credit on how he got started and what the future holds for Pax Credit

129. How Artificial Intelligence Will Actually Change The Healthcare System in America

Ramya Ganti is the CEO of BabySteps. She believes in creating a more efficient healthcare system that passes the savings along to patients.

130. Twitter without Jack: WTF?!

Jack Dorser is leaving Twitter. WHY? And, More Importantly, WHY NOW?!

131. Trucking in America: My Love Song to the Industry

I moved to the U.S. in 2017 and launched my startup in the trucking industry. That's what I find the most exciting about it.

132. Founder Interviews: Joe Mahavuthivanij of Mythic Markets

133. The Day the CEO of Meta Stopped to Like My Vision

Never underestimate the power of sharing what you think. Write, publish, post. Technology is built that way — brick by brick, idea by idea.

134. How to Start, Run and Sell Your Billion-dollar Business

Timeless advice to profit from your passions, capitalize on your ideas and become a better human being.

135. Podcast: Kate Dudzik on AI ethics, product-led data science and more!

One thing that has become clear in the last few years is that the soft parts of data science are becoming even more important. What do I mean by soft parts? I a

136. Duelist King Nominated as Blockchain Game Dev of the Year

Nicole Nguyen is the co-founder of Duelist King, the first NFT game powered by Dual Launch via OccamRazer IDO and PancakeSwap IFO.

137. Meet The Women In Tech: SynFutures Co-Founder and COO Wenny C. and The Next Chapter of DeFi Innovati

SynFutures is redefining decentralized derivatives by blending centralized performance with DeFi transparency.

138. Founder Interviews: Michael Reitblat of Forter

Forter is the leading provider in e-commerce fraud prevention, protecting $130B in digital transactions annually.

139. Noonies Interview: Daria Leshchenko on the Role of Tech in Customer Support

Daria Leshchenko from SupportYourApp shares her entrepreneurial journey and her vision of the future of customer support for startups.

140. Are Agencies Evil? How We Changed the Agency Business Model to Team-as-a-Service

Dima Skortsov shares the transformational journey that led to the birth of the team as a service model

141. How Allison and Gregory Robinson Raised $11 Million For "The Mom Project"

Gregory Robinson’s Fundraising Journey For A Market That Helps Women Return To The Workforce (As told to Nathan Beckord)

142. How To Build Products Like a Scientist

Every decision and step we take at a startup is based on some belief. Here's how to validate those beliefs and build products like a scientist ;)

143. Minds Behind Money: Interview With VC Zachari Saltmer, Co-Founder of One Big Fund

In this interview, we catch up with Zachari Saltmer, Co-Founder of One Big Fund to discuss the state of VC funding, AI, and crypto.

144. Women in Web3: Tracy Leparulo, Founder & CEO of Untraceable

Tracy Leparulo's insights into marketing blockchain and crypto companies through her startup, Untraceable and her experience as a woman in the crypto space.

145. Reddit Marketing for Solo Founders: A 3-Month Retrospective

A practical breakdown of what works, what doesn't, and how to save hours of wasted effort when using Reddit as a marketing channel.

146. The Illusion of Ideas

Why untested ideas remain illusions. Only through simplicity, speed, and real-world testing can you separate what’s real from what’s not.

147. An Inspiring Story of Sowemo Tech Company Founder

148. Meet the Twins That Are Launching the First Comic-Based Learning Experience on the Market

Twins are launching the first comic-based learning experience on the market - Improvement Comics - Learn key ideas about self-improvement via weekly comics.

149. That Moment When You're Boarding a Flight Home, and Andreessen Horowitz Calls…

Joseph Woodbury of Neighbor.com shares three pieces of advice on how to raise capital — from integrating yourself into the local ecosystem to being able to change your plans on a moment’s notice.

150. I Made a Productized Service for the Solopreneur GTM and the Build-in-Public Crowd: Here's How

GTM, marketing, sales. They can't be an afterthought for Indiefounders. That's why I've created a productised service offering a teardown.

151. CEO of Lattice: First-Time Founder Misconceptions

Jack Altman, CEO of Lattice, goes over first-time founder misconceptions.

152. Interview with Jérôme Nagle, CEO and Founder at Ultimate Go-Getter

Become Your Ultimate Self. A brand new app with unique assignments that help you get the most out of yourself. See how Ultimate Go-Getter got started and how you can get started.

153. The Key to Entrepreneurial Success: Seeing a World That Doesn’t Exist

The Entrepreneurial Secret: See a World That Doesn’t Exist

154. Spotify Offered Me Hundreds of Millions for My Company - I Said No

Nathan Barry describes the time Spotify offered him hundreds of millions of dollars for his company.

155. Fear of Publicity: Why Tech Startups Miss Out on PR Opportunities

From personal experience, I can say that many business owners have a near-panic fear of gaining too much publicity.

156. Andrew Wilkinson: Lessons Learned Based on the Last 20 Years of Running Tiny

Here's a big list of things that don't seem to work, based on the last 20 years of running Tiny:

157. Disrupting the Norm: A Tale of Love, Business, and Integration from a Power Couple

This dynamic duo has not only built a loving family over 15 years of marriage but have also nurtured two successful businesses side by side.

158. "We want functional decentralization" Q&A with Wildland Creators

Wildland is a new, open data management protocol with improved users' privacy, security, and multi-categorization. A Q&A with J. Zawistowski and A. Regulski.

159. How to Build a Multi-Channel Outbound Sequence on Lemlist

Understand how to use Lemlist to setup, monitor and track the performance of your outbound marketing campaign.

160. Representing Your Virtual Self: An Interview With Leo Nilsson From Scapin'

Today, I am talking with Leo Nilsson, co-founder of a mobile chat app - Scapin'. Scapin' is designed for our virtual identities.

161. How to Implement First Touch Attribution with RudderStack

Learn how to use Rudderstack's freemium offering to build first touch attribution logic for your website visitors and leads at zero cost.

162. From Zero to Hero: Build a Team of High-Performers

Building a successful business is a challenging task. It takes dedication, hard work, and a team of individuals willing to work together to achieve a common goal. I always say this, but businesses don’t move people; people move businesses.

163. Founder Story: Lessons From Over 25 Years in Silicon Valley

This is part two of a two-part conversation with serial founder and pioneer of “digital identity” Garrett Gafke on how he built and launched his most successful startup, IdentityMind. Click here to read part one.

164. Looking Into Ethereum’s Merge And How KIRA Circumvents PoS’s Biggest Weakness

Ethereum's Merge switched the blockchain from Proof of Work to Proof of Stake. While it addressed some of the old problems, it created a new set to deal with.

165. The Secret of Networking: How High-Tech Companies Expand Into New Markets

Maxim Lukyanov shares insights on how business developers and high tech companies attain noteworthy results through the secret and power of networking

166. Meet the Writer: HackerNoon's Contributor Eran Elhanani, Co-Founder of BullPerks and GamesPad

My name is Eran Elhanani, and I’m the Co-Founder of BullPerks, a decentralized VC and multichain launchpad, currently ranking as the #2 IDO investment platform.

167. Post-Acquisition Lessons on Time & Energy Management: What I'd Do Differently as a Repeat Founder

I've often fantasized about time traveling to coach my younger self. This is the advice I'd give myself when I was launching my last startup.

168. How I Productized Legal Advice Into a Scalable Marketplace

I started as a practicing lawyer working with small businesses. It didn’t take long to see the ceiling of the offline model.

169. What Tech Startups Can Learn from Failed Projects: A Candid Look at My First Fintech Venture

Learn startup lessons from the failure of my first Fintech venture. Discover the importance of market validation, user communication, and knowing when to let go

170. How Mathematics Can Be The Winning Strategy for a Fast-Growing Company

When D’Shawn Russell left her job as a school math teacher to start Southern Elegance Candles, she never imagined that it would grow into what it is today.

171. How To De-Risk Your Startup And Become ‘Definitely Fundable’

Immad Akhund has invested in 100+ startups and was a Y Combinator Partner. Here are his tips for raising capital.

172. “Pay Want You Want” Model Got Us $1M Donations for Online Courses

Join HYLS, donation-based online course platform where you boost your self-development at any price you want.

173. 6 Key Takeaways From Clubhouse FOMO for First-time Founders

Though the FOMO is gone but here are the key takeaways that founders can learn from Clubhouse.

174. "We Work With Nature, Not Against It," says OUDToken CEO Teh Huang Wei

Most innovative concepts lead to some form of manipulation. The only way forward is decentralizing these aspects to keep green investing manipulation-free.

175. "Borders are Getting Thinner, but Division Among Societies is Growing"

An interview with the founder of Quixy, a no-code platform that helps automate processes for any industry and any function.

176. How To Lead Your Business Strategically

The capacity of a leader to envision, plan, direct, and get the most out of the resources at hand effectively is known as strategic leadership.

177. "We Are Moving Forward To a New Digital Age": Shane Oconnor, Seratio BDM

In conversation with Shane Oconnor, Business Development Manager at Seratio, a UK-based think tank.

178. Three Non-Obvious Fundraising Tips from the Startup Veterans Behind Lovevery

When friends Jessica Rolph and Rod Morris partnered to launch Lovevery in 2015, the two founders already had massive success stories under their belts.

Jessica previously had a successful exit from organic baby food company Happy Family, which she founded. Rod helped take SaaS utility platform Opower public as part of the company’s leadership team.

Despite their wealth of past experience, Jessica and Rod had plenty to learn when fundraising for Lovevery, a subscription business that puts sustainable, science-backed play kits into the hands of parents. As parents themselves, Jessica and Rod knew their idea had legs when they began working on it — but they still felt “very vulnerable” during the fundraising process, according to Jessica.

“With the success we had in the raises, on the outside they [seemingly] came easily,” Jessica says. “But on the inside, getting to that place where you have momentum is hard.”

As they grew Lovevery, they found fundraising successfully was all about the timing. On an episode of How I Raised It, Jessica and Rod shared the lessons that came from raising $32 million for Lovevery over three funding rounds.

179. Women in Tech: Interview with Diana Akchurina, Tech Founder and Mentor

Diana Akchurina is a Tech founder, marketing comms specialist, digital nomad, and mother of two. Learn about her journey in this Women-in-tech interview.

180. An Interview With Ian Sanders: Entrepreneurship, Being a Leader, and More

On today’s episode of Startups On Demand, I am joined by Ian Sanders, CEO and Co-Founder of Blue Cape, a stealth startup in the field of healthcare analytics.

181. #FoundersConnect with Oluwatomi Solanke, Co-founder/CEO of Trove Finance

Peace interviews Oluwatomi Solanke, co-founder and CEO of Trove Finance, a micro-investment platform that allows Nigerians to invest in foreign stock markets.

182. How To Run a Tight Fundraising Process

Why you have to own your process from end-to-end

183. Meet the Founder of Cascadia Carbon: Alex Wick

Alex Wick is the founder and CEO of Cascadia Carbon, which is building a verifiable offset database of individual, geotagged trees.

184. Women in Tech: Shanaz Khan's Journey of Building Sustainable Solutions in Tech

Discover the inspiring journey of Shanaz Khan, a woman in tech passionate about clean/green tech and renewable energy.

185. Software Engineer Remi Denoyer’s Curiosity Propelled His Career at Mentoring Platform Plato

Remi Denoyer learned to code and built his first basic application at the age of 14. He was the perfect founding engineer for Plato, a mentorship platform.

186. #FoundersConnect: Abdul Hassan, CEO & Founder of Mono, Backed by Ycombinator

FoundersConnect: Abdul Hassan, CEO & Founder of Mono, Backed by Ycombinator

187. Startup Interview with Vivek Khatri, Director & Founder, at Emizen Tech

Vivek Khatri, Director and Founder of a Startup of the year nominee Emizen Tech, shares their origin story, why they focus on retention and exciting technology.

188. Enabling Business Operations With Computer Vision: Interview With Tanay Dixit, CPO of Wobot.ai

HackerNoon good company with Tanay Dixit, co-founder, and CPO of Wobot.ai.

189. From Early Builder to CTO at 19: The Story of Alexandre Genest

Alexandre Genest’s journey from early coding to CTO at Hilt shows how real-world systems, performance, and observability shape modern engineering.

190. The Entrepreneur's Balancing Act: Cultivating Success While Nurturing Life's Dimensions

Embark on an entrepreneurial journey while maintaining balance in health, finance, relationships, and spirituality. Thrive in all aspects of life! 🚀🌟

191. The Power of Knowing What to Do

The underlying reason a startup is so hard, so strange - and why so many fail - is that you yourself have to figure out what to do.

192. How To Create Personal Breakthroughs By Mastering EI: Interview With Matt Kursh

193. From Connected Cars to Mental Health: Ivan Mishanin's Journey as a Co-Founder and Tech Leader

How to build successful companies and what tech leader should look like in the AI era?

194. How to work on a startup when your motivation runs out

In most cases, positive motivation drives a person starting a new business. He wants to make the best product, become a leader, or earn a profit. When that positive motivation runs out, there are two possible scenarios.

195. Startup cybersecurity 2023: Never be out of the fight

Startups have every reason to feel like they are jumping into an ocean filled with sharks as they approach their 2023 cybersecurity strategies.

196. Successful Founders Built Lives That Energize Rather Than Drain Them

Your home life isn't separate from your business. It's the foundation everything else is built on.

197. Startup Lessons: Customer Discovery is Invaluable

198. Ilya Rouss: “Travel Trends to Watch: digital nomads, non-mainstream places, local economies growth”

When the travel industry will recover after the pandemic, what will the travel experience look like and how modern tech will influence it?

199. Thierry Schellenbach co-founded Stream after struggling to scale activity feeds

Interview with Thierry Schellenbach, co-founder & CEO of Stream, a provider of APIs and SDKs that enable product teams to add in-app chat and activity feeds.

200. Taking the Leap: From Developer to FinTech Startup CEO [Interview]

Ioana started her career as a software developer, but decided to leave Shopify to found Konvi - the investment platform for alternative assets.

201. "Founder Bottleneck" Might Prevent Your Next Raise or Exit

Founder dependence isn’t just an operational bottleneck, it’s a risk multiplier that will kill any operator's chance of exiting a business.

202. Women in Tech: Interview With Maja Roknic, CPO and Co-Founder at CulturePulse AI

CulturePulse's fearless female co-founder and CPO pushes the boundaries of product development in AI.

203. Why I Left a VC Job to Dive into the Hard Path of Building a Startup in Sillicon Valley

Haruka Takamori is an immigrant ex-VC founder and founder of U.S.-based startup, Syval.

204. How to Launch and Sell a Fintech Startup in Less Than 4 Years —Interview, Ankit Singh

From “challenger banks” to cryptocurrency and blockchain technology, fintech startups such as Stripe & Paypal continue to revolutionise the financial industry.

205. Female Entrepreneur Miki Agrawal Champions Global Sustainability Initiatives With TUSHY

Miki Agrawal champions ongoing global sustainability and eco-friendly hygiene through her professional and personal life.

206. How Does One Trade Crypto in Canada and the USA?

By a deep study into the market systems before launch, the company pointed out shortcomings within the crypto industry.

207. Developing Finsterwald Amid a Pandemic: A Startup CEO in The Trenches

Former Huawei manager Peter Stieglbauer talks about Decentralization, Gaming, and Funding for their new VR 3D game, FINSTERWALD

208. Stop Thinking Big and Start Thinking About the Daily 1% Improvement

The only way to learn is by starting and doing things relentlessly. You should go deep into a chosen space, and don't worry about making big leaps.

209. How Mobile Weather Apps Help You Survive the Hurricane Season

Mobile weather apps have evolved a lot, raising awareness and allowing people to plan their time with the weather in mind.

210. The Key to Succeeding With Founder-Led Sales

Sam Blond discusses founder-led sales.

211. "Track Your Mood For Improving Your Mental Health" says a Founder Living With A Bipolar Disorder

Oftentimes we don’t even realize how we’re feeling. Even when someone asks us, “How are you?” our knee-jerk reaction is to say, “Good.” But are you really feeling good? What is your mood right now? If you had to label how you’re feeling in your body and mind, what would you write down?

212. 'Contemporaries Are Always Good for the Industry': Vijay Pravin, CEO of BitsCrunch

Vijay, Founder & CEO of bitsCrunch talks about the importance of securing the NFT ecosystem.

213. Solve for the Edges and Get The Middle for Free: Innovating for Inclusivity

Innovating for inclusivity in tech startups: How solving for edge cases leads to better solutions for all users, illustrated through legal tech advancements.

214. From Bribing Customers with Food to a Universal Secrets Manager: 5 Lessons from a First-Time Founder

Doppler's Brian Vallelunga shares five lessons he learned about raising capital and creating sustainable partnerships.

215. Building a Tech Startup Without a Technical Co-Founder

Finding a technical co-founder is one of the biggest challenges faced by startup founders. Here’s how Audapio’s Founder Dudley Gould overcame this common startup hurdle.

216. Meet the Writer: HackerNoon Contributor Omer Rosenbaum, CTO and Co-Founder at Swimm.io

My name is Omer, I am the CTO and Co-Founder of Swimm, a devtool that helps developers and their teams manage knowledge about their codebase.

217. My College Startup Failed; This is What I Learned

218. What Happens When Purpose Is Assumed, Not Discovered

A cautionary tale of ambition, denial, and the costly consequences of building a startup without a clear problem to solve or customers to serve.

219. How An "Underdog" Founder Raised $4.7 Million To Build A Plastic-Free Grocery Delivery Service

Zuleyka Strasner raised $4.7 million for her environmentally-friendly store Zero Grocery in two years. She shares her advice on fundraising seed rounds.

220. Being a Non-British Founder in the UK Startup Scene: The Good and the Hard

Explore how an international founder’s unique mindset, resilience, and adaptability fuel success in the UK startup ecosystem and global talent mobility.

221. How to Start a SaaS Business When You’ve Never Met Your Cofounder

The most fundamental core of any business relationship is trust. Traditionally this was built through multiple interactions, which included at least one face to face meeting.

222. Ivan Huerta, Parabeac CEO, made every mistake in the book until he pivoted the business

Our startup is called Parabeac, and we make it easy for both designers & developers to make accurate and responsive designs.

223. Lessons Learned From Successful Founders Building in Public

Valuable Lessons learned from 5 successful public building founders.

224. 'At the Coalface of Implementing Data Stacks': kleene's Co-founder & CEO Andrew Thomas

2-minute look at the building of kleene.ai through a founder's eyes.

225. AttachBack So Far: The Story of My Early-Stage Startup

Can a brand new startup forever change the way we use our phones? I think I know the answer. In this post, I’ll share the story of my fledgling startup that aims to do just that.

226. 7 Stories To Learn About Davis Baer

Learn everything you need to know about Davis Baer via these 7 free HackerNoon stories.

227. How a Founder’s Passion Can Hinder Startup Success

It is common advice for founders to build only things they are passionate about. But, there's another side to that story.

228. Providing Credit for Small Businesses - Interview With Dave Lewis, CEO and Founder of Ranqx

Prior to starting Ranqx, I founded a company called VantagePoint, a growth advisory business with offices in Auckland, Sydney and Dubai.

229. Behavioral Signals Analyzes Human Behavior from Voice Data

Behavioral Signals is an AI company that develops AI technology to analyze human behavior from voice data.

230. Andros Wong's Wonder is Providing DAOs with Technical Infrastructure

Wonder has one key concept and it is that “the future is collaborative”

231. Startup Interview with Brady Harris, CEO, Dwolla, Inc.

Dwolla, Inc. is an Iowa-based fintech company helping innovative organizations digitally transform their payments.

232. "Rationality at the expense of another person’s mental health is not worth it", says Elesaro CEO

An interview with Johnpaul Nobodo - the Co-Founder/CEO of Elesaro: a full suite crowdfunding protocol built on Binance smart chain.

233. "Do what you love and love doing it": Colby Tunick, ReFocus AI Co-Founder

"I don't believe it’s possible for someone to ‘just do a startup.’ It's a mission you fall in love with, again and again."

234. How We Built Arengu — Story and Vision of Our Startup

235. The Importance Of Staying Humble And Strong Company Culture: Stephen Goldberg, HarperDB CEO

Harper DB is a startups of the year nominee from Denver, Colorado. Stephen Goldberg, CEO, shares the origin story and what makes their company culture relevant.

236. "Blockchain has the Ability to Raise Billions out of Poverty" Rahkeem Morris, Syrg Co-Founder & CEO.

Syrg is empowering both employers and employees using automation tools. Their CEO shares the fascinating origin story and explains their covid pivot.

237. Building Armenia’s First Live Seafood Supply Chain: A Business Case in Market Creation

How I built Armenia’s first live seafood supply chain by combining custom systems, logistics, and smart business strategy.

238. 10 Features For A Successful Community: An Open Letter

If you’re like us, you probably have some unread red-dot notifications in your Slack sidebar. Work-related, a few are from social groups or communities

239. Building a Successful Fintech by Listening to the Market (Founder Interview)

When serial entrepreneur Illit Geller started telling me her story, I could instantly see why the fintech startup she founded, TradAir raised $11M in its latest funding round.

240. Eicrud: The Solution to Web App Complexity

Discover how I created Eicrud, a Node.js framework designed to eliminate technical debt and simplify web app development.

241. "My mission has always been about freedom," says Anthony Di Iorio, Ethereum Co-founder

“My mission has always been about freedom. As I mentioned, I don’t like school — I never liked being told what to do," says Anthony Di Iorio Ethereum Co-founder

242. Meet the Writer: Sergey Prilutskiy is The Co-founder of Blockchain Company, MixBytes

Short interview with Sergey Prilutskiy, developer, researcher, security specialist, co-founder of MixBytes company, and Hackernoon author.

243. BeyondBoard AR: The Origin Story of a Tehran Startup of the Year Nominee

AR Bulletin Boards: T

244. HackerNoon & The Wild West of Startups

Amy Tom chats with David Smooke (co-founder and CEO of HackerNoon) about his founder's journey with HackerNoon, and with Storm Farrell (Software Developer at Ha

245. The Most Dangerous Lie in Startups

Most founders skip a founder agreement because they trust each other. But when pressure hits - that missing structure becomes the root of chaos.

246. 'Time is the Most Valuable Resource': Michael Skoblov, CEO of BITLEVEX

Startup interview with Micheal Skoblov, founder and CEO of BITLEVEX.

247. The Story of Shuttle Planet, Early Traction, and a Bunch of Misfits

"Keep going; don’t let fear stop you too much. Focus on the fact that every effect has a cause, find out what that cause is."

248. AI Has Become My Co-Founder

From automating LinkedIn posts to building a full-scale enterprise platform, discover how AI evolved from tool to co-founder in the creation of Linkeme.ai.

249. From Rejections to $21M in Funding: A Founder Story

Launching a startup is a huge undertaking that will test your personal and professional relationships to the limit.

250. Interview With Dmitry Kubyshkin: What Makes DevOps Engineers so Valuable for Businesses?

Dmitry Kubyshkin is a seasoned professional in the field of DevOps. Here he discusses the hiring of DevOps engineers and what makes them so valuable.

251. Startup Interview with Patrick Stäuble, Teylor CEO & Founder

Teylor is a modular technology platform to build, automate, deliver and scale credit products. We are building the lenders of tomorrow.

252. Here’s Everything I Learned Building a Blog to Teach Cybersecurity

It was in early 2025 that I initiated my own blog, OpenExploit.in, with one simple aim: to make cybersecurity easy to learn and available to all.

253. Startup Interview With Ryan Edwards-Pritchard, Founder & CEO of Cape

Cape is a technology startup developing corporate cards designed to save businesses time and money.

254. Digging Cold Out of the Internet [Interview with Crypto Mining CEO]

Bitcoin is still far away from it's all time high and these days cryptocurrency mining has become more complicated. Large miners built huge arrays to mine, making it harder for smaller miners to compete. As an alternative to traditional mining on your own equipment, which requires solid initial investments, you can use cloud mining, which allows you to mine crypto currency utilizing a remote datacenter with shared processing power, so you don`t have to install your own hardware.

255. Tech Is Shaping the Airlines Business: Here's How

In this episode of "Flying into the Future: How Tech is Shaping the Airlines Business," Omri Hurwitz welcomes esteemed guest Nathaniel Felsher.

256. AI Meets Crypto: A Conversation With EmpyrX Founder And CEO Cam Sandifur

In this interview with Olayimika Oyebanji, Cam discussed EmpyrX and the importance of AI.

257. Production Horror Story: How My Startup (Almost) Went Bankrupt

Just in time for Halloween failures in production are scarier than most movie monsters. Here's a personal scary story of a production fail.

258. Making Web3 Resilient & User-Friendly With Mayur Relekar

An exploration of the challenges within the Web3 space, focusing on the imperative for solutions that resolve user-centric issues with Arcana CEO Mayur Relekar

259. No Stanford Degree? No Problem. Here’s How to Win as an Underdog Founder

Startups love to talk about disruption, but when it comes to funding, the system still favors the familiar.

260. “Four-Day Workweek? I Hate It.” Top Fintech Founder Max Faldin About Building a Remote-First Startup

Silverbird Founder Max Faldin about Building a Remote-First Startup

261. Startup Journey: From Aviation To Fintech

The ninth interview in the Startup Journey series: Building an airline out of necessity & an innovative fintech product out of passion

262. Why Users Leave Before They Ever See Your App’s Value

If the onboarding experience is poor, users will be discouraged from using the product and will eventually drop off.

263. Future of Telemedicine: Lessons I've Learnt From Building my HealthCare App MVP

While I held the belief that planning is essential, this project reaffirmed that adaptability and agility are equally crucial in developing an app.

264. A Statement From Hayden Adams - The Inventor of Uniswap

Hayden Adams on Uniswap.

265. Figthing the Bad Actors with Machine Learning: Startup Interview with Harsh Pandya, CEO Giant Oak

While working in the financial and government spaces, we saw a need across industries for enhanced entity screening processes that use AI and machine learning.

266. The Highs and Lows of My First Real Startup, CoLaunchly

Discover the journey of launching CoLaunchly, its challenges, and insights on startup life, burnout, and growth

267. Startup Interview with Pavel Shkliaev, CEO Of LensAI

An interview with Pavel Shkliaev, CEO of LensAI, who discusses the vision behind the founding of his company and how he measures the company's success.

268. "AI Shouldn't Have the Final Word in Recruitment Yet" - Jamie Beaumont

Less than a decade ago, we could only dream of being able to spend five minutes on a job that required 10 hours to complete. All we could hope for was a magic wand. Cargo dancing with tambourines could also help, but there was no guarantee (pun intended).

269. From Thesis to Edutainment Platform: My Journey Building Startup as a Solo Founder

Personal story about how a grad school idea turned into an educational game studio that reached nearly a million families.

270. From Fluorescent Lights to Sporting NFTs

It pays to be neurodiverse - Ben Appleby escaped school and followed his instincts - now he is a co founder of an exciting web3 sporting platform launching soon

271. Top Actionable Tips to Grow a Community: More Tips to Monetize

Find this article where it was originally published, on dunncreativess.github.io!

Find a Niche!

Nobody can promote themselves or their projects if they're a jack of all trades. Nor will people find a universal proposition to be appealing. The first key to success is to ask yourself what your differentiating features are and who is your audience? You can then start to identify your niche.

In my case, I noticed that I got a lot more traffic from my money-making code like market making or arbtitrage crypto trading bots than I did from my other GitHub repos. What this means is that while some people are interested in interesting code, there are a lot more people out there interested in turning equity into realized pnl :)

272. 3 Best Tips To Attract Investors Being An Outsider

Unshackled Ventures founding partner Nitin Pachisia explains three ways he built a strong network during his fundraising journey.

273. Focus On The Problem: When Your First Solution Fails, Simply Start Again

Ali Halabi moved to Istanbul in 2013 to solve the city's massive traffic problem. His first startup was an on-demand carpooling service, but it failed.

274. Startup Interview with Bryan Schuldt, Tability Co-founder

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《加密货币评论家》通过打造一个以社交驱动的加密货币排名平台，获得了39分的“实用性评分”

2026-05-29T01:59:59+00:00

TheCryptoReviewer ranks crypto coins by real community activity instead of market cap, using age-based tiers so every project has a fair path to #1. It's a social network where crypto communities drive rankings through posts, groups, and daily fantasy trading competitions.

人工智能音乐领域的下一场战役不在于生成，而在于分发

2026-05-29T01:52:37+00:00

AI music platforms have largely solved generation quality, but distribution is becoming the industry's next major challenge. As AI-generated music floods streaming platforms, recommendation systems, creator ecosystems, moderation infrastructure, and audience ownership may become more important than generation models themselves.

您的图数据库将边视为“哑指针”。以下是您忽略的关键点。

2026-05-29T01:51:09+00:00

TLDR: Most graph models let you traverse edges but not query them. When your edges carry metadata -- permissions, roles, statuses -- this forces you to scan thousands of edges to find the handful you care about. I fixed a 3-second query by making edges indexed and queryable. It dropped to 4ms.

The 3-Second Query

A customer's device had 10,000 relationships pointing to it -- users who owned it, admins who managed it, services that monitored it. Each relationship carried attributes: status (active/retired/terminated), role (admin/viewer/operator), enrollment date.

They asked: "Show me all active admins for this device."

Our system's answer: fetch all 10,000 edges. Deserialize each one. Check status. Check role. Return 47 matches.

Three seconds. For what should have been a B-tree seek.

The problem wasn't the database. The problem was that edges in our graph model were invisible to the query engine. They existed to be traversed -- walked from A to B -- not to be searched.

Edges Are Second-Class Citizens (In Every Graph Database)

Think about how you model a user's permissions in a graph:

User --[HAS_PERMISSION]--> Resource

Now add attributes to that permission: scope, status, effective date, conditions. Where do they go?

In Neo4j, JanusGraph, or Neptune, they go on the edge as properties. Sounds fine. But here's the catch: edge properties aren't indexed. When you query:

"Find all ACTIVE permissions of type ADMIN on this resource"

The engine:

Gets the resource node
Pulls ALL incoming HAS_PERMISSION edges
Checks each one against your filters

That's a full scan. At 100 edges, you don't notice. At 10,000, you're waiting seconds. At 50,000 -which happens for shared resources in large organizations -- you're timeout-ing.

Most teams solve this with a hack: create an intermediate node.

User --> [PermissionNode (status: active, role: admin)] --> Resource

Now the attributes live on a node, which IS indexed. But you've doubled your traversal depth, made your transactions more complex, and your data model now lies about what's actually a relationship and what's an entity.

The Fix: Make Edges Behave Like Indexed Table Rows

The pattern that fixed our 3-second query: typed links -- edges with an ordered set of identity attributes that function as a composite index.

Here's the idea. When you define an edge type, you declare which attributes form its "identity" and in what order:

Edge Type: DeviceOwnership
Identity Attributes (in order):
  1. Status
  2. Role

The storage engine keeps edges sorted by these attributes -- just like a compound index in Postgres or a composite sort key in DynamoDB.

Now when you query Status = 'Active', Role = 'Admin', the engine doesn't scan 10,000 edges. It seeks -- goes directly to the sorted range that matches your prefix. Returns 47 results in 4ms.

The Rules (Same as Any Composite Index)

If you've ever used a compound index in SQL or a composite sort key in DynamoDB, you already know these rules:

Works:

First attribute only: Status = 'Active' (prefix scan)
First + second: Status = 'Active', Role = 'Admin' (exact seek)
First + range on second: Status = 'Active', Role between 'A' and 'M'

Doesn't work:

Second attribute only: Role = 'Admin' (breaks prefix -- like skipping the partition key)
Range on first + exact on second: Status between 'A' and 'C', Role = 'Admin' (range on non-terminal)

Same rules as every composite index ever built. Not novel in theory. Powerful in practice when applied to graph edges.

What This Actually Looks Like in Production

Three real patterns from our system:

1. Permission lookups: "What can this user do on this resource?"

Edge: Principal -> Resource
Identity: [Action, Scope, Condition]
Query: Action = 'Write', Scope = 'Full'  ->  seek, not scan

2. Temporal relationships: "Show relationships created after Jan 2024"

Edge: User -> Device
Identity: [Status, EffectiveDate]
Query: Status = 'Active', EffectiveDate > '2024-01-01'  ->  prefix + range

3. Role filtering: "All active drivers"

Edge: Employee -> Organization
Identity: [Status, Role]
Query: Status = 'Active', Role = 'Driver'  ->  exact seek

Each query returns in single-digit milliseconds regardless of total edge count.

The Gotchas

You can't change the attribute order once deployed. Choose wrong, and your primary query requires a full scan. Think of it like choosing a primary key -- you get one shot. Pick the attribute you filter on most frequently as the first one.

Identity attributes are immutable. Want to change a relationship's status? You can't update in place. You delete the old edge and create a new one. This is fine for status transitions that happen occasionally. Bad for attributes that change every second.

Combined identity values have a size limit. ~200 KB total across all identity attributes. This forces you to use compact discriminators (enums, short strings) not JSON blobs. Which is actually good discipline.

DIY Version (If Your Graph DB Doesn't Support This)

If you're using DynamoDB or Cassandra as a graph backend, you can fake this with composite sort keys:

PK: target_node_id
SK: EDGE_TYPE#active#admin#us-east-1#source_node_id

Query with beginswith(SK, 'EDGETYPE#active#admin') -- same seek behavior.

It's uglier. But it's the same indexed-edge concept under the hood.

When Not to Bother

Your nodes have < 100 edges each. Scanning is fast enough
Your queries are about connectivity ("is A connected to B?"), not about edge attributes
Your edge attributes change at high frequency -- the delete/recreate cost dominates.
You need arbitrary filter combinations (any attribute in any order) -- you want a search engine, not a composite index.

The Point

The graph database world spent two decades optimizing for traversal -- following edges from node to node as fast as possible. But for systems where relationships carry business logic -permissions, memberships, enrollments, delegations -- you don't just traverse edges. You query them.

Making edges indexed and queryable is the difference between scanning 10,000 relationships to find 47 matches and seeking directly to those 47 in 4ms.

Your edges aren't just pointers. They're data. Treat them that way.

The author builds hierarchical storage and identity systems at AWS that serve billions of requests daily at single-digit millisecond latencies.

如何让 Docker 构建更小、更快

2026-05-29T01:49:49+00:00

\ \n Not all Docker files are efficient. A good Docker file produces a small image, rebuilds quickly after a code change, and does not redo all the work every time you edit a single line of code. \n Most Dockerfiles I have seen in real projects are closer to the first kind. They might produce 1.5 GB image for a Python service that imports four libraries, and they take 40 seconds to rebuild after a one line edit. \n This article walks through the changes I keep applying to Dockerfiles. Each section has a working example with before and after numbers from a small Python service I used as a test.

\n 1. Order your layers so the cache actually helps

Docker builds images one instruction at a time and each instruction produces a layer. Docker caches that layer keyed on the instruction itself and the files it depends on. As soon as one layer's cache is invalidated, every layer after it is rebuilt from scratch. \n This is the rule that gets ignored most often. People put COPY . . near the top for many unknown reasons, maybe someone is trying to build a POC and efficiency is not a priority, and then wonder why every code change triggers a full pip install. \n The cheap fix is to copy the dependency manifest first, install dependencies, and only then copy the rest of the code. Application code changes on almost every build, while requirements.txt changes maybe once a week.

\n Example 1. Reordering for cache hits.

Bad order:

dockerfile
FROM python:3.12-slim
WORKDIR /app
COPY . .
RUN pip install -r requirements.txt
CMD ["python", "main.py"]

\ Good order:

dockerfile
FROM python:3.12-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
CMD ["python", "main.py"]

\n The two Dockerfiles produce the same image, but they rebuild very differently after a code edit. These are some rough estimates on my local machine.

| Build | Bad order | Good order | |----|----|----| | First build (cold) | 52 s | 51 s | | Rebuild after editing main.py | 47 s | 2.8 s | | Rebuild after editing requirements.txt | 49 s | 48 s |

\n The cold build is the same. The rebuild after a code edit drops from 47 seconds to under 3 because Docker reuses the cached pip install layer. That is the entire trick. \n

2. Add a .dockerignore

I have lost count of the number of times I have watched a build sit for thirty seconds before printing anything, only to realize Docker was busy shipping a 2 GB .venv to the daemon. \n The build context is everything Docker sees when you rundocker build .. Docker sends all of it to the build daemon before any instruction runs. If you have a virtualenv, a .git directory, training data, model weights, or node_modules in the project, all of that ships with the build context. None of it ends up in the image unless you COPY it, but the daemon still receives it.

A.dockerignore file fixes this. It works like .gitignore.

\n Example 2. Trimming the build context.

A reasonable .dockerignorefor a Python project: \n

.git
.venv
__pycache__
*.pyc
.pytest_cache
.mypy_cache
data/
models/
notebooks/
*.ipynb
.env
.env.*
.idea
.vscode

\n Measured on the test bed project (which had a.venv and a 600 MB data/folder):

| Metric | No .dockerignore | With .dockerignore | |----|----|----| | Build context size | 1.42 GB | 18 MB | | Time to send context | 21.8 s | 0.4 s | | Final image size | 412 MB | 412 MB |

\n Image size is unchanged because nothing was being copied into the image anyway. The win is purely on the build path. Twenty seconds saved every single build is a huge time saver. \n I treat .dockerignore as a file that should exist before the first docker build. It is the lowest-effort optimization on this list.

\n 3. Pick a smaller base image

The base image is the floor of your final image size. If you start from python:3.12, you are already at around 1 GB before you install anything. The slim variant drops that to around 130 MB, and alpineto around 50 MB. \n I default to slim. The Alpine variants are smaller, but they use musl instead of glibc, which means a lot of Python wheels do not have prebuilt binaries for them. The first time you pip install pandas on Alpine and watch it compile NumPy from source, you understand why most people stay on slim. \n There is also distroless, which strips everything that is not the language runtime. No shell, no package manager, no apt. Smaller and harder to attack, but also harder to debug because you cannot docker exec into a shell. A good fit for production runtime images, painful as the base for the build itself. The multi-stage section below shows how to use it without losing your sanity.

\n Example 3. Base image swap, nothing else changed.

Same requirements.txt, same code, same Dockerfile shape:

| Base image | Final image size | Cold build time | |----|----|----| | python:3.12 | 1.18 GB | 58 s | | python:3.12-slim | 412 MB | 51 s | | python:3.12-alpine | 380 MB | 4 min 12 s | | gcr.io/distroless/python3-debian12 (runtime stage of multi-stage) | 168 MB | 62 s |

\n Alpine is smaller than slim by a small margin and slower to build by a large margin, because half the wheels had no Alpine binaries and had to compile. For this project, the math does not work. For a project pinned to pure-Python dependencies, Alpine starts to make sense.

\n 4. Multi-stage builds for anything that needs to compile

Some Python projects need a C compiler at install time. Anything with psycopg2 instead of psycopg2-binary, anything with custom CUDA kernels, anything with a Rust extension that does not ship a wheel for your platform. You install build-essential to make pip install work, and now your image carries gcc, make, headers, and around 400 MB of build tooling that you never use at runtime. \n Multi-stage builds solve this. You do the install in a builder stage, then copy only the resulting site-packages into a clean runtime stage. I tend to skip multi-stage builds when the project uses only prebuilt wheels. The complexity is not free, and a single-stage slim build is usually small enough.

\ Example 4. Single-stage vs multi-stage on a project that needs to compile.

For this test I swapped psycopg2-binary for psycopg2 so the install actually needs gcc.

\n Single-stage Dockerfile:

dockerfile
FROM python:3.12-slim
WORKDIR /app
RUN apt-get update && apt-get install -y --no-install-recommends \
    build-essential libpq-dev \
    && rm -rf /var/lib/apt/lists/*
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
COPY . .
CMD ["python", "main.py"]

Multi-stage version:

dockerfile
FROM python:3.12-slim AS builder
WORKDIR /app
RUN apt-get update && apt-get install -y --no-install-recommends \
    build-essential libpq-dev \
    && rm -rf /var/lib/apt/lists/*
COPY requirements.txt .
RUN pip install --no-cache-dir --prefix=/install -r requirements.txt

FROM python:3.12-slim
WORKDIR /app
RUN apt-get update && apt-get install -y --no-install-recommends \
    libpq5 \
    && rm -rf /var/lib/apt/lists/*
COPY --from=builder /install /usr/local
COPY . .
CMD ["python", "main.py"]

\n The runtime stage installs onlylibpq5, the shared library that psycopg2 links against at runtime. Build tooling stays in the builder stage and never reaches the final image.

| Metric | Single-stage | Multi-stage | |----|----|----| | Final image size | 968 MB | 287 MB | | Cold build time | 78 s | 84 s | | Cached rebuild after code change | 3.1 s | 3.4 s |

\n Multi-stage costs about 6 seconds on the cold build and saves 680 MB on the final image. For anything that ships across networks, that tradeoff is not close.

\n 5. Combine related RUN steps and clean up in the same layer

EveryRUN creates a layer. Layers are immutable. Deleting a file in a later layer does not shrink the layer that created it, it just hides the file. This is the source of a specific kind of bloat that surprises people. They run apt-get install in one step and rm -rf /var/lib/apt/lists/* in a later step, and the cleanup does nothing for image size. \n The fix is to do the install, the use, and the cleanup all inside a singleRUN.

\ Example 5. Splitting versus combining apt-get steps.**

Split version:

dockerfile
RUN apt-get update
RUN apt-get install -y --no-install-recommends curl ca-certificates
RUN rm -rf /var/lib/apt/lists/*

\n Combined version:

dockerfile
RUN apt-get update \ 
    && apt-get install -y --no-install-recommends curl ca-certificates \
    && rm -rf /var/lib/apt/lists/*

| Metric | Split | Combined | |----|----|----| | Image size contribution | 84 MB | 38 MB | | Layers added | 3 | 1 |

\n Same packages installed. The split version carries the apt cache forever because the cache files exist in layer 1, andrm -rf in layer 3 only hides them. \n The same pattern applies topip install (use --no-cache-dir), to npm install(clean the npm cache in the same RUN), and to any source build that produces intermediate files you do not need at runtime. \n One caveat. Combining steps too aggressively hurts cache reuse. If you bundle a rarely-changing apt install together with a frequently-changing pip install, every dependency change wipes both. Keep system packages in one RUN, language dependencies in another, and you get cache reuse and small layers at the same time.

\n 6. Things that are not worth doing

A short list of things that look like optimizations and are not, at least not for most Python and Node services. \n Switching to Alpine when your dependencies have wheels. Already covered above. The build cost is real, the size win is small. \n Hand-pinning every transitive dependency to shave a few MB. Image size is rarely the bottleneck once you are under 500 MB. CI build time and developer iteration speed matter more. \n Adding --squash to the build. It collapses all layers into one. You lose cache reuse across builds and gain almost nothing in shipped size, because the registry already deduplicates layers across images. \n Writing a custom base image. Tempting, almost never worth it. The official slim images are well-maintained and small enough that the marginal win from a custom base does not pay for the maintenance burden.

Putting it together

Run the changes from this article against a typical unoptimized Python service and the numbers stack up:

| Stage | Image size | Rebuild time | |----|----|----| | Starting Dockerfile, python:3.12 base, no .dockerignore | 1.41 GB | 49 s | | After reordering layers and adding .dockerignore | 1.41 GB | 2.8 s | | After switching to python:3.12-slim | 412 MB | 2.8 s | | After multi-stage with distroless runtime | 168 MB | 3.2 s | | After combining RUN steps and --no-cache-dir | 152 MB | 3.2 s |

\n Final image is around 11% of the original size where it started, and the inner-loop rebuild is 15 times faster. None of these changes required rethinking the application. They are all changes to the Dockerfile and one new file next to it. \n If you only do two of them, do the layer reordering and the.dockerignore. Those two cover most of the rebuild-time pain and most of the wasted bandwidth for free. The base image swap and multi-stage are bigger wins on size, but they take an hour or two to set up. The first two take ten minutes and pay back the same afternoon you make them. \n

人工智能如何帮助质量保证团队跳出“理想路径”的思维定式

2026-05-29T01:48:02+00:00

Most test suites are built around what should work. The login succeeds. The item adds to cart. The order confirms. These are the happy paths — the flows every product manager demos, every developer tests locally, and every QA engineer covers first.

The defects that actually reach production rarely live there.

They live in the edge cases nobody thought to document, the error states that only appear under specific conditions, the boundary scenarios that fall between two requirements written by two different people six months apart. Finding those gaps has always been the hard part of test design. Artificial intelligence is starting to change how quality engineers approach that problem — not by replacing the thinking, but by changing what the thinking has to focus on.

The Real Problem Starts Before the First Test Case

Ask any QA engineer where most defects originate and they will not say development. They will say requirements.

Consider a requirement that reads: "Update the checkout flow." No scope definition. No list of what is changing. No device targets. No success condition. No indication of what "update" actually means — is it a visual redesign, a logic change, a payment provider switch? Just an expectation that the QA team will figure it out.

And they do figure it out — because they have to. But what they are actually doing in that figuring-out process is writing the requirements themselves, reconstructing the business intent from a combination of domain knowledge, institutional memory, and educated guessing. That is a significant amount of invisible work that sits upstream of any test case, and it is the work that determines whether the testing that follows is meaningful or not.

Vague requirements produce vague test cases. This is not a testing problem. It is a communication problem that testing inherits.

Common patterns include: "System should load fast" — not measurable, not testable. "User should receive a notification" — when, how, for what events, through which channel, what if delivery fails? "Admin can manage users" — manage how, with what permissions, what are the boundaries? Each of these contains a hidden assumption that will eventually become a defect. The question is whether it surfaces during requirements review or in production.

What AI Actually Does Well in Requirement Analysis

When you feed a well-structured requirement into a capable language model, something genuinely useful happens. The model reads across the entire requirement, extracts the functional flows, identifies the actors involved, and starts generating scenarios from multiple angles simultaneously. It does not get tired. It does not anchor on the first interpretation that comes to mind. It does not skip the error handling because the happy path was more interesting to think about.

The scenarios that come out are, in a word, comprehensive. Happy path coverage, negative cases, boundary conditions, edge cases at the intersection of multiple rules — a good LLM will surface all of these faster than a QA engineer working alone, and it will surface some scenarios the QA engineer might not have reached at all.

There is also genuine value in requirement analysis itself. AI models can parse natural language requirements and surface the ambiguities — the undefined terms, the unstated assumptions, the missing error states. Fed the right prompt, they will ask questions about a requirement that the QA engineer should have asked in the requirements review. That is useful even before a single test case is written.

For teams working in agile environments with short sprint cycles and constant requirement churn, this acceleration matters. The alternative is a QA engineer manually working through scenario identification under time pressure, which is exactly the condition under which edge cases get missed.

What AI-Assisted Test Case Generation Looks Like in Practice

Consider a standard ecommerce requirement: "Users can apply a discount code at checkout."

A QA engineer working through this systematically will cover the obvious scenarios — valid code applied, invalid code rejected, code field left empty. A thorough one will also get to expired codes, codes for minimum order values, single-use versus multi-use codes, and codes that apply to specific product categories.

Feed that same requirement to an LLM with a well-constructed prompt and the output expands significantly. Single-use code applied twice in the same session. Code applied to a cart below the minimum order threshold. Cart recalculates after item removed — does the discount persist or recalculate? Two discount codes applied simultaneously — is stacking allowed, and if not, which error appears? Code entered with extra whitespace or different case — is input normalized before validation? Flash sale price plus discount code — do they stack, override, or block? Concurrent sessions: same user applies the same single-use code from two browser tabs simultaneously. Accessibility: can the discount field be reached and submitted via keyboard only? Localization: does a code configured for one region apply in another?

Several of those scenarios — the concurrent session case, the whitespace normalization, the cart recalculation on item removal — are exactly the kind that reach production. Not because QA engineers are not good at their jobs, but because there are only so many directions a human mind follows in a given session, and time pressure tends to narrow that further.

This is the genuine value of AI in test case design. Not the happy path coverage, which any competent engineer produces. The systematic expansion into the scenarios that sit at the edges of the requirement.

Fast and Vast Is Not the Same as Precise and Defensible

Here is where the honest assessment has to come in.

AI-generated test cases are fast and vast. That is both their value and their limitation.

Fast and vast means the output list is long. Some of what is on that list will be sharp, risk-relevant, and things a QA engineer might have missed. Some of it will be scenarios that cannot actually occur given the system's architecture. Some will duplicate coverage that already exists in the regression suite under a different name. Some will be technically plausible but contextually irrelevant to the business — the model does not know that a particular edge case is a known accepted limitation, or that a specific error state is handled by a downstream system, or that a certain combination of inputs is prevented at the UI layer before it ever reaches the logic being tested.

The other problem is what gets called hallucination in AI research — the model's tendency to generate outputs that are confident, well-formatted, and wrong. In a test case context this looks like scenarios that reference system behavior the requirement does not describe, validation rules the model inferred rather than read, or error messages that do not exist in the actual application.

And then there is the domain knowledge gap. An AI model does not know that your payment processing has a regulatory audit requirement that changes how certain error scenarios must be handled. It does not know that your ecommerce platform has a long-standing limitation with cart persistence across devices. It does not know that your primary user base skews toward mobile and that desktop-specific scenarios are low priority. That context lives in the QA engineer's head, accumulated through months or years of working on the system. No prompt replaces it.

This is not an argument against using AI for test case generation. It is an argument for understanding exactly what you are getting, so you can use it well.

Writing Requirements That AI Can Actually Work With

AI test generation is only as good as the input it receives. Garbage in, garbage out is not a new principle, but it applies with particular sharpness here.

A requirement like "Checkout should be fast" gives an AI model nothing defensible to work with. The scenarios it generates will be equally undefined — and a QA engineer executing them will have no way to determine pass or fail.

Rewrite it as: "The checkout page shall load within 2 seconds for up to 5,000 concurrent users, measured from the moment the user submits the order. Response time degradation beyond 4 seconds shall trigger a user-visible error state with a retry option." Now there is a measurable condition, a load threshold, a success criterion, and a defined failure behavior. Test cases write themselves from that specification — and AI generates fifteen where it previously generated three.

The second example: "Users should receive a notification when their order ships" becomes "When an order status changes to Shipped, the system shall send an email notification to the registered email address within 5 minutes. If email delivery fails, the system shall retry twice at 10-minute intervals and log the failure. Notification content shall include order number, estimated delivery date, and tracking link. Notifications shall be sent in the user's selected language preference." The original produces two test cases. The rewritten version produces twenty.

Good requirements for AI-assisted testing share a few common properties: measurable outcomes, defined actors, explicit error handling, stated dependencies, and examples where behavior might be ambiguous. These are not new principles of requirements writing. They are the same principles that have always produced testable requirements. AI just makes the gap between good and poor requirements more immediately visible.

The Prompt Is the Skill

There is a version of the AI-in-QA conversation that goes: AI will replace test case writers, so QA teams need to adapt or become redundant. That framing misses what is actually happening.

The quality engineers who will be most effective in an AI-assisted environment are not the ones who can generate the most test cases. They are the ones who can construct the right prompt — which means they understand the system well enough to know what context the AI needs, the domain well enough to evaluate whether the output is plausible, and the risk landscape well enough to know which generated scenarios matter and which can be deprioritized.

That requires the same underlying knowledge that good testing has always required. It is just applied at a different point in the process.

The QA engineer's role shifts from scenario generator to scenario reviewer, from requirement interpreter to requirement challenger, from test executor to risk analyst. Those are higher-order activities, not lower. The engineer who spent years learning how systems fail, how requirements drift from intent, and how edge cases cluster around business rules is exactly the person who can use AI test generation effectively — because they can evaluate the output rather than accept it.

The engineer who cannot do that evaluation will not be replaced by AI. They will just be producing large volumes of test cases of uncertain quality, which is a different kind of problem.

What This Actually Changes

AI does not fix vague requirements. It does not replace domain knowledge. It does not understand your regulatory environment, your known limitations, or your user base's actual behavior patterns.

What it does is expand the coverage of test case ideation faster than any human working alone — and it does so without the anchoring bias that causes experienced engineers to weight familiar scenarios over unfamiliar ones.

The happy path was never where quality lived. It was always in the edge cases, the error states, the scenarios nobody thought to write down. AI gives QA teams a better tool for surfacing those scenarios systematically. The judgment about which ones matter, which ones are already covered, and which ones reflect real risk — that stays with the engineer.

AI found the scenarios. You still have to know which ones matter. That gap — between generated and defensible — is where quality engineering lives.

ReaderGo 通过构建一款可扩展的多视角思维工具，获得了 38.36 的实用性评分

2026-05-29T01:46:54+00:00

ReaderGo is a unified thinking tool designed to bridge the gap between note-taking, visual canvases, and structured spreadsheets within a single, flexible ecosystem.

AI 编程工具如何将开发者效率提升 10 倍——同时不牺牲工程判断力

2026-05-29T01:45:51+00:00

From autocomplete to engineering partner

For years, developer productivity tools focused on autocomplete, snippets, templates, and IDE shortcuts. That changed with AI coding agents.

Modern AI tools can now participate across the entire software development lifecycle:

Requirement analysis \n Architecture discovery \n Security and edge-case review \n Technical design documentation \n Existing codebase analysis \n Implementation planning \n Code generation \n Unit test creation \n Code review \n Refactoring \n Debugging \n Documentation \n Jira ticket writing \n Pull request summaries

When I started using Claude CLI/Claude Code for my daily development work, the change was immediate. It was not just faster code generation. The real productivity gain came from using AI across every stage of engineering decision-making.

Instead of starting with code, I now start with structured thinking.

For example, when I get a new feature requirement, I ask AI to analyze:

What are the core functional requirements? \n What architectural areas may be impacted? \n What security risks should be considered? \n What edge cases can break this flow? \n Which existing modules may need changes? \n What implementation approach is safest? \n What tests should be added? \n What documentation should be updated?

This turns AI from a “code writer” into a development workflow accelerator.

A practical AI-assisted development workflow

Here is the workflow that has worked best for me.

1. Requirement analysis

Before writing code, I ask AI to break down the requirement.

Example prompt:

Analyze this feature requirement as a senior software architect.

Identify:
1. Functional requirements
2. Non-functional requirements
3. Security concerns
4. Edge cases
5. Data dependencies
6. API changes
7. UI changes
8. Testing strategy
9. Open questions for product or architecture review

Requirement:
[paste requirement]

This helps surface hidden complexity early. Many production issues happen not because developers cannot code, but because teams miss assumptions, edge cases, or integration impacts.

AI is very useful at expanding the thinking space.

2. Architecture and security review

Once the requirement is clear, I use AI to think from multiple perspectives.

Example prompt:

Review this feature from the perspective of:
1. Principal engineer
2. Security architect
3. Frontend architect
4. Backend engineer
5. Data engineer
6. SRE/production support engineer

For each perspective, identify risks, design concerns, and recommended safeguards.

This is one of the biggest productivity gains. A single developer may naturally think from their primary area of expertise. AI can help simulate multiple review lenses before the design is finalized.

This does not replace real architecture review, but it makes the developer much better prepared.

3. Technical design document generation

After the initial analysis, I ask AI to create a draft technical design document.

Example prompt:

Create a technical design document for this feature.

Include:
- Problem statement
- Goals
- Non-goals
- Current system behavior
- Proposed architecture
- API changes
- UI changes
- Data model changes
- Security considerations
- Observability/logging
- Error handling
- Rollout plan
- Test plan
- Risks and mitigations

The first draft is rarely perfect. But it gives a strong starting point. Instead of spending hours creating structure, I can spend my time validating assumptions, improving accuracy, and making architectural decisions.

That is where engineering judgment matters.

4. Existing codebase analysis

The next step is asking AI to inspect the current codebase.

With CLI-based tools, this becomes especially powerful because the AI can search files, inspect dependencies, understand patterns, and propose a change plan.

Example prompt:

Analyze this repository for the best implementation plan for the feature below.

Do not modify files yet.

Find:
1. Existing modules related to this feature
2. Similar implementations
3. Files likely requiring changes
4. Shared utilities or services to reuse
5. Risks in the current code structure
6. Step-by-step implementation plan

Feature:
[paste feature]

This is where tools like Claude Code, OpenCode, Copilot CLI, and other repo-aware agents become much more useful than a normal chatbot.

5. Implementation planning before implementation

One mistake developers make with AI is asking it to immediately write code.

A better approach is:

Analyze first. \n Plan second. \n Implement third. \n Review fourth.

Example prompt:

Create an implementation plan only. Do not edit files.

For each step, include:
- File name
- Change needed
- Reason for change
- Risk level
- Tests required

This keeps the developer in control. You can review the plan, correct it, and only then allow the AI to make changes.

6. Code implementation

Once the plan is reviewed, I let AI implement the changes.

Example prompt:

Implement the approved plan.

Constraints:
- Follow existing code patterns
- Keep changes minimal
- Do not introduce new dependencies unless necessary
- Add unit tests
- Preserve backward compatibility
- Explain each file changed

This works well for normal development activities like:

Adding a new API field \n Updating UI behavior \n Adding validation \n Refactoring repeated logic \n Writing unit tests \n Fixing lint issues \n Improving error handling \n Updating documentation

But even after implementation, the developer must review every change.

Do not blindly trust AI-generated code

This is the most important lesson from AI adoption.

AI-generated code can look clean, confident, and production-ready — but still be wrong.

I have seen cases where AI-generated code had:

Unnecessary complexity \n Missed edge cases \n Incorrect assumptions \n Security gaps \n Poor performance choices \n Duplicate logic \n Weak test coverage \n Inconsistent coding patterns \n Incorrect error handling \n Over-engineered abstractions

Developers should treat AI-generated code like code written by a junior developer who is fast, knowledgeable, and helpful — but not always aware of your system’s full context.

The developer must still ask:

Does this follow our architecture? \n Is this secure? \n Is this maintainable? \n Does this match existing patterns? \n Does this handle failure cases? \n Are the tests meaningful? \n Will this scale? \n Can I explain this code in review?

If the answer is no, the developer has not finished the work.

The hidden risk: developers losing codebase context

One concern I have seen in real teams is that some developers use AI to generate code without understanding the implementation.

This becomes visible during code review.

A developer raises a pull request. Reviewers add comments. Then the developer struggles to respond because they do not fully understand the code that AI wrote. They go back to AI for every correction, but the review takes longer because the developer has lost context.

This is dangerous.

Over time, if developers rely too much on AI without understanding the codebase, they may lose the ability to:

Explain feature flows \n Debug production issues \n Make architectural suggestions \n Understand dependencies \n Estimate impact \n Respond to review comments \n Improve the design independently

AI should increase developer capability, not reduce it.

A good rule is simple:

Never merge AI-generated code that you cannot explain.

Use AI as an assistant, not as the owner

For now, the safest adoption model is:

AI can assist. \n AI can suggest. \n AI can generate drafts. \n AI can review. \n AI can refactor. \n AI can test.

But the developer owns the final decision.

This is especially important in enterprise systems where mistakes can affect security, compliance, customer data, cost, performance, and production stability.

AI should be part of the engineering workflow, but not the accountable engineer.

Token optimization: the next phase of AI adoption

Early AI adoption inside companies often starts with broad access. Employers want developers to experience the productivity benefit, so many teams initially allow generous usage.

But over time, AI usage can become expensive.

As AI coding agents become more powerful, they read more files, generate longer outputs, use larger context windows, and run more complex reasoning. This increases cost.

Recent pricing trends show why responsible usage matters. GitHub says Copilot CLI currently consumes one premium request per prompt with the default model, while other models may multiply that request by the model’s rate. GitHub has also announced that Copilot is moving from premium-request accounting to usage-based billing using AI credits starting June 1, 2026.

That means teams cannot assume AI usage will remain “effectively unlimited” forever.

Choose the right model for the right job

Not every task needs the strongest model.

A simple file edit does not need a 1M-token reasoning model. A small documentation update does not need deep architectural reasoning. But a complex refactor, production bug, or cross-service feature may justify a stronger model.

A practical model-selection strategy looks like this:

| Task | Recommended model type | |----|----| | Small file edits | Low-cost / fast model | | Simple unit tests | Low-cost / mid-tier model | | Documentation drafts | Low-cost / mid-tier model | | Jira ticket creation | Low-cost model | | Code explanation | Mid-tier model | | Bug investigation | Strong reasoning model | | Architecture review | Strong reasoning model | | Major refactor | Strong model with large context | | Security review | Strong reasoning model | | Final code review | Strong reasoning model |

This is where model switching becomes important.

For example, DeepSeek’s own documentation describes DeepSeek-V4-Flash as faster and cost-effective, with reasoning capabilities close to V4-Pro and strong performance on simple agent tasks. That makes it a reasonable choice for routine development tasks, while V4-Pro is more suitable for complex planning and deeper reasoning.

Similarly, Anthropic’s Claude Opus 4.6 supports a 1M-token context window, but Anthropic also notes premium pricing for prompts over 200k tokens. That kind of model can be valuable for large codebase analysis, but it should not be used casually for every small task.

OpenAI’s current API pricing also shows the cost difference between frontier models and smaller models. For example, GPT-5.5 is listed at $5 per million input tokens and $30 per million output tokens, making it a strong but expensive option for complex coding and professional work.

A cost-efficient AI workflow for developers

A very effective workflow is:

Step 1: Use a strong model for planning

Use a high-capability model when the task needs deep understanding.

Example:

Use deep reasoning. Analyze the full feature requirement and current codebase. Create an implementation plan, but do not modify files.

This is where large-context models are useful. They can scan more of the repository and produce a better plan.

Step 2: Switch to a cheaper model for implementation

Once the plan is clear, many implementation steps are mechanical.

Example:

Follow the approved implementation plan. Make only the file changes listed. Do not redesign the solution.

A cheaper or faster model can often handle this well.

Step 3: Switch back to a strong model for code review

After implementation, use a stronger model again to review the code.

Example:

Review the changes from multiple perspectives:
1. Principal engineer
2. Security engineer
3. Performance engineer
4. QA engineer
5. Production support engineer

Find bugs, missed edge cases, unnecessary complexity, and test gaps.

This gives you the value of strong reasoning where it matters most: design and review.

Prompt optimization: how to reduce token waste

Tokens are consumed by input and output. Long prompts, pasted files, repeated context, and verbose responses all increase cost.

Here are practical ways to optimize.

1. Ask for a plan before code

Do not start with:

Implement this feature.

Use:

Analyze first. Do not edit files. Create a concise implementation plan with impacted files and risks.

This avoids unnecessary edits and rework.

2. Limit the scope

Bad prompt:

Review my whole codebase and fix everything.

Better prompt:

Review only the authentication flow related to these files:
- auth.service.ts
- login.component.ts
- session-manager.ts

Focus on token expiration, refresh behavior, and security edge cases.

A smaller scope reduces cost and improves accuracy.

3. Ask for concise output

Bad prompt:

Explain everything in detail.

Better prompt:

Give a concise answer. Limit the response to:
1. Summary
2. Files to change
3. Risks
4. Test cases

Long AI explanations can waste tokens quickly.

4. Reuse context instead of repeating everything

If your CLI supports project memory, rules files, or saved instructions, use them.

Instead of pasting coding standards every time, store stable rules like:

Use existing patterns. \n Do not introduce dependencies without approval. \n Prefer small changes. \n Write unit tests. \n Follow project lint rules. \n Do not modify unrelated files.

This reduces repeated prompt size.

5. Use file references instead of pasting large files

In repo-aware tools, ask AI to inspect files directly rather than pasting entire file contents.

Example:

Inspect the existing implementation in the auth module and summarize only the relevant files before proposing changes.

This lets the tool retrieve targeted context instead of forcing every prompt to include large pasted content.

6. Ask multiple related questions in one request when billing is request-based

Some tools or plans count usage by request rather than directly by token, although this is changing in several platforms.

For request-based tools, it can be more efficient to combine related questions into one well-structured prompt.

Example:

Analyze this implementation and answer the following in one response:
1. Is the architecture correct?
2. Are there security issues?
3. Are there edge cases missing?
4. Are the unit tests sufficient?
5. What should be changed before PR approval?

This is better than sending five separate prompts.

However, as billing shifts toward token-based usage, concise prompting and model selection become even more important.

Example: inefficient vs optimized prompting

Inefficient prompt

Here is my whole codebase. Please understand everything and implement the new payment validation feature. Also write tests and documentation.

Problems:

Too broad \n Expensive \n Hard to review \n High chance of unrelated changes \n No staged approval \n No control over architecture

Optimized prompt

We need to add payment validation for corporate users.

Step 1 only: Analyze the requirement and existing payment-related code.
Do not modify files.

Return:
1. Relevant files
2. Current flow summary
3. Proposed design
4. Security risks
5. Edge cases
6. Test plan
7. Implementation steps

Keep the response concise.

Then:

Now implement only steps 1–3 from the approved plan.
Do not modify unrelated files.
Add unit tests for validation success, validation failure, missing input, and permission failure.

Then:

Review the diff as a security engineer and senior backend engineer.
Find bugs, missed edge cases, and unnecessary complexity.

This staged flow saves tokens, reduces risk, and improves code quality.

Real-world model strategy example

Here is a practical example of how a developer can use multiple model types in a single feature workflow.

| Development phase | Model choice | Why | |----|----|----| | Requirement analysis | Strong reasoning model | Needs broad thinking | | Architecture review | Strong reasoning model | Needs system-level judgment | | Implementation plan | Large-context model | Needs repo understanding | | Small code edits | Low-cost model | Mostly mechanical | | Unit test generation | Mid-tier model | Needs accuracy but not full reasoning | | Documentation | Low-cost model | Language-heavy, lower risk | | Code review | Strong reasoning model | Needs bug/security detection | | PR summary | Low-cost model | Simple summarization |

This approach gives the best balance between productivity and cost.

AI can increase productivity, but only with engineering discipline

AI coding tools can absolutely transform day-to-day development.

In my experience, they help most in:

Finding architectural gaps early \n Reducing time spent on boilerplate \n Creating better first-draft design docs \n Generating implementation plans \n Improving test coverage \n Reviewing code from multiple perspectives \n Speeding up debugging \n Reducing context-switching \n Improving documentation quality

But AI also introduces new engineering risks:

Developers may accept code they do not understand. \n Teams may merge code with hidden bugs. \n AI may create unnecessary abstractions. \n Costs may grow quickly. \n Developers may lose codebase context. \n Review cycles may slow down if authors cannot explain AI-written code.

The solution is not to avoid AI. The solution is to use AI with discipline.

My recommended rules for AI-assisted development

Use AI in every stage of development, not just coding.
Always ask for analysis and planning before implementation.
Keep the developer in control of architecture and final decisions.
Never merge code you cannot explain.
Use cheaper models for simple tasks.
Use stronger models for architecture, debugging, refactoring, and review.
Optimize prompts to reduce unnecessary token usage.
Review AI-generated code like you would review another developer’s code.
Challenge AI during review by asking it to think from different roles.
Treat AI as a productivity multiplier, not a replacement for engineering ownership.

Conclusion

AI tools are becoming a standard part of modern software engineering. Developers who learn how to use them effectively will move faster, think more broadly, and produce better first drafts of code, tests, and designs.

But the highest-performing developers will not be the ones who blindly delegate everything to AI.

They will be the ones who know:

When to use AI \n Which model to use \n How much context to provide \n How to optimize prompts \n How to review AI-generated code \n How to keep ownership of the system

AI can make developers 10x more productive, but only when combined with human judgment, architecture knowledge, security awareness, and responsible usage.

The future of development is not AI replacing developers.

It is developers who know how to work with AI becoming dramatically more effective than those who do not.