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Hacker News - Newest: "AI"

AI can't read an investor deck AI as an attorney? Student uses ChatGPT, Gemini to sue UW over alleged racial discrimination Hacking MCP Servers in AI Systems – The Rug Pull: Tool Changes After Approval GitHub - MeepCastana/KubeezCut: Free Web based video editor GitHub - GenAI-Gurus/awesome-eu-ai-act: Curated tools, official sources, OSS, templates, and guides for EU AI Act compliance. Can AI judge journalism? A Thiel-backed startup says yes, even if it risks chilling whistleblowers Coming soon: 10 Things That Matter in AI Right Now DARPA built an AI to fact-check enemy weapons claims What explains heterogeneity in AI adoption? When AI Meets Muscle: Context-Aware Electrical Stimulation Promises a New Way to Guide Human Movements - Department of Computer Science AI Changed How We Build. It Did Not Change What Matters. Linux rules on using AI-generated code - Copilot is OK, but humans must take 'full responsibility for the… Meta spins up AI version of Mark Zuckerberg to engage with employees Code Mode: Let Your AI Write Programs, Not Just Call Tools | TanStack Blog GitHub - Delavalom/graft: Go framework for building AI agents. Type-safe tools, multi-provider (OpenAI, Anthropic, Gemini, Bedrock), zero vendor SDKs. India's TCS tops estimates, says new AI models did not dent services demand Gen Z's fading AI hype Strong feeling: we are in a folded AI reality GitHub - machinarii/total-recall-catalog: A reference catalog of latest knowledge retrieval, memory & RAG systems GitHub - mensfeld/code-on-incus: Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops threats automatically.. Quantization, LoRA, and the 8% Problem: Benchmarking Local LLMs for Production AI Iran war: We spoke to the man making Lego-style AI videos that experts say are powerful propaganda Powell, Bessent discussed Anthropic's Mythos AI cyber threat with major U.S. banks GitHub - immartian/bellamem: Persistent belief-graph memory for AI agents. Retrieves decisive context by importance — not recency, not RAG, not /compact. recursive-mode: The Repo-Native Operating System for AI Engineering After the attack on Sam Altman's home, will AI CEO's go on the offensive? The biggest advance in AI since the LLM Opus 4.6 vs GPT 5.4 One Prompt Unity World Generation Test “AI polls” are fake polls Client Challenge Can AI be a 'child of God'? Inside Anthropic's meeting with Christian leaders How to Switch AI Chatbots and Why You Might Want To GitHub - MattMessinger1/agentic_refund_guardrail: Safe refund policy layer for AI agents — Python + TypeScript. Same behavior, shared tests. Adam/papers/emergent_values_whitepaper.md at master · strangeadvancedmarketing/Adam Ask HN: How do you stop playing 20 questions with your AI coding tools How far can automation and AI support psychotherapy? - @theU GitHub - stagas/rtdiff: realtime git diff gui and AI-assisted commits A Mac Studio for Local AI — 6 Months Later A History of the Early Years of AI at the University of Edinburgh Why AI Coding Tools Still Feel Stuck on Localhost MSN AI Datacenters Are Becoming Strategic Targets twitter.com Penn Researchers Use AI to Surface Unreported GLP-1 Side Effects in Reddit Posts Show HN: MoodSense AI (ML and FastAPI and Gradio, Deployed on Hugging Face) Moodsense Ai - a Hugging Face Space by aman179102 AI models are terrible at betting on soccer—especially xAI Grok GitHub - xialeistudio/echoic GitHub - HimashaHerath/github-dev-wrapped: AI-powered weekly GitHub activity reports deployed to GitHub Pages GitHub - alejandrobalderas/claude-code-from-source: Architecture, patterns & internals of Anthropic's AI coding agent — reverse-engineered from source maps AI and Tech brief: Ireland ascendant GitHub - Titovilal/context0: Context0 - Never Surrender Training for a Marathon with an AI Coach: What Worked and What Didn't Cyber Pulse: Agentic Intel - Apps on Google Play I Built an AI PR Reviewer That Catches Bugs by Not Looking for Bugs Gen Z workers are so fearful AI will take their job they’re intentionally sabotaging their company’s AI rollout | Fortune How AI Is Reimagining the Game of Golf–For Both Players and Courses GitHub - nattergabriel/reseed: A CLI tool for managing and distributing agent skills across projects Is SVG the final frontier? My AI workflow evolved from prompts to a near-autonomous workflow MLSharp Help - 3DGS Viewer & Generator I put my cognitive field based AI's runtime on GitHub Is Numble the first AI-proof game? A3: Kubernetes for autonomous AI agent fleets | Emergent Principles Deepali Vyas ("The Elite Recruiter") GitHub - msmarkgu/RelayFreeLLM: A restful API designed to route user prompts to various AI model providers. Unionized ProPublica staff are on strike over AI, layoffs, and wages Unleashing the Advantage of Quantum AI We're heading for an AI-fueled 'dementia crisis,' brain scientist warns The AI-Assisted Breach of Mexico's Government Infrastructure [pdf] GitHub - stef41/lmscan: 🔍 Detect AI-generated text and fingerprint which LLM wrote it. Open-source GPTZero alternative. Zero dependencies, works offline. MSN GitHub - visionscaper/collabmem: Enabling long-term collaboration with Agentic AI - building up episodic and world model memory over time with in-context awareness We gave an AI a 3 year retail lease in SF and asked it to make a profit | Andon Labs AI Code is Hollowing Out Open Source, and Maintainers are Looking the Other Way What leaked "SteamGPT" files could mean for the PC gaming platform's use of AI AI is the boss at this retail store. What could go wrong? GitHub - Wuzu11517/agentic-proxy: Local proxy meant to help reduce With Drones, Geophysics and ArtificiaI Intelligence, Researchers Prepare to Do Battle Against Land Mines A Single Operator, Two AI Platforms, Nine Government Agencies: The Full Technical Report 在 Steam 上购买 FriedrichAI: Offline AI 立省 10% GitHub - inevolin/resume-cli: Hit Claude usage limits? Resume any AI coding session elsewhere. Switch tools at zero friction. GitHub - atripati/ark: AI Runtime Kernel — a context operating system for AI agents. Eliminates tool bloat, loads only what’s needed, and gives LLMs their reasoning space back. How to Build a Secure AI PR Reviewer with Claude, GitHub Actions, and JavaScript This Startup Wants You to Pay Up to Talk With AI Versions of Human Experts Intel Arc Pro B70 Brings 32GB VRAM to Local AI for $949 WordPress 7.0: The Good, the AI, and the Still Missing AI on the couch: Anthropic gives Claude 20 hours of psychiatry IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures AI Agents Know About Supabase. They Don't Always Use It Right. The history and future of AI at Google, with Sundar Pichai Inside an AI‑enabled device code phishing campaign How Meta Used AI to Map Tribal Knowledge in Large-Scale Data Pipelines AI for Systems: Using LLMs to Optimize Database Query Execution Forecasting the Economic Effects of AI Introducing Tinker: Play with AI, bring your ideas to life AI sheds light on an ancient gaming mystery People really hate AI but not as much as Iran—or Democrats | Fortune What is an AI Product Engineer? Phoebe Gates wants her $185 million AI startup to succeed with 'no ties to my privilege or my last name': 'I have a chip on my shoulder' | Fortune
AI doesn't divide developers — it just reveals them
fred1268 · 2026-05-23 · via Hacker News - Newest: "AI"

If there’s one topic guaranteed to split a room full of developers, it’s AI. On one side, the enthusiasts — convinced this is the next major shift in computing, eager to tell you about it. On the other, the skeptics — equally convinced it’s a hype cycle that will quietly deflate like the ones before it.

The polarization is real and surprisingly sharp. But I think its root is deeper than people realize — and it has very little to do with AI itself.

Two kinds of love#

To understand the divide, it helps to think about what software development really involves. There are, at its core, two things going on at once.

There’s the journey: everything required to make the software — the architecture decisions, the algorithms, the debugging sessions, the refactoring, the craft of turning a vague idea into something that actually runs.

And there’s the destination: the finished product itself — the thing users touch, the problem you set out to solve, the value that ends up in someone’s hands.

Every developer who chose this profession loves both. Just in different proportions.

Destination-oriented developers tend to be more product-minded. They intuitively sense which features are missing, which ones nobody will ever use, which flows feel wrong. They’re drawn to simplicity — not because simple is easy, but because they understand that simplicity is what makes great products. The code is the means; the product is the point.

Journey-oriented developers lean the other way. They gravitate toward the algorithmic, the architectural, the elegant. They’ll spend an afternoon finding the right abstraction, the cleaner interface, the approach that makes the next developer’s life easier. The product validates the work; the work is the pleasure.

What AI actually does#

When you look at what AI brings to software development, one thing stands out: it dramatically shrinks the journey while accelerating arrival at the destination. A feature that once required hours of design thinking, careful implementation, and iterative refinement can now materialize in minutes. And if you want more destinations — more features, more products, more creative possibilities — AI removes the technical friction that once stood between the idea and the thing.

Seen through this lens, the polarization almost explains itself.

Developers who love the destination are thrilled. More output, more speed, more latitude. The constraints that slowed them down — the boilerplate, the obscure APIs, the mechanical work — are largely gone. AI is their answer.

Journey-oriented developers feel something closer to loss. What AI took from them isn’t the output — it’s the path. And often the path it chose isn’t the one they would have taken. It works, but it doesn’t feel elegant. It’s not theirs. As I explored in Why I code: it was never about the output, programming was always an intellectual game — the output was just proof that you’d played it well. When the game is handed to an AI, supervision is what’s left. And supervision was never the point.

A spectrum, not a binary#

None of this is black and white. Most developers love both the journey and the destination — the question is which one they love more. And when the gap is wide enough, they end up firmly in one camp.

Here’s a question worth sitting with: do you take more pleasure in designing a product, or in building one? And yes, I’m using two different words deliberately. Designing means thinking through what something should be — its shape, its behavior, its reason for existing. Building means making it happen — writing the code, assembling the pieces, watching it come to life. Both are part of software development, but they are not the same pleasure.

Your answer is probably a decent predictor of your relationship with AI.

Self-knowledge as navigation#

There’s no virtue in preferring the journey over the destination, or the other way around. Both kinds of developers are necessary. Both build great software.

But knowing which you are can change how you navigate what AI is doing to the profession. If you love the destination, you likely already feel liberated. If you love the journey, there are two paths worth considering.

One is to let the disruption be an invitation — maybe AI freeing you from the mechanical work leaves more room to appreciate the product, the user, the outcome. Maybe there’s more destination-love in you than you thought. The other, more natural instinct, is to seek out niches where AI can’t easily reach — problems complex enough, novel enough, or strange enough that the path still belongs to you.

Those niches exist. They’re real.

For now.