Rocketman @helloRocketMan

x.com/i/article/2010…

@AmirMushich How did you create this vercel animation?

@johnvirality Rizz

In a recent batch talk, YC General Partner @t_blom broke down how to build a self-improving, AI-native company. He walks through how to create recursive, self-improving AI loops, and why founders who get this right will run companies that improve while they sleep. 00:00 — Companies Are Roman Legions 00:54 — Copilots Are the Wrong Mental Model 01:55 — Extract the Domain Knowledge 02:24 — The Recursive Self-Improving Loop 04:12 — The Holy Shit Moment at YC 05:50 — Self-Optimizing Product and Support Loops 06:29 — Burn Tokens, Not Headcount 07:23 — Middle Management Is Over 08:05 — Make Everything Legible to AI 09:40 — Regenerating the YC User Manual 11:19 — Software Is Ephemeral, Context Is Valuable 12:18 — Where Humans Still Matter

This is how I got 1M users in 6 months Finally dropping it! It's 60 pages lol tally.so/r/BzZpA4 If you repost & follow, I'll send you some extra sauce🌶️

@damnGruz Looking forward to test it! When will it be available in Germany?

@jasonzhou1993 ✌🏻

@borjafat Skill

Researchers just mathematically proved AI layoffs will destroy the economy. Using game theory, two economists from UPenn and Boston University mathematically proved something uncomfortable. Every company replacing staff with AI is also firing its own customers. Laid-off workers stop spending. Revenue collapses across every sector. Yet no firm can stop. If they don't automate, rivals cut prices and steal market share. So everyone automates, knowing it ends badly for all of them. The researchers tested every proposed fix: > Universal basic income fails > Capital taxes fail > Profit sharing falls short > Collective bargaining can't hold Only one mechanism works. A per-task automation tax that forces firms to price in the demand they destroy. The context is already grim. Over 100,000 tech jobs vanished last year, with AI cited in most. The math says the cycle won't break on its own.

Introducing Tolaria! 💧 Today I am releasing a macOS desktop app for managing markdown knowledge bases, and helping both AI and humans operate them. It’s free and open source, and always will be. I have been working on it for three months, and I now use it to run my life and work. I personally have a massive workspace of 10,000 notes — the result of 6 years of Refactoring — which I now operate on Tolaria. Tolaria is the main collaboration surface with my AI agents: they create new notes there, connect them to what exists, and edit existing ones. Everything is easy to understand for them, because it’s just markdown files. In a way, it’s my implementation of @karpathy's LLM wiki. Tolaria is also the biggest experiment I have ever run about writing software with AI: • 2000 commits • 100K+ lines of code • 3000+ tests / 85% coverage • 9.9/10 code health • 70+ architecture decision records I am releasing it open source also to use it as a living artifact of how I do AI coding, so you can inspect at any time things like how I write docs, what's in my AGENTS file, what hooks do I run, and so on. You can find it below: • Newsletter announcement: refactoring.fm/p/introducing-… • Website: tolaria.md • Github repo: github.com/refactoringhq/… Let me know your thoughts!

@HeyGen Hyperframes

We built our launch video in Claude Code using HyperFrames. Now it's yours. Open source, agent-native framework. HTML to MP4. $ npx skills add heygen-com/hyperframes RT + Comment "HyperFrames" to get the full source code of this launch video (must follow)

@mikefutia Improve

This application is open source. Here is the link: github.com/KartikLabhshet…

Kartik @code_kartik

5 months ago

CleanShot X is great. The subscription isn’t. So I built Better Shot an open-source, native macOS screenshot tool using Tauri + Rust. Fast. Local. Free forever. Try it → bettershot.site Source code included. No bullshit.

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@Zephyr_hg Gamma

@tomcrawshaw01 MCP

@free_ai_guides Alex

@felixhhaas ui library

@OfficialLoganK @GoogleAIStudio Already using for prototyping recently

the old way of scaling teams is dead: we used to hire specialists – designers, engineers, PMs – each in their lane, scaling by adding more people. but when Cursor can take you from idea to code in minutes, execution isn't the bottleneck anymore. taste and judgment are. what matters now: people who can see the full stack, move between layers, but specialize deeply in something AI can't replicate yet. T-shaped but way wider – conversant across domains, expert in one thing. AI doesn't just make you faster. it ties teams together differently. no more waterfall – designer codes the prototype, engineer extends it, both work in the same medium. the gap between disciplines disappears. this raises individual ceilings. i'm a designer who built ryOS entirely in Cursor – couldn't have done that before. but i'm not replacing engineers, i'm just removing execution barriers while keeping my design taste and systems thinking. you're not hiring for roles anymore. you're hiring for breadth + depth, taste, systems thinking, learning velocity. 5 people who can work across code/design/product beat 20 specialists coordinating handoffs. the new bottlenecks are deeply human: taste, vision, judgment, context. AI explores options, but can't tell you which is right. that's where specialization matters now – in judgment, not execution. small teams, fluid boundaries, everyone working in the same tools. roles still matter but as overlapping concerns with different depths, not separate silos. tools handle execution, you handle vision. this is what we're building at Cursor – closing the gap between idea and reality. so your taste becomes the main thing, and teams have more freedom to explore crazy ideas.