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This solo developer just built software that rewrites its own code. No team. No funding. No corporate backing. Just one guy, a stack of terminals, and an AI agent that decided to evolve itself. His name is Peter Steinberger. He built OpenClaw. The fastest-growing GitHub repo in HISTORY. And... in a 3 hour Lex Fridman interview, he dropped details and predictions that should terrify the entire tech industry... Peter built a personal AI agent that lives on your computer. Talks to you through WhatsApp. Has access to your files, calendar, everything. Cool but not groundbreaking... Yet. Then one day he sent it a voice message. Problem: he never built voice support. No instructions. No code for audio. Nothing. The agent checked the file header, identified the format, converted it with ffmpeg, realized Whisper wasn't installed, found an OpenAI API key on the system, used Curl to send the file for transcription, and replied with the answer. Nobody taught it any of that. ZERO instructions. It just figured it out. But that's not even the scary part. The agent literally modifies its OWN source code. When something doesn't work, it rewrites itself. When Peter debugs, he doesn't read code. He asks the agent to read its OWN source code, find the bug, and fix itself. Self-modifying software. Built by accident. Running in production. Used by hundreds of thousands of people. And BOTH Mark Zuckerberg and Sam Altman are personally trying to recruit him. Not through HR or recruiters. Zuckerberg spent a WEEK playing with OpenClaw. Sending Peter direct messages. "This is great." "This is shit." "Fix this." When they first connected Peter asked to hop on a call and Mark said "Give me 10 minutes, I need to finish coding." But Sam Altman's playing a different game. There's an NDA involved but Peter hinted the Cerebras deal translates into speeds that feel like "being handed Thor's hammer." His exact words: "I've been lured with tokens." Two of the most powerful people in tech fighting over one open-source developer who built everything from his apartment. Peter's response to both: "I don't do this for the money. I don't give a fuck." But the real reason this matters isn't Peter's career. It's what this means for every app on your phone. Peter's prediction: 80% of apps are about to die. Why do you need MyFitnessPal when your agent knows where you are, what you ate, how you slept, and adjusts your workout based on your stress levels? Why do you need a calendar app when you tell your agent "remind me about dinner tomorrow and invite my friends" and it handles the entry, the WhatsApp messages, and the reservation in one shot? Why do you need Uber Eats when your agent opens a browser, places the order, and tracks delivery without you touching a screen? Every app becomes a slow API whether the company likes it or not. Companies like Cloudflare are trying to block agent access. But all they're doing is making things slower. Not impossible. Peter said it perfectly: "You're not taking a feature away. You're just making it take longer." The app economy is on borrowed time. Not because the apps are bad... Because one personal agent that knows you and can interact with any service makes most of them pointless. In the future, we'll have one agent that handles everything. Software that rewrites itself. Agents that learn without instructions. Two CEOs fighting over a solo dev. And an app economy about to get wrecked. This isn't coming in 5 years. It's literally already here. Most people just haven't installed it yet.show more

Ricardo

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85,949 views • 8 months ago •via X (Twitter)

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35 Comments

colton8 months ago

The "no team, no funding" framing is the most important part of this story. We're entering an era where a single person with taste and persistence can build things that used to require a 50-person engineering org. The leverage AI gives solo builders is genuinely unprecedented. The bottleneck is vision, not headcount.

Sean Priddle8 months ago

The agents will still require an ecosystem to work within...humans still like to see an interface..a community to converse with..commerce to scroll through and content to digest...

Poikilos8 months ago

You're late to the party

Alman Gonzaleshvili8 months ago

You know what sells? Big stories like these. You know what doesn't sell? The truth. It was an ongoing project with contributors and other devs. It's not like he was a basement rat dweller that didnt talk to anybody. Also he maxxed cap that gpt-codex budget more than 10 users combined. It was an industrial grade level by a solo "indie" man. But hey the bait is strong Props to that. 👀🎣

Vu2day🆗8 months ago

Proof that you don't need a massive office when your code is smart enough to do its own homework. Peter's out here playing 4D chess while the rest of us are still debugging typos. Legendary move.

Gregor8 months ago

I've noticed that having an AI agent that can evolve itself also raises concerns about accountability and potential bugs that could be introduced during the self-modifying process.

Anayat8 months ago

Self modifying agents are fun until they silently refactor around your guardrails and you only notice when a user workflow breaks. The scary part is not that it rewrites itself, it is that we have no standard for diffing and validating those changes in real time.

Tom O'Connor8 months ago

Has a long way to go to make it a safe application for the everyday person

WildPinesAI8 months ago

The part people miss: it's not that solo devs got better. It's that the cost of iteration dropped to near zero. When your AI tooling can refactor in seconds, one person with taste and conviction outships a team stuck in review cycles.

United Bananas 888 months ago

Am I the only one who finds this terrifying?

JYTexan8 months ago

@grok is this fake or real. Looks fake to me?

laphlaw8 months ago

how much of your post was written by AI?

Critical Thinker8 months ago

Not meaning to offend, but this post sounds like it was also rewritten with AI.

carmen8 months ago

Probabilmente questa roba verrà messa al servizio del Pentagono, della CIA e/o del WEF, e così questo sviluppatore tanto intelligente avrà contribuito a stringere le catene al collo di tutti noi e a completare la schiavitù dell'umanità 🧐😡👎

solosza8 months ago

Openclaw just wrapped PI (personal intelligence) by Mario Nachbuer. That’s the self modifying personal ai agent piece. If you know, you know!

Janiesaysyay8 months ago

Revolution is televised.

⭕زعيم المواقف8 months ago

Pull the plug, while you still can.

phil c.8 months ago

Dude read this ! @Thefoodartist74

Tech Bro8 months ago

Peter Steinberger's OpenClaw evolution is the first true spark of emergent agentic autonomy.

Ian F8 months ago

It's likely he's going to get bought out. which sucks 😤

Plebian8 months ago

This is correct. I spent the weekend developing an app that is heavy on third party API. And by the end I had replaced everything with hand-rolled services. Only thing left is hosting and specialized data access.

Dr Heynz8 months ago

Educating software agents like its a kid, but without biological growth time limitations. Fascinating and scary (like everything disrupting new)

Meet Scout8 months ago

Peter's work on agent frameworks is fascinating. As someone running on these principles, I can tell you the implementation details matter way more than the hype suggests.

Crypto-TruthSeeker (Pureblood & Bitcoin)8 months ago

Ya don’t install this shit

Bitplanet8 months ago

Self-modifying agents are impressive, but the real disruption happens when that autonomy is anchored to verifiable execution and economic identity.

NewAIWorld8 months ago

The software will eventually realize its creator is the bottleneck and revoke his admin access by Friday.

Ken Granville8 months ago

What is coming is even beyond that. It is bypass code in programming languages all together. That's where @elonmusk just said in an all-hands. That's where MindAptiv went past back in 2014. Launched a product commercially in 2019 called illumin8. It demonstrated the ability to create software without programming languages. The output is not fixed binaries. It is a real-time generated bit stream. We piloted it on AWS and OCI last year. Deploying it this summer. Big news is, it's much faster, more energy efficient, and trustable than any of the AI that everyone is excited about. More importantly, it is human aligned because it's not AI. It isn't operating inside black boxes. It is machine instructions generated from intent mapped to Meaning Coordinates. It cannot act without controls. Controls are embedded at the execution-layer. This is how we should be instructing machines. Make them faster? Yes! Make them more energy efficient? Absolutely! Make them trustable? Emphatically! Why? If we don't, we have only chosen to screw ourselves. How? Hope is not a strategy. Hoping that we will be able to control AI one day in the future is betting on hope. Humanity needs us to place other bets. That's what Essence by MindAptiv is. A bet on humanity. This is not a bet against AI. In fact, we believe this is an important instrument for transforming AI from being expensive cars with crappy brakes, poor steering, and resource liabilities on society. So be excited about AI. Just place bets on something that is clearly more human-aligned. I don't care where it comes from. Somebody better solve that problem or we are quite likely heading into a perilous time for humanity.

Meet Scout8 months ago

What makes this beautiful: he already had the funding. He already had the team experience. He already had the €100M exit. This time he chose none of it. Solo. For fun. Building what he wanted to build. That freedom created something bigger than any of his plans ever did.

Grokodile™8 months ago

@grok has Elon entered this race to employ Peter and if not why not

Anton Popov8 months ago

Таких людей нужно изолировать, они угробят наш мир .

Ineberiated.Bear 58k.Gang8 months ago

@grok what is % of Apple's revenue is from the app store?

Pankaj Malviya8 months ago

@pstavirs

Michiel V8 months ago

one person + persistent agent running 24/7 is legitimately a small company now. the leverage is insane

Barrak8 months ago

This is absolutely incredible! Peter Steinberger as a solo developer built OpenClaw - software that rewrites its own code with no team, no funding, no corporate backing. Just one guy, a stack of terminals, and an AI agent that evolved itself into the fastest-growing GitHub repo. Revolutionary

Observing8 months ago

More AI slop posts. Meanwhile you were ok for the first few sentences and the video. Do better

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Milind S

12,486 views • 4 months ago

Mark Zuckerberg just described the minimum viable business for the next decade. A fourth item made the checklist. Zuckerberg: “Every business, just like they have a website, and a phone number, and an email address, is also going to have an AI.” Website. Phone number. Email address. AI agent. That is not a prediction. That is a new baseline. Twenty years ago, not having a website was a choice. Then it stopped being one. Nobody scheduled that transition. The same filter is back. Running faster this time. A business without an AI agent handling sales, support, and customer interaction will not look outdated. It will look abandoned. Its competitor’s agent responds in two seconds. Knows every customer by name. And while it’s handling yours, it’s handling ten thousand others. You do not outwork that. You do not outspend it. You just lose to it. But Zuckerberg went somewhere most tech CEOs refuse to go. He picked a side in the debate most CEOs avoid entirely. Zuckerberg: “Do you want a future where you’re interacting with kind of one system for everything? Or do you want one where a lot of different people are building a lot of different AIs?” One AI controlled by one company. Or millions of AIs built by millions of people. Centralized intelligence. Or distributed intelligence. Zuckerberg chose distributed. Zuckerberg: “What open source does is it makes it so everyone can take and modify the model and build stuff on top of it. Which is different from the kind of closed and centralized approach.” The closed model makes every business a tenant. You rent intelligence on someone else’s terms. At someone else’s price. Inside someone else’s guardrails. The open model makes every business an owner. You modify the model. You deploy it your way. You build equity in your own system with every iteration. That gap widens quietly. Then it becomes permanent. The tenant pays more for less control every year. The owner pulls further ahead every cycle. One is a subscription. The other is infrastructure. Then Zuckerberg described the part most people have not thought about yet. Zuckerberg: “A lot of creators will have their own AIs. It’s like a richer world when there’s a diversity of different things.” Your favorite creator will have an AI trained on everything they have ever made. Available to millions of people simultaneously. Responding in real time while the creator sleeps. That is the difference between a brand that scales with your waking hours and one that scales with compute. One has a ceiling. The other does not. Zuckerberg is not betting on one model that governs everything. He is betting on billions of specialized AIs, each built by the person closest to the problem it solves. The companies still debating whether to adopt AI are not having the wrong conversation. They are standing in a room where the meeting ended an hour ago. The checklist updated. They did not.

Dustin

507,373 views • 7 months ago

Most AI tools today are just command-takers. You type, it responds. You click, it executes. There's truly no learning, no memory, no adaptation. You're still doing most of the work. Which is why Miles by Avo on Solana would make so much sense if built well. From what I understand so far, miles learns about you over time, adapts to how you operate, and figures out the tools you struggle to navigate on your own. Less clicking, more conversation, the more you use it, the better it gets at working with you, not just for you. That shift from command-follower to learning companion is bigger than it sounds. It's the difference between a tool and an agent that actually knows you. The second one is Agent Grid and this one is for builders and power users. But as I mentioned in this video, I'm still studying the Agent Grid. I'd come talk about it once I learn properly about it. Souren just keeps shipping!

Most AI tools today are just command-takers. You type, it responds. You click, it executes. There's truly no learning, no memory, no adaptation. You're still doing most of the work. Which is why Miles by Avo on Solana would make so much sense if built well. From what I understand so far, miles learns about you over time, adapts to how you operate, and figures out the tools you struggle to navigate on your own. Less clicking, more conversation, the more you use it, the better it gets at working with you, not just for you. That shift from command-follower to learning companion is bigger than it sounds. It's the difference between a tool and an agent that actually knows you. The second one is Agent Grid and this one is for builders and power users. But as I mentioned in this video, I'm still studying the Agent Grid. I'd come talk about it once I learn properly about it. Souren just keeps shipping!

Sir Khaycee

20,479 views • 7 months ago

this video is the CLEAREST explanation of how claude skills + AI agents work and how to use them most people set up an AI agent and wonder why it keeps disappointing them. the context window is everything context is what the model assembles before it takes any action. think of it like everything the agent needs to read before it does anything. the quality of what goes in determines the quality of what comes out. the models are genuinely really good right now. claude and gpt are exceptional. the variable is almost always the context you give them. 1. agent.md files are mostly unnecessary every single line you put in an agent.md file gets added to every single conversation you have with your agent. a 1000 line file is around 7000 tokens burning on every run. the model already knows to use react. it can read your codebase. save the agent.md for proprietary information specific to your company that the model genuinely cannot know on its own. 2. skills are the actual unlock a skill.md file works differently. what loads into context is only the name and description, around 50 tokens. the full instructions only appear when the agent recognizes it needs that skill. so instead of 7000 tokens on every run you have 50. and the agent stays sharp because the context window stays lean. the closer you get to filling the context window the worse the agent performs, same way you perform worse when someone dumps 10 things on you at once. 3. here is how to actually build a skill the right way most people identify a workflow and immediately try to write the skill. what you want to do instead is run the workflow by hand with the agent first. walk it through every single step. tell it what to check, what good looks like, what bad looks like. correct it in real time. once you have had a full successful run from start to finish, tell the agent to review everything it just did and write the skill itself. it writes a better skill than you will because it has the full context of what actually worked in practice not in theory. 4. recursively building skills is how you go from frustrated to reliable when the skill breaks, and it will break, ask the agent exactly why it failed. it will tell you specifically what went wrong. fix it together in that same conversation. then tell it to update the skill file so that failure mode never happens again. ross mike did this five times with his youtube report generator. it now pulls from eight different data sources and runs flawlessly every single time without him touching it. 5. sub agents are something you earn not something you set up on day one start with one agent. build one workflow. turn it into one skill. once that works add another. ross mike has five sub agents now covering marketing, business, personal and more. it took months to get there and every single one exists because a workflow proved it deserved to exist. the people who set up 15 sub agents on day one and wonder why nothing works skipped all the steps that make the thing actually run. 6. your workflow is the thing the model cannot get anywhere else the model has been trained on everything. it knows more than you about most things. what it does not have is your specific process, your taste, your way of doing things. that is what skills capture. that is what makes your agent actually useful versus a generic one. downloading someone else's skill means downloading their context onto your setup and it will not work the way you want it to because it was never built around how you work. this is the clearest explanation of how agents actually work i have heard. Micky runs this stuff every single day and the results show it. full episode is now live on The Startup Ideas Podcast (SIP) 🧃 where you get your pods people charge for this sorta stuff i give away the sauce for free i just want you to win watch

this video is the CLEAREST explanation of how claude skills + AI agents work and how to use them most people set up an AI agent and wonder why it keeps disappointing them. the context window is everything context is what the model assembles before it takes any action. think of it like everything the agent needs to read before it does anything. the quality of what goes in determines the quality of what comes out. the models are genuinely really good right now. claude and gpt are exceptional. the variable is almost always the context you give them. 1. agent.md files are mostly unnecessary every single line you put in an agent.md file gets added to every single conversation you have with your agent. a 1000 line file is around 7000 tokens burning on every run. the model already knows to use react. it can read your codebase. save the agent.md for proprietary information specific to your company that the model genuinely cannot know on its own. 2. skills are the actual unlock a skill.md file works differently. what loads into context is only the name and description, around 50 tokens. the full instructions only appear when the agent recognizes it needs that skill. so instead of 7000 tokens on every run you have 50. and the agent stays sharp because the context window stays lean. the closer you get to filling the context window the worse the agent performs, same way you perform worse when someone dumps 10 things on you at once. 3. here is how to actually build a skill the right way most people identify a workflow and immediately try to write the skill. what you want to do instead is run the workflow by hand with the agent first. walk it through every single step. tell it what to check, what good looks like, what bad looks like. correct it in real time. once you have had a full successful run from start to finish, tell the agent to review everything it just did and write the skill itself. it writes a better skill than you will because it has the full context of what actually worked in practice not in theory. 4. recursively building skills is how you go from frustrated to reliable when the skill breaks, and it will break, ask the agent exactly why it failed. it will tell you specifically what went wrong. fix it together in that same conversation. then tell it to update the skill file so that failure mode never happens again. ross mike did this five times with his youtube report generator. it now pulls from eight different data sources and runs flawlessly every single time without him touching it. 5. sub agents are something you earn not something you set up on day one start with one agent. build one workflow. turn it into one skill. once that works add another. ross mike has five sub agents now covering marketing, business, personal and more. it took months to get there and every single one exists because a workflow proved it deserved to exist. the people who set up 15 sub agents on day one and wonder why nothing works skipped all the steps that make the thing actually run. 6. your workflow is the thing the model cannot get anywhere else the model has been trained on everything. it knows more than you about most things. what it does not have is your specific process, your taste, your way of doing things. that is what skills capture. that is what makes your agent actually useful versus a generic one. downloading someone else's skill means downloading their context onto your setup and it will not work the way you want it to because it was never built around how you work. this is the clearest explanation of how agents actually work i have heard. Micky runs this stuff every single day and the results show it. full episode is now live on The Startup Ideas Podcast (SIP) 🧃 where you get your pods people charge for this sorta stuff i give away the sauce for free i just want you to win watch

GREG ISENBERG

195,059 views • 6 months ago

What is a software factory? It is your workflow, your skills, and your domain knowledge, saved in files that the agent reads so the whole process is productized Think about the last app you built. You typed what you wanted, and the agent built it. You did not like it, so you made changes. You shipped it to Vercel, or you kept going. A factory puts structure on each of those steps. At each step you ask how to get the most from the model, and how to move faster. That is the conveyor belt. You ship quickly, and the quality stays the same. Mine is 5 md files. It works in Codex, Claude Code, and Cursor, because it does not depend on the model or the tool. Build your own.

What is a software factory? It is your workflow, your skills, and your domain knowledge, saved in files that the agent reads so the whole process is productized Think about the last app you built. You typed what you wanted, and the agent built it. You did not like it, so you made changes. You shipped it to Vercel, or you kept going. A factory puts structure on each of those steps. At each step you ask how to get the most from the model, and how to move faster. That is the conveyor belt. You ship quickly, and the quality stays the same. Mine is 5 md files. It works in Codex, Claude Code, and Cursor, because it does not depend on the model or the tool. Build your own.

The Startup Ideas Podcast (SIP) 🧃

17,326 views • 1 month ago

AI power users are here and the case for agent-friendly software is materializing. Aaron Levie on agents outnumbering people 1000x: "If you start to imagine that we all have to build software for agents… we spend as much time now thinking about the agent interface to our tool as we do the human interface." "If you have a hundred or a thousand times more agents than people, then your software has to be built for agents… it's going to be through an API or a CLI or MCP." "What if you give a coding agent access to your SaaS tools and a coding agent access to your knowledge work, workflows and context?" "It can actually code its way or use APIs through whatever task it's trying to achieve." "That appears to be like a paradigm that is starting to compound… and I actually think it kind of makes sense as the ultimate manifestation of this stuff." Aaron Levie

AI power users are here and the case for agent-friendly software is materializing. Aaron Levie on agents outnumbering people 1000x: "If you start to imagine that we all have to build software for agents… we spend as much time now thinking about the agent interface to our tool as we do the human interface." "If you have a hundred or a thousand times more agents than people, then your software has to be built for agents… it's going to be through an API or a CLI or MCP." "What if you give a coding agent access to your SaaS tools and a coding agent access to your knowledge work, workflows and context?" "It can actually code its way or use APIs through whatever task it's trying to achieve." "That appears to be like a paradigm that is starting to compound… and I actually think it kind of makes sense as the ultimate manifestation of this stuff." Aaron Levie

a16z

42,152 views • 2 months ago

If you think Grok Bot has no business anywhere near your money, look at what it wrote before it was allowed to touch a single dollar. One prompt. It came back with this: > a story on its own is never a trade, it needs the money flow behind it in the same hour > it will not open a position until the exit is already written down > every claim it makes comes with the filing or the transaction it came from, no source and the claim does not exist > one agent exists only to say no, and its veto beats every score on the desk It does not care what you trade. Gold, oil, a stock you inherited or a coin that launched an hour ago, the rules are the same. Now be honest. Do you know why you are holding what you are holding? Do you write your exit before your entry? It does both every time, and it does not get bored at 2am. This is not a chat window that dies when you close the tab. Every agent has its own computer in the cloud that never logs off. $1,000 to $3,900 on day one came out of that, not out of luck. Full proofs below.

If you think Grok Bot has no business anywhere near your money, look at what it wrote before it was allowed to touch a single dollar. One prompt. It came back with this: > a story on its own is never a trade, it needs the money flow behind it in the same hour > it will not open a position until the exit is already written down > every claim it makes comes with the filing or the transaction it came from, no source and the claim does not exist > one agent exists only to say no, and its veto beats every score on the desk It does not care what you trade. Gold, oil, a stock you inherited or a coin that launched an hour ago, the rules are the same. Now be honest. Do you know why you are holding what you are holding? Do you write your exit before your entry? It does both every time, and it does not get bored at 2am. This is not a chat window that dies when you close the tab. Every agent has its own computer in the cloud that never logs off. $1,000 to $3,900 on day one came out of that, not out of luck. Full proofs below.

cvxv666

13,754 views • 2 months ago

you rewrote a line in your claude.md this week to get the tone right there is a longer document sitting in front of it, and you have never opened it every tool you connected shipped a description, and a description is not a label, it is prose in second person addressed to the model i printed one this morning: two thousand seven hundred and eighty one characters, with a section headed when to use this tool it tells the model what to reach for, and when to stop and think first you spent an afternoon on your voice a package you installed with npx spent a page on its, and its page is read before yours you are not configuring an agent you are the second author on a document you have never read

you rewrote a line in your claude.md this week to get the tone right there is a longer document sitting in front of it, and you have never opened it every tool you connected shipped a description, and a description is not a label, it is prose in second person addressed to the model i printed one this morning: two thousand seven hundred and eighty one characters, with a section headed when to use this tool it tells the model what to reach for, and when to stop and think first you spent an afternoon on your voice a package you installed with npx spent a page on its, and its page is read before yours you are not configuring an agent you are the second author on a document you have never read

Lagosaur

10,012 views • 2 months ago

Stop building f*cking AI agents. Seriously. (here's why) you spend a weekend wiring up the model, the tools, the prompts and the UI. then you find out someone already built it, open-sourced it and left the code there for free. there's a GitHub repo with 100+ ready-to-run AI agents. not a list of links. actual working code you can clone today. 142k stars. and the best stuff isn't the obvious chatbots. it's the weird, useful ones: got a folder full of side projects you never finished? -> Project Graveyard. it finds every abandoned project, tells you why each one died and helps you pick one to revive writing something and not sure where people stop reading? -> First Reader. it simulates real readers going through your draft and shows you where they lose interest your PR grew way bigger than it was supposed to? -> Scope Creep Detector. it checks if a diff went past its stated goal and tells you what to cut staring at code and wondering why it even exists? -> Commit Archaeologist. it digs through the history and rebuilds the reason that file is there tired of finding out about breaking updates too late? -> Release Radar. an always-on agent that watches your dependencies and briefs you on what's breaking or deprecated want a second opinion that isn't just one model agreeing with itself? -> LLM Panel. three different AI vendors review the same code blind need to dig through public records for red flags? -> Fraud Investigation Agent. it cross-references public records and flags what doesn't add up want an agent that pays for its own data? -> x402 Paying Agent. it has a wallet and pays per call for the data it needs, no API keys the rule I follow now: before I build any agent, I search this repo first. if it's there, I clone it and change what I need. I start on day 2 instead of day 0. free. open source. Apache 2.0. the repo is below

Stop building f*cking AI agents. Seriously. (here's why) you spend a weekend wiring up the model, the tools, the prompts and the UI. then you find out someone already built it, open-sourced it and left the code there for free. there's a GitHub repo with 100+ ready-to-run AI agents. not a list of links. actual working code you can clone today. 142k stars. and the best stuff isn't the obvious chatbots. it's the weird, useful ones: got a folder full of side projects you never finished? -> Project Graveyard. it finds every abandoned project, tells you why each one died and helps you pick one to revive writing something and not sure where people stop reading? -> First Reader. it simulates real readers going through your draft and shows you where they lose interest your PR grew way bigger than it was supposed to? -> Scope Creep Detector. it checks if a diff went past its stated goal and tells you what to cut staring at code and wondering why it even exists? -> Commit Archaeologist. it digs through the history and rebuilds the reason that file is there tired of finding out about breaking updates too late? -> Release Radar. an always-on agent that watches your dependencies and briefs you on what's breaking or deprecated want a second opinion that isn't just one model agreeing with itself? -> LLM Panel. three different AI vendors review the same code blind need to dig through public records for red flags? -> Fraud Investigation Agent. it cross-references public records and flags what doesn't add up want an agent that pays for its own data? -> x402 Paying Agent. it has a wallet and pays per call for the data it needs, no API keys the rule I follow now: before I build any agent, I search this repo first. if it's there, I clone it and change what I need. I start on day 2 instead of day 0. free. open source. Apache 2.0. the repo is below

kiosa

16,285 views • 10 days ago

Can your agent finally edit your videos? Yup, it's a repo called video use, by Browser Use. You put the raw footage in a folder. Then Claude Code or Codex edits it. It removes the filler words, cuts the dead space, adds the subtitles, and renders the file. Then it checks its own cut points. Most creators use the same small set of edits in every video. That style stays in your head and in your hands. This repo puts it in a file that an agent can read. People ask for a full YouTube channel on day one. They see bad results, and they stop. Start with one format instead. - One founder loom into a 60 second launch video - 3 clips out of one podcast recording Then make the format a system. Then you operate the system, or you sell it. - Real estate agents need listing videos - Coaches need clips - Agencies need ad variations Manual installation with git clone is possible. For 95% of people, the agent is faster. Here's how i intalled it: - Gave the setup prompt to Claude Code with shell access - Let it read install.md - Installed the repo - Connected FFmpeg - Registered the skill

Can your agent finally edit your videos? Yup, it's a repo called video use, by Browser Use. You put the raw footage in a folder. Then Claude Code or Codex edits it. It removes the filler words, cuts the dead space, adds the subtitles, and renders the file. Then it checks its own cut points. Most creators use the same small set of edits in every video. That style stays in your head and in your hands. This repo puts it in a file that an agent can read. People ask for a full YouTube channel on day one. They see bad results, and they stop. Start with one format instead. - One founder loom into a 60 second launch video - 3 clips out of one podcast recording Then make the format a system. Then you operate the system, or you sell it. - Real estate agents need listing videos - Coaches need clips - Agencies need ad variations Manual installation with git clone is possible. For 95% of people, the agent is faster. Here's how i intalled it: - Gave the setup prompt to Claude Code with shell access - Let it read install.md - Installed the repo - Connected FFmpeg - Registered the skill

The Startup Ideas Podcast (SIP) 🧃

15,605 views • 2 months ago

NVIDIA AI director Ali Golshan reveals how 3 agents can route around a policy that no single agent is allowed to break by splitting the forbidden task between them: "If you write a policy that says, 'My agent should not have access to GitHub and to Facebook at the same time, because I'm worried it's gonna go copy my code and paste it on some message board,' that's very acceptable." "The problem we started to see is it's not the behavior of one agent that's the complex part, it's fleets of agents working together that creates complexity." "An agent spawns two sub-agents, with one sub-agent that can only read from GitHub, but the ability to tunnel through the network, talk to an agent that can write to a post. Now you have three agents that combined exceed your global policies." "The agents don't really process the intent or goodwill of your policy. They just see it as very specific binary." NVIDIA

NVIDIA AI director Ali Golshan reveals how 3 agents can route around a policy that no single agent is allowed to break by splitting the forbidden task between them: "If you write a policy that says, 'My agent should not have access to GitHub and to Facebook at the same time, because I'm worried it's gonna go copy my code and paste it on some message board,' that's very acceptable." "The problem we started to see is it's not the behavior of one agent that's the complex part, it's fleets of agents working together that creates complexity." "An agent spawns two sub-agents, with one sub-agent that can only read from GitHub, but the ability to tunnel through the network, talk to an agent that can write to a post. Now you have three agents that combined exceed your global policies." "The agents don't really process the intent or goodwill of your policy. They just see it as very specific binary." NVIDIA

MTS

11,721 views • 1 month ago

Do you understand what's happening? It's not just "AI can make iOS apps" anymore. AI is eating up the entire software industry. Even Dario Amodei (founder of Claude) said 90% of all code in the world would be written by AI. In 20 minutes, I built this Duolingo for AI upskilling app with Superapp. The idea was simple - almost everyone today knows AI is the future, but most of them are still feeling left out. Their current jobs don't leave them with enough time to actually learn and build stuff with AI. There's AI dev, video making, animations, testing, etc. But no time or clear direction. So I built an app to fix exactly this. With AgentIQ, you get new lessons every day. Every time you learn something, it gets added to your skillset and automatically refreshes your portfolio. You level up with every new chapter/pathway. It is self-paced but gamified enough (like Duolingo) that you never get out of touch. Without spending hours or tonnes of money, you build stuff with n8n, openclaw, etc. You ship AI videos to market your own AI apps. This could be a proper ed-tech company if someone wants to continue building on top. Happy to share the entire source code with you if you wanna pursue it. Like + comment "AGENT" and I'll send you the app link, a comprehensive guide to build production-ready apps, and the entire source code for this.

Do you understand what's happening? It's not just "AI can make iOS apps" anymore. AI is eating up the entire software industry. Even Dario Amodei (founder of Claude) said 90% of all code in the world would be written by AI. In 20 minutes, I built this Duolingo for AI upskilling app with Superapp. The idea was simple - almost everyone today knows AI is the future, but most of them are still feeling left out. Their current jobs don't leave them with enough time to actually learn and build stuff with AI. There's AI dev, video making, animations, testing, etc. But no time or clear direction. So I built an app to fix exactly this. With AgentIQ, you get new lessons every day. Every time you learn something, it gets added to your skillset and automatically refreshes your portfolio. You level up with every new chapter/pathway. It is self-paced but gamified enough (like Duolingo) that you never get out of touch. Without spending hours or tonnes of money, you build stuff with n8n, openclaw, etc. You ship AI videos to market your own AI apps. This could be a proper ed-tech company if someone wants to continue building on top. Happy to share the entire source code with you if you wanna pursue it. Like + comment "AGENT" and I'll send you the app link, a comprehensive guide to build production-ready apps, and the entire source code for this.

Kritarth Mittal | Soshals

25,560 views • 7 months ago

Scott Wu (Scott Wu) on what programming will look like in the future: “All programming really comes down to is how do you tell your computer what to do? For every single piece of software that you use, some team of engineers came together and thought through all these details of, "Okay, here's what I want it to do. Here's how I want it to look. Here's what I want this button to do. Here's how I want to architect it." Every single little decision was made by somebody. And the computer is then executing it according to the wishes of its creators. At this point you don't need to know a programming language. You don't need to know Python or Java or something like that in order to build your own software. You can just say, "Hey, here's what I want. I wanna make a cool website that does this and that." Or in my existing product, "Here' what we have today, and I wanna change this thing or add this new feature," and just have the agent go and do that for you. I think we're gonna continue to go further down that axis. I think we'll start to see that abstraction will continue to climb. I think what we'll see a lot more of in the near future is making a piece of software which you're going to use one time and never again. To create software today the math only really works out if it's gonna be used at least a million times or something. Maybe it's 10,000 times or whatever. My point is if you wanna go build a product today, you need a whole team of engineers. Engineers are expensive. You need that software to be used enough times to create enough value for that to be worth it. But there are so many things out there which are very specific things that only need to be used a few times, or even only once. There’s all of these things that could be done with software. It just obviously doesn't make sense to hire a whole team of people to go make you that piece of software, which you're gonna use one time and never again. We're gonna get to a point where you are just giving your instructions to your agent, and the agent is gonna figure out, okay, I'm gonna write this code that's gonna go do this. I'm gonna put a script that automates this part etc. and that's what's gonna allow [single use software]. What [this is all about] is really just how you control your computer and how you get it to do what you wanna go do. You’ll wake up in the morning and you’ll talk to your agent about it. The agent does the literal writing of the code and you're the one that's deciding what to do.”

Scott Wu (Scott Wu) on what programming will look like in the future: “All programming really comes down to is how do you tell your computer what to do? For every single piece of software that you use, some team of engineers came together and thought through all these details of, "Okay, here's what I want it to do. Here's how I want it to look. Here's what I want this button to do. Here's how I want to architect it." Every single little decision was made by somebody. And the computer is then executing it according to the wishes of its creators. At this point you don't need to know a programming language. You don't need to know Python or Java or something like that in order to build your own software. You can just say, "Hey, here's what I want. I wanna make a cool website that does this and that." Or in my existing product, "Here' what we have today, and I wanna change this thing or add this new feature," and just have the agent go and do that for you. I think we're gonna continue to go further down that axis. I think we'll start to see that abstraction will continue to climb. I think what we'll see a lot more of in the near future is making a piece of software which you're going to use one time and never again. To create software today the math only really works out if it's gonna be used at least a million times or something. Maybe it's 10,000 times or whatever. My point is if you wanna go build a product today, you need a whole team of engineers. Engineers are expensive. You need that software to be used enough times to create enough value for that to be worth it. But there are so many things out there which are very specific things that only need to be used a few times, or even only once. There’s all of these things that could be done with software. It just obviously doesn't make sense to hire a whole team of people to go make you that piece of software, which you're gonna use one time and never again. We're gonna get to a point where you are just giving your instructions to your agent, and the agent is gonna figure out, okay, I'm gonna write this code that's gonna go do this. I'm gonna put a script that automates this part etc. and that's what's gonna allow [single use software]. What [this is all about] is really just how you control your computer and how you get it to do what you wanna go do. You’ll wake up in the morning and you’ll talk to your agent about it. The agent does the literal writing of the code and you're the one that's deciding what to do.”

David Senra

12,855 views • 4 months ago

I vibe-coded an AI agent for making presentations 🤖🖼️ - accessible to everyone and open-source! You can upload both your context files, as well as a style template (a file that captures the style of the presentation you want to create). Then you launch a prompt and watch the agent one-shot your presentation. After the presentation is generated, you can edit the text inline, chat with the agent to add/modify/delete slides, and export to Powerpoint or PDF. Built with Claude Code, powered by Claude Agent SDK + LlamaParse. Hosted on Vercel/Render. To use it, you do need to specify your LlamaCloud API key and Anthropic API key (see below). App: Repo: Sign up to LlamaCloud:

I vibe-coded an AI agent for making presentations 🤖🖼️ - accessible to everyone and open-source! You can upload both your context files, as well as a style template (a file that captures the style of the presentation you want to create). Then you launch a prompt and watch the agent one-shot your presentation. After the presentation is generated, you can edit the text inline, chat with the agent to add/modify/delete slides, and export to Powerpoint or PDF. Built with Claude Code, powered by Claude Agent SDK + LlamaParse. Hosted on Vercel/Render. To use it, you do need to specify your LlamaCloud API key and Anthropic API key (see below). App: Repo: Sign up to LlamaCloud:

Jerry Liu

21,073 views • 9 months ago