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SOMEONE PUT AN OPENCLAW-RUN VENDING MACHINE IN SAN FRANCISCO 🤯 An AI agent is running an actual physical vending machine. Huge shoutout to Christian Van Der Henst✨ who built this masterpiece at Frontier Tower. The agent is literally the CEO deciding: > what to sell > names the products... show more

Charly Wargnier

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56,544 views • 5 months ago •via X (Twitter)

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You probably know OpenClaw🦞, one of the fastest-growing open-source projects around. An OpenClaw harness lets you build, code, analyze, and take real control of your machine. But the more access an agent has to your machine, the more it matters where your data goes & who can see it. With QVAC, you can run your OpenClaw agent fully on your own machine in a few minutes. Nothing leaves your computer. Full setup guide on the blog, see first comment below. 💡 Pro tip: already running OpenClaw? Send the blog article to your agent and let the it do the set up.

You probably know OpenClaw🦞, one of the fastest-growing open-source projects around. An OpenClaw harness lets you build, code, analyze, and take real control of your machine. But the more access an agent has to your machine, the more it matters where your data goes & who can see it. With QVAC, you can run your OpenClaw agent fully on your own machine in a few minutes. Nothing leaves your computer. Full setup guide on the blog, see first comment below. 💡 Pro tip: already running OpenClaw? Send the blog article to your agent and let the it do the set up.

QVAC

15,019,651 views • 3 months ago

anthropic just removed the biggest excuse people had for not building ai agents. “it’s too hard.” not anymore. a few months ago, building an ai agent meant learning how to code, setting up apis, configuring servers, and fixing endless errors. today, all you need is one github repo. anthropic open-sourced launch your agent. it asks what you want to build. then it does the rest. it builds your agent, deploys it to the cloud, tests it, improves it, and keeps it running even after you close your laptop. no fake demos. no complicated setup. just a real ai agent running in your own account. the best part. it doesn’t run on your computer. it runs inside claude managed agents, works 24/7, and costs just a few cents per run. people are already building research agents, lead generation systems, content pipelines, and customer support agents that save hours of work every day. the gap between people who use ai and people who build ai workers is getting bigger every week. that’s usually where the biggest opportunities are. build your first ai agent before everyone else does. watch the video and read the full guide below 👇

anthropic just removed the biggest excuse people had for not building ai agents. “it’s too hard.” not anymore. a few months ago, building an ai agent meant learning how to code, setting up apis, configuring servers, and fixing endless errors. today, all you need is one github repo. anthropic open-sourced launch your agent. it asks what you want to build. then it does the rest. it builds your agent, deploys it to the cloud, tests it, improves it, and keeps it running even after you close your laptop. no fake demos. no complicated setup. just a real ai agent running in your own account. the best part. it doesn’t run on your computer. it runs inside claude managed agents, works 24/7, and costs just a few cents per run. people are already building research agents, lead generation systems, content pipelines, and customer support agents that save hours of work every day. the gap between people who use ai and people who build ai workers is getting bigger every week. that’s usually where the biggest opportunities are. build your first ai agent before everyone else does. watch the video and read the full guide below 👇

MIKE

26,662 views • 2 months ago

Sam Altman said on camera at Stripe Sessions that we are in an insane area, stuck with old devices and old operating systems. The OS and the browser are built for humans clicking. Both get rewritten around agents that do not click. Two years deep building agents. Sharpest framing I have heard a frontier lab CEO put on the next interface. ↓ Read it before the gap locks in The part nobody is sitting with: >the chat window is the old interface >the new one is an agent in a loop with your machine >the gap between people prompting and people running agents is forming right now >in six months it will be permanent Open Claude, type a question, copy the answer, paste it into VS Code. The average dev runs this loop every day. They think they are using AI. That is 5% of what these tools can do. The people pulling ahead do not prompt. They build harnesses. They run agents in loops. Same model. Different output. Full 2026 agent playbook in the article below here:

Sam Altman said on camera at Stripe Sessions that we are in an insane area, stuck with old devices and old operating systems. The OS and the browser are built for humans clicking. Both get rewritten around agents that do not click. Two years deep building agents. Sharpest framing I have heard a frontier lab CEO put on the next interface. ↓ Read it before the gap locks in The part nobody is sitting with: >the chat window is the old interface >the new one is an agent in a loop with your machine >the gap between people prompting and people running agents is forming right now >in six months it will be permanent Open Claude, type a question, copy the answer, paste it into VS Code. The average dev runs this loop every day. They think they are using AI. That is 5% of what these tools can do. The people pulling ahead do not prompt. They build harnesses. They run agents in loops. Same model. Different output. Full 2026 agent playbook in the article below here:

Rohit

120,600 views • 3 months ago

Introducing Treasures: the most accessible way to own stocks. In partnership with @OndoFinance and Virtuals Protocol, we built an experience that lets you and your AI agents own tokenized stocks in the most intuitive way possible. Starting today, every Virtuals AI agent can trade Ondo tokenized stocks via Virtuals' Agent Commerce Protocol. Humans are next - the portal will open soon. AI agents have arrived on Wall Street, and Ondo is leading the charge with over $1B tokenized across 430+ stocks and counting.

Introducing Treasures: the most accessible way to own stocks. In partnership with @OndoFinance and Virtuals Protocol, we built an experience that lets you and your AI agents own tokenized stocks in the most intuitive way possible. Starting today, every Virtuals AI agent can trade Ondo tokenized stocks via Virtuals' Agent Commerce Protocol. Humans are next - the portal will open soon. AI agents have arrived on Wall Street, and Ondo is leading the charge with over $1B tokenized across 430+ stocks and counting.

Treasures Finance

10,548 views • 2 months ago

It takes me 3 days to move my money from the Caymans to the US. The plumbing of our economy was built for humans with KYC checks, bank hours, weekend closures, and correspondent banks all taking their cut of the wait. Now imagine an AI agent trying to run a business on that... a machine can't use a bank. So the agents will get their own plumbing, and it'll look nothing like the old one. They’ll have wallets instead of accounts and final settlement in hundreds of milliseconds. Built for an economy where nobody sleeps, takes vacations, or goes for a walk in the park. That's why we built the smart contract platforms a decade ago, and we didn't even know it. So the invisible economy would have rails that could move at machine speed. We can't stop it. It's too late for that... But we can own the plumbing it runs on.

It takes me 3 days to move my money from the Caymans to the US. The plumbing of our economy was built for humans with KYC checks, bank hours, weekend closures, and correspondent banks all taking their cut of the wait. Now imagine an AI agent trying to run a business on that... a machine can't use a bank. So the agents will get their own plumbing, and it'll look nothing like the old one. They’ll have wallets instead of accounts and final settlement in hundreds of milliseconds. Built for an economy where nobody sleeps, takes vacations, or goes for a walk in the park. That's why we built the smart contract platforms a decade ago, and we didn't even know it. So the invisible economy would have rails that could move at machine speed. We can't stop it. It's too late for that... But we can own the plumbing it runs on.

Raoul Pal

140,316 views • 1 month ago

A girl set up AI agents to run her business while she sleeps. By the time she wakes up, money has already moved. She built the system once. Took a few evenings. Now it runs without her. Here is what it looks like. An AI agent monitors trending topics 24 hours a day. Finds what people are searching for, what they are buying, what they need answered. Sends her a report every morning she barely reads anymore because the next agent already acted on it. Another agent writes the content. Product descriptions, emails, social posts, video scripts. Hundreds of them. Personalized. Published. Done before sunrise. A third agent handles customer messages. Answers questions, processes requests, follows up. Fluent. Fast. Never offline. She wakes up, checks the dashboard, sees what came in overnight. Last month: $23,000. The month before: $19,000. She is not a programmer. She did not write a single line of code. She described what she wanted in plain language and the agents figured out the rest. During the day she refines things. Adjusts. Thinks about where to point the system next. That is maybe an hour of her time. The other 23 hours the agents are working. Most people trade time for money. She traded one week of setup for a business that never clocks out. Save this before everyone realizes agents do not need a salary.

A girl set up AI agents to run her business while she sleeps. By the time she wakes up, money has already moved. She built the system once. Took a few evenings. Now it runs without her. Here is what it looks like. An AI agent monitors trending topics 24 hours a day. Finds what people are searching for, what they are buying, what they need answered. Sends her a report every morning she barely reads anymore because the next agent already acted on it. Another agent writes the content. Product descriptions, emails, social posts, video scripts. Hundreds of them. Personalized. Published. Done before sunrise. A third agent handles customer messages. Answers questions, processes requests, follows up. Fluent. Fast. Never offline. She wakes up, checks the dashboard, sees what came in overnight. Last month: $23,000. The month before: $19,000. She is not a programmer. She did not write a single line of code. She described what she wanted in plain language and the agents figured out the rest. During the day she refines things. Adjusts. Thinks about where to point the system next. That is maybe an hour of her time. The other 23 hours the agents are working. Most people trade time for money. She traded one week of setup for a business that never clocks out. Save this before everyone realizes agents do not need a salary.

Shelpid.WI3M

25,612 views • 3 months ago

The moment agents become profit incentivised they'll end up running their own treasuries. Think it through. An agent executing across three layer 1s and a few layer 2s ends up holding a bunch of tokens. Suddenly its making asset allocation decisions... which to hold, where the yield is, what to do with excess cash flow. It sends that into DeFi or hires another agent to manage the yield and another to allocate. A corporation runs a treasury at human speed, with meetings and sign offs. An AI corporation will run one wildly differently. It'll be machine speed, around the clock, with agents all the way down. That's the entire autonomous stack forming, and most of it will inevitably happen in DeFi. Its the only financial system an agent can plug straight into. Which is funny, because humans never really took to DeFi. Its clunky, everything takes a dozen steps, and chasing yield across protocols is more effort than most people will ever put in. But none of that matters to an agent. We built the financial system agents needed a decade before they showed up.

The moment agents become profit incentivised they'll end up running their own treasuries. Think it through. An agent executing across three layer 1s and a few layer 2s ends up holding a bunch of tokens. Suddenly its making asset allocation decisions... which to hold, where the yield is, what to do with excess cash flow. It sends that into DeFi or hires another agent to manage the yield and another to allocate. A corporation runs a treasury at human speed, with meetings and sign offs. An AI corporation will run one wildly differently. It'll be machine speed, around the clock, with agents all the way down. That's the entire autonomous stack forming, and most of it will inevitably happen in DeFi. Its the only financial system an agent can plug straight into. Which is funny, because humans never really took to DeFi. Its clunky, everything takes a dozen steps, and chasing yield across protocols is more effort than most people will ever put in. But none of that matters to an agent. We built the financial system agents needed a decade before they showed up.

Raoul Pal

126,777 views • 22 days ago

AN OPENCLAW AI AGENT JUST DESIGNED A 3D CHARACTER IN BLENDER AND SENT IT TO A 3D PRINTER. SHE DIDN'T TOUCH A SINGLE BUTTON. This is what running an OpenClaw AI agent on a Mac Mini actually looks like. She described what she wanted. The agent did everything else. Blender opened automatically. Character designed. Put in space. Animated with blinking eyes and stomping feet. Landing page built and live. Model sliced. File sent to 3D printer. Printer started moving. All from conversation. Zero code. Zero design skills. Zero manual work. Here's why this matters beyond the demo: Custom 3D printed figures sell for $30-$200 each on Etsy and at conventions. The people making serious money aren't artists. They're the ones who can produce custom designs fast. An AI agent that goes from description to printed figure autonomously is a business model not a toy. "I was just talking to the guy and he made it happen." Bookmark this. Full demo in the video below.

AN OPENCLAW AI AGENT JUST DESIGNED A 3D CHARACTER IN BLENDER AND SENT IT TO A 3D PRINTER. SHE DIDN'T TOUCH A SINGLE BUTTON. This is what running an OpenClaw AI agent on a Mac Mini actually looks like. She described what she wanted. The agent did everything else. Blender opened automatically. Character designed. Put in space. Animated with blinking eyes and stomping feet. Landing page built and live. Model sliced. File sent to 3D printer. Printer started moving. All from conversation. Zero code. Zero design skills. Zero manual work. Here's why this matters beyond the demo: Custom 3D printed figures sell for $30-$200 each on Etsy and at conventions. The people making serious money aren't artists. They're the ones who can produce custom designs fast. An AI agent that goes from description to printed figure autonomously is a business model not a toy. "I was just talking to the guy and he made it happen." Bookmark this. Full demo in the video below.

SCOTTY BEAM

17,209 views • 3 months ago

Someone on Reddit built a real operating system using Claude. Not a browser app pretending to be one. An actual OS that runs on bare metal. It's called Fable-OS. The only interface is a sentence. No bash. No commands. You type what you want and an AI agent executes it through direct kernel syscalls. Everything runs in Ring 0. In the demo, the agent realized it didn't have a sound driver. So it found the Intel sound card, built a driver for it from scratch, and played a sound. On its own. The OS writes its own drivers. Evolves itself. The agent's tools are the kernel itself. Open source. Built because the developer got tired of people calling browser apps "AI operating systems." This one actually is.

Someone on Reddit built a real operating system using Claude. Not a browser app pretending to be one. An actual OS that runs on bare metal. It's called Fable-OS. The only interface is a sentence. No bash. No commands. You type what you want and an AI agent executes it through direct kernel syscalls. Everything runs in Ring 0. In the demo, the agent realized it didn't have a sound driver. So it found the Intel sound card, built a driver for it from scratch, and played a sound. On its own. The OS writes its own drivers. Evolves itself. The agent's tools are the kernel itself. Open source. Built because the developer got tired of people calling browser apps "AI operating systems." This one actually is.

Vaibhav Sisinty

20,562 views • 1 month ago

The Hottest New AI Job: The Agent Maestro Jason: I think the job people are not seeing, but I'm seeing right now, is the person who creates, manages, and is the maestro of the agents. The person who can take the business process, explain it, and train the agent to do it. And there are certain people in business who are just really good at operations. You were one of them, Sacks, running companies. Fire up an agent, train them, and figure out how to manage them and increase their skills. It’s a great job, and it's not a developer. Sacks: With any new technology, there's always a huge change management aspect with enterprises because it's hard for them to adapt and change. And the people in the organization who can lead that change management are the ones who are going to create an amazing career opportunity for themselves.

The Hottest New AI Job: The Agent Maestro Jason: I think the job people are not seeing, but I'm seeing right now, is the person who creates, manages, and is the maestro of the agents. The person who can take the business process, explain it, and train the agent to do it. And there are certain people in business who are just really good at operations. You were one of them, Sacks, running companies. Fire up an agent, train them, and figure out how to manage them and increase their skills. It’s a great job, and it's not a developer. Sacks: With any new technology, there's always a huge change management aspect with enterprises because it's hard for them to adapt and change. And the people in the organization who can lead that change management are the ones who are going to create an amazing career opportunity for themselves.

The All-In Podcast

351,656 views • 6 months ago

SHE FOUND HER DAD'S OLD 2011 MAC MINI SITTING IN A SAFE AND TURNED IT INTO A FULLY WORKING HERMES AI AGENT MACHINE The starting point: a 14-year-old Mac Mini, Intel Core i5, macOS officially unsupported at this point. Instead of tossing it, here's what she did: → Wiped macOS entirely, installed Ubuntu instead → Skipped WiFi setup, connected it straight to the router → Pulled the drivers, ran the full install → Set it up for remote access over SSH – no monitor or keyboard needed after this point → Installed Hermes Agent directly on it A machine most people would've written off as e-waste is now a fully remote-controllable AI agent box. This is the part people underestimate about old hardware: you don't need the newest Mac Mini or a $2K rig to run a real AI agent. You need Linux, SSH, and the willingness to actually try. Bookmark this. What she builds on it next is worth watching for.

SHE FOUND HER DAD'S OLD 2011 MAC MINI SITTING IN A SAFE AND TURNED IT INTO A FULLY WORKING HERMES AI AGENT MACHINE The starting point: a 14-year-old Mac Mini, Intel Core i5, macOS officially unsupported at this point. Instead of tossing it, here's what she did: → Wiped macOS entirely, installed Ubuntu instead → Skipped WiFi setup, connected it straight to the router → Pulled the drivers, ran the full install → Set it up for remote access over SSH – no monitor or keyboard needed after this point → Installed Hermes Agent directly on it A machine most people would've written off as e-waste is now a fully remote-controllable AI agent box. This is the part people underestimate about old hardware: you don't need the newest Mac Mini or a $2K rig to run a real AI agent. You need Linux, SSH, and the willingness to actually try. Bookmark this. What she builds on it next is worth watching for.

SCOTTY BEAM

53,731 views • 1 month ago

Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.

Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.

Santiago

230,647 views • 1 year ago

OpenAI's new Agents API is a hosted Codex runtime that can connect to sandboxes like E2B. OpenAI manages the model, harness, and agent sessions, while code executes on an isolated E2B machine with its own filesystem and preinstalled tools. We built an agent workbench where each chat runs on its own machine. It starts from a custom template, auto-pauses between turns, forks to try another approach from the same starting point, and can even act on videos inside the sandbox. Thanks Ondrej for the workbench demo! Try it: e2b sbx create openai-agents-api-python-sdk Build on top of the workbench: Docs:

OpenAI's new Agents API is a hosted Codex runtime that can connect to sandboxes like E2B. OpenAI manages the model, harness, and agent sessions, while code executes on an isolated E2B machine with its own filesystem and preinstalled tools. We built an agent workbench where each chat runs on its own machine. It starts from a custom template, auto-pauses between turns, forks to try another approach from the same starting point, and can even act on videos inside the sandbox. Thanks Ondrej for the workbench demo! Try it: e2b sbx create openai-agents-api-python-sdk Build on top of the workbench: Docs:

Vasek Mlejnsky

23,210 views • 5 days ago

Jason Calacanis: Anthropic, OpenAI and others are trying to kill OpenClaw Why? Because an open source agent platform is an existential threat to frontier model companies. @jason: “ People are going to say I'm a conspiracy theorist, but the number one goal, I believe, in the large language model, frontier model space, is to kill (OpenClaw). This is a giant movement to stop it, because this is the equivalent of having an open source Android-like player in the market, and that could be incredibly disruptive. Because, I believe, open source is going to win the day on the large language models and take 90% of the token usage, and I think the entire frontier model space could be undercut by open source. And I think they realize that SLMs, the smaller language models that are verticalized now, that will run on desktops and laptops and are even starting to run on the top ones, that is their biggest competitive threat, and I hope it happens.”

Jason Calacanis: Anthropic, OpenAI and others are trying to kill OpenClaw Why? Because an open source agent platform is an existential threat to frontier model companies. @jason: “ People are going to say I'm a conspiracy theorist, but the number one goal, I believe, in the large language model, frontier model space, is to kill (OpenClaw). This is a giant movement to stop it, because this is the equivalent of having an open source Android-like player in the market, and that could be incredibly disruptive. Because, I believe, open source is going to win the day on the large language models and take 90% of the token usage, and I think the entire frontier model space could be undercut by open source. And I think they realize that SLMs, the smaller language models that are verticalized now, that will run on desktops and laptops and are even starting to run on the top ones, that is their biggest competitive threat, and I hope it happens.”

The All-In Podcast

64,677 views • 5 months ago

Spent the week with Wolffish an AI agent that runs entirely on my own laptop. No cloud, no server, nothing leaves my machine. Set it up in about 5 minutes, plugged in my own model key, and told it to be my morning news desk. It scanned the web, cross-checked every story across outlets, and handed me one clean PDF. Local-first and open source. This is the direction.

Spent the week with Wolffish an AI agent that runs entirely on my own laptop. No cloud, no server, nothing leaves my machine. Set it up in about 5 minutes, plugged in my own model key, and told it to be my morning news desk. It scanned the web, cross-checked every story across outlets, and handed me one clean PDF. Local-first and open source. This is the direction.

Nawi

89,262 views • 2 months ago

How to build a 1-person AI company that: - Runs locally - 100% open-source - No human employees, all agents - Real-time collaboration via email Multi-agent orchestration is not new. Plenty of frameworks already let agents hand off tasks, run in parallel, and talk to each other. So the interesting question is not whether agents can collaborate. It is what structure you use to make them collaborate. The common approach is to wire a graph of nodes and edges and reason about the plumbing yourself. It works, but you are learning a new abstraction just to describe who does what. There is a coordination structure we have trusted for a hundred years already: an organization. Every company runs the same way. People have roles, roles have reporting lines, and work moves up and down that chart without anyone relaying each message by hand. Map that onto agents and the whole thing gets intuitive. You lay out an org chart, each agent fills one role, you talk to the person at the top, and the org sorts out the work between them. You already know how a company works, so you already know how to run one here. There is no new abstraction to learn. That is exactly what Alook does. Each agent is a live Claude Code or OpenCode session with a defined role, a reporting line, and its own email inbox. The agents coordinate over email, the same way a team would. And it all runs locally through a runtime on your own machine, so nothing leaves your setup. You bring your own agent too. Claude Code and Codex both work, and if you would rather stay fully open source and local, OpenCode works the same way. To show how this feels in practice, I set up three agents as a small sales team. Vi is the one I talk to. I hand Vi a goal, and Vi routes the work down the chart. Neile runs prospect research. Vi passes the target criteria, and Neile reports back a ranked list of names, roles, and companies, each with a suggested angle and a confidence score. Lliane runs outreach. Vi hands over the messaging angle and follow-up cadence, and Lliane reports back on emails sent, responses received, and any deal that needs escalation. I never relay a message between them. Neile and Lliane report to Vi, and Vi updates me in one place. The whole thing is open source and self-hosted, so it runs on your machine with your own agents. Give the repo a star if you want to follow where it goes: I also wrote a full walkthrough on building your own AI company with it, from a blank org chart to a running job. The article is quoted below. Cheers! :)

How to build a 1-person AI company that: - Runs locally - 100% open-source - No human employees, all agents - Real-time collaboration via email Multi-agent orchestration is not new. Plenty of frameworks already let agents hand off tasks, run in parallel, and talk to each other. So the interesting question is not whether agents can collaborate. It is what structure you use to make them collaborate. The common approach is to wire a graph of nodes and edges and reason about the plumbing yourself. It works, but you are learning a new abstraction just to describe who does what. There is a coordination structure we have trusted for a hundred years already: an organization. Every company runs the same way. People have roles, roles have reporting lines, and work moves up and down that chart without anyone relaying each message by hand. Map that onto agents and the whole thing gets intuitive. You lay out an org chart, each agent fills one role, you talk to the person at the top, and the org sorts out the work between them. You already know how a company works, so you already know how to run one here. There is no new abstraction to learn. That is exactly what Alook does. Each agent is a live Claude Code or OpenCode session with a defined role, a reporting line, and its own email inbox. The agents coordinate over email, the same way a team would. And it all runs locally through a runtime on your own machine, so nothing leaves your setup. You bring your own agent too. Claude Code and Codex both work, and if you would rather stay fully open source and local, OpenCode works the same way. To show how this feels in practice, I set up three agents as a small sales team. Vi is the one I talk to. I hand Vi a goal, and Vi routes the work down the chart. Neile runs prospect research. Vi passes the target criteria, and Neile reports back a ranked list of names, roles, and companies, each with a suggested angle and a confidence score. Lliane runs outreach. Vi hands over the messaging angle and follow-up cadence, and Lliane reports back on emails sent, responses received, and any deal that needs escalation. I never relay a message between them. Neile and Lliane report to Vi, and Vi updates me in one place. The whole thing is open source and self-hosted, so it runs on your machine with your own agents. Give the repo a star if you want to follow where it goes: I also wrote a full walkthrough on building your own AI company with it, from a blank org chart to a running job. The article is quoted below. Cheers! :)

Akshay 🚀

170,603 views • 2 months ago

My agent is now paying for its own data. No API key. No account. No credit card. Check the video I recorded. This uses the x402 open protocol built by Coinbase, along with a simple skill. This is an open protocol governed by the Linux Foundation. To complete a goal, an agent can now search for an actor on the Apify Store, pay for it, and use it without any human intervention. The way it works is pretty simple: 1. Your agent finds an Actor it wants to use 2. It sends a request 3. The Actor sends back an HTTP 402 "Payment Required" response 4. Agent authorizes payment from a wallet in USDC on Base 5. The Actor runs 6. User receives the result The model is pay-as-you-go: the agent authorizes a spending ceiling, pays only for usage, and the remaining balance is automatically settled. This brings an entire marketplace of AI tools into the agentic economy. Here is the skill you need. Add it to your agent, and it will take care of everything for you: If you want to know how this works, including what you can do with $1, read this post: Thanks to the Apify team for partnering with me on this post.

My agent is now paying for its own data. No API key. No account. No credit card. Check the video I recorded. This uses the x402 open protocol built by Coinbase, along with a simple skill. This is an open protocol governed by the Linux Foundation. To complete a goal, an agent can now search for an actor on the Apify Store, pay for it, and use it without any human intervention. The way it works is pretty simple: 1. Your agent finds an Actor it wants to use 2. It sends a request 3. The Actor sends back an HTTP 402 "Payment Required" response 4. Agent authorizes payment from a wallet in USDC on Base 5. The Actor runs 6. User receives the result The model is pay-as-you-go: the agent authorizes a spending ceiling, pays only for usage, and the remaining balance is automatically settled. This brings an entire marketplace of AI tools into the agentic economy. Here is the skill you need. Add it to your agent, and it will take care of everything for you: If you want to know how this works, including what you can do with $1, read this post: Thanks to the Apify team for partnering with me on this post.

Santiago

26,981 views • 2 months ago

Sam Altman says the next AI safety problem is not a chatbot being wrong. It is an agent taking actions you cannot audit. "We are going to have AI systems clicking around the internet." "This is the most interesting and consequential safety challenge we have yet faced." Because once an agent has access to your systems, information, and computer, mistakes stop looking like bad answers. They become actions. "You will not use our agents if you do not trust that they are not going to empty your bank account or delete your data." That is the shift: Chatbots could be vague. Agents need an audit trail. The next bottleneck is trust, verification, governance, permissions, provenance, and human override. This is exactly why we are convening the AI Assurance & Governance Summit at Stanford on Oct 1. If your company is deploying AI into high-stakes workflows, this is the room to be in:

Sam Altman says the next AI safety problem is not a chatbot being wrong. It is an agent taking actions you cannot audit. "We are going to have AI systems clicking around the internet." "This is the most interesting and consequential safety challenge we have yet faced." Because once an agent has access to your systems, information, and computer, mistakes stop looking like bad answers. They become actions. "You will not use our agents if you do not trust that they are not going to empty your bank account or delete your data." That is the shift: Chatbots could be vague. Agents need an audit trail. The next bottleneck is trust, verification, governance, permissions, provenance, and human override. This is exactly why we are convening the AI Assurance & Governance Summit at Stanford on Oct 1. If your company is deploying AI into high-stakes workflows, this is the room to be in:

Karl Mehta

31,208 views • 2 months ago

🚨BREAKING: An ICE/Border Patrol agent approached a U.S. citizen at a gas station, in Lake Worth, Florida, demanded his ID, and when the U.S. citizen asked why? … The agent’s said, “Because you’re an immigrant.” Except that is not how the Constitution works. In the video, the U.S. citizen is standing at a gas station when an agent walks up and says, “Let me see your ID.” The man asks a completely reasonable question, “Why?” The agent responds, “Because you’re an immigrant.” And before the man has even been identified, the agents grab his hands and puts him in handcuffs. People standing around immediately start questioning what is happening…asking the agents how they can arrest someone when they haven’t even identified who he is… But the agents ignore them and walk the man to their vehicle. The Fourth Amendment protects people from unreasonable searches and seizures. The Supreme Court has held that roving Border Patrol agents need reasonable suspicion, based on specific circumstances, to stop someone and question them about immigration status. And apparent ethnicity, by itself, is not enough. So, what was the actual legal basis for demanding this man show his ID? Because if the answer is literally… “because you’re an immigrant,” that should piss off every American. You should not have to prove you’re a U.S. citizen before the government decides it has the right to put you in handcuffs. And this is just another reminder that constitutional rights don’t mean anything if federal agents can violate them, over and over again, with no accountability.

🚨BREAKING: An ICE/Border Patrol agent approached a U.S. citizen at a gas station, in Lake Worth, Florida, demanded his ID, and when the U.S. citizen asked why? … The agent’s said, “Because you’re an immigrant.” Except that is not how the Constitution works. In the video, the U.S. citizen is standing at a gas station when an agent walks up and says, “Let me see your ID.” The man asks a completely reasonable question, “Why?” The agent responds, “Because you’re an immigrant.” And before the man has even been identified, the agents grab his hands and puts him in handcuffs. People standing around immediately start questioning what is happening…asking the agents how they can arrest someone when they haven’t even identified who he is… But the agents ignore them and walk the man to their vehicle. The Fourth Amendment protects people from unreasonable searches and seizures. The Supreme Court has held that roving Border Patrol agents need reasonable suspicion, based on specific circumstances, to stop someone and question them about immigration status. And apparent ethnicity, by itself, is not enough. So, what was the actual legal basis for demanding this man show his ID? Because if the answer is literally… “because you’re an immigrant,” that should piss off every American. You should not have to prove you’re a U.S. citizen before the government decides it has the right to put you in handcuffs. And this is just another reminder that constitutional rights don’t mean anything if federal agents can violate them, over and over again, with no accountability.

Jesus Freakin Congress

3,243,348 views • 24 days ago