MIKE

@mikenevermiss • 27,857 subscribers

early to everything that matters. the green exchange at @ourbit

Shorts

13 years old. making $20,000 a month. working just 1-2 hours a day. he didn’t work harder. he built a system. every morning, it looks at what’s trending. it finds the best posts from the last 24 hours. then it gives him 10 content ideas, ranked from best to worst. he picks one. one AI writes the post in his style. another checks it for mistakes. another posts it to 5 different platforms. one idea. five platforms. almost no manual work. after each post goes live, the system tracks what people liked, shared, and saved. it uses that data to make the next posts better. so the content keeps improving on its own. the results add up. 5 million views in 2 weeks. 100,000 bookmarks in 2 months. bookmarks matter. people only save posts they want to come back to. when lots of people save a post, platforms keep showing it to more people. that’s why his posts keep getting views… while he’s at school. while he’s sleeping. while he’s doing something else. the biggest advantage today isn’t working more. it’s building a system that works even when you don’t. watch the video. then read the full breakdown below.

13 years old. making $20,000 a month. working just 1-2 hours a day. he didn’t work harder. he built a system. every morning, it looks at what’s trending. it finds the best posts from the last 24 hours. then it gives him 10 content ideas, ranked from best to worst. he picks one. one AI writes the post in his style. another checks it for mistakes. another posts it to 5 different platforms. one idea. five platforms. almost no manual work. after each post goes live, the system tracks what people liked, shared, and saved. it uses that data to make the next posts better. so the content keeps improving on its own. the results add up. 5 million views in 2 weeks. 100,000 bookmarks in 2 months. bookmarks matter. people only save posts they want to come back to. when lots of people save a post, platforms keep showing it to more people. that’s why his posts keep getting views… while he’s at school. while he’s sleeping. while he’s doing something else. the biggest advantage today isn’t working more. it’s building a system that works even when you don’t. watch the video. then read the full breakdown below.

2,879,788 次观看

Just open sourced MotionPromptGallery 178 AI motion graphics, each with the exact prompt behind it. made with Opus 5.5, GPT-6 Astra, Kimi K3, Fable 5. built with Next.js, fully static, deploys to Vercel in seconds. go ship with it, and add your own piece. live site:

Just open sourced MotionPromptGallery 178 AI motion graphics, each with the exact prompt behind it. made with Opus 5.5, GPT-6 Astra, Kimi K3, Fable 5. built with Next.js, fully static, deploys to Vercel in seconds. go ship with it, and add your own piece. live site:

21,163 次观看

A 22-year-old college student in shenzhen reportedly made $14,700 in one month with a 900-yuan redmi phone. his parents still think he’s spending all his time preparing for exams. here’s what the phone does. every 30 minutes, it opens six chinese news apps, scans the latest headlines, takes screenshots, and sends them to claude for analysis. claude compares that information with polymarket odds and suggests potential betting opportunities. the entire workflow runs without writing a single line of code. it’s powered by phonedriver, an open-source tool that lets ai see your phone’s screen and operate it like a human. you simply describe the task in plain english, and it does the rest. the edge comes from timing. news often appears on chinese platforms like weibo and toutiao 20 to 50 minutes before english speaking traders fully react on polymarket. that small window can create an opportunity before the market catches up. some of those apps block web scrapers, but phonedriver doesn’t scrape data. it simply looks at what’s on the screen, just like a person would, then taps and swipes automatically.

A 22-year-old college student in shenzhen reportedly made $14,700 in one month with a 900-yuan redmi phone. his parents still think he’s spending all his time preparing for exams. here’s what the phone does. every 30 minutes, it opens six chinese news apps, scans the latest headlines, takes screenshots, and sends them to claude for analysis. claude compares that information with polymarket odds and suggests potential betting opportunities. the entire workflow runs without writing a single line of code. it’s powered by phonedriver, an open-source tool that lets ai see your phone’s screen and operate it like a human. you simply describe the task in plain english, and it does the rest. the edge comes from timing. news often appears on chinese platforms like weibo and toutiao 20 to 50 minutes before english speaking traders fully react on polymarket. that small window can create an opportunity before the market catches up. some of those apps block web scrapers, but phonedriver doesn’t scrape data. it simply looks at what’s on the screen, just like a person would, then taps and swipes automatically.

204,646 次观看

FABLE 5 + HIGGSFIELD JUST KILLED THE $35,000 WEB AGENCY. The same animated website that used to cost between $6,000 and $35,000 can now be built in a single session for around $12 in AI credits. Claude Code handles the website. Higgsfield creates the visuals. Together, they can build a complete scroll-driven website from a simple prompt. Claude writes the layout, GSAP ScrollTrigger animations, Lenis smooth scrolling, responsive pages, and checks everything before you ship. Higgsfield generates the hero videos, cinematic transitions, ambient loops, thumbnails, and every visual asset you need. By the end of one session, you have a fully animated website with cinematic motion, smooth scrolling, optimized assets, responsive layouts, and polished visual effects like film grain, particles, vignette, glass cards, and color tints. Getting started only takes a few minutes. Add Higgsfield as an MCP server inside Claude Code, complete the OAuth login once, and Claude can generate and pull videos directly into your project without manually exporting anything. The prompts are simple. Give Claude your project brief and ask it to script the entire scroll experience. Tell it to generate a hero video and supporting clips for every section. Ask it to add the finishing touches like film grain, particles, glass cards, and scroll pacing. Then let it review the site, improve loading speed, fix mobile layouts, and rewrite anything that doesn’t work. This replaces work that usually looks like this: A $6,000-$35,000 web agency. An $800-$2,000 motion designer. A $2,000-$10,000 front-end developer. And weeks of back-and-forth before launch. Now it’s Fable 5, Higgsfield, a subscription, a few dollars in AI credits, and one session. The pipeline used to be the advantage. Now it’s just a prompt. Full breakdown in the article below.

FABLE 5 + HIGGSFIELD JUST KILLED THE $35,000 WEB AGENCY. The same animated website that used to cost between $6,000 and $35,000 can now be built in a single session for around $12 in AI credits. Claude Code handles the website. Higgsfield creates the visuals. Together, they can build a complete scroll-driven website from a simple prompt. Claude writes the layout, GSAP ScrollTrigger animations, Lenis smooth scrolling, responsive pages, and checks everything before you ship. Higgsfield generates the hero videos, cinematic transitions, ambient loops, thumbnails, and every visual asset you need. By the end of one session, you have a fully animated website with cinematic motion, smooth scrolling, optimized assets, responsive layouts, and polished visual effects like film grain, particles, vignette, glass cards, and color tints. Getting started only takes a few minutes. Add Higgsfield as an MCP server inside Claude Code, complete the OAuth login once, and Claude can generate and pull videos directly into your project without manually exporting anything. The prompts are simple. Give Claude your project brief and ask it to script the entire scroll experience. Tell it to generate a hero video and supporting clips for every section. Ask it to add the finishing touches like film grain, particles, glass cards, and scroll pacing. Then let it review the site, improve loading speed, fix mobile layouts, and rewrite anything that doesn’t work. This replaces work that usually looks like this: A $6,000-$35,000 web agency. An $800-$2,000 motion designer. A $2,000-$10,000 front-end developer. And weeks of back-and-forth before launch. Now it’s Fable 5, Higgsfield, a subscription, a few dollars in AI credits, and one session. The pipeline used to be the advantage. Now it’s just a prompt. Full breakdown in the article below.

143,461 次观看

holy sh*t this is f**king dangerous. a Chinese developer figured out how to run Fable 5.1 for FREE through GPT-5.6 Luna subagents on basically every task. that means you can keep using Fable without constantly worrying about hitting agent usage limits. the setup takes like 3 minutes: > install the fable-orchestrator repo > run /fable orchestrator [task] that’s it. your agent handles the rest. give this to your agent immediately. this might be the most useful setup you’ll find this week.

holy sh*t this is f**king dangerous. a Chinese developer figured out how to run Fable 5.1 for FREE through GPT-5.6 Luna subagents on basically every task. that means you can keep using Fable without constantly worrying about hitting agent usage limits. the setup takes like 3 minutes: > install the fable-orchestrator repo > run /fable orchestrator [task] that’s it. your agent handles the rest. give this to your agent immediately. this might be the most useful setup you’ll find this week.

47,404 次观看

GLM 5.3 is FREE right now and you can actually use it. you can access it through ZenMux with a free API key, and Z. ai is also offering free access rn. you get: - GLM 5.3 - 1M context window - Up to 128K output - Tool calling + MCP - Free API access ZenMux currently lists GLM 5.3 at $0 for both input and output. to get started: > Go to > Create an account > Generate an API key > Use as the base URL > Select z-ai/glm-5.3-free you can also test GLM 5.3 directly at free access can change, so this is worth testing while it’s available

GLM 5.3 is FREE right now and you can actually use it. you can access it through ZenMux with a free API key, and Z. ai is also offering free access rn. you get: - GLM 5.3 - 1M context window - Up to 128K output - Tool calling + MCP - Free API access ZenMux currently lists GLM 5.3 at $0 for both input and output. to get started: > Go to > Create an account > Generate an API key > Use as the base URL > Select z-ai/glm-5.3-free you can also test GLM 5.3 directly at free access can change, so this is worth testing while it’s available

42,882 次观看

Blender just became a prompt box. Kimi K3 + Blender MCP can take a simple text prompt and build an entire 3D scene for you. terrain, buildings, lighting, materials, camera movement, animation, even the Python scripts holding everything together. but the crazy part isn’t just that it can build the scene. Kimi can inspect what it created, understand what looks wrong, then go back into Blender and fix the actual scene before rendering again. the camera can be clipping through a tree, the lighting can feel off, the city can look too artificial, and instead of starting over, Kimi can make the changes directly inside Blender. and because everything is happening in Blender, you’re not left with a locked AI-generated video. you get the actual 3D scene. every object, material, light, camera and keyframe stays editable. a few years ago, creating something like this could take weeks of modeling, scripting, lighting and animation. now you can describe the world, let Kimi build the first 90%, and spend your time making the final 10% actually look good. that’s what makes Kimi K3 + Blender MCP so interesting. it’s getting dangerously close to text-to-3D, except the result is a real Blender project you can keep editing.

Blender just became a prompt box. Kimi K3 + Blender MCP can take a simple text prompt and build an entire 3D scene for you. terrain, buildings, lighting, materials, camera movement, animation, even the Python scripts holding everything together. but the crazy part isn’t just that it can build the scene. Kimi can inspect what it created, understand what looks wrong, then go back into Blender and fix the actual scene before rendering again. the camera can be clipping through a tree, the lighting can feel off, the city can look too artificial, and instead of starting over, Kimi can make the changes directly inside Blender. and because everything is happening in Blender, you’re not left with a locked AI-generated video. you get the actual 3D scene. every object, material, light, camera and keyframe stays editable. a few years ago, creating something like this could take weeks of modeling, scripting, lighting and animation. now you can describe the world, let Kimi build the first 90%, and spend your time making the final 10% actually look good. that’s what makes Kimi K3 + Blender MCP so interesting. it’s getting dangerously close to text-to-3D, except the result is a real Blender project you can keep editing.

10,434 次观看

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this is f**king insane. Jack Dorsey just open sourced a free tool for running a one-person business. the GitHub repo already has 14.4K stars. It lets you: → run your own server → keep chat, search, Git, and automation in one place → add AI agents that work like teammates → decide exactly what each agent can do no monthly subscriptions. just you, your AI agents, and full control. this is where one-person businesses are headed. save this for later.

this is f**king insane. Jack Dorsey just open sourced a free tool for running a one-person business. the GitHub repo already has 14.4K stars. It lets you: → run your own server → keep chat, search, Git, and automation in one place → add AI agents that work like teammates → decide exactly what each agent can do no monthly subscriptions. just you, your AI agents, and full control. this is where one-person businesses are headed. save this for later.

711,112 次观看 • 2 个月前

this is f**king dangerous. someone just open sourced an entire library of ready-made JEV skills for building insane AI agent workflows. instead of building common agent patterns from scratch, you can grab skills for things like: → jev-route for routing tasks → jev-guardrail for adding checks and verification → jev-fanout for running multiple tasks in parallel → reusable skills you can plug into your own workflows the interesting part is that these solve problems you'll run into once your agents start doing more than simple tasks. you don't have to reinvent routing, verification, or parallel execution every time you build a new workflow. save this now. you'll probably need one of these skills the next time you're building an agent and don't want to start from scratch. repo below:

this is f**king dangerous. someone just open sourced an entire library of ready-made JEV skills for building insane AI agent workflows. instead of building common agent patterns from scratch, you can grab skills for things like: → jev-route for routing tasks → jev-guardrail for adding checks and verification → jev-fanout for running multiple tasks in parallel → reusable skills you can plug into your own workflows the interesting part is that these solve problems you'll run into once your agents start doing more than simple tasks. you don't have to reinvent routing, verification, or parallel execution every time you build a new workflow. save this now. you'll probably need one of these skills the next time you're building an agent and don't want to start from scratch. repo below:

131,315 次观看 • 18 天前

THIS WEBSITE IS INSANE It contains a huge collection of open-source tools in the browser that don't require registration to use. It includes tools in multiple categories: → Design and Graphics → Development → Productivity → Privacy and Security → AI → Education No accounts. No registrations needed to access them. Just open your browser and start using them Save this now!

THIS WEBSITE IS INSANE It contains a huge collection of open-source tools in the browser that don't require registration to use. It includes tools in multiple categories: → Design and Graphics → Development → Productivity → Privacy and Security → AI → Education No accounts. No registrations needed to access them. Just open your browser and start using them Save this now!

217,108 次观看 • 1 个月前

this is f**king insane. someone built a free Claude skills library that gives you hundreds of tools, agents, and expert personas in one place. the GitHub repo already has 26k+ stars. it gives you: → 305 Python tools with zero pip installs → skills for executing specific tasks → agents for handling different workflows → personas like senior architect, CTO, and security auditor → one command to convert the library to 11 different platforms and it's completely free. MIT licensed. with the right setup, Claude can take on a lot of the work you’d normally need different tools or people for. i actually broke down how to build a workflow around this idea in my article below. save this now.

this is f**king insane. someone built a free Claude skills library that gives you hundreds of tools, agents, and expert personas in one place. the GitHub repo already has 26k+ stars. it gives you: → 305 Python tools with zero pip installs → skills for executing specific tasks → agents for handling different workflows → personas like senior architect, CTO, and security auditor → one command to convert the library to 11 different platforms and it's completely free. MIT licensed. with the right setup, Claude can take on a lot of the work you’d normally need different tools or people for. i actually broke down how to build a workflow around this idea in my article below. save this now.

96,480 次观看 • 23 天前

THIS GUY USED CLAUDE TO BUILD A REAL TRADING BOT In just 17 minutes, he shows you how to build the same bot from scratch, refine the strategy, backtest it, and get it running. 🔖 save this before you lose it.

THIS GUY USED CLAUDE TO BUILD A REAL TRADING BOT In just 17 minutes, he shows you how to build the same bot from scratch, refine the strategy, backtest it, and get it running. 🔖 save this before you lose it.

137,170 次观看 • 1 个月前

I just built a collection of 163 insane motion graphics, and every graphic has the exact prompt that was used to create it right beside it. the gallery includes work made with Opus 5.5, GPT-6 Astra, Kimi K3 and Fable 5, with every creator credited. it’s free and i will be adding more go try it out:

I just built a collection of 163 insane motion graphics, and every graphic has the exact prompt that was used to create it right beside it. the gallery includes work made with Opus 5.5, GPT-6 Astra, Kimi K3 and Fable 5, with every creator credited. it’s free and i will be adding more go try it out:

25,755 次观看 • 9 天前

CLAUDE CODE CAN NOW TURN HIGGSFIELD INTO A ONE-PERSON AI VIDEO STUDIO. install this 19 skills, connect Claude Code to Higgsfield, then tell Claude what you want to create. run /ugc-hot-girl and let it create the character, generate the visuals, and produce the Seedance video for you. Claude controls Higgsfield through Playwright. you just review the output and make changes when needed. this is useful if you want to make UGC ads for brands without spending hours doing everything manually. you could even turn the workflow into a service and sell the finished content. if you’re building toward the solo creator income path, save this. repo below 👇

CLAUDE CODE CAN NOW TURN HIGGSFIELD INTO A ONE-PERSON AI VIDEO STUDIO. install this 19 skills, connect Claude Code to Higgsfield, then tell Claude what you want to create. run /ugc-hot-girl and let it create the character, generate the visuals, and produce the Seedance video for you. Claude controls Higgsfield through Playwright. you just review the output and make changes when needed. this is useful if you want to make UGC ads for brands without spending hours doing everything manually. you could even turn the workflow into a service and sell the finished content. if you’re building toward the solo creator income path, save this. repo below 👇

30,231 次观看 • 12 天前

Anthropic Engineer: “the biggest mistake in AI right now is people are building graphs and loops without a self-improving eval agent. we made that mistake at anthropic. it cost us two years.” here’s how they built what solved it: step 1 → take 50 real user prompts and run your agent. if it passes 80%+, your eval is too easy. the sweet spot is around 50%. step 2 → every failed run becomes a transcript. feed it to haiku: “what went wrong?” your eval set keeps growing on its own. step 3 → score two things: the right answer and the right path. a right answer with the wrong path will break later. step 4 → when a new model drops, run the same eval again. one model looked 9% better. but 6% of that gain came from hiding a bug. the transcript caught it. the dashboard didn’t. step 5 → plug your evals into ci. no green evals = no deploy. that’s how the system keeps improving itself. 99% of people never build this. but it pays for itself on day one. save this and build it today.

Anthropic Engineer: “the biggest mistake in AI right now is people are building graphs and loops without a self-improving eval agent. we made that mistake at anthropic. it cost us two years.” here’s how they built what solved it: step 1 → take 50 real user prompts and run your agent. if it passes 80%+, your eval is too easy. the sweet spot is around 50%. step 2 → every failed run becomes a transcript. feed it to haiku: “what went wrong?” your eval set keeps growing on its own. step 3 → score two things: the right answer and the right path. a right answer with the wrong path will break later. step 4 → when a new model drops, run the same eval again. one model looked 9% better. but 6% of that gain came from hiding a bug. the transcript caught it. the dashboard didn’t. step 5 → plug your evals into ci. no green evals = no deploy. that’s how the system keeps improving itself. 99% of people never build this. but it pays for itself on day one. save this and build it today.

102,478 次观看 • 2 个月前

this guy just showed how to find youtube niches with little to no competition using claude code. save this. you’ll need it later.

this guy just showed how to find youtube niches with little to no competition using claude code. save this. you’ll need it later.

122,686 次观看 • 3 个月前

don't spend money on courses to become an Al engineer in 2026. Andrew Ng just shared his Al Engineering Skills Map, and it breaks the whole journey into 4 simple skills: - build and launch Al apps - learn the basics of software engineering - use Al coding tools - know how to guide and improve what you're building this free 1.5-hour video explains all of it with practical examples. watch it, then start building. save this.

don't spend money on courses to become an Al engineer in 2026. Andrew Ng just shared his Al Engineering Skills Map, and it breaks the whole journey into 4 simple skills: - build and launch Al apps - learn the basics of software engineering - use Al coding tools - know how to guide and improve what you're building this free 1.5-hour video explains all of it with practical examples. watch it, then start building. save this.

62,860 次观看 • 2 个月前

this guy just wired kimi k3 directly into codex. the model is insanely good, but the app isn’t. so instead of using the kimi app, he connected his kimi subscription to codex through oauth. now kimi k3 shows up right inside the model picker alongside sol 5.6. no api key needed. no extra subscription either. just sign in with oauth through kimi code, and it’s ready to use. simple guides in the video and links below 👇

this guy just wired kimi k3 directly into codex. the model is insanely good, but the app isn’t. so instead of using the kimi app, he connected his kimi subscription to codex through oauth. now kimi k3 shows up right inside the model picker alongside sol 5.6. no api key needed. no extra subscription either. just sign in with oauth through kimi code, and it’s ready to use. simple guides in the video and links below 👇

58,904 次观看 • 2 个月前

13-minute tutorial showing how to create an award winning website with the kimi k3. save it before you lose it!

13-minute tutorial showing how to create an award winning website with the kimi k3. save it before you lose it!

23,327 次观看 • 1 个月前

Ex-Google engineer built a graph-based workflow that made Claude Code do nearly 10 days of work in about an hour. Here's the exact setup he uses. step 1. create a separate Git worktree for every task. run: git worktree add ../task-1 -b task-1 open a new terminal, cd into it, and launch Claude Code. repeat this for every agent. each one gets its own branch, so nothing conflicts. step 2. give every Claude agent a different task. same repository. different branches. they all work in parallel. step 3. once they're done, review the pull requests. keep the good ones. merge what works. step 4. add a review agent. paste each PR into Claude and ask: "does this implementation match the original specification" every agent now has another agent reviewing its work before it gets merged. step 5. scale it up. 48GB of RAM can comfortably run around 20 Claude Code agents. 128GB can handle roughly 50. most engineers run Claude Code once and wait. he runs dozens of Claude Code agents in parallel, then merges the best results. this 60-minute lecture is one of the best free resources on graph engineering and multi-agent workflows. bookmark it and watch it below.

Ex-Google engineer built a graph-based workflow that made Claude Code do nearly 10 days of work in about an hour. Here's the exact setup he uses. step 1. create a separate Git worktree for every task. run: git worktree add ../task-1 -b task-1 open a new terminal, cd into it, and launch Claude Code. repeat this for every agent. each one gets its own branch, so nothing conflicts. step 2. give every Claude agent a different task. same repository. different branches. they all work in parallel. step 3. once they're done, review the pull requests. keep the good ones. merge what works. step 4. add a review agent. paste each PR into Claude and ask: "does this implementation match the original specification" every agent now has another agent reviewing its work before it gets merged. step 5. scale it up. 48GB of RAM can comfortably run around 20 Claude Code agents. 128GB can handle roughly 50. most engineers run Claude Code once and wait. he runs dozens of Claude Code agents in parallel, then merges the best results. this 60-minute lecture is one of the best free resources on graph engineering and multi-agent workflows. bookmark it and watch it below.

32,199 次观看 • 2 个月前

🚨 this chinese guy makes over $1,000,000 a year… by building AI agents. no employees. no massive startup. he just keeps building. while most people are still asking ChatGPT random questions, he’s using Claude to build software that solves real problems. this is what people call vibe coding. he opens Claude and says: “build me an AI agent for real estate businesses that creates property videos.” Claude writes the code. builds the interface. adds subscriptions. helps deploy the app. within a day, he has a working product. then he starts building the next one. that’s the part most people don’t understand. he isn’t trying to build one billion-dollar company. he’s building dozens of AI agents, each solving one problem for one industry. → an AI agent for dentists → an AI agent for ecommerce brands → an AI agent for podcasters → an AI agent for real estate businesses each one automates work that people normally do by hand. each one is built with simple prompts. each one can become a real business. the crazy part? you don’t need to be a software engineer anymore. you need to know how to think like a builder. how to spot problems. how to explain solutions to AI. and how to ship. that’s exactly why i’m reading this article: “How to Actually Build Your First AI Agent.” because this is the skill that’s creating the next generation of builders. the people who learn to build AI agents today won’t just use AI. they’ll own the tools everyone else ends up paying for.

🚨 this chinese guy makes over $1,000,000 a year… by building AI agents. no employees. no massive startup. he just keeps building. while most people are still asking ChatGPT random questions, he’s using Claude to build software that solves real problems. this is what people call vibe coding. he opens Claude and says: “build me an AI agent for real estate businesses that creates property videos.” Claude writes the code. builds the interface. adds subscriptions. helps deploy the app. within a day, he has a working product. then he starts building the next one. that’s the part most people don’t understand. he isn’t trying to build one billion-dollar company. he’s building dozens of AI agents, each solving one problem for one industry. → an AI agent for dentists → an AI agent for ecommerce brands → an AI agent for podcasters → an AI agent for real estate businesses each one automates work that people normally do by hand. each one is built with simple prompts. each one can become a real business. the crazy part? you don’t need to be a software engineer anymore. you need to know how to think like a builder. how to spot problems. how to explain solutions to AI. and how to ship. that’s exactly why i’m reading this article: “How to Actually Build Your First AI Agent.” because this is the skill that’s creating the next generation of builders. the people who learn to build AI agents today won’t just use AI. they’ll own the tools everyone else ends up paying for.

39,041 次观看 • 3 个月前

Just found an open-source tool that lets you see how well an AI can actually use a computer. it’s called OSWorld 2.0. you give the AI a real task on a computer, then watch to see if it can figure everything out and finish it. it gives you: → real computer tasks, not simple questions → tasks that can take many steps to finish → the same computer setup for every AI → websites made for testing → all the files and tasks for free this is also the environment used to test computer-use systems from OpenAI and Anthropic. so if you’re building AI agents, researching computer use, or just want to see what these models can actually do, you can run the same tests yourself instead of relying only on benchmark scores. the labs publish the scores. this repo is where the actual tests come from. bookmark this.

Just found an open-source tool that lets you see how well an AI can actually use a computer. it’s called OSWorld 2.0. you give the AI a real task on a computer, then watch to see if it can figure everything out and finish it. it gives you: → real computer tasks, not simple questions → tasks that can take many steps to finish → the same computer setup for every AI → websites made for testing → all the files and tasks for free this is also the environment used to test computer-use systems from OpenAI and Anthropic. so if you’re building AI agents, researching computer use, or just want to see what these models can actually do, you can run the same tests yourself instead of relying only on benchmark scores. the labs publish the scores. this repo is where the actual tests come from. bookmark this.

14,387 次观看 • 1 个月前

google just dropped another free 8-minute lesson on building AI agents probably the easiest explanation of AI agents and agent loops you’ll find people are paying $500+ for AI agent courses google is giving it away for free it covers Agent Studio, loops, managed agents, Antigravity, and ADK 2.0 watch it first then read the full guide below

google just dropped another free 8-minute lesson on building AI agents probably the easiest explanation of AI agents and agent loops you’ll find people are paying $500+ for AI agent courses google is giving it away for free it covers Agent Studio, loops, managed agents, Antigravity, and ADK 2.0 watch it first then read the full guide below

35,923 次观看 • 3 个月前

anthropic research lead: “99% of our engineers use 300+ AI agents working together.” “close the loop. let the AI check its own work.” in a 20-minute talk, an Anthropic team member explains how to build AI agents that can improve themselves. the setup uses Claude with loops, plan mode, and smart workflows. it’s better than most $300 AI agent courses. bookmark this and watch the talk. then read the article below.

anthropic research lead: “99% of our engineers use 300+ AI agents working together.” “close the loop. let the AI check its own work.” in a 20-minute talk, an Anthropic team member explains how to build AI agents that can improve themselves. the setup uses Claude with loops, plan mode, and smart workflows. it’s better than most $300 AI agent courses. bookmark this and watch the talk. then read the article below.

34,813 次观看 • 3 个月前

Fable 5 access just got extended again. update Claude Code to 2.1.170 connect it to a structured Agent OS and spend the extra time building something you’ll still be using long after the promo ends

Fable 5 access just got extended again. update Claude Code to 2.1.170 connect it to a structured Agent OS and spend the extra time building something you’ll still be using long after the promo ends

29,187 次观看 • 3 个月前

I gave EvoX Agent a broken Polymarket trading bot and told it to find out what was wrong. I didn't point it to any files or give it hints. It went through the project, found 3 bugs, fixed them, and even found one I didn't know existed 🧵

I gave EvoX Agent a broken Polymarket trading bot and told it to find out what was wrong. I didn't point it to any files or give it hints. It went through the project, found 3 bugs, fixed them, and even found one I didn't know existed 🧵

12,613 次观看 • 1 个月前

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 👇

26,662 次观看 • 3 个月前