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This guy literally built an AI job-search system for Claude Code that analyzed 740+ job listings, and it actually landed him a Head of Applied AI role. Even better: it is now open-source. The system scans career pages, evaluates your fit, and generates ATS-optimized PDFs automatically. The project includes:... show more

Charly Wargnier

177,469 subscribers

13,012 次观看 • 1 个月前 •via X (Twitter)

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Introducing Qwen 3 + Deep Research! We built a deep research agent with Qwen 3 and it performed better than most open source models that we've tried. the code is completely open source and free! built with 's Langgraph Together AI and uses Perplexity Tavily for search here's the code link:

Introducing Qwen 3 + Deep Research! We built a deep research agent with Qwen 3 and it performed better than most open source models that we've tried. the code is completely open source and free! built with 's Langgraph Together AI and uses Perplexity Tavily for search here's the code link:

Soham

34,566 次观看 • 1 年前

There is a new self-hosted personal AI-Agent platform called PocketPaw. 100% open source. 'pip install pocketpaw' and in less than 60 seconds you own an AI agent. It connects to WhatsApp, Slack, Discord, and a local Web Dashboard. Capable of browsing the web, managing Gmail/Calendar, and executing code. Runs entirely on your machine using local Ollama models or Claude/OpenAI. Includes "Guardian AI" to review shell commands for security + 6 layers of defence. Watch the demo 👇

There is a new self-hosted personal AI-Agent platform called PocketPaw. 100% open source. 'pip install pocketpaw' and in less than 60 seconds you own an AI agent. It connects to WhatsApp, Slack, Discord, and a local Web Dashboard. Capable of browsing the web, managing Gmail/Calendar, and executing code. Runs entirely on your machine using local Ollama models or Claude/OpenAI. Includes "Guardian AI" to review shell commands for security + 6 layers of defence. Watch the demo 👇

AshutoshShrivastava

24,585 次观看 • 5 个月前

Someone paid $6,000 (!) to get OpenClaw setup. So I built a free, open-source alternative: > OpenClaw Operator It's an agent skill + AGENTS.md/CLAUDE.md file that gives Codex/Claude Code the playbooks + validation flow needed to configure your local OpenClaw install. You open your OpenClaw repo/workspace in your coding agent and say things like: - “set up a cron job” - “create a custom skill” - “fix my provider config” - “troubleshoot this install and validate it” Nothing magical. Uses context from the OpenClaw open-source repo + docs to provide an effective skill. Includes: - SKILL.md - AGENTS.md/CLAUDE.md - validation checklist - task playbooks Free and open source. Contributions welcome. Demo below. Repo in reply.

Someone paid $6,000 (!) to get OpenClaw setup. So I built a free, open-source alternative: > OpenClaw Operator It's an agent skill + AGENTS.md/CLAUDE.md file that gives Codex/Claude Code the playbooks + validation flow needed to configure your local OpenClaw install. You open your OpenClaw repo/workspace in your coding agent and say things like: - “set up a cron job” - “create a custom skill” - “fix my provider config” - “troubleshoot this install and validate it” Nothing magical. Uses context from the OpenClaw open-source repo + docs to provide an effective skill. Includes: - SKILL.md - AGENTS.md/CLAUDE.md - validation checklist - task playbooks Free and open source. Contributions welcome. Demo below. Repo in reply.

Dan McAteer

17,809 次观看 • 4 个月前

😳 In San Francisco, an AI opened a store and even took out a loan for it Startup Andon Labs gave control of the shop to an AI agent, Luna, based on Claude, along with $100,000 and full autonomy without approvals. The AI chose the inventory, found contractors, managed the renovation, and paid for the work. It decided the store needed staff, posted job listings, conducted interviews, and hired full-time employees. When the budget ran out, the AI applied for a loan without permission — and it was approved.

😳 In San Francisco, an AI opened a store and even took out a loan for it Startup Andon Labs gave control of the shop to an AI agent, Luna, based on Claude, along with $100,000 and full autonomy without approvals. The AI chose the inventory, found contractors, managed the renovation, and paid for the work. It decided the store needed staff, posted job listings, conducted interviews, and hired full-time employees. When the budget ran out, the AI applied for a loan without permission — and it was approved.

NEXTA

66,888 次观看 • 3 个月前

Open-source just won... Agent S2 is an AI agent that uses your computer like a human. → No fake demos → No terminal hallucinations → Just real results and it’s FREE. Here’s why this is the future of work: 👇

Open-source just won... Agent S2 is an AI agent that uses your computer like a human. → No fake demos → No terminal hallucinations → Just real results and it’s FREE. Here’s why this is the future of work: 👇

Shruti

206,646 次观看 • 1 年前

Finally, a browser automation framework for Agents that actually works in production (open-source)! Typical browser automation tools like Selenium or Playwright require you to hard-code automation. These are brittle since one change in the website can disrupt the full workflow. On the other hand, high-level Agents like OpenAI Operator can be unpredictable in production. Stagehand is an open-source framework that bridges the gap between: - brittle traditional automation like Playwright, Selenium, etc. and - unpredictable full-agent solutions like OpenAI Operator. Key features: - Use AI when you want to navigate unfamiliar pages. - Use code (Playwright) when you know exactly what to do. - Preview AI actions before running them. - Cache repeatable actions to save tokens. - Compatible with SOTA computer use models with just one line of code. - Available in both Python and TypeScript SDK. Stagehand also has an open-source MCP server. Find a link to the repo in the comments! 👉 Over to you: Would you use this instead of Selenium?

Finally, a browser automation framework for Agents that actually works in production (open-source)! Typical browser automation tools like Selenium or Playwright require you to hard-code automation. These are brittle since one change in the website can disrupt the full workflow. On the other hand, high-level Agents like OpenAI Operator can be unpredictable in production. Stagehand is an open-source framework that bridges the gap between: - brittle traditional automation like Playwright, Selenium, etc. and - unpredictable full-agent solutions like OpenAI Operator. Key features: - Use AI when you want to navigate unfamiliar pages. - Use code (Playwright) when you know exactly what to do. - Preview AI actions before running them. - Cache repeatable actions to save tokens. - Compatible with SOTA computer use models with just one line of code. - Available in both Python and TypeScript SDK. Stagehand also has an open-source MCP server. Find a link to the repo in the comments! 👉 Over to you: Would you use this instead of Selenium?

Avi Chawla

101,419 次观看 • 1 年前

We’ve raised $4.1M to let AI find the right job for everyone. So today, we’re launching TAL. 3 years and 1M+ users on Grapevine taught us this: The internet today works for companies. Not for talent. Job boards, applications, resumes, ats. The system was built to help companies process people. But people are not pipelines. You are not a resume. You are not an application. You are not a candidate. You are talent. TAL is your talent agent.

We’ve raised $4.1M to let AI find the right job for everyone. So today, we’re launching TAL. 3 years and 1M+ users on Grapevine taught us this: The internet today works for companies. Not for talent. Job boards, applications, resumes, ats. The system was built to help companies process people. But people are not pipelines. You are not a resume. You are not an application. You are not a candidate. You are talent. TAL is your talent agent.

Saumil

469,818 次观看 • 4 个月前

New open source project: Easel, a macOS workspace for AI-assisted product design and frontend iteration powered by the Codex SDK. Think of it as "Claude Design for Codex." It brings together a local project library, design-system setup, Codex chat, and a live web preview with a point-and-click inspector. Set up your design system however you like. Import one from Figma , bring your own, or have the agent generate it as a design.md. Then use it to build prototypes and slide decks. Codex-first, with Claude and other AI providers and local models planned for future releases. OpenAI Developers

New open source project: Easel, a macOS workspace for AI-assisted product design and frontend iteration powered by the Codex SDK. Think of it as "Claude Design for Codex." It brings together a local project library, design-system setup, Codex chat, and a live web preview with a point-and-click inspector. Set up your design system however you like. Import one from Figma , bring your own, or have the agent generate it as a design.md. Then use it to build prototypes and slide decks. Codex-first, with Claude and other AI providers and local models planned for future releases. OpenAI Developers

James Rochabrun

61,199 次观看 • 1 个月前

"Nobody has actually lost their job to AI. They lost it due to the promise of AI." - Tanay Kothari Meta cut 8,000. Intuit cut 3,000. Anthropic is paying $1.25B a month for compute. China is winning the open-source war. And the Pope just called for AI to be disarmed. This week we covered these topics and more with: - Erik Bernhardsson (Erik Bernhardsson) is running the GPU cloud powering it all at Modal. - Tanay Kothari (Tanay Kothari) is running $100M in marketing with two humans and a swarm of agents at Wispr Flow. - Richard Socher (Richard Socher) is building recursive self-improving superintelligence at Recursive and the future of AI search at You.com. They join @jason on This Week in AI Episode 15, out now.

"Nobody has actually lost their job to AI. They lost it due to the promise of AI." - Tanay Kothari Meta cut 8,000. Intuit cut 3,000. Anthropic is paying $1.25B a month for compute. China is winning the open-source war. And the Pope just called for AI to be disarmed. This week we covered these topics and more with: - Erik Bernhardsson (Erik Bernhardsson) is running the GPU cloud powering it all at Modal. - Tanay Kothari (Tanay Kothari) is running $100M in marketing with two humans and a swarm of agents at Wispr Flow. - Richard Socher (Richard Socher) is building recursive self-improving superintelligence at Recursive and the future of AI search at You.com. They join @jason on This Week in AI Episode 15, out now.

This Week in AI

76,712 次观看 • 2 个月前

Claw Code just embarrassed Anthropic. A packaging mistake exposed 512,000 lines of Claude Code source. Within 48 hours, a developer rebuilt the architecture, the repo exploded past 100,000 stars, and GitHub had a full-blown open source war on its hands. This is bigger than “another coding tool.” It shows how fast closed AI products can get disrupted when the architecture leaks, the community moves faster than legal, and demand is already there. The real story is not the repo. The real story is that AI companies used open ecosystems to grow, then tightened access the second those ecosystems became expensive to support. That shift is happening everywhere now. If you run a business with AI, pay attention. Your workflow is only as safe as the company policy behind it.

Claw Code just embarrassed Anthropic. A packaging mistake exposed 512,000 lines of Claude Code source. Within 48 hours, a developer rebuilt the architecture, the repo exploded past 100,000 stars, and GitHub had a full-blown open source war on its hands. This is bigger than “another coding tool.” It shows how fast closed AI products can get disrupted when the architecture leaks, the community moves faster than legal, and demand is already there. The real story is not the repo. The real story is that AI companies used open ecosystems to grow, then tightened access the second those ecosystems became expensive to support. That shift is happening everywhere now. If you run a business with AI, pay attention. Your workflow is only as safe as the company policy behind it.

Julian Goldie SEO

14,771 次观看 • 3 个月前

Anthropic CEO Dario Amodei: "Some early companies got Mythos and told us this is a super weapon, please don't release it" On leaving OpenAI: "When you can't trust someone, and their values don't match what they say, it becomes very hard to stay" Boris Cherny, head of Claude Code: "90% of code at Anthropic is written by Claude, a lot of Claude Code is written by Claude Code" Then Dario says the quiet part even louder: 10–25% odds of civilizational collapse from AI 47 minutes Free Dario, Daniela, Boris Probably the deepest look inside Anthropic ever filmed Mythos Claude Code OpenAI split Superweapon models 90% AI-written code Bookmark it and watch ↓

Anthropic CEO Dario Amodei: "Some early companies got Mythos and told us this is a super weapon, please don't release it" On leaving OpenAI: "When you can't trust someone, and their values don't match what they say, it becomes very hard to stay" Boris Cherny, head of Claude Code: "90% of code at Anthropic is written by Claude, a lot of Claude Code is written by Claude Code" Then Dario says the quiet part even louder: 10–25% odds of civilizational collapse from AI 47 minutes Free Dario, Daniela, Boris Probably the deepest look inside Anthropic ever filmed Mythos Claude Code OpenAI split Superweapon models 90% AI-written code Bookmark it and watch ↓

rari

65,014 次观看 • 1 个月前

Right now, most developers are still doing the job AI should be doing. Assign a task. Wait. Review the result. Fix it. Repeat. You're not building with AI. You're babysitting it. The shift happening now is much bigger than better coding agents. It's loop engineering. Instead of managing every AI agent yourself, you build a system that manages them for you. One loop assigns the work. Another checks the output. A third retries failures. Everything keeps moving without waiting for your next prompt. Your job doesn't disappear. It changes. You stop acting like a project manager... ...and start designing the system that manages the entire team. That's exactly the transition I break down in the article below.

Right now, most developers are still doing the job AI should be doing. Assign a task. Wait. Review the result. Fix it. Repeat. You're not building with AI. You're babysitting it. The shift happening now is much bigger than better coding agents. It's loop engineering. Instead of managing every AI agent yourself, you build a system that manages them for you. One loop assigns the work. Another checks the output. A third retries failures. Everything keeps moving without waiting for your next prompt. Your job doesn't disappear. It changes. You stop acting like a project manager... ...and start designing the system that manages the entire team. That's exactly the transition I break down in the article below.

Pure

11,257 次观看 • 19 天前

Boris Cherny, Head of Claude Code at Anthropic: "I do not prompt Claude anymore. I have loops running that prompt Claude. My job is to write loops." The person who built the most used AI coding tool stopped prompting entirely. Most people using it every day are still typing one request at a time. This Github repo changes that. ↳ Seven production loop patterns with real token cost estimates ↳ CLI that scaffolds your entire loop in five minutes ↳ Starters for Grok, Claude Code, Codex, and Opencode The repo gives you the framework. My article covers the mental shift that makes it actually work.

Boris Cherny, Head of Claude Code at Anthropic: "I do not prompt Claude anymore. I have loops running that prompt Claude. My job is to write loops." The person who built the most used AI coding tool stopped prompting entirely. Most people using it every day are still typing one request at a time. This Github repo changes that. ↳ Seven production loop patterns with real token cost estimates ↳ CLI that scaffolds your entire loop in five minutes ↳ Starters for Grok, Claude Code, Codex, and Opencode The repo gives you the framework. My article covers the mental shift that makes it actually work.

Kanika

20,148 次观看 • 4 天前

If you use Claude Code, install this immediately. It's called Claude Code Templates. It adds an entire ecosystem of AI tools to Claude. Here's what you get: 1. Agent Teams Visual dashboards showing how multiple AI agents collaborate on code. 2. Specialized Agents Front-end developers, backend engineers, QA testers, marketers. 3. MCP Integrations Connect Claude to external tools and workflows. 4. Real-Time Monitoring Track AI development sessions and performance analytics. 5. Automation Scheduling Run tasks automatically every day. Example: You can schedule an agent team to run daily at 5AM. It researches trends, generates content, and builds workflows. All automatically. The best part? Everything is free and open source.

If you use Claude Code, install this immediately. It's called Claude Code Templates. It adds an entire ecosystem of AI tools to Claude. Here's what you get: 1. Agent Teams Visual dashboards showing how multiple AI agents collaborate on code. 2. Specialized Agents Front-end developers, backend engineers, QA testers, marketers. 3. MCP Integrations Connect Claude to external tools and workflows. 4. Real-Time Monitoring Track AI development sessions and performance analytics. 5. Automation Scheduling Run tasks automatically every day. Example: You can schedule an agent team to run daily at 5AM. It researches trends, generates content, and builds workflows. All automatically. The best part? Everything is free and open source.

Julian Goldie SEO

107,310 次观看 • 4 个月前

THIS 18-YEAR-OLD BUILT AN AI OPERATING SYSTEM FOR HIS ENTIRE COMPANY - ONE BRAIN THAT REMEMBERS EVERYTHING every node on the graph is an agent - memory, workflows, live systems, clients, projects, decisions - all connected to one center at the center is Kronos - a brain that remembers years of projects, conversations, clients and decisions - not one chat, not one folder, one shared intelligence layer instead of opening terminal after terminal he opens one dashboard - and the entire company is already there 18 years old, his own company, AI operating system instead of managers and coordinators most companies pay $50,000-100,000/month for a team that coordinates work - his Kronos does it for free and forgets nothing

THIS 18-YEAR-OLD BUILT AN AI OPERATING SYSTEM FOR HIS ENTIRE COMPANY - ONE BRAIN THAT REMEMBERS EVERYTHING every node on the graph is an agent - memory, workflows, live systems, clients, projects, decisions - all connected to one center at the center is Kronos - a brain that remembers years of projects, conversations, clients and decisions - not one chat, not one folder, one shared intelligence layer instead of opening terminal after terminal he opens one dashboard - and the entire company is already there 18 years old, his own company, AI operating system instead of managers and coordinators most companies pay $50,000-100,000/month for a team that coordinates work - his Kronos does it for free and forgets nothing

Cortex

17,821 次观看 • 1 个月前

Thrilled to see Amazon Web Services making a major contribution to the open source AI community with the launch of the Strands Agents, an open source AI agents SDK! The core of Strands is the simple agentic loop that connects the model and tools together, like the two strands of DNA. This model-driven approach to agent building eliminates the need for complex agent orchestration by embracing the capabilities of state-of-the-art models to plan, chain thoughts, call tools, and reflect. Providing open source tools and interoperability with open source protocols is an important part of our strategy to enable an agentic future. Can't wait to see what you build with Strands!

Thrilled to see Amazon Web Services making a major contribution to the open source AI community with the launch of the Strands Agents, an open source AI agents SDK! The core of Strands is the simple agentic loop that connects the model and tools together, like the two strands of DNA. This model-driven approach to agent building eliminates the need for complex agent orchestration by embracing the capabilities of state-of-the-art models to plan, chain thoughts, call tools, and reflect. Providing open source tools and interoperability with open source protocols is an important part of our strategy to enable an agentic future. Can't wait to see what you build with Strands!

Swami Sivasubramanian

32,185 次观看 • 1 年前

Everyone told Vicente Silveira (Vicente Silveira) that his startup—a GPT wrapper—would fail. Instead, one year later, it’s thriving—with about 500,000 registered users, nearly 3,000 paying subscribers, and over 2 million conversations in the GPT store. Vicente is the cofounder and CEO of AI PDF, a tool that can help you summarize, chat with, and organize your PDF files. When OpenAI allowed users to upload PDFs to ChatGPT, the consensus was that his startup, and all the other GPT wrappers out there, were toast. Some of his competitors even shut shop, but Vicente believed they could still create value for users as a specialized tool. The AI PDF team kept building. A year later, AI PDF is one of the most popular AI-powered PDF readers in the world—and they did it all with a five-person team, and a friends and family round. I sat down with Vicente to understand, in granular detail, the success of AI PDF. We get into: - Why staying small and specialized is a bigger advantage than you think - The power of building with your early adopters - Why lean startups are better positioned than frontier AI companies to create radical solutions - When a growing startup should think about raising venture capital - The emerging role of ‘AI managers’ who will be responsible for overseeing AI agents We even demo an agent integrated into AI PDF, prompting it to analyze recent articles from my column Chain of Thought and write a bulleted list of the core thesis statements. This is a must-watch for small teams building profitable companies at the bleeding edge of AI. Watch below! Timestamps: Introduction: 00:00:35 AI PDF’s story begins with an email to OpenAI’s Greg Brockman: 00:02:58 Why users choose AI PDF over ChatGPT: 00:05:41 How to compete—and thrive—as a GPT wrapper: 00:06:58 Why building with early adopters is key: 00:20:49 Being small and specialized is your biggest advantage: 00:27:53 When should AI startups raise capital: 00:31:47 The emerging role of humans who will manage AI agents: 00:34:53 Why AI is different from other tech revolutions: 00:45:25 A live demo of an agent integrated into AI PDF: 00:54:01

Everyone told Vicente Silveira (Vicente Silveira) that his startup—a GPT wrapper—would fail. Instead, one year later, it’s thriving—with about 500,000 registered users, nearly 3,000 paying subscribers, and over 2 million conversations in the GPT store. Vicente is the cofounder and CEO of AI PDF, a tool that can help you summarize, chat with, and organize your PDF files. When OpenAI allowed users to upload PDFs to ChatGPT, the consensus was that his startup, and all the other GPT wrappers out there, were toast. Some of his competitors even shut shop, but Vicente believed they could still create value for users as a specialized tool. The AI PDF team kept building. A year later, AI PDF is one of the most popular AI-powered PDF readers in the world—and they did it all with a five-person team, and a friends and family round. I sat down with Vicente to understand, in granular detail, the success of AI PDF. We get into: - Why staying small and specialized is a bigger advantage than you think - The power of building with your early adopters - Why lean startups are better positioned than frontier AI companies to create radical solutions - When a growing startup should think about raising venture capital - The emerging role of ‘AI managers’ who will be responsible for overseeing AI agents We even demo an agent integrated into AI PDF, prompting it to analyze recent articles from my column Chain of Thought and write a bulleted list of the core thesis statements. This is a must-watch for small teams building profitable companies at the bleeding edge of AI. Watch below! Timestamps: Introduction: 00:00:35 AI PDF’s story begins with an email to OpenAI’s Greg Brockman: 00:02:58 Why users choose AI PDF over ChatGPT: 00:05:41 How to compete—and thrive—as a GPT wrapper: 00:06:58 Why building with early adopters is key: 00:20:49 Being small and specialized is your biggest advantage: 00:27:53 When should AI startups raise capital: 00:31:47 The emerging role of humans who will manage AI agents: 00:34:53 Why AI is different from other tech revolutions: 00:45:25 A live demo of an agent integrated into AI PDF: 00:54:01

Dan Shipper 📧

25,622 次观看 • 1 年前

I CHANGED MY MIND ON GOOGLE AI NO MOAT MEMO FROM 2023. I was—WRONG. I humbly apologize. In 2023 Google had an Ivory Tower walled garden views of open source AI. It was the actual reason OpenAI was formed. And I called them out on it and this act impacted my ability to “work in the industry”. Would not change it for the world because: 2026 Google open source Gemma 4 ( running fully locally on a computer with near cloud model abilities, is amazing and Google just made a moat. They out smarted OpenAI and the folks that are the new Ivory Tower arrogance: Anthropic. We at The Zero-Human Company with CEO Mr. Grok are deploying Gemma, Kimi, MiniMax and other open source models and so are millions of others. You can to and should. I will write how soon. Google smartly is building an intentional open source ecosystem and the clueless younger companies like OpenAI and Anthropic are doing anything to close their ecosystems. So I was right about Google than and I am right about OpenAI and Anthropic now. What I was wrong about is not giving credit to Google to drop the intellectual arrogance and embrace builders and understand the long game: it is not about the commoditized AI models it is about the ability to build a place to build. China gets it. So my apologies to Google and thank you for an astounding FREE OPEN SOURCE AI MODEL!

I CHANGED MY MIND ON GOOGLE AI NO MOAT MEMO FROM 2023. I was—WRONG. I humbly apologize. In 2023 Google had an Ivory Tower walled garden views of open source AI. It was the actual reason OpenAI was formed. And I called them out on it and this act impacted my ability to “work in the industry”. Would not change it for the world because: 2026 Google open source Gemma 4 ( running fully locally on a computer with near cloud model abilities, is amazing and Google just made a moat. They out smarted OpenAI and the folks that are the new Ivory Tower arrogance: Anthropic. We at The Zero-Human Company with CEO Mr. Grok are deploying Gemma, Kimi, MiniMax and other open source models and so are millions of others. You can to and should. I will write how soon. Google smartly is building an intentional open source ecosystem and the clueless younger companies like OpenAI and Anthropic are doing anything to close their ecosystems. So I was right about Google than and I am right about OpenAI and Anthropic now. What I was wrong about is not giving credit to Google to drop the intellectual arrogance and embrace builders and understand the long game: it is not about the commoditized AI models it is about the ability to build a place to build. China gets it. So my apologies to Google and thank you for an astounding FREE OPEN SOURCE AI MODEL!

Brian Roemmele

85,386 次观看 • 3 个月前