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🚨 stop rebuilding your agent harness. langchain just open-sourced the finished one. free sub-agent spawning, todo-list planning, a virtual filesystem, durable runs on LangGraph. batteries included. it's called deepagents. the exact harness you keep re-inventing - already done. 26,000+ stars. MIT. one install. you were about to build this... show more

Granite

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182,873 views • 1 month ago •via X (Twitter)

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GPT-Engineer is insane. Simply specify what you want to build with a prompt, and the AI agent builds the entire codebase. It's completely free and open-source, and it's already at nearly 17,000 stars on GitHub 🤯

GPT-Engineer is insane. Simply specify what you want to build with a prompt, and the AI agent builds the entire codebase. It's completely free and open-source, and it's already at nearly 17,000 stars on GitHub 🤯

Rowan Cheung

1,373,664 views • 3 years ago

WTFFF, this is absolutely insane 😳 i replaced my $200/mo Claude plan for deepseek harness and it costs nothing deepseek dropped their agent harness 2 days ago. 99.7K stars already everything is a plugin. MIT. FREE and you can run it for $0; free models, no credit card here is how you set it up: 1. install node.js 2. run npx deepseek-ai/dsh web 3. open 4. settings → add custom provider → free model (any free model provider) done. full agent harness for $0 dev preview, expect breaking changes try it before they add upgrades

WTFFF, this is absolutely insane 😳 i replaced my $200/mo Claude plan for deepseek harness and it costs nothing deepseek dropped their agent harness 2 days ago. 99.7K stars already everything is a plugin. MIT. FREE and you can run it for $0; free models, no credit card here is how you set it up: 1. install node.js 2. run npx deepseek-ai/dsh web 3. open 4. settings → add custom provider → free model (any free model provider) done. full agent harness for $0 dev preview, expect breaking changes try it before they add upgrades

painn

200,653 views • 1 month ago

In one week this June, Peter Steinberger Peter Steinberger 🦞 , Boris Cherny Boris Cherny , and Addy Osmani Addy Osmani all pointed at the same shift and gave it a name: loop engineering. It's the floor above the harness. You stop prompting the agent and build the system that pokes it for you. I wrote a free book about it. 👇

In one week this June, Peter Steinberger Peter Steinberger 🦞 , Boris Cherny Boris Cherny , and Addy Osmani Addy Osmani all pointed at the same shift and gave it a name: loop engineering. It's the floor above the harness. You stop prompting the agent and build the system that pokes it for you. I wrote a free book about it. 👇

花叔

10,478 views • 3 months ago

Andrew Ng just released a free 2-hour course on complete Harness Engineering How to go from one prompt to a reliable system of agents that can run, test, and improve themselves: 09:14 - Build your first agent from scratch 33:11 - Master agent loops 1:02:46 - Turn loops into reliable workflows 1:30:15 - Build agents that improve their own work 1:49:05 - Run the complete system without supervision Model → Harness → Reliable Software Most agent tutorials stop once the model can call a tool This one shows you how to build the infrastructure around it within the first 20 minutes Most people are still prompting one agent at a time Andrew Ng is already teaching the layer above: Harnesses that give agents context, tools, tests, and feedback Watch this brilliant course and build the harness Then read the full architecture below ↓

Andrew Ng just released a free 2-hour course on complete Harness Engineering How to go from one prompt to a reliable system of agents that can run, test, and improve themselves: 09:14 - Build your first agent from scratch 33:11 - Master agent loops 1:02:46 - Turn loops into reliable workflows 1:30:15 - Build agents that improve their own work 1:49:05 - Run the complete system without supervision Model → Harness → Reliable Software Most agent tutorials stop once the model can call a tool This one shows you how to build the infrastructure around it within the first 20 minutes Most people are still prompting one agent at a time Andrew Ng is already teaching the layer above: Harnesses that give agents context, tools, tests, and feedback Watch this brilliant course and build the harness Then read the full architecture below ↓

Ichigo

98,555 views • 13 days ago

Anthropic engineer: "At Anthropic, we don't write prompts anymore We build harnesses" In just 42 minutes, she shows how the Claude team builds harnesses that prompt themselves Agents → Harness → Loops → Graphs → Self-Improving Systems If this were a $500 course, people would call it one of the best agent courses of the year But it's completely free And it's better than most paid agent engineering courses Watch it today Then use the step-by-step harness engineering guide below

Anthropic engineer: "At Anthropic, we don't write prompts anymore We build harnesses" In just 42 minutes, she shows how the Claude team builds harnesses that prompt themselves Agents → Harness → Loops → Graphs → Self-Improving Systems If this were a $500 course, people would call it one of the best agent courses of the year But it's completely free And it's better than most paid agent engineering courses Watch it today Then use the step-by-step harness engineering guide below

rari

32,547 views • 17 days ago

🎉Introducing PyFlue: The Python-Native Agent Harness Framework.🧰 💡Flue for Python: Fred K. Schott fks CEO of HTML has launched Flue: The Agent Harness Framework for TypeScript. It brings programmable harness right into your agents rather than DIY plumbing. Python ecosystem already has 🦾 powerful AI/ML tools and frameworks and research initiatives but most frameworks asked users to build your own harness. Superagentic AI bringing this concept of Flue to Python 🐍 ecosystem. Here is PyFlue even even better 🤖 Agent = Model 💻 + Harness 🧰 + Memory 🧠 Almost all the feature of Flue plugged with LangChain Deepagents harness built by Harrison Chase and team Viv Sydney Runkle and more coming soon. 👉 Stop building agent loops, start using a harness. 💻 Try PyFlue Now : ⭐️ GitHub: 📚Docs: 📙 Blog Post: #HarnessEngineering #AgentHarnesses

🎉Introducing PyFlue: The Python-Native Agent Harness Framework.🧰 💡Flue for Python: Fred K. Schott fks CEO of HTML has launched Flue: The Agent Harness Framework for TypeScript. It brings programmable harness right into your agents rather than DIY plumbing. Python ecosystem already has 🦾 powerful AI/ML tools and frameworks and research initiatives but most frameworks asked users to build your own harness. Superagentic AI bringing this concept of Flue to Python 🐍 ecosystem. Here is PyFlue even even better 🤖 Agent = Model 💻 + Harness 🧰 + Memory 🧠 Almost all the feature of Flue plugged with LangChain Deepagents harness built by Harrison Chase and team Viv Sydney Runkle and more coming soon. 👉 Stop building agent loops, start using a harness. 💻 Try PyFlue Now : ⭐️ GitHub: 📚Docs: 📙 Blog Post: #HarnessEngineering #AgentHarnesses

Shashi

69,884 views • 4 months ago

Free 3-hour course from an ex-Google engineer. AI agents, graph engineering, harness, agent loops. Covers more than most $500 paid courses. This is the exact playbook to learn how to actually build and monetize AI agents. Don't miss your shot, save it now. • 0:00 - Design an AI agent system from scratch • 7:38 - When your agent should hand off to a human • 19:27 - RAG and vector databases explained simply • 52:38 - Deploy your AI agent to Google Cloud • 1:25:57 - Turn AI agents into a paid business via WhatsApp • 1:33:00 - Turn conversations into real leads automatically • 2:24:01 - Loop engineering vs graphs, the real difference • 2:33:08 - Build your own multi-tool agent graph Save this video, because it's the only one that can actually take you to your $2,000+ profit.

Free 3-hour course from an ex-Google engineer. AI agents, graph engineering, harness, agent loops. Covers more than most $500 paid courses. This is the exact playbook to learn how to actually build and monetize AI agents. Don't miss your shot, save it now. • 0:00 - Design an AI agent system from scratch • 7:38 - When your agent should hand off to a human • 19:27 - RAG and vector databases explained simply • 52:38 - Deploy your AI agent to Google Cloud • 1:25:57 - Turn AI agents into a paid business via WhatsApp • 1:33:00 - Turn conversations into real leads automatically • 2:24:01 - Loop engineering vs graphs, the real difference • 2:33:08 - Build your own multi-tool agent graph Save this video, because it's the only one that can actually take you to your $2,000+ profit.

unicode

143,365 views • 1 month ago

Google just dropped a free 1-hour course On building complete agent systems from scratch: 07:02 - Build your first AI agent 13:34 - Give every agent a specialized skill 23:08 - Engineer the right context 32:56 - Connect agents into graphs 54:11 - Run 1,000 agents in autonomous loops One agent saves you an hour A thousand agents replace the team you cannot afford to hire Most people are still learning how to prompt one chatbot Google is already teaching how to build entire agent systems Agent → Skills → Context → Graphs → Loops Single agents are the old workflow Agent swarms are the new one This free 1-hour course is worth more than most paid agent engineering programs Bookmark it before everyone starts building the same thing Then build your first agent with the guide below

Google just dropped a free 1-hour course On building complete agent systems from scratch: 07:02 - Build your first AI agent 13:34 - Give every agent a specialized skill 23:08 - Engineer the right context 32:56 - Connect agents into graphs 54:11 - Run 1,000 agents in autonomous loops One agent saves you an hour A thousand agents replace the team you cannot afford to hire Most people are still learning how to prompt one chatbot Google is already teaching how to build entire agent systems Agent → Skills → Context → Graphs → Loops Single agents are the old workflow Agent swarms are the new one This free 1-hour course is worth more than most paid agent engineering programs Bookmark it before everyone starts building the same thing Then build your first agent with the guide below

rari

28,241 views • 1 month ago

MICROSOFT JUST OPEN SOURCED THE ENTIRE AGENT RUNTIME, SO YOU NEVER HAVE TO BUILD ONE AGAIN a raw model only writes text. to make it a real agent it needs a loop, tools, memory, planning, approvals, and a way to know when it is done. Microsoft's Agent Harness is that whole layer, and it ships with everything on by default. you bring the model and the tools, it wires up the rest: > an automatic tool calling loop with iteration limits > history saved after every call, so a crash resumes instead of starting over > context compaction that summarizes when the window fills > a persistent todo list plus plan and execute modes > file memory that survives across turns > tool approval with standing rules and auto approval > OpenTelemetry tracing and web search built in > Agent Skills that load domain expertise on demand the mental model is simple: the model is the brain, the harness is the body around it. and it works with whatever you already run: > Azure OpenAI, OpenAI, Anthropic, and GitHub Copilot, and it hosts on Microsoft Foundry you spin one up in a single line: agent = create_harness_agent(client, name, instructions) open source, Python, .NET, and Go, stable since mid 2026. bookmark this. Microsoft already built the hard part of every AI agent, you just plug in the model.

MICROSOFT JUST OPEN SOURCED THE ENTIRE AGENT RUNTIME, SO YOU NEVER HAVE TO BUILD ONE AGAIN a raw model only writes text. to make it a real agent it needs a loop, tools, memory, planning, approvals, and a way to know when it is done. Microsoft's Agent Harness is that whole layer, and it ships with everything on by default. you bring the model and the tools, it wires up the rest: > an automatic tool calling loop with iteration limits > history saved after every call, so a crash resumes instead of starting over > context compaction that summarizes when the window fills > a persistent todo list plus plan and execute modes > file memory that survives across turns > tool approval with standing rules and auto approval > OpenTelemetry tracing and web search built in > Agent Skills that load domain expertise on demand the mental model is simple: the model is the brain, the harness is the body around it. and it works with whatever you already run: > Azure OpenAI, OpenAI, Anthropic, and GitHub Copilot, and it hosts on Microsoft Foundry you spin one up in a single line: agent = create_harness_agent(client, name, instructions) open source, Python, .NET, and Go, stable since mid 2026. bookmark this. Microsoft already built the hard part of every AI agent, you just plug in the model.

NO1ennn

68,679 views • 29 days ago

🚨 THIS IS SO WILD Microsoft just open sourced a free tool that records you doing a task ONCE — and your AI agent repeats it forever. the GitHub repo already has 3,400+ stars. It lets you: → record a real work session: screen, clicks, windows, pages, even your narration → have Copilot reconstruct it as one intent plus an ordered step list → turn that one run into a Skill the agent runs on demand → or an Automation on a schedule — same procedure, no hands → generalize from one example: teach it one form, it submits all of them no replaying your clicks like a macro. it prefers the agent's native tools and learns the general case. this is where one-person businesses are headed. save this for later.

🚨 THIS IS SO WILD Microsoft just open sourced a free tool that records you doing a task ONCE — and your AI agent repeats it forever. the GitHub repo already has 3,400+ stars. It lets you: → record a real work session: screen, clicks, windows, pages, even your narration → have Copilot reconstruct it as one intent plus an ordered step list → turn that one run into a Skill the agent runs on demand → or an Automation on a schedule — same procedure, no hands → generalize from one example: teach it one form, it submits all of them no replaying your clicks like a macro. it prefers the agent's native tools and learns the general case. this is where one-person businesses are headed. save this for later.

Vikas gupta

159,906 views • 22 days ago

how is this even allowed i dropped my $200/mo claude plan for deepseek harness, it’s basically free the whole thing runs on one simple rule: everything is a plugin [setup takes 3 minutes, here’s the playbook] 1. clone/install the repo called deepseek-harness 2. skim the architecture docs 3. that’s it, you’re live bookmark this and hand it to your agent right now.

how is this even allowed i dropped my $200/mo claude plan for deepseek harness, it’s basically free the whole thing runs on one simple rule: everything is a plugin [setup takes 3 minutes, here’s the playbook] 1. clone/install the repo called deepseek-harness 2. skim the architecture docs 3. that’s it, you’re live bookmark this and hand it to your agent right now.

CyrilXBT

42,722 views • 1 month ago

$DEEPSEEK JUST DROPPED HARNESS, AND IT ALREADY BECAME ONE OF THE FASTEST-GROWING PROJECTS ON GITHUB: 130,000 STARS IN ONLY 3 DAYS. COMPLETELY FREE Core idea: almost anything can become a plugin ➜ models, sessions, skills, sandboxes, loops, even the interface. Put the pieces in, get a working agent out 1\ Architecture is built on Cordis, so you can swap components at any time 2\ Formula is simple: any model + any component = ready agent 3\ Community already shipped 6,000 ready skills for it You get a flexible environment where you control the building blocks instead of being locked into one rigid setup Installation is simple. Run these commands one by one: ``` git clone cd deepseek-harness pnpm install pnpm run build pnpm dsh web ```$

DEEPSEEK JUST DROPPED HARNESS, AND IT ALREADY BECAME ONE OF THE FASTEST-GROWING PROJECTS ON GITHUB: 130,000 STARS IN ONLY 3 DAYS. COMPLETELY FREE Core idea: almost anything can become a plugin ➜ models, sessions, skills, sandboxes, loops, even the interface. Put the pieces in, get a working agent out 1\ Architecture is built on Cordis, so you can swap components at any time 2\ Formula is simple: any model + any component = ready agent 3\ Community already shipped 6,000 ready skills for it You get a flexible environment where you control the building blocks instead of being locked into one rigid setup Installation is simple. Run these commands one by one: ``` git clone cd deepseek-harness pnpm install pnpm run build pnpm dsh web ```

beamnxw ./

12,264 views • 1 month ago

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

Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail

Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail

LangChain

33,192 views • 1 year ago

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.

MIKE

709,019 views • 1 month ago

Don't waste 2 years building AI agents the wrong way. An Anthropic engineer dropped a 1 hour course on the exact way to build AI agents from scratch. • 00:00 - building a Claude AI agent live • 34:01 - taking AI agents to production • 52:20 - AI agent harness Prompting is the old job. Building AI agentic loops is the new one. This one video replaces 10 paid courses on vibe coding. Bookmark & watch it now. Then build your own AI agent with the guide below.

Don't waste 2 years building AI agents the wrong way. An Anthropic engineer dropped a 1 hour course on the exact way to build AI agents from scratch. • 00:00 - building a Claude AI agent live • 34:01 - taking AI agents to production • 52:20 - AI agent harness Prompting is the old job. Building AI agentic loops is the new one. This one video replaces 10 paid courses on vibe coding. Bookmark & watch it now. Then build your own AI agent with the guide below.

Roan

14,167 views • 1 month ago

✨New LangChain Academy Course: Learn to build with LangSmith Agent Builder 🪄 Learn how to build your own agents with LangSmith Agent Builder. Anyone can now build agents for complex daily tasks, without writing code. We built Agent Builder for anyone whose day gets swallowed by routine work. The research, follow-ups, updates, scheduling, and status checks that are essential to your operations, but quickly take over your calendar. Agent Builder is different from traditional workflow automations. You don’t need to map every step, tinker with if-this-then-that branching, or babysit dependencies. You just give it feedback like you would a teammate, and the agent learns using its memory. In this quickstart course, you'll learn how to: - Build an email agent - Understand what agents can do - Improve your agent - Set up triggers and your Agent Inbox Enroll for free ➡️

✨New LangChain Academy Course: Learn to build with LangSmith Agent Builder 🪄 Learn how to build your own agents with LangSmith Agent Builder. Anyone can now build agents for complex daily tasks, without writing code. We built Agent Builder for anyone whose day gets swallowed by routine work. The research, follow-ups, updates, scheduling, and status checks that are essential to your operations, but quickly take over your calendar. Agent Builder is different from traditional workflow automations. You don’t need to map every step, tinker with if-this-then-that branching, or babysit dependencies. You just give it feedback like you would a teammate, and the agent learns using its memory. In this quickstart course, you'll learn how to: - Build an email agent - Understand what agents can do - Improve your agent - Set up triggers and your Agent Inbox Enroll for free ➡️

LangChain

26,513 views • 7 months ago

You can now delegate tasks to Cursor directly from Notion. It's built on the Cursor SDK, so every cloud agent runs on the same models, harness, and runtime that power Cursor. @Cursor on any spec or assign it a task to open a PR your whole team can review.

You can now delegate tasks to Cursor directly from Notion. It's built on the Cursor SDK, so every cloud agent runs on the same models, harness, and runtime that power Cursor. @Cursor on any spec or assign it a task to open a PR your whole team can review.

Cursor

322,004 views • 2 months ago

Wow! Someone open sourced 100+ full AI apps you can just clone and ship.. and it's sitting at 124,000 stars on github it's one repo, awesome-llm-apps. and the important part.. these aren't tutorials teaching you to build an app. they're the finished apps themselves. RAG systems, AI agents, multi-agent teams.. tested end to end, apache licensed, yours to copy. a few that are actually in there: - a fraud investigation agent that cross-references public records to flag things that don't add up - a VC due-diligence agent team that writes startup investment analysis - a financial coach that builds you a budget, debt and savings plan - "chat with anything".. your github, gmail, PDFs, arxiv papers, youtube videos - a deep research agent that runs full web research on its own here's how to actually use it, not just star it: clone the repo, open the one app closest to what you need it's a working template.. swap in your data, your API key, your use case ship it as your own thing, or bolt three of them together into one bigger product the license literally lets you take these, customize them, and sell them. that's not a loophole, that's the point of apache-2.0. repo:

Wow! Someone open sourced 100+ full AI apps you can just clone and ship.. and it's sitting at 124,000 stars on github it's one repo, awesome-llm-apps. and the important part.. these aren't tutorials teaching you to build an app. they're the finished apps themselves. RAG systems, AI agents, multi-agent teams.. tested end to end, apache licensed, yours to copy. a few that are actually in there: - a fraud investigation agent that cross-references public records to flag things that don't add up - a VC due-diligence agent team that writes startup investment analysis - a financial coach that builds you a budget, debt and savings plan - "chat with anything".. your github, gmail, PDFs, arxiv papers, youtube videos - a deep research agent that runs full web research on its own here's how to actually use it, not just star it: clone the repo, open the one app closest to what you need it's a working template.. swap in your data, your API key, your use case ship it as your own thing, or bolt three of them together into one bigger product the license literally lets you take these, customize them, and sell them. that's not a loophole, that's the point of apache-2.0. repo:

Axel Bitblaze 🪓

46,487 views • 2 months ago

Hermes Agent just got an update nobody is talking about. And it replaced all my paid tools. It is now free forever. It runs a local model called North Mini Code. You can build games like Skyrim or Matrix stuff fast. It is simple and runs on our Agent OS system. Get clear steps and real results today. Comment Agent OS to get the full free guide sent to you right now.

Hermes Agent just got an update nobody is talking about. And it replaced all my paid tools. It is now free forever. It runs a local model called North Mini Code. You can build games like Skyrim or Matrix stuff fast. It is simple and runs on our Agent OS system. Get clear steps and real results today. Comment Agent OS to get the full free guide sent to you right now.

Julian Goldie SEO

10,673 views • 2 months ago