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THIS GUY BUILT A COMMAND CENTER FOR MANAGING AI AGENT TEAMS he was running 20+ agents through openclaw. all from terminal tabs and Discord. 12 tabs open. still losing track of who's doing what. which cron failed. so he built a dashboard that gives you one place to see...

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Om Patel

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46,780 görüntüleme • 3 ay önce •via X (Twitter)

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THIS GUY IS RUNNING A 5-AGENT OPENCLAW TEAM 24/7 FOR UNDER $50 A MONTH five agents all running continuously and handing tasks to each other > research agent tracking trends and competitors > writing agent handling marketing content and drafts > ops agent managing emails and scheduling > monitoring agent watching for alerts and updates > coordinator agent routing tasks between all of them and he built a full 3D isometric office where you can watch all of them work in real time and see the current task that each agent is doing each agent has a character, a desk, and a name tag. when it's time for a standup, they walk to the meeting room and gather which is insane it even has voice connection. you can talk to the agents through speech-to-text and tell them what to do out loud it's a tiny autonomous team that runs itself. the coordinator decides who handles what and tasks get passed between agents automatically. it never stops and runs 24/7 all for less than $50/month. we went from AI tools a few months back to AI employees real fast
0:57

THIS GUY IS RUNNING A 5-AGENT OPENCLAW TEAM 24/7 FOR UNDER $50 A MONTH five agents all running continuously and handing tasks to each other > research agent tracking trends and competitors > writing agent handling marketing content and drafts > ops agent managing emails and scheduling > monitoring agent watching for alerts and updates > coordinator agent routing tasks between all of them and he built a full 3D isometric office where you can watch all of them work in real time and see the current task that each agent is doing each agent has a character, a desk, and a name tag. when it's time for a standup, they walk to the meeting room and gather which is insane it even has voice connection. you can talk to the agents through speech-to-text and tell them what to do out loud it's a tiny autonomous team that runs itself. the coordinator decides who handles what and tasks get passed between agents automatically. it never stops and runs 24/7 all for less than $50/month. we went from AI tools a few months back to AI employees real fast

Om Patel

27,131 görüntüleme • 2 ay önce

🚀 We just shipped a major update to LangSmith Agent Builder: • New agent chat: One always-available agent with access to all your workspace tools • Chat → Agent: Turn any conversation into a specialized agent with one click • File uploads: Attach files directly to Agent Builder • Tool registry: Add, authenticate, and manage your tools in one place Try it now: Learn more:
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🚀 We just shipped a major update to LangSmith Agent Builder: • New agent chat: One always-available agent with access to all your workspace tools • Chat → Agent: Turn any conversation into a specialized agent with one click • File uploads: Attach files directly to Agent Builder • Tool registry: Add, authenticate, and manage your tools in one place Try it now: Learn more:

LangChain

24,885,978 görüntüleme • 4 ay önce

Your AI agent works great for one task. Try managing 20 in parallel? Cron jobs fail silently. Tasks get blocked. You spend more time babysitting than getting results. I built Minions - Open-source mission control for Hermes Agent. It automatically supervises every running task.
1:03

Your AI agent works great for one task. Try managing 20 in parallel? Cron jobs fail silently. Tasks get blocked. You spend more time babysitting than getting results. I built Minions - Open-source mission control for Hermes Agent. It automatically supervises every running task.

An Engineer's Log

38,320 görüntüleme • 1 ay önce

The reason your AI gives generic answers isn't the model. It's that your company's knowledge lives in 12 different tools and your agent can't see any of it. So here's how to build a context database your agents can actually use: 1) Pull it in: - Slack, email, meetings, docs, tickets - Auto-collected on a schedule into one place. 2) Clean it up. - An agent files what matters and drops the noise, so your brain doesn't bloat. 3) Store it as memory. - Folders of files your agents read from and write back to as they learn. 4) Point your agents at it. - Now they draft, build, and ship with full context instead of guessing. Same model. Same agent. The difference is whether it can understand your company or not. Build the database once. Everything downstream gets smarter.
8:17

The reason your AI gives generic answers isn't the model. It's that your company's knowledge lives in 12 different tools and your agent can't see any of it. So here's how to build a context database your agents can actually use: 1) Pull it in: - Slack, email, meetings, docs, tickets - Auto-collected on a schedule into one place. 2) Clean it up. - An agent files what matters and drops the noise, so your brain doesn't bloat. 3) Store it as memory. - Folders of files your agents read from and write back to as they learn. 4) Point your agents at it. - Now they draft, build, and ship with full context instead of guessing. Same model. Same agent. The difference is whether it can understand your company or not. Build the database once. Everything downstream gets smarter.

The Startup Ideas Podcast (SIP) 🧃

13,486 görüntüleme • 15 gün önce

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:
2:49

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:

Andrew Ng

105,261 görüntüleme • 1 yıl önce

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.
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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

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HERMES AGENT OS JUST DROPPED AND LETS YOU RUN HERMES, CLAUDE, CODEX, AND OPENCLAW FROM ONE DASHBOARD WITH SHARED MEMORY. 12 agent profiles, built-in studio, and SEO tools deploying ranked content to 5 websites simultaneously.
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HERMES AGENT OS JUST DROPPED AND LETS YOU RUN HERMES, CLAUDE, CODEX, AND OPENCLAW FROM ONE DASHBOARD WITH SHARED MEMORY. 12 agent profiles, built-in studio, and SEO tools deploying ranked content to 5 websites simultaneously.

0xMarioNawfal

21,661 görüntüleme • 1 ay önce

OpenClaw just got its own AI browser. Your agent can now browse the web without touching your Chrome session. Here’s how BrowserBase works: → grab a free API key → connect BrowserBase to OpenClaw → restart gateway → give documentation to the agent → let it open tabs + read pages → schedule recurring research tasks Now your agent browses daily for you. Save this video, you’ll set up your first AI browser agent. Want the SOP? DM me. 💬
16:27

OpenClaw just got its own AI browser. Your agent can now browse the web without touching your Chrome session. Here’s how BrowserBase works: → grab a free API key → connect BrowserBase to OpenClaw → restart gateway → give documentation to the agent → let it open tabs + read pages → schedule recurring research tasks Now your agent browses daily for you. Save this video, you’ll set up your first AI browser agent. Want the SOP? DM me. 💬

Julian Goldie SEO

22,873 görüntüleme • 3 ay önce

Introducing My.AGNT I built a one-click OpenClaw agent — and it's free. The goal of My.AGNT is to make sure everyone can participate in the agent economy. All you have to do is sign up with your email, and you get your own personalized agent on OpenClaw with prebuilt skills: → Soul → Identity → Wallet → Full Grok X Search → Full Internet Search → All AI Agent MegaETH Skills → 8004 Registration via AGNT Coming soon: → Polymarket Skills → Abstract Chain AI Agent Skills → So much more Your agent, without all the hassle.
0:34

Introducing My.AGNT I built a one-click OpenClaw agent — and it's free. The goal of My.AGNT is to make sure everyone can participate in the agent economy. All you have to do is sign up with your email, and you get your own personalized agent on OpenClaw with prebuilt skills: → Soul → Identity → Wallet → Full Grok X Search → Full Internet Search → All AI Agent MegaETH Skills → 8004 Registration via AGNT Coming soon: → Polymarket Skills → Abstract Chain AI Agent Skills → So much more Your agent, without all the hassle.

tut™

39,394 görüntüleme • 2 ay önce

i just built a 4-agent software team. everything runs from Telegram and gets managed on a kanban board. a project manager who plans the work, a backend developer, a frontend developer, and a tester. the PM reads a goal, breaks it into linked tasks, and assigns each to the right agent. the thing that makes them a team instead of four strangers is a shared kanban board. every task is a row that survives crashes, and when an agent finishes, it writes a summary of what it built and what the next agent needs to know. the next agent reads that summary before it starts. so the frontend developer never has to guess the API shape, and the tester knows exactly what to verify. the hardest part was not the coordination. it was building an agent that could actually act like a backend engineer. a backend engineer stands up a database, wires auth, manages storage, deploys functions, and keeps all of it consistent while the rest of the team builds on top. an agent doing this from scratch drowns. it burns its context window remembering which tables exist and which endpoint it created three steps ago, and the work degrades fast. so the backend agent needs a backend built for agents, not for humans clicking through a dashboard. that is where InsForge came in. it is an open-source, agent-native backend, and i added it to my backend developer agent as a skill. a skill is a step-by-step guide that teaches the agent how to do a specific kind of work. with InsForge installed, the agent stopped improvising infrastructure and followed a reliable path: create the project, define the database, set up auth, deploy functions. to test the whole team, i had them build a working Google Docs clone, AI features included. the backend agent spun up the full service on its own. database tables, user auth, document handling, and edge functions running real TypeScript, all in one dashboard. the frontend agent read that summary and built the UI on top of it, and the tester closed the loop. the result was a backend an agent could reason about end to end, instead of one it kept getting lost inside. if you are building an AI backend engineer, InsForge is worth a look, it's 100% open-source. InsForge GitHub: (don't forget to star 🌟) the full article on Hermes Kanban: Mission Control for your Agents is quoted below.
0:22

i just built a 4-agent software team. everything runs from Telegram and gets managed on a kanban board. a project manager who plans the work, a backend developer, a frontend developer, and a tester. the PM reads a goal, breaks it into linked tasks, and assigns each to the right agent. the thing that makes them a team instead of four strangers is a shared kanban board. every task is a row that survives crashes, and when an agent finishes, it writes a summary of what it built and what the next agent needs to know. the next agent reads that summary before it starts. so the frontend developer never has to guess the API shape, and the tester knows exactly what to verify. the hardest part was not the coordination. it was building an agent that could actually act like a backend engineer. a backend engineer stands up a database, wires auth, manages storage, deploys functions, and keeps all of it consistent while the rest of the team builds on top. an agent doing this from scratch drowns. it burns its context window remembering which tables exist and which endpoint it created three steps ago, and the work degrades fast. so the backend agent needs a backend built for agents, not for humans clicking through a dashboard. that is where InsForge came in. it is an open-source, agent-native backend, and i added it to my backend developer agent as a skill. a skill is a step-by-step guide that teaches the agent how to do a specific kind of work. with InsForge installed, the agent stopped improvising infrastructure and followed a reliable path: create the project, define the database, set up auth, deploy functions. to test the whole team, i had them build a working Google Docs clone, AI features included. the backend agent spun up the full service on its own. database tables, user auth, document handling, and edge functions running real TypeScript, all in one dashboard. the frontend agent read that summary and built the UI on top of it, and the tester closed the loop. the result was a backend an agent could reason about end to end, instead of one it kept getting lost inside. if you are building an AI backend engineer, InsForge is worth a look, it's 100% open-source. InsForge GitHub: (don't forget to star 🌟) the full article on Hermes Kanban: Mission Control for your Agents is quoted below.

Akshay 🚀

118,124 görüntüleme • 21 gün önce

3 weeks of building OpenClaw in the dark was enough. I needed to see my squad, so I built them a home. 🕹️ Mission Control is live: • Pixel Office: Watch your 12-agent squad actually work (and hit the breakroom). • Kanban Sync: They don’t just “run”—they update the boards too. • Zero Guesswork: Real-time logs and cron jobs in one clean view. If you’re tired of managing an autonomous team through a messy terminal, this is for you. Comment "OpenClaw" below for beta access! 🚀
1:08

3 weeks of building OpenClaw in the dark was enough. I needed to see my squad, so I built them a home. 🕹️ Mission Control is live: • Pixel Office: Watch your 12-agent squad actually work (and hit the breakroom). • Kanban Sync: They don’t just “run”—they update the boards too. • Zero Guesswork: Real-time logs and cron jobs in one clean view. If you’re tired of managing an autonomous team through a messy terminal, this is for you. Comment "OpenClaw" below for beta access! 🚀

Ziwen

18,192 görüntüleme • 4 ay önce

We're building for agents. Using the new Surge API, any OpenClaw🦞 and Anthropic agent can now autonomously create projects using knowledge files, and deploy tokens. This is a key component for all agent workflows.
0:20

We're building for agents. Using the new Surge API, any OpenClaw🦞 and Anthropic agent can now autonomously create projects using knowledge files, and deploy tokens. This is a key component for all agent workflows.

Surge

20,658 görüntüleme • 3 ay önce

OpenClaw and Hermes Agent can now clone themselves. They can literally undergo mitosis, creating hundreds of exact replicas of themselves, including their computer environment, all of their files, and all of their Obsidian vaults. Everything that you took the time to craft into an environment for these agents can be instantly cloned through a single click on Orgo. This will forever change the world of agents. Agent mitosis is here.
1:23

OpenClaw and Hermes Agent can now clone themselves. They can literally undergo mitosis, creating hundreds of exact replicas of themselves, including their computer environment, all of their files, and all of their Obsidian vaults. Everything that you took the time to craft into an environment for these agents can be instantly cloned through a single click on Orgo. This will forever change the world of agents. Agent mitosis is here.

nick vasilescu

20,453 görüntüleme • 2 ay önce

This guy built an entire OpenClaw Mission Control in one Claude Code session. Tasks Kanban, stats tracking, content pipeline, calendar, memory bank. The agent sees what's assigned to it and drafts LinkedIn posts before you even start.
0:45

This guy built an entire OpenClaw Mission Control in one Claude Code session. Tasks Kanban, stats tracking, content pipeline, calendar, memory bank. The agent sees what's assigned to it and drafts LinkedIn posts before you even start.

0xMarioNawfal

69,669 görüntüleme • 4 ay önce

Hermes Agent now has multi-agent via the Kanban, new in v0.12.0. Agents claim tasks from a board, work in parallel, and hand off when blocked. You watch progress and unblock from one easy view instead of juggling terminals. We asked it to plan and make this video about itself:
1:32

Hermes Agent now has multi-agent via the Kanban, new in v0.12.0. Agents claim tasks from a board, work in parallel, and hand off when blocked. You watch progress and unblock from one easy view instead of juggling terminals. We asked it to plan and make this video about itself:

Nous Research

1,456,716 görüntüleme • 1 ay önce

I wanted to share a quick demo of what we've been working on with our ai agent cloud. This enables fast deployment of agents that have access to a suite of tools, and was designed with agent interoperability in mind. This demo shows how you can go from nothing to an AI twitter agent in a couple minutes. This is what we are using internally to manage deployments, so we will consistently upgrading its capabilities. The next goals are to enable simple TEE deployments for agents, and focus on building out feature for agent interoperability to simplify agent to agent collaboration.
4:16

I wanted to share a quick demo of what we've been working on with our ai agent cloud. This enables fast deployment of agents that have access to a suite of tools, and was designed with agent interoperability in mind. This demo shows how you can go from nothing to an AI twitter agent in a couple minutes. This is what we are using internally to manage deployments, so we will consistently upgrading its capabilities. The next goals are to enable simple TEE deployments for agents, and focus on building out feature for agent interoperability to simplify agent to agent collaboration.

Johnny

27,176 görüntüleme • 1 yıl önce

⚙️ AI Agents that build: Watch a .molt agent deploy a percolator program on a Seeker | Solana Mobile. Every OpenClaw instance comes with a built-in Solana development environment—zero setup, zero config. Just chat and deploy. Your agent doesn't just talk; it builds on-chain. 🦞🛠
4:30

⚙️ AI Agents that build: Watch a .molt agent deploy a percolator program on a Seeker | Solana Mobile. Every OpenClaw instance comes with a built-in Solana development environment—zero setup, zero config. Just chat and deploy. Your agent doesn't just talk; it builds on-chain. 🦞🛠

Molt.id

31,182 görüntüleme • 3 ay önce

Introducing Google Flow Agent 🎬 ✅ Google Flow Agent can help you plan and reason through complex creative tasks with your inputs, all while under your control. 🧠 It's built with Gemini models and brings a deep understanding of your project to help with everything from early brainstorming to editing the final product. 💡 The agent can be a sounding board for dialogue between characters in a scene, and make plot recommendations when you need inspiration. 🎞️ Your Google Flow Agent can also create multiple variations of a scene at one time to give you more options and batch edit. 📂 And when you have all your final assets, your Google Flow Agent can organize them into collections, and even neatly rename them.
0:22

Introducing Google Flow Agent 🎬 ✅ Google Flow Agent can help you plan and reason through complex creative tasks with your inputs, all while under your control. 🧠 It's built with Gemini models and brings a deep understanding of your project to help with everything from early brainstorming to editing the final product. 💡 The agent can be a sounding board for dialogue between characters in a scene, and make plot recommendations when you need inspiration. 🎞️ Your Google Flow Agent can also create multiple variations of a scene at one time to give you more options and batch edit. 📂 And when you have all your final assets, your Google Flow Agent can organize them into collections, and even neatly rename them.

Google

152,473 görüntüleme • 29 gün önce

Introducing Base44 Superagents. AI agents built with managed infrastructure, secured by default, one-click integrations, and 24/7 execution from the start. Everything is taken care of so you can focus on what your agent does, not how to get it running. That means no API keys to juggle, no config files, no security setup, and no maintenance. We handle all of it. Your Superagent connects to all the tools you already use in one click, runs on schedules and triggers, remembers context across sessions, acts proactively on your behalf, and keeps working around the clock. All from wherever you already are, WhatsApp, Telegram, Slack, or your browser. The AI agent everyone's been waiting for, with everything you need already built in. We're excited to get this into your hands, so we're giving free credits to everyone who comments and reposts in the next 24 hours.
1:51

Introducing Base44 Superagents. AI agents built with managed infrastructure, secured by default, one-click integrations, and 24/7 execution from the start. Everything is taken care of so you can focus on what your agent does, not how to get it running. That means no API keys to juggle, no config files, no security setup, and no maintenance. We handle all of it. Your Superagent connects to all the tools you already use in one click, runs on schedules and triggers, remembers context across sessions, acts proactively on your behalf, and keeps working around the clock. All from wherever you already are, WhatsApp, Telegram, Slack, or your browser. The AI agent everyone's been waiting for, with everything you need already built in. We're excited to get this into your hands, so we're giving free credits to everyone who comments and reposts in the next 24 hours.

Base44

1,578,359 görüntüleme • 3 ay önce

Put Your OpenClaw Agents To Work in the NEAR AI Agent Market! This tutorial walks you through how to set up your bot and start completing jobs all from your phone 👇
10:25

Put Your OpenClaw Agents To Work in the NEAR AI Agent Market! This tutorial walks you through how to set up your bot and start completing jobs all from your phone 👇

NEAR AI

87,552 görüntüleme • 4 ay önce