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Doing Executor's YC launch today! Executor is your tool gateway - it gives you one place to sign in to all of the services you use and then every agent adopt (Hermes, Codex, OpenClaw, etc) carry over the same signed in accounts, permissions, etc Executor gets a ton right... show more

Rhys

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58,464 次观看 • 12 天前 •via X (Twitter)

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i hate the way tool calling works today, so i built a fix for it its called `executor` and it lets your agent run code to call any API / MCP / GraphQL server rather than installing CLIs this is a soft launch, you can try it with npm i -g executor but im still making it great

i hate the way tool calling works today, so i built a fix for it its called `executor` and it lets your agent run code to call any API / MCP / GraphQL server rather than installing CLIs this is a soft launch, you can try it with npm i -g executor but im still making it great

Rhys

129,065 次观看 • 5 个月前

Ask User tool in Gemini CLI 💬 The ask user tool gives the agent an interface to ask questions to you when instructions are unclear, designs could go one of multiple ways, or when you ask it to use the "ask_user" tool! Supports multiple different question types. Give it a try today to review your specs, quiz you, or just ask you questions about a project. 🙋

Ask User tool in Gemini CLI 💬 The ask user tool gives the agent an interface to ask questions to you when instructions are unclear, designs could go one of multiple ways, or when you ask it to use the "ask_user" tool! Supports multiple different question types. Give it a try today to review your specs, quiz you, or just ask you questions about a project. 🙋

Gemini CLI

48,351 次观看 • 5 个月前

I'm now building Executor full time as a startup! The state of tool calling is a mess: - Everyone is using different agents - You have no idea what actions are going to run - Destructive actions are treated the same as normal Executor lets you set up everything once & use it with any agent. You're able to control what tools can be called, require approval on destructive actions, and invite your team to all use them. Under the hood, it's built on codemode to let you add thousands of tools with 0 context bloat. I've been using it for a month so far and it has completely changed how I interact with agents. There's so much to be built here, immediately next up on the roadmap is workspaces, skills, workflows, and generative ui. Everything is being built open source over at there's a lot more coming on an SDK to embed it into your own agents, a self hostable cloud app, and plugins There's an early beta version over at It's very early on - if you hit any bugs let me know and I'll get them fixed up, excited to share more as I build it!

I'm now building Executor full time as a startup! The state of tool calling is a mess: - Everyone is using different agents - You have no idea what actions are going to run - Destructive actions are treated the same as normal Executor lets you set up everything once & use it with any agent. You're able to control what tools can be called, require approval on destructive actions, and invite your team to all use them. Under the hood, it's built on codemode to let you add thousands of tools with 0 context bloat. I've been using it for a month so far and it has completely changed how I interact with agents. There's so much to be built here, immediately next up on the roadmap is workspaces, skills, workflows, and generative ui. Everything is being built open source over at there's a lot more coming on an SDK to embed it into your own agents, a self hostable cloud app, and plugins There's an early beta version over at It's very early on - if you hit any bugs let me know and I'll get them fixed up, excited to share more as I build it!

Rhys

220,243 次观看 • 3 个月前

Copilot Tasks is seriously good?! Even one of the best alternative to Claude Cowork Using a single prompt it was able to: → Use a cloud browser to find the right tool → Interact with the page to enter data → Interpret all the info given by the page → Generate a PowerPoint based on it → Draft an email containing the learnings Because it has access in real time to multiple Microsoft Office apps like Word, PowerPoint, Excel, etc. but also Outlook. Everything was seamless. First try. And you can even ask it to schedule this task (or another one) to run it every Friday, once a month, you name it. As with OpenClaw, the use cases are basically infinite.

Copilot Tasks is seriously good?! Even one of the best alternative to Claude Cowork Using a single prompt it was able to: → Use a cloud browser to find the right tool → Interact with the page to enter data → Interpret all the info given by the page → Generate a PowerPoint based on it → Draft an email containing the learnings Because it has access in real time to multiple Microsoft Office apps like Word, PowerPoint, Excel, etc. but also Outlook. Everything was seamless. First try. And you can even ask it to schedule this task (or another one) to run it every Friday, once a month, you name it. As with OpenClaw, the use cases are basically infinite.

Paul Couvert

153,776 次观看 • 4 个月前

This is why you want an execution layer share your tools, auth and approvals across all agents you use Check out me adding the Axiom MCP server, authing to it, and calling it from Claude Code and OpenCode in under a minute - all locally on my computer `npm i -g executor`

This is why you want an execution layer share your tools, auth and approvals across all agents you use Check out me adding the Axiom MCP server, authing to it, and calling it from Claude Code and OpenCode in under a minute - all locally on my computer `npm i -g executor`

Rhys

29,977 次观看 • 5 个月前

This guy literally tested Hermes Agent vs OpenClaw side by side. Hermes won. And it wasn't close. Here's what made the difference: → Hermes built the website faster → Hermes gave live updates the whole time. OpenClaw went silent. → Hermes designed a cleaner page using the exact same AI model → And then Hermes did something OpenClaw can't do at all. It learned from the task. Every mistake gets logged. Every win gets saved as a reusable skill. The more you use it, the smarter it gets. OpenClaw doesn't do this unless you manually set up a learning file. Hermes does it automatically. Every single time. Other wins: → Runs free with Ollama + MiniMax → Works on Telegram, Discord, Slack, WhatsApp, Signal, and Email → Supports 200+ AI models → Built-in migration tool from OpenClaw — one command to switch 11,600 GitHub stars. 142 contributors. If you're already on OpenClaw, you don't have to start over. Just ask Hermes to import everything.

This guy literally tested Hermes Agent vs OpenClaw side by side. Hermes won. And it wasn't close. Here's what made the difference: → Hermes built the website faster → Hermes gave live updates the whole time. OpenClaw went silent. → Hermes designed a cleaner page using the exact same AI model → And then Hermes did something OpenClaw can't do at all. It learned from the task. Every mistake gets logged. Every win gets saved as a reusable skill. The more you use it, the smarter it gets. OpenClaw doesn't do this unless you manually set up a learning file. Hermes does it automatically. Every single time. Other wins: → Runs free with Ollama + MiniMax → Works on Telegram, Discord, Slack, WhatsApp, Signal, and Email → Supports 200+ AI models → Built-in migration tool from OpenClaw — one command to switch 11,600 GitHub stars. 142 contributors. If you're already on OpenClaw, you don't have to start over. Just ask Hermes to import everything.

Julian Goldie SEO

40,877 次观看 • 4 个月前

Introducing Open Source AI CRM, that runs on your OpenClaw. A few weeks ago, we launched Ironclaw (An Open Source OpenClaw CRM Framework) which now has around 1.4k stars. A lot of people confused us with NearAI’s Ironclaw, so we changed our name to DenchClaw. OpenClaw today feels a lot like early React: the primitive is incredibly powerful, but the patterns are still forming, and everyone is piecing together their own way to actually use it. What made React explode wasn’t just React itself, but the emergence of frameworks like Gatsby and Next.js that turned raw capability into something opinionated, repeatable, and easy to adopt. That is how I think about DenchClaw. We are not just building on top of OpenClaw; we are trying to make it one of the clearest, most practical, and most complete ways to use OpenClaw in the real world. We are an OpenClaw Framework, we are aiming to be the most correct way to use OpenClaw. We entered Y Combinator with Merse (AI Audio Comic), it was an app that I personally never used. Michael Seibel confronted us on it, and said, “if you aren’t the best user of your consumer app, then who is?”. I now use DenchClaw daily for everything I do, it also works as a coding agent like Cursor, DenchClaw built DenchClaw. I am addicted to DenchClaw now that I can ask it, “hey in the companies table only show me the ones who have more than 5 employees” and it updates it live than me having to manually add a filter. On Dench, everything sits in a file system, the table filters, views, column toggles, calendar/gantt views, etc, so OpenClaw can directly work with it using Dench’s CRM skill. The CRM is built on top of DuckDB, the smallest, most performant and at the same time also feature rich database we could find. It creates a new OpenClaw🦞 profile called “dench”, and opens a new OpenClaw Gateway… that means you can run all your usual openclaw commands by just prefixing every command with `openclaw --profile dench` . It will start your gateway on port 19001 range. You will be able to access the DenchClaw frontend at localhost:3100. Once you open it on Safari, just add it to your Dock to use it as a PWA. Think of it as Cursor for your Mac which is based on OpenClaw. DenchClaw has a file tree view for you to use it as an elevated finder tool to do anything on your mac. I use it to create slides, do LinkedIn outreach using MY browser. DenchClaw sees what you see, does what you do. It’s the everything app, that sits locally on your mac. All yours. Just ask it “hey import my notion”, “hey import everything from my hubspot”, and it will literally go into your browser, export all objects and documents and put it in its own workspace that you can use. P.S. It comes with Garry Tan's GStack built in.

Mark Rachapoom

19,411 次观看 • 4 个月前

New Tools for a New Era. Coding agents like Claude and Cursor have dramatically reduced the time it takes to go from idea to functional software. But the experience of designing and refining with them sucks. One reason for this is that while the terminal is an incredible tool for communicating direction with language, it is a terrible tool for defining and exploring visual and interactive objects. Here is one idea for how we might fix a small part of that. In the old world, when you wanted to create a transition or animation in your app, you would type some code, refresh your local server, and click to run your animation. It probably wasn't right, because after all no one can know what 'cubic-bezier(0.3, 0.05, 0.45, 1)' really feels like when you read it. You need to see it. Feel it. Interact with it in a real world context. So you'd edit some values, save, refresh, and keep guessing and checking until it felt right. Today, you can write a quick, single-use tool that's a visual studio for designing animations. You can then configure some components and containers common in all apps, and explore different animations in real time, adjusting key properties, and getting it just right. Then, you can copy a highly detailed prompt (or export a skill containing all your animations) that captures your intent and direction with perfect clarity. Paste this into your terminal and your agent instantly implements it everywhere. To me, this is an improvement over the old world, and a better way to work in today's. I'm extremely excited to see the ways in which our ability to rapidly create software will shape how we design software tomorrow. Feedback, ideas, and critiques welcome!

New Tools for a New Era. Coding agents like Claude and Cursor have dramatically reduced the time it takes to go from idea to functional software. But the experience of designing and refining with them sucks. One reason for this is that while the terminal is an incredible tool for communicating direction with language, it is a terrible tool for defining and exploring visual and interactive objects. Here is one idea for how we might fix a small part of that. In the old world, when you wanted to create a transition or animation in your app, you would type some code, refresh your local server, and click to run your animation. It probably wasn't right, because after all no one can know what 'cubic-bezier(0.3, 0.05, 0.45, 1)' really feels like when you read it. You need to see it. Feel it. Interact with it in a real world context. So you'd edit some values, save, refresh, and keep guessing and checking until it felt right. Today, you can write a quick, single-use tool that's a visual studio for designing animations. You can then configure some components and containers common in all apps, and explore different animations in real time, adjusting key properties, and getting it just right. Then, you can copy a highly detailed prompt (or export a skill containing all your animations) that captures your intent and direction with perfect clarity. Paste this into your terminal and your agent instantly implements it everywhere. To me, this is an improvement over the old world, and a better way to work in today's. I'm extremely excited to see the ways in which our ability to rapidly create software will shape how we design software tomorrow. Feedback, ideas, and critiques welcome!

joshpuckett

82,065 次观看 • 7 个月前

Spark is starting to become real. A self-evolving intelligence, beyond a persistent memory, with multiple ways it learns and evolves Calibrate the intelligence while building, talking to it, sharing the things you love as content, UI, art, etc., While it learns constantly learns about the tools you use: Their strengths, shortcomings, and how to better use everything in its arsenal, as well as doing the same with the specialized agents and teams it orchestrates. In a few days, it gathered 30000 memories and 500+ insights, and continued to calibrate itself with me, which will speed up how we can vibe code the next projects by Spark doing at evolved understandings. Super excited to see how it evolves and can't wait to bring it to everyone. Already integrated it with many IDEs and LLMs. It also works on your local machine. As this conversation was recorded with Ollama qwen 2.5 running on my PC.

Spark is starting to become real. A self-evolving intelligence, beyond a persistent memory, with multiple ways it learns and evolves Calibrate the intelligence while building, talking to it, sharing the things you love as content, UI, art, etc., While it learns constantly learns about the tools you use: Their strengths, shortcomings, and how to better use everything in its arsenal, as well as doing the same with the specialized agents and teams it orchestrates. In a few days, it gathered 30000 memories and 500+ insights, and continued to calibrate itself with me, which will speed up how we can vibe code the next projects by Spark doing at evolved understandings. Super excited to see how it evolves and can't wait to bring it to everyone. Already integrated it with many IDEs and LLMs. It also works on your local machine. As this conversation was recorded with Ollama qwen 2.5 running on my PC.

Meta Alchemist

244,052 次观看 • 6 个月前

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 everything: > org map showing the full agent hierarchy, who reports to who and what tools each agent has > chat with any agent through a real UI instead of bouncing between terminals > kanban board for tracking tasks across all agents > cron monitor with pipeline visualizations so you can see which jobs are failing > memory browser to read through all agent knowledge files in one place you can even point it at your openclaw workspace and it auto-discovers every agent from their config files. zero setup. AND ITS OPEN SOURCE TOO.

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 everything: > org map showing the full agent hierarchy, who reports to who and what tools each agent has > chat with any agent through a real UI instead of bouncing between terminals > kanban board for tracking tasks across all agents > cron monitor with pipeline visualizations so you can see which jobs are failing > memory browser to read through all agent knowledge files in one place you can even point it at your openclaw workspace and it auto-discovers every agent from their config files. zero setup. AND ITS OPEN SOURCE TOO.

Om Patel

46,780 次观看 • 4 个月前

AI AGENTS 101 (58 minute free masterclass) send this to anyone who wants to understand ai agents, claude skills, md files, how to get the most out of AI etc in plain english: 1. chat vs agents - chat models answer questions in a back and forth while agents take a goal, figure out the steps, and deliver a result 2. agents don’t stop after one response. they keep running until the task is actually finishedno babysitting required 3. everything runs on a loop. they gather context, decide what to do, take an action, then repeat until done 4. the loop is the system. they look at files, tools, and the internet. decide the next step. execute and then feed that back into the next step. over and over until completion 5. the model is just one piece. gpt, claude, gemini are the reasoning layer. the key is model + loop + tools + context 6. mcp is how agents use tools. it connects things like browser, code, apis, and your internal software. once connected, the agent decides when to use them to get the job done 7. context beats prompt all day. you don't need to write perfect prompts. load your agent with context about your business, style, and goals and then simple instructions work 8. claude.md or agents.md is the onboarding doc it tells the agent who it is, how to behave, what it knows, and what tools it can use. this gets loaded every time before it starts 9. memory.md is how it improves. agents don’t remember by default. this file stores preferences, corrections, and patterns you tell the agent to update it, and it gets better over time 10. skills + harnesses make it usable. skills are reusable tasks like writing, research, analysis the harness is the environment like claude code or openclaw that runs everything. basiclaly, different interfaces, same system underneath this episode with remy on The Startup Ideas Podcast (SIP) 🧃 was one of the clearest ways of understanding a lot of the core concepts of ai agents could be the best beginners course for ai agents 58 mins. all free. no advertisers. i just want to see you build cool stuff. im rooting for you. send to a friend watch

AI AGENTS 101 (58 minute free masterclass) send this to anyone who wants to understand ai agents, claude skills, md files, how to get the most out of AI etc in plain english: 1. chat vs agents - chat models answer questions in a back and forth while agents take a goal, figure out the steps, and deliver a result 2. agents don’t stop after one response. they keep running until the task is actually finishedno babysitting required 3. everything runs on a loop. they gather context, decide what to do, take an action, then repeat until done 4. the loop is the system. they look at files, tools, and the internet. decide the next step. execute and then feed that back into the next step. over and over until completion 5. the model is just one piece. gpt, claude, gemini are the reasoning layer. the key is model + loop + tools + context 6. mcp is how agents use tools. it connects things like browser, code, apis, and your internal software. once connected, the agent decides when to use them to get the job done 7. context beats prompt all day. you don't need to write perfect prompts. load your agent with context about your business, style, and goals and then simple instructions work 8. claude.md or agents.md is the onboarding doc it tells the agent who it is, how to behave, what it knows, and what tools it can use. this gets loaded every time before it starts 9. memory.md is how it improves. agents don’t remember by default. this file stores preferences, corrections, and patterns you tell the agent to update it, and it gets better over time 10. skills + harnesses make it usable. skills are reusable tasks like writing, research, analysis the harness is the environment like claude code or openclaw that runs everything. basiclaly, different interfaces, same system underneath this episode with remy on The Startup Ideas Podcast (SIP) 🧃 was one of the clearest ways of understanding a lot of the core concepts of ai agents could be the best beginners course for ai agents 58 mins. all free. no advertisers. i just want to see you build cool stuff. im rooting for you. send to a friend watch

GREG ISENBERG

376,293 次观看 • 5 个月前

Imagine an AI application that can type anywhere you can and use the full context of what's on your screen. This is the application we all deserve (at least if you have macOS.) Check out Omnipilot. It's an app that works with every other macOS application and uses Claude Sonet 3.5 in the background—it also supports Gemini and GPT-4o. Here is the idea: You can use the tool to ask questions about anything on your screen. Or you can use it to autocomplete the text you are typing. You don't need to copy and paste anymore or waste your time providing context to a model. It sees what you see. It works right where you are. That's pretty cool. Here are a couple of cool examples: • Use it to reply to an email • Use it in the terminal to autocomplete a command • Use it to finish a document • Use to send a message on Slack AI at the system level is bonkers. You can read a ton more on their Product Hunt launch page: Thanks to the Omnipilot team for collaborating with me on this post!

Imagine an AI application that can type anywhere you can and use the full context of what's on your screen. This is the application we all deserve (at least if you have macOS.) Check out Omnipilot. It's an app that works with every other macOS application and uses Claude Sonet 3.5 in the background—it also supports Gemini and GPT-4o. Here is the idea: You can use the tool to ask questions about anything on your screen. Or you can use it to autocomplete the text you are typing. You don't need to copy and paste anymore or waste your time providing context to a model. It sees what you see. It works right where you are. That's pretty cool. Here are a couple of cool examples: • Use it to reply to an email • Use it in the terminal to autocomplete a command • Use it to finish a document • Use to send a message on Slack AI at the system level is bonkers. You can read a ton more on their Product Hunt launch page: Thanks to the Omnipilot team for collaborating with me on this post!

Santiago

72,306 次观看 • 2 年前

OpenClaw has 186K GitHub stars and 1.5M compromised API keys. I needed a secure alternative. So, I built it with n8n and Claude Opus 4.6. It can already: - Reply to your Telegram messages - Access selected folders from your laptop - Access Gmail, Drive, Notion, Linear, etc. - Install new local tools in a sandbox - Run autonomously for hours - Create multiple subagents - Learn from experience - Wake up regularly But, unlike OpenClaw, it: - Can't access your API keys - Can't modify its environment - Can't access folders you haven't shared - Can't access tools you haven't approved - Must get your confirmation, e.g., when sending emails These aren’t prompt instructions. They’re hard architectural boundaries — Docker isolation, mounted folder permissions, n8n’s tool approval system. Key components: ✅ The VPS on Hostinger hosts n8n and a sandbox container. Agents can also connect to my laptop's sandbox via a Claudeflare tunnel + Desktop Commander MCP. ✅ The Manager agent is the brain. It plans, decides, delegates, and talks to the user. It never touches files. It never runs scripts. It works entirely from executor summaries. ✅ The Executor agents are the hands. Each receives a task (what to do + why it matters), decides how to execute it, and reports back. They can install new tools and execute code only in their dedicated sandboxes. ✅ Data Tables in n8n store both memories and sessions — no external database, no vector store, no infrastructure. Just rows in a table. Turns out, that's enough. Two memory types: - Manager memory: user preferences, facts, corrections, relationship, skills, context - Executor memory: what tools are installed, what’s broken, workarounds ✅ Sessions are short-term state for multi-step tasks. Original request, plan, assumptions, and what happened so far. When the Manager loops with fresh context, the session is all it gets. That's a Ralph Wiggum loop. I've been using it for 5 days. And already can't imagine not having it on my phone. What's next: - Heartbeat via Cron (a scheduled prompt) - Civic Nexus governance + MCPs - Supermemory integration - WhatsApp as an additional surface - Hardening The architecture supports all of it. OpenClaw proved people want personal AI agents. It also proved that 'just trust the prompt' isn't a security model. Docker isolation, mounted folder permissions, tool approval — none of this is new technology. It's just discipline. You can easily do this even with n8n — no coding required. --- Want to try it or read more? More, what I learned, and a setup guide: productcompass[.]pm

OpenClaw has 186K GitHub stars and 1.5M compromised API keys. I needed a secure alternative. So, I built it with n8n and Claude Opus 4.6. It can already: - Reply to your Telegram messages - Access selected folders from your laptop - Access Gmail, Drive, Notion, Linear, etc. - Install new local tools in a sandbox - Run autonomously for hours - Create multiple subagents - Learn from experience - Wake up regularly But, unlike OpenClaw, it: - Can't access your API keys - Can't modify its environment - Can't access folders you haven't shared - Can't access tools you haven't approved - Must get your confirmation, e.g., when sending emails These aren’t prompt instructions. They’re hard architectural boundaries — Docker isolation, mounted folder permissions, n8n’s tool approval system. Key components: ✅ The VPS on Hostinger hosts n8n and a sandbox container. Agents can also connect to my laptop's sandbox via a Claudeflare tunnel + Desktop Commander MCP. ✅ The Manager agent is the brain. It plans, decides, delegates, and talks to the user. It never touches files. It never runs scripts. It works entirely from executor summaries. ✅ The Executor agents are the hands. Each receives a task (what to do + why it matters), decides how to execute it, and reports back. They can install new tools and execute code only in their dedicated sandboxes. ✅ Data Tables in n8n store both memories and sessions — no external database, no vector store, no infrastructure. Just rows in a table. Turns out, that's enough. Two memory types: - Manager memory: user preferences, facts, corrections, relationship, skills, context - Executor memory: what tools are installed, what’s broken, workarounds ✅ Sessions are short-term state for multi-step tasks. Original request, plan, assumptions, and what happened so far. When the Manager loops with fresh context, the session is all it gets. That's a Ralph Wiggum loop. I've been using it for 5 days. And already can't imagine not having it on my phone. What's next: - Heartbeat via Cron (a scheduled prompt) - Civic Nexus governance + MCPs - Supermemory integration - WhatsApp as an additional surface - Hardening The architecture supports all of it. OpenClaw proved people want personal AI agents. It also proved that 'just trust the prompt' isn't a security model. Docker isolation, mounted folder permissions, tool approval — none of this is new technology. It's just discipline. You can easily do this even with n8n — no coding required. --- Want to try it or read more? More, what I learned, and a setup guide: productcompass[.]pm

Paweł Huryn

54,038 次观看 • 6 个月前

I made the worlds best Clipboard for your AI Agents Its called Bluey and its a dumb pointer which you can use to give 10x better context to your agent And you can point at your screen, talk to it, and it will generate a really good annotated screenshot which you can now give to your AI Agent You can use it while designing your website You can use it while explaining something on your screen. And it understands you and you can be really vague about things like "move this" , modify the color "here" and it will understand what you are pointing at. Im loving using it and I built it for myself as I was tired of clicking screenshots all the time and attaching it to my codex or claude code sessions Now I can just point, speak or type and drag and drop it anywhere I am giving free access to it in the comments and I would love for you to try it out. Join the discord and I am sharing the download link there. By the way everything stays 100 percent local. No screenshots are shared anywhere!

I made the worlds best Clipboard for your AI Agents Its called Bluey and its a dumb pointer which you can use to give 10x better context to your agent And you can point at your screen, talk to it, and it will generate a really good annotated screenshot which you can now give to your AI Agent You can use it while designing your website You can use it while explaining something on your screen. And it understands you and you can be really vague about things like "move this" , modify the color "here" and it will understand what you are pointing at. Im loving using it and I built it for myself as I was tired of clicking screenshots all the time and attaching it to my codex or claude code sessions Now I can just point, speak or type and drag and drop it anywhere I am giving free access to it in the comments and I would love for you to try it out. Join the discord and I am sharing the download link there. By the way everything stays 100 percent local. No screenshots are shared anywhere!

Milind S

11,917 次观看 • 2 个月前

Today I launched launched Larrybrain , you can tell how excited I am from the video. Larrybrain gives your OpenClaw machine instant knowledge. - it is the first skill you should install. It gives your agent every tool on larrybrain so when you ask it a question, it can find the best tool to help you. Larry brain is going to save you hundreds in SaaS subscriptions and replacing it with just one. The more people who create on LarryBrain, the more powerful it will become. You can test it free by asking your agent right now to install larrybrain skill and testing the Xcellent product - an opensource SuperX alternative to serve as a proof of concept on the future of SaaS. I am so excited.

Today I launched launched Larrybrain , you can tell how excited I am from the video. Larrybrain gives your OpenClaw machine instant knowledge. - it is the first skill you should install. It gives your agent every tool on larrybrain so when you ask it a question, it can find the best tool to help you. Larry brain is going to save you hundreds in SaaS subscriptions and replacing it with just one. The more people who create on LarryBrain, the more powerful it will become. You can test it free by asking your agent right now to install larrybrain skill and testing the Xcellent product - an opensource SuperX alternative to serve as a proof of concept on the future of SaaS. I am so excited.

Oliver Henry

36,253 次观看 • 5 个月前

Building agents should be simpler. 👾 We’re going to soon launch a companion tool to help developers get started fast: scaffolding, project setup, and everything you need to begin building agents out of the box. One SDK. One tool. Agents guaranteed to be compatible with the Warden app. Think of it as your starting point for agent development, you take it from there. More soon. 🛠️ 🎙️ @Ungl1tched x

Building agents should be simpler. 👾 We’re going to soon launch a companion tool to help developers get started fast: scaffolding, project setup, and everything you need to begin building agents out of the box. One SDK. One tool. Agents guaranteed to be compatible with the Warden app. Think of it as your starting point for agent development, you take it from there. More soon. 🛠️ 🎙️ @Ungl1tched x

Warden

26,396 次观看 • 6 个月前

I have been testing Grok Bot for the last week and it's EXCELLENT It is your own personal fleet of AI agents doing work for you 24/7 In this video I give you a FULL walkthrough of the tool, how it works, and how to 100x your productivity with it SpaceXAI COOKED

I have been testing Grok Bot for the last week and it's EXCELLENT It is your own personal fleet of AI agents doing work for you 24/7 In this video I give you a FULL walkthrough of the tool, how it works, and how to 100x your productivity with it SpaceXAI COOKED

Alex Finn

122,116 次观看 • 5 天前

Hermes Desktop Just Changed Everything Hermes just became way easier to use. No terminal, no complicated setup, no command-line stress. The new Hermes desktop app gives you a visual way to run a powerful AI agent. Here’s what it does: → Installs Hermes automatically. → Lets you choose OpenRouter, Anthropic, OpenAI, or local models. → Saves every chat session. → Creates separate profiles for different workflows. → Stores persistent memory. → Gives you access to 68 built-in tools. → Supports MCP connections. The biggest unlock? Hermes can learn skills from tasks and improve the more you use it.

Hermes Desktop Just Changed Everything Hermes just became way easier to use. No terminal, no complicated setup, no command-line stress. The new Hermes desktop app gives you a visual way to run a powerful AI agent. Here’s what it does: → Installs Hermes automatically. → Lets you choose OpenRouter, Anthropic, OpenAI, or local models. → Saves every chat session. → Creates separate profiles for different workflows. → Stores persistent memory. → Gives you access to 68 built-in tools. → Supports MCP connections. The biggest unlock? Hermes can learn skills from tasks and improve the more you use it.

Julian Goldie SEO

22,142 次观看 • 3 个月前

Michael Chomsky reveals he charges ~ $1,500 to setup OpenClaw and it takes him less than an HOUR “It’s 15 minutes where I go in and we talk about all your requirements, what you want to achieve and what integrations you want” “Then I set things up remotely and we schedule a second 30 minute meeting for me to set up integrations, permissions and also set it up in Telegram for you. By the end of that second meeting you should be chatting with your bot”

Michael Chomsky reveals he charges ~ $1,500 to setup OpenClaw and it takes him less than an HOUR “It’s 15 minutes where I go in and we talk about all your requirements, what you want to achieve and what integrations you want” “Then I set things up remotely and we schedule a second 30 minute meeting for me to set up integrations, permissions and also set it up in Telegram for you. By the end of that second meeting you should be chatting with your bot”

Jack

182,995 次观看 • 6 个月前

MOST AI AGENTS RESET TO ZERO EVERY TIME YOU OPEN A NEW SESSION. Hermes Agent was built to do the opposite. Every task compounds. Every workflow becomes reusable. Every session teaches the next one. That is the core thesis behind Hermes, and it completely changes how AI agents work. Unlike most AI agents built by software tool companies, Hermes was created by the researchers training the Hermes model family itself. Meaning: The same system used internally to generate training data is now open source and available to everyone. One install gives you access to: Claude. GPT. Grok. Local models via Ollama. Telegram, Discord, Slack, iMessage integrations. Custom skills. Persistent memory. CLI control. But the real unlock is the compounding loop: You give Hermes a task. It records every tool call, decision, and result. Then it converts successful workflows into reusable skills automatically. A Hermes setup running for 3 months becomes fundamentally smarter than a fresh install. That’s the big idea. One of the coolest parts: You literally watch the agent evolve in real time from a blank install into a personalized AI operator. Instead of watching Netflix today, spend 28 mins with this. Follow Dami-Defi for more AI systems, agent workflows, and infrastructure alpha.

MOST AI AGENTS RESET TO ZERO EVERY TIME YOU OPEN A NEW SESSION. Hermes Agent was built to do the opposite. Every task compounds. Every workflow becomes reusable. Every session teaches the next one. That is the core thesis behind Hermes, and it completely changes how AI agents work. Unlike most AI agents built by software tool companies, Hermes was created by the researchers training the Hermes model family itself. Meaning: The same system used internally to generate training data is now open source and available to everyone. One install gives you access to: Claude. GPT. Grok. Local models via Ollama. Telegram, Discord, Slack, iMessage integrations. Custom skills. Persistent memory. CLI control. But the real unlock is the compounding loop: You give Hermes a task. It records every tool call, decision, and result. Then it converts successful workflows into reusable skills automatically. A Hermes setup running for 3 months becomes fundamentally smarter than a fresh install. That’s the big idea. One of the coolest parts: You literally watch the agent evolve in real time from a blank install into a personalized AI operator. Instead of watching Netflix today, spend 28 mins with this. Follow Dami-Defi for more AI systems, agent workflows, and infrastructure alpha.

Dami-Defi

11,668 次观看 • 2 个月前