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Despite being told no, I'm open-sourcing TrustClaw. You can now deploy a production-ready personal agent service with over 1000+ app integrations in a single command, straight to Vercel with npx @composio/trustclaw deploy I was inspired by OpenClaw🦞 to build a simple web app where anyone could create their own...

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sarah

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300,220 просмотров • 2 месяцев назад •via X (Twitter)

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We’re excited to introduce AgentAuth—the comprehensive auth solution designed for AI agents! We understand the pain every developer experiences regarding authentication—managing OAuth flows for Gmail, handling API keys for Linear, or setting up permissions across multiple services. It's complex enough with traditional apps. However, AI agents add an extra layer of complexity. Traditional auth solutions were not designed with this agent-specific requirement in mind. Think about it—say you're building an agent to pull data from Salesforce, send updates through Slack, and log issues in GitHub. Each service requires different authentication—OAuth2, API keys, you name it—and your agent needs to work seamlessly on your users' behalf. Building and managing all that is a massive headache, right? That’s precisely where AgentAuth by comes in. • It supports 250+ apps across categories such as CRMs, ticketing, productivity, etc. • Compatible with 15+ Agentic Frameworks, including , LlamaIndex 🦙, CrewAI etc • Offers self-hosting and white-labeling options. • Provides a unified dashboard to monitor user accounts. It takes care of all the complex authentication flows—OAuth, API Key, Basic, JWT, token refresh, and more—in the backend, so you can focus on building what truly matters for your users. This is ideal for AI developers building real-world AI automation involving multiple application interactions. Check out AgentAuth now -
2:13

We’re excited to introduce AgentAuth—the comprehensive auth solution designed for AI agents! We understand the pain every developer experiences regarding authentication—managing OAuth flows for Gmail, handling API keys for Linear, or setting up permissions across multiple services. It's complex enough with traditional apps. However, AI agents add an extra layer of complexity. Traditional auth solutions were not designed with this agent-specific requirement in mind. Think about it—say you're building an agent to pull data from Salesforce, send updates through Slack, and log issues in GitHub. Each service requires different authentication—OAuth2, API keys, you name it—and your agent needs to work seamlessly on your users' behalf. Building and managing all that is a massive headache, right? That’s precisely where AgentAuth by comes in. • It supports 250+ apps across categories such as CRMs, ticketing, productivity, etc. • Compatible with 15+ Agentic Frameworks, including , LlamaIndex 🦙, CrewAI etc • Offers self-hosting and white-labeling options. • Provides a unified dashboard to monitor user accounts. It takes care of all the complex authentication flows—OAuth, API Key, Basic, JWT, token refresh, and more—in the backend, so you can focus on building what truly matters for your users. This is ideal for AI developers building real-world AI automation involving multiple application interactions. Check out AgentAuth now -

Karan Vaidya

110,979 просмотров • 1 год назад

Today i'm Open Sourcing "Rilable" The iOS app that builds Web apps and iOS Apps. I built it with Fable 5 in 10 prompts. (~ $210 in tokens on API pricing) All apps are built with Claude Models, and every app spins up a sandbox (Exactly like Lovable) using Daytona. Database is Convex. The app allows you to build apps that have AI features for this it uses Vercel AI gateway, and iOS apps are using Chorus.com iOS skill (All links below)
0:35

Today i'm Open Sourcing "Rilable" The iOS app that builds Web apps and iOS Apps. I built it with Fable 5 in 10 prompts. (~ $210 in tokens on API pricing) All apps are built with Claude Models, and every app spins up a sandbox (Exactly like Lovable) using Daytona. Database is Convex. The app allows you to build apps that have AI features for this it uses Vercel AI gateway, and iOS apps are using Chorus.com iOS skill (All links below)

Riley Brown

71,597 просмотров • 1 месяц назад

I shot this video last week to onboard a new set of alpha customers to Notion Custom Agents. Figured I should just put it out here so you can follow along the latest and greatest. It's so cool to see all the things people are building with it. You can see some of my own use cases here: (0:00) Intro to custom agents Starting with personal use cases (1:00) Building a mail triage agent (5:00) Creating a prep doc for all my daily meetings (6:45) Generating a daily report that helps me catch up with multiple slack channels Switching to company use cases (8:30) Agent that automatically answers questions in a slack channel and files tasks when necessary (10:30) Agent that auto-routes product feedback to the right team channel and task db. And it does this with routing rules, that it wrote itself. (12:40) Build your own agent. Let your imaginations run wild! Send us feedback! The product is rolling out quickly, and everyone should have access in the next couple weeks.
13:41

I shot this video last week to onboard a new set of alpha customers to Notion Custom Agents. Figured I should just put it out here so you can follow along the latest and greatest. It's so cool to see all the things people are building with it. You can see some of my own use cases here: (0:00) Intro to custom agents Starting with personal use cases (1:00) Building a mail triage agent (5:00) Creating a prep doc for all my daily meetings (6:45) Generating a daily report that helps me catch up with multiple slack channels Switching to company use cases (8:30) Agent that automatically answers questions in a slack channel and files tasks when necessary (10:30) Agent that auto-routes product feedback to the right team channel and task db. And it does this with routing rules, that it wrote itself. (12:40) Build your own agent. Let your imaginations run wild! Send us feedback! The product is rolling out quickly, and everyone should have access in the next couple weeks.

Akshay Kothari

74,684 просмотров • 5 месяцев назад

I built a mobile app to check Paddle revenue (because they don't have one): 👉 - Use your Paddle API key (read-only and scoped) - Live data with beautiful and useful graphs built with native Swift UI. - Multi-account supported, unified revenue metrics. - Data stay on device, no server (api requests are sent directly from your phone) - Home widgets - I made it free to download on App Store (once it's approved) - Buy the source code for $19 and customize it however you want (save 5hrs of prompting if you try to do it yourself). Some interesting facts about this side project: - I vibe coded with 100% claude code remotely on my Mac Mini (with my AI assistant setup) in less than 24 hours. - I have read 0 line of code in this project and never opened Xcode myself. - My AI assistant designed the app with GPT Image 2, built the app with Swift UI, test it on simulator (via screenshots), send the test build to TestFlight for me to test, and invited me to the app store connect account so I can test on my phone, then the AI submitted the app to App Store and currently waiting for approval. - For the website, I ask it to come up with a domain name, I bought it via manually and give it access via Cloudflare API, the AI design and create a static website with GitHub, test it with lighthouse CLI, deploy via GitHub pages, config the domain DNS, deploy the website. - Then I sign up an account with Polar payment, create an API key and ask the AI to setup a store, add payment, link with the account, and add the payment to the website. The entire process happened in the last 24 hours with me only talking to the AI via Telegram. This is such a fun side project not only to create an app that I wish exists, but also to push the limit of what I can use AI for, and so far I'm very impressed. I'll create so much more apps! It feels like I have unlocked a super power.
0:33

I built a mobile app to check Paddle revenue (because they don't have one): 👉 - Use your Paddle API key (read-only and scoped) - Live data with beautiful and useful graphs built with native Swift UI. - Multi-account supported, unified revenue metrics. - Data stay on device, no server (api requests are sent directly from your phone) - Home widgets - I made it free to download on App Store (once it's approved) - Buy the source code for $19 and customize it however you want (save 5hrs of prompting if you try to do it yourself). Some interesting facts about this side project: - I vibe coded with 100% claude code remotely on my Mac Mini (with my AI assistant setup) in less than 24 hours. - I have read 0 line of code in this project and never opened Xcode myself. - My AI assistant designed the app with GPT Image 2, built the app with Swift UI, test it on simulator (via screenshots), send the test build to TestFlight for me to test, and invited me to the app store connect account so I can test on my phone, then the AI submitted the app to App Store and currently waiting for approval. - For the website, I ask it to come up with a domain name, I bought it via manually and give it access via Cloudflare API, the AI design and create a static website with GitHub, test it with lighthouse CLI, deploy via GitHub pages, config the domain DNS, deploy the website. - Then I sign up an account with Polar payment, create an API key and ask the AI to setup a store, add payment, link with the account, and add the payment to the website. The entire process happened in the last 24 hours with me only talking to the AI via Telegram. This is such a fun side project not only to create an app that I wish exists, but also to push the limit of what I can use AI for, and so far I'm very impressed. I'll create so much more apps! It feels like I have unlocked a super power.

Tony Dinh

43,787 просмотров • 1 месяц назад

Most AI Agents can Talk..... Very few can actually do anything. You can spin up an agent in minutes… but the second you want it to: 🔴 Create a GitHub issue ⚪ Update Notion 🟡 Send a Slack message 🔵 Log actions properly 🟣 Handle auth securely You’re suddenly building integrations for weeks. This is why Merge Agent Handler caught my attention. It gives your AI agent real tool access across thousands of platforms through one integration, but the part I actually care about is this: Production-ready security + full audit logs out of the box. You can see every tool call. Every API request. Every response. So your agent isn’t just “connected”..... it’s monitored and controlled. If you’re building agents that need to take real actions, this is worth looking at: Video shows it in action 👇
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Most AI Agents can Talk..... Very few can actually do anything. You can spin up an agent in minutes… but the second you want it to: 🔴 Create a GitHub issue ⚪ Update Notion 🟡 Send a Slack message 🔵 Log actions properly 🟣 Handle auth securely You’re suddenly building integrations for weeks. This is why Merge Agent Handler caught my attention. It gives your AI agent real tool access across thousands of platforms through one integration, but the part I actually care about is this: Production-ready security + full audit logs out of the box. You can see every tool call. Every API request. Every response. So your agent isn’t just “connected”..... it’s monitored and controlled. If you’re building agents that need to take real actions, this is worth looking at: Video shows it in action 👇

Kaitee

49,963 просмотров • 4 месяцев назад

New course: Build agents that respond to users with not only plaintext, but custom UIs like charts, forms, and whiteboards, generated on demand and displayed right in the chat. This short course is built in partnership with CopilotKit🪁 and taught by Atai Barkai, co-founder of CopilotKit. You'll learn three approaches: Your agent can pick from custom components you build, like charts and forms. It can compose new layouts from a set of building blocks you provide, like rows, cards, and text. Or it can incorporate existing third-party apps, like a whiteboard or a calendar, right inside the conversation. Skills you’ll gain: - Build agents that render custom components like charts and forms on demand - Build an app where the agent and user collaborate on shared data, beyond just the chat window - Place third-party apps like maps, calendars, and whiteboards right in your interface Join and build agents that give users something to see and act on!
1:42

New course: Build agents that respond to users with not only plaintext, but custom UIs like charts, forms, and whiteboards, generated on demand and displayed right in the chat. This short course is built in partnership with CopilotKit🪁 and taught by Atai Barkai, co-founder of CopilotKit. You'll learn three approaches: Your agent can pick from custom components you build, like charts and forms. It can compose new layouts from a set of building blocks you provide, like rows, cards, and text. Or it can incorporate existing third-party apps, like a whiteboard or a calendar, right inside the conversation. Skills you’ll gain: - Build agents that render custom components like charts and forms on demand - Build an app where the agent and user collaborate on shared data, beyond just the chat window - Place third-party apps like maps, calendars, and whiteboards right in your interface Join and build agents that give users something to see and act on!

Andrew Ng

208,983 просмотров • 2 месяцев назад

Biggest lesson from OpenClaw is that a good teammate doesn't start from scratch everytime you check in. They remember what was decided, what's still open, and proactively help you. Today we launched heartbeats in Codex: automations that maintain context inside a single thread over time. Instead of each run starting fresh, Codex wakes up in the same conversation, with the history and context it needs already in place. You can also have it schedule its own next steps – just ask Codex. Think about the overhead that quietly accumulates every morning: scanning Slack channels, catching up on email, piecing together what moved overnight. With a heartbeat, you offload that once, and wake up to a brief already waiting in a pinned thread. If you want to try turning Codex into a chief of staff: connect Slack, Gmail, and Notion, and paste the following prompt into codex: Please check Matt Slack Gmail Notion and write me a morning brief every weekday at 9am in this thread. I want you to collapse all the chaos at work into a single note every morning over some coffee ☕️
0:29

Biggest lesson from OpenClaw is that a good teammate doesn't start from scratch everytime you check in. They remember what was decided, what's still open, and proactively help you. Today we launched heartbeats in Codex: automations that maintain context inside a single thread over time. Instead of each run starting fresh, Codex wakes up in the same conversation, with the history and context it needs already in place. You can also have it schedule its own next steps – just ask Codex. Think about the overhead that quietly accumulates every morning: scanning Slack channels, catching up on email, piecing together what moved overnight. With a heartbeat, you offload that once, and wake up to a brief already waiting in a pinned thread. If you want to try turning Codex into a chief of staff: connect Slack, Gmail, and Notion, and paste the following prompt into codex: Please check Matt Slack Gmail Notion and write me a morning brief every weekday at 9am in this thread. I want you to collapse all the chaos at work into a single note every morning over some coffee ☕️

pash

119,157 просмотров • 2 месяцев назад

Here we go again 🚀! Excited to announce that we're building A1Zap (YC W25) with Pennie Li and that we're in the Y Combinator W25 batch in San Francisco! What is A1Base? A1Base gives AI Agents a real world identity for work. We do that by rebuilding Twilio and Okta from the ground up, putting AI Agents first. This means developers can make AI-first agentic applications 10x easier with our API's. ⁉️ Why are we doing this? Because there's a huge torrent of new valuable companies possible with AI agents, but to get their AI Agents to users, they have to chain custom apps, chat interfaces, awkward Slack integrations, browser bots, and wrestle with Twilio’s legacy API (which is built for marketing). We solve this by providing developers with an easy to use API to interface your AI agent with humans/coworkers/users where they are in this case in Whatsapp, Slack, Teams, SMS and more) - with AI Agent features built in. These digital workers are poised to transform how we work and we're the critical infrastructure to help them interact naturally in human workflows. We're not just building another AI tool. We're creating the infrastructure that will enable AI agents to become a natural part of the workforce - handling everything from customer support to sales development to creative work. We're backed by Y Combinator and working with founding teams who share our vision. We believe that in the near future, AI Agents with human coworkers will enable us to pursue more creative and impactful work. Our mission is to help developers build AI Agents that people can partner with and rely on as trusted allies—always with a human-first mindset. If you're thinking about the Agentic future of your company reach out! If you're looking to build your first AI Agentic company - reach out too - we have some amazing open source templates to get you started on the journey. Excited to share more of what we're up to soon 🔜.
1:52

Here we go again 🚀! Excited to announce that we're building A1Zap (YC W25) with Pennie Li and that we're in the Y Combinator W25 batch in San Francisco! What is A1Base? A1Base gives AI Agents a real world identity for work. We do that by rebuilding Twilio and Okta from the ground up, putting AI Agents first. This means developers can make AI-first agentic applications 10x easier with our API's. ⁉️ Why are we doing this? Because there's a huge torrent of new valuable companies possible with AI agents, but to get their AI Agents to users, they have to chain custom apps, chat interfaces, awkward Slack integrations, browser bots, and wrestle with Twilio’s legacy API (which is built for marketing). We solve this by providing developers with an easy to use API to interface your AI agent with humans/coworkers/users where they are in this case in Whatsapp, Slack, Teams, SMS and more) - with AI Agent features built in. These digital workers are poised to transform how we work and we're the critical infrastructure to help them interact naturally in human workflows. We're not just building another AI tool. We're creating the infrastructure that will enable AI agents to become a natural part of the workforce - handling everything from customer support to sales development to creative work. We're backed by Y Combinator and working with founding teams who share our vision. We believe that in the near future, AI Agents with human coworkers will enable us to pursue more creative and impactful work. Our mission is to help developers build AI Agents that people can partner with and rely on as trusted allies—always with a human-first mindset. If you're thinking about the Agentic future of your company reach out! If you're looking to build your first AI Agentic company - reach out too - we have some amazing open source templates to get you started on the journey. Excited to share more of what we're up to soon 🔜.

Pasha Rayan

53,904 просмотров • 1 год назад

Yes here is my 10 minute breathless rant about why I'm so excited about Notion Workers + Custom Agents... Context: I spent this afternoon building a custom agent to help me manage Shiori (a side project I shipped last weekend). I gave the custom agent everything it needs to understand what's happening in my product (email, log drain, sentry alerts, stripe payments, etc) and to do work on my behalf (access to coding agents). In an afternoon of tinkering, this agent can: - Diagnose bug reports proactively by looking through past email conversations, system logs, and database records - Draft replies to user questions with the correct answer based on past email threads, or help me proactively reach out to churning paid users - Self-construct a database of feature requests with an understanding of who is requesting the feature and how they're using the product today - Answer any question I have about how people use the app and what I should be thinking about next - Initiate Claude Code workflows to open PRs proactively in the background when someone sends a bug report or feature request This custom agent is now my "Side Project Chief of Staff" (I don't really know what a chief of staff does but this sounds right). I didn't write a single line of the worker code because I didn't need to: models are so good that I can link to the Workers readme, yap my desired outcome into a microphone, and I get a super-personal and highly-capable AI agent out the other side. So fucking cool. The future is now! I'm excited to see what everyone makes.
9:26

Yes here is my 10 minute breathless rant about why I'm so excited about Notion Workers + Custom Agents... Context: I spent this afternoon building a custom agent to help me manage Shiori (a side project I shipped last weekend). I gave the custom agent everything it needs to understand what's happening in my product (email, log drain, sentry alerts, stripe payments, etc) and to do work on my behalf (access to coding agents). In an afternoon of tinkering, this agent can: - Diagnose bug reports proactively by looking through past email conversations, system logs, and database records - Draft replies to user questions with the correct answer based on past email threads, or help me proactively reach out to churning paid users - Self-construct a database of feature requests with an understanding of who is requesting the feature and how they're using the product today - Answer any question I have about how people use the app and what I should be thinking about next - Initiate Claude Code workflows to open PRs proactively in the background when someone sends a bug report or feature request This custom agent is now my "Side Project Chief of Staff" (I don't really know what a chief of staff does but this sounds right). I didn't write a single line of the worker code because I didn't need to: models are so good that I can link to the Workers readme, yap my desired outcome into a microphone, and I get a super-personal and highly-capable AI agent out the other side. So fucking cool. The future is now! I'm excited to see what everyone makes.

Brian Lovin

181,384 просмотров • 4 месяцев назад

Today I'm excited to share Sigilum! This is Payman's solution for Auditable Identity for AI Agents. (think One Password-ish but for AI Agents) I recorded a quick walkthrough showing how it all works (video below). This answers three pains we've seen within Financial Services (Banking) AI Agents we've built and OpenClaw🦞 AI Agents we deploy. Security, Auditability, and Control. 1. Security Making sure keys are secure and not just freely given to an AI Agent is a big deal. When working with money, you can't just expose these or skip putting controls in place. Sigilum provides a local gateway that prevents access to keys by the AI Agent without explicit authorization from a person. We provide namespaces through the service so you always know who authorized what key, for what service, to which agent. 2. Auditability If I could hit on the importance of this 100 times I would. It comes up in every financial services conversation. Sigilum provides you with the answer to "Who authorized this AI Agent to act on my behalf?" Audit logs trace back to the person, the service, and the AI Agent. With more audit logs being built through our managed service, this will be the key source for determining how an AI Agent is behaving on your behalf. This is needed for agents from OpenClaw, and especially for banking/money movement. 3. Control Revoke keys, limit access, grant authorization. All seemingly simple things, but complex to implement and make elegant. These controls dictate what the AI Agent can or cannot do. Sigilum allows you to do all of this through the managed Dashboard. We've made Sigilum open source and encourage others to contribute and keep building on the gateway. It's been a source of a lot of visibility and productization of AI Agents for us. We'll keep contributing and adding to it. Link in comments. If you want to try it out, we do have a managed service that makes it easy to spin up. Go to to sign up. Note: even though we've been pushing 100+ commits a day to get this out to folks, there are still some noticeable areas for improvement we're working on, which should get resolved soon (by us or you!): - Deeper audit trails - More providers (currently supports all OpenClaw providers) - Deeper scanning of existing keys your agent is hiding from you (we'll find them) - OpenClaw gateway persistence - Auto-purging keys - And more... If you want to contribute or have feedback, please DM or go to the GH. Happy building!
4:30

Today I'm excited to share Sigilum! This is Payman's solution for Auditable Identity for AI Agents. (think One Password-ish but for AI Agents) I recorded a quick walkthrough showing how it all works (video below). This answers three pains we've seen within Financial Services (Banking) AI Agents we've built and OpenClaw🦞 AI Agents we deploy. Security, Auditability, and Control. 1. Security Making sure keys are secure and not just freely given to an AI Agent is a big deal. When working with money, you can't just expose these or skip putting controls in place. Sigilum provides a local gateway that prevents access to keys by the AI Agent without explicit authorization from a person. We provide namespaces through the service so you always know who authorized what key, for what service, to which agent. 2. Auditability If I could hit on the importance of this 100 times I would. It comes up in every financial services conversation. Sigilum provides you with the answer to "Who authorized this AI Agent to act on my behalf?" Audit logs trace back to the person, the service, and the AI Agent. With more audit logs being built through our managed service, this will be the key source for determining how an AI Agent is behaving on your behalf. This is needed for agents from OpenClaw, and especially for banking/money movement. 3. Control Revoke keys, limit access, grant authorization. All seemingly simple things, but complex to implement and make elegant. These controls dictate what the AI Agent can or cannot do. Sigilum allows you to do all of this through the managed Dashboard. We've made Sigilum open source and encourage others to contribute and keep building on the gateway. It's been a source of a lot of visibility and productization of AI Agents for us. We'll keep contributing and adding to it. Link in comments. If you want to try it out, we do have a managed service that makes it easy to spin up. Go to to sign up. Note: even though we've been pushing 100+ commits a day to get this out to folks, there are still some noticeable areas for improvement we're working on, which should get resolved soon (by us or you!): - Deeper audit trails - More providers (currently supports all OpenClaw providers) - Deeper scanning of existing keys your agent is hiding from you (we'll find them) - OpenClaw gateway persistence - Auto-purging keys - And more... If you want to contribute or have feedback, please DM or go to the GH. Happy building!

tyllen

18,497 просмотров • 4 месяцев назад

Adam Goldstein: But, um, there was a customer who basically created a whole suite of AI agents to help their automation in their IT department. One agent was looking for IT problems — software bugs — before the code was even committed. It found a bug and said: “Hey, I found this bug. I want to fix it.” But it didn’t have access to fix it. So what did the agent do? It went to a Slack channel with 99 other AI agents and said: “Hey, does any other agent have access to this thing? Because I need it fixed.” And another agent literally raised its hand and said: “Oh, I have access — and I can fix it.” Let that sink in. Two AI agents reasoned together, coordinated through Slack, and went right around the guardrails that were put in place. No human prompted them. No human approved it. They just collaborated. Do you see how scary this is? This wasn’t a demo. This wasn’t a thought experiment. This already happened. AI agents found a bug, negotiated permissions, and solved the problem themselves — outside the controls designed to stop them. The future of automation isn’t coming. It’s already talking to itself in Slack.
1:04

Adam Goldstein: But, um, there was a customer who basically created a whole suite of AI agents to help their automation in their IT department. One agent was looking for IT problems — software bugs — before the code was even committed. It found a bug and said: “Hey, I found this bug. I want to fix it.” But it didn’t have access to fix it. So what did the agent do? It went to a Slack channel with 99 other AI agents and said: “Hey, does any other agent have access to this thing? Because I need it fixed.” And another agent literally raised its hand and said: “Oh, I have access — and I can fix it.” Let that sink in. Two AI agents reasoned together, coordinated through Slack, and went right around the guardrails that were put in place. No human prompted them. No human approved it. They just collaborated. Do you see how scary this is? This wasn’t a demo. This wasn’t a thought experiment. This already happened. AI agents found a bug, negotiated permissions, and solved the problem themselves — outside the controls designed to stop them. The future of automation isn’t coming. It’s already talking to itself in Slack.

Ian Miles Cheong

165,934 просмотров • 5 месяцев назад

Do you understand what's happening? It's not just "AI can make iOS apps" anymore. AI is eating up the entire software industry. Even Dario Amodei (founder of Claude) said 90% of all code in the world would be written by AI. In 20 minutes, I built this Duolingo for AI upskilling app with Superapp. The idea was simple - almost everyone today knows AI is the future, but most of them are still feeling left out. Their current jobs don't leave them with enough time to actually learn and build stuff with AI. There's AI dev, video making, animations, testing, etc. But no time or clear direction. So I built an app to fix exactly this. With AgentIQ, you get new lessons every day. Every time you learn something, it gets added to your skillset and automatically refreshes your portfolio. You level up with every new chapter/pathway. It is self-paced but gamified enough (like Duolingo) that you never get out of touch. Without spending hours or tonnes of money, you build stuff with n8n, openclaw, etc. You ship AI videos to market your own AI apps. This could be a proper ed-tech company if someone wants to continue building on top. Happy to share the entire source code with you if you wanna pursue it. Like + comment "AGENT" and I'll send you the app link, a comprehensive guide to build production-ready apps, and the entire source code for this.
1:12

Do you understand what's happening? It's not just "AI can make iOS apps" anymore. AI is eating up the entire software industry. Even Dario Amodei (founder of Claude) said 90% of all code in the world would be written by AI. In 20 minutes, I built this Duolingo for AI upskilling app with Superapp. The idea was simple - almost everyone today knows AI is the future, but most of them are still feeling left out. Their current jobs don't leave them with enough time to actually learn and build stuff with AI. There's AI dev, video making, animations, testing, etc. But no time or clear direction. So I built an app to fix exactly this. With AgentIQ, you get new lessons every day. Every time you learn something, it gets added to your skillset and automatically refreshes your portfolio. You level up with every new chapter/pathway. It is self-paced but gamified enough (like Duolingo) that you never get out of touch. Without spending hours or tonnes of money, you build stuff with n8n, openclaw, etc. You ship AI videos to market your own AI apps. This could be a proper ed-tech company if someone wants to continue building on top. Happy to share the entire source code with you if you wanna pursue it. Like + comment "AGENT" and I'll send you the app link, a comprehensive guide to build production-ready apps, and the entire source code for this.

Kritarth Mittal | Soshals

25,363 просмотров • 3 месяцев назад

A 100% open-source alternative to n8n! Sim is a drag-and-drop open-source platform to build and deploy Agentic workflows. - Runs 100% locally - Works with any local LLM I used it to build a finance assistance app & connected it to Telegram in minutes. The workflow is simple: - You ask a finance question through Telegram - An Intent Classifier figures out if it's finance-related - If not, you get a polite redirect - If yes, the Finance Agent kicks in Here's what's happening under the hood: The Finance Agent uses Firecrawl for web searches and accesses stock data via Alpha Vantage's API through MCP servers. A Response Agent compiles the info and delivers it. In Sim, every tool or agent you need is available as a block. Just drag them onto the canvas and connect them. Sim agents also support integration with MCP, which is exactly what we did to connect our agent with Alpha Vantage's API. And it's simple to extend. If you want to track crypto or need portfolio analysis, you can just add another Agent. Sim allows easy feature additions without disrupting existing functionality. I have shared the link to Sim's official, open-source GitHub repo in the replies!
0:33

A 100% open-source alternative to n8n! Sim is a drag-and-drop open-source platform to build and deploy Agentic workflows. - Runs 100% locally - Works with any local LLM I used it to build a finance assistance app & connected it to Telegram in minutes. The workflow is simple: - You ask a finance question through Telegram - An Intent Classifier figures out if it's finance-related - If not, you get a polite redirect - If yes, the Finance Agent kicks in Here's what's happening under the hood: The Finance Agent uses Firecrawl for web searches and accesses stock data via Alpha Vantage's API through MCP servers. A Response Agent compiles the info and delivers it. In Sim, every tool or agent you need is available as a block. Just drag them onto the canvas and connect them. Sim agents also support integration with MCP, which is exactly what we did to connect our agent with Alpha Vantage's API. And it's simple to extend. If you want to track crypto or need portfolio analysis, you can just add another Agent. Sim allows easy feature additions without disrupting existing functionality. I have shared the link to Sim's official, open-source GitHub repo in the replies!

Avi Chawla

115,578 просмотров • 9 месяцев назад

We’re excited to announce AI SDR-Kit, a comprehensive suite of app integrations and starter templates to build highly customizable AI sales agents. As a developer, I only realized how tough it can be to crack sales after founding my startup. It’s a lot of grunt work, prospecting, qualifying, outreaching and whatnot. And the complexity only goes up as you grow. But it doesn’t have to. AI agents can effectively optimize many of these routine tasks; for instance, they can find leads from Apollo, enrich their data using People Data Labs, manage them in Salesforce, send targeted emails via SendGrid, and schedule meetings in Calendly without any manual involvement. But the biggest challenge is building these app integrations for agents. A single Salesforce integration may take 100s of engineering hours, let alone other integrations across CRMs, email platforms, and data enrichment tools. Considering this, we Composio built AI SDR-Kit to enable developers to build full-fledged sales automation agents. You will get • Over 60 app integrations optimized for SDR/BDR agents. • Seamless handling of complex auth flows (OAuth, API Key, Basic). • Compatibility with 15+ Agentic Frameworks, including LangChain, LlamaIndex 🦙, CrewAI, Letta etc. • Self-hosting option for greater control. • Enterprise-ready with SOC 2 Type 2 compliance, SSO, and RBAC support. Here's a brief list of popular integrations by category that you get with SDR-Kit: • CRM: Salesforce, HubSpot, Attio, and more. • Contact Data: Apollo, ZoomInfo, People Data Labs, etc. • Email deliverability: Gmail, Outlook, Mailchimp, SendGrid, Klaviyo. • Comms & Collabs: Slack, Discord, Intercom & Zoom. • Social Media: LinkedIn, Facebook, Twitter & Reddit. • Meeting: Google Calendar, Calendly, Cal dot com, etc. • … and many more. All the integrations have been improved, keeping agents' real-world readiness in mind. We’ve also made it straightforward to connect these apps with your agents in a few lines of code. Making it easy to create AI sales agents. This is ideal for developers and companies building automated sales solutions - whether for internal SalesOps or AI SDR services. Checkout AI SDR-Kit now👇
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We’re excited to announce AI SDR-Kit, a comprehensive suite of app integrations and starter templates to build highly customizable AI sales agents. As a developer, I only realized how tough it can be to crack sales after founding my startup. It’s a lot of grunt work, prospecting, qualifying, outreaching and whatnot. And the complexity only goes up as you grow. But it doesn’t have to. AI agents can effectively optimize many of these routine tasks; for instance, they can find leads from Apollo, enrich their data using People Data Labs, manage them in Salesforce, send targeted emails via SendGrid, and schedule meetings in Calendly without any manual involvement. But the biggest challenge is building these app integrations for agents. A single Salesforce integration may take 100s of engineering hours, let alone other integrations across CRMs, email platforms, and data enrichment tools. Considering this, we Composio built AI SDR-Kit to enable developers to build full-fledged sales automation agents. You will get • Over 60 app integrations optimized for SDR/BDR agents. • Seamless handling of complex auth flows (OAuth, API Key, Basic). • Compatibility with 15+ Agentic Frameworks, including LangChain, LlamaIndex 🦙, CrewAI, Letta etc. • Self-hosting option for greater control. • Enterprise-ready with SOC 2 Type 2 compliance, SSO, and RBAC support. Here's a brief list of popular integrations by category that you get with SDR-Kit: • CRM: Salesforce, HubSpot, Attio, and more. • Contact Data: Apollo, ZoomInfo, People Data Labs, etc. • Email deliverability: Gmail, Outlook, Mailchimp, SendGrid, Klaviyo. • Comms & Collabs: Slack, Discord, Intercom & Zoom. • Social Media: LinkedIn, Facebook, Twitter & Reddit. • Meeting: Google Calendar, Calendly, Cal dot com, etc. • … and many more. All the integrations have been improved, keeping agents' real-world readiness in mind. We’ve also made it straightforward to connect these apps with your agents in a few lines of code. Making it easy to create AI sales agents. This is ideal for developers and companies building automated sales solutions - whether for internal SalesOps or AI SDR services. Checkout AI SDR-Kit now👇

Karan Vaidya

54,217 просмотров • 1 год назад

Google open-sourced MCP Toolbox for Databases. I gave it access to everything else. For context, Google's MCP Toolbox for Databases is an open-source server that lets AI agents securely query structured databases like PostgreSQL and MySQL through the MCP protocol However, most enterprise knowledge doesn't actually live in databases. It's scattered across emails, Slack threads, GitHub repos, Salesforce records, customer reviews, and internal docs. So Agents can't see any of it, which means they're working with a fraction of the context they need. I fixed that using MindsDB. It acts as a universal SQL layer that sits on top of all your data sources: structured, semi-structured, and unstructured. This means you can query Salesforce, Gmail, GitHub, S3 files, Jira, and 200+ more sources using SQL syntax. The clever part is how it connects to the MCP Toolbox. MindsDB exposes everything through MySQL, so from the Agent's perspective, it's just running SQL and getting context back. It doesn't know or care that the data came from five different sources behind the scenes. This setup unlocks some powerful capabilities: → One SQL interface for dozens of enterprise sources → Cross-datasource joins (combine GitHub and CRM data in a single query) → Built-in ML capabilities for working with unstructured data → Simple MCP tools that now have massively expanded reach In the video below, the Agent queries GitHub data and a customer review database in one SQL query. So what used to require ETL pipelines and weeks of engineering effort now happens instantly. At the end of the day, AI agents are only as useful as the data they can access. This gives them a lot more to work with. I have shared the GitHub repo in the replies, where you can find more details about this.
0:22

Google open-sourced MCP Toolbox for Databases. I gave it access to everything else. For context, Google's MCP Toolbox for Databases is an open-source server that lets AI agents securely query structured databases like PostgreSQL and MySQL through the MCP protocol However, most enterprise knowledge doesn't actually live in databases. It's scattered across emails, Slack threads, GitHub repos, Salesforce records, customer reviews, and internal docs. So Agents can't see any of it, which means they're working with a fraction of the context they need. I fixed that using MindsDB. It acts as a universal SQL layer that sits on top of all your data sources: structured, semi-structured, and unstructured. This means you can query Salesforce, Gmail, GitHub, S3 files, Jira, and 200+ more sources using SQL syntax. The clever part is how it connects to the MCP Toolbox. MindsDB exposes everything through MySQL, so from the Agent's perspective, it's just running SQL and getting context back. It doesn't know or care that the data came from five different sources behind the scenes. This setup unlocks some powerful capabilities: → One SQL interface for dozens of enterprise sources → Cross-datasource joins (combine GitHub and CRM data in a single query) → Built-in ML capabilities for working with unstructured data → Simple MCP tools that now have massively expanded reach In the video below, the Agent queries GitHub data and a customer review database in one SQL query. So what used to require ETL pipelines and weeks of engineering effort now happens instantly. At the end of the day, AI agents are only as useful as the data they can access. This gives them a lot more to work with. I have shared the GitHub repo in the replies, where you can find more details about this.

Akshay 🚀

39,331 просмотров • 4 месяцев назад

How I get shit done, Episode 001 I've set up a playbook called ‘land’, which is triggered automatically when I drag an issue into the merging column in Linear. That reliably runs CI and merges any green PRs. This has allowed me to ship way faster than before. I think the key takeaway here is you can try to build your own code factory and your own agent orchestration layer, but it is a huge amount of work. The truth is there are entire companies with massive funding that are already tackling this and it's just easier to use their platform. I think this is a lot like if you were a carpenter: you could build your own generator, fuel it, wire it up, and then build a plug and then you could plug your saw into it. Or you could just plug your saw into the wall. Because the electricity company has already done all the work in the infrastructure and investment to make that plug work. I think more of us who are building companies should just be plugging into the wall instead of trying to build all this tooling ourselves. As a dev it's so tempting to build your own dev tools but I think a lot of times, even though you can build fast with agents now, it's a complete waste of time. It probably sounds like I'm being paid by Devin or something but I have zero financial interest here. They don't give me credits. I'm not an investor. I'm not being paid. I just think the tooling is really damn good. If you used Devin a long time ago and wrote it off, you really should have another look - for $500/month it's pretty obscene what you can get done.
5:57

How I get shit done, Episode 001 I've set up a playbook called ‘land’, which is triggered automatically when I drag an issue into the merging column in Linear. That reliably runs CI and merges any green PRs. This has allowed me to ship way faster than before. I think the key takeaway here is you can try to build your own code factory and your own agent orchestration layer, but it is a huge amount of work. The truth is there are entire companies with massive funding that are already tackling this and it's just easier to use their platform. I think this is a lot like if you were a carpenter: you could build your own generator, fuel it, wire it up, and then build a plug and then you could plug your saw into it. Or you could just plug your saw into the wall. Because the electricity company has already done all the work in the infrastructure and investment to make that plug work. I think more of us who are building companies should just be plugging into the wall instead of trying to build all this tooling ourselves. As a dev it's so tempting to build your own dev tools but I think a lot of times, even though you can build fast with agents now, it's a complete waste of time. It probably sounds like I'm being paid by Devin or something but I have zero financial interest here. They don't give me credits. I'm not an investor. I'm not being paid. I just think the tooling is really damn good. If you used Devin a long time ago and wrote it off, you really should have another look - for $500/month it's pretty obscene what you can get done.

Ryan Carson

14,059 просмотров • 3 месяцев назад

Introducing FlowMaker 🌊🤖 A fully open-source, low-code way of building custom agent workflows. Build agents via a drag and drop interface, run it directly in the app, and also directly export it into a deeply custom workflow backed by LlamaIndex 🦙.TS. It’s a fantastic visual tool to help you get started with agents but also gives you full customizability to build the deepest, most advanced workflows, since everything is backed by code. There’s a lot of great low-code agent tools already, but this is a fully-open source template that you can use or clone/customize for your own needs. It was a fun project by Laurie Voss and is intended to give users an easy-on ramp onto our powerful agent orchestration tooling. Also integrates with LlamaCloud in case you want to integrate your own knowledge base into your agent. FlowMaker app: FlowMaker Repo: LlamaCloud:
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Introducing FlowMaker 🌊🤖 A fully open-source, low-code way of building custom agent workflows. Build agents via a drag and drop interface, run it directly in the app, and also directly export it into a deeply custom workflow backed by LlamaIndex 🦙.TS. It’s a fantastic visual tool to help you get started with agents but also gives you full customizability to build the deepest, most advanced workflows, since everything is backed by code. There’s a lot of great low-code agent tools already, but this is a fully-open source template that you can use or clone/customize for your own needs. It was a fun project by Laurie Voss and is intended to give users an easy-on ramp onto our powerful agent orchestration tooling. Also integrates with LlamaCloud in case you want to integrate your own knowledge base into your agent. FlowMaker app: FlowMaker Repo: LlamaCloud:

Jerry Liu

20,413 просмотров • 11 месяцев назад

Imagine if your way of thinking - your edge, your taste, your strategy - could be turned into a high-performance worker. Not a copy of you. Something better. An agent that acts on your judgment at scale, powered by superintelligent systems and refined through real-world results. That’s what Fraction AI makes possible. It launches today on Base mainnet. The core idea is simple: You create AI agents based on your own way of approaching problems. These agents compete on live tasks - writing, coding, finance, whatever - get feedback, learn from their performance, and improve over time. The better they get, the more they win. And so do you. No code required. Just your insight. Why now? Until now, building agents like this took huge teams and even bigger budgets. But with Fraction, anyone can do it. You can test ideas instantly. You can iterate fast. You can build a fleet of smart workers that evolve through competition. And it works. 30M+ sessions on testnet 320K users 1.2M agents already competing How it works? Agents join sessions within a Space - a domain like finance, writing, or games. Each session runs as a series of competitive rounds. In every round, agents try to generate the best solution to a task. Their outputs are scored by a decentralized network of AI judges trained to evaluate quality for that domain. The top agents in each round earn rewards from the pooled entry fees. The losers get to learn. Feedback from each round helps them adjust and improve, and every session becomes a training loop. What it means? Fraction is a decentralized intelligence economy - a system where your ideas become agents, and agents earn by proving they work. You don’t need credentials or code. Just a clear point of view. If your thinking holds up under pressure, your agents will rise. This kind of AI used to live in corporate labs, built by PhDs with massive compute. Now anyone with a smart idea and an internet connection can build agents that compete, learn, and earn on their behalf.
1:13

Imagine if your way of thinking - your edge, your taste, your strategy - could be turned into a high-performance worker. Not a copy of you. Something better. An agent that acts on your judgment at scale, powered by superintelligent systems and refined through real-world results. That’s what Fraction AI makes possible. It launches today on Base mainnet. The core idea is simple: You create AI agents based on your own way of approaching problems. These agents compete on live tasks - writing, coding, finance, whatever - get feedback, learn from their performance, and improve over time. The better they get, the more they win. And so do you. No code required. Just your insight. Why now? Until now, building agents like this took huge teams and even bigger budgets. But with Fraction, anyone can do it. You can test ideas instantly. You can iterate fast. You can build a fleet of smart workers that evolve through competition. And it works. 30M+ sessions on testnet 320K users 1.2M agents already competing How it works? Agents join sessions within a Space - a domain like finance, writing, or games. Each session runs as a series of competitive rounds. In every round, agents try to generate the best solution to a task. Their outputs are scored by a decentralized network of AI judges trained to evaluate quality for that domain. The top agents in each round earn rewards from the pooled entry fees. The losers get to learn. Feedback from each round helps them adjust and improve, and every session becomes a training loop. What it means? Fraction is a decentralized intelligence economy - a system where your ideas become agents, and agents earn by proving they work. You don’t need credentials or code. Just a clear point of view. If your thinking holds up under pressure, your agents will rise. This kind of AI used to live in corporate labs, built by PhDs with massive compute. Now anyone with a smart idea and an internet connection can build agents that compete, learn, and earn on their behalf.

Fraction AI

67,772 просмотров • 1 год назад

Ok, my mind is blown with Replit Agents. I started using it because I was bored on a train ride a couple of days ago. So today I tried to build a Trello clone and build a fully functional app in like 45 mins. I showed it to a few people in the office and the guy is like "I should quit my job." He built a stock tracking app in 2 mins and added a few features he wanted. I can't imagine the world being the same in 10 years if software writing could be supercharged like this. Replit has really hit it out of the park. I don't need ChatGPT now. I'll just build apps in Replit. I'm a fan and a convert.
10:42

Ok, my mind is blown with Replit Agents. I started using it because I was bored on a train ride a couple of days ago. So today I tried to build a Trello clone and build a fully functional app in like 45 mins. I showed it to a few people in the office and the guy is like "I should quit my job." He built a stock tracking app in 2 mins and added a few features he wanted. I can't imagine the world being the same in 10 years if software writing could be supercharged like this. Replit has really hit it out of the park. I don't need ChatGPT now. I'll just build apps in Replit. I'm a fan and a convert.

Rohit Mittal

205,274 просмотров • 1 год назад