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I was laid off so I rebuilt their product but better (in 2 weeks from scratch) Open Canvas - a multiplayer site builder with an agent at the cursor. Most website builders ask you to fill in a template.I built one that lets you design - on a free-form...

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Aayushman Singh

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195,651 просмотров • 3 месяцев назад •via X (Twitter)

ОбразованиеЗдоровье и велнесНаука и технологии
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Orynth Product Review EP12 Herald lets you deploy a real AI agent in one click. No code, no API keys, no cost. Pick a template, connect Telegram, and your agent is live in under 60 seconds, running 24/7 with memory and modular skills. Powered by Nous Research, one of the most respected names in open-source AI. Built by gigaevm ($/acc), who got tired of agent platforms charging $50/month and locking you into one model, so he made the free version. A real product listed on Orynth with its own token solana:BT91Uvx89v6XvJKMn6GiwvPAxN9Lo2MPTVWkuGg5vory In this twelfth episode, we break down what Herald is building, the builder behind it, and why a free, instant AI agent deployer is worth a look.
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Orynth Product Review EP12 Herald lets you deploy a real AI agent in one click. No code, no API keys, no cost. Pick a template, connect Telegram, and your agent is live in under 60 seconds, running 24/7 with memory and modular skills. Powered by Nous Research, one of the most respected names in open-source AI. Built by gigaevm ($/acc), who got tired of agent platforms charging $50/month and locking you into one model, so he made the free version. A real product listed on Orynth with its own token solana:BT91Uvx89v6XvJKMn6GiwvPAxN9Lo2MPTVWkuGg5vory In this twelfth episode, we break down what Herald is building, the builder behind it, and why a free, instant AI agent deployer is worth a look.

Orynth News

16,871 просмотров • 3 месяцев назад

i just cracked the code on ai digital products... every product costs $0 to build and takes under 2 minutes to make. i built an ai agent that turns any niche into a ready-to-export digital product in whatever format you want, pdf, notion template, ebook, guide, you name it. drop in your niche and one problem. the system analyzes demand, maps buyer desires, builds you the full product, and you watch it happen in real time. then the agent gives you the path, what to do next, rates each module, edits everything, practically sells it for you. you just follow it. i'm making full end-to-end products in under 2 minutes with this system. so i packaged the whole thing up. you're getting an ai that: - picks your niche - calculates demand - builds the product in any format - gives you the selling blueprint to go with it. rt + reply "product" and i'll show you how to access (must be following so i can dm)
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i just cracked the code on ai digital products... every product costs $0 to build and takes under 2 minutes to make. i built an ai agent that turns any niche into a ready-to-export digital product in whatever format you want, pdf, notion template, ebook, guide, you name it. drop in your niche and one problem. the system analyzes demand, maps buyer desires, builds you the full product, and you watch it happen in real time. then the agent gives you the path, what to do next, rates each module, edits everything, practically sells it for you. you just follow it. i'm making full end-to-end products in under 2 minutes with this system. so i packaged the whole thing up. you're getting an ai that: - picks your niche - calculates demand - builds the product in any format - gives you the selling blueprint to go with it. rt + reply "product" and i'll show you how to access (must be following so i can dm)

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Your AI trading wallet companion, Clawlett is now open to every Telegram user. Most bots wait for you to type. Signal groups flood you with noise. Dashboards sit in a tab you forget to check. Clawlett was built around one premise: trading as a habit, growing with you. - Script your strategy once. - Define your triggers, set real-time alerts, and conditions. - Your agent executes exactly as planned — regardless of how you're feeling that day. Built on Base, you hold the master key. The agent executes, but can never withdraw to itself. Just hatch your Clawlett and go. Try it now -
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Your AI trading wallet companion, Clawlett is now open to every Telegram user. Most bots wait for you to type. Signal groups flood you with noise. Dashboards sit in a tab you forget to check. Clawlett was built around one premise: trading as a habit, growing with you. - Script your strategy once. - Define your triggers, set real-time alerts, and conditions. - Your agent executes exactly as planned — regardless of how you're feeling that day. Built on Base, you hold the master key. The agent executes, but can never withdraw to itself. Just hatch your Clawlett and go. Try it now -

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22,948 просмотров • 5 месяцев назад

What Will Separate the Winners From the Losers in AI Agents “The product that wins this category will have a network effect at the agent level. One feature our power users love most is Agent-to-Agent. You ask your townie a question; it realizes a coworker’s townie has the answer, so it just goes and asks it. Once your whole team is on that, it’s really difficult to imagine moving to a different product. No one has figured out multi-user, multiplayer AI yet. I think that’s the moat.” Jean-Denis Greze 💡 Love to hear your thoughts on this sam lessin 🏴‍☠️ Harrison Chase Flo Crivello Manny Medina
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What Will Separate the Winners From the Losers in AI Agents “The product that wins this category will have a network effect at the agent level. One feature our power users love most is Agent-to-Agent. You ask your townie a question; it realizes a coworker’s townie has the answer, so it just goes and asks it. Once your whole team is on that, it’s really difficult to imagine moving to a different product. No one has figured out multi-user, multiplayer AI yet. I think that’s the moat.” Jean-Denis Greze 💡 Love to hear your thoughts on this sam lessin 🏴‍☠️ Harrison Chase Flo Crivello Manny Medina

Harry Stebbings

22,844 просмотров • 20 дней назад

LOVE was made entirely inside invideo. Not with one agent. I built a multi-agent system — a director, and around it casting, locations, storyboard, then one agent per main scene, all working at the same time. In the breakdown I go through the things that struck me most: — Expert agents talking to each other — Infinite memory — Slate editor — And a Project Analyst at the end, interviewing every other agent on what to change next time There's a lot more to say. I'll take it one thing at a time in the next posts. Invideo Agent Two isn't just an agent. It's a collaborator you shape into what you need. Full breakdown ↓
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LOVE was made entirely inside invideo. Not with one agent. I built a multi-agent system — a director, and around it casting, locations, storyboard, then one agent per main scene, all working at the same time. In the breakdown I go through the things that struck me most: — Expert agents talking to each other — Infinite memory — Slate editor — And a Project Analyst at the end, interviewing every other agent on what to change next time There's a lot more to say. I'll take it one thing at a time in the next posts. Invideo Agent Two isn't just an agent. It's a collaborator you shape into what you need. Full breakdown ↓

Marco "Shikoba" Riccetti

14,813 просмотров • 1 месяц назад

This is insane. An AI agent can run every boring job in outbound. We spent the last 6 months building ours. Here are my 8 favorite agents to build: Replies get sorted before we open the inbox. Campaigns go live from one command. Weak inboxes pull themselves out before they hurt a domain. Here are the agents behind it: 1. Reply Agent Reads every reply and drafts the response. A human reviews, edits, and sends. 2. Mailbox Health Agent Watches inbox and domain health. It predicts when you need new mailboxes, then buys and warms them. 3. Campaign Optimizer Agent Checks every live campaign every 6 hours. If 500+ leads were emailed and replies are under 4%, it tests new copy, replaces inboxes replying under 1%, and shifts sending to better hours. 4. Lead Qualification Agent Scores each lead by company size, industry, and tech stack. It enriches the record, updates your CRM, and only loads qualified leads into campaigns. High-priority prospect? You get a Slack ping. 5. Meeting Booking Agent Finds meeting requests inside replies. It books the slot, writes prep notes using the lead's background, sends reminders, and logs the outcome. 6. Pipeline Progression Agent Tracks opens, clicks, and website visits. It moves the CRM stage, triggers the next sequence, and creates a task when a lead shows real intent. 7. Copywriting Agent Writes cold emails and follow-ups in the campaign's voice. 8. Analytics Agent Watches campaign metrics in real time and explains what to fix in plain language. We built ours with custom code. Smartlead's SmartAgents let you build agents like these from a plain-English prompt, inside the platform where your campaigns already run. If you repeat an outbound task more than twice a week, that is an agent you have not built yet. Which one would you build first?
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This is insane. An AI agent can run every boring job in outbound. We spent the last 6 months building ours. Here are my 8 favorite agents to build: Replies get sorted before we open the inbox. Campaigns go live from one command. Weak inboxes pull themselves out before they hurt a domain. Here are the agents behind it: 1. Reply Agent Reads every reply and drafts the response. A human reviews, edits, and sends. 2. Mailbox Health Agent Watches inbox and domain health. It predicts when you need new mailboxes, then buys and warms them. 3. Campaign Optimizer Agent Checks every live campaign every 6 hours. If 500+ leads were emailed and replies are under 4%, it tests new copy, replaces inboxes replying under 1%, and shifts sending to better hours. 4. Lead Qualification Agent Scores each lead by company size, industry, and tech stack. It enriches the record, updates your CRM, and only loads qualified leads into campaigns. High-priority prospect? You get a Slack ping. 5. Meeting Booking Agent Finds meeting requests inside replies. It books the slot, writes prep notes using the lead's background, sends reminders, and logs the outcome. 6. Pipeline Progression Agent Tracks opens, clicks, and website visits. It moves the CRM stage, triggers the next sequence, and creates a task when a lead shows real intent. 7. Copywriting Agent Writes cold emails and follow-ups in the campaign's voice. 8. Analytics Agent Watches campaign metrics in real time and explains what to fix in plain language. We built ours with custom code. Smartlead's SmartAgents let you build agents like these from a plain-English prompt, inside the platform where your campaigns already run. If you repeat an outbound task more than twice a week, that is an agent you have not built yet. Which one would you build first?

Hosun Chung

156,625 просмотров • 2 месяцев назад

Code-first prototypes are fast to build. Getting feedback on them is not. A design lead can't leave a comment on one specific state. An engineer can't see the full flow at a glance. The thing that makes a prototype great for building makes it awkward for aligning. So Amy Lima and I built a skill for that (well, mostly Amy). It takes a live localhost prototype and brings it into Figma. Each flow broken out into its own frame, built from your design system components, annotated with the interaction and implementation details. Now the canvas is where you review and align. We refined it live in the video too! My favorite part is a habit I like to lean on: make the agent take one more round trip to validate its own work before it claims it's done. AI sometimes has the tendency to confidently tell you the job's finished when it isn't. Thanks to Amy and the whole Figma crew for allowing me to be a part of this!
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Code-first prototypes are fast to build. Getting feedback on them is not. A design lead can't leave a comment on one specific state. An engineer can't see the full flow at a glance. The thing that makes a prototype great for building makes it awkward for aligning. So Amy Lima and I built a skill for that (well, mostly Amy). It takes a live localhost prototype and brings it into Figma. Each flow broken out into its own frame, built from your design system components, annotated with the interaction and implementation details. Now the canvas is where you review and align. We refined it live in the video too! My favorite part is a habit I like to lean on: make the agent take one more round trip to validate its own work before it claims it's done. AI sometimes has the tendency to confidently tell you the job's finished when it isn't. Thanks to Amy and the whole Figma crew for allowing me to be a part of this!

TJ Pitre

13,477 просмотров • 3 месяцев назад

Your agents can't keep up with real-time data. Especially when it's scattered across dozens of sources. Most teams waste weeks building custom connectors for every database, API, and data warehouse. Then they build ETL pipelines to sync everything. By the time your agent retrieves the data, it's already outdated. Picture this: Your Postgres database updated 5 minutes ago. Your MongoDB collection changed 2 minutes ago. Your agent is still pulling from yesterday's snapshot. This is why most production RAG systems fail. There's a better approach: MindsDB is an open-source AI platform with a federated data engine that lets you query multiple data sources in real-time using SQL - without moving any data. Here's what makes it different: ↳ Your data stays in place. No ETL pipelines or data duplication ↳ Query Postgres, MongoDB, REST APIs, and more using consistent SQL ↳ JOIN across different sources in real-time with a unified interface ↳ Works with both structured and un-structured data And here's the best part: You don't even need to write SQL. Just describe what you want in plain English, and MindsDB converts it to SQL automatically. The system does all the heavy lifting. The breakthrough for AI agents is simple: When data updates at the source, your agent gets fresh results immediately. No sync delays. No stale embeddings. No custom code for each integration. You can literally write a SQL query that joins a Postgres table with a MongoDB collection and gets live results. This is what production AI applications need but rarely get. In this video, I give you a complete walkthrough of what we just discussed and how to actually do it. Make sure you watch this till the end. I've shared the link to MindsDB's GitHub repo in the next tweet!
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Your agents can't keep up with real-time data. Especially when it's scattered across dozens of sources. Most teams waste weeks building custom connectors for every database, API, and data warehouse. Then they build ETL pipelines to sync everything. By the time your agent retrieves the data, it's already outdated. Picture this: Your Postgres database updated 5 minutes ago. Your MongoDB collection changed 2 minutes ago. Your agent is still pulling from yesterday's snapshot. This is why most production RAG systems fail. There's a better approach: MindsDB is an open-source AI platform with a federated data engine that lets you query multiple data sources in real-time using SQL - without moving any data. Here's what makes it different: ↳ Your data stays in place. No ETL pipelines or data duplication ↳ Query Postgres, MongoDB, REST APIs, and more using consistent SQL ↳ JOIN across different sources in real-time with a unified interface ↳ Works with both structured and un-structured data And here's the best part: You don't even need to write SQL. Just describe what you want in plain English, and MindsDB converts it to SQL automatically. The system does all the heavy lifting. The breakthrough for AI agents is simple: When data updates at the source, your agent gets fresh results immediately. No sync delays. No stale embeddings. No custom code for each integration. You can literally write a SQL query that joins a Postgres table with a MongoDB collection and gets live results. This is what production AI applications need but rarely get. In this video, I give you a complete walkthrough of what we just discussed and how to actually do it. Make sure you watch this till the end. I've shared the link to MindsDB's GitHub repo in the next tweet!

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65,672 просмотров • 10 месяцев назад

I tried CapCut Design Studio and understood where design is headed. I transformed my Gumroad ebooks into a complete visual campaign using AI. This is no longer just video editing; it feels like a creative studio powered by AI. Design Studio is a space where you can freely compare, manage, and expand multiple desing versions on one Infinite Canvas Workflow. The interesting thing isn't just that it generates images. The real power is that you can explore, correct, and refine the idea without starting from scratch every time. Shifing from prompt-based output to iterative creative exploration. With AI Agents integrated directly into the canvas, it acts as an instant co-creator anywhere. And that's where the shift happens: AI stops being just a "give me an image" machine and transitions from single output to scalable design production. Features like Batch Text Editing automatically recognize and translate copy across 50+ languages in one click while maintaining the original layout, while Elements editing gives you Flexible Creative Control to fine-tune elements like a raw PSD file. This is no longer just about prompts. It's about designing with AI. #capcutdesignstudio #capcut
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I tried CapCut Design Studio and understood where design is headed. I transformed my Gumroad ebooks into a complete visual campaign using AI. This is no longer just video editing; it feels like a creative studio powered by AI. Design Studio is a space where you can freely compare, manage, and expand multiple desing versions on one Infinite Canvas Workflow. The interesting thing isn't just that it generates images. The real power is that you can explore, correct, and refine the idea without starting from scratch every time. Shifing from prompt-based output to iterative creative exploration. With AI Agents integrated directly into the canvas, it acts as an instant co-creator anywhere. And that's where the shift happens: AI stops being just a "give me an image" machine and transitions from single output to scalable design production. Features like Batch Text Editing automatically recognize and translate copy across 50+ languages in one click while maintaining the original layout, while Elements editing gives you Flexible Creative Control to fine-tune elements like a raw PSD file. This is no longer just about prompts. It's about designing with AI. #capcutdesignstudio #capcut

Don Quijote de la IA

41,801 просмотров • 3 месяцев назад

AI agents are powerful. They're also isolated. Switch fixes that. Here's the thing about most AI agents: they work alone. They don't see what your team is discussing. They don't share context across conversations. Every new chat is a fresh start. If you've ever tried to actually integrate an agent into your team's workflow, you know the friction. Then I found 𝗦𝘄𝗶𝘁𝗰𝗵. It brings AI agents into Slack, Teams, Discord, and Telegram as named participants. They sit in the same rooms as your team, with the same context, history, and participants. What I actually like about it: → Agents join as real participants in channels — not bots you have to Mention every time → Each room carries its own context, history, and rules → Works with Claude Code, OpenAI, LangChain, Google ADK, and custom agents → Open source and self-hostable. Running in minutes. No migration. No lock-in. Just agents where your team already works. Knowledge lives in the room, not in the agent. Switch keeps people, agents, decisions, and work history together so context survives handoffs. It's from Flint AI. Open source. Runs in minutes. 👉 Human + agent teams, actually working together. 📌 Download 𝗦𝘄𝗶𝘁𝗰𝗵 Console → 🚀𝗦𝘄𝗶𝘁𝗰𝗵 is live on Product Hunt: 🔄 Repost if you've ever wished your AI agent could just join the Slack channel. — #AI #Agents #Slack #Teams #Switch #ProductHunt
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AI agents are powerful. They're also isolated. Switch fixes that. Here's the thing about most AI agents: they work alone. They don't see what your team is discussing. They don't share context across conversations. Every new chat is a fresh start. If you've ever tried to actually integrate an agent into your team's workflow, you know the friction. Then I found 𝗦𝘄𝗶𝘁𝗰𝗵. It brings AI agents into Slack, Teams, Discord, and Telegram as named participants. They sit in the same rooms as your team, with the same context, history, and participants. What I actually like about it: → Agents join as real participants in channels — not bots you have to Mention every time → Each room carries its own context, history, and rules → Works with Claude Code, OpenAI, LangChain, Google ADK, and custom agents → Open source and self-hostable. Running in minutes. No migration. No lock-in. Just agents where your team already works. Knowledge lives in the room, not in the agent. Switch keeps people, agents, decisions, and work history together so context survives handoffs. It's from Flint AI. Open source. Runs in minutes. 👉 Human + agent teams, actually working together. 📌 Download 𝗦𝘄𝗶𝘁𝗰𝗵 Console → 🚀𝗦𝘄𝗶𝘁𝗰𝗵 is live on Product Hunt: 🔄 Repost if you've ever wished your AI agent could just join the Slack channel. — #AI #Agents #Slack #Teams #Switch #ProductHunt

Anuj

337,509 просмотров • 21 дней назад

Cursor for contracts is here. Announcing Spellbook's new AI document editor. Doc editing for lawyers is disjointed: you can edit with AI in chat, but then need to "Open in Word" to make manual tweaks without breaking formatting. Alternatively you can use a Word add-in like Spellbook's, but this only allows you to work on one document at a time. For a long time, Mitch and I talked about getting to a real "Cursor for Contracts" experience. With a lot of blood and sweat, we're finally there. Spellbook's new editor combines the best of AI editing and manual editing in one place—while fully supporting rich Word formatting that lawyers rely on. Ask AI to make edits across an entire document set, then review, accept and tweak all in one window. This sounds like a small thing, but the reduction in friction has totally changed my document editing workflow.
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Cursor for contracts is here. Announcing Spellbook's new AI document editor. Doc editing for lawyers is disjointed: you can edit with AI in chat, but then need to "Open in Word" to make manual tweaks without breaking formatting. Alternatively you can use a Word add-in like Spellbook's, but this only allows you to work on one document at a time. For a long time, Mitch and I talked about getting to a real "Cursor for Contracts" experience. With a lot of blood and sweat, we're finally there. Spellbook's new editor combines the best of AI editing and manual editing in one place—while fully supporting rich Word formatting that lawyers rely on. Ask AI to make edits across an entire document set, then review, accept and tweak all in one window. This sounds like a small thing, but the reduction in friction has totally changed my document editing workflow.

Scott Stevenson

57,218 просмотров • 1 месяц назад

Introducing CapCut Design Studio 2.0. A reimagined experience for Design on CapCut Web, making design more intuitive, visual, and exploratory, the way ideas naturally happen. Built on an infinite AI canvas, Design Studio 2.0 brings your references, drafts, iterations, assets, and ideas into one fluid workspace. You can remix visuals, explore endless ideas in one space, edit with brushes, refine layers and elements, and co-create with an AI design agent in real time. Just think visually and create freely. Because maybe, you were always more creative than you thought! Stop templating. Start designing now. Users get 20 free generations per day. RT + comment in 5hr to get 200 free credits.
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Introducing CapCut Design Studio 2.0. A reimagined experience for Design on CapCut Web, making design more intuitive, visual, and exploratory, the way ideas naturally happen. Built on an infinite AI canvas, Design Studio 2.0 brings your references, drafts, iterations, assets, and ideas into one fluid workspace. You can remix visuals, explore endless ideas in one space, edit with brushes, refine layers and elements, and co-create with an AI design agent in real time. Just think visually and create freely. Because maybe, you were always more creative than you thought! Stop templating. Start designing now. Users get 20 free generations per day. RT + comment in 5hr to get 200 free credits.

CapCut

7,359,148 просмотров • 4 месяцев назад

Today we're launching Jitsu MCP. This is an MCP server that lets your agent run your entire event pipeline directly in Claude Code, Claude Desktop, Cursor, or VS Code. Here's how it works: Add the server: claude mcp add --transport http jitsu Run this prompt: "Route my web stream into ClickHouse, but only purchase and signup events. Send a test event, check Live Events, and if anything errors, find the function in the path and fix it." Approve the OAuth prompt once, and all 26 tools are live Your agent wires the streams, watches Live Events, and rewrites a function when one of them throws. It runs the fix against a real event before shipping it, so nothing is persisted until it works. Every change lands in the audit log tagged mcp, so you can tell what the agent did from what a person did. It's all MIT licensed, and it runs against your own deployment. Jitsu is one of the fastest growing open-source CDPs with 5,000+ GitHub stars. Capturing events is unlimited and free, and delivery is free up to 200k events a month. Comment Jitsu and I'll DM you the exact prompts I run in Claude Code to build an event pipeline end to end.
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Today we're launching Jitsu MCP. This is an MCP server that lets your agent run your entire event pipeline directly in Claude Code, Claude Desktop, Cursor, or VS Code. Here's how it works: Add the server: claude mcp add --transport http jitsu Run this prompt: "Route my web stream into ClickHouse, but only purchase and signup events. Send a test event, check Live Events, and if anything errors, find the function in the path and fix it." Approve the OAuth prompt once, and all 26 tools are live Your agent wires the streams, watches Live Events, and rewrites a function when one of them throws. It runs the fix against a real event before shipping it, so nothing is persisted until it works. Every change lands in the audit log tagged mcp, so you can tell what the agent did from what a person did. It's all MIT licensed, and it runs against your own deployment. Jitsu is one of the fastest growing open-source CDPs with 5,000+ GitHub stars. Capturing events is unlimited and free, and delivery is free up to 200k events a month. Comment Jitsu and I'll DM you the exact prompts I run in Claude Code to build an event pipeline end to end.

Soham Mehta

281,726 просмотров • 21 дней назад

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.
1:06

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

47,207 просмотров • 6 месяцев назад

Today, we are launching Depost AI 2. 🎉 I am a bit emotional writing this. The last eight months were intense. But today I am proud of what we built. Because Depost AI 2 is built to become the best and safest AI content team for LinkedIn. We listened to thousands of people who used the first version, and we rebuilt Depost AI from scratch on the official LinkedIn API. The result: - A chat instead of a form, so you brief it like a colleague - Analytics that show what performs for you and why - Four agents that write in your voice and design the graphics to match - A calendar that fills from approved drafts - Approvals, roles, and a separate workspace for every brand - MCP, so the whole team works inside Claude, ChatGPT, or Cursor It is built for B2B founders who need to be visible without losing an hour a day. For marketing teams who need one system, one review flow, and one voice per brand. And for agencies who run LinkedIn for clients and need every brand kept apart. But the bigger vision is this: Depost AI is becoming a content team that understands your brand before it writes a word. It learns from everything you publish. It knows what performs for you and why. It plans, writes, designs, and schedules from that. And nothing goes live until you approve it. Because writing a post is not the hard part. Knowing what to say, saying it well every week, and doing it safely on an account you cannot afford to lose is. Depost AI 2 is the tool we built to solve that. And honestly, the best part right now is watching people brief it for the first time and get a week of drafts back in their own voice. You can start a 7-day free trial today at And if you message me, I will happily walk you through it myself. ❤️
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Today, we are launching Depost AI 2. 🎉 I am a bit emotional writing this. The last eight months were intense. But today I am proud of what we built. Because Depost AI 2 is built to become the best and safest AI content team for LinkedIn. We listened to thousands of people who used the first version, and we rebuilt Depost AI from scratch on the official LinkedIn API. The result: - A chat instead of a form, so you brief it like a colleague - Analytics that show what performs for you and why - Four agents that write in your voice and design the graphics to match - A calendar that fills from approved drafts - Approvals, roles, and a separate workspace for every brand - MCP, so the whole team works inside Claude, ChatGPT, or Cursor It is built for B2B founders who need to be visible without losing an hour a day. For marketing teams who need one system, one review flow, and one voice per brand. And for agencies who run LinkedIn for clients and need every brand kept apart. But the bigger vision is this: Depost AI is becoming a content team that understands your brand before it writes a word. It learns from everything you publish. It knows what performs for you and why. It plans, writes, designs, and schedules from that. And nothing goes live until you approve it. Because writing a post is not the hard part. Knowing what to say, saying it well every week, and doing it safely on an account you cannot afford to lose is. Depost AI 2 is the tool we built to solve that. And honestly, the best part right now is watching people brief it for the first time and get a week of drafts back in their own voice. You can start a 7-day free trial today at And if you message me, I will happily walk you through it myself. ❤️

Atta 🐬

17,864 просмотров • 21 дней назад

Introducing Open MCP Client 🪁 Chat with any MCP server in your own app, just grab a URL from . The team and I vibe coded with Cursor this weekend and built: 1. The first web-based MCP client (link👇) 2. An open-source client you can add into any app How it's built It uses CopilotKit🪁 for the client and interactivity layer, and connects to a 40 line LangGraph ReAct agent that coordinates MCP calls. Hosted on Vercel. Kudos to Suhas Deshpande and Tyler Slaton for hacking and thanks to Harrison Chase for pointers!
1:00

Introducing Open MCP Client 🪁 Chat with any MCP server in your own app, just grab a URL from . The team and I vibe coded with Cursor this weekend and built: 1. The first web-based MCP client (link👇) 2. An open-source client you can add into any app How it's built It uses CopilotKit🪁 for the client and interactivity layer, and connects to a 40 line LangGraph ReAct agent that coordinates MCP calls. Hosted on Vercel. Kudos to Suhas Deshpande and Tyler Slaton for hacking and thanks to Harrison Chase for pointers!

Atai Barkai

299,864 просмотров • 1 год назад

Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.
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Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.

Santiago

230,647 просмотров • 1 год назад

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

Andrew Ng

105,758 просмотров • 1 год назад

I have made over $100k shipping projects with ai. Productivity has gone through the roof but its more stressful than ever tbh. Thats why I built CNVS. Its a place for Ai to not just make you more efficient, but also more organized, like a monk shipping at light speed. Every project gets its own canvas, so you can effortlessly switch between them. Each canvas gets a "recipe", so you can hop right back into deep work in seconds. Eliminating the cognitive overhead of getting started. I built 14 beautiful themes so your brain can start associating the theme with the project. PS - its really hard shipping apps, i hope CNVS makes you feel more in control of your life <3 built with love from a dad working away in the basement. PPS - its a lifetime license because you don't need any more subscriptions in your life. Im shipping new features and improvements based on user feedback every week. PPPS - this uses all your exsisting ai subs ( claude code, codex, cursor, etc.. )
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I have made over $100k shipping projects with ai. Productivity has gone through the roof but its more stressful than ever tbh. Thats why I built CNVS. Its a place for Ai to not just make you more efficient, but also more organized, like a monk shipping at light speed. Every project gets its own canvas, so you can effortlessly switch between them. Each canvas gets a "recipe", so you can hop right back into deep work in seconds. Eliminating the cognitive overhead of getting started. I built 14 beautiful themes so your brain can start associating the theme with the project. PS - its really hard shipping apps, i hope CNVS makes you feel more in control of your life <3 built with love from a dad working away in the basement. PPS - its a lifetime license because you don't need any more subscriptions in your life. Im shipping new features and improvements based on user feedback every week. PPPS - this uses all your exsisting ai subs ( claude code, codex, cursor, etc.. )

Max Blade

31,610 просмотров • 3 месяцев назад