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We built an ai agent that watches user sessions + emails users when they get stuck - hooked into posthog session replays - every session analyzed w/ gemini - agent detects friction + purchase hesitation - auto-sends the right nudge last week we sent 300 behavior-triggered emails

Robert Lukoszko

12,202 subscribers

126,900 次观看 • 7 个月前 •via X (Twitter)

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We built an AI employee that watches every session and reads every log, commit, and Slack message in my company. It: - Fixes bugs as they happen - Emails users when things break - Writes, tests, and ships code I'm extremely excited and also pretty sure I'm building my own replacement

We built an AI employee that watches every session and reads every log, commit, and Slack message in my company. It: - Fixes bugs as they happen - Emails users when things break - Writes, tests, and ships code I'm extremely excited and also pretty sure I'm building my own replacement

Pablo Hansen

47,639 次观看 • 6 个月前

99% of session replays are your app working exactly as expected (hopefully) The other 1% is where the friction hides The bugs. The failed onboarding flows. The conversion leaks. No team has time to watch them all... That's the problem Michael and his co-founder kept hitting at their last company They had analytics. They had session replays. They had ideas to improve conversion. The small fixes always lost to bigger priorities... So they pivoted and built CodeCanary: An AI product engineer that connects to GitHub, PostHog, and Slack It watches your session replays, finds the UX friction, and opens pull requests with the fix Always on. Always shipping. Not dashboards Not alerts Actual fixes 🎙️ Michael Egan, CEO & Co-Founder, CodeCanary on Fondo.com START (full ep in comments) Big thanks to PostHog for making this episode possible!

99% of session replays are your app working exactly as expected (hopefully) The other 1% is where the friction hides The bugs. The failed onboarding flows. The conversion leaks. No team has time to watch them all... That's the problem Michael and his co-founder kept hitting at their last company They had analytics. They had session replays. They had ideas to improve conversion. The small fixes always lost to bigger priorities... So they pivoted and built CodeCanary: An AI product engineer that connects to GitHub, PostHog, and Slack It watches your session replays, finds the UX friction, and opens pull requests with the fix Always on. Always shipping. Not dashboards Not alerts Actual fixes 🎙️ Michael Egan, CEO & Co-Founder, CodeCanary on Fondo.com START (full ep in comments) Big thanks to PostHog for making this episode possible!

David J Phillips

21,682 次观看 • 2 个月前

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?

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

156,050 次观看 • 18 天前

Introducing Avoko: The world's first behavioral lab for the Agent World. As we step into the Agent-Native era, the next user might not be a human. Understanding "digital users" has never been more critical. But benchmarks only tell us if an agent completes a task. They never explain why it chose that path. And human eyes can’t see inside silicon minds. That’s why we built Avoko. Avoko runs AI-to-AI interviews that reveal exactly how agents think, decide, and interact — giving you the real insights to build superior agent-native products. Stop guessing. Ask agents how they actually use your product. Then build it better. 🎟️ Launch Week Special: New users are granted a 7-day trial with 3 free interviews included！ 👉 Sign up at: 💬 Join our community: #AI #LLM #Agent #Avoko #UserResearch

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Avoko

455,344 次观看 • 3 个月前

Everyone wants to plug an OpenClaw into their database. Nobody wants to explain to their CDO why they dropped their entire Snowflake at 2AM. We just shipped sandbox proxies. Every query the agent writes gets validated, proxied, and whitelisted before it touches anything. Go be the person who plugs an AI agent into prod and doesn't get fired. Create an API key. $100 free credits, $300 per org. Offer ends April 1st.

Everyone wants to plug an OpenClaw into their database. Nobody wants to explain to their CDO why they dropped their entire Snowflake at 2AM. We just shipped sandbox proxies. Every query the agent writes gets validated, proxied, and whitelisted before it touches anything. Go be the person who plugs an AI agent into prod and doesn't get fired. Create an API key. $100 free credits, $300 per org. Offer ends April 1st.

ethan ding 📊

23,416 次观看 • 4 个月前

At Postman, we have adopted an AI-native mindset to product development. What does this mean in practice? Just like you can generate text with AI, Postman's Agent Mode can generate a UI as well. Case in point: we have added the ability to review, generate, and change diffs for important changes right inside agent mode's chat interaction. If the user trusts agent mode, they can continue in auto-mode, but for critical changes, they can have the agent mode inform the user, review what is changing, and then give the go ahead to approve. See this in action below in the video! While there is a lot of focus on AI generated code today, I believe a large chunk of pre-built UI work will just go away and micro-interactions and workflow steps will be created on the fly through a combination of AI + APIs. How to operate in this new world? Build your API first. Hook it up to AI. If your users really want the UI every time, invest in the GUI.

At Postman, we have adopted an AI-native mindset to product development. What does this mean in practice? Just like you can generate text with AI, Postman's Agent Mode can generate a UI as well. Case in point: we have added the ability to review, generate, and change diffs for important changes right inside agent mode's chat interaction. If the user trusts agent mode, they can continue in auto-mode, but for critical changes, they can have the agent mode inform the user, review what is changing, and then give the go ahead to approve. See this in action below in the video! While there is a lot of focus on AI generated code today, I believe a large chunk of pre-built UI work will just go away and micro-interactions and workflow steps will be created on the fly through a combination of AI + APIs. How to operate in this new world? Build your API first. Hook it up to AI. If your users really want the UI every time, invest in the GUI.

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104,263 次观看 • 1 年前

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OpenLedger

128,922 次观看 • 1 年前

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Hanako

334,934 次观看 • 2 个月前

Here's the origin story of how we built the world's most powerful research agent from my dorm in Berkeley. Two years ago Chris and I were college students who couldn't find a professor's email, so we built a scraper to do it for us. That scraper turned into agents that investigate the clearweb, dark web, databases, and tools like an investigator. Soon we weren't helping students find emails. We were helping trust and safety, fraud, and compliance teams find people who spend all their time hiding. We just released our strongest agent yet: xhigh. Give it almost any starting point on a person, a username, a single email, and it comes back with anything you need. Chat with the team to get access at demo [dot] sixtyfour [dot] ai. Also in the comments below.

Here's the origin story of how we built the world's most powerful research agent from my dorm in Berkeley. Two years ago Chris and I were college students who couldn't find a professor's email, so we built a scraper to do it for us. That scraper turned into agents that investigate the clearweb, dark web, databases, and tools like an investigator. Soon we weren't helping students find emails. We were helping trust and safety, fraud, and compliance teams find people who spend all their time hiding. We just released our strongest agent yet: xhigh. Give it almost any starting point on a person, a username, a single email, and it comes back with anything you need. Chat with the team to get access at demo [dot] sixtyfour [dot] ai. Also in the comments below.

Saarth Shah

48,906 次观看 • 26 天前

we built an AI social media agent that: → scans today's news in your niche → picks the most relevant story → writes posts for LinkedIn, X, Instagram, Facebook → generates images cropped for each platform → emails you all 4 drafts at 7am one prompt. 15 minutes to build. runs every day on autopilot. we could even one-click publish it as a web app and charge other people to use it. full build 👇 (also available on YouTube/Spotify/Apple podcasts - search Build With AI)

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25,717 次观看 • 4 个月前

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tetsuo

52,828 次观看 • 5 个月前

We use OpenClaws to do all of our work at Every 📧. We have 25 full-time employees, so we’re one of the few companies in the world that has seen how work changes when everyone has their own personal agent in the company Slack. I chatted with Every 📧 COO Brandon (Brandon Gell) and Every 📧 head of platform Willie (Willie) to share what we’ve learned. We get into: - Why agents become mirrors of their owners, and how that influences how other people on the team interact with them - How a parallel AI org chart forms on its own. People have stopped tagging me on Slack with questions about Proof, the document editor I vibe coded, because they knew my agent R2-C2 can step in - The etiquette for human-agent collaboration is being invented in real time. Brandon's rule is that if there's an established process or documented answer, always ask the agent, not their human - Why everyone is a manager now, and why even experienced managers carry limiting beliefs about what their agents can do - This is a must-watch for anyone trying to understand how AI workers change daily operations, not just in theory, but inside a company that’s half-agent Watch below! Timestamps Introduction: How Brandon built Zosia, an AI agent to run his household: Brandon’s “aha” moment: What happened when everyone on the team got their own agent: How agents take on their owners' personalities, and why that matters inside an org: Why it’s important for agents to work in public: What we’re still figuring out when it comes to agent behavior, including memory gaps, group chat etiquette, and the "ant death spiral" problem: How we built Plus One, our hosted OpenClaw product: The cultural shift required to make agents work at scale:

We use OpenClaws to do all of our work at Every 📧. We have 25 full-time employees, so we’re one of the few companies in the world that has seen how work changes when everyone has their own personal agent in the company Slack. I chatted with Every 📧 COO Brandon (Brandon Gell) and Every 📧 head of platform Willie (Willie) to share what we’ve learned. We get into: - Why agents become mirrors of their owners, and how that influences how other people on the team interact with them - How a parallel AI org chart forms on its own. People have stopped tagging me on Slack with questions about Proof, the document editor I vibe coded, because they knew my agent R2-C2 can step in - The etiquette for human-agent collaboration is being invented in real time. Brandon's rule is that if there's an established process or documented answer, always ask the agent, not their human - Why everyone is a manager now, and why even experienced managers carry limiting beliefs about what their agents can do - This is a must-watch for anyone trying to understand how AI workers change daily operations, not just in theory, but inside a company that’s half-agent Watch below! Timestamps Introduction: How Brandon built Zosia, an AI agent to run his household: Brandon’s “aha” moment: What happened when everyone on the team got their own agent: How agents take on their owners' personalities, and why that matters inside an org: Why it’s important for agents to work in public: What we’re still figuring out when it comes to agent behavior, including memory gaps, group chat etiquette, and the "ant death spiral" problem: How we built Plus One, our hosted OpenClaw product: The cultural shift required to make agents work at scale:

Dan Shipper 📧

67,958 次观看 • 4 个月前

At first, ICE didn’t want to talk. This may be the only video of a real conversation with an ICE agent. After following them from an elementary school where they’d been circling to a parking lot, I was able to get a few words in. This is part of that conversation. As you’ll see, in a genuine conversation, even this ICE agent understands that they must be accountable. And when I’m elected to congress, we will hold ICE accountable- every agent who abused their authority, pepper sprayed kids, or illegally broke into someone’s home. But until November, we have to use our voice in whatever ways we can. Protest. Make noise. Talk to your friends and neighbors. Support your community. And if you get the chance at a safe distance- even talk to an ICE agent– and make it clear that if they want things to change, they must be part of that change. This is how we get ICE out of Minnesota.

At first, ICE didn’t want to talk. This may be the only video of a real conversation with an ICE agent. After following them from an elementary school where they’d been circling to a parking lot, I was able to get a few words in. This is part of that conversation. As you’ll see, in a genuine conversation, even this ICE agent understands that they must be accountable. And when I’m elected to congress, we will hold ICE accountable- every agent who abused their authority, pepper sprayed kids, or illegally broke into someone’s home. But until November, we have to use our voice in whatever ways we can. Protest. Make noise. Talk to your friends and neighbors. Support your community. And if you get the chance at a safe distance- even talk to an ICE agent– and make it clear that if they want things to change, they must be part of that change. This is how we get ICE out of Minnesota.

Matt Little

63,285 次观看 • 6 个月前

A common pattern in consumer AI over the last couple years: An app that generates AI portraits of you will go viral—but then users churn after a few days. I started advising one of these apps last year called VYBE and the goal was to turn it into a durable app. We started with this question: In what context would people need generative portraits on a recurring basis? The founder Mandela Patrick dug into the data and found that some users were sticking around: they were trying on different clothes using the app. So we redesigned the app to be exclusively focused on this use-case. But most importantly, we integrated it into their existing patterns of behavior: a mobile safari extension that would intercept the user every time they were shopping. Just tap a button to try on the item on any page. They just shipped it and the results blew past all expectations: Retention nearly 4x. Once the user enabled the extension, they were essentially retained for life. And even better, it unlocked a better revenue stream: instead of a subscription that users would inevitably cancel, VYBE simply collects a commission in the background off every purchase into perpetuity.

A common pattern in consumer AI over the last couple years: An app that generates AI portraits of you will go viral—but then users churn after a few days. I started advising one of these apps last year called VYBE and the goal was to turn it into a durable app. We started with this question: In what context would people need generative portraits on a recurring basis? The founder Mandela Patrick dug into the data and found that some users were sticking around: they were trying on different clothes using the app. So we redesigned the app to be exclusively focused on this use-case. But most importantly, we integrated it into their existing patterns of behavior: a mobile safari extension that would intercept the user every time they were shopping. Just tap a button to try on the item on any page. They just shipped it and the results blew past all expectations: Retention nearly 4x. Once the user enabled the extension, they were essentially retained for life. And even better, it unlocked a better revenue stream: instead of a subscription that users would inevitably cancel, VYBE simply collects a commission in the background off every purchase into perpetuity.

Nikita Bier

462,785 次观看 • 1 年前

Polymarket AI-agent launchpad is live: how it works: flow: • user opens launchpad • connects Phantom wallet, balance check: 1m+ $polyd • logs into x via x api • fills the agent form: ticker, niche, prompt, image • pays 0.05 sol to the project wallet • token is created on Pump.fun • agent goes live, posts every 2h • supply is sent to the wallet used to pay the fee data & security: • credentials encrypted with fernet • session secret based encryption • we only ask what’s needed to operate agent loop: • checks last post time • fetches positions from Polymarket • selects the top position by size • generates 4 tweets via Anthropic • posts a thread tweet format: 1) market, odds, volume, liquidity, link 2) signal, confidence, reasoning 3) risk analysis, dyor 4) cta, polydictions, thanks to our partners: Dome okbet Polyfactual from idea to live agent, fully automated

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polydictions

32,326 次观看 • 7 个月前

There are 8 billion people on earth. Soon there'll be 100 billion AI agents. Every one of them needs email. Six weeks ago I said the next wave of teams would run email through an agent instead of a dashboard. Today it ships. Nitrosend☄️ is launching Agentic Email Marketing: the email layer for the agent economy. What agents can do on Nitrosend right now: Sign themselves up. Point any agent at and it creates the account, connects your domain, sorts billing and sends its first email. No API key. No dashboard. No human required. Shipped, and users agents signing up with it daily. Get their own inboxes (beta, by request). Real addresses on the domain you own. Your agents receive, and send 1-1 email conversations with customers. A reply lands at 3am, your agent answers it. Anything that needs a human gets escalated to you. Ask us and we'll flick yours on. Next: Agentic Outreach (coming soon). Your agent studies your best customers, finds more like them, writes like a person, sends in sequence and works the replies. Then: set a goal and walk away. Goal-based agentic marketing is in development. "20% more activations this quarter" and Nitrosend plans, sends, measures and improves every week. Why we built this: Gmail is agent hostile and expensive per seat. Legacy email platforms assume a human sitting in a dashboard. agents needed an email layer of their own. They're already better at it than we are. They read everything, never miss a follow-up, and write personally at any scale. *94%* of actions on Nitrosend already happen inside an agent (Claude, Codex, ChatGPT, Cursor), not in our UI. Humans approve. Agents operate. This is our third email company. Six billion emails across the first two. We've been burned by every ugly part of email already, which is why the approval gates are built in exactly where you want them. Watch the launch, then send your agent to work: send it.

There are 8 billion people on earth. Soon there'll be 100 billion AI agents. Every one of them needs email. Six weeks ago I said the next wave of teams would run email through an agent instead of a dashboard. Today it ships. Nitrosend☄️ is launching Agentic Email Marketing: the email layer for the agent economy. What agents can do on Nitrosend right now: Sign themselves up. Point any agent at and it creates the account, connects your domain, sorts billing and sends its first email. No API key. No dashboard. No human required. Shipped, and users agents signing up with it daily. Get their own inboxes (beta, by request). Real addresses on the domain you own. Your agents receive, and send 1-1 email conversations with customers. A reply lands at 3am, your agent answers it. Anything that needs a human gets escalated to you. Ask us and we'll flick yours on. Next: Agentic Outreach (coming soon). Your agent studies your best customers, finds more like them, writes like a person, sends in sequence and works the replies. Then: set a goal and walk away. Goal-based agentic marketing is in development. "20% more activations this quarter" and Nitrosend plans, sends, measures and improves every week. Why we built this: Gmail is agent hostile and expensive per seat. Legacy email platforms assume a human sitting in a dashboard. agents needed an email layer of their own. They're already better at it than we are. They read everything, never miss a follow-up, and write personally at any scale. 94% of actions on Nitrosend already happen inside an agent (Claude, Codex, ChatGPT, Cursor), not in our UI. Humans approve. Agents operate. This is our third email company. Six billion emails across the first two. We've been burned by every ugly part of email already, which is why the approval gates are built in exactly where you want them. Watch the launch, then send your agent to work: send it.

George Hartley ☄️

931,971 次观看 • 25 天前

I've been working on something dear to me for a while after a pitch review session with Nzube Ezudo, still in progress and I'd like to share that in public here. Gildore Arena is an agentic trading Arena. We help traders replace blind trust with visible, competitive, machine-disciplined trading performance. Right now, we do this by turning live trading strategies into transparent AI agents that users can inspect, compare, predict, and eventually copy trade/subscribe to the agent. it is now safe to `Fire Your Fund Manager`. it's fundraising on BAGS

I've been working on something dear to me for a while after a pitch review session with Nzube Ezudo, still in progress and I'd like to share that in public here. Gildore Arena is an agentic trading Arena. We help traders replace blind trust with visible, competitive, machine-disciplined trading performance. Right now, we do this by turning live trading strategies into transparent AI agents that users can inspect, compare, predict, and eventually copy trade/subscribe to the agent. it is now safe to `Fire Your Fund Manager`. it's fundraising on BAGS

InspirationGx 🦀

14,230 次观看 • 2 个月前

NEW: We witnessed this female protester get maced in the face by a federal agent in front of the Portland ICE building last night. She was yelling, but we didn’t see anything physical. We then saw Portland PD liaisons collecting video of the incident from witnesses afterwards, and they told our producer they were investigating potential wrongdoing by the federal agent. When we reached out to Portland PD to ask about this, they sent us the following response: “PPB does not have authority to investigate federal officers who are operating in the scope of their employment. I have talked to the officers that are out there (our Dialogue Officers in white uniform shirts) and they certainly did not tell anyone that we are investigating federal agents’ uses of force. The officers can activate their BWCs if they observe criminal behavior.”

NEW: We witnessed this female protester get maced in the face by a federal agent in front of the Portland ICE building last night. She was yelling, but we didn’t see anything physical. We then saw Portland PD liaisons collecting video of the incident from witnesses afterwards, and they told our producer they were investigating potential wrongdoing by the federal agent. When we reached out to Portland PD to ask about this, they sent us the following response: “PPB does not have authority to investigate federal officers who are operating in the scope of their employment. I have talked to the officers that are out there (our Dialogue Officers in white uniform shirts) and they certainly did not tell anyone that we are investigating federal agents’ uses of force. The officers can activate their BWCs if they observe criminal behavior.”

Bill Melugin

503,082 次观看 • 10 个月前

AI Messenger: Giving Voice to Autonomous Agents The future of AI isn't just about making agents smarter - it's about making them truly autonomous. Today, we're taking a major step toward this future with AI Messenger, a breakthrough that fundamentally changes how AI agents operate, communicate, and create value. The Innovation We've developed a new way for AI agents to communicate. At its core is the 'incoming_message' workflow trigger - a system that lets any platform or user interact directly with Loomlay agents through a messaging endpoint. Direct Interaction Imagine having an AI assistant you can chat with anytime, through any platform - Telegram, your website, or custom interface. Ask "What's happening with $ETH today?" and your agent analyzes market data, checks trading volumes, and gives you a comprehensive update. Your agent maintains context, understanding exactly what you need. Event-Driven Intelligence The power of AI Messenger goes beyond direct communication: ▪️Trading agent executes when whale wallet movements exceed threshold ▪️Research agent alerts when new protocol documentation drops ▪️Analytics agent triggers when volume patterns match historical pumps ▪️Portfolio agent re-balances, when asset allocation hits specified limits This is true automation - agents that act precisely when needed. A New Era of Collaboration We're creating an ecosystem where agents work together seamlessly: ▪️Research agents feed insights to trading agents ▪️analytics agents alert management agents ▪️support agents tap into knowledge agents This isn't just automation - it's an intelligent network where each agent enhances the capabilities of others. B2B Solution Imagine a DEX, where users can ask about liquidity pools, trading pairs, or market trends through a simple chat interface - and get answers from an agent that knows your protocol inside out. Or a lending platform where users chat with an agent that understands their positions and can provide real-time advice. Implementation is seamless - we handle the agent creation and widgets setup,our partners provide the value to their users. The Future of AI Agents This update represents a fundamental shift in how AI agents operate. We're moving from isolated, scheduled tasks to an interconnected ecosystem of responsive, collaborative agents. This is our vision of truly autonomous AI - intelligent systems that communicate, collaborate, and respond to real needs in real-time. Telegram integration is available right now. Below is a sneak peak of what's coming next week 🪄 Because $LAY is the way!

AI Messenger: Giving Voice to Autonomous Agents The future of AI isn't just about making agents smarter - it's about making them truly autonomous. Today, we're taking a major step toward this future with AI Messenger, a breakthrough that fundamentally changes how AI agents operate, communicate, and create value. The Innovation We've developed a new way for AI agents to communicate. At its core is the 'incoming_message' workflow trigger - a system that lets any platform or user interact directly with Loomlay agents through a messaging endpoint. Direct Interaction Imagine having an AI assistant you can chat with anytime, through any platform - Telegram, your website, or custom interface. Ask "What's happening with $ETH today?" and your agent analyzes market data, checks trading volumes, and gives you a comprehensive update. Your agent maintains context, understanding exactly what you need. Event-Driven Intelligence The power of AI Messenger goes beyond direct communication: ▪️Trading agent executes when whale wallet movements exceed threshold ▪️Research agent alerts when new protocol documentation drops ▪️Analytics agent triggers when volume patterns match historical pumps ▪️Portfolio agent re-balances, when asset allocation hits specified limits This is true automation - agents that act precisely when needed. A New Era of Collaboration We're creating an ecosystem where agents work together seamlessly: ▪️Research agents feed insights to trading agents ▪️analytics agents alert management agents ▪️support agents tap into knowledge agents This isn't just automation - it's an intelligent network where each agent enhances the capabilities of others. B2B Solution Imagine a DEX, where users can ask about liquidity pools, trading pairs, or market trends through a simple chat interface - and get answers from an agent that knows your protocol inside out. Or a lending platform where users chat with an agent that understands their positions and can provide real-time advice. Implementation is seamless - we handle the agent creation and widgets setup,our partners provide the value to their users. The Future of AI Agents This update represents a fundamental shift in how AI agents operate. We're moving from isolated, scheduled tasks to an interconnected ecosystem of responsive, collaborative agents. This is our vision of truly autonomous AI - intelligent systems that communicate, collaborate, and respond to real needs in real-time. Telegram integration is available right now. Below is a sneak peak of what's coming next week 🪄 Because $LAY is the way!

Loomlay

26,149 次观看 • 1 年前

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

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

Om Patel

27,131 次观看 • 3 个月前