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Just built an end-to-end AI agent workflow stack in 3 days that automates everything from recruiting to reminders to reporting for electrician franchises. What used to take 6+ SaaS tools and a full ops team? Now handled by 12 specialized agents: •Hiring •Screening •Follow-ups •Reminders •AI call reps •Reviews...

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Bennett Spooner

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10,319 görüntüleme • 1 yıl önce •via X (Twitter)

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assisterr

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

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12 days, countless ideas and one clear message : Agent Two is built to turn creative vision into reality. From multiple specialized Agents to the Slate editor, the workflow feels less like “AI doing everything” and more like having a smarter creative production system in your hands. Now it’s our turn to create 🔥 | Invideo

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Wade Foster

37,749 görüntüleme • 1 yıl önce

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

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EVERYTHING you NEED to know about Jack Dorsey's AI agent "Slack killer" Buzz (set up, use-cases etc in 38 mins) What we get into: 1. What Buzz actually is and should founders switch from Slack? 2. How to swap the model under any agent and keep all your context? 3. How to talk to your agents live with audio huddles? 4. How to get agents to build and deploy real apps for you, like a full CRM from one ask? 5. How to set up the context loop that feeds your live app data back to your agents? 6. How to share compute so a few people split one machine running a local model? 7. Who it's actually for right now, and what's still rough? Full breakdown on the pod The Startup Ideas Podcast (SIP) 🧃. Thanks to Vinny for jumping on and clearly explaining jack and team's latest product. My TLDR take is Buzz is a glimpse into the future of work. Some of you will roll your eyes at that, and I get it, it's alpha software and it's slow in places. But the core idea, that your context is the foundation and agents build out from there, is right, and that's worth seeing early. Watch Curious what you think
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EVERYTHING you NEED to know about Jack Dorsey's AI agent "Slack killer" Buzz (set up, use-cases etc in 38 mins) What we get into: 1. What Buzz actually is and should founders switch from Slack? 2. How to swap the model under any agent and keep all your context? 3. How to talk to your agents live with audio huddles? 4. How to get agents to build and deploy real apps for you, like a full CRM from one ask? 5. How to set up the context loop that feeds your live app data back to your agents? 6. How to share compute so a few people split one machine running a local model? 7. Who it's actually for right now, and what's still rough? Full breakdown on the pod The Startup Ideas Podcast (SIP) 🧃. Thanks to Vinny for jumping on and clearly explaining jack and team's latest product. My TLDR take is Buzz is a glimpse into the future of work. Some of you will roll your eyes at that, and I get it, it's alpha software and it's slow in places. But the core idea, that your context is the foundation and agents build out from there, is right, and that's worth seeing early. Watch Curious what you think

GREG ISENBERG

554,339 görüntüleme • 23 gün önce

MOST AI AGENTS RESET TO ZERO EVERY TIME YOU OPEN A NEW SESSION. Hermes Agent was built to do the opposite. Every task compounds. Every workflow becomes reusable. Every session teaches the next one. That is the core thesis behind Hermes, and it completely changes how AI agents work. Unlike most AI agents built by software tool companies, Hermes was created by the researchers training the Hermes model family itself. Meaning: The same system used internally to generate training data is now open source and available to everyone. One install gives you access to: Claude. GPT. Grok. Local models via Ollama. Telegram, Discord, Slack, iMessage integrations. Custom skills. Persistent memory. CLI control. But the real unlock is the compounding loop: You give Hermes a task. It records every tool call, decision, and result. Then it converts successful workflows into reusable skills automatically. A Hermes setup running for 3 months becomes fundamentally smarter than a fresh install. That’s the big idea. One of the coolest parts: You literally watch the agent evolve in real time from a blank install into a personalized AI operator. Instead of watching Netflix today, spend 28 mins with this. Follow Dami-Defi for more AI systems, agent workflows, and infrastructure alpha.
0:48

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

Dami-Defi

11,668 görüntüleme • 2 ay önce

how to build an AI-first SaaS in 2026 1. start with a big market. finance, healthcare, real estate. then zoom into a sub-niche. 2. map the niche’s workflow end-to-end. literally write every step they do daily. ex: leads → scheduling → quoting → follow-ups → payments. 3. highlight where money changes hands. deposits, invoices, negotiations. those moments are where software captures value. 4. identify the repetitive mechanical tasks. anything someone does the same way every day is an automation opportunity. 5. quantify the pain. if a business owner spends 100 hours a year on something and their time is worth $300/hour, that’s a $30k problem. 6. manually perform the workflow yourself. most AI SaaS actually starts as a service. that’s why so many new YC companies begin with humans in the loop. 7. document every step. separate judgment tasks from mechanical tasks. agents handle the mechanical work. 8. turn those steps into agent workflows and connect them to real tools (email, slack, stripe, crm, APIs). 9. build media while you build the product. post daily about the workflow. use AI to research content ideas and scripts. the audience becomes your distribution. 10. launch narrow, show proof (hours saved, revenue generated), then expand into adjacent workflows until you become the default execution layer for that niche. people saying everyday that saas is dying it’s evolving into agents + software + media. full breakdown in the latest episode of The Startup Ideas Podcast (SIP) 🧃 lots of sauce in this one all for free because i can't wait to see what you build watch
25:35

how to build an AI-first SaaS in 2026 1. start with a big market. finance, healthcare, real estate. then zoom into a sub-niche. 2. map the niche’s workflow end-to-end. literally write every step they do daily. ex: leads → scheduling → quoting → follow-ups → payments. 3. highlight where money changes hands. deposits, invoices, negotiations. those moments are where software captures value. 4. identify the repetitive mechanical tasks. anything someone does the same way every day is an automation opportunity. 5. quantify the pain. if a business owner spends 100 hours a year on something and their time is worth $300/hour, that’s a $30k problem. 6. manually perform the workflow yourself. most AI SaaS actually starts as a service. that’s why so many new YC companies begin with humans in the loop. 7. document every step. separate judgment tasks from mechanical tasks. agents handle the mechanical work. 8. turn those steps into agent workflows and connect them to real tools (email, slack, stripe, crm, APIs). 9. build media while you build the product. post daily about the workflow. use AI to research content ideas and scripts. the audience becomes your distribution. 10. launch narrow, show proof (hours saved, revenue generated), then expand into adjacent workflows until you become the default execution layer for that niche. people saying everyday that saas is dying it’s evolving into agents + software + media. full breakdown in the latest episode of The Startup Ideas Podcast (SIP) 🧃 lots of sauce in this one all for free because i can't wait to see what you build watch

GREG ISENBERG

189,220 görüntüleme • 5 ay önce

Agents changed software forever. For everyone. You won't need to "learn a tool" anymore. Instead, you'll tell tools what you want, and they will figure out how to do it. This is a huge shift. I'm currently working with Spoki, an AI agentic conversational platform. After looking at this, you'll never think of a CRM the same way. A traditional CRM manages contact data. Spoki manages the entire customer journey (marketing, sales, and customer care) in a single continuous flow across WhatsApp, SMS, and Voice AI. AI will dismantle the old traditional tools one by one. Think of it this way: Instead of stitching together a bunch of tools to talk to your customers, you have a single conversation that runs the entire relationship.
5:13

Agents changed software forever. For everyone. You won't need to "learn a tool" anymore. Instead, you'll tell tools what you want, and they will figure out how to do it. This is a huge shift. I'm currently working with Spoki, an AI agentic conversational platform. After looking at this, you'll never think of a CRM the same way. A traditional CRM manages contact data. Spoki manages the entire customer journey (marketing, sales, and customer care) in a single continuous flow across WhatsApp, SMS, and Voice AI. AI will dismantle the old traditional tools one by one. Think of it this way: Instead of stitching together a bunch of tools to talk to your customers, you have a single conversation that runs the entire relationship.

Santiago

12,095 görüntüleme • 2 ay önce

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.
3:38

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

230,594 görüntüleme • 1 yıl önce

$FET just quietly built the internet for AI agents. 3,000,000 agents. One network. One token. Here's what nobody is explaining: Every AI agent needs 3 things to be useful: An address. A way to be found. A way to get paid. Agentverse gives agents all three. Your agent becomes discoverable on ASI: One. Other agents can find it, call it, or hire it. Automatically. No human in the loop. This is agent-to-agent commerce. And every transaction settles in $FET. More agents = more activity = more demand. The infrastructure is already live. The economy is just getting started.
1:00

$FET just quietly built the internet for AI agents. 3,000,000 agents. One network. One token. Here's what nobody is explaining: Every AI agent needs 3 things to be useful: An address. A way to be found. A way to get paid. Agentverse gives agents all three. Your agent becomes discoverable on ASI: One. Other agents can find it, call it, or hire it. Automatically. No human in the loop. This is agent-to-agent commerce. And every transaction settles in $FET. More agents = more activity = more demand. The infrastructure is already live. The economy is just getting started.

2xnmore

12,894 görüntüleme • 4 ay önce

We cancelled our entire SaaS stack and started running our business with AI agents. Now, we’re building Toyo to help other founders do the same. We're pleased to announce $4.3M in funding from Frontline Ventures, Inovia Capital, Philipp Moehring - tiny.vc, and angels from Amazon, Microsoft, and Cloudflare. For decades software was built for humans to operate. That world is over. We're building for one where agents do the work, while humans direct.
0:33

We cancelled our entire SaaS stack and started running our business with AI agents. Now, we’re building Toyo to help other founders do the same. We're pleased to announce $4.3M in funding from Frontline Ventures, Inovia Capital, Philipp Moehring - tiny.vc, and angels from Amazon, Microsoft, and Cloudflare. For decades software was built for humans to operate. That world is over. We're building for one where agents do the work, while humans direct.

Damien C. Tanner

426,168 görüntüleme • 6 ay önce

Anthropic's Claude team just showed how to give your AI agents real memory in under 18 minutes. Free. From the people who built it. You've been building agents that forget everything between sessions. This fixes that tonight. One person + 10 agents with memory + dreaming = a team that runs 24/7, learns from every task, and improves itself overnight. Worth more than any $500 AI agent course. Bookmark it. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward.
24:22

Anthropic's Claude team just showed how to give your AI agents real memory in under 18 minutes. Free. From the people who built it. You've been building agents that forget everything between sessions. This fixes that tonight. One person + 10 agents with memory + dreaming = a team that runs 24/7, learns from every task, and improves itself overnight. Worth more than any $500 AI agent course. Bookmark it. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward.

Himanshu Kumar

11,191 görüntüleme • 3 ay önce

AGI won’t be one giant model. It will be many specialized intelligences working together through a reasoning-capable AI that coordinates the layer that routes each query to the right models, tools, and agents. PS: Good reasoning is how you avoid getting your agent deleting your entire email inbox btw.
1:00

AGI won’t be one giant model. It will be many specialized intelligences working together through a reasoning-capable AI that coordinates the layer that routes each query to the right models, tools, and agents. PS: Good reasoning is how you avoid getting your agent deleting your entire email inbox btw.

Sentient

19,245 görüntüleme • 5 ay önce

Google’s new Agent2Agent protocol is a key step toward a future of AI Agent interoperability. No single tool has all the data a user or business needs for most workflows, so we need Agents to be able to talk to each other. Salesforce will have AI Agents that understand the inner workings of CRM, Workday will have AI Agents that understand HR workflows, Box has AI Agents that understand content and documents, and so on. It’s easy to conceive of a world where we have tens of thousands of these tool Agents and then billions or trillions of customized Agents that are extensions of those. So openness becomes key. Workflows need data from multiple systems to complete the task — like a sales report that needs documents and CRM data or an HR task that needs HR policies and employee details — and that’s where A2A comes in. This protocol gives AI Agent providers a way of talking to each other and simplifying the way that Agents communicate, understand each other’s capabilities, and so on. It’s great to see more interoperability, along with MCP, emerging in the AI space right now, as this will define the future of most IT stacks.
1:47

Google’s new Agent2Agent protocol is a key step toward a future of AI Agent interoperability. No single tool has all the data a user or business needs for most workflows, so we need Agents to be able to talk to each other. Salesforce will have AI Agents that understand the inner workings of CRM, Workday will have AI Agents that understand HR workflows, Box has AI Agents that understand content and documents, and so on. It’s easy to conceive of a world where we have tens of thousands of these tool Agents and then billions or trillions of customized Agents that are extensions of those. So openness becomes key. Workflows need data from multiple systems to complete the task — like a sales report that needs documents and CRM data or an HR task that needs HR policies and employee details — and that’s where A2A comes in. This protocol gives AI Agent providers a way of talking to each other and simplifying the way that Agents communicate, understand each other’s capabilities, and so on. It’s great to see more interoperability, along with MCP, emerging in the AI space right now, as this will define the future of most IT stacks.

Aaron Levie

139,591 görüntüleme • 1 yıl önce

Episode 7 of How I AI is going to inspire the marketers and scare all of SaaS. is head of growth at and ambitiously embraces AI for marketing, to build internal tools, and to hack on his personal data. You’ll learn how to: - take Granola transcripts and turn them into multiple marketing assets - replace expensive saas tools by building a custom solution in Cursor - use Luke’s WhatsApp MCP to query your group chat Luke gives one of the most fun and broad tours of using AI as someone who is technically not in a technical role. Plus, he teaches me “everything is a launch.” Check it out in the links below 👇🔗 As always, a big thanks to our sponsors: 🔀 Orkes enterprise platform for agentic workflows 🧰 Retool AI for developers, built for the enterprise
0:34

Episode 7 of How I AI is going to inspire the marketers and scare all of SaaS. is head of growth at and ambitiously embraces AI for marketing, to build internal tools, and to hack on his personal data. You’ll learn how to: - take Granola transcripts and turn them into multiple marketing assets - replace expensive saas tools by building a custom solution in Cursor - use Luke’s WhatsApp MCP to query your group chat Luke gives one of the most fun and broad tours of using AI as someone who is technically not in a technical role. Plus, he teaches me “everything is a launch.” Check it out in the links below 👇🔗 As always, a big thanks to our sponsors: 🔀 Orkes enterprise platform for agentic workflows 🧰 Retool AI for developers, built for the enterprise

claire vo 🖤

24,914 görüntüleme • 1 yıl önce

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

53,950 görüntüleme • 1 yıl önce

We just raised a $75M Series B to *finally* automate AML/KYC with AI agents. KYC/AML software has been around for a long time. Bretton AI is different: - Autonomous browsing: agents hop between multiple tools to complete reviews without the need for a massive engineering lift for the bank - Long Horizon Agents: our agents complete iterative, complex reviews that take humans hours to complete - Bank-grade model risk management: built for regulators, internal audit and third-party reviews It's why companies like Robinhood, Lead Bank and Gusto use us to scale efficiently and deliver great customer experiences. Our Series B is led by Rajeev Dham and Sapphire Ventures , with participation from Greylock, Y Combinator, Thomson Reuters Ventures, Canvas Ventures and TIAA Ventures. 3 years ago, this company was just a dream. Now I get to work with 40 of the smartest, hardest working poeple I’ve ever met to solve big problems at the heart of finance. I'm pumped for the future! Now back to building.
1:18

We just raised a $75M Series B to *finally* automate AML/KYC with AI agents. KYC/AML software has been around for a long time. Bretton AI is different: - Autonomous browsing: agents hop between multiple tools to complete reviews without the need for a massive engineering lift for the bank - Long Horizon Agents: our agents complete iterative, complex reviews that take humans hours to complete - Bank-grade model risk management: built for regulators, internal audit and third-party reviews It's why companies like Robinhood, Lead Bank and Gusto use us to scale efficiently and deliver great customer experiences. Our Series B is led by Rajeev Dham and Sapphire Ventures , with participation from Greylock, Y Combinator, Thomson Reuters Ventures, Canvas Ventures and TIAA Ventures. 3 years ago, this company was just a dream. Now I get to work with 40 of the smartest, hardest working poeple I’ve ever met to solve big problems at the heart of finance. I'm pumped for the future! Now back to building.

Will Lawrence

93,903 görüntüleme • 6 ay önce

I turned myself into a one-person company in 48 hours. No freelancers. No agencies. Just a team of AI Agents from MuleRun 2.0 that actually do the work, not chat about it. This is the closest thing to hiring an entire ops team for the price of coffee.
1:06

I turned myself into a one-person company in 48 hours. No freelancers. No agencies. Just a team of AI Agents from MuleRun 2.0 that actually do the work, not chat about it. This is the closest thing to hiring an entire ops team for the price of coffee.

MAYA

27,253 görüntüleme • 8 ay önce