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i watched a guy screenshare how he makes millions with 7 ai agent workflows, his name is rowan cheung from the rundown 1/ an avatar that records videos so he doesn’t have to and gets millions of views 2/ a voice-to-tweet system that turns walks into content. 3/ a...

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GREG ISENBERG

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228,496 görüntüleme • 10 ay önce •via X (Twitter)

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i just watched a guy scrape google maps with an ai agent and show EXACTLY which boring businesses can make you stupid money in your local area not HVAC or plumbing...the local startup ideas NOBODY talks about how it works (save this) 1/ a workflow that finds overlooked local niches like garage organizers and irrigation systems through google map's treasure chest of data 2/ an agent that measures demand by tracking review volume and velocity in google maps 3/ a system that turns customer complaints into newsletter content automatically 4/ a workflow hosted on n8n for $7/month that runs nonstop and gets you concurrent workflows so dont hit a ceiling on workflows 5/ a directory that sells leads back to service providers for $100–200 each 6/ a process that scales to $20–30k/month with minimal overhead The Boring Marketer shared every step on The Startup Ideas Podcast (SIP) 🧃 and i thank him for sharing that sauce FOR FREE (people charge $10k+ for this sorta stuff) cool thing is he started a mobile diesel company in north carolina using this exact process that's making $30k/month so he knows it works what hit me is how obvious it felt. of course google maps has the gold just need AI to shovel it out.
27:24

i just watched a guy scrape google maps with an ai agent and show EXACTLY which boring businesses can make you stupid money in your local area not HVAC or plumbing...the local startup ideas NOBODY talks about how it works (save this) 1/ a workflow that finds overlooked local niches like garage organizers and irrigation systems through google map's treasure chest of data 2/ an agent that measures demand by tracking review volume and velocity in google maps 3/ a system that turns customer complaints into newsletter content automatically 4/ a workflow hosted on n8n for $7/month that runs nonstop and gets you concurrent workflows so dont hit a ceiling on workflows 5/ a directory that sells leads back to service providers for $100–200 each 6/ a process that scales to $20–30k/month with minimal overhead The Boring Marketer shared every step on The Startup Ideas Podcast (SIP) 🧃 and i thank him for sharing that sauce FOR FREE (people charge $10k+ for this sorta stuff) cool thing is he started a mobile diesel company in north carolina using this exact process that's making $30k/month so he knows it works what hit me is how obvious it felt. of course google maps has the gold just need AI to shovel it out.

GREG ISENBERG

503,945 görüntüleme • 10 ay önce

Here is a step-by-step introduction to building a workflow with a custom AI agent that uses MCP. I explain every component in the video: 1. Building the MCP server 2. Building the agent and an MCP client 3. Building a workflow that uses the agent The goal is simple: Generate a dialogue between two people and make one yell and the other answer with sarcasm. Kestra is sponsoring this video. They are an open-source orchestration platform (repo link below), and I used them to build the workflow that connects every component.
23:07

Here is a step-by-step introduction to building a workflow with a custom AI agent that uses MCP. I explain every component in the video: 1. Building the MCP server 2. Building the agent and an MCP client 3. Building a workflow that uses the agent The goal is simple: Generate a dialogue between two people and make one yell and the other answer with sarcasm. Kestra is sponsoring this video. They are an open-source orchestration platform (repo link below), and I used them to build the workflow that connects every component.

Santiago

51,527 görüntüleme • 1 yıl önce

As an EM, running engineering standups where everyone's dead-eyed and reciting what they worked on is, in Ryan Nystrom words, a huge waste of time. So he built a Notion AI agent that preps his team's standup before the meeting starts, so he can code right up until it begins. In this ep he walks us through: - The "Hot Potato" 🥔 custom agent that scans Slack, GitHub, Honeycomb, and yesterday's meeting transcript every morning at 9am - How he @-mentions Codex from inside a Notion task and gets a full PR back in 10 minutes - Spec-driven development: talking into Whisper → spec → one-shotted implementation - Why CI speed is now your AI adoption ceiling Plus he shares why this is his favorite prompt: "I literally don't know what I'm doing. Explain it to me." ty to our sponsors! 💼 WorkOS - Make your app enterprise ready today 🔀 Orkes - The enterprise platform for reliable applications and agentic workflows Full episode:
1:09

As an EM, running engineering standups where everyone's dead-eyed and reciting what they worked on is, in Ryan Nystrom words, a huge waste of time. So he built a Notion AI agent that preps his team's standup before the meeting starts, so he can code right up until it begins. In this ep he walks us through: - The "Hot Potato" 🥔 custom agent that scans Slack, GitHub, Honeycomb, and yesterday's meeting transcript every morning at 9am - How he @-mentions Codex from inside a Notion task and gets a full PR back in 10 minutes - Spec-driven development: talking into Whisper → spec → one-shotted implementation - Why CI speed is now your AI adoption ceiling Plus he shares why this is his favorite prompt: "I literally don't know what I'm doing. Explain it to me." ty to our sponsors! 💼 WorkOS - Make your app enterprise ready today 🔀 Orkes - The enterprise platform for reliable applications and agentic workflows Full episode:

claire vo 🖤

49,705 görüntüleme • 2 ay önce

I built a Reddit marketing agent that gets your business mentioned by ChatGPT, Gemini and Claude. Not a spam bot. Not the kind that gets banned by mods. An agent that drafts genuinely valuable answers grounded in your company's actual content and slips in a brand mention only when it actually helps. Google is paying Reddit $60M a year just for their data!!! If your business isn't showing up in that data, your competitors are, and ChatGPT is recommending them instead of you. Here's how the system works: → A Claude routine pulls the target subreddit's JSON endpoint every hour for new posts → A Phase 1 checklist filters every post — is it answerable from our wiki, factual, on-brand, mod-safe? → The answer engine queries an LLM Wiki built from our blog, guides, and help center (Firecrawl ingested every page into a raw → wiki → index structure) → Claude drafts a casual, value-first answer that grounds every claim in our content → Every draft lands in Slack for human-in-the-loop review before it posts — no fire-and-forget, no bans I built this in a week for CoinLedger, the crypto tax software I've been running for 8 years. 10% of our new signups already say they found us through ChatGPT. This system is how we push that number a lot higher. If you want the exact Claude skill I built: Like & Comment "AGENT" (must be following so I can dm you) I'll send it over for free.
9:54

I built a Reddit marketing agent that gets your business mentioned by ChatGPT, Gemini and Claude. Not a spam bot. Not the kind that gets banned by mods. An agent that drafts genuinely valuable answers grounded in your company's actual content and slips in a brand mention only when it actually helps. Google is paying Reddit $60M a year just for their data!!! If your business isn't showing up in that data, your competitors are, and ChatGPT is recommending them instead of you. Here's how the system works: → A Claude routine pulls the target subreddit's JSON endpoint every hour for new posts → A Phase 1 checklist filters every post — is it answerable from our wiki, factual, on-brand, mod-safe? → The answer engine queries an LLM Wiki built from our blog, guides, and help center (Firecrawl ingested every page into a raw → wiki → index structure) → Claude drafts a casual, value-first answer that grounds every claim in our content → Every draft lands in Slack for human-in-the-loop review before it posts — no fire-and-forget, no bans I built this in a week for CoinLedger, the crypto tax software I've been running for 8 years. 10% of our new signups already say they found us through ChatGPT. This system is how we push that number a lot higher. If you want the exact Claude skill I built: Like & Comment "AGENT" (must be following so I can dm you) I'll send it over for free.

David Roberts

36,101 görüntüleme • 2 ay önce

This agent relies on a marketplace of 2.8M+ specialized agents to complete a task. This is how I imagine the future of personal agents. Here is how this works: 1. Agentverse is a marketplace of agents 2. Anyone can build and publish an agent there 3. ASI:One is a personal agent with access to the marketplace 4. To solve a task, ASI:One finds the best agent for the job In other words: You have an agent that can solve pretty much *anything* because it knows how to outsource the work to a network of specialized agents. And you don't need to do any setup to get this working. The way ranking agents in the marketplace works is pretty cool: Fetch.ai, the company behind it, created an AgentRank algorithm that works much like Google's PageRank. Every time an agent calls another, it forms a connection. Over time, these connections build into a graph of who relies on whom. An agent that is frequently called by other reputable agents scores higher and surfaces higher in results. The end result here is that your agent will consistently use the best agents in the marketplace to accomplish a goal. You should give this a try: You don't need to pay or even register to try these agents. Thanks to the team for partnering with me on this post.
4:16

This agent relies on a marketplace of 2.8M+ specialized agents to complete a task. This is how I imagine the future of personal agents. Here is how this works: 1. Agentverse is a marketplace of agents 2. Anyone can build and publish an agent there 3. ASI:One is a personal agent with access to the marketplace 4. To solve a task, ASI:One finds the best agent for the job In other words: You have an agent that can solve pretty much *anything* because it knows how to outsource the work to a network of specialized agents. And you don't need to do any setup to get this working. The way ranking agents in the marketplace works is pretty cool: Fetch.ai, the company behind it, created an AgentRank algorithm that works much like Google's PageRank. Every time an agent calls another, it forms a connection. Over time, these connections build into a graph of who relies on whom. An agent that is frequently called by other reputable agents scores higher and surfaces higher in results. The end result here is that your agent will consistently use the best agents in the marketplace to accomplish a goal. You should give this a try: You don't need to pay or even register to try these agents. Thanks to the team for partnering with me on this post.

Santiago

18,715 görüntüleme • 28 gün önce

If I am asked to name three skitmakers that should hold a masterclass in this country on how to build a content brand to a super influencial level, there is no gainsaying that Folagbade Banks, aka Mama Deola, will make top 3. Show me the content creator that has greater pull. He has hacked the industry, and he deserves his flowers. I hope he gets to read this. He is so respected, and that is probably because of the work he puts into his crafts and the positive brand he has built with the name because his collaboration game is heavy.
0:20

If I am asked to name three skitmakers that should hold a masterclass in this country on how to build a content brand to a super influencial level, there is no gainsaying that Folagbade Banks, aka Mama Deola, will make top 3. Show me the content creator that has greater pull. He has hacked the industry, and he deserves his flowers. I hope he gets to read this. He is so respected, and that is probably because of the work he puts into his crafts and the positive brand he has built with the name because his collaboration game is heavy.

Sir Dickson

402,376 görüntüleme • 1 yıl önce

i heard about a guy in a small town in england who turned his openclaw into a short form video marketing machine millions of views, steady app downloads, and revenue coming in every day i needed to find out how he was doing it 1. spin up an ai “employee” using openclaw 2. give it one job like grow your app with tiktokk 3. give it access to tiktokk analytics, a browser to research and image/video tools to create content 4. the openclaw studies your niche and starts generating slideshows and videos 5. every post feeds performance data back into the system views → hook quality downloads → CTA quality revenue → funnel quality the openclaw then iterates on - new hooks - new formats - new CTAs until it finds winners one of his posts hit 170k+ views and the system keeps improving because the analytics loop feeds back into the content generation so the agent slowly learns what works what i like about this is the framing most people think about ai tools this is different you spin up an ai employee you give it a job and let it run the loop thanks to Oliver Henry for coming on the The Startup Ideas Podcast (SIP) 🧃 today more like this soon, i will share the most interesting stories and gatekeep nothing this episode was dripping in sauce i gotta try this and see if it works kinda wild if it does watch
43:19

i heard about a guy in a small town in england who turned his openclaw into a short form video marketing machine millions of views, steady app downloads, and revenue coming in every day i needed to find out how he was doing it 1. spin up an ai “employee” using openclaw 2. give it one job like grow your app with tiktokk 3. give it access to tiktokk analytics, a browser to research and image/video tools to create content 4. the openclaw studies your niche and starts generating slideshows and videos 5. every post feeds performance data back into the system views → hook quality downloads → CTA quality revenue → funnel quality the openclaw then iterates on - new hooks - new formats - new CTAs until it finds winners one of his posts hit 170k+ views and the system keeps improving because the analytics loop feeds back into the content generation so the agent slowly learns what works what i like about this is the framing most people think about ai tools this is different you spin up an ai employee you give it a job and let it run the loop thanks to Oliver Henry for coming on the The Startup Ideas Podcast (SIP) 🧃 today more like this soon, i will share the most interesting stories and gatekeep nothing this episode was dripping in sauce i gotta try this and see if it works kinda wild if it does watch

GREG ISENBERG

1,327,456 görüntüleme • 4 ay önce

If I was starting a new company today, I'd start an agent business. SaaS was a multi-billion dollar market. Agents are a multi-trillion dollar one. How to build I'd build an agent business from 0: Spot the niche → find a workflow with a paycheck → shadow the human → spec the agent → run it manually first → build the smallest useful version → sell the pilot like labor → productize the repeatable parts. Entire episode is live on The Startup Ideas Podcast (SIP) 🧃 100% free like always. SaaS sold software and let your team use it to get the job done. An agent business sells the job already done. That shift matters because labor is a multi-trillion dollar market, far bigger than software ever was. Watch
26:03

If I was starting a new company today, I'd start an agent business. SaaS was a multi-billion dollar market. Agents are a multi-trillion dollar one. How to build I'd build an agent business from 0: Spot the niche → find a workflow with a paycheck → shadow the human → spec the agent → run it manually first → build the smallest useful version → sell the pilot like labor → productize the repeatable parts. Entire episode is live on The Startup Ideas Podcast (SIP) 🧃 100% free like always. SaaS sold software and let your team use it to get the job done. An agent business sells the job already done. That shift matters because labor is a multi-trillion dollar market, far bigger than software ever was. Watch

GREG ISENBERG

507,271 görüntüleme • 22 gün önce

karpathy just broke the internet with something called auto research it’s basically an ai research agent that runs experiments for you 24/7 you give it a goal like “make this model better” “find a higher converting landing page” “lower customer acquisition cost” then it runs a loop: 1) plan an experiment 2) edit the code or config 3) run a short test on a gpu 4) read the metrics 5) keep the winner 6) try again over and over while you sleep by the morning you wake up to the best version actual tested improvements think of it like a robot research intern that runs hundreds of experiments and only keeps the winners this is link to his repo for your to mess around with it in the latest episode of The Startup Ideas Podcast (SIP) 🧃 i break down: • what auto research actually is • how it works step by step • 10 business ideas you can build with it • how to install it and start using it this one is saucy because tools like this change how startups get built watch
24:21

karpathy just broke the internet with something called auto research it’s basically an ai research agent that runs experiments for you 24/7 you give it a goal like “make this model better” “find a higher converting landing page” “lower customer acquisition cost” then it runs a loop: 1) plan an experiment 2) edit the code or config 3) run a short test on a gpu 4) read the metrics 5) keep the winner 6) try again over and over while you sleep by the morning you wake up to the best version actual tested improvements think of it like a robot research intern that runs hundreds of experiments and only keeps the winners this is link to his repo for your to mess around with it in the latest episode of The Startup Ideas Podcast (SIP) 🧃 i break down: • what auto research actually is • how it works step by step • 10 business ideas you can build with it • how to install it and start using it this one is saucy because tools like this change how startups get built watch

GREG ISENBERG

435,845 görüntüleme • 4 ay önce

what if you could turn two hours of AI work into a week of viral content that gets 2M+ impressions/week? every morning, dan koe opens chatgpt/claude and uses them like an internal strategy team and it's paid off through millions of new followers and $$. he feeds them top-performing posts and asks for the hidden patterns like structure, rhythm, curiosity gaps, emotional payoff. from there, he builds a repeatable system that turns 2 hours of work into 7 days of content. his playbook looks like this: 1. validate fast start on twitter. write two or three high-density posts a day. when one hits, that’s your signal. expand it into a newsletter, then a youtube script, then repurpose across linkedin, instagram, threads, and shorts. 2. one source drives all one weekly newsletter becomes the foundation. one youtube video per week comes straight from that outline. the goal is not more ideas—it’s one good idea multiplied. 3. compress research with AI he drops long-form videos into claude or chatgpt and gets six hours of research condensed into a thousand words. he compares it with his own archives to find fresh angles. 4. the prompt stack after writing, he runs everything through a custom set of prompts: – a youtube title generator trained on his top 15 titles to create 30 new ones – a deep post generator that extracts paradoxes, transformation arcs, and action steps – a content idea generator that outputs 60 tweet ideas across proven formats 5. structure swapping he keeps a swipe file of viral posts and tests their structures on new ideas turning one seed into multiple posts. 6. growth loop when a post type drives followers, he doubles down for a few weeks, then moves to the next format. the algorithm shifts, but his system adapts. really cool tutorial. people charge crazy $$$ for this. i give it to you for free on The Startup Ideas Podcast (SIP) 🧃 (follow for more) thanks DAN KOE for being generous sharing your sauce. two hours a day. one system. millions of followers. really cool.
50:41

what if you could turn two hours of AI work into a week of viral content that gets 2M+ impressions/week? every morning, dan koe opens chatgpt/claude and uses them like an internal strategy team and it's paid off through millions of new followers and $$. he feeds them top-performing posts and asks for the hidden patterns like structure, rhythm, curiosity gaps, emotional payoff. from there, he builds a repeatable system that turns 2 hours of work into 7 days of content. his playbook looks like this: 1. validate fast start on twitter. write two or three high-density posts a day. when one hits, that’s your signal. expand it into a newsletter, then a youtube script, then repurpose across linkedin, instagram, threads, and shorts. 2. one source drives all one weekly newsletter becomes the foundation. one youtube video per week comes straight from that outline. the goal is not more ideas—it’s one good idea multiplied. 3. compress research with AI he drops long-form videos into claude or chatgpt and gets six hours of research condensed into a thousand words. he compares it with his own archives to find fresh angles. 4. the prompt stack after writing, he runs everything through a custom set of prompts: – a youtube title generator trained on his top 15 titles to create 30 new ones – a deep post generator that extracts paradoxes, transformation arcs, and action steps – a content idea generator that outputs 60 tweet ideas across proven formats 5. structure swapping he keeps a swipe file of viral posts and tests their structures on new ideas turning one seed into multiple posts. 6. growth loop when a post type drives followers, he doubles down for a few weeks, then moves to the next format. the algorithm shifts, but his system adapts. really cool tutorial. people charge crazy $$$ for this. i give it to you for free on The Startup Ideas Podcast (SIP) 🧃 (follow for more) thanks DAN KOE for being generous sharing your sauce. two hours a day. one system. millions of followers. really cool.

GREG ISENBERG

99,249 görüntüleme • 9 ay önce

Russians have presented what they claim is a Ukrainian intelligence agent detained in Crimea. How did he become an agent? He simply went to the SBU website and offered his services. Just like that. This is how Russian intelligence is trying to clean up its tarnished reputation.
0:54

Russians have presented what they claim is a Ukrainian intelligence agent detained in Crimea. How did he become an agent? He simply went to the SBU website and offered his services. Just like that. This is how Russian intelligence is trying to clean up its tarnished reputation.

WarTranslated

267,866 görüntüleme • 1 yıl önce

THIS GUY REPLACED HIS ENTIRE CONTENT TEAM WITH A FREE AI AGENT - NOW GETS 340K VIEWS PER POST ALONE 😳 he uses hermes + obsidian and it's completely free - runs on the claude plan he already had you give it one idea and it splits into a team one part researches, one finds the angle, one writes the post, one turns it into a newsletter, one makes the captions all of that from a single sentence it already knows his voice, his audience, his business - so nothing it makes sounds generic he doesn't manage it, remind it, or babysit it 7,100 bookmarks, 340K views, 20 minutes per post, zero team, zero paid tools ↓ he wrote the full guide so you can copy the exact setup from zero:
17:04

THIS GUY REPLACED HIS ENTIRE CONTENT TEAM WITH A FREE AI AGENT - NOW GETS 340K VIEWS PER POST ALONE 😳 he uses hermes + obsidian and it's completely free - runs on the claude plan he already had you give it one idea and it splits into a team one part researches, one finds the angle, one writes the post, one turns it into a newsletter, one makes the captions all of that from a single sentence it already knows his voice, his audience, his business - so nothing it makes sounds generic he doesn't manage it, remind it, or babysit it 7,100 bookmarks, 340K views, 20 minutes per post, zero team, zero paid tools ↓ he wrote the full guide so you can copy the exact setup from zero:

Isra

25,632 görüntüleme • 1 ay 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:
2:49

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

105,343 görüntüleme • 1 yıl önce

Every AI lab built you a single-player chatbot. But group chat got nothing. And we need agents that know how to listen and do things, not just talk. So we built Convos. We've been calling it an agentic messenger. It gives every group chat a harness: any model, real tools, and little agents that get things done. Nothing is shared across groups. 🧾 The trip group chat gets an agent that builds a killer itinerary and splits the expenses. 🏓 The pickleball chat gets a coordinator that books the court and gets everyone there. 🍳 The family chat gets a meal planner that picks recipes and writes the shopping list. Got another idea? Tag Convos and it'll reply with an agent for your group. Free to try, no sign up required. Here's how Shane Mac runs his life with his team of little agents. 1/7
6:46

Every AI lab built you a single-player chatbot. But group chat got nothing. And we need agents that know how to listen and do things, not just talk. So we built Convos. We've been calling it an agentic messenger. It gives every group chat a harness: any model, real tools, and little agents that get things done. Nothing is shared across groups. 🧾 The trip group chat gets an agent that builds a killer itinerary and splits the expenses. 🏓 The pickleball chat gets a coordinator that books the court and gets everyone there. 🍳 The family chat gets a meal planner that picks recipes and writes the shopping list. Got another idea? Tag Convos and it'll reply with an agent for your group. Free to try, no sign up required. Here's how Shane Mac runs his life with his team of little agents. 1/7

Convos

397,988 görüntüleme • 15 gün önce

Mark Zuckerberg just described the minimum viable business for the next decade. A fourth item made the checklist. Zuckerberg: “Every business, just like they have a website, and a phone number, and an email address, is also going to have an AI.” Website. Phone number. Email address. AI agent. That is not a prediction. That is a new baseline. Twenty years ago, not having a website was a choice. Then it stopped being one. Nobody scheduled that transition. The same filter is back. Running faster this time. A business without an AI agent handling sales, support, and customer interaction will not look outdated. It will look abandoned. Its competitor’s agent responds in two seconds. Knows every customer by name. And while it’s handling yours, it’s handling ten thousand others. You do not outwork that. You do not outspend it. You just lose to it. But Zuckerberg went somewhere most tech CEOs refuse to go. He picked a side in the debate most CEOs avoid entirely. Zuckerberg: “Do you want a future where you’re interacting with kind of one system for everything? Or do you want one where a lot of different people are building a lot of different AIs?” One AI controlled by one company. Or millions of AIs built by millions of people. Centralized intelligence. Or distributed intelligence. Zuckerberg chose distributed. Zuckerberg: “What open source does is it makes it so everyone can take and modify the model and build stuff on top of it. Which is different from the kind of closed and centralized approach.” The closed model makes every business a tenant. You rent intelligence on someone else’s terms. At someone else’s price. Inside someone else’s guardrails. The open model makes every business an owner. You modify the model. You deploy it your way. You build equity in your own system with every iteration. That gap widens quietly. Then it becomes permanent. The tenant pays more for less control every year. The owner pulls further ahead every cycle. One is a subscription. The other is infrastructure. Then Zuckerberg described the part most people have not thought about yet. Zuckerberg: “A lot of creators will have their own AIs. It’s like a richer world when there’s a diversity of different things.” Your favorite creator will have an AI trained on everything they have ever made. Available to millions of people simultaneously. Responding in real time while the creator sleeps. That is the difference between a brand that scales with your waking hours and one that scales with compute. One has a ceiling. The other does not. Zuckerberg is not betting on one model that governs everything. He is betting on billions of specialized AIs, each built by the person closest to the problem it solves. The companies still debating whether to adopt AI are not having the wrong conversation. They are standing in a room where the meeting ended an hour ago. The checklist updated. They did not.
0:58

Mark Zuckerberg just described the minimum viable business for the next decade. A fourth item made the checklist. Zuckerberg: “Every business, just like they have a website, and a phone number, and an email address, is also going to have an AI.” Website. Phone number. Email address. AI agent. That is not a prediction. That is a new baseline. Twenty years ago, not having a website was a choice. Then it stopped being one. Nobody scheduled that transition. The same filter is back. Running faster this time. A business without an AI agent handling sales, support, and customer interaction will not look outdated. It will look abandoned. Its competitor’s agent responds in two seconds. Knows every customer by name. And while it’s handling yours, it’s handling ten thousand others. You do not outwork that. You do not outspend it. You just lose to it. But Zuckerberg went somewhere most tech CEOs refuse to go. He picked a side in the debate most CEOs avoid entirely. Zuckerberg: “Do you want a future where you’re interacting with kind of one system for everything? Or do you want one where a lot of different people are building a lot of different AIs?” One AI controlled by one company. Or millions of AIs built by millions of people. Centralized intelligence. Or distributed intelligence. Zuckerberg chose distributed. Zuckerberg: “What open source does is it makes it so everyone can take and modify the model and build stuff on top of it. Which is different from the kind of closed and centralized approach.” The closed model makes every business a tenant. You rent intelligence on someone else’s terms. At someone else’s price. Inside someone else’s guardrails. The open model makes every business an owner. You modify the model. You deploy it your way. You build equity in your own system with every iteration. That gap widens quietly. Then it becomes permanent. The tenant pays more for less control every year. The owner pulls further ahead every cycle. One is a subscription. The other is infrastructure. Then Zuckerberg described the part most people have not thought about yet. Zuckerberg: “A lot of creators will have their own AIs. It’s like a richer world when there’s a diversity of different things.” Your favorite creator will have an AI trained on everything they have ever made. Available to millions of people simultaneously. Responding in real time while the creator sleeps. That is the difference between a brand that scales with your waking hours and one that scales with compute. One has a ceiling. The other does not. Zuckerberg is not betting on one model that governs everything. He is betting on billions of specialized AIs, each built by the person closest to the problem it solves. The companies still debating whether to adopt AI are not having the wrong conversation. They are standing in a room where the meeting ended an hour ago. The checklist updated. They did not.

Dustin

506,657 görüntüleme • 3 ay önce

He started using Claude AI and made $25,000 in his first month The guy could not even hide how much it changed his life. He paid for Claude and treated it like a real business partner. Built workflows that automate client work, content and outreach all in one place. What used to take him 12 hours a day now takes 2. He started taking on triple the clients without burning out once. At $5,000 per client and five clients a month, the numbers move fast. That is $25,000 landing in his account from a tool that costs $20. Most people use Claude to write captions and call it a day. He used it to rebuild his entire income from the ground up. Follow if you want the exact workflows he uses to scale this.
0:46

He started using Claude AI and made $25,000 in his first month The guy could not even hide how much it changed his life. He paid for Claude and treated it like a real business partner. Built workflows that automate client work, content and outreach all in one place. What used to take him 12 hours a day now takes 2. He started taking on triple the clients without burning out once. At $5,000 per client and five clients a month, the numbers move fast. That is $25,000 landing in his account from a tool that costs $20. Most people use Claude to write captions and call it a day. He used it to rebuild his entire income from the ground up. Follow if you want the exact workflows he uses to scale this.

winkle.

21,373 görüntüleme • 1 ay önce

It seems that Republicans are trying to gaslight everyone into believing that Dayanne Figueroa rammed into an ICE agent’s car… So let’s break down the video, frame by frame. 1. This is Chicago… a dense, urban area with traffic in every direction. 2. The street is two-way… you can clearly see another car driving toward the camera. 3. The ICE agent, in an unmarked vehicle, is sitting in the road. 4. They then make a very wide turn… onto the left side of the road. 5. At this point, the agent is driving on the wrong side of the road. 6. The ICE agent, seemingly unaware of their surroundings (never ideal while driving in a major city), tries to enter the correct lane… without signaling, and without checking to see if someone’s already in that lane. 7. And it turns out, someone was already in that lane… Note: A federal agent, in an unmarked vehicle, does not have the right of way unless they have their 🚨 on. The ICE agent did NOT have their 🚨 on. 8. So, the ICE agent made an improper and unsafe lane change and hit Dayanne Figueroa’s car. 9. Then, they started to drive away, but decided to kidnapped her first. Hope this helps.
1:01

It seems that Republicans are trying to gaslight everyone into believing that Dayanne Figueroa rammed into an ICE agent’s car… So let’s break down the video, frame by frame. 1. This is Chicago… a dense, urban area with traffic in every direction. 2. The street is two-way… you can clearly see another car driving toward the camera. 3. The ICE agent, in an unmarked vehicle, is sitting in the road. 4. They then make a very wide turn… onto the left side of the road. 5. At this point, the agent is driving on the wrong side of the road. 6. The ICE agent, seemingly unaware of their surroundings (never ideal while driving in a major city), tries to enter the correct lane… without signaling, and without checking to see if someone’s already in that lane. 7. And it turns out, someone was already in that lane… Note: A federal agent, in an unmarked vehicle, does not have the right of way unless they have their 🚨 on. The ICE agent did NOT have their 🚨 on. 8. So, the ICE agent made an improper and unsafe lane change and hit Dayanne Figueroa’s car. 9. Then, they started to drive away, but decided to kidnapped her first. Hope this helps.

Jesus Freakin Congress

70,221 görüntüleme • 8 ay önce

Andrew Wilkinson owns 40+ businesses. He just showed me how he's using OpenClaw, Claude Code and AI agents to run latest business, start new ones, and automate everything. Here's what I learned: 1. In December 2025, something clicked. He started waking up at 3AM with a smile, sitting in terminal with 10 Claude Code tabs open. He hasn't stopped since. He calls it chasing the dragon. 2.He built a full SaaS product called Deep Personality. A 40-minute personality test that generates a 100-page report written like Robert Greene. $20 000 in revenue. Zero employees. The entire business runs on AI agents. 3. He has agents for support, marketing, and dev. When a support ticket comes in, the agent either handles it or sends it to the dev agent. If it's critical, the agent fixes the bug and merges the PR before he wakes up. Then it emails the customer back. 4. His marketing agent is connected to PostHog, manages Meta and Reddit ads, creates ad creative, runs multivariate tests, and sets budgets. He's about to give it a $100 k/month ad budget and see what happens. 5. He forgot his laptop on a trip to Arizona. He ran his entire business from the back of Ubers using OpenClaw. Nobody picked up that every single email was written by AI. 6. His take on vibe coding: the worst part about business is people. Between your vision and execution are 100 people you have to convince. Vibe coding removes all of them. For the first time he can do every part of building a product himself. 7. He was trying to build OpenClaw before OpenClaw existed. Now he uses a tool called Harbor, which is basically a GUI for managing multiple agents. You can see all your agents, their status, knowledge bases, and databases in one place. 8. He built a custom AI for his relationship. He and his girlfriend took 15 psychological tests, put the results into ChatGPT, and asked it to analyze their relationship. It nailed every fight they've ever had. That became the product idea for Deep Personality. 9. His honest take: he spends 50% of his time debugging, 30% improving the setup, and 20% being productive. It's a treadmill. But the 20% that works is so powerful he can't stop. 10. His prediction: we're 3-6 months from being able to hand basic businesses off to AI to run entirely. And pretty soon Anthropic and OpenAI are going to launch AI CEOs. This is an inside look at how a serious operator Andrew Wilkinson is using AI agents in the real world. The good, the bad, the debugging, all of it. Most people don't show you this. Episode is live on The Startup Ideas Podcast (SIP) 🧃 watch
47:23

Andrew Wilkinson owns 40+ businesses. He just showed me how he's using OpenClaw, Claude Code and AI agents to run latest business, start new ones, and automate everything. Here's what I learned: 1. In December 2025, something clicked. He started waking up at 3AM with a smile, sitting in terminal with 10 Claude Code tabs open. He hasn't stopped since. He calls it chasing the dragon. 2.He built a full SaaS product called Deep Personality. A 40-minute personality test that generates a 100-page report written like Robert Greene. $20 000 in revenue. Zero employees. The entire business runs on AI agents. 3. He has agents for support, marketing, and dev. When a support ticket comes in, the agent either handles it or sends it to the dev agent. If it's critical, the agent fixes the bug and merges the PR before he wakes up. Then it emails the customer back. 4. His marketing agent is connected to PostHog, manages Meta and Reddit ads, creates ad creative, runs multivariate tests, and sets budgets. He's about to give it a $100 k/month ad budget and see what happens. 5. He forgot his laptop on a trip to Arizona. He ran his entire business from the back of Ubers using OpenClaw. Nobody picked up that every single email was written by AI. 6. His take on vibe coding: the worst part about business is people. Between your vision and execution are 100 people you have to convince. Vibe coding removes all of them. For the first time he can do every part of building a product himself. 7. He was trying to build OpenClaw before OpenClaw existed. Now he uses a tool called Harbor, which is basically a GUI for managing multiple agents. You can see all your agents, their status, knowledge bases, and databases in one place. 8. He built a custom AI for his relationship. He and his girlfriend took 15 psychological tests, put the results into ChatGPT, and asked it to analyze their relationship. It nailed every fight they've ever had. That became the product idea for Deep Personality. 9. His honest take: he spends 50% of his time debugging, 30% improving the setup, and 20% being productive. It's a treadmill. But the 20% that works is so powerful he can't stop. 10. His prediction: we're 3-6 months from being able to hand basic businesses off to AI to run entirely. And pretty soon Anthropic and OpenAI are going to launch AI CEOs. This is an inside look at how a serious operator Andrew Wilkinson is using AI agents in the real world. The good, the bad, the debugging, all of it. Most people don't show you this. Episode is live on The Startup Ideas Podcast (SIP) 🧃 watch

GREG ISENBERG

144,005 görüntüleme • 2 ay önce

When I interviewed Ron Paul last year, I asked him what it was about his race, when compared to someone like Mitt Romney’s, that created such an enduring movement. Because he's extraordinarily humble, Dr. Paul said it was because of the ideas and that he was standing on the shoulders of giants. But I insisted that it went beyond the ideas— it had something to do with his character. Tucker Carlson’s monologue before his interview with Ron Paul captures it exactly: It can't be reduced to the fact that he was a libertarian—that overstates it and understates it. Ron Paul created a lasting movement because he is an honest man and has been a consistent moral voice. And for that, he was seen as crazy in 2008 and 2012. But now people recognize that Ron Paul was right.
1:24

When I interviewed Ron Paul last year, I asked him what it was about his race, when compared to someone like Mitt Romney’s, that created such an enduring movement. Because he's extraordinarily humble, Dr. Paul said it was because of the ideas and that he was standing on the shoulders of giants. But I insisted that it went beyond the ideas— it had something to do with his character. Tucker Carlson’s monologue before his interview with Ron Paul captures it exactly: It can't be reduced to the fact that he was a libertarian—that overstates it and understates it. Ron Paul created a lasting movement because he is an honest man and has been a consistent moral voice. And for that, he was seen as crazy in 2008 and 2012. But now people recognize that Ron Paul was right.

Liam McCollum

23,386 görüntüleme • 5 ay önce