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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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229,018 просмотров • 1 год назад •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

504,841 просмотров • 11 месяцев назад

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 просмотров • 1 год назад

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:
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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 🖤

49,862 просмотров • 4 месяцев назад

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 просмотров • 2 месяцев назад

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.
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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

36,463 просмотров • 4 месяцев назад

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
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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

1,329,581 просмотров • 6 месяцев назад

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.
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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 просмотров • 1 год назад

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

511,699 просмотров • 2 месяцев назад

He is 17 and already an AI engineer at OpenAI making $1.4M a year - and came to Stanford to share how: "I finished school and immediately made $100k a month thanks to AI" 00:33 - how to get an OpenAI offer at 17 with no degree 28:34 - how an agent without code brings $100k 49:47 - how Claude Code turns you into a $1.4M AI engineer after watching I realized that 4 years of university gave me a degree - an agent would have given me $1.4M a year. Save & watch - the article below is a step by step guide to build an agent that will land you a job at Anthropic or OpenAI.
1:16:18

He is 17 and already an AI engineer at OpenAI making $1.4M a year - and came to Stanford to share how: "I finished school and immediately made $100k a month thanks to AI" 00:33 - how to get an OpenAI offer at 17 with no degree 28:34 - how an agent without code brings $100k 49:47 - how Claude Code turns you into a $1.4M AI engineer after watching I realized that 4 years of university gave me a degree - an agent would have given me $1.4M a year. Save & watch - the article below is a step by step guide to build an agent that will land you a job at Anthropic or OpenAI.

Noisy

70,524 просмотров • 1 месяц назад

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

437,059 просмотров • 6 месяцев назад

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

99,289 просмотров • 11 месяцев назад

One of the most productive engineers I know cannot read code. Matt Van Horn is not an engineer by training. He co-founded June, has 44,000 GitHub stars, and got contributions merged into Go & Python. I had him build live for an hour & walk me through his process. My fav lessons & quotes from the convo: 1) He never reads code. He does not have an IDE installed. In his words, "I fundamentally believe that very soon no humans should ever write any code and that no humans should ever read any code." 2) Every project starts with the agent writing itself a plan.md file using Compound Engineering. Agents are lazy, he says, and the plan keeps them honest. He never reads the plan either. "Plans are for agents, you silly human." 3) His CLIs leave notes for themselves. Each run records what it learned in a markdown file, so the next run starts where the last one ended. He calls them self-healing. 4) His agent has an email address. From Telegram on his phone, he sends a task. It emails his Mac, authenticated, and the work starts while he is at his kids' soccer practice. 5) He feeds whole transcripts, not summaries. After a two-hour meeting with a Google Ventures researcher, his agent read the researcher's entire book, wrote itself a report on every chapter, and turned it all into a plan for his business. 6) Him yapping to his agents is like nerd ASMR. "Go agent go" is how he likes to finish telling the agent what to do. 7) How he thinks about this next chapter of building: "Every generation of tools moves the engineer's job up a level. The code was never the point. The problem was."
43:18

One of the most productive engineers I know cannot read code. Matt Van Horn is not an engineer by training. He co-founded June, has 44,000 GitHub stars, and got contributions merged into Go & Python. I had him build live for an hour & walk me through his process. My fav lessons & quotes from the convo: 1) He never reads code. He does not have an IDE installed. In his words, "I fundamentally believe that very soon no humans should ever write any code and that no humans should ever read any code." 2) Every project starts with the agent writing itself a plan.md file using Compound Engineering. Agents are lazy, he says, and the plan keeps them honest. He never reads the plan either. "Plans are for agents, you silly human." 3) His CLIs leave notes for themselves. Each run records what it learned in a markdown file, so the next run starts where the last one ended. He calls them self-healing. 4) His agent has an email address. From Telegram on his phone, he sends a task. It emails his Mac, authenticated, and the work starts while he is at his kids' soccer practice. 5) He feeds whole transcripts, not summaries. After a two-hour meeting with a Google Ventures researcher, his agent read the researcher's entire book, wrote itself a report on every chapter, and turned it all into a plan for his business. 6) Him yapping to his agents is like nerd ASMR. "Go agent go" is how he likes to finish telling the agent what to do. 7) How he thinks about this next chapter of building: "Every generation of tools moves the engineer's job up a level. The code was never the point. The problem was."

Alex Lieberman

78,422 просмотров • 1 месяц назад

Drew Brees says Sean Payton betting his career on him changed how he approached every day in an effort to prove him right “I credit him and Mickey being the two guys that were the decision-makers that brought me to New Orleans. But truly Sean being the one that said... Man, this is the guy. This is the guy that I am entrusting my career, his career, with.’” “Given the fact… ‘I’m an offensive guy.’ ‘I’m a play caller.’ ‘It all runs through the guy that I select and I develop.’ ‘And I’m choosing you.’ And so every day I woke up saying… ‘How do I make this guy right?’” “‘How do I make him feel like he always made the right decision?’ And that’s not just the way that I played on the field. But it was the type of teammate that I tried to be. And just the way that I tried to approach everything. Because I felt like I was a representation of him in a lot of ways.”
0:48

Drew Brees says Sean Payton betting his career on him changed how he approached every day in an effort to prove him right “I credit him and Mickey being the two guys that were the decision-makers that brought me to New Orleans. But truly Sean being the one that said... Man, this is the guy. This is the guy that I am entrusting my career, his career, with.’” “Given the fact… ‘I’m an offensive guy.’ ‘I’m a play caller.’ ‘It all runs through the guy that I select and I develop.’ ‘And I’m choosing you.’ And so every day I woke up saying… ‘How do I make this guy right?’” “‘How do I make him feel like he always made the right decision?’ And that’s not just the way that I played on the field. But it was the type of teammate that I tried to be. And just the way that I tried to approach everything. Because I felt like I was a representation of him in a lot of ways.”

Josh Chambers

19,793 просмотров • 21 дней назад

So Piers Morgan, a journalist I value, interviewed Clavicular for his show. I appreciate the time he gave in the segment to talk about the interview Clavicular gave us on Channel 13 and why he left that interview. Unlike other figures, Morgan acted like a journalist, and tried to understand what the problem was with asking him why he is refusing to apologize - while in Israel - for the Heil Hitler incident. Clavicular said that he was asked about it plenty of times, again didn’t want to answer, and threw back accusations at the interviewer as usual. And the real question is: why is that? Why was it so easy for him to stream to tens of millions of followers - at least four times - a song glorifying Hitler, and why is it so hard for him, just once, to acknowledge this as an insult to millions of Jews? Maybe, just maybe, it all comes down to the fact that he knows anti-Semitic content gets you traffic. Just like he knows humiliating young girls gets you views. He still has anti-Semitic friends like Nick Fuentes and just defended Andrew Tate. This guy didn’t aim to do PR for Israel. He didn’t come here and hold formal meetings with Netanyahu’s advisors - a lie he keeps repeating. He was actually thrown out of a club because the owner heard that he sang the Heil Hitler song. He got hate on every corner he visited. His aim was simply to get clicks. He is not a “kid.” He holds an internet empire with managers and employees. He knows how to talk; he certainly is not stupid. He is a professional provocateur who hopped on the Israeli trend. At least Piers Morgan, unlike others, had the fairness to pull the mask off this guy. Piers Morgan
3:01

So Piers Morgan, a journalist I value, interviewed Clavicular for his show. I appreciate the time he gave in the segment to talk about the interview Clavicular gave us on Channel 13 and why he left that interview. Unlike other figures, Morgan acted like a journalist, and tried to understand what the problem was with asking him why he is refusing to apologize - while in Israel - for the Heil Hitler incident. Clavicular said that he was asked about it plenty of times, again didn’t want to answer, and threw back accusations at the interviewer as usual. And the real question is: why is that? Why was it so easy for him to stream to tens of millions of followers - at least four times - a song glorifying Hitler, and why is it so hard for him, just once, to acknowledge this as an insult to millions of Jews? Maybe, just maybe, it all comes down to the fact that he knows anti-Semitic content gets you traffic. Just like he knows humiliating young girls gets you views. He still has anti-Semitic friends like Nick Fuentes and just defended Andrew Tate. This guy didn’t aim to do PR for Israel. He didn’t come here and hold formal meetings with Netanyahu’s advisors - a lie he keeps repeating. He was actually thrown out of a club because the owner heard that he sang the Heil Hitler song. He got hate on every corner he visited. His aim was simply to get clicks. He is not a “kid.” He holds an internet empire with managers and employees. He knows how to talk; he certainly is not stupid. He is a professional provocateur who hopped on the Israeli trend. At least Piers Morgan, unlike others, had the fairness to pull the mask off this guy. Piers Morgan

בר שם-אור Bar Shem-Ur

16,264 просмотров • 1 месяц назад

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

25,704 просмотров • 2 месяцев назад

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

Andrew Ng

105,343 просмотров • 1 год назад

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
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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

399,532 просмотров • 2 месяцев назад

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

507,064 просмотров • 5 месяцев назад