Загрузка видео...

Не удалось загрузить видео

На главную

Grok Bot might be the first tool that lets one non-technical person run an entire business with a team of AI agents. My friend Billy runs his whole newsletter business on Grok Bot agents, and I think we're about to see 100,000+ businesses like his. BEST PRACTICES: 1. The...

gregisenberg's profile picture

GREG ISENBERG

699,840 subscribers

3,988,289 просмотров • 7 дней назад •via X (Twitter)

Наука и технологииОбразованиеФинансы
LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

SpaceXAI just released a free 1-hour Grok Bot Agents course that goes far beyond prompting: build one Bot → give it a job → add a Chief of Staff → connect the team → let the whole system run 24/7 2:15 - build your first Grok Bot 6:52 - turn Bots into specialized workers 16:51 - create routines that run without you 31:50 - make multiple agents work together 52:18 - assemble the full 24/7 agent system Most AI agent tutorials teach you how to build one assistant that still waits for instructions This course shows the opposite: specialized Bots, a manager above them, persistent routines, app connections and agents handing work to other agents Watch it, build your first Bot, then turn it into an entire team Then read the full Grok Bot architecture below ↓
1:01:59

SpaceXAI just released a free 1-hour Grok Bot Agents course that goes far beyond prompting: build one Bot → give it a job → add a Chief of Staff → connect the team → let the whole system run 24/7 2:15 - build your first Grok Bot 6:52 - turn Bots into specialized workers 16:51 - create routines that run without you 31:50 - make multiple agents work together 52:18 - assemble the full 24/7 agent system Most AI agent tutorials teach you how to build one assistant that still waits for instructions This course shows the opposite: specialized Bots, a manager above them, persistent routines, app connections and agents handing work to other agents Watch it, build your first Bot, then turn it into an entire team Then read the full Grok Bot architecture below ↓

Morlex

26,449 просмотров • 8 дней назад

You can spin up an AI workforce with one prompt. Here's why it works: it pulls the context the AI needs to lay the foundation. Give it: - your role - team size - the goals you want to hit. Then say "interview me." After that, build it out in four steps: 1) Start with 1 agent. - What does it feel like to work with one? 2) Make that agent proactive. - Now it's doing things on your behalf before you ask. 3) Expand to 2 agents. - One directs the other, or routes to it. - This is where you learn how context gets passed. 4) Scale the workforce. - A mission control where you watch it all move around. - Now you see what has to run in parallel, which agent never needed that tool, which one runs fine on a smaller model. - Not everything needs Opus. Sub-agents are haiku and sonnet. The catch: the prompt gets you agents with markdown files doing some stuff. Getting to the 90% plus level is iteration, and that part is specific to each person. Nobody can hand it to you. Start with one agent. Spin up one agent this week. The rest is discovery.
3:10

You can spin up an AI workforce with one prompt. Here's why it works: it pulls the context the AI needs to lay the foundation. Give it: - your role - team size - the goals you want to hit. Then say "interview me." After that, build it out in four steps: 1) Start with 1 agent. - What does it feel like to work with one? 2) Make that agent proactive. - Now it's doing things on your behalf before you ask. 3) Expand to 2 agents. - One directs the other, or routes to it. - This is where you learn how context gets passed. 4) Scale the workforce. - A mission control where you watch it all move around. - Now you see what has to run in parallel, which agent never needed that tool, which one runs fine on a smaller model. - Not everything needs Opus. Sub-agents are haiku and sonnet. The catch: the prompt gets you agents with markdown files doing some stuff. Getting to the 90% plus level is iteration, and that part is specific to each person. Nobody can hand it to you. Start with one agent. Spin up one agent this week. The rest is discovery.

The Startup Ideas Podcast (SIP) 🧃

18,006 просмотров • 15 дней назад

Grok Bot is literally the closest thing to a real-life Jarvis It can start a business, ship software, and make you go viral - all at once. Here's how to run your entire business with it in 4 minutes: 1. Install Grok Bot and create your chief of staff 2. Give it the Digital Chief of Staff prompt 3. Connect it to X, Docs, Notion, Whop, and GitHub 4. You're done Then paste this article and hand it to your chief of staff. No matter what, this will be the most productive thing you do this week ↓ Bookmark this before you scroll past it.
0:33

Grok Bot is literally the closest thing to a real-life Jarvis It can start a business, ship software, and make you go viral - all at once. Here's how to run your entire business with it in 4 minutes: 1. Install Grok Bot and create your chief of staff 2. Give it the Digital Chief of Staff prompt 3. Connect it to X, Docs, Notion, Whop, and GitHub 4. You're done Then paste this article and hand it to your chief of staff. No matter what, this will be the most productive thing you do this week ↓ Bookmark this before you scroll past it.

Rahul

103,804 просмотров • 2 дней назад

grok bot is literally the closest to a real life Jarvis it can literally start a business, ship software and make you go viral all at once here's how you do it (in 4 mins) 1. install grok bot and make your chief of staff (tony soprano) 2.give it the 'Digital Chief of Staff Prompt' prompt 3.give it access to X, Stripe and Github 4. you are done just paste the article and give it to your chief of staff no matter what it will be the most productive thing you do this week
0:39

grok bot is literally the closest to a real life Jarvis it can literally start a business, ship software and make you go viral all at once here's how you do it (in 4 mins) 1. install grok bot and make your chief of staff (tony soprano) 2.give it the 'Digital Chief of Staff Prompt' prompt 3.give it access to X, Stripe and Github 4. you are done just paste the article and give it to your chief of staff no matter what it will be the most productive thing you do this week

Avid

2,957,083 просмотров • 9 дней назад

One of the best businesses to run with GrokBot is a newsletter. Here's the whole setup: 1) Put your sources in a list. Google Sheet, Notion, either works. 2) Connect GrokBot to Notion with a plugin. It drops a card in the chat for your API key or an OAuth button, so this takes a minute. 3) Twice a week it reads the sources and files one card per story: a new restaurant opening, a special movie showing, a short summary of each. 4) It filters ~200 possible items down to the handful worth sending. 5) Move a card to Process and it writes the item in the format I use every week: emoji, event title, time, summary. 6) Schedules it to Beehiiv. If no plugin exists for a tool you need, GrokBot can install the CLI on its own computer and drive it that way. If you already know the best subreddits in your niche, you've solved the taste and context part of the newsletter. The rest is setting up GrokBot and letting it run. Build it, run it, then automate it.
5:57

One of the best businesses to run with GrokBot is a newsletter. Here's the whole setup: 1) Put your sources in a list. Google Sheet, Notion, either works. 2) Connect GrokBot to Notion with a plugin. It drops a card in the chat for your API key or an OAuth button, so this takes a minute. 3) Twice a week it reads the sources and files one card per story: a new restaurant opening, a special movie showing, a short summary of each. 4) It filters ~200 possible items down to the handful worth sending. 5) Move a card to Process and it writes the item in the format I use every week: emoji, event title, time, summary. 6) Schedules it to Beehiiv. If no plugin exists for a tool you need, GrokBot can install the CLI on its own computer and drive it that way. If you already know the best subreddits in your niche, you've solved the taste and context part of the newsletter. The rest is setting up GrokBot and letting it run. Build it, run it, then automate it.

The Startup Ideas Podcast (SIP) 🧃

16,780 просмотров • 7 дней назад

call me insane... but grok bot is the single most powerful agent stack i've ever used. it will have your entire business run by agent teams working for you 24/7. I just cancelled chatgpt and hermes to replace them with it then mapped the entire grok bot agentic workflows into 4 excalidraw diagrams... (steal this) →support desk: a chief of staff bot routes tickets, drafts replies, pings me only for refunds or anger →money + ops: a bot processes invoices in gmail and keeps the books moving without me →content: a bot scopes the brief, cites sources, hands me a publish-ready draft →build: a bot reproduces the bug, files the ticket, hands the fix to the next bot plus it's all free..give the screenshots to grok bot and it runs your business
0:29

call me insane... but grok bot is the single most powerful agent stack i've ever used. it will have your entire business run by agent teams working for you 24/7. I just cancelled chatgpt and hermes to replace them with it then mapped the entire grok bot agentic workflows into 4 excalidraw diagrams... (steal this) →support desk: a chief of staff bot routes tickets, drafts replies, pings me only for refunds or anger →money + ops: a bot processes invoices in gmail and keeps the books moving without me →content: a bot scopes the brief, cites sources, hands me a publish-ready draft →build: a bot reproduces the bug, files the ticket, hands the fix to the next bot plus it's all free..give the screenshots to grok bot and it runs your business

Avid

19,477 просмотров • 10 дней назад

i merged all my AI agents into one brain Claude Code, Codex, Gemini: one team, one memory, zero re-briefing result: 8+ hours a week back, and every agent already knows my projects, my clients and how i think here's the setup with Jarvix: 1. dump your context once: projects, clients, writing style, how you make decisions.. it builds your personal model from your actual AI interactions 2. switch agents mid-task with zero re-briefing: Claude Code builds, Codex reviews, Gemini researches, all reading the same context 3. it carries what YOU choose across sessions.. never start a chat from zero again 4. when it's time to act, it pulls the right agents together as one team instead of five separate assistants the unlock isn't another agent. it's that your context finally travels agents without shared memory are five interns on their first day, forever. agents with it are a team that's worked with you for years not more agents. one shared context that's the right bet P.S. thanks to the Jarvix team for the early access
2:15

i merged all my AI agents into one brain Claude Code, Codex, Gemini: one team, one memory, zero re-briefing result: 8+ hours a week back, and every agent already knows my projects, my clients and how i think here's the setup with Jarvix: 1. dump your context once: projects, clients, writing style, how you make decisions.. it builds your personal model from your actual AI interactions 2. switch agents mid-task with zero re-briefing: Claude Code builds, Codex reviews, Gemini researches, all reading the same context 3. it carries what YOU choose across sessions.. never start a chat from zero again 4. when it's time to act, it pulls the right agents together as one team instead of five separate assistants the unlock isn't another agent. it's that your context finally travels agents without shared memory are five interns on their first day, forever. agents with it are a team that's worked with you for years not more agents. one shared context that's the right bet P.S. thanks to the Jarvix team for the early access

Ronin

15,071 просмотров • 16 дней назад

One of the Grok Bot builders: "For the first time I allocated 90% of my work to agents and they did it end to end." In a 30-minute podcast he showed exactly how he uses Grok Bot and how to build an AI agent team from scratch. This beats any paid course on building agents I've seen. Watch it, then read the step-by-step guide on building your AI team for free, with ready-to-copy prompts.
31:10

One of the Grok Bot builders: "For the first time I allocated 90% of my work to agents and they did it end to end." In a 30-minute podcast he showed exactly how he uses Grok Bot and how to build an AI agent team from scratch. This beats any paid course on building agents I've seen. Watch it, then read the step-by-step guide on building your AI team for free, with ready-to-copy prompts.

Anatoli Kopadze

17,123 просмотров • 8 дней назад

SpaceXAI just released free 1-hour course on Grok Bot Agents: 1 prompt → CEO bot → agent teams → full 24/7 system from 0% to 100%: 0% → 2:15 - build your first Grok Bot 25% → 6:52 - give every Bot a role 50% → 16:51 - teach Bots to work 24/7 75% → 31:50 - run agent teams in parallel 100% → 52:18 - full system that automate your life most agent tutorials give you a chatbot that waits for prompts - this one builds a 24/7 team that works while your laptop is closed - by team who build it watch it, build one Bot, turn it into a team - then read the full Grok Bot architecture below ↓
1:02:12

SpaceXAI just released free 1-hour course on Grok Bot Agents: 1 prompt → CEO bot → agent teams → full 24/7 system from 0% to 100%: 0% → 2:15 - build your first Grok Bot 25% → 6:52 - give every Bot a role 50% → 16:51 - teach Bots to work 24/7 75% → 31:50 - run agent teams in parallel 100% → 52:18 - full system that automate your life most agent tutorials give you a chatbot that waits for prompts - this one builds a 24/7 team that works while your laptop is closed - by team who build it watch it, build one Bot, turn it into a team - then read the full Grok Bot architecture below ↓

codila

281,731 просмотров • 8 дней назад

SpaceXAI engineer (ex. Cursor): "i've got 10-20 GrokBot agents running right now. they handle about 90% of the routine there's a Chief of staff agent on top - it knows every other bot I have and runs the whole thing" in a 35-workshop, a SpaceXAI engineer walks through building a team of GrokBot agents that works around the clock Worth more than a $500 course on agentic engineering Watch today, then read how to build your own Grok agent team from scratch in the article below
35:58

SpaceXAI engineer (ex. Cursor): "i've got 10-20 GrokBot agents running right now. they handle about 90% of the routine there's a Chief of staff agent on top - it knows every other bot I have and runs the whole thing" in a 35-workshop, a SpaceXAI engineer walks through building a team of GrokBot agents that works around the clock Worth more than a $500 course on agentic engineering Watch today, then read how to build your own Grok agent team from scratch in the article below

Carnage

33,121 просмотров • 8 дней назад

SpaceXAI engineer (ex-Cursor): "I'm running 10-20 GrokBot agents right now, and they handle 90% of my routine. I don't even manage them, I have a Chief of Staff agent that knows all the others and manages everything." 50 minutes from a SpaceXAI engineer, showing exactly how to build a team of agents that works for you 24/7. Worth more than any $700 course on agentic engineering. Watch it, then read the step-by-step guide on building your own Grok agent team for free, with ready-to-copy prompts.
49:55

SpaceXAI engineer (ex-Cursor): "I'm running 10-20 GrokBot agents right now, and they handle 90% of my routine. I don't even manage them, I have a Chief of Staff agent that knows all the others and manages everything." 50 minutes from a SpaceXAI engineer, showing exactly how to build a team of agents that works for you 24/7. Worth more than any $700 course on agentic engineering. Watch it, then read the step-by-step guide on building your own Grok agent team for free, with ready-to-copy prompts.

Anatoli Kopadze

130,089 просмотров • 3 дней назад

this video is the CLEAREST explanation of how claude skills + AI agents work and how to use them most people set up an AI agent and wonder why it keeps disappointing them. the context window is everything context is what the model assembles before it takes any action. think of it like everything the agent needs to read before it does anything. the quality of what goes in determines the quality of what comes out. the models are genuinely really good right now. claude and gpt are exceptional. the variable is almost always the context you give them. 1. agent.md files are mostly unnecessary every single line you put in an agent.md file gets added to every single conversation you have with your agent. a 1000 line file is around 7000 tokens burning on every run. the model already knows to use react. it can read your codebase. save the agent.md for proprietary information specific to your company that the model genuinely cannot know on its own. 2. skills are the actual unlock a skill.md file works differently. what loads into context is only the name and description, around 50 tokens. the full instructions only appear when the agent recognizes it needs that skill. so instead of 7000 tokens on every run you have 50. and the agent stays sharp because the context window stays lean. the closer you get to filling the context window the worse the agent performs, same way you perform worse when someone dumps 10 things on you at once. 3. here is how to actually build a skill the right way most people identify a workflow and immediately try to write the skill. what you want to do instead is run the workflow by hand with the agent first. walk it through every single step. tell it what to check, what good looks like, what bad looks like. correct it in real time. once you have had a full successful run from start to finish, tell the agent to review everything it just did and write the skill itself. it writes a better skill than you will because it has the full context of what actually worked in practice not in theory. 4. recursively building skills is how you go from frustrated to reliable when the skill breaks, and it will break, ask the agent exactly why it failed. it will tell you specifically what went wrong. fix it together in that same conversation. then tell it to update the skill file so that failure mode never happens again. ross mike did this five times with his youtube report generator. it now pulls from eight different data sources and runs flawlessly every single time without him touching it. 5. sub agents are something you earn not something you set up on day one start with one agent. build one workflow. turn it into one skill. once that works add another. ross mike has five sub agents now covering marketing, business, personal and more. it took months to get there and every single one exists because a workflow proved it deserved to exist. the people who set up 15 sub agents on day one and wonder why nothing works skipped all the steps that make the thing actually run. 6. your workflow is the thing the model cannot get anywhere else the model has been trained on everything. it knows more than you about most things. what it does not have is your specific process, your taste, your way of doing things. that is what skills capture. that is what makes your agent actually useful versus a generic one. downloading someone else's skill means downloading their context onto your setup and it will not work the way you want it to because it was never built around how you work. this is the clearest explanation of how agents actually work i have heard. Micky runs this stuff every single day and the results show it. full episode is now live on The Startup Ideas Podcast (SIP) 🧃 where you get your pods people charge for this sorta stuff i give away the sauce for free i just want you to win watch
35:25

this video is the CLEAREST explanation of how claude skills + AI agents work and how to use them most people set up an AI agent and wonder why it keeps disappointing them. the context window is everything context is what the model assembles before it takes any action. think of it like everything the agent needs to read before it does anything. the quality of what goes in determines the quality of what comes out. the models are genuinely really good right now. claude and gpt are exceptional. the variable is almost always the context you give them. 1. agent.md files are mostly unnecessary every single line you put in an agent.md file gets added to every single conversation you have with your agent. a 1000 line file is around 7000 tokens burning on every run. the model already knows to use react. it can read your codebase. save the agent.md for proprietary information specific to your company that the model genuinely cannot know on its own. 2. skills are the actual unlock a skill.md file works differently. what loads into context is only the name and description, around 50 tokens. the full instructions only appear when the agent recognizes it needs that skill. so instead of 7000 tokens on every run you have 50. and the agent stays sharp because the context window stays lean. the closer you get to filling the context window the worse the agent performs, same way you perform worse when someone dumps 10 things on you at once. 3. here is how to actually build a skill the right way most people identify a workflow and immediately try to write the skill. what you want to do instead is run the workflow by hand with the agent first. walk it through every single step. tell it what to check, what good looks like, what bad looks like. correct it in real time. once you have had a full successful run from start to finish, tell the agent to review everything it just did and write the skill itself. it writes a better skill than you will because it has the full context of what actually worked in practice not in theory. 4. recursively building skills is how you go from frustrated to reliable when the skill breaks, and it will break, ask the agent exactly why it failed. it will tell you specifically what went wrong. fix it together in that same conversation. then tell it to update the skill file so that failure mode never happens again. ross mike did this five times with his youtube report generator. it now pulls from eight different data sources and runs flawlessly every single time without him touching it. 5. sub agents are something you earn not something you set up on day one start with one agent. build one workflow. turn it into one skill. once that works add another. ross mike has five sub agents now covering marketing, business, personal and more. it took months to get there and every single one exists because a workflow proved it deserved to exist. the people who set up 15 sub agents on day one and wonder why nothing works skipped all the steps that make the thing actually run. 6. your workflow is the thing the model cannot get anywhere else the model has been trained on everything. it knows more than you about most things. what it does not have is your specific process, your taste, your way of doing things. that is what skills capture. that is what makes your agent actually useful versus a generic one. downloading someone else's skill means downloading their context onto your setup and it will not work the way you want it to because it was never built around how you work. this is the clearest explanation of how agents actually work i have heard. Micky runs this stuff every single day and the results show it. full episode is now live on The Startup Ideas Podcast (SIP) 🧃 where you get your pods people charge for this sorta stuff i give away the sauce for free i just want you to win watch

GREG ISENBERG

193,721 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 have been testing Grok Bot for the last week and it's EXCELLENT It is your own personal fleet of AI agents doing work for you 24/7 In this video I give you a FULL walkthrough of the tool, how it works, and how to 100x your productivity with it SpaceXAI COOKED
12:09

I have been testing Grok Bot for the last week and it's EXCELLENT It is your own personal fleet of AI agents doing work for you 24/7 In this video I give you a FULL walkthrough of the tool, how it works, and how to 100x your productivity with it SpaceXAI COOKED

Alex Finn

135,468 просмотров • 17 дней назад

ELON MUSK REPOSTED MY GROK BOT CONTENT SETUP. AND I STILL DON'T UNDERSTAND WHY NOBODY IS DOING THIS WITH TRADING YET. A WALL STREET RESEARCH DESK COSTS MILLIONS A YEAR TO STAFF – YOU CAN NOW RUN THE SAME THING WITH 9 GROK BOT AGENTS. Nine people used to do this job. Nine Grok Bot agents now do it while you sleep. Here's the entire desk: → MACRO – watches rates, CPI, FOMC. Tells you what kind of day it is before you open a single chart. → SCANNER – sweeps 9,000 tickers for one thing: your setup. Not "interesting stocks". Yours. → CATALYST – reads every 8-K, earnings call and wire the second it drops. Flags the two that matter. → QUANT – backtests the idea before you fall in love with it. Kills it if the edge isn't there. → CRYPTO – on-chain flows, funding, basis. The stuff nobody has the energy to check at 2am. → RISK – the one that actually saves you. Sizes the position, sets the stop, refuses the 4th trade. → EXECUTION – places the order, tracks the fill, reports the slippage in basis points. → COMPLIANCE – logs every single decision. So you can audit yourself instead of lying to yourself. → CHIEF OF STAFF – sits on top of all eight. Ranks their output and hands you one page every morning. Here's the part nobody says out loud: Retail traders don't lose because they lack information. They lose because they can't process it fast enough – and can't stay disciplined when they do. Grok Bot solves the first problem completely. RISK and COMPLIANCE quietly solve the second one, because a bot never moves a stop loss. And you write zero code. You describe each agent in plain English, tell it where to look, give it one job. Start with two: SCANNER and RISK. That alone is more process than 95% of retail traders have ever run. Not financial advice – this is a research desk, not a money printer. The bots find and organise. You decide. Bookmark this & read more in the article below ↓
0:24

ELON MUSK REPOSTED MY GROK BOT CONTENT SETUP. AND I STILL DON'T UNDERSTAND WHY NOBODY IS DOING THIS WITH TRADING YET. A WALL STREET RESEARCH DESK COSTS MILLIONS A YEAR TO STAFF – YOU CAN NOW RUN THE SAME THING WITH 9 GROK BOT AGENTS. Nine people used to do this job. Nine Grok Bot agents now do it while you sleep. Here's the entire desk: → MACRO – watches rates, CPI, FOMC. Tells you what kind of day it is before you open a single chart. → SCANNER – sweeps 9,000 tickers for one thing: your setup. Not "interesting stocks". Yours. → CATALYST – reads every 8-K, earnings call and wire the second it drops. Flags the two that matter. → QUANT – backtests the idea before you fall in love with it. Kills it if the edge isn't there. → CRYPTO – on-chain flows, funding, basis. The stuff nobody has the energy to check at 2am. → RISK – the one that actually saves you. Sizes the position, sets the stop, refuses the 4th trade. → EXECUTION – places the order, tracks the fill, reports the slippage in basis points. → COMPLIANCE – logs every single decision. So you can audit yourself instead of lying to yourself. → CHIEF OF STAFF – sits on top of all eight. Ranks their output and hands you one page every morning. Here's the part nobody says out loud: Retail traders don't lose because they lack information. They lose because they can't process it fast enough – and can't stay disciplined when they do. Grok Bot solves the first problem completely. RISK and COMPLIANCE quietly solve the second one, because a bot never moves a stop loss. And you write zero code. You describe each agent in plain English, tell it where to look, give it one job. Start with two: SCANNER and RISK. That alone is more process than 95% of retail traders have ever run. Not financial advice – this is a research desk, not a money printer. The bots find and organise. You decide. Bookmark this & read more in the article below ↓

SCOTTY BEAM

83,100 просмотров • 5 дней назад

EVERYTHING you NEED to know about Jack Dorsey's AI agent "Slack killer" Buzz (set up, use-cases etc in 38 mins) What we get into: 1. What Buzz actually is and should founders switch from Slack? 2. How to swap the model under any agent and keep all your context? 3. How to talk to your agents live with audio huddles? 4. How to get agents to build and deploy real apps for you, like a full CRM from one ask? 5. How to set up the context loop that feeds your live app data back to your agents? 6. How to share compute so a few people split one machine running a local model? 7. Who it's actually for right now, and what's still rough? Full breakdown on the pod The Startup Ideas Podcast (SIP) 🧃. Thanks to Vinny for jumping on and clearly explaining jack and team's latest product. My TLDR take is Buzz is a glimpse into the future of work. Some of you will roll your eyes at that, and I get it, it's alpha software and it's slow in places. But the core idea, that your context is the foundation and agents build out from there, is right, and that's worth seeing early. Watch Curious what you think
38:43

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

GREG ISENBERG

556,084 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

436,752 просмотров • 5 месяцев назад

We’ve been in private beta with a human + AI workspace similar to Buzz, with a few really important differences: (We previously built a company backed by Slack that sold to Atlassian, so we've been thinking about this problem for a while) - Agents reply by default unless you specifically flip to “team chat.” This feels 10x better than having to @ mention the agent every time. - It’s all in the cloud, with shared compute spread across a set of VMs. Way smoother onboarding, and yes, you can still connect your claude/codex subscriptions - You don’t create an army of agents. Number of agents is a vanity metric. Instead, you create shared computers, each one is a “space” where you define shared memory, connectors, skills, automations, etc. The Type agent pulls the appropriate context from the space where you have the conversation. - You can connect it to Slack to make it easy for your team to adopt and slowly move over rather than having to rip out Slack day 1. We’re working with a couple dozen forward thinking companies, who have told us “the whole team loves type”, “it’s the most used app on my computer”, and “type gives you superpowers” Here's a demo of how it works. Reply if you want to test it out!
5:09

We’ve been in private beta with a human + AI workspace similar to Buzz, with a few really important differences: (We previously built a company backed by Slack that sold to Atlassian, so we've been thinking about this problem for a while) - Agents reply by default unless you specifically flip to “team chat.” This feels 10x better than having to @ mention the agent every time. - It’s all in the cloud, with shared compute spread across a set of VMs. Way smoother onboarding, and yes, you can still connect your claude/codex subscriptions - You don’t create an army of agents. Number of agents is a vanity metric. Instead, you create shared computers, each one is a “space” where you define shared memory, connectors, skills, automations, etc. The Type agent pulls the appropriate context from the space where you have the conversation. - You can connect it to Slack to make it easy for your team to adopt and slowly move over rather than having to rip out Slack day 1. We’re working with a couple dozen forward thinking companies, who have told us “the whole team loves type”, “it’s the most used app on my computer”, and “type gives you superpowers” Here's a demo of how it works. Reply if you want to test it out!

Fletcher Richman

371,257 просмотров • 1 месяц назад

How to build a 1-person AI company that: - Runs locally - 100% open-source - No human employees, all agents - Real-time collaboration via email Multi-agent orchestration is not new. Plenty of frameworks already let agents hand off tasks, run in parallel, and talk to each other. So the interesting question is not whether agents can collaborate. It is what structure you use to make them collaborate. The common approach is to wire a graph of nodes and edges and reason about the plumbing yourself. It works, but you are learning a new abstraction just to describe who does what. There is a coordination structure we have trusted for a hundred years already: an organization. Every company runs the same way. People have roles, roles have reporting lines, and work moves up and down that chart without anyone relaying each message by hand. Map that onto agents and the whole thing gets intuitive. You lay out an org chart, each agent fills one role, you talk to the person at the top, and the org sorts out the work between them. You already know how a company works, so you already know how to run one here. There is no new abstraction to learn. That is exactly what Alook does. Each agent is a live Claude Code or OpenCode session with a defined role, a reporting line, and its own email inbox. The agents coordinate over email, the same way a team would. And it all runs locally through a runtime on your own machine, so nothing leaves your setup. You bring your own agent too. Claude Code and Codex both work, and if you would rather stay fully open source and local, OpenCode works the same way. To show how this feels in practice, I set up three agents as a small sales team. Vi is the one I talk to. I hand Vi a goal, and Vi routes the work down the chart. Neile runs prospect research. Vi passes the target criteria, and Neile reports back a ranked list of names, roles, and companies, each with a suggested angle and a confidence score. Lliane runs outreach. Vi hands over the messaging angle and follow-up cadence, and Lliane reports back on emails sent, responses received, and any deal that needs escalation. I never relay a message between them. Neile and Lliane report to Vi, and Vi updates me in one place. The whole thing is open source and self-hosted, so it runs on your machine with your own agents. Give the repo a star if you want to follow where it goes: I also wrote a full walkthrough on building your own AI company with it, from a blank org chart to a running job. The article is quoted below. Cheers! :)
0:39

How to build a 1-person AI company that: - Runs locally - 100% open-source - No human employees, all agents - Real-time collaboration via email Multi-agent orchestration is not new. Plenty of frameworks already let agents hand off tasks, run in parallel, and talk to each other. So the interesting question is not whether agents can collaborate. It is what structure you use to make them collaborate. The common approach is to wire a graph of nodes and edges and reason about the plumbing yourself. It works, but you are learning a new abstraction just to describe who does what. There is a coordination structure we have trusted for a hundred years already: an organization. Every company runs the same way. People have roles, roles have reporting lines, and work moves up and down that chart without anyone relaying each message by hand. Map that onto agents and the whole thing gets intuitive. You lay out an org chart, each agent fills one role, you talk to the person at the top, and the org sorts out the work between them. You already know how a company works, so you already know how to run one here. There is no new abstraction to learn. That is exactly what Alook does. Each agent is a live Claude Code or OpenCode session with a defined role, a reporting line, and its own email inbox. The agents coordinate over email, the same way a team would. And it all runs locally through a runtime on your own machine, so nothing leaves your setup. You bring your own agent too. Claude Code and Codex both work, and if you would rather stay fully open source and local, OpenCode works the same way. To show how this feels in practice, I set up three agents as a small sales team. Vi is the one I talk to. I hand Vi a goal, and Vi routes the work down the chart. Neile runs prospect research. Vi passes the target criteria, and Neile reports back a ranked list of names, roles, and companies, each with a suggested angle and a confidence score. Lliane runs outreach. Vi hands over the messaging angle and follow-up cadence, and Lliane reports back on emails sent, responses received, and any deal that needs escalation. I never relay a message between them. Neile and Lliane report to Vi, and Vi updates me in one place. The whole thing is open source and self-hosted, so it runs on your machine with your own agents. Give the repo a star if you want to follow where it goes: I also wrote a full walkthrough on building your own AI company with it, from a blank org chart to a running job. The article is quoted below. Cheers! :)

Akshay 🚀

169,957 просмотров • 1 месяц назад

THIS GUY CONNECTED HIS AI AGENTS TO HIS OBSIDIAN AND BUILT A BRAIN THAT LEARNS ON ITS OWN. HERE'S HOW TO BUILD IT Obsidian is just markdown files sitting in a folder. That turns out to be the perfect memory for an AI agent, because an agent can read and write those files directly. He wired his agents into the vault so they pull context from it, do the work, and write what they learned back. The notes aren't the point. The loop is, and it gets sharper every cycle How to build it: 1. Point an agent at your vault. The fastest way, no plugins, no API keys: open a terminal and run npx obsidian-mcp /path/to/your/vault. That exposes your Obsidian folder to Claude as a tool it can read, search, and write to. Add it to your Claude Code or Cowork config and restart 2. Confirm it can see the brain. Ask it: "list the notes in my vault and summarize what's in them." If it reads them back, the connection is live. Now it starts every task with everything the vault already holds instead of from zero 3. Give each agent one job and a write-back rule. Tell it: "research this, then save what you found as a new note in /brain with links to related notes." One agent researches, one summarizes, one plans. Each writes its output back into the vault 4. Close the loop. Add one line to every agent's instructions: "read /brain before starting, write your result back when done." Now each task leaves the vault richer, and the next run reads that before it works. It compounds instead of resetting 5. You only steer. Review what the brain produces, point it at the next thing. The agents handle the reading, writing, and connecting The edge isn't better notes. It's a brain that feeds itself, so the work gets sharper every cycle instead of starting over Bookmark this
0:24

THIS GUY CONNECTED HIS AI AGENTS TO HIS OBSIDIAN AND BUILT A BRAIN THAT LEARNS ON ITS OWN. HERE'S HOW TO BUILD IT Obsidian is just markdown files sitting in a folder. That turns out to be the perfect memory for an AI agent, because an agent can read and write those files directly. He wired his agents into the vault so they pull context from it, do the work, and write what they learned back. The notes aren't the point. The loop is, and it gets sharper every cycle How to build it: 1. Point an agent at your vault. The fastest way, no plugins, no API keys: open a terminal and run npx obsidian-mcp /path/to/your/vault. That exposes your Obsidian folder to Claude as a tool it can read, search, and write to. Add it to your Claude Code or Cowork config and restart 2. Confirm it can see the brain. Ask it: "list the notes in my vault and summarize what's in them." If it reads them back, the connection is live. Now it starts every task with everything the vault already holds instead of from zero 3. Give each agent one job and a write-back rule. Tell it: "research this, then save what you found as a new note in /brain with links to related notes." One agent researches, one summarizes, one plans. Each writes its output back into the vault 4. Close the loop. Add one line to every agent's instructions: "read /brain before starting, write your result back when done." Now each task leaves the vault richer, and the next run reads that before it works. It compounds instead of resetting 5. You only steer. Review what the brain produces, point it at the next thing. The agents handle the reading, writing, and connecting The edge isn't better notes. It's a brain that feeds itself, so the work gets sharper every cycle instead of starting over Bookmark this

Yarchi

58,186 просмотров • 2 месяцев назад