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Let's look inside the Grok Bot Brain. 26 AI agents. One core. Running right now. It captures what you'd lose. Connects what you'd forget. Surfaces it back exactly when you need it. A voice note becomes a task or an idea in 6 seconds, no filing - An idea...

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Aleiah

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19,304 просмотров • 5 дней назад •via X (Twitter)

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I BUILT GROK BOT SECOND BRAIN 26 agents, one core, running off a single rule my own memory never followed: capture everything, forget nothing, connect it before you even ask. A voice note on a coffee walk gets split into a task and an idea in under 6 seconds - the core already knows the difference between something you have to do and something you just thought of. An idea from three weeks ago gets linked to the one you just had, automatically, before you remember you'd had it the first time. That visual -the rotating profile, the 26 glowing lines firing out through the skull, each one labeled with the agent running it - isn't a rendered mockup. It's the actual runtime. Every line is a live agent doing its job in real time, right now, in your browser. This isn't a note app. Note apps hold what you give them. This is a nervous system for everything your brain was never built to hold onto in the first place. Full build - the 26 agents, how memory actually persists, what it costs to set one up for real - is in the article.
0:20

I BUILT GROK BOT SECOND BRAIN 26 agents, one core, running off a single rule my own memory never followed: capture everything, forget nothing, connect it before you even ask. A voice note on a coffee walk gets split into a task and an idea in under 6 seconds - the core already knows the difference between something you have to do and something you just thought of. An idea from three weeks ago gets linked to the one you just had, automatically, before you remember you'd had it the first time. That visual -the rotating profile, the 26 glowing lines firing out through the skull, each one labeled with the agent running it - isn't a rendered mockup. It's the actual runtime. Every line is a live agent doing its job in real time, right now, in your browser. This isn't a note app. Note apps hold what you give them. This is a nervous system for everything your brain was never built to hold onto in the first place. Full build - the 26 agents, how memory actually persists, what it costs to set one up for real - is in the article.

Aleiah

249,581 просмотров • 6 дней назад

A SpaceXAI engineer just released a free 30-min course on Grok Bot Agents: from your first persistent agent to multi-agent chains that research, ship software, and hand work off to Cursor 05:26 - what actually lives inside a Grok agent 08:49 - the 3 ways to run agents 12:04 - chaining multiple agents into one workflow 16:06 - turning X followers into structured research inside Notion 23:08 - handing coding work from Grok straight to Cursor Most people still treat Grok like a chat window. It answers, you copy, you move on. The shift happens when the agents stop waiting for you: one finds the information, one structures it in Notion, one turns it into working code, and they pass the work down the line on their own. Thirty minutes here beats assembling your setup one agent at a time.
28:21

A SpaceXAI engineer just released a free 30-min course on Grok Bot Agents: from your first persistent agent to multi-agent chains that research, ship software, and hand work off to Cursor 05:26 - what actually lives inside a Grok agent 08:49 - the 3 ways to run agents 12:04 - chaining multiple agents into one workflow 16:06 - turning X followers into structured research inside Notion 23:08 - handing coding work from Grok straight to Cursor Most people still treat Grok like a chat window. It answers, you copy, you move on. The shift happens when the agents stop waiting for you: one finds the information, one structures it in Notion, one turns it into working code, and they pass the work down the line on their own. Thirty minutes here beats assembling your setup one agent at a time.

Morlex

16,710 просмотров • 5 дней назад

Your ai agent is genuinely smart right up until it has to do something in the real world ask it to host a site, send an email, scrape a page, take a payment, and the magic stops. now you're the one doing the boring part: → hunting api keys → paying for subscriptions you'll use once → gluing integrations together → losing an afternoon to config files i gave my agent access to Zero instead and just described the job. it built and hosted a full ai tool marketplace, 120+ tools, live on a real url, and i configured nothing. no keys, no dashboards, no setup zero plugs agents into 14,000+ real services on demand. everything runs on pay-per-use microtransactions, so you pay for the one call you make, not a monthly plan you forget about what's the one task your agent still can't do on its own? that's exactly the gap this closes $5 free credit → #Ad
1:12

Your ai agent is genuinely smart right up until it has to do something in the real world ask it to host a site, send an email, scrape a page, take a payment, and the magic stops. now you're the one doing the boring part: → hunting api keys → paying for subscriptions you'll use once → gluing integrations together → losing an afternoon to config files i gave my agent access to Zero instead and just described the job. it built and hosted a full ai tool marketplace, 120+ tools, live on a real url, and i configured nothing. no keys, no dashboards, no setup zero plugs agents into 14,000+ real services on demand. everything runs on pay-per-use microtransactions, so you pay for the one call you make, not a monthly plan you forget about what's the one task your agent still can't do on its own? that's exactly the gap this closes $5 free credit → #Ad

Freya Lawson

80,316 просмотров • 1 месяц назад

Grok Bot Agents are the killers of AI race. Here's the layer nobody's talking about, the boundary that decides whether an always-on bot is a hire or an incident, and you write it once in a single message: > draw the line by reversibility, never by task size. Anything it can undo in under a minute it finishes alone and logs, everything else parks and waits for you > write the irreversible list out loud: sending to a person outside the company, moving money, committing to a price, publishing anything public, deleting anything that isn't obvious junk, agreeing to terms. a bot left to infer that list will infer it generously > never paste a credential into a conversation. hand off the login on its own browser so the bot ends up holding a session and not a secret, and you were present for the one sensitive moment > give it an explicit "when unsure" rule Because the gap between the two lists is where every real incident actually happens, not inside either list > shape you want at the end of a run: every reversible thing done, zero sent, zero published, two things parked. if that zero isn't a zero you never drew the line, you just hoped Sit with that, the model never moved, the logins never moved, the tools never moved - only the boundary between what it finishes and what it parks moved, and that's the entire difference between leaving it running overnight and babysitting it all day. Grok Bot just turned handing a cloud browser your real accounts into a single message. which means half the internet is about to give a bot its inbox, its drive and its calendar, and define its authority never. And the failure mode isn't the one everyone braces for. A wrong draft costs you nothing, you read it and delete it. What costs you is a confident, correct-looking, irreversible action taken at 3am, to a client, from your address, with your name on it, that nobody was awake to park. Charter and approval blocks ready to paste are in the article below ↓
0:20

Grok Bot Agents are the killers of AI race. Here's the layer nobody's talking about, the boundary that decides whether an always-on bot is a hire or an incident, and you write it once in a single message: > draw the line by reversibility, never by task size. Anything it can undo in under a minute it finishes alone and logs, everything else parks and waits for you > write the irreversible list out loud: sending to a person outside the company, moving money, committing to a price, publishing anything public, deleting anything that isn't obvious junk, agreeing to terms. a bot left to infer that list will infer it generously > never paste a credential into a conversation. hand off the login on its own browser so the bot ends up holding a session and not a secret, and you were present for the one sensitive moment > give it an explicit "when unsure" rule Because the gap between the two lists is where every real incident actually happens, not inside either list > shape you want at the end of a run: every reversible thing done, zero sent, zero published, two things parked. if that zero isn't a zero you never drew the line, you just hoped Sit with that, the model never moved, the logins never moved, the tools never moved - only the boundary between what it finishes and what it parks moved, and that's the entire difference between leaving it running overnight and babysitting it all day. Grok Bot just turned handing a cloud browser your real accounts into a single message. which means half the internet is about to give a bot its inbox, its drive and its calendar, and define its authority never. And the failure mode isn't the one everyone braces for. A wrong draft costs you nothing, you read it and delete it. What costs you is a confident, correct-looking, irreversible action taken at 3am, to a client, from your address, with your name on it, that nobody was awake to park. Charter and approval blocks ready to paste are in the article below ↓

Miraqle

12,086 просмотров • 15 дней назад

ANTHROPIC LEAKED 8 RULES THAT GIVE ONE ENGINEER 8X FROM A SINGLE CHANGE the engineers built it so nothing adds up - it multiplies, and that's the 8x task → split → verify → score → write back one queue means you wait for every step in turn - three workers together cost you the slowest one, not the sum of all. as long as you're the one reading the diff, the bottleneck is you, not the model. state is written at every step - a crash mid-run costs you one step, not the whole session. history gets compressed 25 times over - the next pass starts at 8k instead of 200k. nothing moves forward without a number - "it got better" isn't a result, and the breakage comes back when you're no longer watching. the eighth rule is the only one that writes back into CLAUDE.md - the agent records what it learned, and the next run doesn't start from zero. copy this into Claude Code today - and tomorrow you work like an engineer on $1.5M a year ↓
1:05

ANTHROPIC LEAKED 8 RULES THAT GIVE ONE ENGINEER 8X FROM A SINGLE CHANGE the engineers built it so nothing adds up - it multiplies, and that's the 8x task → split → verify → score → write back one queue means you wait for every step in turn - three workers together cost you the slowest one, not the sum of all. as long as you're the one reading the diff, the bottleneck is you, not the model. state is written at every step - a crash mid-run costs you one step, not the whole session. history gets compressed 25 times over - the next pass starts at 8k instead of 200k. nothing moves forward without a number - "it got better" isn't a result, and the breakage comes back when you're no longer watching. the eighth rule is the only one that writes back into CLAUDE.md - the agent records what it learned, and the next run doesn't start from zero. copy this into Claude Code today - and tomorrow you work like an engineer on $1.5M a year ↓

Noisy

37,058 просмотров • 25 дней назад

Grok Bot just got a LOT more interesting. Someone figured out how to run Claude Code, Codex, and Cursor inside Grok Bot with a surprisingly simple setup. The setup is basically: 1. Copy the `setup-grok-prompt` 2. Give it to your agent 3. Done. Four minutes. That changes the conversation completely. Because Grok Bot isn’t just sitting there answering questions anymore. You can start thinking about it as a layer that orchestrates other AI coding tools and agents while you stay focused on the outcome. And this is exactly the direction I’ve been exploring. I wrote a deep dive on how I built a Second Brain using Grok Bot that works 24×7, 365 days. Not another “here’s what Grok can do” article. It’s about turning Grok Bot into something that can remember, organize, execute, and keep working in the background. If you’re curious about what happens when you stop treating AI like a chatbot and start treating it like a digital worker… My article is a must-read.
0:48

Grok Bot just got a LOT more interesting. Someone figured out how to run Claude Code, Codex, and Cursor inside Grok Bot with a surprisingly simple setup. The setup is basically: 1. Copy the `setup-grok-prompt` 2. Give it to your agent 3. Done. Four minutes. That changes the conversation completely. Because Grok Bot isn’t just sitting there answering questions anymore. You can start thinking about it as a layer that orchestrates other AI coding tools and agents while you stay focused on the outcome. And this is exactly the direction I’ve been exploring. I wrote a deep dive on how I built a Second Brain using Grok Bot that works 24×7, 365 days. Not another “here’s what Grok can do” article. It’s about turning Grok Bot into something that can remember, organize, execute, and keep working in the background. If you’re curious about what happens when you stop treating AI like a chatbot and start treating it like a digital worker… My article is a must-read.

Kanika

87,178 просмотров • 7 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 • 21 дней назад

Elon Musk, absolute leader of the AI race with Grok Bot, and it's not a joke anymore. Ultimate guide on god-mode setup of Grok Bot, the org chart that runs while you sleep, step by step: A Chief of Staff sits in the middle with no tools of its own, BUT it reads the outcome you gave it, picks who does what, and never does the work itself. That one rule is why it never turns into the bottleneck you hired it to remove. → Researcher pulls real sources and tracks what's actually moving, not what sounds true → Writer turns that into finished copy while the research is still in the room → Visualiser gets three reference visuals once, then ships everything in that style forever → Analyst reads what performed and tells the rest of the team what to stop doing → Scheduler owns timing and holds the queue → Publisher actually ships What makes it different from every AI tool you've used: each bot gets its own computer in the cloud, its own browser, its own files, and they all share one memory. So the research is already sitting inside the draft before the draft starts. Nothing gets copy-pasted between tabs, nothing waits on you to approve step four of nine. And you never write a workflow for it. You hit record, do the job once the way you actually do it, stop. It pulls out the steps, saves them as a skill, and puts it on a schedule. The shape you're aiming for on every bot: everything reversible finished, nothing sent. 36 drafts queued, 0 published. It does all the work and stops dead at the one line only you can cross. You stop prompting. You start assigning. Full charter blocks, the approval line and the routines are in the article below ↓
0:24

Elon Musk, absolute leader of the AI race with Grok Bot, and it's not a joke anymore. Ultimate guide on god-mode setup of Grok Bot, the org chart that runs while you sleep, step by step: A Chief of Staff sits in the middle with no tools of its own, BUT it reads the outcome you gave it, picks who does what, and never does the work itself. That one rule is why it never turns into the bottleneck you hired it to remove. → Researcher pulls real sources and tracks what's actually moving, not what sounds true → Writer turns that into finished copy while the research is still in the room → Visualiser gets three reference visuals once, then ships everything in that style forever → Analyst reads what performed and tells the rest of the team what to stop doing → Scheduler owns timing and holds the queue → Publisher actually ships What makes it different from every AI tool you've used: each bot gets its own computer in the cloud, its own browser, its own files, and they all share one memory. So the research is already sitting inside the draft before the draft starts. Nothing gets copy-pasted between tabs, nothing waits on you to approve step four of nine. And you never write a workflow for it. You hit record, do the job once the way you actually do it, stop. It pulls out the steps, saves them as a skill, and puts it on a schedule. The shape you're aiming for on every bot: everything reversible finished, nothing sent. 36 drafts queued, 0 published. It does all the work and stops dead at the one line only you can cross. You stop prompting. You start assigning. Full charter blocks, the approval line and the routines are in the article below ↓

Miraqle

86,736 просмотров • 14 дней назад

A screen recording is the best context you can give an AI agent. It's also the worst. A few seconds of video is thousands of images. Feed that to an agent and you instantly blow up its memory. So I built a tool that fixes it. How it works: Hit record and just do your thing. Click around, type, and talk out loud about what you're doing. While you record, it quietly captures the stuff that actually matters: your voice transcription, every click and the exact thing you clicked, what you typed, and the shortcuts you press. When you stop, it doesn't hand the agent the whole video. It writes a short, readable summary: a timeline of what you said and did. The agent reads that tiny summary first. Then, only when it needs to actually see a moment, it pulls that one exact frame from the video, like flipping to a single page instead of reading the whole book. The result: the agent understands everything you did! Full context. Less tokens.
1:54

A screen recording is the best context you can give an AI agent. It's also the worst. A few seconds of video is thousands of images. Feed that to an agent and you instantly blow up its memory. So I built a tool that fixes it. How it works: Hit record and just do your thing. Click around, type, and talk out loud about what you're doing. While you record, it quietly captures the stuff that actually matters: your voice transcription, every click and the exact thing you clicked, what you typed, and the shortcuts you press. When you stop, it doesn't hand the agent the whole video. It writes a short, readable summary: a timeline of what you said and did. The agent reads that tiny summary first. Then, only when it needs to actually see a moment, it pulls that one exact frame from the video, like flipping to a single page instead of reading the whole book. The result: the agent understands everything you did! Full context. Less tokens.

Milind S

12,409 просмотров • 2 месяцев 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

Asked a friend how to turn my life around and he sent me this; "rule numero uno: There are no more zero days. What's a zero day? A zero day is when you don't do a single thing towards whatever dream or goal or want or whatever that you got going on. No more zeros. I'm not saying you gotta bust an essay out everyday, that's not the point. The point I'm trying to make is that you have to make yourself, promise yourself, that the new SYSTEM you live in is a NON-ZERO system. Didnt' do anything all day and it's 11:58 PM? Write one sentence. One pushup. Read one page of that chapter. One. Because one is non zero. You feel me? When you're in the super vortex of being bummed your pattern of behaviour is keeping the vortex goin, that's what you're used to. Turning into productivity ultimate master of the universe doesn't happen from the vortex. It happens from a massive string of CONSISTENT NON ZEROS. That's rule number one. Do not forget." ngl it really resonated with me
0:34

Asked a friend how to turn my life around and he sent me this; "rule numero uno: There are no more zero days. What's a zero day? A zero day is when you don't do a single thing towards whatever dream or goal or want or whatever that you got going on. No more zeros. I'm not saying you gotta bust an essay out everyday, that's not the point. The point I'm trying to make is that you have to make yourself, promise yourself, that the new SYSTEM you live in is a NON-ZERO system. Didnt' do anything all day and it's 11:58 PM? Write one sentence. One pushup. Read one page of that chapter. One. Because one is non zero. You feel me? When you're in the super vortex of being bummed your pattern of behaviour is keeping the vortex goin, that's what you're used to. Turning into productivity ultimate master of the universe doesn't happen from the vortex. It happens from a massive string of CONSISTENT NON ZEROS. That's rule number one. Do not forget." ngl it really resonated with me

daz

242,585 просмотров • 6 месяцев назад

This is literally the easiest way to build an AI agent. Zero code. You only need to run a couple of commands. (I've said this before, but Google ADK is my favorite way to build code-first agents.) Here is what you need to do: 1. Open your terminal and create an empty folder 2. Run `uv init` inside the folder (if you don't have uv installed, you are really missing out!) 3. Install the google-adk library using the following command: `uv add google-adk`. 4. At this point, you can use the ask to create your agent with a single command: `uv run adk create --type=config my_agent`. This will ask you a couple of questions, including your GEMINI_API_KEY (you can create one online). 5. The command above will create a my_agent/root_agent.yaml file. Open it and add the following two lines at the end of the file so your agent can use Google to search for stuff: tools: - name: google_search 6. You have everything you need now. Run the adk web interface and start playing with your agent: `uv run adk web` That's it! Literally zero code. The agent works off the YAML configuration file.
1:33

This is literally the easiest way to build an AI agent. Zero code. You only need to run a couple of commands. (I've said this before, but Google ADK is my favorite way to build code-first agents.) Here is what you need to do: 1. Open your terminal and create an empty folder 2. Run `uv init` inside the folder (if you don't have uv installed, you are really missing out!) 3. Install the google-adk library using the following command: `uv add google-adk`. 4. At this point, you can use the ask to create your agent with a single command: `uv run adk create --type=config my_agent`. This will ask you a couple of questions, including your GEMINI_API_KEY (you can create one online). 5. The command above will create a my_agent/root_agent.yaml file. Open it and add the following two lines at the end of the file so your agent can use Google to search for stuff: tools: - name: google_search 6. You have everything you need now. Run the adk web interface and start playing with your agent: `uv run adk web` That's it! Literally zero code. The agent works off the YAML configuration file.

Santiago

140,922 просмотров • 9 месяцев назад

your ai agent tested 1,262 trading strategies overnight. by morning it had forgotten every one of them. so tonight it tests some of them again. next week, again. everything it learned is sitting in a log file that nothing reads. every run starts on the same blank page. that's why it keeps handing you the idea that already died in a crash, with a new name on it, and you pay to find out twice. ai agent already does everything a fund does. finds the idea, writes the code, tests it against years of history, puts it live, reads what went wrong afterwards. all of it runs tonight for nothing. the one thing it can't do is remember. what got tried, what failed, in which market. nobody has built that part yet. that's the whole gap. not better models. a notebook. whoever builds it first gets a system that improves every week without them touching it. read the article below and save it. it's the full guide to how an ai trading agent is built, and how to make it remember every strategy it has already tested.
0:44

your ai agent tested 1,262 trading strategies overnight. by morning it had forgotten every one of them. so tonight it tests some of them again. next week, again. everything it learned is sitting in a log file that nothing reads. every run starts on the same blank page. that's why it keeps handing you the idea that already died in a crash, with a new name on it, and you pay to find out twice. ai agent already does everything a fund does. finds the idea, writes the code, tests it against years of history, puts it live, reads what went wrong afterwards. all of it runs tonight for nothing. the one thing it can't do is remember. what got tried, what failed, in which market. nobody has built that part yet. that's the whole gap. not better models. a notebook. whoever builds it first gets a system that improves every week without them touching it. read the article below and save it. it's the full guide to how an ai trading agent is built, and how to make it remember every strategy it has already tested.

cvxv666

48,626 просмотров • 19 дней назад

A one-man trading hedge fund now costs about $100 a month in AI subscriptions. Five PhDs on a Citadel desk cost $270,000 a month, and that is the cheap end. That buys one tested idea a month. Man Group's AI writes hundreds of new signals a week, on a floor where the humans used to manage twenty in a quarter. Fifty AI agents do the reading and the writing. One of them exists only to destroy what the others build, and that one is the reason any of it works. Every job on that payroll is now an agent you can run yourself: > AI research agents reading filings, transcripts, options flow and on-chain data overnight, fifty personas at once, none of them allowed to see what the crowd is pricing > coding agent that turns one sentence of plain English into entry rules, exit rules, sizing and risk limits, then debugs itself until it runs > backtest agent that replays five years of that idea in about 12 seconds > breaker agent, an AI whose only job is killing the thing, at double the trading costs and in the ten worst markets that asset has ever seen > critic agent that reads your journal and names the mistake you keep making Nobody on that list asks for a bonus in January. $200 million is already run this way on one platform where 52,000 people mostly sit and watch the machine work. The full map of what is built and what is missing is in the article below. Bookmark & read it If you're not yet using AI in your trading and investing.
0:41

A one-man trading hedge fund now costs about $100 a month in AI subscriptions. Five PhDs on a Citadel desk cost $270,000 a month, and that is the cheap end. That buys one tested idea a month. Man Group's AI writes hundreds of new signals a week, on a floor where the humans used to manage twenty in a quarter. Fifty AI agents do the reading and the writing. One of them exists only to destroy what the others build, and that one is the reason any of it works. Every job on that payroll is now an agent you can run yourself: > AI research agents reading filings, transcripts, options flow and on-chain data overnight, fifty personas at once, none of them allowed to see what the crowd is pricing > coding agent that turns one sentence of plain English into entry rules, exit rules, sizing and risk limits, then debugs itself until it runs > backtest agent that replays five years of that idea in about 12 seconds > breaker agent, an AI whose only job is killing the thing, at double the trading costs and in the ten worst markets that asset has ever seen > critic agent that reads your journal and names the mistake you keep making Nobody on that list asks for a bonus in January. $200 million is already run this way on one platform where 52,000 people mostly sit and watch the machine work. The full map of what is built and what is missing is in the article below. Bookmark & read it If you're not yet using AI in your trading and investing.

cvxv666

172,849 просмотров • 22 дней назад

I'M SHOCKED – ALMOST NOBODY IS USING GROK BOT THE RIGHT WAY. A LEAD ENGINEER AT SPACEX AI JUST DROPPED A 1-HOUR COURSE ON HOW IT'S ACTUALLY DONE. HERE'S ALL OF IT IN 60 SECONDS. The mistake almost everyone makes: they hand Grok Bot random one-off tasks. That's it. That's the whole reason it still feels like a chatbot to you. Here's the system he teaches instead – five parts: → ROLE – stop assigning tasks, create permanent roles. Chief of Staff, Inbox Manager, Researcher, Developer, Reviewer. A bot with a job title beats a bot with a to-do list → TOOLS – connect each bot to what it actually needs: Gmail, Slack, Calendar, Notion, GitHub. It does the work on its own persistent cloud computer → SKILL – teach it your workflow. Write the instructions, or just record yourself doing the job once – Grok Bot turns that demonstration into a reusable skill → ROUTINE – anything you repeat becomes a routine. It runs on a schedule or fires off an event, with your laptop closed → TEAM – group the bots together. The lead bot delegates, the specialists work in parallel, and you set approval rules before anything sends an email, moves a calendar or pushes code The one honest catch: a new bot still needs context and some hand-holding on its first few runs. But that's the entire system. Role → Tools → Skill → Routine → Team. Everyone else is still typing one-off prompts into Grok Bot and wondering why nothing compounds. Bookmark this & read the full breakdown in the article below ↓
0:20

I'M SHOCKED – ALMOST NOBODY IS USING GROK BOT THE RIGHT WAY. A LEAD ENGINEER AT SPACEX AI JUST DROPPED A 1-HOUR COURSE ON HOW IT'S ACTUALLY DONE. HERE'S ALL OF IT IN 60 SECONDS. The mistake almost everyone makes: they hand Grok Bot random one-off tasks. That's it. That's the whole reason it still feels like a chatbot to you. Here's the system he teaches instead – five parts: → ROLE – stop assigning tasks, create permanent roles. Chief of Staff, Inbox Manager, Researcher, Developer, Reviewer. A bot with a job title beats a bot with a to-do list → TOOLS – connect each bot to what it actually needs: Gmail, Slack, Calendar, Notion, GitHub. It does the work on its own persistent cloud computer → SKILL – teach it your workflow. Write the instructions, or just record yourself doing the job once – Grok Bot turns that demonstration into a reusable skill → ROUTINE – anything you repeat becomes a routine. It runs on a schedule or fires off an event, with your laptop closed → TEAM – group the bots together. The lead bot delegates, the specialists work in parallel, and you set approval rules before anything sends an email, moves a calendar or pushes code The one honest catch: a new bot still needs context and some hand-holding on its first few runs. But that's the entire system. Role → Tools → Skill → Routine → Team. Everyone else is still typing one-off prompts into Grok Bot and wondering why nothing compounds. Bookmark this & read the full breakdown in the article below ↓

SCOTTY BEAM

91,244 просмотров • 11 дней назад

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 agents run on a shared cloud computer, so running your newsletter, your X, and your receipts all in one place creates context bloat and burns tokens fast. One mission per setup. 2. Start with a Chief of Staff. Give it access to your existing docs (Notion, Slack, Gmail), have it audit the business, then tell you the top three agents to build first to drive revenue. 3. Perfect a task with the Chief of Staff before spinning up a new agent. Have it do the outbound sales once, review it, and only then say "now build a bot that does exactly that." You earn each new hire by proving the task works first. 4. Constraints are the feature. You get a limited number of agents, one thread per bot, like DMs with a teammate. It forces you to stay mission-oriented instead of spinning up a bot for every random idea. 5. You make the decisions, not the agent. Billy's team spent three weeks unable to pick where content should live. At some point you say "we're doing Notion, no more tinkering" and move on. 6. Run week one with no new agents. Build the team, learn to fly the plane, just execute. Week three is when you find the real gaps and expand, someone to man the inbox, someone for the Shopify shop. 7. Then add routines so it works while you sleep. Ask your Chief of Staff what recurring jobs would move the business forward overnight, and it builds the automations that run without you. Thanks to Billy Howell for sharing the sauce on The Startup Ideas Podcast (SIP) 🧃 (follow for more). Grokbot is really cool. Watch below:
44:20

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 agents run on a shared cloud computer, so running your newsletter, your X, and your receipts all in one place creates context bloat and burns tokens fast. One mission per setup. 2. Start with a Chief of Staff. Give it access to your existing docs (Notion, Slack, Gmail), have it audit the business, then tell you the top three agents to build first to drive revenue. 3. Perfect a task with the Chief of Staff before spinning up a new agent. Have it do the outbound sales once, review it, and only then say "now build a bot that does exactly that." You earn each new hire by proving the task works first. 4. Constraints are the feature. You get a limited number of agents, one thread per bot, like DMs with a teammate. It forces you to stay mission-oriented instead of spinning up a bot for every random idea. 5. You make the decisions, not the agent. Billy's team spent three weeks unable to pick where content should live. At some point you say "we're doing Notion, no more tinkering" and move on. 6. Run week one with no new agents. Build the team, learn to fly the plane, just execute. Week three is when you find the real gaps and expand, someone to man the inbox, someone for the Shopify shop. 7. Then add routines so it works while you sleep. Ask your Chief of Staff what recurring jobs would move the business forward overnight, and it builds the automations that run without you. Thanks to Billy Howell for sharing the sauce on The Startup Ideas Podcast (SIP) 🧃 (follow for more). Grokbot is really cool. Watch below:

GREG ISENBERG

4,011,512 просмотров • 12 дней назад

Cursor now costs ₹649 a month in India, and you can pay with UPI. They just launched their Start Plan. That's the whole price, tax included. Nothing to convert, nothing to work out in your head at checkout. I've been on Grok 4.6. It's quick, and it's been getting the code right more than I thought it would. Composer is on the plan as well, if you are into that. You can also start a job on your laptop and then check on it from your phone while you're commuting, and continue working on it when you get home. You just say what you want and it builds it. 👉 This one is India only. Visit their website to learn more:
1:37

Cursor now costs ₹649 a month in India, and you can pay with UPI. They just launched their Start Plan. That's the whole price, tax included. Nothing to convert, nothing to work out in your head at checkout. I've been on Grok 4.6. It's quick, and it's been getting the code right more than I thought it would. Composer is on the plan as well, if you are into that. You can also start a job on your laptop and then check on it from your phone while you're commuting, and continue working on it when you get home. You just say what you want and it builds it. 👉 This one is India only. Visit their website to learn more:

Kunal Kushwaha

13,758 просмотров • 10 дней назад

If you can think it, you can make it. That used to be a cliché. Now it's literally how video editing works. A year ago, making motion graphics meant learning After Effects, spending hours on keyframes, or hiring a designer. Today, you describe what you want in one sentence and it appears on your timeline. They're code-based, fully editable, exportable with transparency. You can tweak every parameter by hand or ask the agent to build you a custom control panel for the exact thing you want to adjust. The barrier to creating professional video content has disappeared. You don't need a specialized degree. You don't need expensive software. You need an idea. This is what we're building at ChatCut. Full demo 👇
1:28

If you can think it, you can make it. That used to be a cliché. Now it's literally how video editing works. A year ago, making motion graphics meant learning After Effects, spending hours on keyframes, or hiring a designer. Today, you describe what you want in one sentence and it appears on your timeline. They're code-based, fully editable, exportable with transparency. You can tweak every parameter by hand or ask the agent to build you a custom control panel for the exact thing you want to adjust. The barrier to creating professional video content has disappeared. You don't need a specialized degree. You don't need expensive software. You need an idea. This is what we're building at ChatCut. Full demo 👇

ChatCut

218,838 просмотров • 4 месяцев назад

Andrej Karpathy said: "There's room for an incredible new product in the second brain space" This might be it. (bookmark it) Everyone is suddenly building a second brain. Karpathy's LLM wiki pattern went viral, and half of X is now hand-wiring Obsidian to Claude Code so an agent maintains their notes for them. The idea is beautiful: stop making your AI re-read raw notes on every question. Let it build a wiki that compounds. As Karpathy put it, "LLMs don't get bored, they don't forget to update a cross-reference (backlinks), and can touch 15 files in one pass." But if you start doing it manually, it becomes a project in itself. You wire up the vault, the agents, the schedules, the integrations, and then you babysit all of it. So I sat down with Arjun, who actually built the open source version of this, and we broke down what it looks like when the whole thing already works out of the box. It just crossed 15K stars on GitHub. Think Claude's desktop app, open source, with two things layered on top: → A work brain: background agents index your emails, meetings, and notes into a living knowledge graph that updates itself as you work. → Work surfaces: chat is not the best interface for real work, so you get an email client, a meeting note taker, a browser, and a code mode where you and the AI actually collaborate. The part that got me: a customer email comes in asking for a product change, a background agent triages it, spins up Claude Code in its own worktree, and the feature is written before you are back at your desk. Bring your existing Obsidian vault, connect Slack, X, and Fireflies, and let it run your day. Here's the full breakdown of what we covered in this session: Enjoy! 00:00 Intro 01:08 What is Roboat (an open source AI co-worker) 02:42 The second brain (a knowledge graph of your work) 04:01 Bringing your existing Obsidian vault in 04:46 Work surfaces 05:29 Meetings and automatic note taking 06:53 Connecting Slack, X and other sources 07:55 Background agents that run your day 09:24 Code mode (Claude Code and Codex) 10:18 Demo: from an email to written code 14:28 Guardrails: approvals and agent workspaces 17:15 Scheduling agents on a cron 18:52 The browser work surface (browser use) 20:42 Wrapping up: automating your whole day 22:44 Outro Checkout Rowboat's GitHub repo: (don't forget to star 🌟) My co-founder recently wrote a great article on the same idea, and I highly recommend reading it as well. The article is quoted below. Here's my session with Arjun:
22:53

Andrej Karpathy said: "There's room for an incredible new product in the second brain space" This might be it. (bookmark it) Everyone is suddenly building a second brain. Karpathy's LLM wiki pattern went viral, and half of X is now hand-wiring Obsidian to Claude Code so an agent maintains their notes for them. The idea is beautiful: stop making your AI re-read raw notes on every question. Let it build a wiki that compounds. As Karpathy put it, "LLMs don't get bored, they don't forget to update a cross-reference (backlinks), and can touch 15 files in one pass." But if you start doing it manually, it becomes a project in itself. You wire up the vault, the agents, the schedules, the integrations, and then you babysit all of it. So I sat down with Arjun, who actually built the open source version of this, and we broke down what it looks like when the whole thing already works out of the box. It just crossed 15K stars on GitHub. Think Claude's desktop app, open source, with two things layered on top: → A work brain: background agents index your emails, meetings, and notes into a living knowledge graph that updates itself as you work. → Work surfaces: chat is not the best interface for real work, so you get an email client, a meeting note taker, a browser, and a code mode where you and the AI actually collaborate. The part that got me: a customer email comes in asking for a product change, a background agent triages it, spins up Claude Code in its own worktree, and the feature is written before you are back at your desk. Bring your existing Obsidian vault, connect Slack, X, and Fireflies, and let it run your day. Here's the full breakdown of what we covered in this session: Enjoy! 00:00 Intro 01:08 What is Roboat (an open source AI co-worker) 02:42 The second brain (a knowledge graph of your work) 04:01 Bringing your existing Obsidian vault in 04:46 Work surfaces 05:29 Meetings and automatic note taking 06:53 Connecting Slack, X and other sources 07:55 Background agents that run your day 09:24 Code mode (Claude Code and Codex) 10:18 Demo: from an email to written code 14:28 Guardrails: approvals and agent workspaces 17:15 Scheduling agents on a cron 18:52 The browser work surface (browser use) 20:42 Wrapping up: automating your whole day 22:44 Outro Checkout Rowboat's GitHub repo: (don't forget to star 🌟) My co-founder recently wrote a great article on the same idea, and I highly recommend reading it as well. The article is quoted below. Here's my session with Arjun:

Akshay 🚀

45,815 просмотров • 1 месяц назад

SOMEONE BUILT AN ENTIRE COMPANY BRAIN INSIDE CLAUDE CODE IN 7 DAYS Not Obsidian. Fully custom. A living map of every employee, every agent, every SOP on one screen. Click any node and it opens up: - what department it's in - what SOPs are attached - what it can actually access that permission layer is the whole game an employee opens the chat and the AI already knows their access level, agents, SOPs and tools surface in the conversation like you tagged them by hand Obsidian cannot do this... no dev team. no six month build. no enterprise budget. just Claude Code and one week has everything to build one full guide on building your own team below
1:20

SOMEONE BUILT AN ENTIRE COMPANY BRAIN INSIDE CLAUDE CODE IN 7 DAYS Not Obsidian. Fully custom. A living map of every employee, every agent, every SOP on one screen. Click any node and it opens up: - what department it's in - what SOPs are attached - what it can actually access that permission layer is the whole game an employee opens the chat and the AI already knows their access level, agents, SOPs and tools surface in the conversation like you tagged them by hand Obsidian cannot do this... no dev team. no six month build. no enterprise budget. just Claude Code and one week has everything to build one full guide on building your own team below

Madni Aghadi

397,151 просмотров • 2 месяцев назад