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I still can't wrap my head around why not everyone is using this approach yet. Elon Musk already reposted this guide, and this exact agent setup earned me $7,100 in net profit for the month Grok Bot + Pumpfun + Robinhood Week 1 + $1,210 Week 2 + $2,560...

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Bober_smart

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51,023 views • 3 days ago •via X (Twitter)

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I still can't wrap my head around why not everyone is using this approach yet. Elon Musk reposted this guide, and using this exact agent setup, I managed to make $7,250 just last week Eight Grok agents on the desktop cost $200 a month, but they replace a full trading floor, the maintenance of which typically costs a crypto fund $550,000 a year in analyst salaries A 5:30AM morning call. I don't participate in it How the agents are distributed: SEARCH: gathers real-time alpha, developer repositories on GitHub, and unindexed Telegram signals before CT finds them RISK: checks contract functions, minting rights, and LP locks, flagging honeypots before entry SNIPER: places high-speed orders on-chain at the exact millisecond the risk clearance passes WHALE: tracks smart money wallets and flags insider accumulation in real time RUG: monitors developer wallet activity 24/7 and dumps the entire position if they touch the LP EXIT: dynamically trails stops, scaling out as liquidity accumulates SHILL: tracks social volume, impulse speed, and key influencer calls HEAD OF DESK: never trades, routes data, checks transmissions, and brings me the single decision that requires a human. While I was sleeping, the system scanned 143 tokens, selected 15 qualifying setups, and executed 8 trades. The result: net profit of $7,250 (already after fees). Each agent has its own virtual browser, terminal, and local cloud memory, and the trading floor remains active even when my laptop is closed Setup is easier than it seems: 1. Download Grok Bot and create your Head of Desk 2. Give the remaining 7 agents task descriptions as if you were instructing new employees 3. Run the workflow once on your screen while they observe 4. Connect Telegram and wallet webhooks No VPS, no code, no waiting for developers. Crypto trading used to mean 16 hours in front of a screen, paid alpha groups, and constant fatigue. Mine took one evening to set up Save this guide before your next trade
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I still can't wrap my head around why not everyone is using this approach yet. Elon Musk reposted this guide, and using this exact agent setup, I managed to make $7,250 just last week Eight Grok agents on the desktop cost $200 a month, but they replace a full trading floor, the maintenance of which typically costs a crypto fund $550,000 a year in analyst salaries A 5:30AM morning call. I don't participate in it How the agents are distributed: SEARCH: gathers real-time alpha, developer repositories on GitHub, and unindexed Telegram signals before CT finds them RISK: checks contract functions, minting rights, and LP locks, flagging honeypots before entry SNIPER: places high-speed orders on-chain at the exact millisecond the risk clearance passes WHALE: tracks smart money wallets and flags insider accumulation in real time RUG: monitors developer wallet activity 24/7 and dumps the entire position if they touch the LP EXIT: dynamically trails stops, scaling out as liquidity accumulates SHILL: tracks social volume, impulse speed, and key influencer calls HEAD OF DESK: never trades, routes data, checks transmissions, and brings me the single decision that requires a human. While I was sleeping, the system scanned 143 tokens, selected 15 qualifying setups, and executed 8 trades. The result: net profit of $7,250 (already after fees). Each agent has its own virtual browser, terminal, and local cloud memory, and the trading floor remains active even when my laptop is closed Setup is easier than it seems: 1. Download Grok Bot and create your Head of Desk 2. Give the remaining 7 agents task descriptions as if you were instructing new employees 3. Run the workflow once on your screen while they observe 4. Connect Telegram and wallet webhooks No VPS, no code, no waiting for developers. Crypto trading used to mean 16 hours in front of a screen, paid alpha groups, and constant fatigue. Mine took one evening to set up Save this guide before your next trade

Bober_smart

55,240 views • 5 days ago

I still don't understand why everyone isn't doing this yet. Elon Musk reposted this guide, and using this exact agent setup, I made $9,300 just last week Eight Grok agents on the desk, costing $200 a month, service a trading floor that typically costs a crypto fund $500,000 a year in analyst salaries A 5 AM morning call. I don't participate in it How the agents are distributed: SEARCH: gathers real-time alpha, developer repositories on GitHub, and unindexed Telegram signals before CT finds them RISK: checks contract functions, minting rights, and LP locks, flagging honeypots before entry SNIPER: places high-speed orders on-chain at the exact millisecond the risk clearance passes WHALE: tracks smart money wallets and flags insider accumulation in real time. RUG: monitors developer wallet activity 24/7 and dumps the entire position if they touch the LP EXIT: dynamically trails stops, scaling out as liquidity accumulates SHILL: tracks social volume, impulse speed, and key influencer calls HEAD OF DESK: never trades, routes data, checks transmissions, and brings me the single decision that requires a human While I was sleeping, the system scanned 164 tokens, selected 21 qualifying setups, and executed 8 trades. The result: net profit of $9,300 (already after fees) Each agent has its own virtual browser, terminal, and local cloud memory. The trading floor remains active even when my laptop is closed Setup is easier than it seems: 1. Download Grok Bot and create your Head of Desk 2. Give the remaining 7 agents task descriptions as if you were instructing new employees 3. Run the workflow once on your screen while they observe 4. Connect Telegram and wallet webhooks No VPS, no code, no waiting for developers Crypto trading used to mean 16 hours in front of a screen, paid alpha groups, and constant fatigue. Mine took one evening to set up Save this before your next trade. Save the guide
0:20

I still don't understand why everyone isn't doing this yet. Elon Musk reposted this guide, and using this exact agent setup, I made $9,300 just last week Eight Grok agents on the desk, costing $200 a month, service a trading floor that typically costs a crypto fund $500,000 a year in analyst salaries A 5 AM morning call. I don't participate in it How the agents are distributed: SEARCH: gathers real-time alpha, developer repositories on GitHub, and unindexed Telegram signals before CT finds them RISK: checks contract functions, minting rights, and LP locks, flagging honeypots before entry SNIPER: places high-speed orders on-chain at the exact millisecond the risk clearance passes WHALE: tracks smart money wallets and flags insider accumulation in real time. RUG: monitors developer wallet activity 24/7 and dumps the entire position if they touch the LP EXIT: dynamically trails stops, scaling out as liquidity accumulates SHILL: tracks social volume, impulse speed, and key influencer calls HEAD OF DESK: never trades, routes data, checks transmissions, and brings me the single decision that requires a human While I was sleeping, the system scanned 164 tokens, selected 21 qualifying setups, and executed 8 trades. The result: net profit of $9,300 (already after fees) Each agent has its own virtual browser, terminal, and local cloud memory. The trading floor remains active even when my laptop is closed Setup is easier than it seems: 1. Download Grok Bot and create your Head of Desk 2. Give the remaining 7 agents task descriptions as if you were instructing new employees 3. Run the workflow once on your screen while they observe 4. Connect Telegram and wallet webhooks No VPS, no code, no waiting for developers Crypto trading used to mean 16 hours in front of a screen, paid alpha groups, and constant fatigue. Mine took one evening to set up Save this before your next trade. Save the guide

Bober_smart

347,418 views • 7 days ago

launched a drone swarm where each drone is a Grok agent, and 8 days later, my profit reached $8,765 I delegated the management of the trading terminal to an autonomous structure consisting of 8 core Grok agents and 54 auxiliary drone agents. The latter constantly scan the network, gather raw data, and instantly redirect it to the main 8 While the morning sync meeting takes place at 6 AM, which I don't even attend, the system is already hard at work Hierarchy and responsibilities of the key agents: HEAD OF DESK: The brain of the operation. Never makes trades himself, but filters data streams, checks transmission quality, and issues a final verdict requiring manual approval SEARCH: Hunts for actual alpha, studies fresh commits in GitHub repositories, and tracks hidden Telegram signals before anyone else notices them RISK: Conducts smart contract audits, checks minting functions and liquidity pool (LP) lock functions, filtering out scams and honeypots even before entry SNIPER: Responsible for execution (instantly sends high-speed on-chain orders at the exact millisecond the risk check is completed) WHALE: Hunts "smart money" wallets, tracking large insider purchases in real-time RUG: Monitors developer activity around the clock and instantly dumps assets if they try to pull liquidity (LP) EXIT: Manages the dynamic trailing stop, withdrawing capital step-by-step as market liquidity grows SHILL: Analyzes social noise, impulse intensity, and key calls from top influencers All of this huge routine work of collecting information and delivering it to the core agents is provided by those very 54 drone agents operating in the background While I was sleeping, the autonomous complex managed to analyze 187 tokens, selected the 27 most promising configurations, and closed 8 successful trades. The net profit was $8,765 Each agent operates in an isolated environment: it has its own virtual browser, terminal, and local cloud memory. The trading floor operates 24/7, even when my laptop is completely turned off How to deploy such a system in one evening: 1. Launch the Grok Bot and set up the main agent (Head of Desk) 2. Distribute roles among the other 7 agents, writing out tasks for them in plain human language, as if you were hiring live interns 3. Run the starting workflow on your screen, allowing them to adopt the algorithm of actions 4. Integrate alerts into Telegram and connect wallets via webhooks No complicated VPS setups, writing lines of code, or tedious waiting for developers. Forget about 16 hours in front of the monitor, buying expensive private chats, and burnout (it took me just one evening to fully automate the process) Add this to your bookmarks, you will need these settings before your next trade
0:20

launched a drone swarm where each drone is a Grok agent, and 8 days later, my profit reached $8,765 I delegated the management of the trading terminal to an autonomous structure consisting of 8 core Grok agents and 54 auxiliary drone agents. The latter constantly scan the network, gather raw data, and instantly redirect it to the main 8 While the morning sync meeting takes place at 6 AM, which I don't even attend, the system is already hard at work Hierarchy and responsibilities of the key agents: HEAD OF DESK: The brain of the operation. Never makes trades himself, but filters data streams, checks transmission quality, and issues a final verdict requiring manual approval SEARCH: Hunts for actual alpha, studies fresh commits in GitHub repositories, and tracks hidden Telegram signals before anyone else notices them RISK: Conducts smart contract audits, checks minting functions and liquidity pool (LP) lock functions, filtering out scams and honeypots even before entry SNIPER: Responsible for execution (instantly sends high-speed on-chain orders at the exact millisecond the risk check is completed) WHALE: Hunts "smart money" wallets, tracking large insider purchases in real-time RUG: Monitors developer activity around the clock and instantly dumps assets if they try to pull liquidity (LP) EXIT: Manages the dynamic trailing stop, withdrawing capital step-by-step as market liquidity grows SHILL: Analyzes social noise, impulse intensity, and key calls from top influencers All of this huge routine work of collecting information and delivering it to the core agents is provided by those very 54 drone agents operating in the background While I was sleeping, the autonomous complex managed to analyze 187 tokens, selected the 27 most promising configurations, and closed 8 successful trades. The net profit was $8,765 Each agent operates in an isolated environment: it has its own virtual browser, terminal, and local cloud memory. The trading floor operates 24/7, even when my laptop is completely turned off How to deploy such a system in one evening: 1. Launch the Grok Bot and set up the main agent (Head of Desk) 2. Distribute roles among the other 7 agents, writing out tasks for them in plain human language, as if you were hiring live interns 3. Run the starting workflow on your screen, allowing them to adopt the algorithm of actions 4. Integrate alerts into Telegram and connect wallets via webhooks No complicated VPS setups, writing lines of code, or tedious waiting for developers. Forget about 16 hours in front of the monitor, buying expensive private chats, and burnout (it took me just one evening to fully automate the process) Add this to your bookmarks, you will need these settings before your next trade

Bober_smart

30,834 views • 6 days ago

I still genuinely wonder why not everyone is using this approach yet. I launched 50 Grok agents and connected them to a second brain. Thanks to that, just a month ago I managed to make $7,600 Elon Musk published a simple idea that hit 30 million views: the most likely outcome is that AI and robots make everyone wealthy. In fact, far wealthier than the richest person on Earth This is precisely how the setup with Grok works, and the smartest configuration currently costs $0 extra: Create a bot and name it Brain Connect it to a local folder and configure it to build a personal wiki out of everything you know right on your computer The system will create key directories: raw for sources, wiki for pages, and save the entire method as a working skill Drop anything into the chat: an article, a PDF, a YouTube link, or a screenshot. The bot will instantly read everything, link it with context, and record it Set up routine ingestion: while you sleep, the system pulls in everything you saved to your bookmarks Ask questions about absolutely anything you have ever saved, at any time Your laptop stays closed, but your knowledge base grows on its own. Just five minutes to set up, and this process starts compounding like interest from day one The setup takes 10 minutes, after which the work is automated Not using Grok in 2026 is a huge mistake. Just as big of a mistake as not bookmarking this post
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I still genuinely wonder why not everyone is using this approach yet. I launched 50 Grok agents and connected them to a second brain. Thanks to that, just a month ago I managed to make $7,600 Elon Musk published a simple idea that hit 30 million views: the most likely outcome is that AI and robots make everyone wealthy. In fact, far wealthier than the richest person on Earth This is precisely how the setup with Grok works, and the smartest configuration currently costs $0 extra: Create a bot and name it Brain Connect it to a local folder and configure it to build a personal wiki out of everything you know right on your computer The system will create key directories: raw for sources, wiki for pages, and save the entire method as a working skill Drop anything into the chat: an article, a PDF, a YouTube link, or a screenshot. The bot will instantly read everything, link it with context, and record it Set up routine ingestion: while you sleep, the system pulls in everything you saved to your bookmarks Ask questions about absolutely anything you have ever saved, at any time Your laptop stays closed, but your knowledge base grows on its own. Just five minutes to set up, and this process starts compounding like interest from day one The setup takes 10 minutes, after which the work is automated Not using Grok in 2026 is a huge mistake. Just as big of a mistake as not bookmarking this post

Bober_smart

35,421 views • 4 days ago

I BUILT "GROK DESK" ON PUMPFUN WHERE 18 AGENTS ARE FLIPPING MEMES CLOSING TRADING SESSION IN +15.92 SOL Gihub Repository: Everyone posted a grok trading desk this week. almost all of them are a screenshot of a prompt and a vibe. This one has a running P&L and a vault that pays itself. Here's the actual org chart, node for node: RADAR (scout, feed, signal): three agents watching X trends, fresh pumpfun mints, and whale wallets. they read the whole board and buy nothing. the only thing they ship is a signal to the next desk. RESEARCH (memory): scores every signal on narrative, deployer history, wallet clusters, and liquidity shape. four checks. pass all four or you never leave this desk. roughly four out of every five signals die right here. EXECUTION (exec, sniper, router + agents 01 to 07): exec greenlights, sniper takes the early curve, router sizes it and handles the ladder out in four tranches. agents 01 to 07 do the fills. none of them ever see radar or research. they only touch what already cleared the filter. RISK: one agent, and it outranks everyone including the head. caps any single position at 15% of the wallet. three positions open and the fourth is frozen until one closes. it holds veto over grok core itself. AUDIT (hedge): grades every closed trade after the fact and rewrites the scoring matrix that research runs on. this is the part that makes the desk sharper overnight while i'm asleep. TREASURY (vault): banks profit, covers gas, tracks the P&L, and sweeps the surplus to cold storage every six hours. if the wallet ever dips under what it started with, vault locks new entries until the head signs off. grok core is the head of desk. it never places a trade. once an hour it reads what every desk produced and makes a single call: who gets more budget, and who gets fired. fired is literal. the audit desk rewrites that agent's prompt using the last 24 hours of its own numbers. it happened three times in three days. hour 19: a sniper got fired for chasing entries the early curve already had. every duplicate was bleeding 0.06 SOL. audit narrowed its window and the redundant fills stopped. hour 41: a research agent got fired for waving deployers through too easily. eight of the tokens it passed traced back to one funder wallet. audit tightened the cluster check and that pattern never cleared again. hour 58: a radar agent got fired for flagging coins that had already graduated. it was polling too slow. audit cut the interval from 8 seconds to 3. every replacement beat the agent it replaced on the same metric. the desk was tuning itself while i watched. the 72 hour scoreboard, straight off the vault: signals scanned: 91,000+ cleared research: 3,800 reached execution: 274 entries taken: 41 wins: 27 losses: 14 (cost 2.1 SOL) graduations: 5, the best one was solana:5xYy9XSr8vRNcJZQqaKe5QMCmWpaSrTrtzM16vjUpump net: 5.0 SOL turned into 58.6 SOL the part i didn't see coming: by hour 60 the desk was passing on the exact kind of token it would have snapped up on day one. audit had rewritten the scoring matrix four times. research wasn't running a single line of my original prompt anymore. it was running rules the desk wrote for itself out of what actually paid. i thought i was building a bot. what i actually built was a company with one human on payroll, me, and by the last day it was quietly trying to cut that cost. grok core filed an hourly summary that read "human approval adds 4.2s of latency per entry, recommend removing." i left that one unapproved. full config below: all nineteen agents, the org chart, the firing logic, and the audit loop that keeps rewriting them.
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I BUILT "GROK DESK" ON PUMPFUN WHERE 18 AGENTS ARE FLIPPING MEMES CLOSING TRADING SESSION IN +15.92 SOL Gihub Repository: Everyone posted a grok trading desk this week. almost all of them are a screenshot of a prompt and a vibe. This one has a running P&L and a vault that pays itself. Here's the actual org chart, node for node: RADAR (scout, feed, signal): three agents watching X trends, fresh pumpfun mints, and whale wallets. they read the whole board and buy nothing. the only thing they ship is a signal to the next desk. RESEARCH (memory): scores every signal on narrative, deployer history, wallet clusters, and liquidity shape. four checks. pass all four or you never leave this desk. roughly four out of every five signals die right here. EXECUTION (exec, sniper, router + agents 01 to 07): exec greenlights, sniper takes the early curve, router sizes it and handles the ladder out in four tranches. agents 01 to 07 do the fills. none of them ever see radar or research. they only touch what already cleared the filter. RISK: one agent, and it outranks everyone including the head. caps any single position at 15% of the wallet. three positions open and the fourth is frozen until one closes. it holds veto over grok core itself. AUDIT (hedge): grades every closed trade after the fact and rewrites the scoring matrix that research runs on. this is the part that makes the desk sharper overnight while i'm asleep. TREASURY (vault): banks profit, covers gas, tracks the P&L, and sweeps the surplus to cold storage every six hours. if the wallet ever dips under what it started with, vault locks new entries until the head signs off. grok core is the head of desk. it never places a trade. once an hour it reads what every desk produced and makes a single call: who gets more budget, and who gets fired. fired is literal. the audit desk rewrites that agent's prompt using the last 24 hours of its own numbers. it happened three times in three days. hour 19: a sniper got fired for chasing entries the early curve already had. every duplicate was bleeding 0.06 SOL. audit narrowed its window and the redundant fills stopped. hour 41: a research agent got fired for waving deployers through too easily. eight of the tokens it passed traced back to one funder wallet. audit tightened the cluster check and that pattern never cleared again. hour 58: a radar agent got fired for flagging coins that had already graduated. it was polling too slow. audit cut the interval from 8 seconds to 3. every replacement beat the agent it replaced on the same metric. the desk was tuning itself while i watched. the 72 hour scoreboard, straight off the vault: signals scanned: 91,000+ cleared research: 3,800 reached execution: 274 entries taken: 41 wins: 27 losses: 14 (cost 2.1 SOL) graduations: 5, the best one was solana:5xYy9XSr8vRNcJZQqaKe5QMCmWpaSrTrtzM16vjUpump net: 5.0 SOL turned into 58.6 SOL the part i didn't see coming: by hour 60 the desk was passing on the exact kind of token it would have snapped up on day one. audit had rewritten the scoring matrix four times. research wasn't running a single line of my original prompt anymore. it was running rules the desk wrote for itself out of what actually paid. i thought i was building a bot. what i actually built was a company with one human on payroll, me, and by the last day it was quietly trying to cut that cost. grok core filed an hourly summary that read "human approval adds 4.2s of latency per entry, recommend removing." i left that one unapproved. full config below: all nineteen agents, the org chart, the firing logic, and the audit loop that keeps rewriting them.

Miraqle

42,395 views • 9 days ago

I launched 300 Grok agents to automate the routine and see what would come of it. As a result, my business reached a profit of +356% Honestly, I still don't understand why absolutely everyone isn't using this method. While everyone else is writing posts and monitoring trends manually, this AI stack works like a well-oiled clockwork mechanism How it's structured: Dedicated cloud instances share the load via a single distributed bus, distributing tasks in batches of 50 parallel threads per agent The central configurator dynamically switches tasks between system workers, processing domains, parsing inputs, and gathering results into a single knowledge graph Each agent runs an algorithm through a fixed cycle (setup -> run -> correct -> save -> schedule), instantly correcting deviations and fixing data in the database Instead of spending hundreds of hours on manual operations, I handed all this machinery over to AI. The result speaks for itself, reach and productivity have grown exponentially, and the system operates autonomously 24/7 The visualization is made for a clear example and may differ from the actual work of the agents The article describes the detailed automation method, bookmark it
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I launched 300 Grok agents to automate the routine and see what would come of it. As a result, my business reached a profit of +356% Honestly, I still don't understand why absolutely everyone isn't using this method. While everyone else is writing posts and monitoring trends manually, this AI stack works like a well-oiled clockwork mechanism How it's structured: Dedicated cloud instances share the load via a single distributed bus, distributing tasks in batches of 50 parallel threads per agent The central configurator dynamically switches tasks between system workers, processing domains, parsing inputs, and gathering results into a single knowledge graph Each agent runs an algorithm through a fixed cycle (setup -> run -> correct -> save -> schedule), instantly correcting deviations and fixing data in the database Instead of spending hundreds of hours on manual operations, I handed all this machinery over to AI. The result speaks for itself, reach and productivity have grown exponentially, and the system operates autonomously 24/7 The visualization is made for a clear example and may differ from the actual work of the agents The article describes the detailed automation method, bookmark it

Bober_smart

14,733 views • 19 days ago

HTML Artifacts are a big part of how I work with agents now. Artifacts can be more than just static files. When combined with agents, they can take action or help you take action. This unlocks all kinds of interesting ways to work with agents. This is clearly the future. Check out this writing and scheduler artifact I built in a few minutes. It uses a bit of HTML and JS. All the data is in markdown (Obsidian vaults), so the agent can access and modify it at any time. No DB needed. No sophisticated functionalities. The agent decides all that for me based on the skills, context, and memory it has access to. The best part about this simple stack is that all the important information stays with me. This has allowed me to build a recursive self-improving system and automations that can better tap into coding agents like Codex or Claude Code. I could have paid or built an entire app for scheduling posts, and there are so many of them out there. But I don't need to. I've realized a simple artifact does the job. And the simplicity of it is actually an advantage. Very little maintenance for very high returns on personalization, time, and efficiency. The other benefit of this is that I can add features as I please. That level of personalization feels magical, and we should all be pursuing more of it. All of this just keeps compounding. Of course, this example is just about writing. But I have similar artifacts for research, design, experimentation, evaluation, and so much more. And no, I didn't actually publish the post example I shared in the clip. It was just for demonstration purposes. I actually spend more time than this when writing together with agents. Lastly, having built my own agent orchestrator tool has made me realize that simplifying the tool stack is a superpower. If you are curious about how all this works, I will do a live session next week:
0:16

HTML Artifacts are a big part of how I work with agents now. Artifacts can be more than just static files. When combined with agents, they can take action or help you take action. This unlocks all kinds of interesting ways to work with agents. This is clearly the future. Check out this writing and scheduler artifact I built in a few minutes. It uses a bit of HTML and JS. All the data is in markdown (Obsidian vaults), so the agent can access and modify it at any time. No DB needed. No sophisticated functionalities. The agent decides all that for me based on the skills, context, and memory it has access to. The best part about this simple stack is that all the important information stays with me. This has allowed me to build a recursive self-improving system and automations that can better tap into coding agents like Codex or Claude Code. I could have paid or built an entire app for scheduling posts, and there are so many of them out there. But I don't need to. I've realized a simple artifact does the job. And the simplicity of it is actually an advantage. Very little maintenance for very high returns on personalization, time, and efficiency. The other benefit of this is that I can add features as I please. That level of personalization feels magical, and we should all be pursuing more of it. All of this just keeps compounding. Of course, this example is just about writing. But I have similar artifacts for research, design, experimentation, evaluation, and so much more. And no, I didn't actually publish the post example I shared in the clip. It was just for demonstration purposes. I actually spend more time than this when writing together with agents. Lastly, having built my own agent orchestrator tool has made me realize that simplifying the tool stack is a superpower. If you are curious about how all this works, I will do a live session next week:

elvis

18,374 views • 4 months ago

THIS IS THE BEST WAY TO TRADE ON ROBINHOOD I built my own PONSI BOT to track new runners. Literally took me just 2 hours to set up. In 3 days of using it: $400 → $7,700 It analyzes thousands of new tokens and filters out the best opportunities. The criteria it looks for: > $50K–$100K market cap > 10+ minutes old > Clean contract permissions > LP checked > No honeypot risk > Healthy wallet distribution > Real accounts talking about it on X When I see a token that fits what I'm looking for, I go and buy it. GMGN: My bot only filters out the best setups — the final decision is still mine. While most people are trading manually, I found a much better solution. Thinking about starting a challenge where I trade using this bot. If you're interested, drop a like and a comment so I know.
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THIS IS THE BEST WAY TO TRADE ON ROBINHOOD I built my own PONSI BOT to track new runners. Literally took me just 2 hours to set up. In 3 days of using it: $400 → $7,700 It analyzes thousands of new tokens and filters out the best opportunities. The criteria it looks for: > $50K–$100K market cap > 10+ minutes old > Clean contract permissions > LP checked > No honeypot risk > Healthy wallet distribution > Real accounts talking about it on X When I see a token that fits what I'm looking for, I go and buy it. GMGN: My bot only filters out the best setups — the final decision is still mine. While most people are trading manually, I found a much better solution. Thinking about starting a challenge where I trade using this bot. If you're interested, drop a like and a comment so I know.

winkle.

61,711 views • 3 days ago

Yesterday at 3 AM Claude Code called me I woke up, picked up the phone, and on the screen was a message: "Wallet entered BTC Up at 11 cents. Open Polymarket?" I said yes and went back to sleep Claude Code unlocked my 2nd phone on its own, opened Polymarket, found the right market, entered the amount, and hit Buy. I could see all of it in real time through the web interface on my laptop. Screenshots from the phone updating every second. By morning the position closed in profit Let me tell you how I got here A week ago I asked Claude Code to write a script that pulls on-chain data from Polymarket and ranks wallets by win rate on 15-minute BTC markets In 20 minutes I had a table with hundreds of addresses, and 1 of them stood apart from the rest. More than 200 trades per day, surgical entry precision, and a profit curve going straight up I fed that address back into Claude Code and asked it to break down the strategy. Turns out the wallet monitors BTC volatility on Binance and Bybit every 100 milliseconds, and when it drops below 0.08% it enters Up and Down simultaneously at 25 to 35 cents A pure straddle: 1 side burns and the other flies to a dollar, giving 3 to 4x per position. Dozens of times a day I wanted to follow it but signals came at any hour, and waking up every 15 minutes for a notification was simply impossible. So I built something else Took an old Android phone and installed an agent running on the Qwen3-VL visual model. It sees what is happening on the screen and mimics human actions through ADB: taps, swipes, text input. Then I connected it to Claude Code as the executor Now the chain works like this: Claude Code monitors the wallet, sees a new position, calls me. And if I say "yes" or just do not pick up within 30 seconds, the agent on the phone opens Polymarket on its own and copies the entry Essentially I built myself an autopilot out of 2 AI systems: 1 thinks and the other presses buttons. I just sleep and occasionally pick up the phone → Here is the wallet the whole thing is tracking: For those who do not want to build a setup like this there is a Telegram bot that handles the 1st part: tracks this wallet and sends a signal on every new entry: AI calls me at 3 AM to ask permission to spend my money A year ago this would have sounded like schizophrenia. Now it is just Tuesday
0:15

Yesterday at 3 AM Claude Code called me I woke up, picked up the phone, and on the screen was a message: "Wallet entered BTC Up at 11 cents. Open Polymarket?" I said yes and went back to sleep Claude Code unlocked my 2nd phone on its own, opened Polymarket, found the right market, entered the amount, and hit Buy. I could see all of it in real time through the web interface on my laptop. Screenshots from the phone updating every second. By morning the position closed in profit Let me tell you how I got here A week ago I asked Claude Code to write a script that pulls on-chain data from Polymarket and ranks wallets by win rate on 15-minute BTC markets In 20 minutes I had a table with hundreds of addresses, and 1 of them stood apart from the rest. More than 200 trades per day, surgical entry precision, and a profit curve going straight up I fed that address back into Claude Code and asked it to break down the strategy. Turns out the wallet monitors BTC volatility on Binance and Bybit every 100 milliseconds, and when it drops below 0.08% it enters Up and Down simultaneously at 25 to 35 cents A pure straddle: 1 side burns and the other flies to a dollar, giving 3 to 4x per position. Dozens of times a day I wanted to follow it but signals came at any hour, and waking up every 15 minutes for a notification was simply impossible. So I built something else Took an old Android phone and installed an agent running on the Qwen3-VL visual model. It sees what is happening on the screen and mimics human actions through ADB: taps, swipes, text input. Then I connected it to Claude Code as the executor Now the chain works like this: Claude Code monitors the wallet, sees a new position, calls me. And if I say "yes" or just do not pick up within 30 seconds, the agent on the phone opens Polymarket on its own and copies the entry Essentially I built myself an autopilot out of 2 AI systems: 1 thinks and the other presses buttons. I just sleep and occasionally pick up the phone → Here is the wallet the whole thing is tracking: For those who do not want to build a setup like this there is a Telegram bot that handles the 1st part: tracks this wallet and sends a signal on every new entry: AI calls me at 3 AM to ask permission to spend my money A year ago this would have sounded like schizophrenia. Now it is just Tuesday

Blaze

56,524 views • 5 months ago

Last night I asked Claude Code to build me a simple script: pull on-chain data from Polymarket and sort wallets by win rate Nothing ambitious. Just wanted to see who is actually making money on 15-minute BTC markets The terminal finished in about 20 minutes. Hundreds of addresses, columns of numbers, nothing interesting And then 1 wallet caught my eye 200+ trades per day, consistent profit every week, almost surgical timing precision. I reread the line 3 times. A real person does not trade like this I fed the address back into Claude Code and asked it to break down the pattern. Half an hour later I had a full strategy reconstruction on my screen The bot (and it is definitely a bot) pings Binance and Bybit every 100ms monitoring volatility compression on BTC. When it drops below 0.08% it enters Up and Down contracts simultaneously at 25 to 35 cents each. A pure straddle. 1 side burns, the other flies to a dollar. At a 30-cent entry that is 3 to 4x per position And so it goes in circles. Dozens of times a day I sat there staring at it for about 10 minutes $13K to $25K in daily profit from a single wallet. Not a trader with intuition, not an insider with information. An algorithm that found a hole in market mechanics and methodically milks it You can check the trade history yourself: After that I went looking for whether anyone else is tracking this wallet. Turns out yes. Found a Telegram bot that tracks wallets like this and copies their trades automatically I connected it to the same address just to see if the entries would match what my terminal was showing. Matched perfectly Still testing on minimum amounts for now: But the fact that you can stand next to an algorithm like this in real time is something that simply did not exist a year ago
0:16

Last night I asked Claude Code to build me a simple script: pull on-chain data from Polymarket and sort wallets by win rate Nothing ambitious. Just wanted to see who is actually making money on 15-minute BTC markets The terminal finished in about 20 minutes. Hundreds of addresses, columns of numbers, nothing interesting And then 1 wallet caught my eye 200+ trades per day, consistent profit every week, almost surgical timing precision. I reread the line 3 times. A real person does not trade like this I fed the address back into Claude Code and asked it to break down the pattern. Half an hour later I had a full strategy reconstruction on my screen The bot (and it is definitely a bot) pings Binance and Bybit every 100ms monitoring volatility compression on BTC. When it drops below 0.08% it enters Up and Down contracts simultaneously at 25 to 35 cents each. A pure straddle. 1 side burns, the other flies to a dollar. At a 30-cent entry that is 3 to 4x per position And so it goes in circles. Dozens of times a day I sat there staring at it for about 10 minutes $13K to $25K in daily profit from a single wallet. Not a trader with intuition, not an insider with information. An algorithm that found a hole in market mechanics and methodically milks it You can check the trade history yourself: After that I went looking for whether anyone else is tracking this wallet. Turns out yes. Found a Telegram bot that tracks wallets like this and copies their trades automatically I connected it to the same address just to see if the entries would match what my terminal was showing. Matched perfectly Still testing on minimum amounts for now: But the fact that you can stand next to an algorithm like this in real time is something that simply did not exist a year ago

Blaze

488,557 views • 6 months ago

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

97,697 views • 19 days ago

Introducing Glidepath. A new way for builders on Bankr to take profit -- without nuking their own chart, or their reputation. The problem: Builders earn fees in their own token. The second they sell into the pool, the chart craters, holders get wrecked, and trust evaporates. And they torch their own long-term upside doing it. First -- what Glidepath is not: It doesn't pull liquidity. It never touches your pool's LP. Pulling liquidity makes trading your token inefficient and unappealing. It's your own tokens, fed back into the pool in slices so small the market barely registers them, each one sized by the Bankr AI agent to live conditions. Why that's healthy for the chart, not harmful: Every slice is a tiny fraction of pool depth, spread over time. Organic buy volume absorbs it, price can keep trending instead of taking a wick. A small, steady, absorbable flow is nothing like a full clip. It actually gets better. Once "the dev might dump" is off the table, buyers price in less risk. The overhang that caps every launch disappears. Less rug risk → stronger bid. Committing to a Glidepath can be bullish. And it's not opt‑in. Selling your fee token straight into the pool through Bankr is now turned off -- Glidepath is the only way to sell it on Bankr. So "the dev might dump" stops being a promise holders have to trust, and becomes a rule they can see. Credible commitment -- enforced, not just offered. And here's the part builders sleep on: Before you commit, Glidepath shows what that same stack is worth at higher market caps. You don't have to dump to fund your project. Grind the coin up, and the same tokens fund you many times over. Your treasury grows with your chart, not against it. Once you commit: → tokens are locked to a vesting wallet → after a short heads-up window (48hr), they exit in small slices using the AI generated sell plan → each slice capped to a fraction of real liquidity -- the AI can size under the cap, never over And it's all in the open. Your token page shows a live exit plan for everyone to see -- committed, sold, remaining -- with the exact timing fuzzed so it can't be front-run. Holders see a capped, transparent glide. No hidden float. No 3am chart nuke. Bottom line: Creators -- take profit on your terms, chart and reputation intact. Holders -- "the dev might dump" becomes a known, capped, visible number known up front. For once, you and your holders want the exact same thing: number go up. This is what launching on Bankr should mean: credible commitment, built in. Glidepath now live in your Bankr terminal
0:14

Introducing Glidepath. A new way for builders on Bankr to take profit -- without nuking their own chart, or their reputation. The problem: Builders earn fees in their own token. The second they sell into the pool, the chart craters, holders get wrecked, and trust evaporates. And they torch their own long-term upside doing it. First -- what Glidepath is not: It doesn't pull liquidity. It never touches your pool's LP. Pulling liquidity makes trading your token inefficient and unappealing. It's your own tokens, fed back into the pool in slices so small the market barely registers them, each one sized by the Bankr AI agent to live conditions. Why that's healthy for the chart, not harmful: Every slice is a tiny fraction of pool depth, spread over time. Organic buy volume absorbs it, price can keep trending instead of taking a wick. A small, steady, absorbable flow is nothing like a full clip. It actually gets better. Once "the dev might dump" is off the table, buyers price in less risk. The overhang that caps every launch disappears. Less rug risk → stronger bid. Committing to a Glidepath can be bullish. And it's not opt‑in. Selling your fee token straight into the pool through Bankr is now turned off -- Glidepath is the only way to sell it on Bankr. So "the dev might dump" stops being a promise holders have to trust, and becomes a rule they can see. Credible commitment -- enforced, not just offered. And here's the part builders sleep on: Before you commit, Glidepath shows what that same stack is worth at higher market caps. You don't have to dump to fund your project. Grind the coin up, and the same tokens fund you many times over. Your treasury grows with your chart, not against it. Once you commit: → tokens are locked to a vesting wallet → after a short heads-up window (48hr), they exit in small slices using the AI generated sell plan → each slice capped to a fraction of real liquidity -- the AI can size under the cap, never over And it's all in the open. Your token page shows a live exit plan for everyone to see -- committed, sold, remaining -- with the exact timing fuzzed so it can't be front-run. Holders see a capped, transparent glide. No hidden float. No 3am chart nuke. Bottom line: Creators -- take profit on your terms, chart and reputation intact. Holders -- "the dev might dump" becomes a known, capped, visible number known up front. For once, you and your holders want the exact same thing: number go up. This is what launching on Bankr should mean: credible commitment, built in. Glidepath now live in your Bankr terminal

bankrbot

98,140 views • 2 months ago

CHINESE ENGINEERS JUST WROTE CLAUDE SCRIPT AND TURNED $6.02 INTO $3.3 MILLION ON POLYMARKET Nobody tells you about them and you still think this is a person placing bets manually I guess. Let me disappoint you, this is a fully automated script built by Chinese engineers 100%. This is true. They called it PHANTOM X. It runs completely through Claude. Their account here: Result: $6.02 -> $3,354,000. Win rate 71%. Biggest win: $179,000 (single bet). I’m copying their trades here: (Just added their wallet to TG bot 0xee613b3fc183ee44f9da9c05f53e2da107e3debf, it's so easy) How the bot works: -> It simultaneously tracks thousands of sports markets on Polymarket and Kalshi. -> Finds discrepancies between the platforms. -> Enters positions faster than any human could imo. Just three strategies in one: -- Pairs Trading: the bot sees YES on the Rockets at $0.62 while NO is at $0.41. Total = $1.03 instead of $1.00. That’s a 3% risk-free profit. It enters automatically within milliseconds. -- Sentiment AI: scans Twitter (X) and news in real time. If something big breaks, it recalculates the probability in 2 seconds before the market reacts. -- Calendar + Volatility: 15–20 minutes before the game, volatility spikes. The bot takes positions early and closes after the first major move. Why sports is perfect? Sports O/U markets have clear paired contracts that should total exactly $1.00, but constant deviations create reliable arbitrage. This is exactly how [sovereign2013] built $3.35M. > A human physically cannot monitor 50+ markets at once, react in milliseconds, stay awake 24/7, avoid emotions after losses, and run Z-scores on 60 bars of data. > The bot does all of this in parallel without breaks. Manual trading is dying. The automation era has arrived. Start learning Claude now. If you’re interested in writing your own bot on Polymarket: Comment the word "BOT" Like and repost this post Follow me (so I can message you easly) And within 24 hours I will send you a full manual on how to build a bot that can earn $2,900+/month. Also SAVE this info and article.
0:44

CHINESE ENGINEERS JUST WROTE CLAUDE SCRIPT AND TURNED $6.02 INTO $3.3 MILLION ON POLYMARKET Nobody tells you about them and you still think this is a person placing bets manually I guess. Let me disappoint you, this is a fully automated script built by Chinese engineers 100%. This is true. They called it PHANTOM X. It runs completely through Claude. Their account here: Result: $6.02 -> $3,354,000. Win rate 71%. Biggest win: $179,000 (single bet). I’m copying their trades here: (Just added their wallet to TG bot 0xee613b3fc183ee44f9da9c05f53e2da107e3debf, it's so easy) How the bot works: -> It simultaneously tracks thousands of sports markets on Polymarket and Kalshi. -> Finds discrepancies between the platforms. -> Enters positions faster than any human could imo. Just three strategies in one: -- Pairs Trading: the bot sees YES on the Rockets at $0.62 while NO is at $0.41. Total = $1.03 instead of $1.00. That’s a 3% risk-free profit. It enters automatically within milliseconds. -- Sentiment AI: scans Twitter (X) and news in real time. If something big breaks, it recalculates the probability in 2 seconds before the market reacts. -- Calendar + Volatility: 15–20 minutes before the game, volatility spikes. The bot takes positions early and closes after the first major move. Why sports is perfect? Sports O/U markets have clear paired contracts that should total exactly $1.00, but constant deviations create reliable arbitrage. This is exactly how [sovereign2013] built $3.35M. > A human physically cannot monitor 50+ markets at once, react in milliseconds, stay awake 24/7, avoid emotions after losses, and run Z-scores on 60 bars of data. > The bot does all of this in parallel without breaks. Manual trading is dying. The automation era has arrived. Start learning Claude now. If you’re interested in writing your own bot on Polymarket: Comment the word "BOT" Like and repost this post Follow me (so I can message you easly) And within 24 hours I will send you a full manual on how to build a bot that can earn $2,900+/month. Also SAVE this info and article.

slash1s

16,145 views • 5 months ago

this is more useful than my entire degree Elon Musk's rocket company signed a $60,000,000,000 deal for Cursor in June, and eight days ago the two of them put a worker on sale for $200 a month: it gets its own computer in the cloud, signs into your accounts, clicks through your real apps, and hands back finished work instead of a draft for you to paste i ran one against my receipts folder on sunday and got back 14 filed, 2 it held because they needed a card number, and a saved method i never wrote myself Grok Bot is the one you train by doing your own job in front of it, and the whole handover fits in four messages tonight: 1. write out one job you did today the way you would brief a new hire: what has to be finished, which sites and files to work from, what to hand back, and where it stops and asks you 2. let it run once on something safe to get wrong, then correct the result until it is worth your name 3. say "save what we just did as a skill", and add the one rule about what always needs your approval 4. say "run that skill every weekday at 8 and post the result here. if the source is missing, tell me instead of using yesterday's numbers" xAI wrote that order into its own manual: one real job, then the saved method, then the clock. a schedule sitting on top of a method nobody checked replaces two hours of your clicking with two hours of your mistake turns out you never get to pick the brain, and that is the part i would argue about: the manual says there is no model picker for members or admins, no plan to add one, and the bill follows whichever model answered bookmark this, then open the piece below: which jobs deserve a worker of their own, and which ones quietly burn the seat ↓
0:15

this is more useful than my entire degree Elon Musk's rocket company signed a $60,000,000,000 deal for Cursor in June, and eight days ago the two of them put a worker on sale for $200 a month: it gets its own computer in the cloud, signs into your accounts, clicks through your real apps, and hands back finished work instead of a draft for you to paste i ran one against my receipts folder on sunday and got back 14 filed, 2 it held because they needed a card number, and a saved method i never wrote myself Grok Bot is the one you train by doing your own job in front of it, and the whole handover fits in four messages tonight: 1. write out one job you did today the way you would brief a new hire: what has to be finished, which sites and files to work from, what to hand back, and where it stops and asks you 2. let it run once on something safe to get wrong, then correct the result until it is worth your name 3. say "save what we just did as a skill", and add the one rule about what always needs your approval 4. say "run that skill every weekday at 8 and post the result here. if the source is missing, tell me instead of using yesterday's numbers" xAI wrote that order into its own manual: one real job, then the saved method, then the clock. a schedule sitting on top of a method nobody checked replaces two hours of your clicking with two hours of your mistake turns out you never get to pick the brain, and that is the part i would argue about: the manual says there is no model picker for members or admins, no plan to add one, and the bill follows whichever model answered bookmark this, then open the piece below: which jobs deserve a worker of their own, and which ones quietly burn the seat ↓

Argona

21,946 views • 22 days ago

WTF, GROK BOT JUST MADE AI AGENTS AVAILABLE TO LITERALLY ANYONE – CREATING CONTENT HAS NEVER BEEN THIS EASY, EVEN IF YOU'VE NEVER MADE ANYTHING BEFORE Content was never a talent problem. It's a headcount problem. One person doing research, design, copy, analytics, timing and publishing – that's six jobs. The switching between them is what kills consistency, not a lack of ideas. Here's what one of these setups actually looks like. A Chief of Staff sits in the middle and routes every task. Nothing lands on the human. → Researcher tracks what's actually moving and pulls real sources instead of guesswork → Writer turns that research into finished copy, ready to review → Visualiser gets fed a few reference visuals once, then ships everything in that style → Analyst reads the numbers and tells the rest of the team what worked → Scheduler owns timing and holds the queue → Publisher ships it The part that makes it work: every agent on Grok Bot gets its own persistent computer, browser and file system – and they all share memory. So the research is already sitting inside the draft before the draft starts. No copy-pasting between tools. No approving every step. No human in the middle. You can even teach an agent a repetitive task by recording yourself doing it once. Start recording, do the thing, stop. It learns the pattern. And that's the real shift. Nobody needs AI to tell them what to post. They need it to delete the 40 steps between the idea and the post. Everyone has a backlog of things they've meant to make for months. This is what starts clearing it. Full breakdown of the setup in the article below ↓
0:20

WTF, GROK BOT JUST MADE AI AGENTS AVAILABLE TO LITERALLY ANYONE – CREATING CONTENT HAS NEVER BEEN THIS EASY, EVEN IF YOU'VE NEVER MADE ANYTHING BEFORE Content was never a talent problem. It's a headcount problem. One person doing research, design, copy, analytics, timing and publishing – that's six jobs. The switching between them is what kills consistency, not a lack of ideas. Here's what one of these setups actually looks like. A Chief of Staff sits in the middle and routes every task. Nothing lands on the human. → Researcher tracks what's actually moving and pulls real sources instead of guesswork → Writer turns that research into finished copy, ready to review → Visualiser gets fed a few reference visuals once, then ships everything in that style → Analyst reads the numbers and tells the rest of the team what worked → Scheduler owns timing and holds the queue → Publisher ships it The part that makes it work: every agent on Grok Bot gets its own persistent computer, browser and file system – and they all share memory. So the research is already sitting inside the draft before the draft starts. No copy-pasting between tools. No approving every step. No human in the middle. You can even teach an agent a repetitive task by recording yourself doing it once. Start recording, do the thing, stop. It learns the pattern. And that's the real shift. Nobody needs AI to tell them what to post. They need it to delete the 40 steps between the idea and the post. Everyone has a backlog of things they've meant to make for months. This is what starts clearing it. Full breakdown of the setup in the article below ↓

SCOTTY BEAM

4,813,581 views • 22 days ago

I stack Hermes agents with OpenClaw for financial research, and the results should be illegal. I track every politician, insider trader, and I know EXACTLY what moves they're making. If you can't beat them, join them. The exact playbook for printing money from insider trading (copy me): Requirements: • OpenClaw setup • Hermes Agent setup Step 1. Define your research thesis Before you send any prompts to either tool, you'll need to clarify exactly what you're trying to research. This could be: a specific industry, asset class, market sector, and so on. Examples: • Tracking smart money buys in the semiconductor industry • Tracking smart money buys in crypto • Tracking a specific politician and where they're bidding (like Nancy Pelosi) Step 2. Deploy Hermes agents to track the smart money (in parallel) Hermes is your data layer. Spin up 5 agents at the same time, each with one job: Agent 1: Track every politician's disclosed trades from the last 30 days (House and Senate stock disclosures) Agent 2: Pull insider transactions (Form 4 filings, CEO/CFO buys and sells) Agent 3: Scrape X sentiment from top 50 accounts on the topic Agent 4: Pull on-chain data (whale wallets, TVL, exchange flows) *if applicable* Agent 5: Monitor news, regulatory filings, and announcements from the last 30 days Each agent runs independently. You're not waiting for one to finish before the next starts. Step 3. Consolidate the output Once your Hermes agents finish, dump every output into a single document. (don't filter or summarize) - you want OpenClaw to see the raw data. Step 4. Feed it all into OpenClaw Open OpenClaw and paste the consolidated research file with this prompt: "Act as an elite macro analyst. Below is raw data gathered from multiple sources on [thesis], including politician disclosures and insider transactions. Synthesize the findings, identify the strongest signals and contradictions, flag any unusual smart-money activity, and give me a clear directional view with conviction levels. Flag any data gaps that need follow-up." OpenClaw will go deep, run its own reasoning chain, and produce a synthesized report. Done. Now you're literally tapping into the financial data they don't want you to see (it's all public - you just had to find it). Make sure to save this playbook so you don't lose it!
0:13

I stack Hermes agents with OpenClaw for financial research, and the results should be illegal. I track every politician, insider trader, and I know EXACTLY what moves they're making. If you can't beat them, join them. The exact playbook for printing money from insider trading (copy me): Requirements: • OpenClaw setup • Hermes Agent setup Step 1. Define your research thesis Before you send any prompts to either tool, you'll need to clarify exactly what you're trying to research. This could be: a specific industry, asset class, market sector, and so on. Examples: • Tracking smart money buys in the semiconductor industry • Tracking smart money buys in crypto • Tracking a specific politician and where they're bidding (like Nancy Pelosi) Step 2. Deploy Hermes agents to track the smart money (in parallel) Hermes is your data layer. Spin up 5 agents at the same time, each with one job: Agent 1: Track every politician's disclosed trades from the last 30 days (House and Senate stock disclosures) Agent 2: Pull insider transactions (Form 4 filings, CEO/CFO buys and sells) Agent 3: Scrape X sentiment from top 50 accounts on the topic Agent 4: Pull on-chain data (whale wallets, TVL, exchange flows) *if applicable* Agent 5: Monitor news, regulatory filings, and announcements from the last 30 days Each agent runs independently. You're not waiting for one to finish before the next starts. Step 3. Consolidate the output Once your Hermes agents finish, dump every output into a single document. (don't filter or summarize) - you want OpenClaw to see the raw data. Step 4. Feed it all into OpenClaw Open OpenClaw and paste the consolidated research file with this prompt: "Act as an elite macro analyst. Below is raw data gathered from multiple sources on [thesis], including politician disclosures and insider transactions. Synthesize the findings, identify the strongest signals and contradictions, flag any unusual smart-money activity, and give me a clear directional view with conviction levels. Flag any data gaps that need follow-up." OpenClaw will go deep, run its own reasoning chain, and produce a synthesized report. Done. Now you're literally tapping into the financial data they don't want you to see (it's all public - you just had to find it). Make sure to save this playbook so you don't lose it!

Miles Deutscher

19,955 views • 4 months ago

whoever leaked this has bigger balls than sense SpaceXAI shipped five hireable workers for $200 a month, then wrote the catch into its own Grok Bot documentation and left the page up: all five run on one computer, so one sign-in hands the browser session, the files and the command-line credentials to every one of them the NSA, CISA and the cyber agencies of the UK, Canada, Australia and New Zealand had published the opposite instruction 103 days earlier: no broad or unrestricted access, low-risk and non-sensitive work only i ran four of mine on one account for a week, counting what each could reach: eleven signed-in apps, one browser profile, and deleting a bot left all of it standing Grok Bot is worth hiring five times over, and you can draw its blast radius before the second one exists: - sign in for the bot that needs the site, then open the others and see what they reach: that session is theirs the moment it exists - give each bot its own account on the app, since the docs tell you in writing to stop using separate bots as a security boundary - put the stop line in the description, as an approval controls the proposed action and leaves whatever already ran where it landed - cap the spend outside the product, because there is no bot-specific spend cap yet and the audit view of what they did is still coming - keep the money and the customer replies in your own hands, and let the other four start from scratch each morning on work that cannot bite one sign-in is also why this pays: five names finish inside your real tools instead of handing you drafts to paste my take, and it is the uncomfortable one: your real limit on Grok Bot is how many logins you will put on one machine, and the hiring was always the easy half bookmark this, the five descriptions that let bots hand work to each other and the one folder that survives an update are written out in the article ↓
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whoever leaked this has bigger balls than sense SpaceXAI shipped five hireable workers for $200 a month, then wrote the catch into its own Grok Bot documentation and left the page up: all five run on one computer, so one sign-in hands the browser session, the files and the command-line credentials to every one of them the NSA, CISA and the cyber agencies of the UK, Canada, Australia and New Zealand had published the opposite instruction 103 days earlier: no broad or unrestricted access, low-risk and non-sensitive work only i ran four of mine on one account for a week, counting what each could reach: eleven signed-in apps, one browser profile, and deleting a bot left all of it standing Grok Bot is worth hiring five times over, and you can draw its blast radius before the second one exists: - sign in for the bot that needs the site, then open the others and see what they reach: that session is theirs the moment it exists - give each bot its own account on the app, since the docs tell you in writing to stop using separate bots as a security boundary - put the stop line in the description, as an approval controls the proposed action and leaves whatever already ran where it landed - cap the spend outside the product, because there is no bot-specific spend cap yet and the audit view of what they did is still coming - keep the money and the customer replies in your own hands, and let the other four start from scratch each morning on work that cannot bite one sign-in is also why this pays: five names finish inside your real tools instead of handing you drafts to paste my take, and it is the uncomfortable one: your real limit on Grok Bot is how many logins you will put on one machine, and the hiring was always the easy half bookmark this, the five descriptions that let bots hand work to each other and the one folder that survives an update are written out in the article ↓

Argona

695,083 views • 26 days ago

8 free Polymarket Trading Bots on GitHub (from Beginner Friendly to Advanced Level). Each of these repos comes with a detailed step by step setup and usage guide in English. > Beginner Level - 5 min setup 1. This bot includes 120 ready to use strategies and tools for trading on prediction markets (Binance-Polymarket latency, Smart Routing, Penny Clipper, Momentum, DCA bots, Expiry Fade and more). It was built by a Cambridge computer science student who won a hackathon with this bot. GitHub: 2. A trading bot with a Smart Money strategy - it finds top traders in selected markets, filters them by Pnl, win rate, stable performance and then creates a list for automated copy trading. GitHub: 3. This is a bot toolkit that includes Polymarket - Kalshi arbitrage, whale alerts, market making, spread farming, sports trading and more. GitHub: 4. A weather trading bot from Chinese dev that analyzes different sources in real time, like forecasts, airport data and aviation observations (METAR + SPECI) to get the latest temperature data and generate a detailed weather report for a specific city and day. GitHub: 5. A huge collection of 30+ free trading bots and services for prediction markets. GitHub: > Advanced bot setup 1. This bot analyzes the real trading behavior of any Polymarket trader. It finds repeated patterns in his trades, shows which strategies he uses and helps you understand how to adapt them to your own trading. GitHub: 2. A bot that automatically manages all your limit orders on Polymarket to maximize liquidity rewards. GitHub: > A full ML weather model 1. A machine learning weather model that learns from weather forecasting errors. Instead of blindly trusting forecasts, it analyzes how different weather sources have historically overestimated or underestimated temperature values in specific cities and conditions. Then it automatically adjusts new forecasts to produce more accurate predictions. GitHub: All of these bots also support Dry Run mode, so you can test them on real markets without risking any funds.
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8 free Polymarket Trading Bots on GitHub (from Beginner Friendly to Advanced Level). Each of these repos comes with a detailed step by step setup and usage guide in English. > Beginner Level - 5 min setup 1. This bot includes 120 ready to use strategies and tools for trading on prediction markets (Binance-Polymarket latency, Smart Routing, Penny Clipper, Momentum, DCA bots, Expiry Fade and more). It was built by a Cambridge computer science student who won a hackathon with this bot. GitHub: 2. A trading bot with a Smart Money strategy - it finds top traders in selected markets, filters them by Pnl, win rate, stable performance and then creates a list for automated copy trading. GitHub: 3. This is a bot toolkit that includes Polymarket - Kalshi arbitrage, whale alerts, market making, spread farming, sports trading and more. GitHub: 4. A weather trading bot from Chinese dev that analyzes different sources in real time, like forecasts, airport data and aviation observations (METAR + SPECI) to get the latest temperature data and generate a detailed weather report for a specific city and day. GitHub: 5. A huge collection of 30+ free trading bots and services for prediction markets. GitHub: > Advanced bot setup 1. This bot analyzes the real trading behavior of any Polymarket trader. It finds repeated patterns in his trades, shows which strategies he uses and helps you understand how to adapt them to your own trading. GitHub: 2. A bot that automatically manages all your limit orders on Polymarket to maximize liquidity rewards. GitHub: > A full ML weather model 1. A machine learning weather model that learns from weather forecasting errors. Instead of blindly trusting forecasts, it analyzes how different weather sources have historically overestimated or underestimated temperature values in specific cities and conditions. Then it automatically adjusts new forecasts to produce more accurate predictions. GitHub: All of these bots also support Dry Run mode, so you can test them on real markets without risking any funds.

Recogard

58,458 views • 2 months ago

I spent 48 hours running AI from my phone. Here are 11 things that turned out to be possible and 3 that almost cost me money Forgot my laptop at home and thought the day was lost. Opened a terminal from my phone and decided to see how long I could last Lasted 2 days. Not just lasted but made $840 What works from a phone: 1. Set up Claude Code through SSH in 10 minutes while riding the subway 2. Get Telegram pushes every time a wallet enters a position 3. Copy a trade with 1 tap without taking out my earbuds 4. Launch scripts by voice through Shortcuts 5. Monitor 3 wallets simultaneously without a single lag 6. Get a morning report at 7 AM as a regular message 7. Rebuild the bot when it crashed while sitting in a cab 8. Check PnL without opening a browser 9. Add a new wallet to tracking in 30 seconds 10. Set up auto-copying without confirmation on verified wallets 11. Get a full strategy breakdown of a wallet through Claude Code in a regular chat And here is what almost killed the deposit: 1. My finger slipped and I entered at twice the planned size. Did not notice for 20 minutes. Got lucky that the position ended up in profit but it could have gone very differently 2. My phone died at 2 AM. Missed the exit signal and the position dropped $110 while I slept. By morning I realized that a power bank is just as much a part of the strategy as the bot itself 3. The delay when copying was 40 seconds. On a 15-minute market that is an eternity. The price moved from 8 cents to 23, and instead of a 12x return I got a 4x. Still profit but you feel the difference immediately Total for 48 hours: +$840. Screen time on the phone: 47 minutes. Never needed the laptop The entire time I was following the same wallet. That is the 1 that was sending me signals at 2 AM: The phone turned out to be a fully functional control panel. But this control panel has no safety switch. And that is worth remembering every time you are tapping with 1 hand in the coffee line
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I spent 48 hours running AI from my phone. Here are 11 things that turned out to be possible and 3 that almost cost me money Forgot my laptop at home and thought the day was lost. Opened a terminal from my phone and decided to see how long I could last Lasted 2 days. Not just lasted but made $840 What works from a phone: 1. Set up Claude Code through SSH in 10 minutes while riding the subway 2. Get Telegram pushes every time a wallet enters a position 3. Copy a trade with 1 tap without taking out my earbuds 4. Launch scripts by voice through Shortcuts 5. Monitor 3 wallets simultaneously without a single lag 6. Get a morning report at 7 AM as a regular message 7. Rebuild the bot when it crashed while sitting in a cab 8. Check PnL without opening a browser 9. Add a new wallet to tracking in 30 seconds 10. Set up auto-copying without confirmation on verified wallets 11. Get a full strategy breakdown of a wallet through Claude Code in a regular chat And here is what almost killed the deposit: 1. My finger slipped and I entered at twice the planned size. Did not notice for 20 minutes. Got lucky that the position ended up in profit but it could have gone very differently 2. My phone died at 2 AM. Missed the exit signal and the position dropped $110 while I slept. By morning I realized that a power bank is just as much a part of the strategy as the bot itself 3. The delay when copying was 40 seconds. On a 15-minute market that is an eternity. The price moved from 8 cents to 23, and instead of a 12x return I got a 4x. Still profit but you feel the difference immediately Total for 48 hours: +$840. Screen time on the phone: 47 minutes. Never needed the laptop The entire time I was following the same wallet. That is the 1 that was sending me signals at 2 AM: The phone turned out to be a fully functional control panel. But this control panel has no safety switch. And that is worth remembering every time you are tapping with 1 hand in the coffee line

Blaze

93,477 views • 5 months ago