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I’m sharing the exact AI trading stack that reportedly turned a simple setup into an incredible trading machine. A Brazilian college dropout built a Polymarket trading bot from his parents’ garage using only open-source AI agents. 📈 Reported results: • $794,000 earned in 14 months • 40,000+ trades •...

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Marry Evan

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12,959 Aufrufe • vor 1 Monat •via X (Twitter)

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I turned Claude Opus 4.7 into a 24/7 trading bot that places real trades, manages stops, and sends me hourly recaps. Save this video. It's the complete tutorial. And to make the setup even easier, I've prepared my exact step-by-step guide. Normally priced at $999, but it's free for 24 hours. To get it: 1. Comment "Money". 2. Like and Retweet this post. 3. Follow me Himanshu Kumar, so i can DM you. You only need Claude Opus 4.7 + 1 laptop + 2 hours to set up once. After that the bot runs forever. Watch the video for the full walkthrough. Use my guide to skip the mistakes and set it up in half the time. Claude will do below for you: Researches the market before you wake up Places real trades via Alpaca when the bell rings Scans midday for new opportunities Manages all your stop-losses automatically Summarise your day after close Sends a full weekly review every Friday No Python process running anywhere. No servers to maintain. Claude IS the bot. 5 cloud routines handle your entire trading day. Memory lives in markdown files on your main branch. Hard strategy rules gate every single order before it fires. You don't touch a single button. You Must Follow me Himanshu Kumar, so i can DM you. Save the video. Grab the guide. Set it up tonight.

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Claude + a laptop + 60 minutes/day = $8,200/month. I could easily charge $999 for this ai trading guide… But for the next 48 hours, it’s 100% FREE. Inside you’ll get: • The exact asset I trade • The full AI workflow • My Claude prompts • How to scale this to $10k/month working ~1 hour/day Most people still use AI for homework and emails. A small group is quietly building income systems with it. Prerequisite: Sign up on Weex + deposit any amount so we can connect the API. Every $100 deposit gets a $40 bonus for a limited time👇 (partner) Like + comment “AI” and follow ZILLIONAIRE (33%)💰💸 I’ll DM you the full guide for FREE.
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Claude + a laptop + 60 minutes/day = $8,200/month. I could easily charge $999 for this ai trading guide… But for the next 48 hours, it’s 100% FREE. Inside you’ll get: • The exact asset I trade • The full AI workflow • My Claude prompts • How to scale this to $10k/month working ~1 hour/day Most people still use AI for homework and emails. A small group is quietly building income systems with it. Prerequisite: Sign up on Weex + deposit any amount so we can connect the API. Every $100 deposit gets a $40 bonus for a limited time👇 (partner) Like + comment “AI” and follow ZILLIONAIRE (33%)💰💸 I’ll DM you the full guide for FREE.

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At the BNB Chain hackathon, CZ 🔶 BNB made several very important points about AI trading (Everything in parentheses is my own view and judgment.) He first said that AI will be involved in trading everywhere. Trading itself is already a huge market: there are 300 million users on Binance alone, and if you add the decentralized ecosystems, that number is not small either. In such a mass-market environment, many different trading strategies can work, with countless different coins, different projects, and different ways to play. But there is a big problem here: building commercial AI trading platforms for retail users is actually very hard. If a trading strategy works very well for one person, once a billion people start using the same strategy, that strategy “might still work, or might stop working.” Take copy trading / follow trading as an example: if you buy first and everyone follows you, the first buyer will perform very well, but the last person to follow may not end up with good results. So, with the exact same strategy and the exact same copy logic, the outcomes can be completely different for different people. (On top of that, every strategy also has its own capital capacity limits.) Teams that can really build strong AI are, with high probability, going to trade with their own money. In today’s world, money itself is already somewhat like a “commodity”; many people have a lot of capital, and it’s actually not that hard to raise funds. If you truly have an algorithm that can make a lot of money, it’s not hard to get money and run your own book. There is really only one situation where you would sell this algorithm to mass-market users: for example, if you charge a $10 monthly subscription and can sell it to one million users, then your $10 million monthly subscription revenue is higher than the profit you could make by trading the strategy yourself. (Here this touches one of our earlier theses: as training AI models becomes relatively easier and the supply of models increases, model companies have more incentive to open-source. By analogy, as the production process of trading strategies is increasingly simplified by AI and the supply of strategies explodes, traders will have stronger incentives to monetize by expanding their influence in other words, by “open-sourcing” their strategies.) Of course, CZ did not say that this model can never work. Another path is to build an AI trading platform that lets users tune different AI algorithms, or very easily assemble their own structures and strategies, so that what each person ends up running is different and better tailored to themselves. Some people will make money, some people will lose money, but the platform still has value because it’s very hard for most people to build an AI trading algorithm from scratch. So there are a lot of trade-offs here; it’s not as simple as saying “once AI shows up, everything automatically gets better.” (This is exactly what we presented at the hackathon: you describe your own strategy in natural language, and the AI automatically generates a workflow. The parameters in that workflow, the models used, the logical structure, the APIs it calls, and even the algorithms it invokes are all customizable. The reasons we think workflows are a good way to do this include: controllable execution paths, Lego-like modular nodes, and better visualization that makes it easier for users to build and adjust their workflows.) Finally, his conclusion was very clear: it’s not that AI will definitely make trading better, and it’s not that AI will definitely make things worse. Rather, no matter what, in the future a huge number of people will use AI to trade. This will be a very large field, and whoever can build the best algorithms will make a lot of money.
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At the BNB Chain hackathon, CZ 🔶 BNB made several very important points about AI trading (Everything in parentheses is my own view and judgment.) He first said that AI will be involved in trading everywhere. Trading itself is already a huge market: there are 300 million users on Binance alone, and if you add the decentralized ecosystems, that number is not small either. In such a mass-market environment, many different trading strategies can work, with countless different coins, different projects, and different ways to play. But there is a big problem here: building commercial AI trading platforms for retail users is actually very hard. If a trading strategy works very well for one person, once a billion people start using the same strategy, that strategy “might still work, or might stop working.” Take copy trading / follow trading as an example: if you buy first and everyone follows you, the first buyer will perform very well, but the last person to follow may not end up with good results. So, with the exact same strategy and the exact same copy logic, the outcomes can be completely different for different people. (On top of that, every strategy also has its own capital capacity limits.) Teams that can really build strong AI are, with high probability, going to trade with their own money. In today’s world, money itself is already somewhat like a “commodity”; many people have a lot of capital, and it’s actually not that hard to raise funds. If you truly have an algorithm that can make a lot of money, it’s not hard to get money and run your own book. There is really only one situation where you would sell this algorithm to mass-market users: for example, if you charge a $10 monthly subscription and can sell it to one million users, then your $10 million monthly subscription revenue is higher than the profit you could make by trading the strategy yourself. (Here this touches one of our earlier theses: as training AI models becomes relatively easier and the supply of models increases, model companies have more incentive to open-source. By analogy, as the production process of trading strategies is increasingly simplified by AI and the supply of strategies explodes, traders will have stronger incentives to monetize by expanding their influence in other words, by “open-sourcing” their strategies.) Of course, CZ did not say that this model can never work. Another path is to build an AI trading platform that lets users tune different AI algorithms, or very easily assemble their own structures and strategies, so that what each person ends up running is different and better tailored to themselves. Some people will make money, some people will lose money, but the platform still has value because it’s very hard for most people to build an AI trading algorithm from scratch. So there are a lot of trade-offs here; it’s not as simple as saying “once AI shows up, everything automatically gets better.” (This is exactly what we presented at the hackathon: you describe your own strategy in natural language, and the AI automatically generates a workflow. The parameters in that workflow, the models used, the logical structure, the APIs it calls, and even the algorithms it invokes are all customizable. The reasons we think workflows are a good way to do this include: controllable execution paths, Lego-like modular nodes, and better visualization that makes it easier for users to build and adjust their workflows.) Finally, his conclusion was very clear: it’s not that AI will definitely make trading better, and it’s not that AI will definitely make things worse. Rather, no matter what, in the future a huge number of people will use AI to trade. This will be a very large field, and whoever can build the best algorithms will make a lot of money.

Tykoo

25,535 Aufrufe • vor 9 Monaten

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MOST AI AGENTS RESET TO ZERO EVERY TIME YOU OPEN A NEW SESSION. Hermes Agent was built to do the opposite. Every task compounds. Every workflow becomes reusable. Every session teaches the next one. That is the core thesis behind Hermes, and it completely changes how AI agents work. Unlike most AI agents built by software tool companies, Hermes was created by the researchers training the Hermes model family itself. Meaning: The same system used internally to generate training data is now open source and available to everyone. One install gives you access to: Claude. GPT. Grok. Local models via Ollama. Telegram, Discord, Slack, iMessage integrations. Custom skills. Persistent memory. CLI control. But the real unlock is the compounding loop: You give Hermes a task. It records every tool call, decision, and result. Then it converts successful workflows into reusable skills automatically. A Hermes setup running for 3 months becomes fundamentally smarter than a fresh install. That’s the big idea. One of the coolest parts: You literally watch the agent evolve in real time from a blank install into a personalized AI operator. Instead of watching Netflix today, spend 28 mins with this. Follow Dami-Defi for more AI systems, agent workflows, and infrastructure alpha.

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ANTHROPIC IS PREPARING TO RELEASE CLAUDE RS - AN AUTOMATED TRADING BOT FOR POLYMARKET Having already automated S&P500 and SPX trading , the company is now making its move into the crypto space. One standout case: a Polymarket bot that grew $1.98 into $1,031,000 over just 4 months. The account behind -> [BoneReader]: -> Mirror its trades like Claude does here: Just add his wallet and start earning: 0xd84c2b6d65dc596f49c7b6aadd6d74ca91e407b9 Here's the breakdown of how it operates: // --> The system tracks hundreds of wallets around the clock. --> It analyzes win rates, entry timing, and position sizing. --> Small test trades are run to identify the most effective strategy. --> Everything is executed automatically with pre-set SL and TP levels. // This is exactly why AI is no longer optional in 2026. Markets move at a pace no human can keep up with and I've been saying this for weeks ngl. Your real advantage lies in speed, deep analysis, and flawless execution. Anyone still trading manually will find their edge gone within months. This is where everything is headed imo. Manual trading is most likely dead and it's not coming back. Like, comment, retweet and I'll drop you an open GitHub link to a similar bot that helped me pull in $2,660 in just 5 days. Follow me so I can DM you directly. Also don't forget to SAVE THIS ALPHA.
0:20

ANTHROPIC IS PREPARING TO RELEASE CLAUDE RS - AN AUTOMATED TRADING BOT FOR POLYMARKET Having already automated S&P500 and SPX trading , the company is now making its move into the crypto space. One standout case: a Polymarket bot that grew $1.98 into $1,031,000 over just 4 months. The account behind -> [BoneReader]: -> Mirror its trades like Claude does here: Just add his wallet and start earning: 0xd84c2b6d65dc596f49c7b6aadd6d74ca91e407b9 Here's the breakdown of how it operates: // --> The system tracks hundreds of wallets around the clock. --> It analyzes win rates, entry timing, and position sizing. --> Small test trades are run to identify the most effective strategy. --> Everything is executed automatically with pre-set SL and TP levels. // This is exactly why AI is no longer optional in 2026. Markets move at a pace no human can keep up with and I've been saying this for weeks ngl. Your real advantage lies in speed, deep analysis, and flawless execution. Anyone still trading manually will find their edge gone within months. This is where everything is headed imo. Manual trading is most likely dead and it's not coming back. Like, comment, retweet and I'll drop you an open GitHub link to a similar bot that helped me pull in $2,660 in just 5 days. Follow me so I can DM you directly. Also don't forget to SAVE THIS ALPHA.

slash1s

154,546 Aufrufe • vor 5 Monaten

A blackjack dealer in Macau got blacklisted from the VIP rooms last spring for counting cards. By August he couldn't get a floor job at any property in Cotai. So he deposit $500, ran a Hermes trading agent on Polymarket and pulled in $881,319 over the next 14 months. His wallet: The casinos taught him one thing - count, size your bet to your edge, walk away when the edge is gone. So he makes 5 trades a day. Not 50. Not 500. Five. And waits for the rest. Here's the actual stack. Claude Opus 4.7 reads the order book nightly, scores every threshold market by Markov persistence x Kelly edge, and surfaces the 2-3 mispriced ones. Hermes Agent by NousResearch executes. A $10/mo Hetzner VPS runs it 24/7. Telegram pings on every fill. Total cost: $10/month. Setup: 30 minutes. No coding. One trade in April: Will Bitcoin reach $90,000? Market said 1.2¢. He put $3,088 on Yes. It hit. +$123,196. A 3,988% return on a single position. The real edge is the nightly self-learning loop. Every midnight, Opus reads the day's trade journal and rewrites MIN_PROB and MIN_EDGE in the .env file. Last week the threshold was 0.87. This week 0.89. Next week maybe 0.91. His version of the bot has rewritten itself 412 times in 14 months. The Macau syndicate couldn't ban him from Polymarket. The bot doesn't sit at a table. It doesn't show a passport. It just hunts the tails. Save this post - if you want to build something of your own based on Hermes. Or just start copying algorithm that has improved itself 412 times:
1:12

A blackjack dealer in Macau got blacklisted from the VIP rooms last spring for counting cards. By August he couldn't get a floor job at any property in Cotai. So he deposit $500, ran a Hermes trading agent on Polymarket and pulled in $881,319 over the next 14 months. His wallet: The casinos taught him one thing - count, size your bet to your edge, walk away when the edge is gone. So he makes 5 trades a day. Not 50. Not 500. Five. And waits for the rest. Here's the actual stack. Claude Opus 4.7 reads the order book nightly, scores every threshold market by Markov persistence x Kelly edge, and surfaces the 2-3 mispriced ones. Hermes Agent by NousResearch executes. A $10/mo Hetzner VPS runs it 24/7. Telegram pings on every fill. Total cost: $10/month. Setup: 30 minutes. No coding. One trade in April: Will Bitcoin reach $90,000? Market said 1.2¢. He put $3,088 on Yes. It hit. +$123,196. A 3,988% return on a single position. The real edge is the nightly self-learning loop. Every midnight, Opus reads the day's trade journal and rewrites MIN_PROB and MIN_EDGE in the .env file. Last week the threshold was 0.87. This week 0.89. Next week maybe 0.91. His version of the bot has rewritten itself 412 times in 14 months. The Macau syndicate couldn't ban him from Polymarket. The bot doesn't sit at a table. It doesn't show a passport. It just hunts the tails. Save this post - if you want to build something of your own based on Hermes. Or just start copying algorithm that has improved itself 412 times:

cvxv666

208,552 Aufrufe • vor 3 Monaten

This trader built a bot with Claude Fable 5 and made $96,000 on Polymarket. Average trade size: $3. The bot trades crypto Up/Down markets using a hybrid strategy that combines two-sided market making, arbitrage, and directional trading. The strategy has 5 steps: 1. Monitors multiple crypto markets continuously The bot tracks BTC, ETH, and SOL price action in real-time across different time windows. 2. Calculates its own fair probability for Up and Down No reliance on Polymarket prices. The bot builds its own model and compares it to the order book. 3. Places orders at prices that keep the combined cost of Up + Down below $1 This is the arbitrage edge. If Up costs 0.52 and Down costs 0.49, total is 1.01. The bot waits. When total drops below 1.00, it enters. 4. Manages the unhedged portion of the position After capturing arbitrage, the bot actively manages remaining exposure instead of holding passively. 5. Keeps directional exposure when its model identifies one outcome as undervalued When the bot sees clear mispricing, it leans into the undervalued side and holds until the edge closes. The entire edge is repeating small wins thousands of times. With an average trade size of $3, the bot captures micro-edges that manual traders ignore. No emotions. No hesitation. Just calculated entries repeated at scale until they compound into serious profit. Most people try to make big bets and predict major moves. This system just identifies tiny mispricings, enters with $3 average positions, and repeats the process until it grows the account. $96K profit built on thousands of $3 trades. The system runs autonomous: → Claude Fable 5 handles 5-step decision logic → Monitors multiple crypto markets 24/7 → Calculates fair probability independent of Polymarket prices → Enters when combined Up + Down cost drops below $1 → Manages unhedged positions actively → Holds directional exposure when model sees clear edge No manual trading. No guessing. Just finding micro-edges and exploiting them thousands of times. 💡 I'm sharing the complete Claude Fable 5 prompt and 5-step hybrid trading workflow. Free for 24 hours. To get it: 1️⃣ Comment the "Claude" 2️⃣ Like and Repost 3️⃣ Follow Himanshu Kumar I'll DM you the setup.
0:32

This trader built a bot with Claude Fable 5 and made $96,000 on Polymarket. Average trade size: $3. The bot trades crypto Up/Down markets using a hybrid strategy that combines two-sided market making, arbitrage, and directional trading. The strategy has 5 steps: 1. Monitors multiple crypto markets continuously The bot tracks BTC, ETH, and SOL price action in real-time across different time windows. 2. Calculates its own fair probability for Up and Down No reliance on Polymarket prices. The bot builds its own model and compares it to the order book. 3. Places orders at prices that keep the combined cost of Up + Down below $1 This is the arbitrage edge. If Up costs 0.52 and Down costs 0.49, total is 1.01. The bot waits. When total drops below 1.00, it enters. 4. Manages the unhedged portion of the position After capturing arbitrage, the bot actively manages remaining exposure instead of holding passively. 5. Keeps directional exposure when its model identifies one outcome as undervalued When the bot sees clear mispricing, it leans into the undervalued side and holds until the edge closes. The entire edge is repeating small wins thousands of times. With an average trade size of $3, the bot captures micro-edges that manual traders ignore. No emotions. No hesitation. Just calculated entries repeated at scale until they compound into serious profit. Most people try to make big bets and predict major moves. This system just identifies tiny mispricings, enters with $3 average positions, and repeats the process until it grows the account. $96K profit built on thousands of $3 trades. The system runs autonomous: → Claude Fable 5 handles 5-step decision logic → Monitors multiple crypto markets 24/7 → Calculates fair probability independent of Polymarket prices → Enters when combined Up + Down cost drops below $1 → Manages unhedged positions actively → Holds directional exposure when model sees clear edge No manual trading. No guessing. Just finding micro-edges and exploiting them thousands of times. 💡 I'm sharing the complete Claude Fable 5 prompt and 5-step hybrid trading workflow. Free for 24 hours. To get it: 1️⃣ Comment the "Claude" 2️⃣ Like and Repost 3️⃣ Follow Himanshu Kumar I'll DM you the setup.

Himanshu Kumar

101,880 Aufrufe • vor 29 Tagen

An engineer at a Chicago HFT shop spent six years building latency arb pipes between CME and NYSE. On May 1st his desk got cut. Severance: $40K. He deposited $3000, ran a Hermes trading agent on Polymarket, and pulled in $236,913 over the next 23 days. His agent wallet: The pit taught him one thing - find where one venue knows something another doesn't, size to the gap, exit before the spread closes. So he made 757 trades a day. Not 7. Not 75. And let the rest expire. Here's the actual stack. Claude Opus 4.7 reads spot momentum off Chainlink, scores every 5-minute BTC market by Markov persistence × Kelly edge Then surfaces the windows where Polymarket hasn't priced in what Binance and Coinbase already confirmed. Hermes Agent by NousResearch executes. A $10/mo Hetzner VPS runs it 24/7. Telegram pings on every fill. Total cost: $10/month. Setup: 30 minutes. No coding. One trade on May 14: Bitcoin Down at 9AM ET. Market said 15.8¢. He put $1,681 on Down. It hit. +$8,974. A 533% return in 47 minutes. The real edge is the nightly self-learning loop. Every midnight, Opus reads the day's trade journal and rewrites MIN_PROB and MIN_EDGE in the .env file. May 2nd the threshold was 0.87. May 12th 0.89. May 23rd 0.91. The bot tightens with the regime. His version of the bot has rewritten itself 187 times in 23 days. The desk that cut him couldn't ban him from Polymarket. The bot doesn't sit in the colo. It doesn't need a leased line. It just reads two endpoints and presses a button. Save this if you want to dig in and understand Hermes. Or just copy this guy trades using TG bot - his algorithm has been perfected 187 times:
0:56

An engineer at a Chicago HFT shop spent six years building latency arb pipes between CME and NYSE. On May 1st his desk got cut. Severance: $40K. He deposited $3000, ran a Hermes trading agent on Polymarket, and pulled in $236,913 over the next 23 days. His agent wallet: The pit taught him one thing - find where one venue knows something another doesn't, size to the gap, exit before the spread closes. So he made 757 trades a day. Not 7. Not 75. And let the rest expire. Here's the actual stack. Claude Opus 4.7 reads spot momentum off Chainlink, scores every 5-minute BTC market by Markov persistence × Kelly edge Then surfaces the windows where Polymarket hasn't priced in what Binance and Coinbase already confirmed. Hermes Agent by NousResearch executes. A $10/mo Hetzner VPS runs it 24/7. Telegram pings on every fill. Total cost: $10/month. Setup: 30 minutes. No coding. One trade on May 14: Bitcoin Down at 9AM ET. Market said 15.8¢. He put $1,681 on Down. It hit. +$8,974. A 533% return in 47 minutes. The real edge is the nightly self-learning loop. Every midnight, Opus reads the day's trade journal and rewrites MIN_PROB and MIN_EDGE in the .env file. May 2nd the threshold was 0.87. May 12th 0.89. May 23rd 0.91. The bot tightens with the regime. His version of the bot has rewritten itself 187 times in 23 days. The desk that cut him couldn't ban him from Polymarket. The bot doesn't sit in the colo. It doesn't need a leased line. It just reads two endpoints and presses a button. Save this if you want to dig in and understand Hermes. Or just copy this guy trades using TG bot - his algorithm has been perfected 187 times:

cvxv666

38,535 Aufrufe • vor 3 Monaten

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 Aufrufe • vor 20 Tagen

🎉 $300 MBP GIVEAWAY – 30 LUCKY WINNERS! 🎉 To celebrate the upcoming launch of our AI-Powered Trading Agent And Our Blockchain, we’re giving away $300 worth of $MBP tokens to 30 lucky users! 💡 What’s Inside MBP: 🧠 Advanced AI Trading Agent ⚡ 500,000+ TPS for real-time scalability 🔒 ZK-Rollups for next-gen security 🌐 Built for Web3, DeFi & global adoption 🧠 MBP AI Agent: What’s Coming Soon? ⚙️ 24/7 Market Analysis 📈 Predictive Trade Execution ⚡ Real-Time Strategy Optimization 🔐 Smart, Secure & Scalable Blockchain Framework 🎁 How to Enter: ✅ Follow us on Twitter - ✅ Join our Telegram - ✅ Watch and like Video - ✅ Like & RT this post ✅ Tag 3 friends in the comments ✅ (Optional) Share a proof post = Boosts your chance to win! 🗓️ Important Dates: 📢 Start Date: July 5, 2025 🎊 End date: July 15, 2025 🔁 Like | 💬 Comment | 📲 Follow for more #MBPtoken #AIAgent #CryptoGiveaway #Web3Trading #DeFi #BlockchainInnovation #LaunchingSoon #MEXC #BitMart #Coinmarketcap #CoinGecko
1:30

🎉 $300 MBP GIVEAWAY – 30 LUCKY WINNERS! 🎉 To celebrate the upcoming launch of our AI-Powered Trading Agent And Our Blockchain, we’re giving away $300 worth of $MBP tokens to 30 lucky users! 💡 What’s Inside MBP: 🧠 Advanced AI Trading Agent ⚡ 500,000+ TPS for real-time scalability 🔒 ZK-Rollups for next-gen security 🌐 Built for Web3, DeFi & global adoption 🧠 MBP AI Agent: What’s Coming Soon? ⚙️ 24/7 Market Analysis 📈 Predictive Trade Execution ⚡ Real-Time Strategy Optimization 🔐 Smart, Secure & Scalable Blockchain Framework 🎁 How to Enter: ✅ Follow us on Twitter - ✅ Join our Telegram - ✅ Watch and like Video - ✅ Like & RT this post ✅ Tag 3 friends in the comments ✅ (Optional) Share a proof post = Boosts your chance to win! 🗓️ Important Dates: 📢 Start Date: July 5, 2025 🎊 End date: July 15, 2025 🔁 Like | 💬 Comment | 📲 Follow for more #MBPtoken #AIAgent #CryptoGiveaway #Web3Trading #DeFi #BlockchainInnovation #LaunchingSoon #MEXC #BitMart #Coinmarketcap #CoinGecko

MBP COIN

85,812 Aufrufe • vor 1 Jahr

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 Aufrufe • vor 9 Tagen