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Building a backtesting engine that never stops searching. 24/7. Next-gen Backtesting Engine - AUTO MODE update: → Claude scans the web: Reddit, forums, trading communities & research → Grok scans X for new trading concepts and setups → Both feed fresh strategy ideas directly into the platform → The... engine automatically converts them into backtests → Profitable ideas get identified → Bad ideas get rejected → Then the search continues. Some strategies work. Most don't. And that's exactly the point. Instead of manually hunting for the next edge, I'm building a system that can search → test → reject → discover → repeat… 24/7. Still building. Still improving. But this is getting seriously interesting. Would you let an AI research engine search for your next trading edge while you sleep?show more

Herman Trading

12,766 subscribers

18,145 次观看 • 22 天前 •via X (Twitter)

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38 条评论

Ben | Trades 🦍 的头像

Ben | Trades 🦍22 天前

🥹🔥

Herman Trading 的头像

Herman Trading22 天前

The next generation of backtesting 💪

Ben | Trades 🦍 的头像

Ben | Trades 🦍22 天前

You’ll have my fully support about this!! 💪

Herman Trading 的头像

Herman Trading22 天前

Thanks Ben! Means a lot. Expect more in the future!

Ben | Trades 🦍 的头像

Ben | Trades 🦍22 天前

🫡

The Cigarette Man 的头像

The Cigarette Man21 天前

I'm actually building this too. Different stack and my approach is different than yours but yes... working on it.

Herman Trading 的头像

Herman Trading21 天前

Took me a couple of days - and still improving it. Let me know how it goes

All.them.Witches 的头像

All.them.Witches21 天前

how do you make it search 24/7

Vincent Noca 的头像

Vincent Noca21 天前

Spent all last year building mine. Would suggest trying other cheaper models or the costs will be a bottleneck. Had success with Google’s models

Herman Trading 的头像

Herman Trading21 天前

Ohh dont mention that :) Cost of the business.

SpikePanel 的头像

SpikePanel21 天前

👏

Eduar Escobar 的头像

Eduar Escobar21 天前

Great work man, congratulations

Herman Trading 的头像

Herman Trading21 天前

Thanks buddy. Still working on the engine - its a beast already.

Lee 的头像

Lee22 天前

goat

ReboundTrader 的头像

ReboundTrader20 天前

We’ve been building a very similar loop inside TheSystem Next — but the interesting part for us starts after the idea is found. Research → strategy generation → backtest → optimization → walk-forward / out-of-sample validation → robustness filters → reject or promote. The goal isn’t to find as many “profitable backtests” as possible. It’s to automatically kill fragile ideas fast, keep statistically defensible ones, and continuously repeat the process across markets. 24/7 discovery is powerful. 24/7 falsification is probably even more important. @thesystemnext

Charles 的头像

Charles21 天前

Beautiful setup! What platform do you do the backtests on?

Herman Trading 的头像

Herman Trading21 天前

Thanks. OHLCV file from databento

Prashant Gupta 的头像

Prashant Gupta21 天前

can yu share more detials

Herman Trading 的头像

Herman Trading21 天前

SUre- will post a more videos

Prashant Gupta 的头像

Prashant Gupta10 天前

Any further updates

Herman Trading 的头像

Herman Trading10 天前

Of witch feature buddy?

Prashant Gupta 的头像

Prashant Gupta10 天前

I am looking for a profitable strategy which i can execute, do you have practice option selling or buying strategy which is profitable

Herman Trading 的头像

Herman Trading10 天前

You mean an Enigma on a silver plate? I am reading this right?

$kito🐺 的头像

$kito🐺21 天前

Internal autosearch > AI autosearch 1000x AI autosearch > manual 1000x Internal cannot be public, AI can

Herman Trading 的头像

Herman Trading21 天前

Both are in place. Plus auto improve

ProfitAlgos 的头像

ProfitAlgos20 天前

Genuinely interesting build — the search→test→reject→repeat loop is the right shape. A few questions from someone building CFD strategies for ProRealTime: On data: What are you backtesting against? Which instruments, and where do you source the historical data — your broker's feed, a provider (Dukascopy, Polygon, etc.), or something else? And are you testing on cash/CFD prices or futures? It matters a lot whether the "profitable" ideas were found on the same price series you'd actually trade. On timeframes: How does the engine decide which timeframe to test a given idea on? Is it fixed, swept across several, or does the idea itself imply one? A concept can look dead on 15M and alive on 1H purely by chance, so I'm curious whether TF is part of the search space — and if so, how you stop that from just multiplying the false positives.

IConstantStudent 的头像

IConstantStudent22 天前

where do you get historical data for such backtesting?

Herman Trading 的头像

Herman Trading22 天前

databento

Tiago 的头像

Tiago20 天前

While I love the general unblocking potential of AI, I still much prefer deterministic systems. Might be the old school dev in me though (can't believe I'm saying that at my age)... absolutely love it though that we're reaching a point where we can build at the speed of thought!

Herman Trading 的头像

Herman Trading20 天前

Thanks Tiago. Means a lot when coming from an old school dev.

CoinCollector 的头像

CoinCollector21 天前

Really nice, keep posting about it

Herman Trading 的头像

Herman Trading21 天前

Sure- still improving it. Thanks

𝗦𝗼𝗻𝗮𝗻𝗰𝗲 𝗧𝗿𝗮𝗱𝗲𝘀 📈 的头像

𝗦𝗼𝗻𝗮𝗻𝗰𝗲 𝗧𝗿𝗮𝗱𝗲𝘀 📈22 天前

@RHerman you are doing great👍👏

Herman Trading 的头像

Herman Trading22 天前

Thanks buddy. Its just the beginning...

Arkady Mirchin 的头像

Arkady Mirchin21 天前

💪🏼💪🏼

alphabate🐊 的头像

alphabate🐊21 天前

Spent a few months building my trade ideas sandbox. It has 20 years of price history and a rigorous testing methodology. I’ve fed it countless ideas. Some do great in the sample years and collapse from regime change. A few survive and get certified for paper trading. When…

Herman Trading 的头像

Herman Trading21 天前

Thats what its all about - those just few but special ones

SinghTrades 的头像

SinghTrades21 天前

can u just hard code and teach the LLM your own edge with context , rather than dicovering a news one

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Maybe 5 of them had actual setups. The other 10 were boredom. Boredom trades are the most expensive hobby in human history. 3. Leverage. You use 20x-50x on trades where you're not even sure about the direction. That's not trading. That's a casino with a nicer interface. 4. Fees. You're smashing market orders. Paying spread. Paying commission. On 15 trades a day. Your broker makes more money from your account than you do. Think about that. Your broker is profitable on your account. You're not. You're the product. Not the trader. These four things are why 90% of traders lose. Not bad luck. Not the market. You. Save this post and follow Himanshu Kumar because the solution is coming next. ↓ The solution is painfully obvious. Remove yourself from the equation. Not partially. Not "I'll be more disciplined." Not "I'll journal my trades." Not "I'll meditate before trading." Completely remove yourself. Build a bot. Let the bot trade. You go live your life. The bot doesn't feel emotions. 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Spent years building apps and SaaS businesses without writing a single line of code. Hired developers on Upwork instead. Spent hundreds of thousands of dollars paying other people to build what he could have built himself. Because he was scared to learn. That fear cost him years. And hundreds of thousands of dollars. Sound familiar? You're doing the same thing right now. Not with developers. But with your time. You're spending thousands of hours trading manually because you're scared to learn the thing that would make trading automatic. The fear of learning to code is costing you more than any bad trade ever did. Because every month you trade manually is a month of emotional decisions, overleveraged entries, and unnecessary losses that a bot would never make. And here's the thing that should really frustrate you: AI does the hard parts now. You don't need a computer science degree. You don't need to work at a hedge fund. You don't need to be "good at math." Claude Code writes the code for you. You just need to think clearly about trading ideas. That's it. If you can describe a strategy in English, Claude can build it in Python. "I don't know how to code" stopped being a valid excuse in 2024. It's 2026. You're 2 years late on that excuse. Find a new one. Or stop making excuses entirely. Save this post. Follow Himanshu Kumar because I'm showing you how people with zero coding experience are building profitable bots. ↓ The process that actually makes money. Three letters. R. B. I. Research. Backtest. Implement. That's it. That's the entire process. Every single day. Research: Find an idea. A pattern. A market inefficiency. Don't trade it yet. Don't even think about trading it yet. Just research it. Backtest: Test the idea against historical data. Does it work? Not "does it look good on one chart." Does it work across thousands of trades? Across different market conditions? Across in-sample AND out-of-sample data? If no, kill it. Find another idea. If yes, move to step 3. Implement: Build the bot. Deploy it. Paper trade first. Then live with small size. Scale only on evidence. Research. Backtest. Implement. Every day. No exceptions. You know what your current process is? Feel. Enter. Pray. F. E. P. Feel bullish. Enter a trade. Pray it works. That's not a process. That's gambling with a TradingView subscription. RBI is the only process that works. Save this post. Tattoo it on your forearm. Follow Himanshu Kumar for daily RBI breakdowns. ↓ What Claude Code actually does that your manual process can't. You can maybe test 3-5 strategy ideas per week. Manually adjusting parameters. Manually checking results. Manually writing code (badly). Claude Code tests 50-100 ideas per week. With parallel agents running simultaneously. Multiple strategies being built, tested, and validated at the same time. While you sleep. The guy in this video spends 4-8 hours a day building systems with Claude Code. Not trading. Building. Research. Backtest. Implement. Then iterate. Improve. Optimize. Every day the systems get better. Every day the edge compounds. Every day the bots get smarter. While you? You spend 4-8 hours a day staring at charts making the same mistakes you made last month. Same indicators. Same patterns. Same entries. Same losses. He's iterating forward. You're running in circles. Same 8 hours per day. Completely different outcomes. Because he's building systems. And you're feeding a casino. Stop feeding the casino. Start building the machine. Save this post and follow Himanshu Kumar for the Claude Code workflow that iterates strategies while you sleep. ↓ Jim Simons. That's the benchmark. You probably don't know who Jim Simons is. And that tells me everything about how seriously you take trading. Jim Simons. Mathematician. Founded Renaissance Technologies. Built a net worth of $31 billion. 100% from algorithmic trading. Not one single manual trade. Not one "gut feeling" entry. Not one RSI divergence. Not one "smart money concept." Algorithms. Bots. Systems. Data. $31 billion. His fund averaged 66% annual returns for over 30 years. While you're excited about making $200 on a trade that you'll give back tomorrow. The best trader in human history never placed a manual trade in his life. And you think your edge is staring at a 5-minute chart with bloodshot eyes at 2 AM? Your edge is building the system. Not being inside it. Jim Simons is the benchmark. Everything else is noise. Save this post. Follow Himanshu Kumar because I'm building toward the same goal and showing every step publicly. ↓ What you need to understand about patience. This is not get-rich-overnight. The guy in this video says it directly: "This channel is not for people looking to get rich overnight. It's not plug and play. There are no shortcuts. If you're impatient, this probably isn't for you." And that's exactly why most people will fail at this. Because you want results now. Today. This trade. You don't want to spend a week building a bot. You don't want to paper trade for 2 weeks. You don't want to test 50 ideas to find 1 that works. You want to copy someone's bot, run it live with your rent money, and be rich by Friday. That's why you'll be broke by Friday. The guy making $2.3M spent months iterating. Testing. Failing. Rebuilding. Testing again. He was patient when you would have quit. He was calm when you would have panicked. He was consistent when you would have given up. Patience isn't just a virtue in trading. It's the only virtue. Without it, everything else fails. Impatience is the most expensive personality trait in trading. Save this post. Follow Himanshu Kumar and learn to build systems with the patience that actually pays. ↓ The live streams where the real learning happens. The YouTube video is the trailer. The live streams are the movie. Real-time bot building. Real-time questions answered. Real code shown. Real mistakes made and fixed. Not polished highlight reels where everything works perfectly. Actual development. Where things break. Where strategies fail. Where code doesn't compile. Where the fix takes 2 hours. Because that's what real development looks like. And seeing the messy parts is more valuable than any polished tutorial. Because when your bot breaks at 3 AM, you need to know how to fix it. Not just how to celebrate when it works. The streams mix beginner and advanced. Start with how to automate trading. How to use AI for code generation. Then dive into the daily work. Claude Code. Parallel agents. Constant iteration. Live debugging. 4-8 hours of real algorithmic trading development. Live. Uncut. No filter. Most "trading education" shows you the wins. This shows you the work. Save this post. Follow Himanshu Kumar for the stream schedules and breakdowns. ↓ The belief that changes everything. Code is the greatest equalizer. Not money. Not connections. Not a degree. Not where you grew up. Not what school you went to. Code. Once you can build systems, you can build anything. For the rest of your life. A trading bot today. A SaaS product tomorrow. An automation business next month. A completely different life next year. The skill isn't "algorithmic trading." The skill is building systems. And that skill transfers to everything. The guy who can build a trading bot can also build a lead gen tool. Can also build a content pipeline. Can also build a SaaS product. Can also build literally anything that runs on logic and code. One skill. Infinite applications. And AI makes learning it 100x easier than it was 5 years ago. You don't need to be smart. You don't need talent. You need Claude Code and the willingness to sit down and build something instead of consuming content about building something. Building is the skill. Everything else is entertainment disguised as education. Save this post. Follow Himanshu Kumar because I'm showing you how to build, not just how to watch. ↓ If any of this applies to you, pay attention. If you've lost money from overtrading. If you've been liquidated. If you know trading is the vehicle but manual execution keeps crashing you. If you've tried "being more disciplined" and it never lasted more than a week. If you keep saying "next month I'll start automating." If you've spent more money on courses than you've made from trading. There is a better way. It's not a magic indicator. It's not a signal group. It's not a $997 mentorship from a guy who makes money teaching, not trading. It's building your own system. A system that trades without emotion. A system that follows rules without exception. A system that runs while you sleep. A system that compounds while you live your life. That's the answer. It's always been the answer. You've just been too scared to accept that the solution requires building something instead of buying something. ↓ What the next 30 days look like if you actually commit. Week 1: Watch the video. Learn Claude Code basics. Build your first simple strategy. Run your first backtest. Week 2: Iterate. Let Claude improve the strategy. Run Monte Carlo validation. Paper trade. Week 3: Go live with $50-100. Tiny positions. Watch every trade. Compare to paper results. Week 4: Scale based on evidence. Not based on excitement. Not based on one good day. Based on data. 30 days from now you either have a running bot that trades without your emotions destroying every position. Or you're exactly where you are right now. Reading another post. Making another promise. Breaking it by Tuesday. Same 30 days either way. Different actions. Different results. Different life. ↓ Full video tutorial attached. Live bot building with Claude Code. From zero to running Polymarket trading bot. Every line of code. Every decision explained. The video is free. Claude Code is available now. The market is open 24/7. The only thing standing between you and a profitable trading bot is the same thing that's been standing there for months. You. Get out of your own way. Follow Himanshu Kumar for daily AI trading bot breakdowns, live build sessions, and the full RBI process. Save this post. Watch the video. Build the bot. Or keep trading manually and keep losing. The choice has never been easier. And you've never been more stubborn about making the wrong one.

Made $530,000 with Ai Bot that started with $313. Didn't know how to code. Now this bots run 24/7 printing money while sleeping. I've made the exact step-by-step guide to build this Claude Code Polymarket trading bot. Prompts. Code. Risk settings. Paper trading checklist. Everything from zero to running bot. It's free. For 24 hours. After that I'm charging $499 for it. To grab it right now: 1. Comment "Claude Bot" 2. Like and Retweet this post 3. Follow me Himanshu Kumar ( I can't send DMs to non-followers ) I'm DMing everyone who Complete the 3 steps. I spent hundreds of thousands hiring developers because he was too scared to learn. Then learned Claude Code. Built algorithmic trading systems. $313 → $530,000. You have the same tools available right now. And you're using them to ask ChatGPT for Instagram captions. This attached video is a goldmine. Full live walkthrough. Claude Code building actual Polymarket trading bots. From zero. Every line of code. Every decision explained. Now let me break down why everything you're doing in trading is wrong and exactly how to fix it. Save this post. You'll hate yourself if you lose it. ↓ Let's start with why you keep losing money. You already know the answer. You just won't admit it. You overtrade. Every. Single. Day. You see a candle move. You feel something. You enter. No plan. No edge. No reason. Just feelings. Then it goes against you. You feel something else. Panic. Anger. Denial. You move your stop loss. Or you didn't set one at all. "It'll come back." It doesn't come back. So you take another trade. A revenge trade. Bigger size this time. Because you need to "make it back." That one fails too. Now you're emotional. Now you're tilted. Now you're using leverage you have no business touching. 40x. 50x. 100x. On a trade you entered because a candle looked "bullish" and some guy on Twitter said "send it." You get liquidated. Close the laptop. Punch something. Tell yourself you'll be "more disciplined" tomorrow. Tomorrow comes. Same cycle. Same result. Same liquidation. You've been doing this for months. Maybe years. And you still think the problem is your strategy. The problem isn't your strategy. The problem is you. Save this post right now. What I'm about to show you is the only way to remove yourself from the equation. Follow Himanshu Kumar so you don't miss any of this. ↓ Here's what's actually killing your account. It's not the market. The market doesn't care about you. It's not your indicators. RSI works fine. MACD works fine. They all "work." It's not your timeframe. It's not your broker. It's not the "manipulation." It's four things: 1. Emotions. You hold losers because hope feels better than loss. You cut winners because fear feels stronger than greed. You size up when angry. You skip trades when scared. Your emotional state determines your position size. That's insane. And you know it's insane. But you keep doing it. 2. Overtrading. You take 15 trades a day. Maybe 5 of them had actual setups. The other 10 were boredom. Boredom trades are the most expensive hobby in human history. 3. Leverage. You use 20x-50x on trades where you're not even sure about the direction. That's not trading. That's a casino with a nicer interface. 4. Fees. You're smashing market orders. Paying spread. Paying commission. On 15 trades a day. Your broker makes more money from your account than you do. Think about that. Your broker is profitable on your account. You're not. You're the product. Not the trader. These four things are why 90% of traders lose. Not bad luck. Not the market. You. Save this post and follow Himanshu Kumar because the solution is coming next. ↓ The solution is painfully obvious. Remove yourself from the equation. Not partially. Not "I'll be more disciplined." Not "I'll journal my trades." Not "I'll meditate before trading." Completely remove yourself. Build a bot. Let the bot trade. You go live your life. The bot doesn't feel emotions. The bot doesn't overtrade. The bot doesn't use reckless leverage. The bot doesn't smash market orders and bleed fees. The bot follows the rules. Every single time. Without exception. Without "just this once." Without "I have a feeling about this one." Rules in. Execution out. No human in the middle to mess everything up. That's algorithmic trading. And before your ego jumps in with "but I'm different, I have discipline" — No you don't. Your account balance proves you don't. If you had discipline, your account would be green. It's not. So you don't. Accept it. Automate it. Move on. This is the hardest truth in trading. Your discipline will always fail. A bot's won't. Save this post. Follow Himanshu Kumar for the exact bot setup that removes your emotions permanently. ↓ "But I don't know how to code." Neither did he. The guy in this video didn't know how to code for most of his life. Got held back in 7th grade. People counted him out early. Spent years building apps and SaaS businesses without writing a single line of code. Hired developers on Upwork instead. Spent hundreds of thousands of dollars paying other people to build what he could have built himself. Because he was scared to learn. That fear cost him years. And hundreds of thousands of dollars. Sound familiar? You're doing the same thing right now. Not with developers. But with your time. You're spending thousands of hours trading manually because you're scared to learn the thing that would make trading automatic. The fear of learning to code is costing you more than any bad trade ever did. Because every month you trade manually is a month of emotional decisions, overleveraged entries, and unnecessary losses that a bot would never make. And here's the thing that should really frustrate you: AI does the hard parts now. You don't need a computer science degree. You don't need to work at a hedge fund. You don't need to be "good at math." Claude Code writes the code for you. You just need to think clearly about trading ideas. That's it. If you can describe a strategy in English, Claude can build it in Python. "I don't know how to code" stopped being a valid excuse in 2024. It's 2026. You're 2 years late on that excuse. Find a new one. Or stop making excuses entirely. Save this post. Follow Himanshu Kumar because I'm showing you how people with zero coding experience are building profitable bots. ↓ The process that actually makes money. Three letters. R. B. I. Research. Backtest. Implement. That's it. That's the entire process. Every single day. Research: Find an idea. A pattern. A market inefficiency. Don't trade it yet. Don't even think about trading it yet. Just research it. Backtest: Test the idea against historical data. Does it work? Not "does it look good on one chart." Does it work across thousands of trades? Across different market conditions? Across in-sample AND out-of-sample data? If no, kill it. Find another idea. If yes, move to step 3. Implement: Build the bot. Deploy it. Paper trade first. Then live with small size. Scale only on evidence. Research. Backtest. Implement. Every day. No exceptions. You know what your current process is? Feel. Enter. Pray. F. E. P. Feel bullish. Enter a trade. Pray it works. That's not a process. That's gambling with a TradingView subscription. RBI is the only process that works. Save this post. Tattoo it on your forearm. Follow Himanshu Kumar for daily RBI breakdowns. ↓ What Claude Code actually does that your manual process can't. You can maybe test 3-5 strategy ideas per week. Manually adjusting parameters. Manually checking results. Manually writing code (badly). Claude Code tests 50-100 ideas per week. With parallel agents running simultaneously. Multiple strategies being built, tested, and validated at the same time. While you sleep. The guy in this video spends 4-8 hours a day building systems with Claude Code. Not trading. Building. Research. Backtest. Implement. Then iterate. Improve. Optimize. Every day the systems get better. Every day the edge compounds. Every day the bots get smarter. While you? You spend 4-8 hours a day staring at charts making the same mistakes you made last month. Same indicators. Same patterns. Same entries. Same losses. He's iterating forward. You're running in circles. Same 8 hours per day. Completely different outcomes. Because he's building systems. And you're feeding a casino. Stop feeding the casino. Start building the machine. Save this post and follow Himanshu Kumar for the Claude Code workflow that iterates strategies while you sleep. ↓ Jim Simons. That's the benchmark. You probably don't know who Jim Simons is. And that tells me everything about how seriously you take trading. Jim Simons. Mathematician. Founded Renaissance Technologies. Built a net worth of $31 billion. 100% from algorithmic trading. Not one single manual trade. Not one "gut feeling" entry. Not one RSI divergence. Not one "smart money concept." Algorithms. Bots. Systems. Data. $31 billion. His fund averaged 66% annual returns for over 30 years. While you're excited about making $200 on a trade that you'll give back tomorrow. The best trader in human history never placed a manual trade in his life. And you think your edge is staring at a 5-minute chart with bloodshot eyes at 2 AM? Your edge is building the system. Not being inside it. Jim Simons is the benchmark. Everything else is noise. Save this post. Follow Himanshu Kumar because I'm building toward the same goal and showing every step publicly. ↓ What you need to understand about patience. This is not get-rich-overnight. The guy in this video says it directly: "This channel is not for people looking to get rich overnight. It's not plug and play. There are no shortcuts. If you're impatient, this probably isn't for you." And that's exactly why most people will fail at this. Because you want results now. Today. This trade. You don't want to spend a week building a bot. You don't want to paper trade for 2 weeks. You don't want to test 50 ideas to find 1 that works. You want to copy someone's bot, run it live with your rent money, and be rich by Friday. That's why you'll be broke by Friday. The guy making $2.3M spent months iterating. Testing. Failing. Rebuilding. Testing again. He was patient when you would have quit. He was calm when you would have panicked. He was consistent when you would have given up. Patience isn't just a virtue in trading. It's the only virtue. Without it, everything else fails. Impatience is the most expensive personality trait in trading. Save this post. Follow Himanshu Kumar and learn to build systems with the patience that actually pays. ↓ The live streams where the real learning happens. The YouTube video is the trailer. The live streams are the movie. Real-time bot building. Real-time questions answered. Real code shown. Real mistakes made and fixed. Not polished highlight reels where everything works perfectly. Actual development. Where things break. Where strategies fail. Where code doesn't compile. Where the fix takes 2 hours. Because that's what real development looks like. And seeing the messy parts is more valuable than any polished tutorial. Because when your bot breaks at 3 AM, you need to know how to fix it. Not just how to celebrate when it works. The streams mix beginner and advanced. Start with how to automate trading. How to use AI for code generation. Then dive into the daily work. Claude Code. Parallel agents. Constant iteration. Live debugging. 4-8 hours of real algorithmic trading development. Live. Uncut. No filter. Most "trading education" shows you the wins. This shows you the work. Save this post. Follow Himanshu Kumar for the stream schedules and breakdowns. ↓ The belief that changes everything. Code is the greatest equalizer. Not money. Not connections. Not a degree. Not where you grew up. Not what school you went to. Code. Once you can build systems, you can build anything. For the rest of your life. A trading bot today. A SaaS product tomorrow. An automation business next month. A completely different life next year. The skill isn't "algorithmic trading." The skill is building systems. And that skill transfers to everything. The guy who can build a trading bot can also build a lead gen tool. Can also build a content pipeline. Can also build a SaaS product. Can also build literally anything that runs on logic and code. One skill. Infinite applications. And AI makes learning it 100x easier than it was 5 years ago. You don't need to be smart. You don't need talent. You need Claude Code and the willingness to sit down and build something instead of consuming content about building something. Building is the skill. Everything else is entertainment disguised as education. Save this post. Follow Himanshu Kumar because I'm showing you how to build, not just how to watch. ↓ If any of this applies to you, pay attention. If you've lost money from overtrading. If you've been liquidated. If you know trading is the vehicle but manual execution keeps crashing you. If you've tried "being more disciplined" and it never lasted more than a week. If you keep saying "next month I'll start automating." If you've spent more money on courses than you've made from trading. There is a better way. It's not a magic indicator. It's not a signal group. It's not a $997 mentorship from a guy who makes money teaching, not trading. It's building your own system. A system that trades without emotion. A system that follows rules without exception. A system that runs while you sleep. A system that compounds while you live your life. That's the answer. It's always been the answer. You've just been too scared to accept that the solution requires building something instead of buying something. ↓ What the next 30 days look like if you actually commit. Week 1: Watch the video. Learn Claude Code basics. Build your first simple strategy. Run your first backtest. Week 2: Iterate. Let Claude improve the strategy. Run Monte Carlo validation. Paper trade. Week 3: Go live with $50-100. Tiny positions. Watch every trade. Compare to paper results. Week 4: Scale based on evidence. Not based on excitement. Not based on one good day. Based on data. 30 days from now you either have a running bot that trades without your emotions destroying every position. Or you're exactly where you are right now. Reading another post. Making another promise. Breaking it by Tuesday. Same 30 days either way. Different actions. Different results. Different life. ↓ Full video tutorial attached. Live bot building with Claude Code. From zero to running Polymarket trading bot. Every line of code. Every decision explained. The video is free. Claude Code is available now. The market is open 24/7. The only thing standing between you and a profitable trading bot is the same thing that's been standing there for months. You. Get out of your own way. Follow Himanshu Kumar for daily AI trading bot breakdowns, live build sessions, and the full RBI process. Save this post. Watch the video. Build the bot. Or keep trading manually and keep losing. The choice has never been easier. And you've never been more stubborn about making the wrong one.

Himanshu Kumar

38,153 次观看 • 5 个月前

This is fk*ng insane. LuxAlgo is quietly open sourcing every major trading software, one repo at a time and it's 100% FREE. Charting engine. Pine Script® runtime. Indicator encyclopedia. Trading statistics engine. Insider Tracking, Prop Firm Sims, Edge Stats + More The Git Hub includes: → Vela: a full charting engine with a native WebGL2 renderer, 70+ built-in indicators, drawing tools, multi-chart workspace and a plugin SDK. Apache 2.0, commercial use included. → PineTS: run native Pine Script® v6 in Node, Bun, Deno or the browser. 60+ TA functions, live streaming, backtesting, your own data → Vela-pinets: the addon that runs Pine indicators and strategies directly on the chart → Edge-stats: ask "how often did this setup actually work" over your own bars. gap fills, ORB, initial balance, seasonality, anything you can compose. every number ships with its sample size and a 95% confidence interval → luxalgo-mcp-server: the whole encyclopedia of trading & TA as MCP tools your AI agent can call. concepts, formulas, indicators, source code → market-trackers: an open pipeline for the public record of US markets. congress trades, insider filings, 13F holdings, short-sale volume, served to your agent over MCP → prop-firm-sim: runs 10,000 challenge journeys through a firm's exact ruleset and tells you your real pass odds before you pay Every trading platform charges you monthly to rent the same tools. charts, indicators, backtesting, stats. this is all of it, on GitHub. No seat licenses. no vendor lock-in. no telemetry. no waiting for a platform to ship the feature you need. Save this for later. repos below

This is fk*ng insane. LuxAlgo is quietly open sourcing every major trading software, one repo at a time and it's 100% FREE. Charting engine. Pine Script® runtime. Indicator encyclopedia. Trading statistics engine. Insider Tracking, Prop Firm Sims, Edge Stats + More The Git Hub includes: → Vela: a full charting engine with a native WebGL2 renderer, 70+ built-in indicators, drawing tools, multi-chart workspace and a plugin SDK. Apache 2.0, commercial use included. → PineTS: run native Pine Script® v6 in Node, Bun, Deno or the browser. 60+ TA functions, live streaming, backtesting, your own data → Vela-pinets: the addon that runs Pine indicators and strategies directly on the chart → Edge-stats: ask "how often did this setup actually work" over your own bars. gap fills, ORB, initial balance, seasonality, anything you can compose. every number ships with its sample size and a 95% confidence interval → luxalgo-mcp-server: the whole encyclopedia of trading & TA as MCP tools your AI agent can call. concepts, formulas, indicators, source code → market-trackers: an open pipeline for the public record of US markets. congress trades, insider filings, 13F holdings, short-sale volume, served to your agent over MCP → prop-firm-sim: runs 10,000 challenge journeys through a firm's exact ruleset and tells you your real pass odds before you pay Every trading platform charges you monthly to rent the same tools. charts, indicators, backtesting, stats. this is all of it, on GitHub. No seat licenses. no vendor lock-in. no telemetry. no waiting for a platform to ship the feature you need. Save this for later. repos below

Mr. Quant (Jacob)

181,401 次观看 • 8 天前

Wall Street has PhDs, billions in infrastructure, and mathematical models. Retail traders had YouTube and hope. This is why so many feel like they’re always “right” yet still not getting paid. You've seen this evolution firsthand. 233% growth in futures traders, but failure rates still >90%.That gap has just closed. Most trading education sells you their system. We teach you to build your own using institutional tools. Use our Backtesting Engine to test ideas, profile probability scenarios, and enforce risk automatically. You become self-reliant, not dependent. Starts Jan 17th. The Daily Profiler Bootcamp: → Not another "watch me trade" course → Not another "trust me bro, it's high probability but won't show you the numbers" seminar It's 12 weeks of building your trading infrastructure: - Daily Profiler Framework (P12 scenarios + Four Steps execution + HOD/LOD times and probabilities) - Candle Science (OHLC pattern probabilities) - Trading Journal (track your actual performance with the correct measurements for sustainability and survivability of edge) - Business Plan (use our system to build your risk plan, business plan, and trading plan) - Risk Profiling (using the tool to save hours of manual backtesting; understand which metrics to use to determine where your stop and TP should go based on data, not what you were told) Limited spots. First come, first served. Enrollment closes Jan 16th until next quarter. Retweet if you found value in the video. Sign up in comments Austin Clark

The Daily Profiler

17,160 次观看 • 8 个月前

Jev builds the MOST POWERFUL trading agents and someone JUST open sourced jev-trader, a fully working 24/7 trading bot with Jev along with COMPLETE low latency CODEBASE WHAT THIS MEANS FOR YOU - you no longer have to build a trading bot with Jev from scratch, you just clone this and make it yours here is how you make your own Jev trading bot with this repo: 1. clone it and run three commands, it boots straight into dry run mode with real book data, real decisions, and simulated fills so you can watch it think with zero capital 2. drop in your Jev API key and the model starts answering buy or sell on every block with calibrated probabilities in 81 milliseconds 3. swap the book reader for your own venue, the model interface is clean so any order book that returns bids and asks plugs straight in 4. tune the decision cadence and horizon, ask the model every N blocks about the move over the next M, so you control how aggressive the engine trades 5. the hot loop already fits one block with exactly two round trips, one to read the book, one to send the order, nothing else on the path, this is the institutional latency discipline most retail bots never reach 6. plug in the live server and every block, every decision, every fill streams to a public dashboard so you watch your engine run the whole point is this repo hands you HARDEST part for FREE - > the low latency engine the COMPLETE breakdown of how i turned this into hedge fund grade HFT trading system is in my article below:

Jev builds the MOST POWERFUL trading agents and someone JUST open sourced jev-trader, a fully working 24/7 trading bot with Jev along with COMPLETE low latency CODEBASE WHAT THIS MEANS FOR YOU - you no longer have to build a trading bot with Jev from scratch, you just clone this and make it yours here is how you make your own Jev trading bot with this repo: 1. clone it and run three commands, it boots straight into dry run mode with real book data, real decisions, and simulated fills so you can watch it think with zero capital 2. drop in your Jev API key and the model starts answering buy or sell on every block with calibrated probabilities in 81 milliseconds 3. swap the book reader for your own venue, the model interface is clean so any order book that returns bids and asks plugs straight in 4. tune the decision cadence and horizon, ask the model every N blocks about the move over the next M, so you control how aggressive the engine trades 5. the hot loop already fits one block with exactly two round trips, one to read the book, one to send the order, nothing else on the path, this is the institutional latency discipline most retail bots never reach 6. plug in the live server and every block, every decision, every fill streams to a public dashboard so you watch your engine run the whole point is this repo hands you HARDEST part for FREE - > the low latency engine the COMPLETE breakdown of how i turned this into hedge fund grade HFT trading system is in my article below:

Roan

108,685 次观看 • 2 天前

The next internet will not be browsed. It will be operated by agents. OptimAI is building the infrastructure behind that shift. • A research task begins with Search pulling live context from the public web and social web • That context moves into Claw, where the agent can execute directly on your device • Domain knowledge becomes a Persona Agent • Core Node v2 keeps the system running at the edge • And x402 will make access and payment feel native to the flow That is the real shift: - from asking AI questions - to deploying intelligence that can work, learn, and compound. A trader can monitor signals. A founder can prepare reports overnight. A builder can publish a specialized agent once, then let others reuse it. This is what the agent-native internet looks like when it is built from the ground up. Start with OptimAI: • Persona Agent: • Claw / Core Node v2: • Search:

The next internet will not be browsed. It will be operated by agents. OptimAI is building the infrastructure behind that shift. • A research task begins with Search pulling live context from the public web and social web • That context moves into Claw, where the agent can execute directly on your device • Domain knowledge becomes a Persona Agent • Core Node v2 keeps the system running at the edge • And x402 will make access and payment feel native to the flow That is the real shift: - from asking AI questions - to deploying intelligence that can work, learn, and compound. A trader can monitor signals. A founder can prepare reports overnight. A builder can publish a specialized agent once, then let others reuse it. This is what the agent-native internet looks like when it is built from the ground up. Start with OptimAI: • Persona Agent: • Claw / Core Node v2: • Search:

OptimAI Network

18,613 次观看 • 4 个月前

Most market commentary starts with a narrative and then searches for evidence. ORION starts with the data instead. The engine scans decades of market history to find periods that most closely resemble current conditions across price structure, volatility, momentum, macro regime, and market behavior, then maps how those analogs actually evolved afterward. Built for people asking questions like: • “When have markets looked like this before?” • “What typically happened next?” • “Is this move normal, euphoric, or breaking historical precedent?” • “How different is this cycle really?” Features include: • Historical analog search across multiple timeframes • Forward path projections from matched periods • Macro-aware similarity scoring • Time Machine mode to test what the engine would have shown at past moments in real time • Interactive overlays and regime analysis The goal is not prediction theater. It is building a better framework for probabilistic thinking under uncertainty. Try the live app for free at !

Most market commentary starts with a narrative and then searches for evidence. ORION starts with the data instead. The engine scans decades of market history to find periods that most closely resemble current conditions across price structure, volatility, momentum, macro regime, and market behavior, then maps how those analogs actually evolved afterward. Built for people asking questions like: • “When have markets looked like this before?” • “What typically happened next?” • “Is this move normal, euphoric, or breaking historical precedent?” • “How different is this cycle really?” Features include: • Historical analog search across multiple timeframes • Forward path projections from matched periods • Macro-aware similarity scoring • Time Machine mode to test what the engine would have shown at past moments in real time • Interactive overlays and regime analysis The goal is not prediction theater. It is building a better framework for probabilistic thinking under uncertainty. Try the live app for free at !

Orion Engine

101,863 次观看 • 4 个月前

I sat down with matt van horn (Matt Van Horn) and watched him turn claude code into a real-time research engine with his /last30days claude code skill he "fixes" claude code in 30 seconds. this skill pulls what’s actually working right now from x, reddit, and the web, then feeds that context straight into your prompts so you stop building off stale advice. we went from trending rap songs → cold email frameworks → researching clawdbot → planning and building a competitor live, with almost zero hand-written code. pretty nifty little claude code skill share this with a friend / full ep available on The Startup Ideas Podcast (SIP) 🧃 where i will give you ideas/tools/tutorials to make your dreams a reality i will not hold back any alpha and this claude skill is alpha forsure you can install this claude code skill in 30 seconds dream big my friends

I sat down with matt van horn (Matt Van Horn) and watched him turn claude code into a real-time research engine with his /last30days claude code skill he "fixes" claude code in 30 seconds. this skill pulls what’s actually working right now from x, reddit, and the web, then feeds that context straight into your prompts so you stop building off stale advice. we went from trending rap songs → cold email frameworks → researching clawdbot → planning and building a competitor live, with almost zero hand-written code. pretty nifty little claude code skill share this with a friend / full ep available on The Startup Ideas Podcast (SIP) 🧃 where i will give you ideas/tools/tutorials to make your dreams a reality i will not hold back any alpha and this claude skill is alpha forsure you can install this claude code skill in 30 seconds dream big my friends

GREG ISENBERG

177,179 次观看 • 7 个月前

This trader reportedly made $90,000 in one day after using Claude Fable 5 to test 600 strategies in 48 hours. He was not smarter than Wall Street. He simply killed bad ideas thousands of times faster. His old backtesting system needed nearly a week to evaluate one strategy. Claude Fable 5 reportedly reduced the same process to around two minutes, letting him test hundreds of ideas over a single weekend. The results were brutal. 597 strategies failed. Only 3 survived. Those three were then deployed into live Polymarket trading and reportedly generated $90,000 in one day. The real edge was not discovering one brilliant strategy. It was eliminating almost every weak strategy before real money touched the market. His process started with a simple rule: “When the order book leans 70/30 during the final 90 seconds, buy the UP side.” Fable 5 then replayed that rule tick by tick across thousands of settled markets, including real order books, fills, liquidity and slippage. Two minutes later, the system could show whether the idea had any chance of surviving. The three successful strategies now reportedly run through MiroFish, use Kelly-based position sizing and only enter when simulated expectations diverge from the live market. That is what makes AI quant trading powerful. It does not instantly turn someone into a trading genius. It gives them far more attempts to test ideas, reject weak setups and identify the few patterns that remain profitable after realistic simulation. A traditional fund might test 20 strategies in a quarter. He tested 600 in one weekend. The advantage was not better intuition. It was faster elimination.

This trader reportedly made $90,000 in one day after using Claude Fable 5 to test 600 strategies in 48 hours. He was not smarter than Wall Street. He simply killed bad ideas thousands of times faster. His old backtesting system needed nearly a week to evaluate one strategy. Claude Fable 5 reportedly reduced the same process to around two minutes, letting him test hundreds of ideas over a single weekend. The results were brutal. 597 strategies failed. Only 3 survived. Those three were then deployed into live Polymarket trading and reportedly generated $90,000 in one day. The real edge was not discovering one brilliant strategy. It was eliminating almost every weak strategy before real money touched the market. His process started with a simple rule: “When the order book leans 70/30 during the final 90 seconds, buy the UP side.” Fable 5 then replayed that rule tick by tick across thousands of settled markets, including real order books, fills, liquidity and slippage. Two minutes later, the system could show whether the idea had any chance of surviving. The three successful strategies now reportedly run through MiroFish, use Kelly-based position sizing and only enter when simulated expectations diverge from the live market. That is what makes AI quant trading powerful. It does not instantly turn someone into a trading genius. It gives them far more attempts to test ideas, reject weak setups and identify the few patterns that remain profitable after realistic simulation. A traditional fund might test 20 strategies in a quarter. He tested 600 in one weekend. The advantage was not better intuition. It was faster elimination.

Secta

85,453 次观看 • 2 个月前

Anthropic want to launch CLAUDE RS automated trading bot for Polymarket After automating trading of the S&P500 they went further and are entering the cryptocurrency market For example they took a Polymarket bot that turned $1.60 into $1 000 000 in 4 month His account is BoneReader: Copytrading like Claude: How it works: - Claude monitors hundreds of wallets 24/7 - Evaluates win rates, market timing and sizing - Tests micro trades to find the best strategy - Executes automatically with AL and TP rules This is why AI is mandatory in 2026. Markets move faster than humans, I've been telling it for months. Your edge is speed, analysis, and execution. Anyone still clicking buttons manually will lose edge within months. This is the future. Manual trading is probably dead FOREVER. Like comment retweet and I will send you an open GitHub with a similar bot on which I managed to earn $4700 in 3 days Don’t forget to follow so I can DM you

Anthropic want to launch CLAUDE RS automated trading bot for Polymarket After automating trading of the S&P500 they went further and are entering the cryptocurrency market For example they took a Polymarket bot that turned $1.60 into $1 000 000 in 4 month His account is BoneReader: Copytrading like Claude: How it works: - Claude monitors hundreds of wallets 24/7 - Evaluates win rates, market timing and sizing - Tests micro trades to find the best strategy - Executes automatically with AL and TP rules This is why AI is mandatory in 2026. Markets move faster than humans, I've been telling it for months. Your edge is speed, analysis, and execution. Anyone still clicking buttons manually will lose edge within months. This is the future. Manual trading is probably dead FOREVER. Like comment retweet and I will send you an open GitHub with a similar bot on which I managed to earn $4700 in 3 days Don’t forget to follow so I can DM you

AdiiX

67,287 次观看 • 5 个月前

🚨 THIS IS ACTUALLY INSANE Your AI agent can have access to the web. But if it can't reliably read what’s actually on the page, that access is almost useless. We looked at Firecrawl as the web layer for AI agents and the numbers are hard to ignore. The setup is simple: Give it a URL, search query, or website. Firecrawl handles the ugly part — crawling, scraping, rendering, extracting, and turning web content into something an AI model can actually use. The headline numbers: → 173,000+ GitHub stars → Search, scrape and interact with the web at scale → Supports web pages, PDFs, DOCX and other content → Structured data extraction for AI workflows → MCP support for connecting it directly to AI agents The workflow looks like this: Search → Scrape → Crawl → Extract → Feed the agent Three things stand out: 1. Scraping becomes an infrastructure layer Instead of maintaining your own pile of HTTP clients, parsers, browser automation and retry logic, you can treat web access as an API. 2. Agents get more than raw HTML The goal isn't just downloading a webpage. It's turning messy web content into clean context that an LLM can reason over. 3. The same layer works across different agent workflows Research agents. RAG pipelines. AI search. Competitive intelligence. Web-data extraction. The interesting shift: AI agents don't just need better models. They need better access to the information those models are supposed to reason about. Firecrawl is building that layer. Save this repo.

🚨 THIS IS ACTUALLY INSANE Your AI agent can have access to the web. But if it can't reliably read what’s actually on the page, that access is almost useless. We looked at Firecrawl as the web layer for AI agents and the numbers are hard to ignore. The setup is simple: Give it a URL, search query, or website. Firecrawl handles the ugly part — crawling, scraping, rendering, extracting, and turning web content into something an AI model can actually use. The headline numbers: → 173,000+ GitHub stars → Search, scrape and interact with the web at scale → Supports web pages, PDFs, DOCX and other content → Structured data extraction for AI workflows → MCP support for connecting it directly to AI agents The workflow looks like this: Search → Scrape → Crawl → Extract → Feed the agent Three things stand out: 1. Scraping becomes an infrastructure layer Instead of maintaining your own pile of HTTP clients, parsers, browser automation and retry logic, you can treat web access as an API. 2. Agents get more than raw HTML The goal isn't just downloading a webpage. It's turning messy web content into clean context that an LLM can reason over. 3. The same layer works across different agent workflows Research agents. RAG pipelines. AI search. Competitive intelligence. Web-data extraction. The interesting shift: AI agents don't just need better models. They need better access to the information those models are supposed to reason about. Firecrawl is building that layer. Save this repo.

Vikas gupta

18,053 次观看 • 17 天前