Offshore
Video
Moon Dev
Reveals chasing Jim Simons who ran up 31 billion net worth - mind-blowing inspiration https://t.co/DB0eEr9i2F
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Reveals chasing Jim Simons who ran up 31 billion net worth - mind-blowing inspiration https://t.co/DB0eEr9i2F
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Offshore
Photo
Quartr
$NVDA Q4 2026
"Computing demand is growing exponentially — the agentic AI inflection point has arrived." - Jensen Huang
Revenue +73%
*Data Center +75%
*Gaming +47%
*Professional Vis. +159%
*Automotive +6%
EBIT +84%
*marg. 65% (61)
EPS +98% https://t.co/I2SVMrds8u
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$NVDA Q4 2026
"Computing demand is growing exponentially — the agentic AI inflection point has arrived." - Jensen Huang
Revenue +73%
*Data Center +75%
*Gaming +47%
*Professional Vis. +159%
*Automotive +6%
EBIT +84%
*marg. 65% (61)
EPS +98% https://t.co/I2SVMrds8u
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Offshore
Video
Moon Dev
Inspirational quote about defying authority - this resonates with developers https://t.co/3gw7fVxB36
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Inspirational quote about defying authority - this resonates with developers https://t.co/3gw7fVxB36
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Offshore
Video
Moon Dev
Yo the AI actually made the video and hes losing his mind about it https://t.co/G3u6j2BqG9
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Yo the AI actually made the video and hes losing his mind about it https://t.co/G3u6j2BqG9
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Offshore
Video
Moon Dev
At 350 bucks versus 18 racks this learning curve pays for itself fast https://t.co/RME3WSyxgO
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At 350 bucks versus 18 racks this learning curve pays for itself fast https://t.co/RME3WSyxgO
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Moon Dev
The $1,000,000 Backtest Hack: How Claude Code Sub-Agents Are Replacing Quant Developers
claude code just changed the game so fast that wall street didn't even see the wall hit them. the makers of these ai models probably didn't realize they just handed retail traders a nuclear weapon. it makes building complex trading systems so easy it almost feels like cheating
i used to spend hundreds of thousands of dollars on developers thinking i could never code this myself. most people stay stuck in that trap forever but there is a specific way to bridge the gap without a computer science degree. the secret lies in how you structure your ai sub agents to do the heavy lifting for you
this shift happened because of sub agents which are specialized ai workers that know exactly how to architect a backtest. i can take any indicator code from the web and feed it to my architect to generate five different strategy variations in seconds. it is like having a team of senior developers working for you for the price of a cup of coffee
most traders fail because their code has a tiny bug that makes their results look amazing until they go live. there is one specific setting involving a million dollars that fixes this immediately. if you don't set your position sizing correctly the math will break and your bot will fail when it matters most
learning to code live on youtube was my way of proving that code is the great equalizer. now instead of getting liquidated i have fully automated systems doing the heavy lifting while i sleep. i realized that if i could just get the logic out of my head and into python i could finally stop being exit liquidity
if you are still using the built in backtesting on tradingview you are likely being lied to by the charts. there is a phenomenon called repainting that makes a strategy look like a gold mine when it is actually a dumpster fire. this happens because the chart knows the future price while the candle is still forming
to avoid the math bugs in backtesting libraries you have to set your initial cash and position size to one million. this ensures the decimal math doesn't trip over itself when you are testing high price assets like bitcoin. it sounds simple but this one change prevents the system from crashing during heavy calculations
success in this game isn't about finding one magical bot that prints money forever. it is about a three step workflow that jim simons used to build a thirty billion dollar empire. he understood that you just have to make your systems better and better because everyone else is trying to do the same
you have to get your code off the browser and into a local environment to see the truth. local backtesting allows you to run your logic against twenty five different data sources at once to see if it actually has an edge. testing on a single pair is a recipe for disaster because any strategy can look good on one chart
the rbi method stands for research backtest and implement which is the only way to iterate to success. by constantly feeding new ideas through the sub agent architect you can find the strategies that actually survive the test of time. you research a new indicator then you backtest it across multiple timeframes then you implement the winners
i recently tested a delta ladder strategy that used an adx filter to find high probability setups. the results showed a solid expectancy that most manual traders would dream of having. because the bot has no emotions it just executes the plan while the rest of the world is panic selling
using tools like claude code allows you to bypass the years of frustration i went through. you don't need to be a math genius or go to stanford to build these systems. you just need to be a good researcher who knows how to ask the right questions to your sub agents
when you are running these tests you must avoid using plotting functions because they slow down the process. i found that disabling the browser popups saved me hours of waiting for results. [...]
The $1,000,000 Backtest Hack: How Claude Code Sub-Agents Are Replacing Quant Developers
claude code just changed the game so fast that wall street didn't even see the wall hit them. the makers of these ai models probably didn't realize they just handed retail traders a nuclear weapon. it makes building complex trading systems so easy it almost feels like cheating
i used to spend hundreds of thousands of dollars on developers thinking i could never code this myself. most people stay stuck in that trap forever but there is a specific way to bridge the gap without a computer science degree. the secret lies in how you structure your ai sub agents to do the heavy lifting for you
this shift happened because of sub agents which are specialized ai workers that know exactly how to architect a backtest. i can take any indicator code from the web and feed it to my architect to generate five different strategy variations in seconds. it is like having a team of senior developers working for you for the price of a cup of coffee
most traders fail because their code has a tiny bug that makes their results look amazing until they go live. there is one specific setting involving a million dollars that fixes this immediately. if you don't set your position sizing correctly the math will break and your bot will fail when it matters most
learning to code live on youtube was my way of proving that code is the great equalizer. now instead of getting liquidated i have fully automated systems doing the heavy lifting while i sleep. i realized that if i could just get the logic out of my head and into python i could finally stop being exit liquidity
if you are still using the built in backtesting on tradingview you are likely being lied to by the charts. there is a phenomenon called repainting that makes a strategy look like a gold mine when it is actually a dumpster fire. this happens because the chart knows the future price while the candle is still forming
to avoid the math bugs in backtesting libraries you have to set your initial cash and position size to one million. this ensures the decimal math doesn't trip over itself when you are testing high price assets like bitcoin. it sounds simple but this one change prevents the system from crashing during heavy calculations
success in this game isn't about finding one magical bot that prints money forever. it is about a three step workflow that jim simons used to build a thirty billion dollar empire. he understood that you just have to make your systems better and better because everyone else is trying to do the same
you have to get your code off the browser and into a local environment to see the truth. local backtesting allows you to run your logic against twenty five different data sources at once to see if it actually has an edge. testing on a single pair is a recipe for disaster because any strategy can look good on one chart
the rbi method stands for research backtest and implement which is the only way to iterate to success. by constantly feeding new ideas through the sub agent architect you can find the strategies that actually survive the test of time. you research a new indicator then you backtest it across multiple timeframes then you implement the winners
i recently tested a delta ladder strategy that used an adx filter to find high probability setups. the results showed a solid expectancy that most manual traders would dream of having. because the bot has no emotions it just executes the plan while the rest of the world is panic selling
using tools like claude code allows you to bypass the years of frustration i went through. you don't need to be a math genius or go to stanford to build these systems. you just need to be a good researcher who knows how to ask the right questions to your sub agents
when you are running these tests you must avoid using plotting functions because they slow down the process. i found that disabling the browser popups saved me hours of waiting for results. [...]