AkhenOsiris
It's consensus now, we got that going for us!
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It's consensus now, we got that going for us!
JUNE 2028.
The S&P is down 38% from its highs. Unemployment just printed 10.2%. Private credit is unraveling. Prime mortgages are cracking. AI didn’t disappoint. It exceeded every expectation.
What happened?
https://t.co/JzzwCrbJgS tweet
AkhenOsiris
Are all Citrini readers reading about impending bear market mulling over their discretionary substack subscriptions? 😂
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Are all Citrini readers reading about impending bear market mulling over their discretionary substack subscriptions? 😂
JUNE 2028.
The S&P is down 38% from its highs. Unemployment just printed 10.2%. Private credit is unraveling. Prime mortgages are cracking. AI didn’t disappoint. It exceeded every expectation.
What happened?
https://t.co/JzzwCrbJgS tweet
Offshore
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AkhenOsiris
$CRWD CEO Kurtz responds to Claude Cybersecurity
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$CRWD CEO Kurtz responds to Claude Cybersecurity
Can AI replace security platforms? I asked Claude to build a CrowdStrike replacement.
Claude: "I have to be straightforward: building a replacement for CrowdStrike isn't something I can do here. CrowdStrike is a massive platform built by thousands of engineers over a decade-plus. Its core capabilities include real-time kernel-level endpoint monitoring across millions of devices, a proprietary threat intelligence graph built from trillions of security events...That's not something you can replicate with a script — it's an infrastructure product."
If you want to create AI, you need GPUs. If you want to deploy AI, you need security. That's not a hallucination – it's a fact.
Watch the demo → https://t.co/77OnRmpjUx tweet
Moon Dev
Renting Wall Street Power For $1/Hour: Use Cloud GPUs And Python To Automate Your Trading Edge
no more paid courses needed because the actual secrets to building an edge are hidden in sight within the code you write yourself instead of some guru’s outdated pdf. most people think using ai in trading is just asking a chatbot where bitcoin is going next but they are looking at the wrong data entirely.
my name is moon dev and i believe that code is the great equalizer because through losing money with liquidations and over trading i knew i had to automate my trading. in the past i spent hundreds of thousands on devs for apps thinking i would not be able to code myself but with bots you must iterate to success.
i decided to learn live on youtube and now we are here with fully automated systems trading for me instead of getting liquidated. if you have ever felt that punch in the gut when a position gets wiped out you know why i am obsessed with removing the human heart from the execution.
to actually win in this game you have to follow a process called the rbi system which stands for research backtest and implement. most beginners fail because they try to build a bot immediately without knowing if their strategy even has a statistical edge in the historical data.
the r is for research where you look at academic papers on google scholar or listen to veteran quants on podcasts to find ideas that have worked for decades. once you have a basket of ideas you move to the b which is backtesting to see how that idea would have performed over the last few years.
if the backtest shows you a profit only then do you move to the i for implementation with tiny size to see if it works in the live market. you are probably wondering why everyone else is looking at the same open high low close volume data while getting chopped up every single day.
the real alpha is hidden in unique data specifically liquidation data because when traders get forced out of their positions it creates a massive vacuum that price often fills. everyone else is looking at what already happened while we are looking at the forced selling and buying that is about to drive the next move.
this is where the machine learning comes in because we use something called an lstm or long short term memory neural network to find patterns in these sequences. lstms are specialized brains for numerical time series data which is why they are much better at predicting price moves than something like chatgpt.
chatbots are great for writing code or chatting but they suck at predicting numbers because they were not built for time series data. a transformer model like the one inside cursor or claude looks at text context while our lstm looks at the relationship between liquidation spikes and five minute price targets.
you might be tempted to run these models on your local computer but you will quickly realize that training on 17 million records can take 25 hours or more. i realized that as a trader i am making a trade of either dollars or time when i decide where to train my models.
you can actually rent high end gpus in the cloud like an rtx 4090 or an a100 for less than a dollar an hour and get 20 hours of your life back. training a model 10 times faster than your home computer means you can iterate and find winning strategies while the rest of the world is still waiting for their progress bar.
one of the biggest roadblocks you will hit is when your data has infinite values because some altcoin prices are so close to zero they break the math. we found nearly 8000 infinite targets in our data set which would have caused an infinite loss during training and crashed the entire model.
instead of just deleting that data we implemented a capping strategy to keep the math sane while preserving the raw alpha of those small cap liquidations. we do not want to discriminate against small coins because a 100k liquidation on a tiny asset can still be a massive signal for the broader market.
[...]
Renting Wall Street Power For $1/Hour: Use Cloud GPUs And Python To Automate Your Trading Edge
no more paid courses needed because the actual secrets to building an edge are hidden in sight within the code you write yourself instead of some guru’s outdated pdf. most people think using ai in trading is just asking a chatbot where bitcoin is going next but they are looking at the wrong data entirely.
my name is moon dev and i believe that code is the great equalizer because through losing money with liquidations and over trading i knew i had to automate my trading. in the past i spent hundreds of thousands on devs for apps thinking i would not be able to code myself but with bots you must iterate to success.
i decided to learn live on youtube and now we are here with fully automated systems trading for me instead of getting liquidated. if you have ever felt that punch in the gut when a position gets wiped out you know why i am obsessed with removing the human heart from the execution.
to actually win in this game you have to follow a process called the rbi system which stands for research backtest and implement. most beginners fail because they try to build a bot immediately without knowing if their strategy even has a statistical edge in the historical data.
the r is for research where you look at academic papers on google scholar or listen to veteran quants on podcasts to find ideas that have worked for decades. once you have a basket of ideas you move to the b which is backtesting to see how that idea would have performed over the last few years.
if the backtest shows you a profit only then do you move to the i for implementation with tiny size to see if it works in the live market. you are probably wondering why everyone else is looking at the same open high low close volume data while getting chopped up every single day.
the real alpha is hidden in unique data specifically liquidation data because when traders get forced out of their positions it creates a massive vacuum that price often fills. everyone else is looking at what already happened while we are looking at the forced selling and buying that is about to drive the next move.
this is where the machine learning comes in because we use something called an lstm or long short term memory neural network to find patterns in these sequences. lstms are specialized brains for numerical time series data which is why they are much better at predicting price moves than something like chatgpt.
chatbots are great for writing code or chatting but they suck at predicting numbers because they were not built for time series data. a transformer model like the one inside cursor or claude looks at text context while our lstm looks at the relationship between liquidation spikes and five minute price targets.
you might be tempted to run these models on your local computer but you will quickly realize that training on 17 million records can take 25 hours or more. i realized that as a trader i am making a trade of either dollars or time when i decide where to train my models.
you can actually rent high end gpus in the cloud like an rtx 4090 or an a100 for less than a dollar an hour and get 20 hours of your life back. training a model 10 times faster than your home computer means you can iterate and find winning strategies while the rest of the world is still waiting for their progress bar.
one of the biggest roadblocks you will hit is when your data has infinite values because some altcoin prices are so close to zero they break the math. we found nearly 8000 infinite targets in our data set which would have caused an infinite loss during training and crashed the entire model.
instead of just deleting that data we implemented a capping strategy to keep the math sane while preserving the raw alpha of those small cap liquidations. we do not want to discriminate against small coins because a 100k liquidation on a tiny asset can still be a massive signal for the broader market.
[...]
Offshore
Moon Dev Renting Wall Street Power For $1/Hour: Use Cloud GPUs And Python To Automate Your Trading Edge no more paid courses needed because the actual secrets to building an edge are hidden in sight within the code you write yourself instead of some guru’s…
a massive shift happens when you realize you should look at all crypto liquidations but only predict the price of bitcoin specifically. by filtering 17 million records to just btc targets while keeping global market sentiment we create a much more powerful signal for the king of crypto.
it is easy to feel defeated when the market is rigged against you but code allows you to remove the one thing that always fails which is your emotions. jim simons built a net worth of over 31 billion dollars because he realized there are patterns a robot can trade that a human can never see.
the goal isn’t to find a magic bot that makes you a million dollars overnight because that is just a scam designed to drain your wallet. the goal is to build a swarm of small profitable systems that give you your time and your freedom back so you can be free as a bird.
if you are tired of the red candle emails and the emotional rollercoaster the only way out is through automation and relentless testing of your ideas. just keep making your systems better and better every single day because that is exactly what the top 0.1 percent are doing right now.
tweet
it is easy to feel defeated when the market is rigged against you but code allows you to remove the one thing that always fails which is your emotions. jim simons built a net worth of over 31 billion dollars because he realized there are patterns a robot can trade that a human can never see.
the goal isn’t to find a magic bot that makes you a million dollars overnight because that is just a scam designed to drain your wallet. the goal is to build a swarm of small profitable systems that give you your time and your freedom back so you can be free as a bird.
if you are tired of the red candle emails and the emotional rollercoaster the only way out is through automation and relentless testing of your ideas. just keep making your systems better and better every single day because that is exactly what the top 0.1 percent are doing right now.
tweet
X (formerly Twitter)
Moon Dev (@MoonDevOnYT) on X
Renting Wall Street Power For $1/Hour: Use Cloud GPUs And Python To Automate Your Trading Edge
no more paid courses needed because the actual secrets to building an edge are hidden in sight within the code you write yourself instead of some guru’s outdated…
no more paid courses needed because the actual secrets to building an edge are hidden in sight within the code you write yourself instead of some guru’s outdated…
Offshore
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Moon Dev
closing soon
our all access lifetime pass to every course moondev has on automated trading is closing on thursday
this is everything you need to go from hand trader to fully automated trader
i found something huge with my multi computer ai process and i need to go heads down on that
so i am closing the lifetime pass
if you want in this is your moment
join here https://t.co/EHUr5aAxhF
moondev
tweet
closing soon
our all access lifetime pass to every course moondev has on automated trading is closing on thursday
this is everything you need to go from hand trader to fully automated trader
i found something huge with my multi computer ai process and i need to go heads down on that
so i am closing the lifetime pass
if you want in this is your moment
join here https://t.co/EHUr5aAxhF
moondev
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Offshore
Video
Moon Dev
I’m going to say 1 word and if you understand it
You’re already ahead of 99% of people in the world https://t.co/A8q5xllTHt
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I’m going to say 1 word and if you understand it
You’re already ahead of 99% of people in the world https://t.co/A8q5xllTHt
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Offshore
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Moon Dev
last chance to automate your trading
if you actually want to automate your trading in 2026 this is your absolute last chance
my all access lifetime pass to algo trade camp plus api plus quant app is closing forever
i need to go all in on this multi computer ai for trading project
if you want to learn from me join before it is gone on thursday
get in now https://t.co/EHUr5aAxhF
moondev
tweet
last chance to automate your trading
if you actually want to automate your trading in 2026 this is your absolute last chance
my all access lifetime pass to algo trade camp plus api plus quant app is closing forever
i need to go all in on this multi computer ai for trading project
if you want to learn from me join before it is gone on thursday
get in now https://t.co/EHUr5aAxhF
moondev
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