Offshore
Photo
Quartr
Edge #74: Reddit
Every day, millions of people research something the
same way: by adding "Reddit" to the end of a Google search. How did a forum become the internet's most trusted source?
Coming to your inbox in a few hours. https://t.co/8VBHd4f31t
tweet
Edge #74: Reddit
Every day, millions of people research something the
same way: by adding "Reddit" to the end of a Google search. How did a forum become the internet's most trusted source?
Coming to your inbox in a few hours. https://t.co/8VBHd4f31t
tweet
Offshore
Video
Moon Dev
The $200/Month Claude Code Tax: How To Get Opus Performance For Exactly $10
you are currently paying a two hundred dollar monthly tax for your ai tools simply because you do not know about the backdoor that the biggest pros are using right now. it feels like anthropic has us all by the throat with their pricing but there is a way to get the exact same performance for about ten bucks a month
i am going to show you exactly how i set this up so i can run six different projects at the same time without worrying about my bank account or my usage limits. if you have been using claude code lately you know it is the most powerful agentic framework out there but the bill at the end of the month can be absolutely soul crushing
i know this because i am a pro user who uses it all day every day to build out my trading systems. most people are stuck paying the standard rates because they think there is no other option but i found a simple way to make your setup twenty times cheaper without losing the quality of your outputs
there is a massive secret in the ai world where models are being distilled and remixed to the point where you can get opus level intelligence for a fraction of the cost. i am talking about a model called minimax m2.5 which is currently sitting in that sweet spot between sonnet and opus level reasoning
this is the kind of alpha that usually stays hidden in private discord chats but i believe that code is the great equalizer and everyone deserves access to these tools. if you are tired of hitting usage limits right when you are in the middle of a flow state then you need to pay close attention to this specific setup
the first loop we need to close is how you actually connect a chinese model to a terminal built by anthropic. it sounds like it would be a technical nightmare but it is actually just a few lines of configuration in your settings file
you essentially just point your terminal at the minimax api endpoint and swap out your secret key. the crazy part is that minimax is literally twenty times cheaper than what you are likely paying right now for the official plan
we are talking about ten dollars for a hundred prompts every five hours which is a limit that almost nobody will ever actually hit in a real coding session. compare that to the two hundred dollar a month barrier and you start to realize how much money you have been leaving on the table
some people will tell you that you should never send your data to certain regions because of privacy concerns but i have a very different take on that. i have ten android phones in my house and i know that everyone is already listening so i prioritize speed and cost over everything else
if a model is cheap and fast and good i am going to use it to build my wealth regardless of where it comes from. that is the reality of the game we are playing and if you want to win you have to be willing to use the most efficient tools available
this brings us to a much deeper loop about how to actually find success in a pvp industry like algorithmic trading. i spent hundreds of thousands of dollars on developers in the past because i thought i was not smart enough to code the systems myself
i was getting liquidated and over trading because i was emotional and i knew that automation was the only way out of the hole. it was only when i decided to learn live on youtube and iterate in public that i finally found the systems that work for me
the secret to my success was not coming up with some genius original idea that nobody else had ever thought of before. it was actually the opposite because i realized that nothing is truly original and that great artists always steal from the best
if you read the book steal like an artist you will understand that the best creators just find things that work and then they remix them until they are better. i applied this exact same logic to my trading through what i call the rbi system which stands for research backtest and implement
most traders fa[...]
The $200/Month Claude Code Tax: How To Get Opus Performance For Exactly $10
you are currently paying a two hundred dollar monthly tax for your ai tools simply because you do not know about the backdoor that the biggest pros are using right now. it feels like anthropic has us all by the throat with their pricing but there is a way to get the exact same performance for about ten bucks a month
i am going to show you exactly how i set this up so i can run six different projects at the same time without worrying about my bank account or my usage limits. if you have been using claude code lately you know it is the most powerful agentic framework out there but the bill at the end of the month can be absolutely soul crushing
i know this because i am a pro user who uses it all day every day to build out my trading systems. most people are stuck paying the standard rates because they think there is no other option but i found a simple way to make your setup twenty times cheaper without losing the quality of your outputs
there is a massive secret in the ai world where models are being distilled and remixed to the point where you can get opus level intelligence for a fraction of the cost. i am talking about a model called minimax m2.5 which is currently sitting in that sweet spot between sonnet and opus level reasoning
this is the kind of alpha that usually stays hidden in private discord chats but i believe that code is the great equalizer and everyone deserves access to these tools. if you are tired of hitting usage limits right when you are in the middle of a flow state then you need to pay close attention to this specific setup
the first loop we need to close is how you actually connect a chinese model to a terminal built by anthropic. it sounds like it would be a technical nightmare but it is actually just a few lines of configuration in your settings file
you essentially just point your terminal at the minimax api endpoint and swap out your secret key. the crazy part is that minimax is literally twenty times cheaper than what you are likely paying right now for the official plan
we are talking about ten dollars for a hundred prompts every five hours which is a limit that almost nobody will ever actually hit in a real coding session. compare that to the two hundred dollar a month barrier and you start to realize how much money you have been leaving on the table
some people will tell you that you should never send your data to certain regions because of privacy concerns but i have a very different take on that. i have ten android phones in my house and i know that everyone is already listening so i prioritize speed and cost over everything else
if a model is cheap and fast and good i am going to use it to build my wealth regardless of where it comes from. that is the reality of the game we are playing and if you want to win you have to be willing to use the most efficient tools available
this brings us to a much deeper loop about how to actually find success in a pvp industry like algorithmic trading. i spent hundreds of thousands of dollars on developers in the past because i thought i was not smart enough to code the systems myself
i was getting liquidated and over trading because i was emotional and i knew that automation was the only way out of the hole. it was only when i decided to learn live on youtube and iterate in public that i finally found the systems that work for me
the secret to my success was not coming up with some genius original idea that nobody else had ever thought of before. it was actually the opposite because i realized that nothing is truly original and that great artists always steal from the best
if you read the book steal like an artist you will understand that the best creators just find things that work and then they remix them until they are better. i applied this exact same logic to my trading through what i call the rbi system which stands for research backtest and implement
most traders fa[...]
Offshore
Moon Dev The $200/Month Claude Code Tax: How To Get Opus Performance For Exactly $10 you are currently paying a two hundred dollar monthly tax for your ai tools simply because you do not know about the backdoor that the biggest pros are using right now. it…
il because they try to be too unique instead of just looking at what the big funds and the phd researchers are already doing. you can go on google scholar or read old trading books and find logic that has worked for decades and then just automate it
this is how i built my entire library of bots and why i am able to stay fully automated instead of staring at charts all day. i take an idea from a podcast or a white paper and i use these cheap ai models to write the code for a backtest in seconds
the beautiful thing about using a setup like the ten dollar minimax backend is that it removes the friction of experimentation. when it costs you pennies to fail you are much more likely to keep trying until you find the strategy that actually prints money
if you are worried about how to switch back to your original setup if things do not work out then do not stress because it is just as easy to undo. you just keep a backup of your original configuration file and you can swap between the expensive and the cheap models whenever you want
i actually keep both ready to go because i like to have a backup plan for when i inevitably hit some kind of weird limit or if one model is acting up. having this kind of flexibility is what separates the people who just play with ai from the people who actually use it to build a career
the industry is filled with people who want to gatekeep information because they are scared of competition but i have found that the more i give away the more i get back. i only found out about this minimax secret because someone in my community shared it with me after seeing how much value i provide
this abundance mindset is the final loop that you need to close if you want to actually make it in this world. when you share your tools and your logic you attract other high level people who will then share their secrets with you in return
you can spend your time trying to be the smartest person in the room or you can spend your time building a system that allows you to be the most persistent. i choose persistence every single day because i know that code is the only thing that can truly level the playing field for a regular person
if you want to stop getting liquidated and start building real systems then you need to stop making excuses about the cost of tools. the backdoor is open and the tools are cheaper than they have ever been so there is nothing stopping you from automating your entire life
i am going to keep building and sharing everything i find because i want to see more people break free from the manual trading trap. just remember that the best time to start was yesterday but the second best time is right now with a ten dollar setup and a dream
tweet
this is how i built my entire library of bots and why i am able to stay fully automated instead of staring at charts all day. i take an idea from a podcast or a white paper and i use these cheap ai models to write the code for a backtest in seconds
the beautiful thing about using a setup like the ten dollar minimax backend is that it removes the friction of experimentation. when it costs you pennies to fail you are much more likely to keep trying until you find the strategy that actually prints money
if you are worried about how to switch back to your original setup if things do not work out then do not stress because it is just as easy to undo. you just keep a backup of your original configuration file and you can swap between the expensive and the cheap models whenever you want
i actually keep both ready to go because i like to have a backup plan for when i inevitably hit some kind of weird limit or if one model is acting up. having this kind of flexibility is what separates the people who just play with ai from the people who actually use it to build a career
the industry is filled with people who want to gatekeep information because they are scared of competition but i have found that the more i give away the more i get back. i only found out about this minimax secret because someone in my community shared it with me after seeing how much value i provide
this abundance mindset is the final loop that you need to close if you want to actually make it in this world. when you share your tools and your logic you attract other high level people who will then share their secrets with you in return
you can spend your time trying to be the smartest person in the room or you can spend your time building a system that allows you to be the most persistent. i choose persistence every single day because i know that code is the only thing that can truly level the playing field for a regular person
if you want to stop getting liquidated and start building real systems then you need to stop making excuses about the cost of tools. the backdoor is open and the tools are cheaper than they have ever been so there is nothing stopping you from automating your entire life
i am going to keep building and sharing everything i find because i want to see more people break free from the manual trading trap. just remember that the best time to start was yesterday but the second best time is right now with a ten dollar setup and a dream
tweet
Offshore
Video
Moon Dev
If you are not using bots to trade in 2026
You’re probably not going to last https://t.co/cKga0OMJhw
tweet
If you are not using bots to trade in 2026
You’re probably not going to last https://t.co/cKga0OMJhw
tweet
Moon Dev
From Hundreds of Thousands Lost to a 24/7 AI Bot: My TCN Model for High Frequency Trading
most people think you need a basement full of liquid cooled servers and a phd from mit to run high frequency trading bots but i just proved that you can build a predatory hft system right from your kitchen table with nothing but an internet connection and some ai. there is a specific reason why 99 percent of manual traders end up as exit liquidity for the big banks and it has everything to do with the temporal convolutional network model i just finished cooking up
the secret sauce starts with a machine learning architecture that has a 73.3 percent area under the curve which basically means it has a massive statistical edge over the rest of the market. when you combine that with a 56 percent win rate you are no longer guessing which way the price will move because you are playing a game of pure probability
i believe that code is the great equalizer because i spent years losing money with liquidations and over trading before i realized that my human emotions were the only thing holding me back. in the past i spent hundreds of thousands of dollars on developers to build apps for me because i was terrified that i would never be able to code myself
it was only after i decided to learn live on youtube and iterate through the pain that i finally reached the point where fully automated systems are trading for me instead of me getting liquidated. you might think the hard part is coming up with the strategy but the real trap is actually in the technical execution of the bot itself
the engine of this hft bot is built on order flow imbalance data which we pull directly from the binance websocket to see exactly where the big orders are hitting. we are not just looking at price action but we are calculating things like ofi velocity and acceleration along with multi level weighted ofi using harmonic waiting
by looking at depth imbalance and volume spread we can predict where the market is going to move in the next few seconds with scary accuracy. this model is so much more powerful than traditional correlation based strategies because it actually understands the micro price structure of the order book
the implementation of these bots requires a strict entry and exit loop where we only use maker orders to avoid paying taker fees and losing our edge to the exchange. we make sure to always fill on the bids or the asks and cancel any orders that do not get filled immediately before putting in new ones
one of the biggest adjustments we made was increasing the max hold time to 300 seconds so the bot has enough room to let the trade play out without getting chopped up by noise. tracking stats across multiple sub accounts is essential because it allows us to incubate different versions of the strategy at the same time
you will run into bugs that seem impossible to fix like when your bot throws a signature error or fails because your anaconda environment is missing a specific package. i spent an hour chasing a ghost in the machine only to realize that the tensorflow environment needed a simple pip install for the extended exchange sdk
this is why most people quit because they expect the path to be easy when in reality you have to be willing to sit in the trenches and debug your code until it works perfectly. building is compounding and every time you solve a technical problem you are adding another layer of armor to your trading system
the rbi system which stands for research backtest and incubate is the only way to move from a theoretical idea to a production ready bot that actually prints. once the model shows a strong edge in backtesting we move it into the incubator phase where it trades small size in the live market to prove its worth
we have different bots running simultaneously where one might use a liquidation filter to avoid high volatility periods while the other trades through everything. it is a constant game of testing and optimizing because the [...]
From Hundreds of Thousands Lost to a 24/7 AI Bot: My TCN Model for High Frequency Trading
most people think you need a basement full of liquid cooled servers and a phd from mit to run high frequency trading bots but i just proved that you can build a predatory hft system right from your kitchen table with nothing but an internet connection and some ai. there is a specific reason why 99 percent of manual traders end up as exit liquidity for the big banks and it has everything to do with the temporal convolutional network model i just finished cooking up
the secret sauce starts with a machine learning architecture that has a 73.3 percent area under the curve which basically means it has a massive statistical edge over the rest of the market. when you combine that with a 56 percent win rate you are no longer guessing which way the price will move because you are playing a game of pure probability
i believe that code is the great equalizer because i spent years losing money with liquidations and over trading before i realized that my human emotions were the only thing holding me back. in the past i spent hundreds of thousands of dollars on developers to build apps for me because i was terrified that i would never be able to code myself
it was only after i decided to learn live on youtube and iterate through the pain that i finally reached the point where fully automated systems are trading for me instead of me getting liquidated. you might think the hard part is coming up with the strategy but the real trap is actually in the technical execution of the bot itself
the engine of this hft bot is built on order flow imbalance data which we pull directly from the binance websocket to see exactly where the big orders are hitting. we are not just looking at price action but we are calculating things like ofi velocity and acceleration along with multi level weighted ofi using harmonic waiting
by looking at depth imbalance and volume spread we can predict where the market is going to move in the next few seconds with scary accuracy. this model is so much more powerful than traditional correlation based strategies because it actually understands the micro price structure of the order book
the implementation of these bots requires a strict entry and exit loop where we only use maker orders to avoid paying taker fees and losing our edge to the exchange. we make sure to always fill on the bids or the asks and cancel any orders that do not get filled immediately before putting in new ones
one of the biggest adjustments we made was increasing the max hold time to 300 seconds so the bot has enough room to let the trade play out without getting chopped up by noise. tracking stats across multiple sub accounts is essential because it allows us to incubate different versions of the strategy at the same time
you will run into bugs that seem impossible to fix like when your bot throws a signature error or fails because your anaconda environment is missing a specific package. i spent an hour chasing a ghost in the machine only to realize that the tensorflow environment needed a simple pip install for the extended exchange sdk
this is why most people quit because they expect the path to be easy when in reality you have to be willing to sit in the trenches and debug your code until it works perfectly. building is compounding and every time you solve a technical problem you are adding another layer of armor to your trading system
the rbi system which stands for research backtest and incubate is the only way to move from a theoretical idea to a production ready bot that actually prints. once the model shows a strong edge in backtesting we move it into the incubator phase where it trades small size in the live market to prove its worth
we have different bots running simultaneously where one might use a liquidation filter to avoid high volatility periods while the other trades through everything. it is a constant game of testing and optimizing because the [...]
Offshore
Moon Dev From Hundreds of Thousands Lost to a 24/7 AI Bot: My TCN Model for High Frequency Trading most people think you need a basement full of liquid cooled servers and a phd from mit to run high frequency trading bots but i just proved that you can build…
market is always evolving and what worked yesterday might not work tomorrow
if you are still trading by hand you are basically bringing a knife to a gunfight where the guns are powered by ai and they never sleep or get tired. the beauty of learning to code is that you no longer have to chase the market because you have built a machine that waits for the perfect setup to appear
i am here live every single day because i want to show you that this level of automation is possible for anyone who is willing to put in the work. take the code and play with it yourself because the more you subtract the noise and focus on the logic the closer you get to true financial freedom
tweet
if you are still trading by hand you are basically bringing a knife to a gunfight where the guns are powered by ai and they never sleep or get tired. the beauty of learning to code is that you no longer have to chase the market because you have built a machine that waits for the perfect setup to appear
i am here live every single day because i want to show you that this level of automation is possible for anyone who is willing to put in the work. take the code and play with it yourself because the more you subtract the noise and focus on the logic the closer you get to true financial freedom
tweet
X (formerly Twitter)
Moon Dev (@MoonDevOnYT) on X
From Hundreds of Thousands Lost to a 24/7 AI Bot: My TCN Model for High Frequency Trading
most people think you need a basement full of liquid cooled servers and a phd from mit to run high frequency trading bots but i just proved that you can build a predatory…
most people think you need a basement full of liquid cooled servers and a phd from mit to run high frequency trading bots but i just proved that you can build a predatory…
Moon Dev
Beyond Generative AI: Building a High-Precision LSTM Trading Bot from Scratch
most people are chasing the shiny objects of generative ai while the real wealth is hidden in the machine learning engines that actually power them. i am going to show you exactly how to build a system that is fundamentally better than any ai assistant you have ever seen.
before we dive into the code i need to tell you about the one year lead i have on the rest of the market. if you start today you are already behind unless you understand the specific data structure i am about to reveal.
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. i spent hundreds of thousands on devs for apps in the past thinking i would not be able to code myself.
with bots you must iterate to success so i decided to learn live and now i have fully automated systems trading for me instead of getting liquidated. everyone is talking about ai agents right now but they are mostly just general purpose tools that lack mathematical precision.
machine learning is actually the precursor to what we call ai today and it is much better for finding the repetitive patterns in the market. if you use the same models as everyone else you will never have an edge which is why the data you feed them is everything.
i have been storing proprietary tick level liquidation data for over a year now which gives me a massive head start on the competition. most traders use open high low close data that a million other people can access easily.
the real alpha is found in the data that others simply do not have or are too lazy to collect themselves. if you can find patterns in the liquidation flow before they are absorbed into the price you can predict the next move with scary accuracy.
we are going to focus on lstms or long short term memory networks because they excel at detecting sequential patterns in order flow. these models can remember what happened sixty minutes ago and use that context to predict what will happen in the next five minutes.
there is a specific feature that most people overlook when they try to build these models and it has nothing to do with price. i call it the whale liquidation ratio and it is one of the five loops i use to keep the model focused on high impact events.
while most people are trying to predict price we are actually trying to predict the probability of a specific move based on liquidation intensity. if you only look at price indicators like rsi or macd you are just doing regular technical analysis which has no edge.
i focus purely on usd liquidation volume and the velocity of those liquidations to see when a cascade is building up. the reason this is better than ai is because we are handcrafting the features to look for specific market anomalies.
one of the biggest mistakes i made early on was faking my data with forward filling or back filling to make the charts look pretty. in the real world that creates data leakage that will blow up your account the moment you go live.
you have to be willing to drop rows with missing information and keep your data as raw and honest as possible. if your model shows ninety five percent accuracy it is almost certainly overfit and you are in for a rude awakening.
there is a rumor that wall street is trying to suppress this type of information because it allows the retail trader to compete on their level. i have seen my own content being pulled because it shows too much of the internal plumbing of the markets.
i am not going to stop sharing this because code belongs to everyone and it is the only way to escape the trap of manual trading. if i do not show up one day it is because the powers that be have finally decided i am too much of a threat.
to build a proper lstm you need to split your data into eighty percent training ten percent validation and ten percent test sets. the validation set is critical because it tells you when[...]
Beyond Generative AI: Building a High-Precision LSTM Trading Bot from Scratch
most people are chasing the shiny objects of generative ai while the real wealth is hidden in the machine learning engines that actually power them. i am going to show you exactly how to build a system that is fundamentally better than any ai assistant you have ever seen.
before we dive into the code i need to tell you about the one year lead i have on the rest of the market. if you start today you are already behind unless you understand the specific data structure i am about to reveal.
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. i spent hundreds of thousands on devs for apps in the past thinking i would not be able to code myself.
with bots you must iterate to success so i decided to learn live and now i have fully automated systems trading for me instead of getting liquidated. everyone is talking about ai agents right now but they are mostly just general purpose tools that lack mathematical precision.
machine learning is actually the precursor to what we call ai today and it is much better for finding the repetitive patterns in the market. if you use the same models as everyone else you will never have an edge which is why the data you feed them is everything.
i have been storing proprietary tick level liquidation data for over a year now which gives me a massive head start on the competition. most traders use open high low close data that a million other people can access easily.
the real alpha is found in the data that others simply do not have or are too lazy to collect themselves. if you can find patterns in the liquidation flow before they are absorbed into the price you can predict the next move with scary accuracy.
we are going to focus on lstms or long short term memory networks because they excel at detecting sequential patterns in order flow. these models can remember what happened sixty minutes ago and use that context to predict what will happen in the next five minutes.
there is a specific feature that most people overlook when they try to build these models and it has nothing to do with price. i call it the whale liquidation ratio and it is one of the five loops i use to keep the model focused on high impact events.
while most people are trying to predict price we are actually trying to predict the probability of a specific move based on liquidation intensity. if you only look at price indicators like rsi or macd you are just doing regular technical analysis which has no edge.
i focus purely on usd liquidation volume and the velocity of those liquidations to see when a cascade is building up. the reason this is better than ai is because we are handcrafting the features to look for specific market anomalies.
one of the biggest mistakes i made early on was faking my data with forward filling or back filling to make the charts look pretty. in the real world that creates data leakage that will blow up your account the moment you go live.
you have to be willing to drop rows with missing information and keep your data as raw and honest as possible. if your model shows ninety five percent accuracy it is almost certainly overfit and you are in for a rude awakening.
there is a rumor that wall street is trying to suppress this type of information because it allows the retail trader to compete on their level. i have seen my own content being pulled because it shows too much of the internal plumbing of the markets.
i am not going to stop sharing this because code belongs to everyone and it is the only way to escape the trap of manual trading. if i do not show up one day it is because the powers that be have finally decided i am too much of a threat.
to build a proper lstm you need to split your data into eighty percent training ten percent validation and ten percent test sets. the validation set is critical because it tells you when[...]
Offshore
Moon Dev Beyond Generative AI: Building a High-Precision LSTM Trading Bot from Scratch most people are chasing the shiny objects of generative ai while the real wealth is hidden in the machine learning engines that actually power them. i am going to show…
to stop training before you start memorizing the noise.
you also need to scale your features using a standard scaler or a min max scaler so the model does not get confused by large numbers. if you feed a model usd volume of five hundred thousand next to a time stamp of twelve it will think the volume is infinitely more important.
the rbi system is how i stay disciplined in this game which stands for research backtest and implement. you cannot just work harder at trading to get better because trading requires patience and a total lack of greed.
most humans are not built for this which is why we must remove the human element entirely through automation. i am not a guy who is afraid to die on a treadmill and if we get on one together you are getting off first.
discipline is doing what you hate to do but doing it like you love it every single day. i spent a decade being scared to code because i thought it was only for geniuses but i was wrong.
you just have to start with the first line and keep iterating until your bots are doing the heavy lifting for you. the prize is not just the money but the freedom from the emotional roller coaster of the charts.
i have documented every step of this journey and provided the roadmap so you do not have to spend years wandering in the dark. if you follow the heart and intuition you have they already know what you truly want to become.
everything else is secondary to the pursuit of your own edge in a world that wants you to follow the pack. stay hungry and stay foolish because that is how we win against the incumbents who have grown fat and lazy.
the fully automated life is waiting for anyone who is willing to learn the language of the machine. through code we can finally achieve the equality that the financial world has tried to keep for itself.
once you close the loop on your first profitable bot you will never want to look at a manual chart again. keep pushing and keep coding until the systems are working for you instead of you working for the systems
tweet
you also need to scale your features using a standard scaler or a min max scaler so the model does not get confused by large numbers. if you feed a model usd volume of five hundred thousand next to a time stamp of twelve it will think the volume is infinitely more important.
the rbi system is how i stay disciplined in this game which stands for research backtest and implement. you cannot just work harder at trading to get better because trading requires patience and a total lack of greed.
most humans are not built for this which is why we must remove the human element entirely through automation. i am not a guy who is afraid to die on a treadmill and if we get on one together you are getting off first.
discipline is doing what you hate to do but doing it like you love it every single day. i spent a decade being scared to code because i thought it was only for geniuses but i was wrong.
you just have to start with the first line and keep iterating until your bots are doing the heavy lifting for you. the prize is not just the money but the freedom from the emotional roller coaster of the charts.
i have documented every step of this journey and provided the roadmap so you do not have to spend years wandering in the dark. if you follow the heart and intuition you have they already know what you truly want to become.
everything else is secondary to the pursuit of your own edge in a world that wants you to follow the pack. stay hungry and stay foolish because that is how we win against the incumbents who have grown fat and lazy.
the fully automated life is waiting for anyone who is willing to learn the language of the machine. through code we can finally achieve the equality that the financial world has tried to keep for itself.
once you close the loop on your first profitable bot you will never want to look at a manual chart again. keep pushing and keep coding until the systems are working for you instead of you working for the systems
tweet
X (formerly Twitter)
Moon Dev (@MoonDevOnYT) on X
Beyond Generative AI: Building a High-Precision LSTM Trading Bot from Scratch
most people are chasing the shiny objects of generative ai while the real wealth is hidden in the machine learning engines that actually power them. i am going to show you exactly…
most people are chasing the shiny objects of generative ai while the real wealth is hidden in the machine learning engines that actually power them. i am going to show you exactly…