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God of Prompt
RT @rryssf_: MIT researchers just mass-published evidence that the next paradigm after reasoning models isn't bigger context windows ☠️
Recursive Language Models (RLMs) let the model write code to examine, decompose, and recursively call itself over its own input.
the results are genuinely wild. here's the full breakdown:
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RT @rryssf_: MIT researchers just mass-published evidence that the next paradigm after reasoning models isn't bigger context windows ☠️
Recursive Language Models (RLMs) let the model write code to examine, decompose, and recursively call itself over its own input.
the results are genuinely wild. here's the full breakdown:
tweet
Offshore
Video
Bourbon Capital
$AMZN AWS CEO Matt Garman: Utilities don't scale with the level that we need them to scale....so there's probably some steps between here and there where you're going to have to do behind the meter power......we're going to have to fund that ramp up while the world catches up
Congrats Utilities.... you've unlocked a long term Godfather
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$AMZN AWS CEO Matt Garman: Utilities don't scale with the level that we need them to scale....so there's probably some steps between here and there where you're going to have to do behind the meter power......we're going to have to fund that ramp up while the world catches up
Congrats Utilities.... you've unlocked a long term Godfather
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Dimitry Nakhla | Babylon Capital®
Kensho is one of the more under-the-radar assets inside $SPGI.
It’s $SPGI AI and data analytics platform, built to analyze massive, complex datasets across economics, geopolitics, financial markets, and corporate fundamentals—used by asset managers, banks, governments, and enterprises.
While most of the focus is on ratings and indices, Kensho quietly expands $SPGI moat by embedding AI-driven insights deeper into client workflows, increasing switching costs and long-term relevance.
Not flashy, but the kind of capability that can strengthen a toll-booth business over time.
___
3Q 2025 Earnings Call:
“We acquired Kensho back in 2018, including that acquisition since 2018, we have invested over $1B in AI innovation across three developmental stages…
Importantly, our AI innovation serves as a powerful example of our ability to leverage our scale, our expertise and our fiscal discipline. The fact that we made such bold investments early on means that we’ve been able to innovate very efficiently from a financial perspective.”
___
@contextinvestor thank you for the thoughtful comment.
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Kensho is one of the more under-the-radar assets inside $SPGI.
It’s $SPGI AI and data analytics platform, built to analyze massive, complex datasets across economics, geopolitics, financial markets, and corporate fundamentals—used by asset managers, banks, governments, and enterprises.
While most of the focus is on ratings and indices, Kensho quietly expands $SPGI moat by embedding AI-driven insights deeper into client workflows, increasing switching costs and long-term relevance.
Not flashy, but the kind of capability that can strengthen a toll-booth business over time.
___
3Q 2025 Earnings Call:
“We acquired Kensho back in 2018, including that acquisition since 2018, we have invested over $1B in AI innovation across three developmental stages…
Importantly, our AI innovation serves as a powerful example of our ability to leverage our scale, our expertise and our fiscal discipline. The fact that we made such bold investments early on means that we’ve been able to innovate very efficiently from a financial perspective.”
___
@contextinvestor thank you for the thoughtful comment.
I don’t think many investors truly appreciate how deep the moats at $SPGI and $MCO really are.
These aren’t just data businesses — they’re embedded gatekeepers in global capital markets, with network effects, regulatory reliance, & decades of trust that are hard to replicate. tweet
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Benjamin Hernandez😎
Stop over-analyzing every ticker. 📊
Analysis paralysis is a profit killer. I provide clean, simple breakout alerts on WhatsApp so beginners and pros alike can act with total confidence.
Get in✅ https://t.co/71FIJId47G
Keep your trading simple and effective.
$SOFI $HOOD $PLTR
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Stop over-analyzing every ticker. 📊
Analysis paralysis is a profit killer. I provide clean, simple breakout alerts on WhatsApp so beginners and pros alike can act with total confidence.
Get in✅ https://t.co/71FIJId47G
Keep your trading simple and effective.
$SOFI $HOOD $PLTR
⚡ The "Electronic Giant" Choice
Recommendation: $AXTI ~$28.20
AXT Inc. is a "Buy" rated powerhouse with a $1.56B valuation. Today's +17.19% rally is backed by a massive 6.97M shares traded.
Reason calling it: High institutional turnover at $28.20 suggests a long-term bottom. https://t.co/dGsp8x98EG tweet
Offshore
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God of Prompt
Prompting is foundational infrastructure, not a surface-level trick - it only appears to die because success means integration. https://t.co/KidFQLFwnO
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Prompting is foundational infrastructure, not a surface-level trick - it only appears to die because success means integration. https://t.co/KidFQLFwnO
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Javier Blas
RT @JavierBlas: COLUMN: Britrish oil giant BP should suspend its $750 million quarterly share buybacks to give incoming CEO Meg O'Neill (who arrives in April) extra financial breathing room.
@Opinion $BP
https://t.co/23vNRD4Nsw
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RT @JavierBlas: COLUMN: Britrish oil giant BP should suspend its $750 million quarterly share buybacks to give incoming CEO Meg O'Neill (who arrives in April) extra financial breathing room.
@Opinion $BP
https://t.co/23vNRD4Nsw
tweet
Offshore
Video
Moon Dev
The Code Equalizer: Build a Professional Market Maker Bot and Stop Trading Manually
imagine a world where the market crashing actually puts more money in your pocket than a moonshot ever could. this isn't some pipe dream but the reality of a market maker that trades algorithmically every single second of the year. if you've ever felt the sting of a liquidation then you know exactly why manual trading is a rigged game that we are finally going to beat
the secret to directionless profit isn't about guessing the next candle but about becoming the liquidity that everyone else is desperate to buy. within the next few minutes you'll see why most bots fail and how a simple kill switch is the only thing standing between you and a total account wipeout. it's time to stop gambling and start building systems that don't care about the news or the hype
i spent hundreds of thousands on developers for different apps in the past because i was convinced i could never code myself. i believed that programming was for geniuses and that i was destined to lose money through overtrading and painful liquidations. then i realized that code is the great equalizer because it removes the emotion that usually destroys a trader's bankroll
now we are here with fully automated systems trading for me while i live my life. i decided to learn to code live on youtube to show that anyone can iterate their way to success if they just stay consistent. the path from getting liquidated to building a market maker is paved with many small failures and constant adjustments
market making is the adult version of a video game where the goal is to win regardless of which way the player moves. if the price goes up we win and if the price goes down we win and if the price goes sideways we also win. we are looking for steady times to buy and sell because that is where the real money is hidden from the average retail trader
to get started we need to connect to an exchange like phemex using the ccxt library in python. this connection is the bridge between our logic and the actual capital in the market. we set our symbol to ubtc and establish our initial inputs like position size and sleep timers to keep things moving smoothly
most people get excited and jump straight into the trading logic but that is how you lose everything. before we ever place a trade we have to implement a kill switch that monitors our risk levels in real time. if our position size ever exceeds a certain limit like one thousand dollars the bot will immediately close everything out
this safety feature is what i call a size kill and it protects you from those rare moments when the bot goes crazy or the market moves too fast. i would much rather have ten thousand small trades at five hundred dollars than one massive trade that ruins the account. risk management is the boring part that actually makes you wealthy over the long term
once the safety nets are in place we dive into the bid and ask data to see where the market is actually priced. we pull the highest bid and the lowest ask to determine where our orders should sit on the books. our bot is designed to be patient and wait for the market to come to us instead of chasing price like a desperate amateur
but how do we know if the market is too volatile to trade in the first place. this is where we bring in indicators like the average true range to measure the volatility of the assets we are watching. if the volatility is too high then our bot will simply sit on the sidelines and wait for things to calm down
we set up a no trade rule where if the current atr is higher than our predefined threshold we won't enter the market. this keeps us out of dangerous flash crashes where the spread becomes unpredictable and the risk of loss increases. we are looking for a steady environment where we can safely provide liquidity and collect our profits
every twenty seconds our bot loops through the logic to check our open positions and active orders. it pulls the latest ca[...]
The Code Equalizer: Build a Professional Market Maker Bot and Stop Trading Manually
imagine a world where the market crashing actually puts more money in your pocket than a moonshot ever could. this isn't some pipe dream but the reality of a market maker that trades algorithmically every single second of the year. if you've ever felt the sting of a liquidation then you know exactly why manual trading is a rigged game that we are finally going to beat
the secret to directionless profit isn't about guessing the next candle but about becoming the liquidity that everyone else is desperate to buy. within the next few minutes you'll see why most bots fail and how a simple kill switch is the only thing standing between you and a total account wipeout. it's time to stop gambling and start building systems that don't care about the news or the hype
i spent hundreds of thousands on developers for different apps in the past because i was convinced i could never code myself. i believed that programming was for geniuses and that i was destined to lose money through overtrading and painful liquidations. then i realized that code is the great equalizer because it removes the emotion that usually destroys a trader's bankroll
now we are here with fully automated systems trading for me while i live my life. i decided to learn to code live on youtube to show that anyone can iterate their way to success if they just stay consistent. the path from getting liquidated to building a market maker is paved with many small failures and constant adjustments
market making is the adult version of a video game where the goal is to win regardless of which way the player moves. if the price goes up we win and if the price goes down we win and if the price goes sideways we also win. we are looking for steady times to buy and sell because that is where the real money is hidden from the average retail trader
to get started we need to connect to an exchange like phemex using the ccxt library in python. this connection is the bridge between our logic and the actual capital in the market. we set our symbol to ubtc and establish our initial inputs like position size and sleep timers to keep things moving smoothly
most people get excited and jump straight into the trading logic but that is how you lose everything. before we ever place a trade we have to implement a kill switch that monitors our risk levels in real time. if our position size ever exceeds a certain limit like one thousand dollars the bot will immediately close everything out
this safety feature is what i call a size kill and it protects you from those rare moments when the bot goes crazy or the market moves too fast. i would much rather have ten thousand small trades at five hundred dollars than one massive trade that ruins the account. risk management is the boring part that actually makes you wealthy over the long term
once the safety nets are in place we dive into the bid and ask data to see where the market is actually priced. we pull the highest bid and the lowest ask to determine where our orders should sit on the books. our bot is designed to be patient and wait for the market to come to us instead of chasing price like a desperate amateur
but how do we know if the market is too volatile to trade in the first place. this is where we bring in indicators like the average true range to measure the volatility of the assets we are watching. if the volatility is too high then our bot will simply sit on the sidelines and wait for things to calm down
we set up a no trade rule where if the current atr is higher than our predefined threshold we won't enter the market. this keeps us out of dangerous flash crashes where the spread becomes unpredictable and the risk of loss increases. we are looking for a steady environment where we can safely provide liquidity and collect our profits
every twenty seconds our bot loops through the logic to check our open positions and active orders. it pulls the latest ca[...]
Offshore
Moon Dev The Code Equalizer: Build a Professional Market Maker Bot and Stop Trading Manually imagine a world where the market crashing actually puts more money in your pocket than a moonshot ever could. this isn't some pipe dream but the reality of a market…
ndlestick data including the timestamp and open and high and low and close values. we store all of this in a pandas dataframe so we can perform complex calculations on the fly
the heart of our market maker logic relies on calculating the high and the low of our recent price data. we find the maximum high and the minimum low to establish a range for our trades. we also calculate an average price because that helps us determine where the center of the market is at any given moment
if the distance between the high and the low is too large then we trigger our no trading flag. this is a secondary safety measure that works alongside our atr logic to ensure we are only active in a specific range. if the range exceeds eight hundred units then we call the kill switch and exit the market gracefully
now we get to the loopity loop part of the strategy which is where we check the last seventeen bars of data. we are looking to see if we are making higher highs or lower lows which would indicate a strong trend. market makers generally prefer sideways movement so a strong trend is a signal for us to pause our activity
we convert our price data into a list and iterate through it to see if the current low is bigger than any of the past seventeen lows. if it is then we know we are not in a steady state and we set no trading to true. this level of depth is what separates a profitable algorithm from a simple script that just buys and sells blindly
the bot is constantly giving us feedback in the terminal so we can see exactly why it is or isn't trading. it might tell us that no trading was triggered by the high or the low or that we hit our max profit and loss for the day. seeing these messages in real time is like watching a video game play itself to perfection
i iterate on these versions every single day because i want my systems to do better and be more efficient. treat your trading like an adult game where every day you log on you try to find a better wall to hide behind. as long as you manage your risk and don't use too much money at once you can scale your success over time
many people won't share this level of code or logic on the internet because they want to keep the secrets to themselves. i believe in transparency because the more people who learn to code the more we can all escape the trap of manual trading. success in this game is about constant iteration and never being afraid to show your losing trades
if you appreciate this deep dive into market making then you should know that part two is where things get even more interesting. we are going to finish the bot and show exactly how it handles the order placement and the exit strategy. stay focused and keep building because your fully automated future is closer than you think
tweet
the heart of our market maker logic relies on calculating the high and the low of our recent price data. we find the maximum high and the minimum low to establish a range for our trades. we also calculate an average price because that helps us determine where the center of the market is at any given moment
if the distance between the high and the low is too large then we trigger our no trading flag. this is a secondary safety measure that works alongside our atr logic to ensure we are only active in a specific range. if the range exceeds eight hundred units then we call the kill switch and exit the market gracefully
now we get to the loopity loop part of the strategy which is where we check the last seventeen bars of data. we are looking to see if we are making higher highs or lower lows which would indicate a strong trend. market makers generally prefer sideways movement so a strong trend is a signal for us to pause our activity
we convert our price data into a list and iterate through it to see if the current low is bigger than any of the past seventeen lows. if it is then we know we are not in a steady state and we set no trading to true. this level of depth is what separates a profitable algorithm from a simple script that just buys and sells blindly
the bot is constantly giving us feedback in the terminal so we can see exactly why it is or isn't trading. it might tell us that no trading was triggered by the high or the low or that we hit our max profit and loss for the day. seeing these messages in real time is like watching a video game play itself to perfection
i iterate on these versions every single day because i want my systems to do better and be more efficient. treat your trading like an adult game where every day you log on you try to find a better wall to hide behind. as long as you manage your risk and don't use too much money at once you can scale your success over time
many people won't share this level of code or logic on the internet because they want to keep the secrets to themselves. i believe in transparency because the more people who learn to code the more we can all escape the trap of manual trading. success in this game is about constant iteration and never being afraid to show your losing trades
if you appreciate this deep dive into market making then you should know that part two is where things get even more interesting. we are going to finish the bot and show exactly how it handles the order placement and the exit strategy. stay focused and keep building because your fully automated future is closer than you think
tweet