God of Prompt
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R E A D
T H I S
N O W
O R
Y O U
W I L L
R E G R E T
I T
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https://t.co/ivXRKXJvQg tweet
X (formerly Twitter)
Matt Shumer (@mattshumer_) on X
Something Big Is Happening
Jukan
Rapidus plans to begin mass-producing 2nm wafers at a rate of 6,000 wafers per month by the end of 2027, and ramp up to 25,000 wafers per month by the end of 2028.
According to the business plan Rapidus submitted to Japan's Ministry of Economy, Trade and Industry (METI), mass production of 2-nanometer chips is set to begin in the second half of fiscal year 2027.
The company plans to scale production to four times the 2027 level by 2028.
At the start of mass production in the second half of FY2027, Rapidus plans to produce 6,000 wafers per month, with the goal of expanding capacity to approximately 25,000 wafers per month within one year.
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Rapidus plans to begin mass-producing 2nm wafers at a rate of 6,000 wafers per month by the end of 2027, and ramp up to 25,000 wafers per month by the end of 2028.
According to the business plan Rapidus submitted to Japan's Ministry of Economy, Trade and Industry (METI), mass production of 2-nanometer chips is set to begin in the second half of fiscal year 2027.
The company plans to scale production to four times the 2027 level by 2028.
At the start of mass production in the second half of FY2027, Rapidus plans to produce 6,000 wafers per month, with the goal of expanding capacity to approximately 25,000 wafers per month within one year.
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God of Prompt
RT @godofprompt: The longer you wait to jump into AI, the bigger the gap between you and early adopters.
Not because AI gets harder. Because it gets easier.
More seamless. More plug-and-play. More black box.
Right now you can still see how it works under the hood. Context engineering. Open-source models. Building your own workflows in n8n.
Early internet users who configured dial-up and navigated BBS boards didn’t just understand networking better.
They became the founders, CTOs, and architects who built the companies everyone else ended up working for.
The people who understood HTTP, DNS, and FTP in 1995 weren’t just “tech savvy.”
They were the ones who saw ecommerce, SaaS, and cloud infrastructure coming before those words even existed.
The same thing is happening with AI right now.
The people tinkering with prompts, agents, and open-source models today aren’t wasting time on tools that’ll feel primitive in 5 years.
They’re building the intuition that lets them architect what comes next.
The DIY window doesn’t stay open forever.
tweet
RT @godofprompt: The longer you wait to jump into AI, the bigger the gap between you and early adopters.
Not because AI gets harder. Because it gets easier.
More seamless. More plug-and-play. More black box.
Right now you can still see how it works under the hood. Context engineering. Open-source models. Building your own workflows in n8n.
Early internet users who configured dial-up and navigated BBS boards didn’t just understand networking better.
They became the founders, CTOs, and architects who built the companies everyone else ended up working for.
The people who understood HTTP, DNS, and FTP in 1995 weren’t just “tech savvy.”
They were the ones who saw ecommerce, SaaS, and cloud infrastructure coming before those words even existed.
The same thing is happening with AI right now.
The people tinkering with prompts, agents, and open-source models today aren’t wasting time on tools that’ll feel primitive in 5 years.
They’re building the intuition that lets them architect what comes next.
The DIY window doesn’t stay open forever.
tweet
Offshore
Photo
God of Prompt
Prompt engineering is dead.
"Prompt chaining" is the new meta.
Break one complex prompt into 5 simple prompts that feed into each other.
I tested this for 30 days. Output quality jumped 67%.
Here's how to do it ↓ https://t.co/K3r7wrcJw7
tweet
Prompt engineering is dead.
"Prompt chaining" is the new meta.
Break one complex prompt into 5 simple prompts that feed into each other.
I tested this for 30 days. Output quality jumped 67%.
Here's how to do it ↓ https://t.co/K3r7wrcJw7
tweet
Javier Blas
BREAKING: Libya awards its first oil and gas bidding round in 18 years, with Chevron, ENI, Repsol and several others securing acreage.
Still, the country struggle to attract candidates, with most blocks on offer not receiving a bid. Libya has promised to try again in late 2026.
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BREAKING: Libya awards its first oil and gas bidding round in 18 years, with Chevron, ENI, Repsol and several others securing acreage.
Still, the country struggle to attract candidates, with most blocks on offer not receiving a bid. Libya has promised to try again in late 2026.
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Offshore
Photo
Bourbon Capital
RT @BourbonCap: Are we in a bubble?
Demis Hassabis CEO of $GOOG DeepMind: There aren’t enough compute chips to satisfy demand https://t.co/ega9rwNQg6
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RT @BourbonCap: Are we in a bubble?
Demis Hassabis CEO of $GOOG DeepMind: There aren’t enough compute chips to satisfy demand https://t.co/ega9rwNQg6
The semiconductor ecosystem:
The US dominates design and equipment: $AMAT $LRCX $KLAC $SNPS $CDNS $NVDA $AMD $QCOM $MU $AVGO
Europe dominates lithography: $ASML
South Korea dominates the RAM market: Samsung and SK Hynix
Taiwan produces the most advanced chips: $TSM https://t.co/AtoeBxKr1f tweet
The Transcript
RT @TheTranscript_: $AMZN CFO: "Last year, US Prime members received over 8 billion items with the same or next day, up more than 30% year over year with groceries and everyday essentials making up half of the total items."
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RT @TheTranscript_: $AMZN CFO: "Last year, US Prime members received over 8 billion items with the same or next day, up more than 30% year over year with groceries and everyday essentials making up half of the total items."
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Offshore
Video
Moon Dev
The Fastest Growing Quant Repo On GitHub: Build Your Own Army Of Autonomous AI Trading Agents
getting your hands on the fastest growing trading repository on github is like finding the keys to a vault that never stops printing. most people think they need a math degree to build these things but i am going to show you how a kid from a bedroom can build an empire of autonomous agents
the repo was private for months while i perfected the internal logic and now it is back for anyone who wants to stop getting liquidated. you have to wonder why someone would give away the exact code that runs their entire trading business for free but the answer is simpler than you might think
i believe code is the great equalizer and if we all have the tools we can finally beat the institutions at their own game. once you realize that the institutions are just using better code than you then the path forward becomes very clear
the core of this system is an army of specialized ai agents that handle every single aspect of a professional trading desk. we have a strategy agent that executes the main logic while the risk agent sits over its shoulder to make sure you never lose more than you planned
most traders think one bot is enough but the real secret to 2026 trading is having an entire team of ai agents that talk to each other. what happens when your sentiment agent sees a crash coming but your strategy agent is still trying to go long is where most people get wrecked
that is exactly where the focus agent and the compliance agent come in to keep the whole system from blowing up your account. by separating these duties into different files you create a system that is robust enough to handle the wildest market conditions imaginable
i have been testing every major model from claude to deepseek to see which one actually understands the nuances of the crypto markets. grock is the newest addition to the models folder because the performance we are seeing is finally starting to match the hype
you might be wondering how you can possibly manage all these files if you have never written a line of python in your life. there is a specific way to use these models that allows you to vibe code your way to a functional trading desk without a computer science degree
if you can copy a folder structure and follow a basic readme then you already have everything you need to start building. the barrier to entry has officially been destroyed by ai and now the only thing left is your willingness to iterate
everything lives inside the src folder because organization is the difference between a bot that prints and a bot that crashes. the models folder is where we swap out the brains of the operation whenever a newer and faster llm hits the market to keep us ahead of the curve
there is a hidden danger in just copying code without understanding the underlying risk agent logic. if you do not understand how the base agent connects to the exchange then you are just one api error away from a zero balance or a failed execution
checking the env example and setting up your keys correctly is the first step to making sure your agents actually have the power to execute. this setup phase is the foundation that everything else is built upon so you cannot afford to be lazy here
we have specific agents for every niche including whale watching and sentiment analysis to give you an edge that manual traders can never have. the listing arbitrage agent and the funding agent are there to capture those small inefficiencies that add up over time
these agents are not just pieces of code they are employees that never sleep and never let their emotions get in the way of a trade. i spent hundreds of thousands on developers before i realized i could just build these systems myself with the help of ai
code is the only thing that does not panic when the market starts dropping or get greedy when things are going up. once you automate your first strategy and see it execute without you being ther[...]
The Fastest Growing Quant Repo On GitHub: Build Your Own Army Of Autonomous AI Trading Agents
getting your hands on the fastest growing trading repository on github is like finding the keys to a vault that never stops printing. most people think they need a math degree to build these things but i am going to show you how a kid from a bedroom can build an empire of autonomous agents
the repo was private for months while i perfected the internal logic and now it is back for anyone who wants to stop getting liquidated. you have to wonder why someone would give away the exact code that runs their entire trading business for free but the answer is simpler than you might think
i believe code is the great equalizer and if we all have the tools we can finally beat the institutions at their own game. once you realize that the institutions are just using better code than you then the path forward becomes very clear
the core of this system is an army of specialized ai agents that handle every single aspect of a professional trading desk. we have a strategy agent that executes the main logic while the risk agent sits over its shoulder to make sure you never lose more than you planned
most traders think one bot is enough but the real secret to 2026 trading is having an entire team of ai agents that talk to each other. what happens when your sentiment agent sees a crash coming but your strategy agent is still trying to go long is where most people get wrecked
that is exactly where the focus agent and the compliance agent come in to keep the whole system from blowing up your account. by separating these duties into different files you create a system that is robust enough to handle the wildest market conditions imaginable
i have been testing every major model from claude to deepseek to see which one actually understands the nuances of the crypto markets. grock is the newest addition to the models folder because the performance we are seeing is finally starting to match the hype
you might be wondering how you can possibly manage all these files if you have never written a line of python in your life. there is a specific way to use these models that allows you to vibe code your way to a functional trading desk without a computer science degree
if you can copy a folder structure and follow a basic readme then you already have everything you need to start building. the barrier to entry has officially been destroyed by ai and now the only thing left is your willingness to iterate
everything lives inside the src folder because organization is the difference between a bot that prints and a bot that crashes. the models folder is where we swap out the brains of the operation whenever a newer and faster llm hits the market to keep us ahead of the curve
there is a hidden danger in just copying code without understanding the underlying risk agent logic. if you do not understand how the base agent connects to the exchange then you are just one api error away from a zero balance or a failed execution
checking the env example and setting up your keys correctly is the first step to making sure your agents actually have the power to execute. this setup phase is the foundation that everything else is built upon so you cannot afford to be lazy here
we have specific agents for every niche including whale watching and sentiment analysis to give you an edge that manual traders can never have. the listing arbitrage agent and the funding agent are there to capture those small inefficiencies that add up over time
these agents are not just pieces of code they are employees that never sleep and never let their emotions get in the way of a trade. i spent hundreds of thousands on developers before i realized i could just build these systems myself with the help of ai
code is the only thing that does not panic when the market starts dropping or get greedy when things are going up. once you automate your first strategy and see it execute without you being ther[...]
Offshore
Moon Dev The Fastest Growing Quant Repo On GitHub: Build Your Own Army Of Autonomous AI Trading Agents getting your hands on the fastest growing trading repository on github is like finding the keys to a vault that never stops printing. most people think…
e you will finally understand what true freedom looks like
i challenge you to pull this code and start building your own agents because the infrastructure is already there for you to use. you do not need to be a pro coder to start but you do need to be a builder who is ready to ship and iterate every single day
the world is changing fast and the people who embrace autonomous trading agents are the ones who will be left standing when the dust settles. i will keep updating the github and shipping new features because the mission is to make sure every trader has the chance to automate their success
if you want to join this revolution then go ahead and star the repo so you can follow along as we build out the future of finance. we are just getting started and the agents are only going to get smarter and more efficient from here on out
tweet
i challenge you to pull this code and start building your own agents because the infrastructure is already there for you to use. you do not need to be a pro coder to start but you do need to be a builder who is ready to ship and iterate every single day
the world is changing fast and the people who embrace autonomous trading agents are the ones who will be left standing when the dust settles. i will keep updating the github and shipping new features because the mission is to make sure every trader has the chance to automate their success
if you want to join this revolution then go ahead and star the repo so you can follow along as we build out the future of finance. we are just getting started and the agents are only going to get smarter and more efficient from here on out
tweet
Offshore
Photo
The Transcript
Vertiv CEO: "Significant growth in orders, sales, margins & cash reflects our ability to scale while maintaining a sharp focus on operational execution..Our record backlog provides clear visibility into what we expect to be another year of significant growth
$VRT: +13% AH https://t.co/V20L7fgdcE
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Vertiv CEO: "Significant growth in orders, sales, margins & cash reflects our ability to scale while maintaining a sharp focus on operational execution..Our record backlog provides clear visibility into what we expect to be another year of significant growth
$VRT: +13% AH https://t.co/V20L7fgdcE
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