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Roan
2.4K posts
Roan
@RohOnChain
building my life around quant systems in prediction markets and crypto
on chain Katılım Eylül 2025
764 Takip Edilen56K Takipçiler
@RohOnChain These are simply incredible possibilities when using Claude correctly. I’m saving this to enjoy later.
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Roan retweetledi
My friend applied to 200 tech jobs in two years. No MIT. No Stanford.
Last month Anthropic offered him $750,000.
I asked him how he broke in from zero.
He sent me the exact video that got him in. A 4-hour course on mastering Claude Code.
I watched it last night.
Halfway through, I realized I've been using Claude Code completely wrong for a year.
Bookmark this and read the article below.
• 00:00 - Claude Code setup
• 49:34 - building apps with Claude Code
• 2:07:52 - prompting Claude Code
• 2:46:16 - Claude Code for production
Avid@Av1dlive
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@maverickarpathy yeah bro, not only in anthropic it will make you 10x more productive at shipping with claude code
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@RohOnChain Learning claude code well gets you into anthropic NEVER KNEW ABOUT THIS ROAN
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@polysuccubus i am sure you will use claude code in much better way after this 4 hours course
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@RohOnChain Looking at the content, it looks just the perfect course required for learning Claude code,
Nice share roan this will definitely help lots of people!
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@RohOnChain The biggest shift isn’t AI replacing engineers - it’s AI changing what “being an engineer” means. The advantage is moving from writing every line of code to knowing how to direct, debug, and scale intelligent systems. The new skill is orchestration
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@RohOnChain 2:07:52 on prompting claude code sounds like the real eye opener moment here
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Google Brain co-founder Andrew Ng explained the roadmap for building AI agents in 5 simple steps:
00:00 - Intro to AI agents and prompting
02:22 - Context and memory for better agent behavior
09:22 - Code execution and building real apps
21:12 - Why agentic workflows beat one-shot prompting
34:07 - Reflection, tool use, planning and multi-agent collaboration
51:24 - The rise of AI agents and agentic reasoning
This is not another AI tools tutorial.
It is a practical roadmap for building useful agents: context, memory, code execution, app building, reflection, tool use, planning, and multi-agent workflows.
Watch it today, then read the article below to learn how to build AI agents that actually work.
Alex@de1lymoon
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Outtake built a long-running agent on Claude that investigates cyber attacks for up to 2 hours unattended. their lead engineer gave away the two hardest lessons:
"prompts are suggestions."
"as this agent runs longer, every single word in that prompt eventually will probably be ignored."
the fix: anything the agent must do every time gets pulled OUT of the prompt and built into the harness - so it never has to think about it, and that attention goes where it can actually improvise.
second lesson, before you write any code:
"you have to be the agent before you can build the agent."
they ran the investigations by hand first to learn what good looks like.
and the part nobody expects - a cyber investigator needed to be half coding agent:
file system + bash → it writes its own tools mid-investigation → routes around broken APIs → finishes the job anyway
Anthropic's Applied AI take: the agent loop has converged to something simple. the power is now entirely in what you give the model - memory, tools, skills - then you get out of the way.
median run: 16 minutes. longest: about 2 hours.
Watch it today ↓
0xDipper@Dipper_pol
Andrej Karpathy builds GPT from scratch in one 2-hour video - before he led pretraining at Anthropic: he starts with an empty file and tiny Shakespeare, and ends generating infinite fake Shakespeare, character by character - the exact same way ChatGPT runs, just token by token. "now we get to the crux of self-attention - this is probably the most important part of this video." then he explains the whole engine: every token emits a query (what am I looking for) and a key (what do I contain), and attention is just them finding each other. by the end he connects it to the real thing: "to train ChatGPT there are roughly two stages: pre-training, then fine-tuning." this one video is the clearest path from "I use ChatGPT" to "I understand how it's built." Watch it today ↓
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A famous dev team just built a new AI terminal for trading Polymarket. And they launched it completely FREE.
It's called @bananagun. Same crew that built one of the biggest trading tools in crypto - now pointed at prediction markets.
> What you get:
Wallet Tracker - import any address, watch every trade live with alerts.
Social Tracker - live X feeds from top Polymarket traders, filtered by market.
Copy Trade - mirror any wallet in ~1 second. Same entry price as the whale.
Leaderboard - top wallets ranked by weekly, monthly, all-time PnL and volume.
Portfolio - track your own positions and PnL across every market you're in.
> Predict: [predict.bananagun.io/?referral=HfUx…]
Every day you scroll past this, someone else is already copying the top wallet and taking the entry you could've had.
Prediction markets are won on speed and information - and right now the traders using this terminal have both, while everyone else is trading blind off the price alone.
Bookmark this page so you don't lose your edge over other traders.
Atenov int.@Atenov_D
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Andrej Karpathy just reveales how LLMs actually thinks:
"GPT-4 knows it failed. It just won't tell you unless you ask."
>80% of GPT-4 errors are recoverable - the model already knows it screwed up.
It has 80 transformer layers and spends the SAME compute on every single token as your brain
In a 20-minute speach at Microsoft Build, Karpathy reveals the full psychology of LLMs.
Worth more than any $500 prompting course you've seen on your timeline.
Ricker@0xRicker
Ex-Google AI Agent Architect just launched a full course on " Harness, Loop, AI Agent Memory system" 90% AI agents are wasting 60%+ of their tokens wrong 00:00 - Ai Agent Memory 12:06 - Harness, Loop 31:18 - Ai Agent System This 50-minute will replace 10 paid courses and guides on Harness and Looping Watch it today, then read how to build proper agent loops in the article below
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Senior Quant Researchers just revealed how they use Generative AI for trading and asset management.
60-minutes. free. By Quant PHD Researchers.
here's what they cover:
• why LLMs hallucinate financial logic (like misapplying the square root of 252)
• agentic AI frameworks for parsing alternative data (10-Ks, Fed speeches)
• evaluating synthetic data via "train on synthetic, test on real" protocols
• the myth of explainability vs 7-billion parameter trading models
worth more than any $900 Quant course.
venus@RitOnchain
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I don't ask AI to predict the market.
I ask it to prove me wrong.
Again.
And again.
Every new prompt is another attempt to break my thesis.
"What am I missing?"
"What's the strongest case for NO?"
"What news could completely flip this market?"
I don't stop when AI agrees with me.
I stop when it can't make a stronger case against my thesis.
That's when I finally have enough confidence to open a position.
This article made me realize I've been using AI the wrong way.
ELG@elg_oleksandr
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A 19 YEAR OLD BUILT A QUANT TRADING WEBSITE THAT THINKS LIKE A HEDGE FUND
most traders stare at charts
he built a system that watches the market for him
Here's what it does:
-> Tracks real time market data across multiple assets
-> Identifies high probability trading setups automatically
-> Analyzes order flow and market structure
-> Backtests strategies before execution
-> Generates quant based trading insights in seconds
-> Visualizes complex data through a beautiful UI
the crazy part?
he didn't build another TradingView clone
he built a quant trading machine
while everyone else is looking for the next 100x trade
His system is:
-> Calculating probabilities
-> Finding statistical edges
-> Filtering bad setups
-> Monitoring the market 24/7
-> Preparing the next opportunity before it appears on your timeline
the edge isn't predicting the future
it is building systems that understand the present better than humans can
the next generation of traders won't spend all day watching charts
they will spend their time building systems that never stop watching them
Bookmark this before quant trading becomes everyone's unfair advantage
0xSlyth@0xSlyth
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Met a quant making mid-seven figures running systematic allocation at a quant fund.
I asked him how he learned to build allocations that don't fall apart the moment market correlation shifts.
He sent me the exact video that got him in. MIT's 79-minute portfolio management lecture.
You won't find anything better about the actual math of diversification, risk parity, and why your weights swing wildly when you feed new data into a raw covariance matrix than this video.
I watched it last night.
Halfway through, I realized I had been running optimizers on raw sample covariance matrices for years and wondering why my allocations destabilized every time the window changed.
Bookmark this and watch today. Then read the article below.
• 00:00 - portfolio construction roadmap: sizing, objectives, and constraints
• 30:23 - two-asset variance and correlation math
• 35:34 - risk parity and why textbook MPT breaks
• 40:20 - rebalancing discipline and why weight drift destroys your allocation
Ruuj@RuujSs
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Someone built a free open-source version of vercel v0. no $149/mo subscription needed.
it's called screenshot-to-code. solo project by abi raja, sitting at 73,276 stars.
drop in any screenshot, mockup or screen recording and it ships working code:
- outputs html+tailwind, react, vue, bootstrap or ionic
- video mode turns a screen recording into a live prototype
- pulls real logos and images out of your screenshot via gemini
- works with gemini 3.1 pro, claude opus 4.8, gpt-5.5
- self-host via one-line docker compose
100% free. open source.
Archive@ArchiveExplorer
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