I’m convinced.
Claude is the most profitable AI tool of 2026.
I use it to create simple digital assets,
it generates $50,000/month.
If you start today, you can make at least $3,000 by the end of July.
Comment “Claude” and I’ll send you a FREE training breaking the entire system down.
(With all the AI prompts)
⏳ Taking this down in 24 hours
MIT JUST LEAKED THE EXACT DOCUMENT WALL STREET QUANT FIRMS USE TO HIRE PEOPLE.
It is called the MIT Quant Bible.
And it covers everything the $500,000 a year quants actually know that you do not.
Here is what is inside:
Probability fundamentals. Conditional probability, Bayes theorem, expected value, variance, joint distributions. The mathematical foundation every trading decision at Jane Street and Citadel is built on.
Stats fundamentals. The Law of Large Numbers. Central Limit Theorem. Confidence intervals. The tools quants use to know when a signal is real and when it is noise.
Quant research and data science. Least squares, regressions, dimensionality reduction. Real case studies from Two Sigma, QuantCo, and CitiBikes.
Quant trading and market making. What market making actually is and how the theory translates into real trading decisions.
And then the part that makes this document worth more than most finance degrees.
A question bank with real interview questions from Jane Street, Virtu Financial, Optiver, Akuna Capital, Citadel, Hudson River Trading, Two Sigma, Five Rings, and SIG.
Not prep questions.
The actual questions these firms ask.
With answers.
The firms charging $50,000 a year for access to this type of preparation are not going to be happy this exists.
Bookmark this before it disappears.
Follow
@cyrilXBT
for every elite resource that gives you access to what the top 1% actually know
All Paid Courses (Free for First 4500 People)
𝗣𝗮𝗶𝗱 𝗖𝗼𝘂𝗿𝘀𝗲 𝗙𝗥𝗘𝗘 (PART - 1)
1. Artificial Intelligence
2. Machine Learning
3. Prompt Engineering
4. Claude,Chatgpt,Grok
5. Data Analytics
6. AWS Certified
7. Data Science
8. BIG DATA
9. Python
10. Ethical Hacking
(72 Hours only )
Like + RT + comment ' Drive '
Must Follow me so I can DM you.
Beginner video: How to install & use Grok Build (made for non-technical SuperGrok and X Premium+ users)
I got so many questions from friends, so I made this simple step-by-step guide.
You’ll see exactly how to:
• Install Grok Build in seconds with one command
• Create real websites
• Use Grok Imagine to auto-generate images & videos
• Run multiple projects at once in different folders
Grok even runs commands for you. No coding experience needed.
Watch the full walkthrough 👇
Anthropic pays $750,000+ a year for engineers who can build LLM architectures from scratch.
This 2-hour Stanford lecture gives you the exact pipeline LLM engineers get paid $750K/year for.
Data + architecture + scaling laws + post-training.
Bookmark it & watch today. Then read article below.
Anthropic pays $750,000+ a year for engineers who know how to build LLMs from scratch.
Stanford just released the exact lecture that teaches it - 1 hour 44 minutes, free, straight from CS229.
Bookmark and watch it this weekend.
It'll teach you more about how ChatGPT & Claude actually work than most people at top AI companies learn in their entire careers.
Creator of C++, Bjarne Stroustrup:
AI-generated code isn't ready — it generates more bugs, more bloat, more security holes, and is nearly impossible to validate
"senior developers are already retiring rather than deal with it"
The problem is that even a small prompt change can shift the entire codebase in unpredictable ways
Alex Xu's System Design Interview is the most recommended book in tech hiring.
Volume 1: $39.99 on Amazon.
Volume 2: $40.00 on Amazon.
Both together: $79.99.
Thousands of engineers have bought them. Millions have been told to buy them. Every tech interview prep list on the internet includes these two books.
In December 2024, one engineer at AWS read both volumes cover to cover.
His name is Gaurav Kumar. CS grad from USC. Day job at Amazon Web Services. He goes by liquidslr on GitHub.
He took notes on every single chapter. Organized them by topic. Linked every section to the original research papers from Amazon, Google, and Discord. Then he pushed the whole thing to GitHub for free.
Then he built a free website to read them on. He named it Pagefy.
Every chapter. Every diagram concept. Every system. Free. Forever.
Here is what is inside:
→ Chapter 1: Scale From Zero To Millions Of Users
→ Chapter 2: Back-of-the-Envelope Estimation
→ Chapter 3: A Framework For System Design Interviews
→ Chapter 4: Design A Rate Limiter
→ Chapter 5: Design Consistent Hashing
→ Chapter 6: Design A Key-Value Store
→ Chapter 7: Design A Unique ID Generator In Distributed Systems
→ Chapter 8: Design A URL Shortener
→ Chapter 9: Design A Web Crawler
→ Chapter 10: Design A Notification System
→ Chapter 11: Design A News Feed System
→ Chapter 12: Design A Chat System
→ Chapter 13: Design A Search Autocomplete System
→ Chapter 14: Design YouTube
→ Chapter 15: Design Google Drive
→ Chapter 16: Proximity Service
And that is Volume 1.
Volume 2 continues:
→ Nearby Friends
→ Google Maps
→ Distributed Message Queue
→ Metrics Monitoring and Alerting System
→ Ad Click Event Aggregation
→ Hotel Reservation System
→ Distributed Email Service
→ S3-like Object Storage
→ Real-Time Gaming Leaderboard
→ Payment System
→ Digital Wallet
→ Stock Exchange
Here is why this matters:
Every FAANG company asks system design questions. Google. Amazon. Meta. Microsoft. Apple. Netflix. Uber. Airbnb. Stripe.
The median software engineer at these companies makes $226,000. Senior makes $312,000. Staff makes $457,000.
The interview that stands between you and that salary is system design.
The book that everyone says to read costs $79.99. The official video course on ByteByteGo costs $499 for lifetime or $189 a year. Hello Interview charges $279 lifetime. Educative charges $59 a month.
These notes cover the same 28 chapters as the books. For $0.
Not a summary. Not a cheatsheet. Structured notes with diagrams, key concepts, and source papers for every chapter of both volumes. Browse them as a website at https://t.co/dJGyoX8MBH. Search any topic. Jump to any chapter at 1 AM the night before the interview.
5,555 stars. 1,059 forks. One AWS engineer on his own time.
One honest flag: there is no LICENSE file on the repo. These are study notes summarizing a copyrighted book. If you can afford $79.99, buy the books. Alex Xu deserves the royalty. These notes are for the night before, when you already read the book and forgot half of it.
One engineer. Two books. Twenty eight chapters. Free on GitHub.
The book teaches you the answers. This repo helps you remember them.
CLAUDE CODE CAN NOW PULL LIVE DATA FROM 17,000+ STOCKS, CRYPTO PRICES, AND FINANCIAL STATEMENTS IN SECONDS.
One command. 60 seconds. Done.
Here is the exact setup:
Step 1: Open Claude Code and paste this:
claude mcp add --transport http financial-datasets https://t.co/cupUKrWK0C
Step 2: Authenticate
Type `/mcp` inside Claude Code and complete the OAuth flow in your browser.
Verify the connection anytime:
claude mcp list
Step 3: Start prompting
- "What is Apple's current P/E ratio and market cap?"
- "Show me Tesla's income statement for the last 4 quarters."
- "How has Bitcoin's price changed over the past year?"
That is it.
Claude Code now has direct access to real financial data across 17,000+ stocks, earnings reports, balance sheets, income statements, cash flow data, and crypto prices.
The analysts paying $24,000 a year for a Bloomberg Terminal are not going to be happy this exists.
Before this you needed a Bloomberg Terminal or a complex financial data API or hours of manual research across multiple sources.
Now you need one command and 60 seconds.
The quants, analysts, and portfolio managers who figure out how to combine Claude Code's reasoning with live financial data access will have a research edge that compounds every single day.
Bookmark this before you open your next brokerage account.
Docs if you run into errors: https://t.co/CgF6B3dS5V
Follow @cyrilXBT for every Claude Code integration that changes how you work with data.
Claude Code x TradingView is the best AI trading quant of all time.
Gone are the days of AI slop market analysis - AI is now better at technical analysis than you.
Here's how you can turn Claude Code into your expert trading quant (in <5 minutes):
Step 1. Ensure you have these requirements:
• Claude Code - installed on your computer (this is what talks to TradingView)
• Node.js 18+ - installed on your computer (the MCP server runs on this)
• TradingView Desktop app - downloaded from https://t.co/1YkJpaCU8L
• A valid TradingView subscription (paid plan for real-time data)
Step 2. Open Claude Code and run the following prompt to connect the TradingView MCP:
"Install the TradingView MCP server. Clone and explore https://t.co/k1Ql1o0CYi, run npm install, add to my MCP config at ~/.claude/.mcp.json, and launch TradingView with the debug port."
Step 3. Health check
Restart Claude Code, and paste this prompt:
"Use tv_health_check to confirm TradingView is connected."
If correctly connected, Claude Code should respond with a confirmation.
Step 4. Start prompting
Claude Code now has access to your ENTIRE TradingView environment
Your charts, your technical analysis, alerts - everything.
Use this prompt to turn Claude Code into your personal market analyst:
"Act as an elite quantitative trader and technical analyst with full access to my TradingView environment.
Analyze the current market structure for [ASSET] on the following timeframes: 5m, 15m, 1H, 4H, 1D.
Use my existing indicators, drawings, and chart context to:
Identify the current trend and market regime (trending, ranging, accumulation, distribution)
Mark key support and resistance levels based on price action and liquidity
Identify liquidity pools, stop clusters, and likely areas of manipulation
Analyze momentum using RSI, MACD, and volume where available
Detect any chart patterns (breakouts, consolidations, deviations, etc.)
Evaluate confluence across timeframes
Then provide:
A clear directional bias (bullish, bearish, neutral)
The highest probability trade setup right now
Exact entry, stop loss, and take profit levels
Risk-to-reward ratio
Invalidation point (what would prove this analysis wrong)
Finally:
Explain your reasoning step-by-step in plain English.
Avoid generic statements. Be decisive.
If no high-quality setup exists, explicitly say “no trade” and explain why."
This is an EXTREMELY powerful setup - make sure to save this post so you don't forget it.
Stop wasting hours trying to learn AI.
I have already done it for you.
With one list. Zero confusion. And no fluff.
📹 Videos:
1. LLM Introduction: https://t.co/sfqLeUwf3W
2. LLMs from Scratch: https://t.co/GbnKbfvhcg
3. Agentic AI Overview (Stanford): https://t.co/EnqB4YMpeY
4. Building and Evaluating Agents: https://t.co/vp8RCDEoZP
5. Building Effective Agents: https://t.co/mngwlvMHna
6. Building Agents with MCP: https://t.co/TVk18pOf6Z
7. Building an Agent from Scratch: https://t.co/bfnRYfrFjd
8. Philo Agents: https://t.co/SQcGLseeM1
🗂️ Repos
1. GenAI Agents: https://t.co/cXJNVqPZqv
2. Microsoft's AI Agents for Beginners: https://t.co/WHiolowRZi
3. Prompt Engineering Guide: https://t.co/rVMK9vZfBJ
4. Hands-On Large Language Models: https://t.co/zpmaATDtdr
5. AI Agents for Beginners: https://t.co/WHiolowRZi
6. GenAI Agents: https://t.co/s9uA1N24PV
7. Made with ML: https://t.co/AKffs9HkUz
8. Hands-On AI Engineering: https://t.co/h9OVhJ3tWn
9. Awesome Generative AI Guide: https://t.co/lV1YMGL52R
10. Designing Machine Learning Systems: https://t.co/IUXQzlY97i
11. Machine Learning for Beginners from Microsoft: https://t.co/KrSHxdZMju
12. LLM Course: https://t.co/6U4Vww6Uyk
🗺️ Guides
1. Google's Agent Whitepaper: https://t.co/5Wpf7xvQqz
2. Google's Agent Companion: https://t.co/bVmjIK8Xam
3. Building Effective Agents by Anthropic: https://t.co/7SsNu6xr6Y
4. Claude Code Best Agentic Coding practices: https://t.co/X22UJOHlbC
5. OpenAI's Practical Guide to Building Agents: https://t.co/Bn5SYDT9KR
📚 Books:
1. Understanding Deep Learning: https://t.co/csAFkaw3Qp
2. Building an LLM from Scratch: https://t.co/72W4q5QV4z
3. The LLM Engineering Handbook: https://t.co/WgHM7dn8xq
4. AI Agents: The Definitive Guide - Nicole Koenigstein: https://t.co/2vXzCQXEqg
5. Building Applications with AI Agents - Michael Albada: https://t.co/MQAwMPbzQZ
6. AI Agents with MCP - Kyle Stratis: https://t.co/CcaNk01utK
7. AI Engineering: https://t.co/GD45IogK63
📜 Papers
1. ReAct: https://t.co/Nk77rLspmX
2. Generative Agents: https://t.co/CJEokZcGSw
3. Toolformer: https://t.co/GVKiIt2pj3
4. Chain-of-Thought Prompting: https://t.co/YyoEidCGMi
🧑🏫 Courses:
1. HuggingFace's Agent Course: https://t.co/288ifz8r9R
2. MCP with Anthropic: https://t.co/F07zf0lfXi
3. Building Vector Databases with Pinecone: https://t.co/6MFjlpTHab
4. Vector Databases from Embeddings to Apps: https://t.co/ngGDY3Rc7r
5. Agent Memory: https://t.co/BnlgGadL7o
Follow @iansh04_ for more!!
👇 Comment “AI” for more resources
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Bookmark for future.
Baseball can sometimes feel a little boring. This play was absolutely the highlight of the week when it happened. We definitely need to see more of this. 💯😲🤣
Anthropic pays engineers $750,000+ a year to understand how LLMs work.
Stanford just put a 2 hour lecture that covers 80% of it for FREE.
Bookmark this. Give it 2 hours today.
It might be the highest ROI thing you do this month: