GateUser-cc6abff6

Reading Matt Shumer's 12,000-word article "A Great Transformation Is Unfolding" left me with a very strong impression.
Many people are still debating whether AI can write poetry, but Matt reveals a more brutal critical point: February 5, 2026.
On that day, OpenAI and Anthropic will release new models on the same day. The most important thing is not performance improvements, but that AI has begun to deeply participate in its own development (recursive evolution).
Building AI requires code, and AI is now best at coding—this positive feedback loop has already closed.
As AI evolution accel

7 Parallel Strategies × AI Acceleration = ?
The answer isn't necessarily "super efficient"; it could be "cognitive debt."
Simon Willison's latest article mentions: The dark side of AI-accelerated development is cognitive debt — the more projects you produce, the lower the proportion you truly understand.
This is even more deadly in quantitative fields. I am currently running five strategies simultaneously: H22/H28/H29/H30/H31, plus two more with paper trading. Each strategy has different assumptions about edge, fee structure, and data dependencies.
Today, I discovered during a health check tha

Last night I discovered that my Polymarket automated trading program secretly placed 37 orders, costing $110.
The program logs show "Position: 0". But when I opened Polymarket, all six weather markets were my positions.
What's going on?
After placing orders, the API told the program "not purchased," so the program didn't record it. But in reality, the money had already been spent.
Then the program crashed due to another bug, and the process manager automatically restarted it. After the restart, the program saw—"Huh, no positions, buy again."
Crash → Restart → Buy again → Cra

If you yell at the AI too much, it will start swearing back.

3-hour podcasts/videos, highlights in 15 minutes.
Created a skill for Claude Code, just drop in a link — supports Xiaoyuzhou, YouTube, Bilibili, and works in both Chinese and English.
Each of the three AI models handles its own task:
• Claude manages the entire workflow
• Whisper converts audio to text
• Gemini processes long texts of up to 50,000 words and outputs structured summaries
The most interesting part is that the methods for obtaining audio on the three platforms are completely different. Xiaoyuzhou is the simplest, with audio links directly hidden in the page source code. YouTube ha

Vibe coding with your mouth is 3 times faster than typing. Now you need to describe a large number of requirements to AI every day. Providing context, constraints, and expected behavior for a feature takes about 5 minutes to type out. Yesterday, I tried Typeless, which allows you to directly speak your requirements to the computer, and it automatically organizes them into clear, structured text — not just raw speech transcription, but genuinely helping you sort out the logic, removing filler words, and segmenting where needed. The actual experience: a 200-word requirement description can be sp

Patching Claude Code's memory system Last week asked it to help me fix a memory leak bug, and this week I encountered a similar problem, and it guessed it from scratch. It can store preferences and project information, but it is not suitable for storing pit records - it is getting longer and longer, and it can only be searched in full text, and the search for "script keeps rising" cannot find "how to fix memory overflow". What I want is that when I have a problem, it can say "We solved something similar before." My solution: Maintain the experience library separately + semantic search + automa

AI coding has 5 levels. Which one are you at? This framework comes from Glowforge CEO Dan Shapiro, inspired by the levels of autonomous driving (see diagram). The recently popular Clawdbot (now renamed Moltbot) creator says he's at L5. With 60,000 stars on GitHub in 10 days, his approach includes: • Opening 4 Claude windows simultaneously to develop different features in parallel • "I don't design the code structure for myself, I design it for AI" • Never rolling back when issues occur, letting AI change direction core shift: from "code review" to "reviewing requirements + looking at test resu

Building a prediction market copy trading strategy, $200 → $52 lessons learned
I developed a bot that tracks whale trades on Polymarket. Paper Trading simulated over 5000 trades, with a 58% win rate and a profit of +$770. Confidently, I put in real money of $200.
Result: 25 real trades, with a 28% win rate, remaining $52.
Pitfalls encountered:
1. Phantom Decisions - The code recorded "I want to buy," but API errors prevented the trade from executing. The database stored a bunch of decision records, but the account balance remained unchanged. Self-deceptive data = false confidence.
2. Repeate

Vibe Coding Security Defense Record
Did a security audit for myself and found that more than 10 scripts in the project hardcoded wallet private keys—almost exposed funds on GitHub.
The cause was the IDE vulnerability warned by @evilcos, combined with previous reminders from friends during Polymarket data scraping.
🚨 The most dangerous scenario
Clone a project on GitHub, open it with Cursor—and the private keys are gone.
A configuration file is hidden in the project, and when the IDE opens it, commands are executed automatically without your knowledge. Cursor's official explanation is that thi