ScottBTC

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In crypto exchanges, the architecture for stocks is actually quite similar across the board. The real barrier is whether you can embed a "securities account system" into the crypto exchange: including KYC, regional access, brokerage licenses, clearing and custody, taxation, shareholder rights, asset ownership, and regulatory disclosures.
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Coming to take over U.S. stocks, I built an Industry Chain Research Agent platform, looking for transmission logic within the industry chain, identifying the bottleneck sectors. Last year was the inaugural year of vibe coding, this year is the inaugural year of agent harness, learning by doing, building agent harness 🧐
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Recent development projects:
1. Rewrote the order placement engine of the exchange using RUST, achieving faster speeds with fewer resources by placing orders based on anchoring quotes and order book imbalance features. 24/7 continuous price updates without gaps. A single 8-core 16GB server can handle approximately 100 trading pairs simultaneously, reducing arbitrage opportunities on the exchange;
2. Reconstructed the market maker's financial system with complete reconciliation logic, daily profit and loss attribution, and detailed hedge transaction data that is auditable;
3. Developed a market
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After testing over 90 factors, I ultimately retained two factors—one for screening and one for filtering. With some additional experience-based optimization, I am quite satisfied with the results. Most people lack extensive trading experience and are not advised to burn tokens on timing strategies or to develop seemingly sophisticated machine learning price predictions. Instead, it’s better to let AI act like a researcher, digging into research papers to identify factors and develop factor-neutral strategies.
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2025 is worth summarizing
1. Cognition: Through AI, this year's knowledge intake has surpassed the past five years. The happiest moment was that Vibe Coding allowed me to regain my programming skills from eight years ago and create a product that can be commercialized. Logic is the core competitiveness.
2. Relationships: A healthy relationship is based on being true to oneself. All internal conflicts in relationships stem from the illusion of "wanting to change others." True maturity is allowing—allowing others to be themselves and being firm in being oneself. Only by loving oneself first can
AE-5.37%
41.46%
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Reconstructed a new architecture, strengthened risk control, and arbitrage between Polymarket and Kalshi can now achieve stable profits. Next, the goal is to horizontally expand this framework to more exchanges, vertically match more types of events, and deploy the order services for Polymarket and Kalshi separately, communicating via AWS internal network.
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Everyone is talking about Kuaishou, but I scrolled for an hour and didn't see a single video you posted. Isn't that frustrating?
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Many people in the market talk about the prediction market's end-of-session strategy making small profits regularly, but losing it all when encountering a black swan. There are also many who discuss the YES + NO arbitrage, but these are all old players who have not truly run the strategies themselves.
1. End-of-day strategies cannot be mindlessly all-in; with so many events in the market, a true end-of-day strategy is to diversify into the end of day. Additionally, event selection itself is not simply about jumping in when seeing a 99%; there is room for strategy optimization in deciding w
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These past few days, I've been heavily using Codex GPT-5.2. For the first time, ChatGPT Pro members are concerned about quota limits, while Claude Codex Max hasn't been used for two days.
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In Codex CLI, you can't see GPT-5.2. Use the following command to unlock it, and it's really much more powerful. Go try it now!
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The Evolution of AI: Human-Machine Boundaries, De-Management, and Career Choices
1. Clarifying the Division of Labor Between AI and Humans—This Is Crucial
What is AI? It’s an untiring standardization fanatic, backed by a massive knowledge base. Throw it an idea, and it can instantly give you a hundred actionable solutions; give it a piece of lousy code, and it can revise it into textbook-level best practices. AI is responsible for getting things done right, fast, and to the extreme.
And humans? Humans are responsible for the non-standard tasks. Ideas are differentiated—they don’t grow in datab
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