ScottBTC

Yesterday, many people said providing LP on Robinhood was highly profitable. Today, many are saying MEM rug-pulled and providing LP resulted in massive losses. I recommend LPs pairing core stocks with ETH—the yield is high enough, and I’m willing to hold the assets regardless of which way they move.

I've been working on on-chain strategies recently. For speed, I enabled QuickNode RPC, thinking subscribing would be enough. I checked the bill today and cried myself unconscious 🥲

What are you doing while AI is working? The optimal office environment in the AI era

Didn’t think PayPal could surge like this too. Take a look at the old-dude stock dip-buying and DCA plan I set back in June—basically everything is already up around 20%. The AI volatility is too high, so I’m starting to embrace old-timers.

Finally waited until 12:50 for the token to recover, but it burned up after just over ten minutes??? I've been running fable for the past two days and it never burned this fast. Is cc secretly running the token tonight?

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 🧐

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

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.