I've been fascinated by agentic AI - systems that don't just answer questions, but take actions autonomously. The challenge? Most tutorials stop short of practical agentic workflows. I wanted to build something that actually does something in the real world. So I built ai_trader: an autonomous trading system powered by Claude that analyzes market news, generates trading signals with confidence scores, and executes paper trades through Alpaca's API. It's been running for a few weeks now, generating 500+ signals, and I've learned a lot about what it takes to let an AI make decisions on your behalf. This post covers the architecture, shows the key code, and shares what I learned along the way. What It Does The system is a CLI tool that connects Claude's reasoning capabilities to a paper trading account: $ trader run claude Analyzing AAPL... Signal: BUY | Confidence: 0.75 Reason: Strong earnings beat and positive guidance suggest continued momentum Analyzing TSLA......
Cranking out good code