How I Built an Algorithmic Trading System With Python, AI, and Live Signals

Originally published at chudi.dev System Architecture Overview When I started building a trading bot, I expected the hard part to be the trading logic. It wasn't. The hard part was building a system that could run continuously for weeks without losing state, crashing silently, or entering impossible positions. A production trading bot needs five core modules that work together: Signal Generation - Monitors price feeds and generates trade signals Position Management - Executes trades, tracks holdings, and prevents overlapping positions Exit Strategies - Knows when to close positions and takes profits or cuts losses State Persistence - Survives process crashes, power failures, and restarts Health Monitoring - Detects stuck orders, orphaned positions, and api failures Each module can fail independently, so the system needs to handle partial failures gracefully. A signal can fail without crashing position management. An API call can timeout without losing the position state. The monitoring