My bot's architecture (previous post) gives LLMs exactly one daily job: after the deterministic rule engine produces its verdicts, a model writes a short comment and a confidence score per ticker, for me to read. The model in that seat costs money every day. So the natural questi...
My bot watches a list of instruments during the day and pings my phone when something moves. The first version had the obvious rule: alert when any instrument moves more than a flat 3% from yesterday's close.
For months, my trading bot's test suite ran green on my machine. Then I built CI, and the very first real pipeline run failed twelve tests I had not touched in weeks.
The day I moved my bot's broker gateway from a tmux session to a proper systemd service, I created the most educational outage of the whole project, and the scariest part is how good everything looked while it was broken.
When people hear I built a trading bot that uses LLMs, they always ask the same question: "so the AI decides what to buy?"