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I Turned JEV AI Into a 24/7 Stock Trader (Full Tutorial Breakdown)
Most “AI trading bots” ask a language model what to buy and hope for the best. This architecture does the opposite.
Most AI trading demos work like this: you paste market data into a chatbot, ask what to buy, and place the trade. It makes for a good demo and a risky system. The model has no guardrails, the logic is hard to audit, and nobody can say why a trade happened.
A recent tutorial from ThinkTrade takes a different approach. It uses Claude Code to build the infrastructure and Jev AI, TypeSafe’s fast decision model, as a narrow decision layer inside a rules-based system. The author built three bots and compared them against baselines. Here is how the system works and what the results showed.
The Core Architecture: Rules First, AI Second
The AI is not asked “what should I trade today?” It only sees a market once the strategy’s own rules have found a valid setup.
- Strategy rules run first. They pull market data and determine whether a valid setup exists at all.
- Jev gets a scoped question. If a setup exists, the system sends Jev a structured market snapshot and a fixed set of choices, such as enter long, enter short, or wait.
- Jev decides quickly. It…
