Your fitness coaching assistant uses a system prompt with detailed conditional logic: "If the user mentions…

Question

Your fitness coaching assistant uses a system prompt with detailed conditional logic: "If the user mentions being a beginner, provide step-by-step form instructions. If they use the terms 'progressive overload' or 'superset', respond concisely. If they ask about injury history, always recommend consulting a physician." During evaluation, you find the assistant handles explicit expertise declarations correctly but struggles when users don't clearly state their level—often defaulting to overly detailed responses regardless of contextual cues like technical terminology. Which change to the system prompt would most directly address this failure to pick up on implicit expertise signals?

Accepted Answer

A. Replace most conditionals with a general principle: "Adapt explanation depth to match user expertise, mirroring their terminology." Keep only the safety-critical conditional about consultations.

Answer

B. Add more conditional branches to cover additional expertise signals, such as "If user mentions specific rep ranges or asks about periodization, treat as advanced."

Answer

C. Implement a pre-conversation intake that asks users to rate their experience level, then inject that rating into the system prompt as context for all subsequent responses.

Answer

D. Add an explicit instruction for the model to ask a clarifying question about experience level whenever the user's expertise isn't immediately clear from their first message.

Question 223