AI works entirely from what you give it. When context is absent, it fills the gap with the most statistically likely assumption — which is the average case, not your case. Understanding exactly which type of context is missing tells you exactly what to add.
Diagnose your instructions free — 10 runs includedBefore your request, describe the relevant situation: what you're working on, what the goal is, what constraints apply. One or two sentences of background eliminates most wrong assumptions.
Tell AI what kind of expert it should be: "Act as an experienced B2B copywriter focused on SaaS." Role assignment changes framing, vocabulary, and depth of response across the entire reply.
Constraints are as important as instructions. "Do not recommend paid tools" or "Do not suggest changes to the pricing structure" prevents AI from filling suggestions with things you've already ruled out.
Who will read or use this output? "This is for a VP of Finance who has no technical background" changes vocabulary, assumed knowledge, and framing. Without it, AI writes for whoever seems most likely to ask.
Enough that the AI can answer without making assumptions that affect the output. If you removed the context and gave the prompt to a new employee on day one, would they still produce the right answer? If not, add more context.
AI fills gaps with statistically likely defaults from its training data. Those defaults reflect the average situation, not yours. Every wrong assumption is a signal that a specific type of context is missing.
More relevant context helps. Irrelevant context can dilute the signal. The goal is the right context, not maximum context — background, role, constraints, audience, and prior state.