Prompt-shaping behaviour

What it is

Prompt-shaping behaviour is the way users refine the wording of their prompts mid-conversation to steer an assistant towards a better answer. It marks a shift from one-off keyword entry to iterative conversation.

Why it matters

These refinements reveal the true intent and the gaps in the first answer, giving a clearer picture of need than a single query and signalling which content actually resolves a request.

How it works

It is observed by tracking how a prompt evolves across turns: added constraints, requested formats, clarifications, and corrections that move the conversation towards a satisfying result.

When it applies

It applies during multi-turn interactions with a generative assistant rather than single-shot search.

Examples

• A user follows a broad question with make it shorter and for beginners.
• Someone adds a constraint such as only options under a set budget after seeing the first reply.
• A searcher reframes a vague request into a specific scenario to get a targeted answer.

How it is measured

• Average number of refinement turns per conversation
• Rate of added constraints or format requests across turns
• Correction or clarification frequency within a session
• Turn at which the user accepts the answer and stops