Aglet

Verify query learning signals before tuning search

Verification should show that a search change improves the intended learning signal without disguising behavior as success. Compare representative query paths before and after, inspect result context, and confirm session definitions. Keep a manual or structural sample when analytics coverage is incomplete.

Check whether the outcome improved

  1. Check successful behavior

    Replay a query that previously led to a useful result or filter. Confirm the desired path remains available and that a click or refinement still supports the person’s task. Record query family and context.

  2. Check failed behavior

    Exercise a zero-result, irrelevant-result, or repeated-reformulation path in scope. Confirm the change improves the intended next action and does not force a misleading click. Preserve a path that should remain unchanged as a control.

  3. Review the evidence claim

    Compare sampled events, result state, and session boundary with the closure text. State omitted devices, query families, and missing events. Leave the result partial when behavior improved but the reason remains uncertain or coverage is sparse.

What to carry forward

Verification passes when the intended search path improves for tested sessions, successful behavior remains intact, and the claim matches evidence coverage. If motives or session continuity remain unknown, document that limit. A changed click rate alone cannot prove a better search journey.

Technical background: Elastic documentation.

Keep the decision with the work.

Use a Work Item in Aglet to record the problem, the evidence you have, and the next decision. Add an owner and priority, then keep updates in the discussion so the next person can follow the reasoning.

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