Keep the lesson for the next incident
Record the count promise
Keep the query, selected filters, count universe, visible rows, variant rule, and freshness state. Write what a person was expected to infer. This gives later reviewers a concrete promise to test rather than a vague complaint about trust.
Compare later decisions
Review new queries after the correction and look for impossible selections, abandoned filters, or a different aggregation surprise. Preserve a control where counts worked. Do not treat fewer complaints as proof unless the reviewed queries cover the original boundary.
Refine one check
Require a broad query, selected facet, pagination state, and variant example in future count reviews, or add scope language to the design contract. Assign the change and a revisit date. Keep the original mismatch linked so the improvement remains measurable.
What to carry forward
The learning record should connect a count mismatch to the decision it distorted and one repeatable count review change. Stop when another reviewer knows which universe and edge case to compare. Keep uncertainty visible where data freshness or grouping still limits the promise.
Technical background: Adobe developer 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.
Create an account See the product workflow