Evaluate decisions, not impressive demos

A polished answer to a prepared question says little about daily use. Build a test journey that starts with a real question, confirms definitions, reviews the result, follows up, checks evidence, and ends with a business decision. Include recurring questions, ambiguous questions, and questions whose data scope must differ by user.

Make definitions part of acceptance

For every test, record the expected metric, time range, dimensions, filters, and exception rules. “Did East China sales fall?” is incomplete until sales, comparison period, and refund treatment are defined. A reliable system should surface material ambiguity instead of silently choosing defaults.

Test evidence and permission boundaries

Users need to see the data time, scope, and dimensions behind an answer. Run the same question as members with different access and confirm each only sees authorized data. AskTable.ai has confirmed organization, role, project, data-scope, and usage controls; exact connectors and deployment scope still require POC confirmation.

Measure the action loop

Test whether findings can become reports, alerts, notifications, or follow-up work. During a one-week pilot, count invalid answers, manual definition changes, review time, and completed actions. This produces process evidence rather than a subjective score of model intelligence.

Public references

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