Keep checking an assistant after the launch test passes

The decision to improve

A successful launch test does not tell you how an assistant behaves as inputs change. Plan a recurring sample review of its actual outputs. Use the review to find error patterns and decide when a workflow needs to pause or change.

A practical starting record

Define output types, sample selection, reviewer and error categories before looking at results. For customer-answer drafts, include routine questions and escalated cases. Avoid selecting only easy examples. Preserve source references so a reviewer can distinguish an unsupported answer from outdated source material.

Review and tool fit

A process owner reviews serious errors immediately and changes only approved rules or sources. Keep version history for the sampling sheet and document why an output failed. Confirm your system can retrieve the relevant source without exporting unnecessary customer data. Sampling cannot prove every unreviewed output is correct.

Google documents spreadsheet version history. Confirm account access and sharing before using a sheet as a review record. Google: manage spreadsheet data

Measure the real value

Measure error categories, correction minutes and review cost alongside the time the assistant saves. Include ongoing evaluation in monthly ownership costs. If errors become difficult to detect, reduce autonomy or return to draft-only use instead of increasing volume.

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This guide applies across Canada. We provide remote AI consulting for businesses in Toronto; it does not describe a local client or a staffed office.

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