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Use the questions to expose evidence gaps in a live workflow. Answer with a source and an owner rather than an unsupported confidence rating.
Tensile AI
Self-guided worksheet
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Self-guided worksheet. This reading edition provides questions and evidence criteria. It does not calculate a score, produce a radar chart, compare peers, save answers, email results or generate a PDF.
Use the questions to expose evidence gaps in a live workflow. Answer with a source and an owner rather than an unsupported confidence rating.
How to use it
Choose one workflow. For each question, record the answer, source, owner, date, gap and next check in your team’s document. Use “unknown” when the evidence is absent. Repeat after a material workflow change to compare your own records.
Ownership
Who can authorize, change, stop and accept the agent’s work?
Evidence to collect: Named operating and technical owners with recorded decision authority.
Policy coverage
Which written rules have checks, and which remain manual?
Evidence to collect: An expectation-to-check map with unsupported conditions explicitly retained.
Production visibility
Can the team investigate the first upstream failure?
Evidence to collect: Linked executions, business context and authoritative effects, with freshness limits.
Release discipline
What prevents an untested correction from becoming a new failure?
Evidence to collect: Reviewed changes, counterexamples and baseline/candidate tests across relevant tool states.
Customer result
What proves that the original job is complete?
Evidence to collect: Independent result evidence and any required owner acknowledgment, including recovery work.
Turn the gaps into a bounded next step
Start with the most consequential unresolved job. Agree what would establish a better result, test the correction, and retain the source and outcome limits.
Use the reliability workflow worksheet · Explore Tensile · Discuss a concrete workflow
Explore the failure mechanisms, the tests they need and the evidence that establishes the customer outcome.
AI reliability, from production to customer outcome.