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Retrospective Template

AI Feature Decision

Evaluate an AI feature by user value, model capability, failure modes, and required guardrails.

5 columns
AI at Work
1 min read
AI product management, feature decision, AI risk

The AI Feature Decision template helps product teams decide whether an AI capability is useful, reliable, and responsible enough to ship. It puts user value and model limitations in the same conversation.

Evaluate the whole product decision

Capture the user outcome first. Then assess what the model can do consistently, the failure modes users may face, and the guardrails required to detect, prevent, or recover from those failures. Record the decision with the assumptions that support it.

This avoids two common traps: shipping a technically impressive feature without a valuable job, or rejecting useful AI because the team has not designed the right review and recovery path.

How to facilitate

  1. 1
    Define value without mentioning AI. State the user problem and desired outcome.
  2. 2
    Test realistic edge cases. Average demos hide the failures users remember.
  3. 3
    Design recovery. Give users a way to inspect, correct, retry, or escalate output.
  4. 4
    Record the threshold. Define what must be true to ship, pilot, pause, or stop.

When to use this template

Use this board for copilots, generative features, recommendation systems, autonomous agents, AI summaries, or any feature where model behavior affects the customer experience.

Template Columns

Column structure and prompts for your retrospective

User value

Items for User value

Model capability

Items for Model capability

Failure modes

Items for Failure modes

Guardrails

Items for Guardrails

Decision

Items for Decision