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Growth

· 7 min read

Shipping AI features without breaking trust

AI can save your customers hours or quietly erode their confidence. The guardrails we use before any AI feature reaches production.

Daniel Ross

Daniel Ross

Co-founder & CTO

Rising adoption chart next to a shield with a check mark

When we started building AI release notes, the first prototype was impressive in demos and nerve-wracking in practice. It was confidently wrong about one change in ten. For a feature that speaks on our customers’ behalf, that was nowhere near good enough.

Keep a human in the loop

Every AI draft in Liftoff is a suggestion. Nothing is published until a person reviews it, and the editor highlights exactly which sentences came from the model.

Make the source visible

Each generated line links back to the pull request or task it was written from. If something looks off, you can check the source in one click.

  • Clear labels on anything AI-generated

  • Citations back to the original work

  • An easy way to report a bad suggestion

  • No training on customer data without opt-in

Measure trust, not just usage

We track how often drafts are accepted unchanged, edited or discarded. Usage tells you people tried the feature; acceptance tells you they trust it.

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