How to add AI to an existing SaaS product without breaking it is mostly a sequencing problem. Most failed integrations are the ones that became a separate UI users never adopted. The right pattern is to embed AI inside an existing workflow, behind a feature flag, with eval and a kill-switch from day one.
The pattern we use
- 01Pick the highest-friction step in an existing workflow.
- 02Build the AI assist inside that step (not in a new tab).
- 03Hide it behind a feature flag rolled to 10% first.
- 04Eval running on every change, cost telemetry from day one.
- 05Kill-switch wired so the feature can be disabled per-tenant without a deploy.
- 06Watch adoption and override-rate metrics. Iterate.
Auth, RBAC, audit
- AI features inherit the user's RBAC. The agent must not read what the user can't.
- Every AI decision is logged with user, input, output, model version, cost.
- Per-tenant configuration: some customers enable AI, some don't.
- Data isolation: per-tenant retrieval indices, never mixed.
What we wire on day one
- Feature flag (LaunchDarkly, GrowthBook, or your own).
- Cost telemetry per feature per tenant.
- Eval suite running in CI on every prompt change.
- Kill-switch endpoint accessible to support without a deploy.
- Audit log table with input, output, model, confidence, override.