AI for product managers
**Scope MVPs, defer risky autonomy, define metrics** — before engineering writes a line of agent code.
1Try it yourself
Playground
Product scope triage
PMs define outcomes and guardrails — engineers ship bounded MVPs with metrics.
Summarize support tickets for agents
2Read & reflect
Recap
#What you just did
You triaged three AI feature ideas: ship bounded MVP, defer high-risk autonomy, or block launch until metrics exist.
Read
#PRD sketch
Problem: agents spend 20m/ticket on repeat lookups
Outcome: draft reply in <30s with policy citations
Not in v1: auto-send refunds, legal responses
Metrics: time-to-first-draft, human edit rate, escalation rate
Eval gate: 20 golden tickets before beta
Use it
#When you'd use this
- Writing AI PRDs for eng and design
- Stakeholder reviews on scope creep
- Launch readiness checklists
Watch out
#Watch out
“Fully autonomous” on day one is a scope trap — stage human review and evals.
Try next
#Try this next
Write one north-star metric and one guardrail metric for your next AI feature.
3Spark check