Plan AO: AI PRD Writing

Interviews → feature list → user stories → acceptance criteria → review iterations

Time
3-6 hours
Cost
Low
Difficulty
Beginner

Best for

For product managers who want to turn scattered ideas into an executable PRD quickly — grounded in interview notes, not generated from thin air.

Steps

Collect interviews & inputs

30-60 min

Notion + you

Write user interview notes, feedback, competitor observations and stakeholder asks into Notion, tagging each as 'verified' or 'assumption'. With raw material in place, AI output won't drift.

💡For every requirement, capture who runs into what problem in which scenario — that's the raw material for user stories.

Feature list

30-60 min

Claude / ChatGPT

Have the model organize the material into a feature list: grouped by module, prioritized (P0/P1/P2), with dependencies and conflicting requirements removed. Align on 'what we build' before touching details.

💡Ask the model to score each feature on user value × build cost; keep only high-value, low-cost items in P0.

User stories

1-2 hours

Claude / ChatGPT

For each P0/P1 feature, write a user story: 'As a <role>, I want <action>, so that <outcome>.' Have the model fill in edge cases and error flows to build story cards.

💡Give every story one happy path and two exception paths — that's ready-made input for dev and QA.

Acceptance criteria

1 hour

Claude / ChatGPT

Turn user stories into testable conditions using 'when X happens, the system should Y', covering normal, edge and error cases, plus an explicit 'not a bug' list.

💡Write criteria well enough that QA can copy them directly; half an hour here saves days in development.

Review & iterate

1-2 hours

Gamma + Notion

Lay the PRD out as a visual document in Gamma for team review, feed feedback back into Notion, and have AI update requirements and priorities into a v2 for another pass.

💡In review, debate only whether it serves target users — leave implementation arguments for the technical design stage.

Tools involved

ClaudeChatGPTNotionGammaReplit

Pitfalls to avoid

Letting AI invent the whole PRD

A PRD with no interviews or data is a castle in the air; feed material first, then let AI organize — reverse the order and you're just talking to yourself.

A feature list with no priorities

All-P0 is no P0; rank by user value and cost. Cutting features protects delivery quality better than adding them.

Vague acceptance criteria

'Great UX' or 'fast' can't be tested; write concrete, testable conditions so QA has a verdict to apply.

Writing without reviewing

A PRD that skips review breeds requirement drift during implementation; run at least one formal review before development.

Related Workflows

Plan I: AI Presentations (Slides)

Topic & audience → outline & storyline → per-slide generation → visual consistency → speaker notes → rehearsal

Time：
30-60 min / deck
Cost：
Low
Difficulty：
Beginner

Plan J: AI Data Analysis / Research Report

Define the question → clean data → exploratory analysis → deep modeling → visualize & narrate → conclusions

Time：
2-6 hours / report
Cost：
Low-Medium
Difficulty：
Advanced

Plan K: AI Meeting Notes Workflow

Record & transcribe → AI summary → extract action items → archive & distribute → follow up & review

Time：
15-30 min / session
Cost：
Low
Difficulty：
Beginner