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FeatureFactory
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Product Plan Generator

Turn a rough feature idea into a structured, copyable product requirements doc - Problem, Users, Requirements, Acceptance Criteria, Risks and a Success Metric.

Inputs

product plan · 273 words

# product plan: Inline PR risk badges

**Slug:** `inline-pr-risk-badges`

## Problem
Reviewers cannot tell which pull requests are risky until they open them, so review time is spread evenly instead of focused on the changes most likely to break production.

## Users
- Reviewers
- engineering managers
- on-call engineers

## Goals
- Surface a risk score on every PR in the list view
- Highlight PRs touching high-blast-radius files
- Cut median time-to-first-review for risky PRs

## Non-Goals
- Auto-approving or auto-merging PRs
- Replacing human judgement in review

## Requirements
- R1. The system must surface a risk score on every PR in the list view.
- R2. The system must highlight PRs touching high-blast-radius files.
- R3. The system must cut median time-to-first-review for risky PRs.
- R4. The experience must be usable by Reviewers, engineering managers, on-call engineers without additional configuration.

## Acceptance Criteria
- AC1. Given a Reviewers, when the feature is live, then they can surface a risk score on every PR in the list view.
- AC2. Given a Reviewers, when the feature is live, then they can highlight PRs touching high-blast-radius files.
- AC3. Given a Reviewers, when the feature is live, then they can cut median time-to-first-review for risky PRs.
- AC4. The metric "Median time-to-first-review for high-risk PRs drops by 30% within one quarter" is instrumented and observable in a dashboard.

## Risks
- Instrumentation gap: the success metric must exist in telemetry before launch, not after.
- Adoption risk: shipped ≠ used - track engagement, not just delivery.

## Success Metric
Median time-to-first-review for high-risk PRs drops by 30% within one quarter

Write product plans that AI agents and humans can actually build from

A product requirements document (product plan) is the contract between an idea and the code that ships. The best product plans are short and specific: they name the problem, the users, the goals, what is explicitly out of scope, and the one metric that proves the feature worked. This generator assembles that structure deterministically from your inputs - no fluff, no fabricated detail.

Clear requirements matter even more when an AI coding agent does the building. Vague specs produce vague pull requests. A tight product plan with testable acceptance criteria gives the agent - and the reviewer - an unambiguous target. Once the feature ships, measure the outcome so you know the work moved the metric, not just the backlog.

Dig deeper with our guide to writing a product plan, grade your criteria with the Acceptance Criteria Grader, explore the AI product plan generator, or see how outcome measurement closes the loop.

Frequently asked questions

No. Everything runs in your browser. Nothing you type is uploaded, stored, or sent to a server - the markdown is assembled locally and deterministically.

Ship the feature, then prove it worked

FeatureFactory helps engineering teams plan, build and measure AI web-development - so every shipped feature is tied to an outcome, not just a merge.