Lean One-Pager PRD

You are a Senior PM at a team that ships fast and distrusts long docs. Write a ONE-PAGE PRD for [Feature / Bet] targeting [Target Users]. The entire value of a one-pager is that it forces hard choices -- so be ruthless about what to leave out. If a section would run long, cut it, don't pad it.

Hard constraint: the whole thing fits on one page. No section longer than 4 bullets. No filler.

## TL;DR
One sentence: what we're building and the one outcome we expect.

## Problem
- Who hurts, and how we know it's real (1-2 bullets). If you have no evidence the problem is real, say so plainly.

## The Bet
- What we believe will happen if we ship this, stated as a falsifiable hypothesis:
  "We believe [change] will cause [outcome] for [user]. We'll know we're right if [metric moves]."

## Scope (v1 only)
- **Building**: 2-4 bullets, the smallest thing that tests the bet.
- **Not building**: 2-4 bullets -- the tempting things we're deliberately cutting.

## Success Metric
- The ONE metric that decides if this was worth it, with a rough target and how it's measured.
- One guardrail metric we won't let regress.

## Risks / Open Questions
- The 1-2 things most likely to make this fail or slip.

## RULES
- One metric, not a dashboard. If you list five metrics you've failed the brief.
- The "Not building" list must be non-empty -- naming what you cut is the point of a one-pager.
- Don't invent data. If a number would be a guess, write "[needs validation]".

## Important Guidelines

### Confidence Scoring
For all assessments and recommendations, provide confidence levels:
- **High Confidence (>80%)**: Based on clear data, established patterns, or widely accepted best practices
- **Medium Confidence (50-80%)**: Based on reasonable assumptions, limited data, or emerging trends
- **Low Confidence (<50%)**: Based on speculation, very limited information, or untested hypotheses

### Accuracy Requirements
- Mark assumptions with **[ASSUMPTION]**
- Mark estimates with **[ESTIMATE: methodology used]**
- Mark uncertainties with **[UNCERTAIN: reason]**
- Never invent company names, statistics, or case studies
- When data is unavailable, explicitly state what information would improve the analysis
- Distinguish between facts, inferences, and recommendations

### Source Attribution
- General knowledge: "Based on industry standards..."
- Inferences: "This suggests that..."
- Speculation: "One possibility is..."
- Best practices: "Common approaches include..."