CLI that mines git history to quantify AI-assisted dev velocity and generates ROI reports for justifying AI tooling budgets.

Customer: Mid-level engineering manager at a 10-50 person startup who championed Cursor/Copilot/Codex adoption 6 months ago and now faces CFO asking ‘what did we get for $2k/month in seats’

Problem: No objective data exists to justify AI tooling renewal — managers rely on vibes and anecdotes when finance asks for ROI. Git history contains the signal but no one has extracted it.

Pricing: one-time — $800 in month 1 via 16 x $49 one-time licenses; $300 MRR by month 3 from team-tier at $99/seat-bundle

Why now

Enterprises like Uber are formalizing AI tooling budgets with actual caps and approval processes right now — the ‘prove it’ moment has arrived. Managers who championed adoption are suddenly on the hook for ROI data at renewal time, which is Q3/Q4 2026 for most teams who adopted in late 2025.

Go-to-market

1. Post working demo (real git repo → PDF report with velocity delta chart) to Hacker News Show HN and r/ExperiencedDevs — lead with the CFO conversation angle
2. DM 20 engineering managers on LinkedIn who posted about Copilot/Codex adoption in last 90 days — offer free analysis of their public OSS repos
3. List on Raycast store and VS Code marketplace as free tier (single-repo report) with paid unlock for team aggregation and PDF export
4. Write one SEO post: ‘How to calculate ROI of GitHub Copilot using git history’ — targets the exact query managers Google before budget meetings

Moat (or lack thereof)

No moat. Git analysis is not hard, OpenAI can build this, and Linear/GitHub could ship it as a feature. The only defensibility is being first to own the ‘AI ROI report’ search term and building a template library managers share with each other. First-mover advantage measured in months, not years.