product-mode
Misaligned PM-eng handoffs waste months of engineering effort on misdirected features.
The most expensive bug in AI-assisted building is shipping the wrong thing, well. A CLAUDE.md for PM + eng teams using Claude Code- 7 principles for problem framing, scope, tradeoffs, and outcome measurement. Built on @karpathy's observations.
- Ask Claude to help frame a feature request using the 7 principles before engineering starts building.
- Generate a scope document that clearly defines tradeoffs between speed, quality, and resource constraints.
- Find misalignment between product and engineering teams by reviewing problem statements against the principles.
Misaligned PM-eng handoffs waste months of engineering effort on misdirected features. This framework systematizes problem definition and scope negotiation upfront, reducing rework and ensuring Claude-assisted development targets actual user needs.
Product managers and engineering leads coordinating AI-assisted development projects and feature prioritization.
https://github.com/sohaibt/product-mode
By sohaibt
How to Get It
claude plugins install sohaibt/product-mode
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help frame a feature request using the 7 principles before engineering starts building
Trust Signals Auto-scanned
Community Pulse Growing
Discussed on Hacker News
- Product Model at Spotify — Hacker News · 3 pts
- Unseating the Giant: Amazon, Inkling, and the rise of a new product model. — Hacker News · 2 pts
- The Product Model and Org Design — Hacker News · 2 pts
3 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 51 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Evaluation
Scored from trust signals (evidence-eval-v1): 51 GitHub stars; contributors unknown; last commit 0d ago; license MIT.