🔢 Treat models like code dependencies — version them
PM AI Versioning
(2026 Edition)
5 practices and 4 traps for AI versioning.
Build AI Versioning PM Skills — Free →5 Practices
1.
Pin model versions in production — automatic upgrades break things
2.
Run new models in shadow before promoting
3.
Eval suite is the gate for any version change
4.
Communicate model upgrades to enterprise customers
5.
Plan for model deprecation by vendors
4 Traps
❌
Auto-upgrading to latest model — breaks behavior
❌
No prompt version control
❌
Skipping shadow tests because 'evals look fine'
❌
No rollback path when a model regresses
FAQ
How often do silent model changes break products?
More often than vendors admit. OpenAI, Anthropic, Google all update underlying models periodically. Production AI products that don't pin or shadow-test see silent regressions monthly. PMs who treat models as code dependencies — versioned, tested, deprecated deliberately — ship more reliably.