The Real Cost of Model Migration - What Swapping LLMs Actually Requires

So OpenAI deprecated gpt-4o-mini. Or some other model you've built your whole system around just got a sunset date. The email lands and your first thought is: how hard can a model swap be? I've been through this a few times now. The API call swap? Easy. Twenty minutes, tops. But the swap has a way of revealing every shortcut and assumption your system has been quietly depending on. That's the part people don't usually mention until you're already in it. Table of contents What migration actually is The model options in 2026 Phase 0 - Know what you're migrating from Phase 1 - Build your evaluation harness first Phase 2 - The prompt portability problem Phase 3 - Automated prompt optimization with DSPy Phase 4 - Reasoning models: where they belong Phase 5 - Handling missing parameters Phase 6 - Risk assessment Phase 7 - Progressive rollout Phase 8 - Post-migration monitoring The systems audit you should run regardless What migration actually is Here's the (uncomfortable) truth: a model…