Lesson 501 of 2116
Switching Costs: Migrating Between Frontier Vendors
Models look interchangeable in demos. Migrating production from one vendor to another is rarely a swap — there is a real switching cost to plan for.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1Same outputs, different inputs
- 2switching cost
- 3prompt migration
- 4tool schema differences
Concept cluster
Terms to connect while reading
Section 1
Same outputs, different inputs
Two frontier models can produce similar outputs from quite different prompts. Migrating from one to another usually means rewriting prompts, re-evaluating tool schemas, and re-tuning safety language. Budget weeks, not hours.
Where switching costs hide
- 1Prompt phrasing — what works on Claude reads weird to GPT and vice versa
- 2Tool / function-calling schemas — slight syntax differences cause silent breaks
- 3Streaming format — server-sent events look different across vendors
- 4Refusal patterns — the new vendor refuses things the old one accepted
- 5Token tokenization — the same prompt costs different amounts on different models
Compare the options
| Migration kind | Effort | Risk |
|---|---|---|
| Same vendor, new model | Low to medium | Subtle quality regressions |
| Cross-vendor, similar capability tier | Medium | Prompt rewriting throughout |
| Cross-vendor, different paradigms (e.g. open-weights to closed) | High | Re-architecture |
| From cloud API to self-hosted open weights | High | Operational complexity |
Applied exercise
- 1Estimate your switching cost: weeks of engineer time to fully migrate
- 2Multiply by your loaded engineer rate to get a dollar figure
- 3Compare to the savings or capability gain from switching
- 4Decide if a partial migration — only the highest-volume endpoints — is the right move
Key terms in this lesson
The big idea: vendor switches are projects, not button presses. Plan accordingly and use abstractions where they pay off.
End-of-lesson quiz
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