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Blog — MLOps & Architecture

Avoiding AI vendor lock-in
before it breaks your product.

When a model provider deprecates a parameter or changes a default, and every call in your product breaks at the same moment — that's not a vendor problem. That's an architecture decision made months earlier, showing up at the worst possible time.

Devji Chhanga Oct 7, 2026
Why it happens

Direct coupling feels fine, until it doesn't.

Calling a model provider's SDK directly from wherever you need it is the fastest way to ship a first version — and it's a reasonable choice for a prototype. The problem shows up once that pattern spreads across a real codebase: the provider's API is now called directly in dozens or hundreds of places, each one coupled to that specific SDK's shape.

Then the provider deprecates a parameter, changes a default behavior, or has an extended outage. Every one of those call sites breaks at the same time, and there's no single place to patch the fix — it has to be found and corrected everywhere, under time pressure, while the product is visibly down.

This isn't hypothetical risk. Model providers iterate fast, and deprecations happen on their timeline, not yours. The question isn't whether an API will change under you — it's whether your architecture absorbs that change in one place or in two hundred.

The fix

A provider abstraction layer, from day one.

The fix is a thin internal interface that the rest of your codebase calls, instead of calling the provider's SDK directly:

  • One internal interface — your application code calls something like generate(prompt, options), never the provider SDK directly.
  • Provider-specific logic lives in one place, behind that interface — request formatting, response parsing, retry behavior, all contained to a single module.
  • Model and provider become a config value, not something hardcoded across the codebase. Swapping models, or adding a fallback provider for resilience, becomes a configuration change, not a rewrite.
  • Deprecations get patched once. When a provider changes something, the fix happens in the abstraction layer, and every call site is fixed simultaneously without being touched.

This is a small amount of upfront engineering discipline that costs almost nothing at prototype scale and becomes the difference between a config change and a three-week outage once the product is live.

A second benefit

It also makes cost and quality experiments cheap.

The same abstraction that protects you from a breaking change also makes it trivial to route different requests to different models — a cheaper model for simple requests, a more capable one for complex ones, or an A/B test between two providers on quality — because the switch happens in configuration, not in application logic. The resilience benefit and the cost-optimization benefit come from the same architectural decision.

Related

Where this fits.

A provider abstraction layer is a standard part of our MLOps and LLM integration work — built in at the architecture stage, so a provider change is a config update, not an incident.

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