Provider Adapters Are Cheap Insurance

The fastest way to add an AI provider is to call its SDK directly wherever you need it. It also quietly welds your product to that one vendor, and vendors change. Prices move, models get deprecated, a better option appears, a compliance review rules one provider out for a specific customer. When that day comes, "call the SDK directly, everywhere" turns a business decision into a code migration.

A thin provider adapter is the insurance against that, and it is cheap. Put a small interface between your app and the model: your code asks for a completion, the adapter talks to whatever provider is configured. Most modern providers speak an OpenAI-compatible shape, so the interface is not exotic. The cost is one layer of indirection and a bit of discipline about not leaking provider-specific details past it.

What you buy is real optionality. You can point the same adapter at a managed provider in production and a local model in development. You can switch providers through configuration instead of a refactor. You can run one customer on a different backend for compliance reasons without forking your code. And you can make the provider choice a scorecard decision (quality, cost, latency, operations) that you revisit later, instead of a decision you accidentally locked in on day one.

The rule of thumb: any external dependency you would hate to be trapped by deserves a thin boundary. Model providers are near the top of that list right now, because the market is moving too fast to bet the whole product on any single one.