The problem
The first production AI feature was built against OpenAI. A year later the best model for the job is Claude. Six months after that, a self-hosted Llama variant fine-tuned on your domain outperforms both. Migrating means rewriting every call site, every prompt template, every tool schema mapping. Nobody has time. The team ships against whatever they started with and eats the gap.
This is the lock-in tax. It is not charged on invoices. It is charged on velocity.
Why the usual approach breaks
Abstraction layers written by each team diverge. LangChain wraps everything but leaks provider-specific quirks through the abstraction. The platform team writes an internal SDK, and then half the teams ignore it because they already shipped. By the time the next model generation arrives, the surface area to migrate is spread across twenty repositories.
The problem is not the abstraction. The problem is that the abstraction is in the application layer, which changes constantly. It needs to be in the network layer, which does not.
How AI Gateway closes the gap
AI Gateway presents a single provider-agnostic API that every application calls. Under the hood, the gateway translates to whichever provider-and-model is bound to the logical model the application asked for. Tool schemas are normalized. Response formats are normalized. Streaming semantics are normalized. When a team wants to try a new provider, the platform team registers the provider in the gateway and changes one binding. The application code does not move.
Prompt templates live in the gateway as versioned artifacts, not as strings inside application code. When a prompt needs to be retuned for a new model, the platform team rolls a new template version and routes traffic to it. The application sees no change.
Implementation pattern
The gateway exposes one endpoint per logical model: nuviax-reasoning-v1, nuviax-summarization-v2, nuviax-extraction-v1. Applications call these. Providers and prompts live as gateway-side bindings. Migrations are a config change with staged rollout, a shadow traffic period, and a rollback switch. The platform team carries the cognitive load once so every product team can move fast without re-learning a provider API every six months.
Next step
An architecture review inventories your current provider couplings, identifies the three applications with the worst lock-in, and sketches a migration path. Ninety minutes with you, one week to the written output.
Next step
Map Gateway against your stack in 90 minutes.