Most AI applications begin with a direct model integration. Install an SDK, add an API key and send a...
Most AI applications begin with a direct model integration.
Install an SDK, add an API key and send a prompt. This works well until the application needs a second provider.
A coding task may work better with one model, while another may be more suitable for vision, reasoning, long context or low-cost processing. At that point, model access becomes an architecture problem.
The dependency problem
When provider-specific logic lives inside product code, the application becomes responsible for:
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A practical staging checklist for teams that want multi-model access, better cost control, and fewer...
