When a prototype uses only one model, the integration feels simple. You add an SDK, set one API key, and ship the first version. The risk appears later. A production AI feature may need GPT for general reasoning, Claude for long-context writing, Gemini for multimodal tasks, DeepSeek for cost-sensitive coding, and Qwen or other Chinese LLMs for Chinese-language scenarios. Each provider can have different keys, pricing, model names, latency, and failure behavior. That is why many teams eventually add an AI API gateway. The integration risk is not just code Changing providers is rarely only a code change.…