Enterprise AI workloads are shifting away from closed-source frontier APIs toward open-source models as they scale due to prohibitive API rental costs. For production systems, this means you must architect your pipelines to easily transition from proprietary endpoints to self-hosted open models once your transaction volumes hit the inflection point where hosting your own weights becomes cheaper than paying per token. Failing to build this model-agnostic flexibility into your orchestration layer now will lock you into scaling costs that will eventually break your unit economics.