The Missing Infrastructure: Why AI Coding Agents Need an LLM Gateway

Coding agents like Goose are evolving from simple autocomplete into sophisticated multi-step workflow engines, fundamentally changing how they consume language models. Each agent session now generates dozens of chained requests with varying computational demands—some steps need premium models, others can run on cheaper local alternatives, and many repeat context that benefits from intelligent caching. An LLM gateway between agent and provider centralizes these decisions, enabling efficient provider switching, cost optimization, and fault handling that direct connections simply cannot achieve at this scale.