AI gateways provide a single API endpoint for routing LLM calls across multiple providers, centralizing reliability controls, model selection, and cost governance for multi-agent environments. Key practices include configuring centralized retry logic, circuit breakers, and fallback models to handle provider outages gracefully; using gateway routing rules to swap models per agent task without code changes; enforcing per-team and per-key budget limits via virtual keys and TPM/RPM caps; and instrumenting per-task telemetry to validate routing decisions and catch regressions. Tools like LiteLLM and OpenRouter are highlighted, with Datadog Agent Observability recommended for trace-level visibility across the full agent loop.
