This post originally appeared on tokenjam.dev/blog . It's part of a 14-post series on the agentic AI ecosystem. TL;DR An LLM gateway is a unified API layer that abstracts away provider differences, sitting between your app and OpenAI, Anthropic, Bedrock, or any other LLM provider. Core functions: single API interface, key management, rate limiting, automatic fallbacks, retries, response caching, and observability of API traffic. Teams adopt them to reduce vendor lock-in, control costs, swap models without code changes, and gain visibility into LLM usage. Gateways and observability tools are converging, though they solve different problems: routing decisions vs. measurement. You need one if you use multiple providers or run agents in production; single-provider hobby projects don't require one. What is an LLM gateway?…