AI Gateway

TL;DR * Coding agents bill by token, so the real cost of running them at enterprise scale is driven by context size, redundant calls, and model choice, not by seat licenses. * Connecting 8 to 16 MCP servers to a coding agent loads every tool definition into context on every turn;

TL;DR * LLM infrastructure is the full set of compute, serving, data, routing, and operational systems that take a large language model from a model file to a reliable production service. * The stack has five layers: GPU compute, model serving and inference, the retrieval and data layer (vector databases), the

A guide to attributing LLM tokens, requests and cost to the team that generated them, and the six tools and approaches that do it.

TL;DR * Claude Pro costs $20 per month and gives at least five times the per-session usage of the free tier, but that usage is still capped by a five-hour session window and a weekly limit that applies across all models, per Anthropic's Help Center. * Claude

A guide to fixing Claude rate limit exceeded errors, covering the three limits behind a 429 and how a gateway routes around saturated quota.

Bifrost, LiteLLM, Kong, Envoy and Apache APISIX compared as open-source AI gateways on performance, MCP support, governance and caching.