AgentField just released a multi‑agent code reviewer that builds a custom strategy for each pull request. A planner scans the PR, then dispatches specialized agents—security for auth changes, schema for migrations, behavior for refactors—according to team settings. Deployable via a single Docker‑Compose file, it runs on open or closed models such as Kimi, DeepSeek or Claude, costing only cents per review.

LLM agents consume tokens rapidly because they loop, resend full context each turn, and call the most expensive frontier models. Claude Opus 4.7 charges $5 per million input tokens and $25 per million output tokens, so a simple chat stays cheap while a multi‑step review can reach hundreds of thousands of tokens. A router sends each request to the cheapest model that can handle its difficulty.

Implementing a router requires two layers: a unified entry point that translates a standard request into each provider’s API, and a decision engine that selects a model based on known signals or on‑the‑fly difficulty prediction. Teams that adopt this pattern report up to 50 % cost reduction while preserving 95 % of frontier‑model quality, proving that smarter routing tames token waste.