How to Tame Runaway LLM Token Costs With Smarter Model Routing

Running LLM agents in production can rack up massive token bills when every loop hits the most expensive frontier model. In an interview with Kilo's founders, the article breaks down practical cost-control patterns already used by tools like Cursor, Cline, and OpenRouter. Key strategies include intelligent model routing that matches task complexity to the cheapest capable model, prompt caching to avoid resending full context, and context distillation to shrink what actually reaches the API. These techniques apply to any agent making repeated model calls, not just coding agents.