LLM Cost Optimization

Agent initiatives often stall because of cost, not feasibility. Costs explode when context windows grow, retrieval becomes noisy, tool orchestration triggers multiple model calls per task, and systems retry repeatedly. Optimizing cost requires engineering discipline and measurement tied to outcomes.

Start by measuring: tokens, model calls, retrieval payload size, latency, and the workflow result you care about. Then reduce cost drivers systematically. Improve retrieval quality to return fewer, higher-signal chunks. Constrain tool loops to avoid runaway calls. Cache stable computations. Route simpler requests to cheaper mechanisms while reserving higher-capability calls for high-value tasks.

Cost work must be validated with evaluation. If optimization reduces groundedness or increases unsafe actions, you didn't optimize—you broke reliability.