Complete Guide to AI Agent Cost Optimization

Not every request needs a frontier model. Route simple tasks (FAQ answers, classification, short responses) to a fast, cheap model (Haiku-class: ~$0.25/M tokens) and complex tasks (reasoning, multi-step planning, nuanced writing) to a capable model (Sonnet/Opus-class: $3-15/M tokens). A classifier model or rule-based router evaluates each request and selects the cheapest model that can handle it. Typical savings: 40-60% with less than 2% quality degradation.

Many agent requests are semantically identical: 'What are your hours?' and 'When are you open?' should return the same cached response instead of making a new LLM call. Semantic caching uses embeddings to match incoming queries against cached responses, serving identical or near-identical results instantly. Effective cache hit rates reach 20-40% for support agents, saving both cost and latency.

Shorter prompts cost less. Audit your system prompts: remove redundant instructions, consolidate examples, use prompt caching (Anthropic's cache keeps frequently-used prompt prefixes warm, cutting costs up to 90% on the cached portion). Typical system prompts can be compressed 30-50% without quality loss by eliminating verbose instructions the model already understands.

Tasks that don't need instant results—nightly ticket categorization, weekly report generation, bulk email personalization—should use batch APIs (50% cheaper than real-time on most providers). Schedule batch jobs during off-peak hours for additional potential savings. A support team that batch-categorizes overnight tickets saves 50% on classification costs.

Stuffing the full conversation history into every request wastes tokens. Implement conversation summarization (compress long histories into key points), selective retrieval (only include relevant KB articles, not all of them), and context pruning (drop stale or irrelevant context). Reducing average context from 8K to 3K tokens cuts input costs by 60%.

Track cost per task (not just total spend): cost per ticket resolved, cost per email sent, cost per document analyzed. Set cost budgets per agent and alert when spending exceeds thresholds. Monitor cost efficiency over time—costs should decrease as you optimize prompts, improve caching, and refine routing. Tools like Langfuse, Helicone, and provider dashboards provide cost breakdowns.