Token-Efficient Agent Design: Reducing LLM Costs Without Sacrificing Quality
Practical strategies for reducing LLM token costs in agentic systems including compact prompts, tool result summarization, selective context, and model tiering approaches.
Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
Practical strategies for reducing LLM token costs in agentic systems including compact prompts, tool result summarization, selective context, and model tiering approaches.
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