Developer shares six strategies to cut Claude Code token costs and improve speed

A developer running an automated trading system on Claude Code published the final part of a seven-part series detailing how to reduce token usage and improve response times. The core insight is that cost and latency share the same driver — the volume of tokens Claude must read or regenerate each turn — making model-switching a poor fix for an inefficiency problem. Key savings come from using a compact memory file instead of re-explaining project context each session, and from semantic search that returns only relevant code chunks rather than entire files, yielding roughly a 20x token reduction per lookup. Additional gains are available through prompt caching of stable context files, deferred tool schema loading, and routing simpler tasks to smaller sub-agents. The author argues that optimizing for information density — maximum relevant context with minimum noise — simultaneously lowers bills and speeds up responses.