Claude Code, Beyond the Prompt — Part 7: How I Cut Claude Code's Token Bill (and Made It Faster)

Short summary

Part 7 of a series on running a live automated trading system on Claude Code, focused on cutting token bills and latency. The core insight: tokens are the shared currency of cost and speed — reducing what Claude reads wins on both. Six prior architectural patterns (memory files, grounding, command invocations, MCP tools, semantic search, GitHub as task queue) collectively form a token-reduction system, with semantic search delivering ~20× reductions per lookup. Three additional levers — prompt caching, deferred tool loading, and subagents for heavy reading — provide further savings.

• •Tokens drive both cost and latency; reducing context size improves both simultaneously
• •Semantic search over whole-file reading yields ~20× token reduction per lookup
• •Prompt caching, deferred tool loading, and subagents are three additional pure token-saving levers

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