◦ Prompt · Cache

Give Your Sub-Agent Team Prompt Caching — From Re-Paying for Every System Prompt to a High Cache-Hit Rate in One Session

Paste this into Claude Code, Cursor, or Aider and it'll audit every place your agent team calls the Anthropic API, find where you're re-sending large system prompts and tool schemas at full price on every sub-agent call, and add cache_control in the right places — the shared tool loop, the main conversation history, and the per-agent one-shots — while catching the silent invalidators (a timestamp in the system prompt, an unstable tool order) that quietly keep your hit rate near zero. Audit first, then fix tier by tier. Each fix ships independently with before/after verification from the usage numbers you already get back.

Jun 15, 2026agentprompt-cachingclaude-apianthropic-sdkcost-optimizationtutorial

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Give Your AI Agent a Scout — From Hard-Coded Prompts to Operator-Tunable Doctrine in One Session →

Paste this into Claude Code, Cursor, or Aider and it'll walk your agent codebase through building a scheduled scout sub-agent: a research loop that ends in a validated structured report, an evidence-first rubric with explicit hard kills, rotating hunting lanes that change what it looks for by the day, a review pipeline where a human decides and the agent never does, and — the part almost everyone skips — an instruction set that lives in editable documents your operator can retune from the UI with override, revert, version history and hot reload, instead of a Python constant nobody can reach without a deploy. Interview first, then build tier by tier. Each tier ships independently with verification.