Team adoption of Claude prompt caching: habits and norms
Turn Claude prompt caching into a durable team habit: centralized prompt assembly, cache-aware reviews, hit-rate dashboards, and shared norms.
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Turn Claude prompt caching into a durable team habit: centralized prompt assembly, cache-aware reviews, hit-rate dashboards, and shared norms.
Claude prompt caching cost model: 1.25x writes, 0.1x reads, break-even math, and where latency and dollar savings actually come from.
Move an existing workflow onto Claude agents safely: strangler-fig migration, shadow mode, canary traffic, and clean one-flag rollback.
Build a Claude agent eval loop: outcome and trajectory metrics, real-failure datasets, rubric-driven LLM-as-judge, and CI gates that block regressions.
Harden Claude agents with sandboxing, least-privilege tools, safe secrets handling, and prompt-injection defense — concrete patterns for untrusted input.
Cut Claude agent cost and latency with prompt caching, batching, model routing, and context discipline — techniques for cheaper, faster runs.
Diagnose and fix Claude agent failures — tool-call loops, wrong tool selection, and hallucinated arguments — without invalidating your prompt cache.
Design Claude context to cache well: a three-layer budget for what to keep, what to cut, and how to inject dynamic facts without breaking the cache.
Make Claude tool use and MCP servers cache-friendly: deterministic schemas, host-side auth, well-formed error results, and idempotent side effects.
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