Spent the evening auditing and overhauling my entire agent ecosystem against Anthropic's published best practices. 20 agents, all getting smarter.
The process: kicked off a Research agent to pull every relevant Anthropic engineering post (Building Effective Agents, Context Engineering, Writing Tools for Agents, Effective Harnesses). Then ran parallel Explore agents to map every skill file and context doc in the system. Fed all of that into a Plan agent to design the changes.
Four phases shipped:
Progressive disclosure for the four largest context docs. Tank, Keeper, Link, and Forge were loading 400-900 lines of context on every invocation. Now they load a slim core (infrastructure overview, key IPs, safety rules) and pull in reference files only when the task actually needs them. Troubleshooting docs, runbooks, and architecture patterns stay out of context until relevant.
Standard error handling across all 20 agents. Three rules: retry once then report, never claim success if something errored, and if blocked, say what worked and what didn't. Simple, but none of them had it before.
Pipeline handoff contract for the prospect workflow. Radar, Signal, Ghost, and Morpheus now share a formal data contract defining exactly what fields pass between each stage. No more informal handoffs.
State persistence for infrastructure agents. Tank and Keeper now write checkpoints during multi-step work so they can resume if a session dies mid-task instead of starting over.
The whole thing ran in about an hour. Plan mode kept the scope tight. Three background agents split the context docs in parallel while I handled the other phases. No content lost, just reorganized for efficiency.
The key insight from Anthropic's docs: context is a finite resource with diminishing returns. Every line your agent loads that it doesn't need is stealing attention from the lines it does.