Organising your AI workflow is no longer just about putting the chaos in order, it directly impacts your AI costs. Every command your agent runs and every file it reads ends up in the context window, and the bigger that window grows, the more you pay and the less focused the agent becomes.

This article looks at three tools I run in my local dev setup to fight that - one for trimming shell output, one for compressing context and one for giving the agent a memory that outlives the session. It also covers where context compression falls short, when running Claude Code through a proxy.

Coding agents forget everything between sessions, and the bigger the codebase grows, the more they have to rediscover before they can do anything useful.

This article covers spec-driven development as a whole - why agents need specs, the frameworks worth starting with, and how my own setup evolved from homegrown commands to OpenSpec and beads.