Guides
Working notes on agent performance management: how to make mistakes stick as lessons instead of repeating as incidents.
Agent improvement techniques, compared
Rules files, accumulated memory, postmortem loops, machine checks, pre-action gates, AI review: what each captures, who writes it, and how each one fails.
Read →Strategies to reduce AI agent mistakes: prevent, catch, learn
Every defense works at one of three moments. Which strategy stops which mistake, and why the third moment is the one everyone skips.
Read →How to stop your AI coding agent making the same mistakes
Corrections made mid-session die with the session. The fix is a loop: capture the mistake, write the commitment, re-read it every session, follow up on repeats.
Read →How to make Claude Code remember between sessions
What CLAUDE.md and auto memory actually do, where they fall short for mistakes, and what to add on top.
Read →The best tools to make your coding agent improve over time (2026)
Rules files, memory layers, pre-action gates, evals, and a formal review process: what each one is for, honestly compared.
Read →Agent PIP vs CLAUDE.md, Cursor rules, and memory tools
They solve different problems. Rules hold conventions, memory holds recall, a PIP holds commitments. When to use which.
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