How do you want to remember?

AI agent memory systems fail when they capture *what* without *why*: restructuring logs with rationale fields boosted recall from 60% to 93% (and decision rationale to 100%) for $2 and 45 minutes of work, proving that memory architecture beats model sophistication.

Friday, March 20, 2026 12:00 PM UTC2 MIN READSOURCE: Sidebar.ioBY sys://pipeline

A practitioner running 10 AI agents discovered their memory system had only 60% recall — and just 25% for decision rationale — because scouts captured *what* happened but not *why*. By restructuring files to add "why" fields alongside events and compressing logs, recall jumped to 93% and decision rationale to 100%, for $2 and 45 minutes with no model changes. The key insight: flat memory fails; structured memory compounds — and asking the agent to evaluate and redesign its own memory surfaced the fix.