Every agent, on every run, starts with everything your team has already learned, your architecture, your conventions, your gotchas. The more Clears ships, the smarter it ships.
Global memory holds the conventions that span your whole org. Repository memory captures the patterns of each codebase. Session memory records exactly what happened on every run, files changed, decisions made, contracts discovered. Each tier feeds the agent at the right moment.
Clears doesn't keep a chronological log. After each story, a model distills raw execution data into living, deduplicated knowledge documents, patterns, decisions, gotchas, API contracts, organized by topic and merged into your global and repo memory.
Semantic search surfaces past executions by concept, not keyword. Ask "how did we handle rate limiting?" and get back the runs that actually did it, ranked by relevance.
The agent already knows your setup. It follows your conventions and past decisions instead of inventing new ones.
Gotchas from past runs are handled proactively, not relearned the hard way.
Pre-load repository memory with your architecture and patterns so the very first execution lands like it's your hundredth.
Memory is the difference between an agent that guesses and an agent that knows. It's editable, inspectable, and yours, a knowledge base that grows every time a story ships.
