How memory changes multi-agent collaboration
Memory lets agent teams carry decisions and lessons across runs, but it also needs scope, validation, and traceability.
Without memory, every agent team starts from scratch. With ungoverned memory, every team can inherit stale or unsafe assumptions.
AstraRunner treats this as an execution-platform concern: the run needs durable state, traceable decisions, cost visibility, and enough structure for teams to review what happened after the agent finishes.
Patterns that work
- Store accepted decisions and lessons after validation.
- Retrieve role-specific memory.
- Trace memory usage in handoffs and reviews.
- Supersede outdated decisions.
Implementation checklist
- Scope memory by tenant, repo, workflow, and role.
- Grade memory usefulness.
- Keep source artifacts linked.
- Apply deletion and retention policy.
Watch outs
- Shared memory can spread bad assumptions.
- Role-specific lessons may not generalize.
- Memory needs review just like code.
Related reading
How this fits the Astra stack
AstraRunner owns the operational path for agent work: orchestration, scheduling, approval gates, traces, costs, and role-agent handoffs. AstraMemory owns durable context and retrieval. AstraGenie turns those capabilities into product workflows for teams that want automation without rebuilding the platform layer.