Memory and context injection
Read more about SDD in Spec-Driven Development.
Maturity: Not for now
Summary
Agents generating or refining an Agent plan need context beyond the current work item: project conventions, past decisions, architectural patterns, team preferences. This page covers how that external context is modeled, stored, and injected.
Epic: Workstream 2 — Memory loop
Memory layers
Context exists at multiple scopes: Project, Group, Instance, Organization. The model for retrieving and prioritizing layered context is TBD. A possible fifth scope (Product) has been discussed.
Injection point
Where in the AI Gateway pipeline memory gets injected — before prompt assembly as system context, or as a tool the agent calls on demand — is TBD.
Learning loop
When an agent completes work and the result is reviewed (approved/rejected), the outcome should be captured as a learning and fed back into memory for future plan generation. The mechanism for this feedback loop is TBD.
Storage
Where memory lives — repository files (.gitlab/memory/), a database-backed store, or the Wiki — is TBD.
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