make-plan

To create a memory-grounded work plan, load recent session timelines and vector memory to search for past summaries, decisions, and errors. This surfaces known blockers so you can prioritize tasks and organize upcoming sprint work realistically.

Memory-aware sprint planning generates concise 3-5 step plans by referencing actual files, systems, and decisions from past sessions. It loads timeline and vector memory searches to identify in-progress work and constraints instead of planning from a blank slate.

Yes, you can turn a fragmented sprint backlog and multiple session notes into a prioritized roadmap. The process extracts context from memory to resolve in-progress blockers and produces explicit next steps and open questions for the project.

After generating your work plan, persist it as a decision in the memory store. This records the prioritized steps and resolved blockers into the session timeline, ensuring future planning cycles can reference the project context.

Plans made from a blank slate miss prior decisions and known blockers. You need to load recent session timelines and vector memory to search for summaries and errors, ensuring next steps are aligned with past project context.