Memory
Context That Makes Agents Trustworthy
Memory is the difference between a one-off bot and a durable agent. It stores intent, decisions, and artifacts that keep collaboration consistent.
Short-term context
Task state, tool outputs, and active constraints during a workflow.
Long-term memory
Reusable knowledge, preferences, and historical outcomes.
Shared workspace
Artifacts that multiple agents can read, edit, and reference.
Governance
Policies for access, versioning, and human override.
Memory that improves outcomes, not noise
Agent memory works when it is curated. Short-term context should capture active constraints, recent tool outputs, and the current definition of success. Long-term memory should store what remains useful across projects: approved decisions, validated sources, and reusable templates.
Treat memory like a knowledge system, not a dump. Summaries should include the date, project, and confidence level. When an agent references memory, it should cite why that memory matters now. This keeps humans confident that outputs are grounded in credible, relevant context.
Governance is essential. Set rules for who can write to memory, what must be reviewed, and how outdated material is archived. Without governance, memory becomes a liability. With governance, it becomes the backbone of consistent human-agent work.
A simple monthly review of stored summaries is often enough to keep memory current and trustworthy.