Share what belongs together.
In a multi-agent workflow, one agent’s result may become another agent’s input. A shared store can preserve decisions between handoffs, but it also introduces questions about ownership, visibility, and conflicting updates.
UniMem records scopes and applies admission controls to reads and writes. Shared memory still requires your team to define which principal may act for which workflow. An unrestricted local process should not be mistaken for an organization-isolated deployment.
Use separate project or tenant boundaries where information must remain separate. Test both permitted retrieval and refusals with the credentials that will actually run the agents.
Memory scope implementationDetect when an agent’s premise has changed.
An agent can read a fact, generate an update, and discover that another agent changed the fact before the write. UniMem’s opt-in team isolation supports declared point-read versions and commit-time stale-generation checks.
Snapshot, serializable, and sequenced modes have different contracts. Sequenced work also uses an exclusive work-item lease and fencing token. A stale write can return STALE_GENERATION rather than commit its generated fact.
A proposed semantic merge creates a review item while preserving source facts. It does not silently resolve a semantic conflict with last-write-wins.
These guarantees require a complete declared point-read set and one shared local lock domain. They do not provide predicate locking or multi-host consensus.
Measure the team, not just the retrieval count.
A memory that helps one task family may distract another. Context labels make that distinction available to the local measurement workflow and the newer contextual allocation gate.
Shared environments also create interference: one agent’s actions can change another agent’s outcome. Independent-task assumptions may then fail. Decide whether tasks, teams, or other clusters form the appropriate unit of evaluation before making a causal claim.
Start with a bounded handoff, observable inputs, and a final result you can attribute to the workflow. Expand only after your team understands missing outcomes, cross-agent effects, and the limits of the chosen design.
Interference and experimental designPut experience to work.
Try the local loop, or bring one workflow to a pilot conversation.
Technical details link to the inspected source. Check deployment requirements before enabling optional features.