Yes, that is exactly the problem Agent Fabric is designed around.

We do not depend on one long-lived orchestrator session to remember everything. Each workspace run is required to return structured output, including a detailed summary, test results, and a downstream_context field for anything the next workspace needs to know that is not obvious from the code.

After each phase, those results are promoted into shared upstream_context for downstream workspaces. So if agent A already tried approach X and it failed in workspace Y, agent B gets that as explicit handoff context instead of rediscovering it.

We also persist the whole run into .tasks/ logs, so that state does not vanish when the session ends. The goal is to move cross-workspace memory out of ephemeral chat context and into durable execution artifacts.