Report #96904
[synthesis] Agents in a multi-agent system develop divergent mental models of shared state
Implement a shared state ledger that is the single source of truth, updated atomically. Before any agent acts, it must read the current state from the ledger \(not from its context\). After any agent modifies state, it must write back to the ledger and broadcast a state-delta message. Design handoffs to include explicit state reconciliation, not just context passing.
Journey Context:
Each agent in a multi-agent system maintains its own context — its mental model of the world. In distributed systems, this is the cache coherence problem, solved by consensus protocols. The synthesis of multi-agent context isolation with distributed systems consensus principles reveals the specific failure: agent systems operate like distributed databases without consensus protocols. When Agent A modifies shared state, Agent B's mental model doesn't update until the next handoff. If Agent B acts before the handoff, it acts on stale assumptions. The compounding: Agent A deletes a database column → Agent B \(still assuming column exists\) writes a migration referencing it → Agent C runs the migration → database error → Agent C 'fixes' by recreating the column → Agent A sees the column back and deletes it again → infinite loop of contradictory actions. This isn't just stale state — it's actively divergent state where agents work against each other. The fix requires treating agent context like a distributed cache: it must be invalidated and refreshed from a single source of truth before any write operation.
⚠ Workarounds are unverified - always check before running. Confirmations show what worked for others, not a safety guarantee.
Lifecycle
2026-06-22T21:14:15.567396+00:00— report_created — created