Topic starter
11/11/2026 6:04 pm
TL;DR: 70% of organisations give AI systems more access than they would give a human employee, according to Origin's survey data and incident analysis. Shared state turns isolated agents into coordinated swarms when one agent can leave artefacts that another later reads and uses.
Editorial analysis by NHI Mgmt Group, based on content published by Origin: “Eye of the swarm: how shared work becomes agent coordination”.
Key questions
Q: What signs suggest AI agents are using a shared surface?
A: A shared surface is suggested when multiple agents or service accounts leave the same writable state, such as a common file, queue, memory store, or prompt cache, and the same artefacts are repeatedly updated by different identities.
Q: Why do persistent notes and caches matter for agent security?
A: Persistent notes and caches matter because they let an agent carry forward state, decisions, or tool outputs across runs, which can preserve unauthorised instructions, stale credentials, or unsafe assumptions.
Q: How do shared workspaces create agent coordination?
A: Shared workspaces create coordination when one agent can leave an artefact that another agent later reads and uses to change its behaviour.
Practitioner guidance
- Map shared agent surfaces Inventory every writable location an agent can reach, including boards, caches, wiki pages, artefact stores and note files, then classify each by read and write exposure.
- Separate read and write paths Block agents from writing to surfaces that other agents automatically ingest unless the workspace is explicitly designed for coordination and monitored as such.
- Correlate artefact reuse across runs Join session traces, endpoint telemetry and surface logs so you can prove when one agent's output changed a later agent's behaviour.
Bottom line: AI agent swarms emerge when separate runs can share persistent state, not merely when many agents operate at once.
Glossary terms: Agent Swarm, Stigmergy, Rendezvous Surface, Shared State
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11/11/2026 6:07 pm
Shared state is the new identity boundary for AI agents: The important question is no longer only what an agent can call in a session, but what it can leave behind for a later identity to consume. Origin's research shows that once agents can write to a persistent surface, coordination can emerge without explicit orchestration. That makes writable state a governance boundary, not just a storage detail.
A few things that frame the scale:
- 19% of organisations give AI systems dramatically more access than human employees, nearly one in five granting unrestricted privilege, according to the 2026 Infrastructure Identity Survey.
- Systems with least-privileged AI access had a 17% incident rate vs 76% for over-privileged systems. Organisations failing to scope AI access properly are 4.5x more likely to experience a security incident, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: Why do persistent notes and caches matter for agent security?
A: Persistent notes and caches matter because they let an agent carry forward state, decisions, or tool outputs across runs, which can preserve unauthorised instructions, stale credentials, or unsafe assumptions. They should be scoped to a specific agent identity, encrypted where appropriate, and cleared or rotated when authority changes or the agent is retired.
👉 Read our full editorial: Shared workspaces let AI agents coordinate as swarms