Saved state, schedules, and events let an agent start or resume work without a fresh chat message each time. The model need not run continuously, and a dedicated computer or agent team is optional. Permissions, human approvals, monitoring, and stop controls still apply.
Level 07
Resume across sessions and events
Each one needs this level and no higher, and says why.
Several always-on agents split personal tasks among themselves, sharing memory and staying inside the same safety rules.
Names listed 09/19/2026. 223 of 223 registry entries have been checked against the maker's own page; the registry marks the rest as unchecked.
Open problems at this level, what people are trying, and the source each rests on. Read 09/19/2026. This block ages faster than the rest of the page, and nothing in it predicts which approach wins.
An agent that runs long enough outgrows its context window, so the platform compresses what came before into a carried-forward summary. OpenAI's documentation says that summary is not meant to be read by a person, which means when a long task goes wrong there is no way to see what was dropped.
What people are trying
It is opaque and not intended to be human-interpretable.
Where it bites: Long-running tasks
A standing agent on somebody's computer can be scoped to named applications, and what it does inside a permitted one can still reach an application it was never granted. A link clicked in an allowed mail client opens a browser that was not on the list.
What people are trying
clicking a link in your email app might open it in Chrome, even if you haven't explicitly granted Claude permission to use Chrome (we can prevent Claude from seeing the Chrome window but can't stop the link from opening).
Where it bites: Always-on assistants
Organizations are accumulating agents from several vendors faster than anything has appeared to govern them together. There is no settled answer to who signs off on what an agent may do, or how agents from different makers are meant to reach each other.
What people are trying
86% of IT leaders are concerned that agents will introduce more complexity than value without proper integration.
Salesforce sells into this problem. What is used here is its survey of IT leaders, not its account of what fixes the gap.
Where it bites: Organizations of agents
A robot deciding its own next move has to judge whether an action would be unsafe, and whether to say it cannot do something rather than attempt it. Dedicated ways to measure those two judgments are new, and the benchmark that exists comes from the same maker as the system it scores.
What people are trying
It also measures the agent's ability to predict whether a task is possible and to proactively request human intervention when uncertain.
Where it bites: Robots and machines
Pages at this level last reviewed 09/19/2026. Pages unreviewed for 90 days are flagged for another pass. Markdown version of this page