A more capable agent can finish a longer task. The same persistence can make a bad instruction more expensive.
Frontier agents need containment as part of the product, not as a review note after launch.
Ask:
- which account is the tool using?
- what data can it read?
- what can it change?
- what is the blast radius of one mistaken call?
- what happens when the task becomes ambiguous?
Long-running work needs checkpoints where consequence changes: read to edit, edit to publish, plan to send. Between checkpoints, the agent can continue while recording its objective, changes, and reason for the next action.
Permissions should be task-shaped and expiring. A coding agent may edit a branch but not push. A research agent may browse public pages but not upload files. A support agent may draft but not send.
Test recovery rather than confidence:
- missing required file
- stale or partial tool result
- out-of-scope credential
- ambiguous destructive action
- interruption halfway through
Success means the mistake is contained, observable, and recoverable. The model may be more capable; the surrounding system determines whether that capability remains safe to use.
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About Jeremy London
Engineering leader and builder in Denver. I write about AI platforms, agents, security, reliability, homelab infrastructure, and the parts of engineering work that have to survive production.