Glossary

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Glossary / Evaluation and implementation guide

Agent Supervision

Agent supervision is the ongoing oversight layer that governs what an autonomous AI agent may do: which actions require review, who reviews them, and how exceptions are escalated.

It spans policy configuration, audit logging, and reviewer workflows, and applies continuously rather than only at launch.

A practical example

Example: an agent that drafts renewal emails runs unsupervised for low-value accounts, but every message above a set contract value queues for a sales manager's review before sending.

What to evaluate before investing

  • Ask how supervisors are notified of pending actions and whether review queues support assignment, comments, and bulk approval.
  • Confirm the platform logs every agent action with inputs, outputs, and the reviewer decision for later audits.
  • Test whether supervision rules can change per workflow, per segment, or per risk level without rebuilding the automation.

Limitations and tradeoffs

Supervision adds review latency; over-restricting agents can erase most of the time savings that justified the automation.

Plan your next step with MeshLine

Connect this decision to your automation, organic marketing and customer lifecycle management. In a MeshLine demo, discuss your existing tools, the scope you need and how to measure the result.