TEACHING AI AGENTS WHERE THE LINE IS

Most teams experimenting with agents ask questions constantly: Which actions can be automatic? Which need approval? Which should be blocked?

The constant questioning is necessary because the boundaries rarely sit in the model. They have to be designed into the workflow.

This becomes more important once an agent can update a record, submit a form, send a communication or trigger another system. In regulated work, a poor judgement quickly becomes an operational, legal or evidentiary problem.

Our latest Brightbeam Perspective looks at the governance layer around agentic systems - how organisations can define those boundaries, enforce them at the point of action and test whether they hold under real conditions.

But it's a lighter, more enjoyable read than that makes it sound. See the full story on our Substack.