People and AI agents on one team. Here’s the human’s part.
People in the loop means people and AI agents work side by side, and a person decides what an agent can approve, stop or escalate. Picture a flat team, each member doing what they do best. Governance frameworks say “a human reviews it” and stop there. People in the Loop describes what that human does.
Five moves, in order.
The human in the loop is a teammate with a named role and written authority. Here’s what they bring.
- 01
Read the intent
Before judging the output, read what the agent set out to do and what it was told.
- 02
Read the trace
Follow the steps, the tools it touched and the sources it used.
- 03
Add what it can’t see
The client history, the politics, the thing that changed this morning.
- 04
Decide, with a reason
A decision with a written reason can be checked, taught and improved.
- 05
Feed it back
Settled questions stop coming back, and new ones get the attention.
A role with a name, a budget and a stop.
Named, in writing
Each agent works with a named human partner. Their authority is written down, so every human on the team knows who can say stop.
An approval budget
Reviews take time. The role gets hours and money for them, and the number is tracked.
Metrics that catch decay
Approval rates that drift toward 100% mean the review stopped working. Measure for that.
Fresh eyes on purpose
Reviewers rotate so the same blind spot doesn’t approve the same mistake for a year.
A stop that works
The human can halt the agent, and the halt has been tested before it’s needed.
High agency
Caution fails in both directions. The job needs a human willing to approve, and willing to stop.
The 3 Stages of AI Adoption
The loop looks different at each stage. Same job, different scale.
Exploring
Curious, but not using AI consistently. Needs confidence and simple wins.
The loop: a person checks every output before it’s used.
Applying
Using AI tools, but not systematically. Needs workflow integration.
The loop: a named reviewer per workflow, with a written reason for each decision.
Automating
Systematic AI use, ready for agents that act on their own.
The loop: an approval budget, decay metrics and a tested stop.
Human oversight as a control
NIST AI RMF, the EU AI Act’s Article 14 and ISO 42001 all call for it. I build on that work and credit it.
The human as a named role on the team
Training, metrics and a budget, run with the discipline of a security operations team and mapped to the 3 Stages.
People ask
What does people in the loop mean?
People and AI agents work side by side on one team. Agents do the tasks. A person brings what can’t be written down and decides what an agent can approve, stop or escalate.
Who decides when an AI agent acts?
A named person with written authority. They read what the agent intended, read what it did, add context it can’t see, and decide with a written reason.
How is this different from human in the loop in data labeling?
In data labeling, a human corrects training data. People in the loop is about live work: a person on the team who reviews, decides and feeds the decision back while agents work.
Does a small business need a human in the loop?
Yes. The job is the same at a three-person shop and a ten-thousand-person firm. Only the scale changes.
Can the human in the loop be automated?
No. Knowing when to stop an agent depends on knowledge people can’t fully write down in advance, so the judgment stays with a person.
In the Loop
Essays on people and AI agents working together. Sources linked, no hype.