Customer data glossary

Trainer agent

A trainer agent is an agent that keeps evaluation sets and drills current and proposes rail changes, without editing a production rail or approving its own proposals.

By Art Kukharenko · Published 2026-11-02 · Updated 2026-11-02

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Part of the Learn hub and the customer data glossary.

What it means in practice

A trainer agent stops corrections from vanishing. On AI agent rails it is called the Trainer, and it runs at L2. It reads masked samples, ledger entries with masked payloads, rail cards and evaluation sets. It proposes test cases, rail changes and training assignments, and it runs tests in non-production only.

It has two audiences. For agents, it turns reviewer rejections and edits into labelled test cases and flags drift. For people, it prepares drills, such as a deliberately bad draft that a reviewer should reject. The rail owner accepts each addition and change, and the data protection officer decides on data scope.

The name can mislead, because a trainer agent does not retrain a model's weights. It improves tests, rails and people's skills. A rail changes only when its owner accepts the proposal.

People-facing work needs care. EU AI Act Annex III point 4(b) lists monitoring workers' performance and allocating tasks by individual behaviour as high-risk uses 1, so report drill results by rail and role, and take advice. Article 4, as amended in 2026, asks providers and deployers to take measures that support AI literacy 2, and drills can form part of those measures.

A script, a calendar and a monthly review can do this job for a small team.

A trainer agent is a role in a vendor-neutral method, and PrivyCDP does not ship one. PrivyCDP expects teams to check AI outputs, and those checks are the raw material for this kind of loop.

Example (professional services firm, illustrative): reviewers keep rejecting drafts that misread a date field. The Trainer proposes a new test case and a change to the rail's output contract. The rail owner accepts the case, rejects the change, and the regression run happens in non-production.

Evaluation set: what it keeps current.
Rail card: what it may propose changes to.
Rail level: it stays at L2.
Orchestrator agent: moves work, while this one improves it.

Where it matters

The Trainer agent: how teams and agents learn on rails.
Data quality triage: historic failures become tests.

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FAQ

Can reviewer feedback change an agent automatically?

Not on a rail. Feedback becomes a proposal, and the rail owner accepts or rejects it. Automatic learning from reviewers would let one person's habits, or a compromised account, reshape a production rail.

Does a trainer agent grade individual staff?

No. It must not rank named staff. Report by rail and role, and take advice before any report could identify a person.

Sources

This entry is general information, not legal advice.