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Training teams for AI agents·Template

Learning path template for AI agent roles

A learning path template for AI agent roles: which track each role takes, in what order, what proves completion and what triggers the next step.

Map each person to the decisions they make, then give them tracks in a fixed order: a shared foundation first, then reviewer certification for anyone who approves held actions, then builder for those who design agents, then architect for those who lead regulated, multi-agent deployments. The template below sets this out by role, with the proof each step requires.

What is a learning path, and why order matters

A learning path is a sequence of learning steps that leads a person from where they are to a defined level of competence for a role. The general idea is explained in what a learning path is. For agent roles, order is not a matter of taste. Each step depends on the one before.

A reviewer cannot judge a held action without knowing what depth means and how verdicts are decided. A builder cannot write a sound agent brief without having decided held actions, because they will not know what reviewers need to see. An architect cannot design controls across several agents without understanding how a single agent is built and certified. Skipping steps produces people who can pass tests but not make decisions.

The guide to training teams for AI agents sets the same order for teams. This template applies it to individual roles.

How do you fill it in?

  1. List the roles in your organisation that touch agents. Use job families, not job titles, so the path survives restructures.
  2. Write each role's decisions in one line: what it approves, designs, owns or audits.
  3. Assign the tracks in order. Stop each path at the highest track the role needs.
  4. Define the proof for each step: a test, a practicum, a certified agent, a board review.
  5. Write the trigger for moving to the next step, and the trigger for renewal.

For a fuller walk-through of these steps, see how to create a learning path for AI agent roles.

The learning path template

Role family Decisions about agents Step 1 Step 2 Step 3 Step 4 Renewal
Executives and board members Approve risk appetite; sign off depth policy Shared foundation Stop here Refresh when the product version changes
Buyers and procurement Choose and contract for agents Shared foundation Stop here As above
Frontline staff who read agent output Act on information the agent provides Shared foundation Stop here As above
Reviewers Approve, edit or reject held actions Shared foundation Certified reviewer Every 12 months
Team leads and operations managers Run the held queue, calibration, cover Shared foundation Certified reviewer Every 12 months
Builders Write briefs, choose sources and bounds, run certification Shared foundation Certified reviewer Certified builder Every 12 months
Architects and deployment leads Design controls across several agents in a regulated setting Shared foundation Certified reviewer Certified builder Certified architect Every 24 months
Risk, compliance and audit Test controls, reconstruct decisions Shared foundation Certified reviewer for those who sample decisions Architect for the lead Matches the highest step held

Add a column for "Proof" if your auditors want it in one place: test score, practicum record, certified agent, board review.

Worked example

Take an illustrative university that runs agents in admissions and student services. The roles needing training are covered in more detail in which roles in universities need AI agent training; here is one path from that set.

Role family: digital services officer, student services. Decisions: maintains the student services agent's brief; prepares it for certification; reads refusals to spot gaps.

  • Step 1, shared foundation: completed in week 1. Proof: test score by concept.
  • Step 2, certified reviewer: weeks 2 to 8, including a two-week practicum on the agent's held replies. Proof: marked practicum and certificate.
  • Step 3, certified builder: weeks 10 to 20, ending with a capstone agent certified on the university's own past enquiries. Proof: the certified agent and a builder certificate.
  • Step 4: not needed for this role; the director of student services holds the architect path.
  • Renewal: both certificates every 12 months, placed outside enrolment.

Some organisations attach internal recognition to each completed step; how that works is explained in what a learning credit is.

Where the Academy fits

Pryme Intelligence Academy is built as this path: four tracks, each the key to the next. Foundations takes about four hours and earns a free badge with no expiry; Operator about 14 hours plus a practicum; Builder about 24 hours plus a capstone; Architect about 30 hours plus a capstone and a board review. Operator and Builder certificates last 12 months, Architect 24 months.

Questions people ask

Can someone skip straight to the builder track?

They should not. A builder who has never decided held actions writes briefs that make reviewers' work harder. The reviewer step is short compared with what it saves.

Who should own learning paths in an organisation?

Learning and development usually maintains them, with process and agent owners deciding the content for each role. The split is covered in the role of learning and development in AI agent rollouts.

What happens when someone changes role?

Re-map them. If the new role needs a higher step, start it before they take on its decisions. If it needs a lower one, their existing certificates can simply lapse at expiry.

Train the people who run your agents.

Pryme Intelligence Academy: free courses on the real product, audio lessons, labs in a free workspace, and certificates anyone can check on VerifyDoc.ai. Teams get seats, an admin view and a free readiness assessment.