A walkthrough is a guided demonstration in which someone who knows a task or system takes others through it step by step, explaining each decision as they go. For AI agents, a walkthrough usually follows one case from start to finish: what arrived, what the agent did, which verdict it reached, what the person checked, and what was filed.
Why does a walkthrough matter?
People new to agents often cannot picture how the parts fit. Being told that "every action meets five bounds and the lowest wins" is abstract. Watching someone open a held payment, show the source class of the invoice, show the limit that held it, and approve or escalate, makes it concrete.
Walkthroughs also make reasoning visible. An experienced reviewer explaining why they sent a draft back shows what to look at and in what order. That tacit knowledge rarely makes it into procedures.
How is a good walkthrough run?
A useful walkthrough for agent oversight has a clear shape:
- Pick a real case, with details changed, that shows the point you want to teach.
- Start from the queue: what the reviewer sees first.
- Open the verdict: which bound decided, and why.
- Check the sources: which are sealed, signed, declared or external.
- Make the decision aloud: approve, send back or escalate, with the reason.
- Show the record: what has been filed and how it could be reconstructed later.
- Invite questions, then let a learner drive the next case.
The last step turns a demonstration into practice. Walkthroughs where the learner never takes the controls teach less than they seem to.
An example
A clinic group introduces an agent that drafts appointment reminders and rescheduling messages, holding any that mention test results. The new practice manager's induction starts with a walkthrough. Her predecessor takes her through five cases: a routine reminder sent, a rescheduling draft approved, a message held because it referred to a scan, one refused because the patient had withdrawn consent for messages, and one where the agent's certificate had lapsed and it could only read. She then drives five more herself. The guide to onboarding a clinic practice manager to an agent workspace covers the rest of the induction.
How is a walkthrough different from a worked example?
A worked example is a solved problem presented for study, usually written, with each step shown. A walkthrough is a live, guided tour, often of a system, with explanation and questions. A worked example can be read alone; a walkthrough is usually led by a person. Both show rather than ask, which is why they should be followed by practice.
It also differs from a demo, which shows what a product can do. A walkthrough shows how to do a job with it.
Which terms are related?
- Worked example: a written, solved case.
- Lab exercise: hands-on practice after a walkthrough.
- Centre of excellence: a team that often owns walkthrough material; see what a centre of excellence is.
Walkthroughs are part of what a team should practise before an agent goes live, and again before raising an agent's depth. For the full approach, read training teams for AI agents.
Where the Academy fits
Pryme Intelligence Academy lessons are paired with labs in a free Build workspace, so learners move from seeing how a governed agent decides to working cases on the real product themselves. That is the walkthrough-then-practice pattern built into the track.
Questions people ask
How long should a walkthrough take?
As long as one or two cases need, usually fifteen to thirty minutes. Several short walkthroughs on different points work better than one long one.
Should walkthroughs be recorded?
Yes, for people who join later. Keep each recording to one case and label it with the agent version it shows.