Agent pilot walkthrough
Watch an agent handle an inbound request end to end: understand it, retrieve context, draft a response, check it, and route it, with the rules that decide when it acts alone and when it hands off to a person.
What it shows
- What an agentic pilot actually does, step by step
- The difference between a confidence gate and a policy gate
- Exactly when a person stays in the loop, and why
A demonstration built from public and synthetic data, not from any real client or organization.
This demonstration follows a single request through an agentic pilot from arrival to resolution: the five steps it runs, the rules it checks its own draft against, and the moment it either sends the reply or hands off to a person.
Two scenarios below run a small agent through the same five-step pattern: understand the request, retrieve the relevant context, draft a response, check the draft against a fixed set of rules, and route it. Every request either gets sent automatically or escalated to a person, and the reason is always visible.
The two ways a request escalates are the interesting part: because the agent genuinely could not resolve something with confidence, or because the request type is flagged for mandatory human review no matter how confident the agent is. Those are different architecture decisions, and conflating them is a common way a pilot ends up escalating everything, or nothing.
Scenario
Inbound request
Inbound message
“Hi, I filed a permit application three weeks ago and haven't heard anything. Can you tell me where it stands?”
A demonstration using a scripted, synthetic trace. No request here calls a model; every step, check, and outcome was written by hand to show how the pattern works. No real applicant, case, or organization is represented.
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