Monitor the service and its safeguards
Course overview · 4 min reading + 12 min practice, estimated
Principles and method
Monitor outcomes, quality, reliability and handling controls together. A healthy API can still produce unusable candidate summaries. Define signals tied to known failure modes, such as queue age, unmatched records, correction rate and blocked unauthorised actions. Set thresholds with a baseline and review them as volume changes. Every alert needs an owner and an action; excessive noise trains people to ignore it. Distinguish a warning requiring investigation from a condition that should automatically pause a workflow. Keep monitoring proportionate to the information being processed.
Worked example
A workflow reports 99% technical success but reviewers correct many role locations. The dashboard adds a material correction measure and a source-field check rather than celebrating successful requests alone.
Put it into practice
Choose six monitoring signals for an interview-pack workflow and assign actions.
Use fictional information and keep your work in your own notes.
Compare your approach: self-review guidance
Include one quality signal, one backlog signal and one handling control. Explain the denominator and threshold. Remove alerts that have no clear owner or response.
Sources and further reading
Original Academy teaching and fictional examples. These references provide context, not endorsement. Edition 2026.09; updated 2026-09-24.
- GOV.UK: Responsible AI in recruitment
UK guidance on procuring and deploying recruitment AI.
- NIST: AI Risk Management Framework
Voluntary framework for organising AI risks and controls.