Lesson 1
Capability is not permission
An AI system being technically able to act does not mean the business should allow it to act autonomously.
All learning tracks
Applied AI EngineeringApplied 90 min
AI Governance & Human-in-the-loop
Turn confidence, risk, approval, auditability and fallback into concrete workflow controls.
GovernanceHITLRisk
Learning outcomes
Define approval thresholds
Design audit evidence
Separate low-risk assistance from high-risk action
Guided lessons
Learn the engineering thinking
Lesson 2
Risk-tiering decisions
Classify actions by consequence, reversibility, regulatory sensitivity and customer impact.
Lesson 3
Human approval patterns
Use review, edit, approve, reject and escalation patterns where confidence alone is insufficient.
Lesson 4
Auditability
Capture context, prompt/version, output, confidence, user decision and final action so outcomes can be reconstructed.
Lesson 5
Safe fallback
A mature workflow knows when to stop, escalate or ask for clarification instead of fabricating certainty.
Hands-on practice
Do something with what you learned
Do not just tick these mentally. Write the query, create the test matrix, refactor the code, or document the decision. Practical evidence is the point.