Lesson 4: Production Monitoring, Governance, Improvement, and Practice

This lesson develops practical understanding of production monitoring, governance, improvement, and practice within the ISTQB Certified Generative AI Testing (CT-GenAI) Training. It connects core concepts with realistic testing and quality-engineering decisions.

Learners examine methods, evidence, risks, stakeholder expectations, and implementation considerations before applying the ideas in a focused activity.

Topics Covered

• Production logs, traces, prompts, outputs, feedback, and privacy controls
• Quality monitoring, drift, model updates, prompt changes, and regression
• User feedback, review queues, incidents, and corrective action
• Responsible AI governance, documentation, accountability, and audit
• Versioning models, prompts, data, evaluations, and guardrails
• Continuous evaluation, red teaming, experiments, and residual risk
• Certification scenarios for testing, evaluation, safety, and governance

Practical Activity

Apply the lesson concepts to a realistic ISTQB Certified Generative AI Testing (CT-GenAI) scenario and document the test approach, evidence, risks, and recommended next actions.

Lesson Outcome

Learners can explain and apply production monitoring, governance, improvement, and practice using structured, risk-aware, and evidence-based testing decisions.