AI Evaluation & Reliability

What you'll learn

• Explain why evaluation is the load-bearing engineering activity for AI systems, and why "it looked good in the demo" is not evidence.
• Design an eval: a repeatable way to measure whether the system produces correct, grounded output across a representative set of inputs, rather than judging it by a single impressive example.
• Describe grounding — anchoring the model's answer in retrieved, citable evidence — and why it is the primary defence against confident fabrication.
• Recognise the silent failure modes (hallucinated facts, stale context, ungrounded confidence, evals that pass while the product breaks) and the checks that surface each one.