Evaluate before you trust
Use a small representative set to test an AI feature.
Choose cases that can reveal failure
Build examples for a straightforward question, an ambiguous question, missing source context and a misleading instruction inside retrieved content. Specify the expected behavior before testing the system.
Record evidence and limits
Review correctness, grounding and whether the tool stayed within its permitted actions. Repeat key checks after changing a prompt, model or content source. Keep automated scores separate from human review and learner self-assessment.
Keep simulation and evidence distinct
A small simulated test can demonstrate a mechanism under its stated assumptions. It cannot establish that a real external integration behaves identically. Label which pieces are simulated, use controlled synthetic fixtures and test the real boundary separately before relying on it.