A practical guide to testing AI agents built in Microsoft Copilot Studio. Covers why agent testing is harder than traditional software testing due to nondeterminism, silent failures, and unpredictable user behavior. Explains how classic testing types (unit, integration, E2E, regression, performance) map to agent testing with adjustments. Details Copilot Studio's built-in tools: test canvas, conversation trace, variable inspector, analytics dashboards, and the Evaluate feature for automated testing. Provides a four-layer testing framework (prompt/intent, knowledge/grounding, actions/connectors, conversation flow), a pre-publish checklist, key metrics for test readiness (95%+ trigger accuracy, <5% fallback rate), and actionable steps like building a test utterance bank and running exploratory sessions with uninitiated users.