Agentic AI Course: Stage 5 — Lesson 3: Design an Effective Digital Twin System Prompt

An unconstrained AI agent can easily hallucinate credentials, misquote rates, or yield to prompt injections. In this lesson, discover how to engineer a production-ready system prompt for your professional digital twin across five essential pillars: identity, tone, factual grounding, negative constraints, and tool policies. We structure composable Python prompt modules using explicit XML tags and evaluate performance using an automated test harness against five conversational edge cases, verifying zero hallucinations and solid anti-injection defense. How do you handle scope boundaries and unexpected user queries in your own AI prompts?