Testing AI Boundaries: System Prompts and LLM Constraints

Large language models rely on system rules to behave correctly, but how secure are these boundaries? Understanding how to design, test, and defend these rules is essential for building robust AI systems that behave exactly as intended. In this text-based course, you will explore the relationship between human input and machine constraints, transitioning from writing basic prompts to understanding the deep mechanics of system instructions, role definition, and security boundaries in modern language models. What you'll learn: * Understand the role of system instructions in controlling model outputs; * Design robust developer rules to restrict AI behavior to specific domains; * Test the boundaries of AI models using adversarial prompting and injection techniques; * Apply defensive prompt engineering strategies to protect your applications; * Analyze how models handle conflicting instructions between system rules and user input. This course starts with foundational concepts of model roles and system prompts before moving into practical scenarios where you will analyze and test constraint boundaries through written examples. This course is designed for beginners interested in prompt engineering, AI development, and application security, with no prior machine learning experience required. Start exploring the limits of AI behavior and learn to secure your applications today.