What is Generative AI? Understanding the Foundation of Modern AI Agents #2

Everyone is talking about AI Agents. But before you build an AI Agent, there is one concept you absolutely need to understand: Generative AI. Generative AI is the technology that transformed software from systems that simply follow rules into systems that can understand language, generate responses, reason through instructions, and assist users in a natural way. As part of my new course: Develop Your First AI Agent with Microsoft Foundry I published the first lesson where we explore the journey from traditional software to Generative AI and understand why modern AI Agents became possible. 🎥 Watch the video here: Why This Topic Matters Many developers jump directly into AI Agents, prompts, tools, and frameworks. However, without understanding the evolution of AI, it becomes difficult to understand: Why AI Agents exist Why Large Language Models are important Why prompts work Why tools are needed How modern AI systems actually operate In this lesson, we start from first principles and build the foundation required for the rest of the course. What You'll Learn Traditional Software For decades, software followed a simple pattern: Input → Rules → Output Developers explicitly defined every behavior. This worked well until humans started interacting with software using natural language. Why Rule-Based Systems Break Imagine building a dietician chatbot. Users might ask: What should I eat? Suggest a healthy breakfast. What foods contain protein? Can I eat oats daily? All of these questions are similar. Yet they are phrased differently. Supporting thousands of variations quickly becomes impossible with manually written rules. Predictive AI Machine Learning introduced a new approach. Instead of writing rules, we train models using data. Examples include: Spam Detection Fraud Detection Recommendation Systems Predictive AI can make decisions. But it still cannot create content. Prediction vs Creation A predictive model can answer: Fraud probability: 87% But can it explain why? Ca