Learn the key components that make agents work, perception, reasoning, action selection, and execution loops. You’ll compare reactive, deliberative, and hybrid designs, and see how prompt templates and state management enable multi-turn interactions. By the end, you’ll know how different agent types function, when to use each, and how they provide value in real-world scenarios.

You'll build and test simple reactive agents that respond predictably using structured prompts and rule-based decision logic. You'll implement input parsing, apply deterministic behavior patterns through severity classification and action-mapping frameworks, and design clear output formatting strategies. Through validation frameworks, reasoning traces, and structured debugging, you'll evaluate how consistent your agent's behavior is across different scenarios. By the end, you'll know how to create reliable, production-ready reactive agents and understand why structured behavior is the foundation for more advanced systems with tools and memory.

You’ll extend agents with tools and memory so they can recall context and perform real tasks. You’ll implement tool-calling patterns, design short-term and long-term memory strategies, and test how agents handle conversation history. These capabilities transform basic models into production-ready agents that adapt to users, integrate with systems, and deliver consistent value over time.