Building AI Agents in Python from Scratch

AI agents are transforming how we interact with technology, moving beyond simple chat interfaces to autonomous, multi-step problem-solving. If you want to understand how these intelligent systems actually work under the hood, building one from scratch is the most effective approach. This course strips away the magic of heavy, complex frameworks, guiding you to build functional, autonomous AI agents using plain Python. You will learn the underlying architecture of agentic systems, from memory management to tool execution, empowering you to design custom AI solutions tailored to your specific needs. What you'll learn: • Understand the fundamental terminology, concepts, and architecture of autonomous AI agents. • Build core agent loops and decision-making processes using standard Python. • Implement modern tool calling capabilities so your agents can interact with external APIs and services. • Design basic memory systems and retrieval-augmented generation (RAG) patterns for context awareness. • Apply modern Python practices, including type hints and async functions, to structure your agent code effectively. • Practice foundational prompt engineering techniques to guide agent behavior reliably. You will start by exploring the foundational definitions and concepts of agentic AI before moving into practical implementation. The text-based lessons will walk you step-by-step through writing the logic, managing state, and expanding your agent's capabilities through written coding exercises. This course is designed specifically for beginners with basic Python knowledge who want to understand AI agents without any prior machine learning experience. Start reading today to unlock the mechanics of autonomous AI and build your first intelligent agent from scratch.