Agentic Software Development with OpenAI: Building Coding Agents

As software development evolves, the ability to build and deploy autonomous coding agents is becoming an essential skill for modern developers. Transitioning from simple code completion to fully agentic workflows allows you to automate complex programming tasks, code reviews, and debugging processes. In this course, you will learn how to design, build, and manage agentic software systems using OpenAI APIs. You will start with the foundational concepts of LLM-based agents, progress to implementing function calling and state management, and ultimately construct a self-correcting coding assistant that can write, test, and refine its own code. What you'll learn: - Understand the core principles of agentic workflows, planning, and tool use in software development. - Configure OpenAI APIs and function calling to allow agents to interact with file systems and runtimes. - Build autonomous coding assistants that can write, execute, and debug Python code. - Implement self-correction loops using automated testing frameworks like pytest to verify agent outputs. - Manage state and memory in multi-turn agentic conversations for complex programming tasks. - Apply modern Python practices, including async/await and type hints, to ensure robust agent execution. You will begin by mastering key agentic concepts and API foundations before moving on to hands-on written exercises where you will construct and refine your own autonomous development tools. This text-based course is designed for software developers, technical automation enthusiasts, and programming beginners who want to explore the future of AI-driven development, with no prior experience with agentic systems required. Start reading today to unlock the potential of agentic software development and build your first autonomous coding assistant.