Agentic Coding Foundations with GPT and AI Assistants

Software development is evolving rapidly as AI transitions from simple autocomplete tools to autonomous coding agents. Understanding how to collaborate with these intelligent systems is becoming a critical skill for modern developers. In this text-based course, you will learn the fundamentals of agentic coding, exploring how modern GPT-style models plan, write, test, and refine code with minimal manual intervention. What you'll learn: - Understand the core concepts of agentic workflows, autonomous reasoning, and the shift from simple prompting to multi-agent coding. - Design effective system prompts and constraints to guide AI agents through complex programming tasks. - Implement test-driven development cycles where AI agents write code and self-correct based on test feedback. - Manage AI context windows and token usage efficiently during software development projects. - Establish human-in-the-loop oversight to review, validate, and secure AI-generated code. - Practice debugging and refactoring existing codebases using agentic AI strategies. You will start by learning key terminology, basic LLM capabilities, and foundational concepts of autonomous agents. From there, you will progress through written explanations and practical code-based scenarios that illustrate how to design, monitor, and guide these workflows. This course is designed for beginners looking to integrate AI agents into their development process, with no prior AI engineering experience required. Start reading today to master the future of AI-driven software engineering.