Prompt Repair and Iteration for AI-Assisted Coding

When using generative AI to write code, your initial prompt rarely produces perfect results on the first try. The secret to building working software with AI lies in your ability to systematically diagnose, repair, and iterate on prompts when things go wrong. This text-based course teaches you how to guide AI models effectively, turning broken code and vague outputs into precise, functional software through structured prompting techniques. What you'll learn: - Understand the fundamentals of AI code generation and why initial prompts fail - Diagnose common errors like hallucinated libraries, logic loops, and context drift - Apply systematic prompt repair techniques to narrow scope and enforce strict constraints - Structure your instructions using modern patterns, system prompts, and explicit output formats - Manage the model's context window to prevent performance degradation during long sessions - Iterate on code outputs incrementally to refine features without breaking existing logic You will start with core definitions and the foundational mechanics of how language models process instructions. From there, you will explore written walkthroughs of real-world troubleshooting scenarios, learning how to rewrite prompts to fix buggy outputs. This course is designed for absolute beginners, hobbyists, and creators who want to build applications using AI assistance. No prior programming experience is required. Start reading today to master the art of prompt iteration and bring your software ideas to life.