AI Assisted Development

by Bo Min

About this course

I remember my first "AI-assisted" project. I pasted code into ChatGPT, got something back, copied it... and it didn't work. I didn't know why it failed. I didn't know how to fix it. I didn't even know what questions to ask. Sound familiar? The problem wasn't the AI. It was my understanding of how LLMs think and how to communicate with them**. This course is everything I wish existed when I started: ✅ Part 1: Mental Models How do LLMs actually process information? Why do they fail? When can you trust them? Understanding token-based processing, attention mechanisms, context windows, and probabilistic behavior - not as abstract theory, but as practical knowledge that makes you a better AI-assisted developer. ✅ Part 2: Prompt Engineering Beyond "write better prompts" - systematic frameworks: zero-shot vs few-shot, chain-of-thought reasoning, role-based prompting, constraint specification. Build a reusable template library. Turn vague ideas into precise instructions. ✅ Part 3: Development Workflow The real work: decomposition, iteration, verification. How to break complex problems into AI-friendly chunks. How to give effective feedback. How to verify outputs. How to integrate AI into your actual development process. ✅ Part 4: Production Systems Architecture decisions, testing strategies, deployment workflows, performance optimization, security considerations. AI helps you build - you ensure it's production-ready. ✅ Part 5: Real Projects Theory means nothing without practice. Build actual applications from scratch: requirements analysis → architecture → implementation → testing → deployment. Each project demonstrates patterns you'll use repeatedly. ✅ This course is for you if: - You've tried AI coding tools but results feel inconsistent - You want systematic understanding, not just tips and tricks - You're building production software, not just prototypes - You value depth over hype ✅ What makes this different: Not a collection of ChatGPT tricks. A complete framework for thinking about and working with AI in software development. Technical depth without academic overhead. Practical immediately, valuable long-term. After this course: You'll understand not just *how* to use AI tools, but *when*, *why*, and *what to watch out for*. You'll build faster without sacrificing quality. You'll have mental models that work across any AI tool or model. Whether you're a non-developer exploring automation or a senior engineer integrating AI into your workflow - if you're building software in 2025, this is how you do it. 20+ hours. Hands-on. Production-focused. Let's build.

Course Content(1 lessons)