AI-Native Engineering Foundations

Course details

Explore the foundations of AI-native engineering and transform your workflows by integrating AI tools. Learn about the AI-native mindset, where you can distinguish between casual AI coding and disciplined engineering, and can choose the best approach for each situation. Discover AI-enhanced IDEs, command-line AI tools, and cloud agents to optimize your coding practices. Learn about the 70% problem and human-AI collaboration principles to improve your coding standards and productivity. Master the essentials of prompt and context engineering to provide the right information for optimal AI performance. Engage in interactive exercises that mirror real-world scenarios. Ideal for developers, tech leads, senior engineers, and anyone eager to harness AI's potential for more strategic and impactful coding, this course helps you build the skills to manage and iterate on AI-generated code confidently.

Learning objectives
Build a working solution using hands-on, quick-start exercises.
Explain the 70% problem and identify the three core workflow patterns used to address it.
Apply each workflow pattern through structured, interactive exercises.
Establish quality standards at the outset to support consistent, scalable outcomes.

Concepts

Introduction

Becoming an AI native engineer

The AI-Native Mindset

Vibe coding vs. agentic engineering
The 70 problem - Understanding AI's role
Human-AI collaboration principles

Tools and Modalities

Editors - AI-enhanced IDEs
Command-line AI tools
Choosing your modality
Cloud agents - Running AI in a sandbox

Your First AI Coding Session

Writing your first AI-generated code
The review-iterate workflow
When AI gets it wrong

Prompt Engineering Essentials

Crafting effective prompts
Common prompting patterns
From prompt to production

Context Engineering Fundamentals

Why context beats prompts
Feeding AI the right information

Conclusion

Building your personal AI workflow
Next steps and resources