Software Engineering in the Age of AI
A practical guide for using AI in real software work, without hype and without panic.
Why this site exists
Most software teams already use AI every day, but many still don't know the difference between a model and a product, don't understand tool categories, and don't have a clear map of how it all fits together.
This site exists to organize that mess. No vendor worship, no jargon theater. Just the map that matters.
Sessions
Six sessions covering what you actually need to know. Each one works on its own, but together they give you the full map.
What is an AI-Native Engineer?
The starting point. What changes when AI becomes part of the workflow, not just an extra tool on the side.
The words people keep using
Prompt, token, context, agent. A glossary that keeps the vocabulary useful without turning it into jargon soup.
Tools: IDEs vs CLI
Cursor, Windsurf, GitHub Copilot, Claude Code. What each tool does, where it shines, and where it trips.
LLMs and the models people actually use
GPT, Claude, Gemini, Llama. How they work at a useful level, what makes them different, and how to choose.
How AI development matured
From copying ChatGPT answers to orchestrating agents. The 5 maturity phases and where your workflow fits.
How to operate AI-native in practice
Real workflows, project examples, and what changes day to day when you operate AI-native.
Hands-on Project
Done with theory? Build a project from scratch with your code agent and publish it to GitHub Pages. A practical guide that teaches the real agentic workflow.
Go to the hands-on projectHow AI matured in software development
Using AI isn't the point. Maturing how you use it is the point.
How to study
Each session stands alone. If you want a path, here are a few good ones.