AI for Software Engineering

Author

Neil Ernst

Published

February 5, 2026

How to use AI to do software engineering (mid 2025 version!)

Learning Outcomes

  • be able to explain components of the AI4SE lifecycle:
    • prompting
    • context and RAG
    • tool use with MCP
    • evals
    • models and pitfalls
  • use a modern LLM for software development
  • contextualize the places AI can assist in, replace, and/or hinder good SE practices and good SE systems.

Topics and slides

These are the submodules I covered in class.

Readings (before class)

  1. Simon Willison: How I use LLMs
  2. Simon Willison: The Last 6 Months in LLMs
  3. Fowler: Exploring GenAI series;
  4. Gene Kim/Steve Yegge pairing with Claude Code (watch)

In the previous class we installed a common set of AI tools. Make sure that this works for you on a machine you can bring to class.

Exercises

These are done in class. The source code below is a combo of what I typed and what I prepped before hand.

  1. Vibe Coding example - no code worth sharing
  2. Using Gemini to do “data science” (file is AI generated)
  3. Promptfoo and promptfoo config file

Optional Readings and Activities (so many … send more!)