Software engineering for the AI era by Max Piechota

Carrying engineering excellence forward into the AI era.

Look around and everyone's chasing the same things: better models, more skills, sharper rules, LLM-as-a-judge. Almost overnight the industry forgot about plain solid software fundamentals — maybe because it's easier to hope the models will handle the hard parts for us than to put in the work of actually learning them. AI writes most of the code now, and the things that made software durable are quietly eroding: deliberate architecture, real tests, delivery discipline, and the judgment that tells good from merely plausible.

This is the place that goes the other way. We don't take shortcuts — we study software engineering hard and work out how it actually applies in the AI era. That makes this both an academy, where those disciplines get taught, and a lab, where we experiment and find out what holds and what doesn't.

This isn't theory for me. I work on exactly this every day in my professional practice, and these sessions are where I bring that work into the open and teach what I'm learning as I go.

For engineers, tech leads, and architects who intend to still recognize their craft on the other side of this shift.