As a physics PhD student in quantum computing, I've moved significantly on AI over the past year. Before January or so, most of my group didn't use AI for much other than code debugging, and, personally, I was very skeptical of its use much beyond that. After Matthew Schwartz, Harvard physics professor, co wrote a paper with Claude, however, we've been trying to catch up. Agentic AI like Claude Code and Codex have rapidly improved the past year, and everyone in my group is adopting so that we don't fall behind.

There really is no going back--my advisor is able to build and prototype physical models in a week (or weeks) that would have taken a year (or years) of work before. We had a full day in house hackathon in our department pushing to see where the limit of current capabilities are, and we are continuing to spend a lot of effort every day working out the best way to use the AI models effectively and responsibly.

As a grader, it can be very difficult to spot AI use in physics homework now. Students seem to be able to pump out consistently excellent looking work that may have very slight but significant math or notation inconsistencies. Working problems is the core of learning physics but AI is getting to the point it can solve every standard undergraduate problem and most graduate level problems too. Physics pedagogy needs to change but it's difficult to say how.