This Week's Posts
(Including one from two weeks ago.)
2025-07-30
You know what would be a really thought-provoking team project for undergrad software engineering students? Building a dashboard that measures and reports programmers’ productivity and identifies process bottlenecks. Lots of coding, lots of requirements gathering, lots of UI design, and lots of “what the hell are we actually measuring and do we believe it’s meaningful?” which would be the most illuminating part of the whole exercise for them.
2025-08-09
My sister Sylvia died of pancreatic cancer in 2012 at the age of 47, leaving three teenage children behind. The mRNA cancer vaccine being developed in the US was the best hope we’ve ever had to prevent this. The Trump Administration’s decision to cut funding for this live-saving research based on pseudo-scientific hysteria condemns more people like my sister to death and more children to grow up without their mothers.
2025-08-11
There is a lot of ageism in tech. One reason, I think, is that 30-year-olds spouting recycled Y Combinator bullshit don’t like having the obvious flaws and contradictions in their statements pointed out by people who’ve lived through two or three previous hype cycles. Not hiring the elderly ensures that they’re always in a high-adulation environment, and never have to worry about whether staff will resist being guilted or bullied into sacrificing their personal lives for someone else’s gain.
2025-08-12
Andreas Zeller’s work is the most admirable example of software engineering research I know of. Over several decades he and his team have done deep theoretical work and translated it into usable tools, both to see if their ideas work in the real world and as a basis for dialog with developers about what problems to work on next. (Go ahead, check out The Fuzzing Book and The Debugging Book — you can thank me later.)
If I could go back 20 years and re-start my failed attempt to become a researcher myself, I would try to do the same thing, but would focus on developer productivity. More specifically, I would try to build deployable tools that programmers would actually use to find bottlenecks in real-world development processes, while simultaneously doing the theoretical work needed to figure out “what do we actually mean by ‘productivity’ and how do we tell if someone’s productive or not?”
There are lots of products in this space (Swarmia, Flow, etc.) but I haven’t seen something that is (a) open source, (b) straightforward to deploy, (c) actively being improved, and (d) backed up by the kind of research that Cat Hicks and the contributors to this book do. I think that if we had something like this today, a lot of the debate about whether AI makes programmers more productive would have a much higher signal-to-noise ratio.
2025-08-12
If you are using AI coding tools, please copy your prompt into the generated code as a comment (or have your agent do that):
- You wrote a precise requirement spec - why throw it away?
- It’ll help the next person understand the code.
- It’s good context for the AI when you revise the code, too.
- It will help researchers who want to study these tools’ accuracy and effectiveness.
- It’s a good way to label code as “AI-generated” or “AI-assisted”.
Thank you.