There isn't a sports figure who shaped my fandom at a very formative age more than Bob Huggins. And there are no teams I've ever been as emotionally invested in as the Bearcats teams he coached. Prayers and best wishes to Bob and his family.

I just declared a moratorium against AI-written change descriptions (e.g. PR and commit messages, also issues/tickets) from my team. AI was writing change descriptions that were worse than useless to me as I tried to review PRs: outlining details of the code that could easily be seen by looking at the code, but omitting the higher-level framing needed to understand broadly what the code is doing. I think people like having AI write these things because the output looks structured and thorough, which makes it feel professional in a way. But this isn't actually valuable. Concise, high-level descriptions are better for everyone. If I need to use my own AI to interpret what your AI wrote then something is wrong. Let AI write code, sure, but for the description, I'd rather see your prompt than your output. We could maybe have extended agents.md with guidelines on writing descriptions, but this seemed a bit pointless since a good, concise change description only takes a few minutes to write -- not a significant time savings to delegate to AI. At least, it doesn't take long if you understand the code -- and if you don't understand the code, then I'm definitely not merging it.

If I open your codebase, I can usually tell within a few minutes whether you’re still thinking like a beginner or you’re starting to think like an engineer. Here are common coding habits that make code harder to scale and the better alternatives.

I think millennials are the real AI sweet spot. Digital natives with just enough experience to prompt well and sanity-check the output. Gen Z is too inexperienced and trusts AI like it’s gospel. Gen X is trying to make it to retirement without learning another interface. Boomers are still googling how to convert a pdf.