8 articles
Sunil Pai's “senior engineer death spiral” describes what happens when engineers start managing perception instead of reporting reality. The deeper problem may not be individual pride or fear, but organizations that make uncomfortable information too expensive.
A recent discussion on how AI was used effectively made me wonder what "effective" or "better" meant, because there's no way to test the alternative any more to compare. I still don't know how to characterize my own results, but I think it makes me better because it gives me a chance to work out who I am and what I mean to say, but not really how to say it.
Sean Goedecke argues that domain expertise is the real prompting skill. He's describing two quantities as one: a floor, available to anyone who can describe what acceptance looks like, and a gain that multiplies whatever you bring.
Andi Roberts wrote up Alex Pentland's research on why some teams outperform others. The research is good; the practical advice mostly assumes a watercooler you may not have. Some additions from the trenches: what Brooks actually said, two cheap levers for building the idea flow, and when you want the opposite.
Christian Rackerseder argues that the real axis for testing decisions isn't integration versus end-to-end, it's control: whether a team can make a dependency predictable enough for a given test and actually act when it fails.
This is a working example of using red/green testing to fix a bug - one that starts in the issue description and lives in the code. You can fix the issue, but the bug remains because it's part of an unexamined specification. Testing - and caring - are the fix.
Junior programmers mess up paradigms because they think they're more experienced than they actually are. They end up blaming the system for not working the way they think it should. I trusted the wrong thing, just like a junior programmer: I assumed my tests were wrong, my results were wrong, that I was wrong, and I was - but the error was in the location of the problem.
Yury Selivanov recently released lat.md, a knowledge graph for your codebase, stored as user-editable markdown. The tool itself sounds useful enough, but checking it out and working out what it provides for your code was more useful than the tool's existence itself: effective agent management means going through an onboarding process.