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I feel like there is a huge subset of people who just do trial and error programming. The other day, I watched a whole team of 8 people spend a whole work day swapping out random components on Zoom to diagnose a problem because not a single person considered attaching a debugger to see the exact error in 5 minutes.

I feel like you have to tell people to not roll your own whatever because there are so many of these types of people.






I was so surprised the first time I saw this. I mostly work alone and my workflow is usually study an example (docs or project), collect information (books and article), and iteratively build a prototype while learning the domain. Then I saw a colleague literally copying and pasting stuff, hoping that the errors go away in his project. After he asked for my help, I tell him to describe how he planned to solve the problem and he couldn't. For him, it was just endless tweaking until he got something working. And he could have understood the (smallish) problem space by watching one or two videos on YouTube.

Those same people are utterly incapable of reading logs. I’ve had devs send me error messages that say precisely what the problem is, and yet they’re asking me what to do.

The form of this that bothers me the most is in infra (the space I work in). K8s is challenging when things go sideways, because it’s a lot of abstractions. It’s far more difficult when you don’t understand how the components underpinning it work, or even basic Linux administration. So there are now a ton of bullshit AI products that are just shipping return codes and error logs out to OpenAI, and sending it back rephrased, with emoji. I know this is gatekeeping, and I do not care: if you can’t run a K8s cluster without an AI tool, you are not qualified to run a K8s cluster. I’m not saying don’t try it; quite the opposite: try it on your own, without AI help, and learn by reading docs and making mistakes (ideally not in prod).




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