[sshine]

I use AI for Kubernetes. On a day-to-day basis, it runs 80%+ of my kubectl commands. It’s the most steroidal auto-complete I’ve tried. But I do get dumber for it.

What I do to compensate:

  - make it my duty to own every change, i.e. cognitively debt-free:
  - write summaries on every new thing I do (blog post, memo to colleague)
  - contribute documentation to the open-source projects I rely on
  - practice for CKA/CKAD certificates which require pre-LLM muscle memory
  - build interactive learning material for what I’m trying to learn
  - work with things that LLMs don’t yet trivially solve
  - repeat or reconstruct my recipes to perfect workflows, 

We’re incentivised to take the short path. I’m trying to create at least one path through a subject that I have to walk myself, preferably several times.

[PrimalPower]

agreed, ultimately claude is faster than an expert K8s in my org at finding things. kubectl has a lot of commands and things to cross-reference. AI Agents handle it like a champ.

That being said, Claude is dumb. I've seen it over-complicate diagnosing things - even though it's initial theory was correct.

I am convinced a good harness can solve this.

Outside of the k8s operating model, I don't see the point of becoming a wiz at the CLI. I learn by practice and I atrophy if i do not practice, there's no world where I will get enough practice to do it on my own anymore.

I compensate by trying to either move up or down the stack depending on the problem.