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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 i
by sshine 4mo ago
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 4mo agoagreed, 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.