[pfp]

At least in my 2.5 person devops team, no.

Also I can't imagine how being handed a bunch of autogenerated terraform and ansible code would help me. Maybe 10% of my time is spent actually writing the code, the rest is running it (ansible is slow), troubleshooting incidents, discussing how to solve them & how to implement new stuff, etc.

If someone works in a devops position where AI is more of a threat, I'd like to hear more about it.

[kasey_junk]

I use Claude code with terraform all the time. It’s particularly good when your codebase is well modularized or at modularizing existing terraform.

It’s also quite good at getting to a solution by using validate/plan loops and figuring out syntax/state issues.

The biggest challenge is the lack of test sophistication in most terraform setups.

But llms generally are _amazing_ for my ops work. Feeding a codebase into one and then logs I’ve seen Claude code identify exact production issues with no other prompting. I use llms to help write incident reports, translate queries in the various time series db we use, etc.

I’d encourage you to try an llm for your tasks, for me for ops it’s been a huge boon.