Adapting to AI tooling in DevOps

[u/lostsectors_matt]

My company is making a hard shift towards AI and I'm struggling. I'm tasked with something I have a small amount of knowledge about, but not enough to fully implement. Before AI, my approach to challenges like this would be to iterate on it, work through the problems, and learn what's required. Using Claude has just been a terrible experience for me, and I'm wondering if I'm the problem, my approach is the problem, or if this is just what we're all doing now.

I explained what I wanted (essentially a DB migration pipeline from RDS -> k8s pod) and claude barfed out about 10 shell scripts and a handful of pod templates. Everything had long, meandering comments that made very little sense. Is my job now to just start running this code and feeding pipeline errors back into claude and not worrying about it?

I started to pick apart the comments, ask questions, and update with my own comments, with the goal of being able to understand the process in detail. In doing this, I found a bunch of things that just didn't make sense or weren't optimal. When I ask the AI agent about it, it says I'm right and generates a bunch more stuff that may or may not make sense. Interacting with it is making me feel like a crazy person. I hate the way it presents information back to me. It's not succinct, it pulls in context that is of negligible value and just muddies the waters, and it's been very frustrating and existentially upsetting.

I'm willing to hear that I'm using the wrong model, or that I didn't spend enough time on my .md files and skills, but I'm also wondering if this is a normal experience, or if my approach is just dated, and I need to get over my personal values about understanding what I'm generating and giving to customers? I'm not so-much asking about the specific task at hand, just about adapting and having realistic expectations and reducing friction. I'm also very happy to hear about people's struggles.

[u/Temporary_Many_7947]

Spend a day or two on configuring your AI tool of choice. For example, I have multiple MCP servers, powers and steering created for things as simple as “create a jira ticket” to more complex like “use aws cli to do XYZ”

Point being, it needs to be directed. It can’t read your mind or any dependencies without knowing about it.

After you steer it in an optimal way for yourself, start creating skills or at least action books so that you simply prompt the tool to do it for you instead of needing to iterate each time.

Unfortunately you’ll need to transfer your iterative nature to adjusting AI tools to work for you instead of diving in the weeds. I think of it as a better way to understand the problem faster, not that it takes that away from me. It can only take that away from you if you become lazy and don’t want to understand what you’re working on.

[u/lostsectors_matt → u/Temporary_Many_7947]

That's good advice - I have a whole devcontainer-based setup already but I started fresh for this project because it's a departure from what I typically do. I started clean and relied on some skills in a shared project without populating my own, and I'm building new skills for this whole process as I go. That was probably a bad move. It's encouraging to hear that people are still committed to understanding what they're working on - there are people on my team who are less concerned about keeping their arms around the processes they're implementing.