> The higher paid engineers i've worked with are always worth their salary/hourly rate because of the way they approach problems and the solutions they come up with.

I'm honestly just happy at the moment, because our two junior admins/platform engineers have made some really good points to me in preparation for their annual reviews.

One now completed his own bigger terraform project, with the great praise of "That looks super easy to maintain and use" from the other more experienced engineers. He figured: "It's weird, you actually end up thinking and poking at a problem for a week or two, and then it actually folds into a very small amount of code. And sure, Copilot helped a bit with some boilerplate, but that was only after figuring out how to structure and hold it".

The other is working on getting a grip on running the big temperamental beast called PostgreSQL. She was recently a bit frustrated. "How can it be so hard to configure a simple number! It's so easy to set it in ansible and roll it out, but to find the right value, you gotta search the entire universe from top to bottom and then the answer is <maybe>. AAaah I gotta yell at a team". She's on a good way to become a great DBA.

> Agents are great at building out features, i'm not so sure about complex software that grows over time. Unless you know the right questions to ask, the agent misses alot. 80/20 doesn't work for systems that need 100% reliability.

Or if it's very structured and testable. For example, we're seeing great value in rebuilding a Grafana instance from manually managed to scripted dashboards. After a bit of scaffolding, some style instructions and a few example systems, you can just chuck it a description and a few queries, it just goes to successful work and just needs a little tweaking afterwards.

Similar, we're now converting a few remnants of our old config management to the new one using AI agents. Setup a good test suite first, then throw old code and examples of how the new config management does it into the context and modern models do that well. At that point, just rebuilding the system once is better than year-long deprecation plans with undecided stakeholders as mobile as a pet ferret that doesn't want to.

It's really not the code holding the platform together, it's the team and the experiences and behaviors of people.