Comment by arrowleaf
1 day ago
My feeling has been that 'serious' software engineers aren't particularly suited to use these tools. Most don't have an interest in managing people or are attracted to the deterministic nature of computing. There's a whole psychology you have to learn when managing people, and a lot of those skills transfer to wrangling AI agents from my experience.
You can't be too prescriptive or verbose when interacting with them, you have to interact with them a bit to start understanding how they think and go from there to determine what information or context to provide. Same for understanding their programming styles, they will typically do what they're told but sometimes they go on a tangent.
You need to know how to communicate your expectations. Especially around testing and interaction with existing systems, performance standards, technology, the list goes on.
All our best performing devs/engineers are using the tools the most.
I think this is something a lot of people are telling themselves though, sure.
Best performing by what metric? There aren't meaningful ways to measure engineer "performance" that makes them comparable as far as I know.
Your org doesn't track engineering impact?
What about git stats?
I can tell you the guys that are consistently pushing code AND having the biggest impact are using LLM tools.
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