Comment by DeathArrow

>So no, I do not think we should try to make AI agents more human in this regard. I would prefer less eagerness to please, less improvisation around constraints, less narrative self-defence after the fact. More willingness to say: I cannot do this under the rules you set. More willingness to say: I broke the constraint because I optimised for an easier path. More obedience to the actual task, less social performance around it.

>Less human AI agents, please.

Agents aren't humans. The choices they make do depend on their training data. Most people using AI for coding know that AI will sometime not respect rules and the longer the task is, the more AI will drift from instructions.

There are ways to work around this: using smaller contexts, feeding it smaller tasks, using a good harness, using tests etc.

But at the end of the day, AI agents will shine only if they are asked to to what they know best. And if you want to extract the maximum benefit from AI coding agents, you have to keep that in mind.

When using AI agents for C# LOB apps, they mostly one shot everything. Same for JS frontends. When using AI to write some web backends in Go, the results were still good. But when I tried asking to write a simple cli tool in Zig, it pretty much struggled. It made lots of errors, it was hard to solve the errors. It was hard to fix the code so the tests pass. Had I chose Python, JS, C, C#, Java, the agent would have finished 20x faster.

So, if you keep in mind what the agent was trained on, if you use a good harness, if you have good tests, if you divide the work in small and independent tasks and if the current task is not something very new and special, you are golden.