Less human AI agents, please

I ask my coding agent to do some tedious, extremely well-specified refactor, such as (to give a concrete real life example) changing a commonly used fn to take a locale parameter, because it will soon need to be locale-aware. I am very clear — we are not actually changing any behavior, just the fn signature. In fact, at all call sites, I want it to specify a default locale, because we haven't actually localized anything yet!

Said agent, I know, will spend many minutes (and tokens) finding all the call sites, and then I will still have to either confirm each update or yolo and trust the compiler and tests and the agents ability to deal with their failures. I am ok with this, because while I could do this just fine with vim and my lsp, the LLM agent can do it in about the same amount of time, maybe even a little less, and it's a very straightforward change that's tedious for me, and I'd rather think about or do anything else and just check in occasionally to approve a change.

But my f'ing agent is all like, "I found 67 call sites. This is a pretty substantial change. Maybe we should just commit the signature change with a TODO to update all the call sites, what do you think?"

And in that moment I guess I know why some people say having an LLM is like having a junior engineer who never learns anything.

I believe how "neurotypical" (for the lack of a better word) you want model to be is a design choice. (But I also believe model traits such as sycophancy, some hallucinations or moral transgressions can be a side effect of training to be subservient. With humans it is similar, they tend to do these things when they are forced to perform.)

"Ignoring" instructions is not human thing. It's a bad LLM thing. Or just LLM thing.

"ChatGPT wrapper" is no longer a pejorative reference in my lexicon. How you expose the model to your specific problem space is everything. The code should look trivial because it is. That's what makes it so goddamn compelling.

They drift to their training data. If thousand of humans solved a thing in a particular way, it's natural that AI does it too, because that is what it knows.

More of that please. Perhaps on a check box, "[x] Less bullsh*t".

>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.

In fairness to coding agents, most of coding is not exactly specified like this, and the right answer is very frequently to find the easiest path that the person asking might not have thought about; sometimes even in direct contradiction of specific points listed. Human requirements are usually much more fuzzy. It's unusual that the person asking would have such a clear/definite requirement that they've thought about very clearly.