Comment by naasking
6 days ago
> Most of what we write is not highly creative, but it is load-bearing, and it's full of choices.
The idea that you can't specify the load bearing pillars of your structure to the AI, or that it couldn't figure them out by specifying the right requirements/constraints, will not age well.
> The idea that you can't specify the load bearing pillars of your structure to the AI
But English is a subjective and fuzzy language, and the AI typically can't intuit the more subtle points of what you need. In my experience a model's output always needs further prompting. If only there were a formal, rigorous language to express business logic in! Some sort of "programming language."
> But English is a subjective and fuzzy language, and the AI typically can't intuit the more subtle points of what you need.
I disagree on the "can't". LLMs seem no better or worse than humans at making assumptions when given a description of needs, which shouldn't be surprising since they infer such things from examples of humans doing the same thing. In principle, there's nothing preventing a targeted programming system from asking clarifying questions.
> In my experience a model's output always needs further prompting.
Yes, and the early days of all tooling were crude. Don't underestimate the march of progress.
What have you written with ai that ha made you or your business money
> What have you written with ai that ha made you or your business money
I use R a little more than I should, given the simplicity of my work. Claude writes better R quicker than I can. I double check what it's doing. But it's easier to double check it used twang correctly than spend five trying to remember how to use the weird package that does propensity scoring [1].
I'm sure data analysis will still sort of be a thing. But it's just not as useful anymore in the form of a human being for most commercial applications at sub-enterprise scale.
[1] https://cran.r-project.org/web/packages/twang/index.html