My experience with using AI for coding is that if you are not asking it
questions from an algorithms class or similar, you get a lot of
hallucinations that do not work, e.g. R packages that don't exist. You can
ask it follow up questions and it will eventually fix the issues, but that
requires having a firm mental model and the ability to read code and know
how it would work in practice.

I can see the utility of a Prompt Engineering Carpentries lesson, but I
have no idea how to properly teach prompt engineering.

--
Reed A. Cartwright, PhD
Associate Professor of Genomics, Evolution, and Bioinformatics
School of Life Sciences and The Biodesign Institute
Arizona State University
Address: The Biodesign Institute, PO Box 876401, Tempe, AZ 85287-6401 USA
Packages: The Biodesign Institute, 1001 S. McAllister Ave, Tempe, AZ
85287-6401 USA
Office: Biodesign B-220C, 1-480-965-9949
Website: http://cartwrig.ht/


On Tue, Mar 18, 2025 at 5:04 PM Paul Harrison via discuss <
[email protected]> wrote:

>
> I wonder if more could be said about *how* to demonstrate the use of
> LLMs. All the bad things people do with LLMs (and Stack Overflow) are
> opportunities to demonstrate a better way.
>
> So we could show getting some code from an LLM, and then the steps of
> examining variables and understanding their types, inserting debugging
> "print" statements, looking up documentation, considering alternative
> solutions, and explaining our thought process.
>
> It's not so different from the skills needed to read other people's code.
>
> Since LLM output is random it's hard to script this fully, but that also
> seems in keeping with the Carpentries workshop format.
>
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