[mediaman]

This was solved a hundred years ago.

It's the same problem factories have: they produce a lot of parts, and it's very expensive to put a full operator or more on a machine to do 100% part inspection. And the machines aren't perfect, so we can't just trust that they work.

So starting in the 1920s Walter Shewhart and Edward Deming came up with Statistical Process Control. We accept the quality of the product produced based on the variance we see of samples, and how they measure against upper and lower control limits.

Based on that, we can estimate a "good parts rate" (which later got used in ideas like Six Sigma to describe the probability of bad parts being passed).

The software industry was built on determinism, but now software engineers will need to learn the statistical methods created by engineers who have forever lived in the stochastic world of making physical products.

[thawawaycold]

I hope you're being sarcastic. SPC is necessary because mechanical parts have physical tolerances and manufacturing processes are affected by unavoidable statistical variations; it is beyond idiotic to be provided with a machine that can execute deterministic, repeatable processes and then throw that all into the gutter for mere convenience, justifying that simply because "the time is ripe for SWE to learn statistics"

[int_19h]

We don't know how to implement a "deterministic, repeatable process" that can look at a bug in a repo and implement a fix end-to-end.

[thawawaycold]

that is not what OP was talking about though.

[rorytbyrne]

LLMs are literally stochastic, so the point is the same no matter what the example application is.

[warkdarrior]

Humans are literally stochastic, so the point is the same no matter what the example application is.

[perching_aix]

The deterministic, repeatable process of human (and now machine) judgement and semantic processing?