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Comment by throw2321 | Hacker News Reader

I've been thinking about this for a while now, wrt two points:

1. This will be the end of traditional SWEs and the rise of the age of debuggers, human debuggers who spend their days setting up breakpoints and figuring bugs in a sea of LLM generated code.

2. Hiring will switch from using Leetcode questions to "pull out your debugger and figure out what's wrong with this code".

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What makes you think the LLM couldn’t run a debugging session from the content of a JIRA ticket and the whole code base + documentation?

Having never seen it, or anything even close to it. (Of course, I'm a little biased by seeing product demos that don't even get "add another item to this list of command line arguments" right; maybe if everyone already believes it works, nobody bothers to actually sell that?)

If the codebase is anything more than a simple Python project... I don't think that'll happen.

It just doesn't scale that well. Hell, GPT-4 can't make sense of my own projects.

Who can say what's possible but there are very few "debugging transcripts" for neural nets to train on out there. So it'd have to sort of work out how to operate a debugger via functions, understand the codebase (perhaps large parts of it), intuit what's going wrong, be able to modify the codebase, etc. Lots of work to do there.

Nobody wants to face the potential that their skills are going to greatly decrease in value.

The first interview where I was handed some (intentionally) broken C code and gdb was about 15 years ago. I'm not sure that part is a change in developer workflow (this may apply more in systems and embedded though.)

I've been paying attention to this too (mostly by following Simon Willison) and I'm still solidly in the "get back to me when this stuff can successfully review a pull request or even interpret a traceback" camp...

Yep, time to start adding source_file.prompt sidecar files next to each generated module so debugging sessions can start at the same initial condition.

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