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Comment by mattlutze | Hacker News Reader

Most software devs would prefer a debugger, but most non-software devs would probably prefer a virtual developer.

If a technical product manager was able to generate the code needed for a feature using some combination of LLMs and CoPilots—even for proof of concepts, for example—the business would need to hire fewer developers and saves significant operating costs.

Extending it to your everyday person. Aunt Jane bought a new washing machine and wants to add it into her smart house. Either she's gotta call the niece to hook it all up, write the integration to Home Assistant, write automations for her iOS devices, etc, or, she asks her favorite LLM / Co-Pilot for help and it step-by-step walks her through it directly, with code, with individual troubleshooting.

There's business in both use cases, but the total addressable market is quite a bit bigger for one of them.

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Aunt Jane likely didn't even want or might not even have a smart house in the first place. That's perhaps the thing you're missing here - your average person doesn't give a shit if it's "smart", they just want things to work and the only difference for them between "it's smart" and "it's dumb" is if the remote they're fiddling with is their phone, an on-device button or a regular remote (as well as how likely it is that they get spied on externally).

Your average person's ideal amount of exposure to code is zero (as in, most would prefer to not even think about code). If the device isn't automated from the getgo in an easy way, then Aunt Jane has no smart device and no matter how easy it is to write the connection, she's not going to have it unless her niece shows up.

You're severely overestimating the desire for an everyday person to automate their home. Most people are perfectly fine manually flicking light switches and unless you live on a very specific schedule, often automation ends up falling short of practical reality, so even the majority of people who "automate" just end up moving the light switch to their phone.

I think there are more roles out there that can benefit than people realize.

I know a cartographer who makes maps in some specialized software and then also has to occasionally interact with some official federally managed database. This person is not a software engineer and the database interaction has been historically painful in the office. This year ChatGPT just helped whip up some Python scripts.

Two hypotheses: 1) the “in house tooling” market is huge and will make great use of this tech; 2) that will contribute to pushing the floor lower and lower where more and more roles and people will take advantage of it.

How about the washing machine just plugs itself seamlessly into her smart house, without Aunt Jane having to do anything than a quick identity check on her phone? Probably needs to be an Apple washing machine, though.

You mean some kind of interoperability standard?? We'll invent AGI before that becomes a reality!

...with expensive quickly deteriorating cable

Those are sold extra. Also it only has an Apple Socket™ by default, so you'll need a dongle to have it fit common outlets.

>it step-by-step walks her through it directly, with code

This is exactly where it completely breaks down. The AI might as well show her some hieroglyphics.

I think the idea of replacing devs with LLMs is missing the point of what a developer does.

Yes, today, developers are people who know programming languages, that's something non-developers don't know, so teach an AI do code and you can spare a developer, right?

But no, what developers really do is tell the computer precisely what it should do, a programming language simply the best way we have found to do it. Using GUIs, natural languages, etc... may fell less obscure to the layman, but the problem doesn't go away, in fact, it is often made worse because of the fuzziness of natural languages. There is a reason developer have been using programming languages for so long despite countless attempts to find alternatives, they simply haven't been matched for the task of telling a computer what to do precisely. And if something better is found, then developers will use that, and besides some syntactic technicalities, the job will be essentially the same.

So you postulate that the installation of every home appliance will have instructions for how to do so with 100% accuracy in Chatgpt? I don't know about you, but having read many installation instructions... I wouldn't trust most humans to get them right, and definitely not an LLM. Half of them refer to screws that don't exist...

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