Craft software that makes people feel something

Kinda tangential but in the advent of AI I feel like there won’t be a niche for “handcrafted software”.

When quartz watches came up the makers of mechanical watches struggled. Quartz watches are cheaper, more accurate in many cases and servicing is usually restricted to replacing a battery. However some people appreciate a good mechanical watch (and the status symbol aspect of course) and nowadays the mechanical watch market is flourishing. Something similar happened with artificial fabrics (polyester, acrylic) and cheap made clothes, there’s a market for handmade clothes that use natural fabrics.

Nobody (well, barring a few HN readers) will ever care if the software was written by people or a bot, as long as it works.

So the proof for your claim is two counterexamples?

Or maybe it's like someone saying homecooked meals and professional chefs are outdated because McDonalds exists. Homecooked meals are cheaper and healthier, and professional chefs still make better food. I don't think McDonalds is about to disappear, but I'm pretty sure those other categories aren't about to become obsolete any time soon.

I disagree. It enables more people to build utility software without the pain of writing the boilerplate code for it. This should leave more room for their taste and expertise.

That's how it works for me. I'm currently turning a lot of raw data into a map of Berlin rents. I spend less time figuring out the map API, and more time polishing the interesting parts.

I don't care if a craftsman used hand tools or a CNC to build beautiful furniture. I pay for taste, not toil.

I believe OP’s intent was that for software, normal users don’t see or understand what’s under the hood so how the software is built doesn’t matter.

I think you're agreeing, not disagreeing. I also misread the comment originally.

Emphasis mine:

> there won’t be a niche

This is a bad analogy.

> more accurate in many cases

It's laughable that LLMs can be considered more accurate than human operators at the macro level. Sure, if I ask a search bot the date Notre Dame was built, it'll get it right more often than me, but if I ask it to write even a simple heap memory allocator, it's going to vomit all over itself.

> Nobody [...] will ever care if the software was written by people or a bot, as long as it works

Yeah.. wake me up when LLMs can produce even nominally complex pieces software that are on-par with human quality. For anything outside of basic web apps, we're a long way off.

Watches are a horrible example. The rich buy them because they're a status symbol. Rich people aren't going to start retaining teams of software experts just for status.

"Mechanical watches" also aren't exploding at all. When people cite this, they're citing the overall watch market growing, because the market for million dollar watches is being driven by a very small group of collectors. Its also not sustainable, and will die down in ~10-20 years when these old guys finish dying. The average not rich person could not give less of a damn about mechanical watches. There's no great comeback on the horizon

Exactly. I thought my last paragraph made it clear that software is not like the other couple of things.

> Nobody (well, barring a few HN readers) will ever care if the software was written by people or a bot, as long as it works.

That is probably true. But all evidence to date is that if the software is written by a bot, it won't work. That is why people will care.

> if I ask a search bot the date Notre Dame was built, it'll get it right more often than me

With both of you doing research in your own ways, you'll get it right more often (I hope).

I meant without looking it up

The bot always looks it up, in a way.

I mean, so do I, if you think about it like that. I just have a much lower chance of successfully retrieving the correct information.

In the comparison I was making with respect to accuracy was that the bot is much more likely to accurately answer fact-based queries, and much less likely to succeed at any tasks that require actual 'thinking'. Especially when that task is not particularly common in the training set, such as writing a memory allocator. I can write and debug a simple allocator in half an hour, no worries. I'd be surprised if any of the current LLMs could.

I agree. I was just making a tangential point with a bit of exaggeration; sorry if it seemed to distract from your main point.

If you look up the factual question in a quality source, you'll be more accurate than the bot which looked at many sources. That's all I meant.