It's easy to buy one plane ticket when a person has a specific plan -- to attend a meeting or a conference, or to match up with an airbnb timeslot or something.

It's harder to buy one plane ticket for the lowest cost amongst all the different ways that plane tickets can be bought, and harder yet to do so with a lack of specificity.

So, for instance: Maybe I don't have a firm plan. Maybe I'm very flexible.

Maybe all I want to do is say "Hey, bot. I want to go visit my friend in Florida sometime in the next couple of weeks and spend a few days there as inexpensively as I can. He's in Orlando. I can fly out of Detroit or Cleveland; all the same to me. If I drive to the airport myself, I'll need a place to keep my car at or near the airport. I also want to explore renting a car in Orlando. I pack light; personal bag only. Cattle class is OK, but I prefer a window seat. Present to me a list of the cheapest options, with itinerary."

That's all stuff that a human can sort out, but it takes time to manually fudge around dates and locations and deal with different systems and tabulate the results. And there's nuances that need covered, like parking at DTW is weird: It's all off-site, and it can be cheaper and better to rent a room for one night in a nearby hotel that includes long-term parking than to pay for parking by itself.

So the hypothetical bot does a bunch of API hits, applies its general knowledge of how things flow, and comes back with a list of verified-good options for me to review. And then I get to pick around that list, and ask questions, and mold it to best fit my ideal vision of an inexpensive trip to go spend time with a friend.

In English, and without ever dealing with any travel websites myself.

"Right. So I go to Detroit on Tuesday and check in at the hotel any time after noon, and take the free shuttle to the airport the next morning at around 0400 to the Evans terminal. Also, thanks for pointing out that this airport is like a ghost town until 0600 and I might want to bring a snack. Anyway, I get on the flight, land at Orlando, and they'll have a cheap car waiting for me at Avis. This will all cost me a total of $343, which sounds great. If that's all I need to know right now, then make it so. Pay for it and put it on my calendar."

(And yeah, this is a problem that I actually have from time to time. I'd love to have a bot that could just sort this stuff out with a few paragraphs.)

I think it's a fallacy that if you make creating anything easier, more useful things will be created. In reality, you just end up with more useless things being created. Like with art, when it gets easier to create you don't end up with more good art. And with software - it's not like the quality of software has gone up as it's gotten easier to build, it's gotten much worse.

A related fallacy is that great things are easier to build when you can rapidly create stuff. That isn't really how great ideas are generated, it's not a slot machine where if you pull the lever 1000 times you generate a good idea and thus a successful piece of software can be made. This seems like a distinctly Silicon Valley, SFBA type mentality. Steve Jobs didn't invent the iPhone by creating 1000 different throwaway products to test the market. Etc etc.

I'm sympathetic to this view too, but I don't think the solution is to have LLM's generate bespoke code to do it. We absolutely should be using them for more natural language interfaces tho.

It won't help, though. The scalpers have much more motivation write a better bot ("agent") than I, an occasional concertgoer, do.

So we burn the planet up to deploy individually craft UIs on demand? I mean, I've read your comment three times, and I just don't see it. If we end up in that future, we're doomed.

> And typically the ui/ux is not the core value of companies

Huh? The user experience is basically ALL of the core product of a company.

If it's so easy for an AI to create ticket purchasing software that people can generate it themselves, then it's also true that the company can also use AI to generate that software for users who then don't need to generate it themselves. Obviously I think neither of these things are true or likely to happen.

Well ticketmaster (for example) is used by millions of people. It seems to me like spinning up millions of LLMs to produce a million different apps is way more wasteful than having a dozen developers produce one efficient app that everyone can use?

Why would it be? If you can describe an approximation of a system and regenerate it to be, let’s say, 98% accurate in 1% of the time that it would take to generate it by hand (and that’s being generous, it’s probably more like 0.1% in today’s day and age and that decimal is only moving left) aren’t there a giant set of use cases where the approximation of the system is totally fine? People will always bring up “but what about planes and cars and medicine and critical life or death systems”. Yeah sure, but a vast majority of the systems an end user interacts with every day do not have that level of risk tolerance

The word “many” is carrying a lot of weight here. Given the probabilistic nature of AI I suspect that systems that are 98% correct will be just fine for all but the “this plane will crash” or “this person will get cancer” use cases. If the recreation of the system failed in that 2% by slightly annoying some end user, who gives a shit? If the stakes are low, and indeed they are for a large majority of software use cases, probabilistic approximation of everyone’s open source will do just fine.

If you’re worried about them achieving the 98%, worry no more, due to the probabilistic nature it will eventually converge on 9’s. Just keep sending the system through the probabilistic machine until it reaches your desired level of nines