Comment by crote
1 day ago
I think a big problem is that the most useful AI agents essentially go unnoticed.
The email labeling assistant is a great example of this. Most mail services can already do most of this, so the best-case scenario is using AI to translate your human speech into a suggestion for whatever format the service's rules engine uses. Very helpful, not flashy: you set it up once and forget about it.
Being able to automatically interpret the "Reschedule" email and suggest a diff for an event in your calendar is extremely useful, as it'd reduce it to a single click - but it won't be flashy. Ideally you wouldn't even notice there's a LLM behind it, there's just a "confirm reschedule button" which magically appears next to the email when appropriate.
Automatically archiving sales offers? That's a spam filter. A really good one, mind you, but hardly something to put on the frontpage of today's newsletters.
It can all provide quite a bit of value, but it's simply not sexy enough! You can't add a flashy wizard staff & sparkles icon to it and charge $20 / month for that. In practice you might be getting a car, but it's going to look like a horseless carriage to the average user. They want Magic Wizard Stuff, not invest hours into learning prompt programming.
> Most mail services can already do most of this
I'll believe this when I stop spending so much time deleting email I don't want to read.
And dumpster diving in my spam folder for actually important emails
Yeah but I'm looking forward to the point where this is not longer about trying to be flashy and sexy, but just quietly using a new technology for useful things that it's good at. I think things are headed that direction pretty quickly now though! Which is great.
Honestly? I think the AI bubble will need to burst first. Making the rescheduling of appointments and dozens of tasks like that slightly more convenient isn't a billion-dollar business.
I don't have a lot of doubt that it is technically doable, but it's not going to be economically viable when it has to pay back hundreds of billions of dollars of investments into training models and buying shiny hardware. The industry first needs to get rid of that burden, which means writing off the training costs and running inference on heavily-discounted supernumerary hardware.
Yeah this sounds right to me.