alt Hacker NewsA good alternative for your example is to make it create a stateful artefact (Claude) / whatever OpenAI calls ChatGPT.
And there, it has a database of sorts, running god knows where on god knows what, and you have a single-user web app that you may or may not ever open and see (since your favorite AI agent can just read and update it for you anyway).
Today it’s still something the user has to suggest / request.
Tomorrow? If they put a bit of effort these models will reach for building these one-off ephemeral or long-lived hyper-custom apps the same way they now reach for a python sandbox for basic arithmetics and statistics.
Looking for a flat? Scheduled task + CRM like artefact for it to monitor, maintain, and update.
Looking for holidays? Your own personal shareable moodboard with destinations and what not.
Have a use case or task for which chat or editing text docs is a frustrating way of correcting or giving feedback? Have it build a dedicated, custom artefact just for that.
When you encounter a use case where LLMs limits show, make them build tools.
Your last line is actually very insightful. I was just looking at LLM from the chat app perspective.
I wonder how open these services will be to data storage if they do become a "universal app". If I used LLM to make an app for tracking training for endurance running, and I slapped an 800kb .fit file in there each day, the storage for all of these files would probably be fine, but without condensing each run down to a textual summary like Garmin/Strava currently does ("You ran 10km in 35:00, at a pace of 3:30/km. This improved your speed/{vague motivational LLM quote}"), wouldn't the context become enormous after a pretty short duration, causing huge costs? Genuinely curious.