The value is in being able to prompt AI something like "Here's my data that comes from endpoint X. Give me a table that shows this data that is also searchable."
I personally find that valuable (along with not having to think about which auth vendor and component library to use).
I can do that manually with existing tools in half an hour. Endpoints change very rarely, once you setup your "view" of that endpoint you are mostly done for a long time, with some smaller changes over time.
Also if I wanted to go AI route, I can ask Cloude Opus or GPT4 : "Here is an endpoint that returns this type of data <paste data type here>, make me a React component that fetches this data and presents it in searchable table using shadcn"
It will get me 80-90% there, it would need just a little manual tweaking to conform to the current project code standards.
This is the exact thing I've personally tried several times and it doesn't work well. But it works with a prompt in our app right now.
Some reasons listed below:
1. Gpt hallucinates shadcn's big data table implementation more often than not. Also, you don't have props for everything by default (page size, filtering, sticky columns etc)
2. We have certain rules we ask our AI to stick to, such as always putting a table in a card and consistent padding. So there's lesser cognitive effort in you thinking about how to style your tools.
3. Current LLMs are shaky with next14 right now, especially on where to use server and client components.
> The value is in being able to prompt AI something like "Here's my data that comes from endpoint X. Give me a table that shows this data that is also searchable."
This is a billion dollar idea even if at like a 70%+ success rate. And as a data engineer, I assure you the success rate is not there. There are so many edge cases, so many caveats, so many headaches; an AI generated solution will only work in the perfect API scenario (which never happens in the real world).
Just like Retool (or any other platform), you're expected to bring your own endpoint (but you're also free to write it in our app if you want).
The value will be in closing that feedback loop:
1. Here's the shape of the data coming in from endpoint /api/xyz. Currently, generating an endpoint with AI with this much nuance is very low in terms of success rate (and I think is what you're talking about).
2. However, once you know the endpoint and what the data looks like, our tool becomes valuable because you can just specify in natural language, which component you want to use, and how it has to be laid out on the page.
Several people will prefer natural language over dragging and dropping UI elements on a screen. And the success rate is far higher for something like this.
The value is in being able to prompt AI something like "Here's my data that comes from endpoint X. Give me a table that shows this data that is also searchable."
I personally find that valuable (along with not having to think about which auth vendor and component library to use).