There are a lot of versions of this already, the main blocker is people not wanting to learn a bespoke DSL.
The second problem is the escape latch story, how do people customize beyond the functions when they inevitably reach that point. If you haven't hit this, you haven't built complex enough applications yet with your framework.
The elephant in the room is, why this instead of Ai? (I personally have an answer to this question, in the scope of my take on the framework described in your post)
Also true, suppose one would have to basically make it support basically full nodejs code? I wonder how restricting AWS Lambda gets, once you start building something complex.
Why instead of AI? I started thinking about this more because of AI, if you have a clear definition of your backend, with solid primitives, that can just get deployed at each commit, without much concern for the infra and such, this makes it easier to slop your way through features?
Not if I have to load up a bunch of explanation and pollute my context because of a tool with bespoke DSL
I already built this same thing with CUE as the DSL. So (1) my questions come from experience (2) the LLMs already know CUE because it has been around longer and it's in their training data
I don't think Elixir's Ash is too far off: https://ash-hq.org
New lines got nuked, great, here's the same doc on a github gist - https://gist.github.com/sssemil/fa94948ae0c12d92f9b1fdc272f7...
There are a lot of versions of this already, the main blocker is people not wanting to learn a bespoke DSL.
The second problem is the escape latch story, how do people customize beyond the functions when they inevitably reach that point. If you haven't hit this, you haven't built complex enough applications yet with your framework.
The elephant in the room is, why this instead of Ai? (I personally have an answer to this question, in the scope of my take on the framework described in your post)
True, I'd hate learning a new DSL...
Also true, suppose one would have to basically make it support basically full nodejs code? I wonder how restricting AWS Lambda gets, once you start building something complex.
Why instead of AI? I started thinking about this more because of AI, if you have a clear definition of your backend, with solid primitives, that can just get deployed at each commit, without much concern for the infra and such, this makes it easier to slop your way through features?
Not if I have to load up a bunch of explanation and pollute my context because of a tool with bespoke DSL
I already built this same thing with CUE as the DSL. So (1) my questions come from experience (2) the LLMs already know CUE because it has been around longer and it's in their training data