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ipsin | 6 months ago
Like, surfacing APIs, fostering interoperability... I don't want an AI agent, but I might be interested in an agent operating with fixed rules, and with a limited set of capabilities.
Instead we're trying to train systems to move a mouse in a browser and praying it doesn't accidentally send 60 pairs of shoes to a random address in Topeka.
simonw|6 months ago
We don't need to figure out the one true perfect design for standardized APIs for a given domain any more.
Instead, we need to build APIs with just enough documentation (and/or one or two illustrative examples) that an LLM can help spit out the glue code needed to hook them together.
roxolotl|6 months ago
I think about code generation in this space a lot because I’ve been writing Gleam. The LSP code actions are incredible. There’s no “oh sorry I meant to do it the other way” you get with LLMs because everything is strongly typed. What if we spent 100billion on a programming language?
We’ve now spent many hundreds of billions on tools which are powerful but we’ve also chosen to ignore many other ways to spend that money.
eastbound|6 months ago
Time of executing bytecode << REST APIs << launching a full JVM for each file you want to compile << launching an LLM to call an API (each << is above x10).
AdieuToLogic|6 months ago
> ... we need to build APIs with just enough documentation (and/or one or two illustrative examples) that an LLM can help spit out the glue code needed to hook them together.
If a developer relies on client code generated by an LLM to use an API, how would they know if what was generated is a proper use of said API? Also, what about when lesser used API functionality should be used instead of more often used ones for a given use-case?
If the answer is "unit/integration tests certify the production code", then how would those be made if the developer is reliant upon LLM for code generation? By having an LLM generate the test suite?
And if the answer is "developers need to write tests themselves to verify the LLM generated code", then that implies the developer understands what correct and incorrect API usage is beforehand.
Which begs the question; why bother using an LLM to "spit out the glue code" other than as a way to save some keystrokes which have to be understood anyway?
PaulDavisThe1st|6 months ago
I get that in the webdev space, that is true to a much larger degree than has been true in the past. But it's still not really the central problem there, and is almost peripheral when it comes to desktop/native/embedded.
xnx|6 months ago
Gigachad|6 months ago
Mix of open platforms facing immense abuse from bad actors, and companies realising their platform has more value closed. Reddit for example doesn't want you scraping their site to train AIs when they could sell you that data. And they certainly don't want bots spamming up the platform when they could sell you ad space.
tyre|6 months ago
LLMs are 10x better than the existing state of the art (scraping with hardcodes selectors). LLMs making voice calls are at least that compared to the existing state of the art (humans sitting on hold.)
The beauty of LLMs is that they can (can! not perfectly!) turn something without an API into one.
I’m 100% with you that an API would be better. But they’re not going to make one.
medhir|6 months ago
Like, we already had a perfectly reasonable decentralized protocol with the internet itself. But ultimately businesses with a profit motive made it such that the internet became a handful of giant silos, none of which play nice with each other.
1oooqooq|6 months ago