> the LLM glue logic is what makes it effective
Allegedly (it's proprietary, we don't know). Maybe it's the triage approach, and there are undiscovered non-LLM triage techniques that would surpass it.
If I were to guess, the AI naming was for marketing purposes (to ride on the hype train), not because it accurately describes the product (even though it might accurately describe the product).
Most importantly, how is that it's so effective? I want to know. Perhaps you and some others just want to celebrate an LLM win. That's fine, but I want to know how it works.
I'd say my guess is fair, and it's a viable approach for someone trying to create a similar tool. If I were to try and replicate this, I would definitely start with an existing static analyzer. For example, I would do it with phpstan (just because I know it a little bit better).
I would extend it so it becomes more verbose than what it currently is (something humans don't want, but machines might benefit from it). Perhaps I would introduce some rules that make it report things that aren't even issues, but just information I can gauge from the AST (like, does this controller has a middleware? If so, emit something in the report). Then I would attempt to use that enriched report as the input for a coding model, and experiment with different prompts and different granularity units on the input.
It sounds reasonable, doesn't it? I could describe that approach as "LLM right in the core of the solution", but I know by heart that in that arrangement, the quality of the final product is still capped by the static analyzer and what it can detect and describe. It doesn't matter that the LLM is what makes it better. My wheat farm is still about wheat, not the fancy sift I recently bought to separate it from the chaff.
I don't understand why this sounds so offensive to some of the readers here. I was just thinking "how would I use AI in such a product" and the only way I can come up with is this way in which is not the main show.
I mean, my experience with LLMs also confirm that. Prompting "find me bugs" or stuff like that almost never works. It works better if I get an error and ask it to explain it to me, giving the application context. The static analyzer is there to give this initial kick, to create these nucleation sites in which the LLM will crystalize answers upon.
This sounds like the most viable, easy to make product that can find bugs with LLMs. It's only offensive if that's actually what these products are doing, it's not supposed to be known and I struck a nerve or something.