[cpimhoff]

> way beyond the capabilities of standard SQL

Maybe the more precise language would be "way beyond the _expressive_ capabilities of standard SQL". Ultimately Hashquery compiles into SQL for execution, in that way it's a bit of a transpiler.

One concrete example is funnel analysis. In SQL, an efficient funnel analysis on large data sets will span several hundred lines of pipelined queries; writing, reading, and re-parameterizing this is very challenging. In Hashquery, it's abstracted into a single function call: `model.funnel(*str[])`.

> AI and LLMs (coming soon)

Frankly? SEO just told us to drop "AI" _somewhere_ on the page for new `.dev` website. I agree it's a little silly to make it a top-line bullet point.

We do think Hashquery is better suited for coding co-pilot tools, as it's a known language, and you can establish API boundaries that an AI tool won't break into and futz with (good for writing queries on top of already defined business logic).