Fascinating since I found the recent Claude models untrustworthy for writing and editing SQL. E.g. it'd write conditions correctly, but not add parens around ANDs and ORs (which gemini pro then highlighted as a bug, correctly.)
As a recent example, I am working on a Rust app with integrated DuckDB, and asked it to implement a scoring algorithm query (after chatting with it to generate a Markdown file "RFC" describing how the algorithm works.) It started the implementation with an absolute minimal SQL query that pulled all metrics for a given time window.
I questioned this rather than accepting the change, and it said its plan was to implement the more complex aggregation logic in Rust because 1) it's easier to interpret Rust branching logic than SQL statements (true) and 2) because not all SQL dialects include EXP(), STDDEV(), VAR() support which would be necessary to compute the metrics.
The former point actually seems like quite a reasonable bias to me, personally I find it harder to review complex aggregations in SQL than mentally traversing the path of data through a bunch of branches. But if you are familiar with DuckDB you know that 1) it does support these features and 2) the OLAP efficiency of DuckDB makes it a better choice for doing these aggregations in a performant way than iterating through the results in Rust, so the initial generated output is suboptimal.
I informed it of DuckDB's support for these operations and pointed out the performance consideration and it gladly generated the (long and certainly harder to interpret) SQL query, so it is clearly quite capable, just needs some prodding to go in the right direction.
It is very useful for simpler tasks like writing tests, converting code bases etc where the hard part is already done.
When it comes to actually doing something hard - it is not very useful at least in my experience.
And if you do something even a bit niche - it is mostly useless and its faster do dig into topic on your own that try to have Claude implement it.