Google may be getting AI to write good SQL, but they aren’t getting it to write good blog posts.

The blog post lacks lots of details and sounds more of a marketing piece and “Try this!”. They did not release the evals, a very basic architecture flow which is not novel nor any real world benchmarks that says how it worked expect some vague statements. Must have been generated by Gemini

You can’t fake human clinical trials.

Definitely not worldwide, Colombia has a plant doing EA decaf

The Discogs integration is a great feature. I’ve checked out musicbrainz but it’s no where near as complete for the music I listen to.

Not on Mac. Absolutely worth it though

Your stakeholders?

I’ve seen enough awk behemoths in my time, no thanks.

I’m curious: what are some problems where awk was (presumably) a reasonable choice at first but then the implementation grew into a behemoth? Did the solution need to grow as the problem grew? Or was awk just the wrong choice from the beginning?

One case I saw it used was for processing genomics data. It was kinda ok at first but when we needed to add a new sequencing type it was laborious.

Personally I don’t think awk is a good choice for anything beyond one liners and personal scripts. Here it was fine because it was (initially) some write-once academic code that needed to not be insanely slow.

I definitely agree that using a tool like Fivetran is generally needless complexity when FDWs would get the job done.