I also worked at Google (on the original Gemini, when it was still Bard internally) and my experience largely mirrors this. My finding is that Gemini is pretty great for factual information and also it is the only one that I can reliably (even with the video camera) take a picture of a bird and have it tell me what the bird is. But it is just pretty bad as a model to help with development, myself and everyone I know uses Claude. The benchmarks are always really close, but my experience is that it does not translate to real world (mostly coding) task.

tldr; It is great at search, not so much action.

Gemini interesting with Google software gives me the best feature of all LLMs. When I receive a invite for an event, I screenshot it, share with Gemini app and say: add to my Calendar.

It's not very complex, but a great time saver

I don't know ... as of now I am literally instructing it to solve the chained expression computation problem which incurs a lot of temporary variables, of which some can be elided by the compiler and some cannot. Think linear algebra expressions which yield a lot of intermediate computations for which you don't want to create a temporary. This is production code and not an easy problem.

And yet it happily told me what I exactly wanted it to tell me - rewrite the goddamn thing using the (C++) expression templates. And voila, it took "it" 10 minutes to spit out the high-quality code that works.

My biggest gripe for now with Gemini is that Antigravity seems to be written by the model and I am experiencing more hiccups than I would like to, sometimes it's just stuck.