The "micro" trend in AI is fascinating. We're seeing diminishing returns from just making models bigger, and increasing returns from making them smaller and more focused.

For practical applications, a well-tuned small model that does one thing reliably is worth more than a giant model that does everything approximately. I've been using Gemini Flash for domain-specific analysis tasks and the speed/cost ratio is incredible compared to the frontier models. The latency difference alone changes what kind of products you can build.