Hi, I lead the teams responsible for our internal developer tools, including AI features. We work very closely with Google DeepMind to adapt Gemini models for Google-scale coding and other Software Engineering usecases. Google has a unique, massive monorepo which poses a lot of fun challenges when it comes to deploying AI capabilities at scale. 1. We take a lot of care to make sure the AI recommendations are safe and…
I'm continually surprised by the amount of negativity that accompanies these sort of statements. The direction of travel is very clear - LLM based systems will be writing more and more code at all companies. I don't think this is a bad thing - if this can be accompanied by an increase in software quality, which is possible. Right now its very hit and miss and everyone has examples of LLMs producing buggy or ridiculou…
At Google, today, for sure.
I do believe we still are not across the road on this one.
> if this can be accompanied by an increase in software quality, which is possible. Right now its very hit and miss
So, is it really a smart move of Google to enforce this today, before quality have increased? Or did this set off their path to losing market shares because their software quality will deteriorate further over the next couple years?
From the outside it just seems Google and others have no choice, they must walk this path or lose market valuation.