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Comment by skywhopper | Hacker News Reader

I’m not seeing any evidence that any of this is actually good for Google’s business. Their observations that half of code checked in is from suggestions by an LLM is not really surprising in a regimented dev platform with tons of boilerplate. That stat tells us nothing about actual code quality, development velocity, or skill curves over time, much less business impact.

What product of Google’s has been improved by this feedback loop? The trajectory of Google search itself in the past year has been steadily downhill. And what other products of theirs I use don’t really change much, at least not in positive ways. Gmail is just gradually being crushed from every side by other app widgets scrounging for attention. Chrome has added… genAI features and more spyware? Great.

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Xoogler here.

This exactly. There is so much boilerplate involved in writing anything inside Google.

AI was great to cut that down a bit. It's still nowhere near what it's like in the outside and/or non-Java world.

Which isn't to say that this isn't progress - just that that stat should be taken with context.

Yeah I kind of agree that when LLMs work REALLY well for autocomplete of your codebase -- that might be an indication that the language and library abstractions you use don't fit the problem very well.

Code is read more than it's written. And it should be written to be read.

If you are barfing out a lot of auto-completed stuff, it's probably not very easy to read.

You have to read code to maintain it, modify it, analyze its performance, handle production incidents, etc.

> If you are barfing out a lot of auto-completed stuff, it's probably not very easy to read.

From my experience using LLMs, I'd guess the opposite. LLMs aren't great at code-golf style, but they're great at the "statistically likely boilerplate". They max out at a few dozen lines at the extreme end, so you won't get much more than class structures or a method at a time, which is plenty for human-in-loop to guide it in the right direction.

I'm guessing the LLM code at Google is nearly indistinguishable from the rest of it for a verbose language with a strong style expectation like java. Google must have millions of lines of Java, and a formatter that already maintains standards. An LLM spitting out helper methods and basic ORM queries will look just like any other engineers code (after tweaking to ensure it compiles).

If you already apply a code-formatter or a style guide in your organization, I'm guessing you'd find that LLM code looks and reads a lot like the rest of your code.

Yes, it can make stuff that fits in the rest of the codebase

But I am saying it's not going to ever make the code significantly better

In my experience, code naturally gets worse over time as you add features, and make the codebase bigger. You have to apply some effort and ingenuity to keep it manageable.

So if everyone is using LLMs to barf out status quo code, eventually you will end up with something not very readable. It might look OK locally, but the readability you care about is a global concern.

Google prints money until search goes away. Nothing else they work on has to succeed.

But increasingly I prefer to ask LLMs the same things I used to search Google for...

And then you do search to check that the output reflects reality, right? If not, good luck.

Hallucinations saved Google.

What you say tracks - but I'm wondering what happens if they manage to unlock some meaningful velocity increase to the point where they can begin tackling other domains and shuttling out products at a higher rate...Agree with your thoughts on search - it's f'ing unusable now and frustrating to look at.

Meaningful velocity increase while keeping quality high enough for the services to function in production and charge users..

Coding velocity is not a barrier to google tackling other domains.

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