Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

AI in software engineering at Google: Progress and the path ahead

research.google

Post reply on HN
Print view View original

111–120 of 245 posts

Re: AI in software engineering at Google: Progress and the path ahead

#111

Post by brainwad »

endisneigh wrote: post #7

Anyone who works at Google knows they are force feeding the employees with this stuff. Same thing they’re doing with the general public and search. Anyone who worked at google during + can see this is the same half hearted type of force feeding that will fail, with the rationalizations to boot. Disclaimer: I hold google stock but don’t work at google

The AI suggestions they added to our editor and review tool are pretty uninvasive. The review suggestions are right 60% of the time, but the reviewer can just turn off the bad suggestions. The autocomplete is 90% good, but it isn't very ambitious. There's also a free text LLM chat thingy which can act on selected code, but I only ever tell it "fix" or "extract function" and for those use cases it's quite good.

Re: AI in software engineering at Google: Progress and the path ahead

#112

Post by bamboozled »

knallfrosch wrote: post #105
suyash wrote: post #94

So how long till AI will be fully replacing a SWE at Google? That is where the drive for productivity at organizations like Google are leading towards.

Assuming Google has tens of thousands of software engineers (for a lower bound of 10,000) and artificial intelligence increases productivity by at least 0.01%, the first engineer has already been replaced.

So how long till AI will be fully replacing a SWE at Google?

Notice parent said "fully"

Re: AI in software engineering at Google: Progress and the path ahead

#114

Post by asabla »

kgilpin wrote: post #74

When AI is used properly, it’s doing one of two things: 1) Making non-controversial fixes that save time and take cognitive load off the developer. The best example is when code completion is working well. 2) It’s making you smarter and more knowledgeable by virtue of the suggestions it makes. You may discard them but you still learn something new, and having an assistant brainstorm for you enables a different mode o…

> So how can AI usefully suggest design-level and conceptual ideas in a way that doesn’t require a user “trigger”?

I'm just guessing here. But maybe make it part of some other (already natural and learned) trigger made by the user.

I'm thinking part of refactoring. Were your AI is not only looking at the code, but the LSP, recent git changes (both commit and branch name), which code files you've been browsing.

And if you want to make it even more powerful. I guess also part of your browser history will be relevant (even if there is privacy concerns)

Re: AI in software engineering at Google: Progress and the path ahead

#115

Post by reacharavindh »

WalterSear wrote: post #109
jprete wrote: post #6

Earlier quoted context omitted.

This isn't a good trend. Reviewers never have the depth of knowledge or understanding of authors.

IMHO, review is a misnomer for where software engineering is going. I'm not sure where we are going, but review implies less responsibility for the outcome. But I do think that we will have less depth of knowledge of the underlying processes. That's the point of having a machine do it. I expect this, however, to be a good trend: the systems will need to be up to a task before it makes sense to rely on them.

This is how progress (in developer productivity) has always been made. We coded in assembler, then used macros, then a language like C, Fortran, then more of Java/Go/Puthon/Rust/Ruby et al. A developer writing a for loop over a list in Python need to necessarily know about linked lists and memory patterns because Python takes care of it. This frees up that developer from abstracted details and think one level closer to the problem at a higher speed.

LLMs _can_ be a good tool under the right hands. They certainly have some ways to become a reliable assistant. I suppose in the way of LLMs, they need better training before they can get there.

Re: AI in software engineering at Google: Progress and the path ahead

#116

Post by SrslyJosh »

zackproser wrote: post #51
mensetmanusman wrote: post #44

Earlier quoted context omitted.

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.

Re: AI in software engineering at Google: Progress and the path ahead

#117

Post by hi-v-rocknroll »

The gradual, eventual, ultimate conclusion killer app of AI is to run the systems, debug apps like an SRE, manage warm datastores, and eventually write app code based on the desires of feedback and requirements descriptions from users, design new programming languages/formats for it, and later design silicon. The curious bit is how product managers will fit into this picture to perhaps supervise what is allowed, only to eventually removed. There's no conceivable job that can't be eaten partially or mostly by AI, if not nearly entirely eaten in the future.

At some region on the technological "singularity" timeline, there will can and will be fully-autonomous corporations. The question is: With corporate personhood, can a corporation exist, pay (some) taxes, reinvest in itself, and legally function without any human owners? This may also be contingent on whether or not a corporation conduct legal and business activities, i.e., if performed by a human agent or through some automated means, even if they were directed by AI management. IANAL, but I guess an autonomous corporation could be sued, and perhaps even the creators of the software used to create the AI that run it could also be potentially at risk.

Re: AI in software engineering at Google: Progress and the path ahead

#118

Post by zekica »

bamboozled wrote: post #112
knallfrosch wrote: post #105

Earlier quoted context omitted.

Assuming Google has tens of thousands of software engineers (for a lower bound of 10,000) and artificial intelligence increases productivity by at least 0.01%, the first engineer has already been replaced.

So how long till AI will be fully replacing a SWE at Google? Notice parent said "fully"

Never? Google will probably reduce their SWE more and more assuming we get exponentially better at LLMs or something better comes along, but it won't ever be fully replaced.

Re: AI in software engineering at Google: Progress and the path ahead

#119

Post by vineyardmike »

jprete wrote: post #6
trybackprop wrote: post #2

From the blog post: > We observe that with AI-based suggestions, the code author increasingly becomes a reviewer, and it is important to find a balance between the cost of review and added value. We typically address the tradeoff with acceptance rate targets. In the past year since GPT-4 came out, I've also found this to be the case. I'm an ML/backend engineer with little experience in frontend development. Yet, I've…

This isn't a good trend. Reviewers never have the depth of knowledge or understanding of authors.

Frankly, its fine more often than we may care to admit.

As the parent comment suggested, UI elements are a great candidate for this. Often very similar (how many apps have a menu bar, side bar, etc) and full of boilerplate. And at the rate things change on the front-end, it's often a candidate for frequent re-writes, so code quality and health don't need to be as strict.

It'd be nice if every piece of software ever written was done so by wise experts with hand-crafted libraries, but sometimes it's just a job and just needs to be done.

Re: AI in software engineering at Google: Progress and the path ahead

#120

Post by vineyardmike »

knallfrosch wrote: post #105
suyash wrote: post #94

So how long till AI will be fully replacing a SWE at Google? That is where the drive for productivity at organizations like Google are leading towards.

Assuming Google has tens of thousands of software engineers (for a lower bound of 10,000) and artificial intelligence increases productivity by at least 0.01%, the first engineer has already been replaced.

> for a lower bound of 10,000

I'm guessing it's 30+k, depending on how liberal you are with the job (eg. data engineering, SREs, etc).

> the first engineer has already been replaced

Realistically, many engineers never got hired because of this already. Also they've had a few rounds of layoffs, so probably plenty are fired by now.

Google already was known for their use of automated code-gen long before they invented LLMs so I wouldn't be surprised if they're on the verge of major systems being gen'ed or templated with LLMs.

Post reply on HN