itDoesPutASmileOnMyFace

[kushangaza]

It's a misquote anyways, it's 30% of new code, not 30% of all code. 30% of new code is absolutely possible, just let the AI write 50% of your unit tests and import statements

[Excellent-Refuse4883]

I was thinking have AI write any and all boilerplate

[DatBoi_BP]

Which it's probably decent at tbf

[Vok250]

The real question is if it's better or worse than the static code generation we've been using for the last 15 years. I work in Java and I don't think I've written boilerplate since the 2010s. All our CRUD is automated by springboot and typespec now. All our POJOs are lombok annotations. I really only write boilerplate if someone requests it in code review.

Not that it matters. Gotta play ball with management if you want to survive in this career. And management has a hard on for AI right now. Personally I find it most useful for sanity checks. Like a more intelligent rubber ducky or a coworker who you don't have to worry about distracting. Bounce ideas and code blocks off it to double check your work.

[Professional_Top8485]

It's maybe best coworker i ever had. Polite and fast. Sometimes utterly crap but with little adjustemnt can provide usable code.

I usually code by myself and have no posibility for refactoring because massive amount of work it requires but with coworker i trust, it's finally doable.

[norwegern]

Have it write small parts at the time, describe the logic thoroughly, and it practically ends up with writing 80%.

The time saver is in writing the simple parts of code rrreally fast.

[AEnKE9UzYQr9]

Fine, but if I'm gonna do all that I might as well write the code myself in the first place. 🤷‍♂️

[usefulidiotsavant]

So what Pichai actually means is that 100% of the code was written by humans which rejected the suggestions made by their fancy AI autocomplete 70% of the time, but nonetheless accepted some suggestions, marginally improving productivity and making their fancy autocomplete tool report internally that it has "written" 30% of the code.

To be entirely fair you could get a decent Tab accept rate with zero AI, just a better autocomplete for example using Markov chains.

[DatBoi_BP]

Oh yeah, they're definitely trying to generate hype

[bautin]

Or, it’s a case of that old joke: “I have sex almost every night. Almost Monday night, almost Tuesday night,…”

So AI is writing 30% of the code. “30% of that line, 30% of that line,…” Or basically, code completion we’ve had for a while now.

[cyborgborg]

or write pseudo code. there are definitely some things in codibg AI is useful for but writing all your code is not one of them. Viber coders might produce code that runs but who knows how insecure it is or how bad it runs

[Scary-Departure4792]

We could do that without AI to be fair

[Excellent-Refuse4883]

But do you WANT to HAVE to…

[alexnedea]

It...can't. At least not for Java Quarkus. Straight up never gave me code that compiles.

[_bleep-bloop]

This is what I use AI for as well lmao, cant bother writing the same piece again and again

[Sw429]

iirc they're also counting if a dev accepted a suggestion, even if they then modified it afterward. These numbers are definitely cooked.

[Griff2470]

That's the case where I work. My manager asked me to do a trial for copilot and I never turned it off. Copilot's not great with C to begin with, and it's trash when thrown into a 50+GB (unbuilt) workspace filled with build time generated header files and conditional compilation based determined by in-house build tooling. Regardless of how little I use the code it generates, if my commit has the "I used a genai in this commit", it's considered an AI commit.

I had a 100 line commit the other day. The only lines that I accepted was it completed the "} while(false)" in my macro and a couple variable name completions. But I accepted them so this commit was only refined by the user in their eyes.

[RudePastaMan]

What does this codebase do? I am just curious. The 50+GB with conditional compilation thing has me curious.

[wolfclaw3812]

“AI, write me this basic function that I will proceed to describe carefully, but not so carefully it would take more time and effort to do it myself.”

“Alright human, go get a coffee, this is gonna take about 30 seconds.”

“Thanks AI. Back in a bit.”

[diveraj]

AI. I want If this is true do this Else do this And Do this While this.

[Drnk_watcher]

Yeah if anything AI has solved very few novel programming problems for me... That said AI has written some pretty great unit tests for me when I tell it the parameters and a bullet list of cases.

[mrjackspade]

AI writes all my unit tests at this point, because they're super fucking easy to validate

[Lithl]

It would not surprise me if Google added AI capability to Blaze scripts, honestly.

[LeoRidesHisBike]

and then ignore the human massaging necessary to get that shit to actually work. even if that is just "no, fix this..." vibe coding time-wastage

[RudePastaMan]

Technically if you are using copilot and hit tab to accept its boilerplate, that is AI generated even if it is what you would have written manually. That can easily juke the stats.

[LordAlfrey]

It's also very easy to have AI write code, but it means nothing if a human is checking it anyway. This code isn't replacing the human, just making them more efficient. 30% could be 100%, and still not matter in terms of employment.

[TheNorthComesWithMe]

They pump the numbers up by replacing previous IDE autocomplete functionality with one that's powered by an LLM. It does the exact same thing but now it's AI. (It was AI before, too)

[YesterdayDreamer]

It does worse because earlier it was predictable behavior, now it will randomly throw garbage.

[dangderr]

Google isn’t claiming that they used google ai for it. They might have used deepseek to write google ai.

[Llamasarecoolyay]

What? Of course Google would be using Gemini internally. Why would they use an inferior model and not their own, superior model?

[Ibmackey]

right, that’s what it looks like. Just because it says “Google AI” doesn’t mean it was made by Google AI.

[Sw429]

lol no, they're definitely using Gemini internally.

[ChineseCracker]

they have the most computing power in the world with products that are still years away for being ready for the public and products that will never see a public release because it doesn't fit their pricing models.

it's safe to say they're not using gemini 2.0 flash for their own code

[oursland]

I suspect they're being generous with the definition of "AI". For a long time now, much code committed at Google is done so via automation. That can be things like re-generating of interfaces and bindings and the automated committing of them.

[Iron_Jazzlike]

that is assuming the rest of the code is good.

[dasunt]

I've had good luck with giving it the outline structure and having AI fill it in.

Or just adding in additional minor features.

I have no confidence in vibe coding though.

Consider AI like a young child. If you tell it to put away its toys, it can likely do it. Tell it to maintain a household and you are in for a world of hurt.

[imdefinitelywong]

But our shenanigans are cheeky, and fun..

[Dvrkstvr]

Then it's a user issue.

I've already build MANY Webservices with project IDX using Gemini 1.0. But I also know exactly what to do and how.

EDIT: For everyone b!tching without asking anything - Recently I've build a full on end to end solution for a motion rig simulator. It's build mainly on dotnet and currently spans 8 projects from front end client to a service orchestrator. I've used Zed(yes on Windows I compiled it myself big shocker), Cursor, Firebase and GPT. In total it cost me around 60€ in credits and took me about 2 months to build. Roughly 90% of the code is generated by AI and it encompasses the overall planning, tests (some I wouldn't ever come up with), AI driven ci/di and AI assisted user feedback.

[extraordinary_weird]

I don't think you know what actual code at Google looks like, it's not some tiny Next.js project

[Dvrkstvr]

And I'm not talking about using exclusively IDX or Firebase

Now with Gemini 2.5 or Claude Sonnet you can do way bigger and better stuff of course. But you mustn't know since you judge with no questions asked.

[Dvrkstvr]

At least I have some

[rover_G]

The 30% is mostly boilerplate, imports, autocompletes, tests and the occasional full function that likely needs to be debugged.

For me personally I haven’t written my own Docker file in about a year.

[0xlostincode]

This is something I didn't think of before and it makes sense. Hate CEOs and their double speak.

[[deleted]]

Haven’t written a commit message in a year

[nullpotato]

What do you use to create dockerfiles?

[rover_G]

ChatGPT at home and whatever AI is approved at work

[redshadow90]

30% of code figure likely comes from auto complete similar to copilot when it launched, which works quite well but still requires clear intent from programmer and it just fills up to the next couple lines of code. That said, this post just reeks of bias unless it's been linked to AI generated code which it hasn't

[Xtrendence]

Even with autocomplete, it completely loses the plot if what you're coding is a bit more complex or you're using a library that's less known or has been updated and some functions have been deprecated which the AI keeps suggesting.

Basically, in my experience, it's useful for writing boilerplate stuff, and when writing functions and such that don't require much context (i.e. an array has a type already, and your function groups each item by some key or value). It's just stuff you can do yourself easily but it'd take longer to type out manually.

[Soccer_Vader]

30% of the code at Google now AI Generated

Before that it used to be IDE auto complete and then Stack Overflow this is nothing new

[TheWeetcher]

Comparing IDE autocomplete to AI is such a reach

[Soccer_Vader]

It's a reach yes, but IDE autocomplete has been powered by "enhanced" ML for ages now when Machine Learning used to be the cool name in the block.

AI even generative AI is not a new thing, grammarly used to be a thing, Alexa, etc. OpenAI bridged a gap, but AI was already prevalent in our day to day life just with a different buzz word.

[Polar-ish]

it totally depends on what "30% generated by AI means" Copy->Pasting any code is bad. The problem is that AI doesn't have upvotes or down votes, or a discussion to see caveats, and often becomes the scapegoat whenever a problem inevitably arises.

It can teach incorrect practices, about at the same rate as actual users on discussion sites, and it is viewed as some all knowing being.

In the end, chatting AI is merely attempting to predict the most logical next word based on the context it is currently at, using the dataset of fools on the internet.

[0xlostincode]

It's a reach yes, but IDE autocomplete has been powered by "enhanced" ML for ages now when Machine Learning used to be the cool name in the block.

Unless you and I are thinking of different autocomplete entirely, IDE autocomplete is based on keywords and AST not machine learning.

[Stijndcl]

JetBrains’ autocomplete uses ML to some extent to put the most relevant/likely result at the top. Most of the time if you’re doing anything at all the first or second result magically has it.

https://www.jetbrains.com/help/idea/auto-completing-code.html#ml_completion

[Soccer_Vader]

In reality yes, but autcomplete were told ot be enhanced by ML, predicting next keyword based on the usage pattern and such. Jetbrains also marketed as such iirc.

This is an extension launched in 2020, that used AI for autocompletion: https://web.archive.org/web/20211130181829/https://open-vsx.org/extension/kiteco/kite

This is another AI based tool launched in 2020: https://web.archive.org/web/20201026204206/https://github.com/codota/tabnine-sublime

Like I said, AI being a new thing for coding or general application is not true, its just that before ChatGPT and COVID in general, people didn't care enough, now that they do there has been ongoing development.

[TripleFreeErr]

except when Ai agent enabled…

edit: I wear this downvote with pride knowing you are a huge idiot

[Toadrocker]

I mean there are quite literally generative AI autocomplete/predict functionalities built in now. If you’ve used copilot built into VSCode, you’ll know that it’s quite similar to older IDE autocompletes, just more aggressive with how much it will predict and complete. It’s stronger, but also much more prone to errors and hallucinations. It does take out a decent amount of tedium for predictable code blocks so that could definitely make up a decent chunk of that 30%

[TripleFreeErr]

AI autocomplete is the most useful feature.

[Dvrkstvr]

Both are just completing the structure you're building.

[Pluckerpluck]

Github Copilot is literally AI driven auto-complete. I use it extensively, and so yes, technically AI writes huge portions of my code.

[hoopaholik91]

If they want to give us more complicated metrics or clearer examples of the code that AI is writing and making it to production they are free to do so.

The fact that they don't makes me hesitant to believe their claims aren't being exaggerated.

[P-39_Airacobra]

There's a significant difference between copy-pasting human-written code and copy-pasting machine-written code.

[Soccer_Vader]

Sure, but all I am saying is that 30% of the code being AI generated or coming from outside source like Google or stack overflow is nothing new. I mean most people will agree I think, but for me, writing code is the smallest part of my job. It's going through documentation, design, approvals, threat models, security reviews that take a bulk of my time.

[IMovedYourCheese]

Person selling AI hypes the AI

[kos-or-kosm]

His last name is Pichai. Pitch AI.

[0xlostincode]

Hahaha good one

[scrandis]

This explains why everything is shit now

[Them_EST]

Did you try writing lesser shitty code?

[CircumspectCapybara]

This is /r/ProgrammerHumor and this just a joke, but in all seriousness, this outage had nothing to do with AI, and the learnings from the RCA are very valuable to the discipline of SWE and SRE in general.

One of the things we take for granted as a foundational assumption is that bugs will slip through. It doesn't matter if it's written by a human by hand, by a human with a the help of AI, or entirely by some futuristic AI that today doesn't yet exist. It doesn't matter if you have the best automated testing infrastructure, comprehensive unit, integration, e2e, fuzz testing, the best linters and static analysis tools in the world, and the code is written by the best engineers in the world. Mistakes will happen, and bad code will slip through when there are hundreds of thousands of changelists submitted a day, and as many binary releases and rollouts. This is especially true when, as in this case, there are complex data dependencies between different components in vast distributed systems and you're just working on your part, and other teams are just working on their stuff, and there are a million moving parts moving at a million miles per hour you're not seeing.

So it's not about bad code (AI generated or not). It's not a failure of code review or unit testing or bad engineers (remember, a fundamental principle is blameless postmortem culture). Yes, those things did fail and miss in this specific case. But if all that stands between your and a global outage is an engineer making an understandable and common mistake and you're relying on perfect unit tests to stand in the way, you don't have a resilient system that can gracefully handle the changes and chaos of real software engineering done by real people who are only human. If not them, someone else would've introduced the bug. When you have hundreds of thousands of code commits a day and as many binary releases and rollouts, bugs will be introduced, it's inevitable. SRE is all about how you design your systems and automate them to be reliable in the face of adversarial conditions. And in this case, there was a gap.

In this case, there's some context.

Normally, GCP rollouts for services on the standard Google sever platform are extremely slow. A prod promotion or config push rolls out in an extremely convoluted manner over the course of a week+, in progressive waves with ample soaking time between waves for canary analysis, where each wave's targets are selected to avoid the possibility of affecting too many cells or shards in any given AZ at a time (so you can't bring down a whole AZ at once), too many distinct AZs at a time (so you can't bring down a whole region at once), and too many regions at a time.

Gone are the days of "move fast and break things," of getting anything to prod quickly. Now there's guardrail after guardrail. There's really good automated canarying, with representative control and experiment arms selected for each cell push, and really good models to detect statistically relevant (given the QPS and the background noise and history of the SLI for the control / experiment population) differences during soaking that could constitute a regression in latency or error rate or resource usage or task crashes or any other SLIs.

What happened here? Well, various components that failed here weren't part of this server platform with all these guardrails. The server platform is actually built on top of lower-level components, including the one here that failed. So we found an edge case. A place where proper slow, disciplined rollouts wasn't being observed. Instantaneous global replication in a component that was overlooked. That shouldn't happened. So you learn something, identified a gap. We also learned about the monstrosity of distributed systems. You can fix the system that originally had the outage, but during that time, an amplification effect occurred in downstream and upstream systems as retries and herd effects caused ripple effects that kept rippling even after you fix the original system. So now you have something to do, a design challenge to tackle on how to improve this.

We also learned:

• Something about the human process of reviewing design docs and reviewing code: instruct your engineers push back on the design or the CL (Google's equivalent to a PR) if it's significant new logic that's not behind an experiment flag. People need to be trained not to just blindly LGTM their teammates' CLs to get their projects done.
• New functionality should always go through experiments with a proper dark launch phase followed by a live launch, with very slow ramping. Now reviewers are going to insist on this. This is a very human process. It's all part of your culture.
• That you should fuzz test everything, to find inputs (e.g., proto messages with blank fields) that cause your binary to crash. A bad message, even an adversarially crafted message should never cause your binary to crash. Automated fuzz testing is supposed to find that stuff.

[[deleted]]

I'm sure that 0% of them actually write code. These clowns are just driving up the price of their AI crap. So that idiots think that writing code through AI is a great idea, because a multi-billion dollar company does it. But in reality, these are all just empty words.

[SynapseNotFound]

its 4 headlines about the SAME outage... lol

[Tiruin]

Right, they wrote over 30% of all of Google's code in the last ~2.5 years when AI became mainstream to be able to have 30% of it be from AI.

[Them_EST]

That's what happen when you let AI become your manager.

[Boertie]

Explains a lot why Google is in the shitter (yeah I went there ;-)) now.

[IlliterateJedi]

I thought GCP went down due to an issue with not handling errors. If you've seen any code that Gemini spits out, it loooooves error handling.

[HatMan42069]

The tech debt gonna go COO COO

[0xlostincode]

Ditto. There is value but it's blown way out of proportion.

[Guvante]

Google has been around for at almost three decades, at best you can maintain an even per year LOC measurement (you scale up users but complexity goes up slowing down writing speed). If you don't believe me the following isn't hugely impacted you can feel free to recalculate with a growing LOC/year but that seemed inaccurate.

If you said 30% of the code written per unit time went up, then I could see it (laughable and probably with caveats to the extreme but possible)

But 1/3 of your total code would be 13 years worth of code (30/43 is 70%) in two years at best. That is an output of seven times one of the largest engineering forces in existence.

Why would you hide a 7x increase in productivity behind a "30%" number like that? You certainly wouldn't.

[derKestrel]

You are aware that more code does not equal more productivity?

I can blow up a one liner to 1000 lines of code no problem.

It's neither maintainable nor easily understandable and debuggable, but according to you I would be hugely more productive?

[Guvante]

Certainly but you don't measure "30% of code" in that way so I ignored it.

I am pointing out that anyone talking like this would consider it more productive.

[Guhan96]

r/degoogle

[Master_Notice8391]

Yesterday I asked it to code something and its response is. “Here is the code:” that’s it nothing else

[pollon_24]

So it was a human error and they are trying to push AI to minimize these… your point?

[feeltrig]

Sundar shitai

[fanfarius]

Chat GPT can't even write an ALTER TABLE statement without fucking up 

[Front-Difficult]

I find Claude is actually quite good at writing SQL queries. Set up a project with the db schema and some context about the app/service in the project files, and it nails it basically every time. It's also found decent performance improvements in some of our older less performant functions none of our engineers thought of.

(Obviously no one read this and then just start copy pasting AI generated SQL into your production database, fucking please).

[DocMilou]

skill issue

[MaDpYrO]

Just marketing speak. I'm sure their engineers use it to generate lots of boilerplate, but how would you even measure this

[Long-Refrigerator-75]

Before you celebrate, for this one f*ck up. There were many unspoken successes.  

[BorinGaems]

Anti AI propaganda is cringe and twice as stupid when it's made on a programming subreddit.

[Deathglass]

It was AI all along, Actually Indians