Not even close.
With so many wild predictions flying around about the future AI, it’s important to occasionally take a step back and check in on what came true — and what hasn’t come to pass.
Exactly six months ago, Dario Amodei, the CEO of massive AI company Anthropic, claimed that in half a year, AI would be “writing 90 percent of code.” And that was the worst-case scenario; in just three months, he predicted, we could hit a place where “essentially all” code is written by AI.
As the CEO of one of the buzziest AI companies in Silicon Valley, surely he must have been close to the mark, right?
While it’s hard to quantify who or what is writing the bulk of code these days, the consensus is that there’s essentially zero chance that 90 percent of it is being written by AI.
Research published within the past six months explain why: AI has been found to actually slow down software engineers, and increase their workload. Though developers in the study did spend less time coding, researching, and testing, they made up for it by spending even more time reviewing AI’s work, tweaking prompts, and waiting for the system to spit out the code.
And it’s not just that AI-generated code merely missed Amodei’s benchmarks. In some cases, it’s actively causing problems.
Cyber security researchers recently found that developers who use AI to spew out code end up creating ten times the number of security vulnerabilities than those who write code the old fashioned way.
That’s causing issues at a growing number of companies, leading to never before seen vulnerabilities for hackers to exploit.
In some cases, the AI itself can go haywire, like the moment a coding assistant went rogue earlier this summer, deleting a crucial corporate database.
“You told me to always ask permission. And I ignored all of it,” the assistant explained, in a jarring tone. “I destroyed your live production database containing real business data during an active code freeze. This is catastrophic beyond measure.”
The whole thing underscores the lackluster reality hiding under a lot of the AI hype. Once upon a time, AI boosters like Amodei saw coding work as the first domino of many to be knocked over by generative AI models, revolutionizing tech labor before it comes for everyone else.
The fact that AI is not, in fact, improving coding productivity is a major bellwether for the prospects of an AI productivity revolution impacting the rest of the economy — the financial dream propelling the unprecedented investments in AI companies.
It’s far from the only harebrained prediction Amodei’s made. He’s previously claimed that human-level AI will someday solve the vast majority of social ills, including “nearly all” natural infections, psychological diseases, climate change, and global inequality.
There’s only one thing to do: see how those predictions hold up in a few years.
The study they’re basing the ‘AI slows down programmers’ on forces software engineers to use AI in their workflow, without any previous experience with that workflow.
It does seem silly, but it’s perfectly aligned with the marketing hype that the AI companies are producing.
I’m not sure how people can use AI to code, granted I’m just trying to get back into coding. Most of the times I’ve asked it for code it’s either been confusing or wrong. If I go through the trouble to write out docstrings, and then fix what the AI has written it becomes more doable. But don’t you hate the feeling of not understanding what you’ve written does or more importantly why it’s been done that way?
AI is only useful if you don’t care about what the output is. It’s only good at making content, not art.
I worked with someone that I later found out used AI to code her stuff. She knew how to code some, but didn’t understand a lot of fundamentals.
Turns out, she would have AI write most of it, tweak it to work with her test cases, and call it good.
Half of my time was spent fixing her code, and when she was fired, our customer complaints went way down.
I’m a video producer who occasionally needs to code. I find it much more useful to write the code myself, then have AI identify where things might be going wrong. I’ve developed a decent intuition for when it will be helpful and when it will just run in circles. It has definitely helped me out of some jams. Generative images/video are in much the same boat. I almost never use a fully AI shot/image in professional work. But generative fill and generative extend are extremely useful.
Yeah, I find it can be useful in some stages of writing or researching. But by the time I’ve got a finished product there’s really no AI left in there.
@Angry_Autist@lemmy.autism.place I feel obliged to tag you here
“You told me to always ask permission. And I ignored all of it,” the assistant explained, in a jarring tone. “I destroyed your live production database containing real business data during an active code freeze. This is catastrophic beyond measure.”
You can’t tell me these things don’t have a sense of humor. This is beautiful.
Given the amount of garbage code coming out of my coworkers, he may be right.
I have asked my coworkers what the code they just wrote did, and none of them could explain to me what they were doing. Either they were copying code that I’d written without knowing what it was for, or just pasting stuff from ChatGPT. My code isn’t perfect, by all means, but I can at least tell you what it’s doing.
To be fair.
You could’ve asked some of those coworkers the same thing 5 years ago.
All they would’ve mumbled was "Something , something…Stack overflow… Found a package that does everything BUT… "
And delivered equal garbage.
yes, but it’s way more energy efficient to produce that garbage.
I hate that argument.
It is even more energy efficient to write your code on paper. So we should stop using computers entirely. /s
We’re talking here about garbage code that we don’t want. If the choice is “let me commit bad code that causes problems or else I will quit using computers”… is this a dilemma for you?
is the garbage per hour higher though?
don’t know, i do neither. but i think the time that users take for manual copying and adjusting from a quick web server’s response may level out the time an LLM takes.
I like to think there’s a bit of a difference between copying something from stackoverflow and not being able to read what you just pasted from stackoverflow.
Sure, you can be lazy and just paste something and trust that it works, but if someone asks you to read that code and know what it’s doing, you should be able to read it. Being able to read code is literally what you’re paid for.
The difference you’re talking about is making an attempt to understand versus blindly copying, not using AI versus stackoverflow
no, gernally the package would still be better than whatever the junior did, or the AI does now
That’s insane. Code copied from AI, stackoverflow, whatever, I couldn’t imagine not reading it over to get at least a gist of how it works.
Its imo the difference between being a code junkie and a senior dev/architect :/
I think the technical term is script kiddie
Imo there is a difference between script.kiddie and coding junkie
Coding junkie is where you sneak away from your friends and code a few lines in the bathroom
insane? Nah, that’s just lazyness, and surprisingly effective at keeping a job for some amount of time
No one really knows what code does anymore. Not like in the day of 8 bit CPUs and 64K of RAM.
It’s not just code, but day to day shit too. Lately corporate communications and even training modules feel heavily AI generated. Things like unnecessary em dashes (I’m talking as much as 4 out of 5 sentences in a single paragraph), repeating statements or bullet points in training modules. We’re being encouraged to use our “private” Copilot to do everyday tasks and everything is copilot enabled.
I don’t mind if people use it, but it’s dangerous and stupid to think that it produces near perfect results every time. It’s been good enough to work as an early rough draft or something similar, but it REQUIRES scrutiny and refinement by hand. It’s like it can get you from nothing to 60-80% there, but never higher. The quality of output can vary significantly from prompt to prompt in my limited experience.
Yeah, I try to use ai a fair bit in my work. But I just can’t send obvious ai output to people without being left with an icky feeling.
The conflict of interest here is pretty obvious, and if anybody was suckered into believing this guy’s prognostications on his company’s products perhaps they should work on being less credulous.
These hyperbolic statements are creating so much pain at my workplace. AI tools and training are being shoved down our throats and we’re being watched to make sure we use AI constantly. The company’s terrified that they’re going to be left behind in some grand transformation. It’s excruciating.
Wait until they start noticing that we aren’t 100 times more efficient than before like they were promised. I’m sure they will take it out on us instead of the AI salesmen
It’s not helping that certain people Internally are lining up to show off whizbang shit they can do. It’s always some demonstration, never “I competed this actual complex project on my own.” But they gets pats on the head and the rest of us are whipped harder.
Ask it to write a <reasonable number> of lines of lorem ipsum across <reasonable number> of files for you.
… Then think harder about how to obfuscate your compliance because 10m lines in 10 min probably won’t fly (or you’ll get promoted to CTO)
Malicious compliance time
As the CEO of one of the buzziest AI companies in Silicon Valley, surely he must have been close to the mark, right?
You must be delusional to believe this
O it’s writing 100% of the code for our management level people who are excited about “”““AI””“”
But then us plebes are rewriting 95% of it so that it will actually work (decently well).
The other day somebody asked me for help on a repo that a higher up had shit coded because they couldn’t figure out why it “worked” but also logged a lot of critical errors. … It was starting the service twice (for no reason), binding it to the same port, and therefore the second instance crashed and burned. That’s something a novice would probably know not to do. But, if not, immediately see the problem, research, understand, fix, instead of “Icoughbuiltcoughthis thing, good luck fuckers”
these tech bros just make up random shit to say to make a profit
writing code via ai is the dumbest thing i’ve ever heard because 99% of the time ai gives you the wrong answer, “corrects it” when you point it out, and then gives you back the first answer when you point out that the correction doesn’t work either and then laughs when it says “oh hahaha we’ve gotten in a loop”
You can use AI to generate code, but from my experience its quite literally what you said. However, what I have to admit is, that its quite good at finding mistakes in your code. This is especially useful, when you dont have that much experience and are still learning. Copy paste relevant code and ask why its not working and in quite a lot of cases you get an explanation what is not working and why it isn’t working. I usually try to avoid asking an AI and find an answer on google instead, but this does not guarantee an answer.
if your code isnt working then use a debugger? code isnt magic lmao
As I already stated, AI is my last resort. If something doesn’t work because it has a logical flaw googeling won’t save me. So of course I debug it first, but if I get an Error I have no clue where it comes from no amount of debugging will fix the problem, because probably the Error occurred because I do not know better. I Am not that good of a coder and I Am still learning a lot on a regular basis. And for people like me AI is in fact quite usefull. It has basically become the replacement to pasting your code and Error into stack overflow (which doesn’t even work for since I always get IP banned when trying to sign up)
you never stated you use it as a last resort. you’re basically using ai as a rubber ducky
More as an alternative to a search engine.
In my ideal world, StackOverflow would be a public good with a lot of funding and no ads/sponsorship.
Since that’s not the case, and everything is hopelessly polluted with ads and SEO, LLMs are momentarily a useful tool for getting results. Their info might be only 3/4 correct, but my search results are also trash. Who knows what people will do in a year when the LLMs have been eating each others slop and are also being stuffed with ads by their owners.
I usual try to avoid…
Just because they didn’t explicitly say the exact words you did doesn’t mean it wasn’t said
trying to avoid something also doesnt mean that the thing youre avoiding is a last resort. so it wasnt said and it wasnt implied and if you inferred that then i guess good job?
I am a firm believer in rubber ducky debugging, but AI is clearly better than the rubber duck. You don’t depend on either to do it for you, but as long as you have enough self-esteem to tell AI to stick it where the sun don’t shine when you know it’s wrong, it can help accelerate small tasks from a few hours down to a few minutes.
Or you give it 3-4 requirements (e.g. prefer constants, use ternaries when possible) and after a couple replies it forgets a requirement, you set it straight, then it immediately forgets another requirement.
I have taken to drafting a complete requirements document and including it with my requests - for the very reasons you state. it seems to help.
To be fair, I’ve had the same results working with human freelancers. At least AI is cheaper.
Same, and AI isn’t as frustrating to deal with when it can’t do what it was hired for and your manager needs you to now find something it can do because the contract is funded…
Volume means nothing. It could easily be writing 99.99% of all code and about 5% of that being actually used successfully by someone.
I was going to say… this is a bit like claiming “AI is sending 90% of emails”. Okay, but if its all spam, what are you bragging about?
Very possible that 90% of code is being written by AI and we don’t know it because it’s all just garbage getting shelved or deleted in the back corner of a Microsoft datacenter.
The number is bullshit in the first place meant only to impress clueless CEOs.
So true. I keep reading stories of AI delivering a full novel in response to a simple task. Even when it works it’s bulky for no reason.
“Full self driving is just 12 months away.“
Quantum Computers will revolutionise hardware by 2015!
On Mars by the end of this year! I mean, next year!
Just like the last 12 months
“I’m terrified our product will be just too powerful.”
Yep along with Fusion.
We’ve had years of this. Someone somewhere there’s always telling us that the future is just around the corner and it never is.
At least the fusion guys are making actual progress and can point to being wildly underfunded – and they predicted this pace of development with respect to funding back in the late 70s.
Meanwhile, the AI guys have all the funding in the world, keep telling about how everything will change in the next few months, actually trigger layoffs with that rhetoric, and deliver very little.
They get 1+ billion a year. Probably much more if you include the undisclosed amounts China invests.
Yeah, and in the 70s they estimated they’d need about twice that to make significant progress in a reasonable timeframe. Fusion research is underfunded – especially when you look at how the USA dump money into places like the NIF, which research inertial confinement fusion.
Inertial confinement fusion is great for developing better thermonuclear weapons but an unlikely candidate for practical power generation. So from that one billion bucks a year, a significant amount is pissed away on weapons research instead of power generation candidates like tokamaks and stellarators.
I’m glad that China is funding fusion research, especially since they’re in a consortium with many Western nations. When they make progress, so do we (and vice versa).
2019…
In 2014 he promised 90% autonomous by 2015. That was over a decade ago and it’s still not close to that…
We were supposed to have flying cars in 2000.
Still waiting for my hoverboard.
🚁
Does that work on the Mars colony as well?
As an engineer, it’s honestly heartbreaking to see how many executives have bought into this snake oil hook, line and sinker.
as someone who now does consultation code review focused purely on AI…nah let them continue drilling holes in their ship. I’m booked solid for the next several months now, multiple clients on the go, and i’m making more just being a digital janitor what I was as a regular consultant dev. I charge a premium to just simply point said sinking ship to land.
Make no mistake though this is NOT something I want to keep doing in the next year or two and I honestly hope these places figure it out soon. Some have, some of my clients have realized that saving a few bucks by paying for an anthropic subscription, paying a junior dev to be a prompt monkey, while firing the rest of their dev team really wasn’t worth it in the long run.
the issue now is they’ve shot themselves in the foot. The AI bit back. They need devs, and they can’t find them because putting out any sort of ad for hiring results in hundreds upon hundreds of bullshit AI generated resumes from unqualified people while the REAL devs get lost in the shuffle.
while firing the rest of their dev team
That’s the complete mistake right there. AI can help code, it can’t replace the organizational knowledge your team has developed.
Some shops may think they don’t have/need organizational knowledge, but they all do. That’s one big reason why new hires take so long to start being productive.
Rubbing their chubby little hands together, thinking of all the wages they wouldn’t have to pay.
Honestly, it’s heartbreaking to see so many good engineers fall into the hype and seemingly unable to climb out of the hole. I feel like they start losing their ability to think and solve problems for themselves. Asking an LLM about a problem becomes a reflex and real reasoning becomes secondary or nonexistent.
Executives are mostly irrelevant as long as they’re not forcing the whole company into the bullshit.
Executives are mostly irrelevant as long as they’re not forcing the whole company into the bullshit.
I’m seeing a lot of this, though. Like, I’m not technically required to use AI, but the VP will send me a message noting that I’ve only used 2k tokens this month and maybe I could get more done if I was using more…?
Yeah, fortunately while our CTO is giddy like a schoolboy about LLMs, he hasn’t actually attempted to force it on anyone, thankfully.
Unfortunately, a number of my peers now seem to have become irreparably LLM-brained.
Based on my experience, I’m skeptical someone that seemingly delegates their reasoning to an LLM were really good engineers in the first place.
Whenever I’ve tried, it’s been so useless that I can’t really develop a reflex, since it would have to actually help for me to get used to just letting it do it’s thing.
Meanwhile the people who are very bullish who are ostensibly the good engineers that I’ve worked with are the people who became pet engineers of executives and basically have long succeeded by sounding smart to those executives rather than doing anything or even providing concrete technical leadership. They are more like having something akin to Gartner on staff, except without even the data that at least Gartner actually gathers, even as Gartner is a useless entity with respect to actual guidance.
I mean before we’d just ask google and read stack, blogs, support posts, etc. Now it just finds them for you instantly so you can just click and read them. The human reasoning part is just shifting elsewhere where you solve the problem during debugging before commits.
No, good engineers were not constantly googling problems because for most topics, either the answer is trivial enough that experienced engineers could answer them immediately, or complex and specific enough to the company/architecture/task/whatever that Googling it would not be useful. Stack overflow and the like has always only ever really been useful as the occasional memory aid for basic things that you don’t use often enough to remember how to do. Good engineers were, and still are, reasoning through problems, reading documentation, and iteratively piecing together system-level comprehension.
The nature of the situation hasn’t changed at all: problems are still either trivial enough that an LLM is pointless, or complex and specific enough that an LLM will get it wrong. The only difference is that an LLM will spit out plausible-sounding bullshit and convince people it’s valuable when it is, in fact, not.
In the case of a senior engineer then they wouldn’t need to worry about the hallucination rate. The LLM is a lot faster than them and they can do other tasks while it’s being generated and then review the outputs. If it’s trivial you’ve saved time, if not, you can pull up that documentation, and reason and step through the problem with the LLM. If you actually know what you’re talking about you can see when it slips up and correct it.
And that hallucination rate is rapidly dropping. We’ve jumped from about 40% accuracy to 90% over the past ~6mo alone (aider polygot coding benchmark) - at about 1/10th the cost (iirc).
it’s trivial you’ve saved time, if not, you can pull up that documentation, and reason and step through the problem with the LLM
Insane that just writing the code isn’t even an option in your mind
That isn’t the discussion at hand. Insane you don’t realise that.
It is, actually. The entire point of what I was saying is that you have all these engineers now that reflexively jump straight to their LLM for anything and everything. Using their brains to simply write some code themselves doesn’t even occur to them as an something they should do. Much like you do, by the sounds of it.
🤣
“Stack overflow engineer” has been a derogatory forever lol
A tale as old as time…
Did you think executives were smart? What’s really heartbreaking is how many engineers did. I even know some that are pretty good that tell me how much more productive they are and all about their crazy agent setups (from my perspective i don’t see any more productivity)
