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.
AI writes 100% of my code, but this is only a small percent of the overall development effort.
Well, 90% of code of which only 3% works. That sounds sbout right.
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’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.
Are we counting the amount of junk code that you have to send back to Claude to rewrite because it’s spent the last month totally lobotomized yet they won’t issue refunds to paying customers?
Because if we are, it has written a lot of code. It’s just awful code that frequently ignores the user’s input and rewrites the same bug over and over and over until you get rate limited or throw more money at Anthropic.
“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.
This is beautiful.
These are truly lyrics, they are begging for a banger of a pop music video.
@Angry_Autist@lemmy.autism.place I feel obliged to tag you here
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.
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 :/
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.
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.
“Full self driving is just 12 months away.“
deleted by creator
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.
2019…
In 2014 he promised 90% autonomous by 2015. That was over a decade ago and it’s still not close to that…
Does that work on the Mars colony as well?
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.
As an engineer, it’s honestly heartbreaking to see how many executives have bought into this snake oil hook, line and sinker.
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)
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)
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”
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.
It is writing 90% of code, 90% of code that goes to trash.
Writing 90% of the code, and 90% of the bugs.
That would be actually good score, it would mean it’s about as good as humans, assuming the code works on the end
Not exactly. It would mean it isn’t better than humans, so the only real metric for adopting it or not would be the cost. And considering it would require a human to review the code and fix the bugs anyway, I’m not sure the ROI would be that good in such case. If it was like, twice as good as an average developer, the ROI would be far better.
If, hypothetically, the code had the same efficacy and quality as human code, then it would be much cheaper and faster. Even if it was actually a little bit worse, it still would be amazingly useful.
My dishwasher sometimes doesn’t fully clean everything, it’s not as strong as a guarantee as doing it myself. I still use it because despite the lower quality wash that requires some spot washing, I still come out ahead.
Now this was hypothetical, LLM generated code is damn near useless for my usage, despite assumptions it would do a bit more. But if it did generate code that matched the request with comparable risk of bugs compared to doing it myself, I’d absolutely be using it. I suppose with the caveat that I have to consider the code within my ability to actual diagnose problems too…
Human coder here. First problem: define what is “writing code.” Well over 90% of software engineers I have worked with “write their own code” - but that’s typically less (often far less) than 50% of the value they provide to their organization. They also coordinate their interfaces with other software engineers, capture customer requirements in testable form, and above all else: negotiate system architecture with their colleagues to build large working systems.
So, AI has written 90% of the code I have produced in the past month. I tend to throw away more AI code than the code I used to write by hand, mostly because it’s a low-cost thing to do. I wish I had the luxury of time to throw away code like that in the past and start over. What AI hasn’t done is put together working systems of any value - it makes nice little microservices. If you architect your system as a bunch of cooperating microservices, AI can be a strong contributor on your team. If you expect AI to get any kind of “big picture” and implement it down to the source code level - your “big picture” had better be pretty small - nothing I have ever launched as a commercially viable product has been that small.
Writing code / being a software engineer isn’t like being a bricklayer. Yes, AI is laying 90% of our bricks today, but it’s not showing signs of being capable of designing the buildings, or even evaluating structural integrity of something taller than maybe 2 floors.
