looking forward to see same title but for developers.
Developers will go extinct because of UML/MDD.
Developers will go extinct because of open source.
Developers will go extinct because of IDEs.
Developers will go extinct because of DevOps.
Developers will go extinct because of no-code tools.
Developers will go extinct because of AI.
Each time someone predicts the death of software engineering the demand for developers just goes up 10x.
Cite numbers, compare them against other numbers, and then come back with an actual position.
Now we as developers know that coding, and in particular, coding of a de novo feature, is only a fraction of our job. Actual typing in of code is estimated to be between 10 and 60% of the software developer’s job [2].
1] https://github.blog/2022-09-07-research-quantifying-github-c...
2] https://www.microsoft.com/en-us/research/uploads/prod/2019/0...
Edit: No direct citations, my own experience, sorry! Interesting to see how many people are throwing up the pitchforks in defense of engineering. Even if you are only getting a 5% increase in productivity via AI assistants, thats ultimately less people you may have to hire.
I like Sam Altman's quote on this. "I think the world is gonna find out that if you can have 10 times as much code at the same price, you can just use even more. So write even more code."
I agree that it will have an impact, but I'm wary to predict something specific, whether negative or positive.
I'm just curious to see numbers from places that I assume somewhat meaningfully measure productivity across a range of "engineering" roles
Yeah sure I'm getting a ~10% productivity boost personally from those tools but it's not like you can give those to non-devs and expect them to replace a developer with it.
Let's not forget that we have code generators usable by non developers since the 90s. It's not like it's a particularly new addition.
> Let's not forget that we have code generators usable by non developers since the 90s. It's not like it's a particularly new addition.
I never said anything about non-developers. If you hire 10 developers and on average the AI assistants give a 10% productivity boost, that potentially means you don't have to hire the 11th developer. I am not suggesting that engineers are gone, only that headcount reduction via AI tooling is already happening.
If I was the CEO of a company making headcount reduction with AI, I would be more worried about my company itself than the job of the ones I'm firing.
I've never been in a company where the roadmap isn't full to the brim, there doesn't seem to be a limiting factor on this side.
I have experimented a bunch with llm, copilot, etc. The current offering is useful in a limited scope. People google a bit less, and they are a bit better than existing IDE snippeting tools. I see potential but what is on the market doesn't give me a 10% improvement.
If you ask an LLM to write you a story it will write you a story. If it want a very specific story you have to write a very detailed prompt. Code generation is also like this. A seasoned developer can write code as fast as they can write a detailed prompt, and a newbie may be able to work faster in unfamiliar technologies but is susceptible to following bad suggestions (e.g. llm will tell you to write your own email validation instead of using the teams preferred library).
The vibe I get is like low code technologies. Initially they look promising and you wonder if you need skilled people anymore but any non trivial problem and you're just coding on diagram form realising text is better.
What are you / that using? I'd really like to try it if it is publicly available.
What I see anecdotally is, now debt costs money a lot of buisness cases for tech investment just don't make sense. Borrowing to buy future growth made a lot of sense when interest rates were negative. Now we have a lot of pressure to deliver profits today.
I will use a flavor of a chat interface (Mistral Chat, ChatGPT, Gemini) when I am trying to figure out something I don't have domain expertise on. For example I have a lot of trouble digesting AWS docs, I often get permissioning wrong or a configuration that is not well outlined to me. I use a chat interface to walk through the problem and more times than not get to a solution a lot quicker than if I had tried to step through all the docs.
I am still doing most of the thinking, I don't find LLMs to be that amazing for engineering solutions. I think it will happen in the future though as they become perhaps more opinionated, especially on software engineering.
That is misleading. Usually what happens for me is I write a line of code, then I wait few seconds and copilot will write the next 5-10 lines. I have in my head what I expect it to write, so I can immediately tell if it is good. It is much less mentally draining as well, it is easy for me to code 12h a day and with higher productivity rates than before. I have done so many side and interesting hobby projects because of that productivity boost.
But overall it hasn't made me code less, it has made me spend more time coding because it is much faster to get the same value.
Same might be for the companies. Projects that weren't worth to do before will now be, because they are cheaper and faster to do.
it would need some human touch but most of the work will be done already
edit: i just had this thought that my dev job has become less coding and more process and tooling over the years. which is why i dont enjoy it. it feels like tedium that should be automated.
Developers whose primary skill and interest is in coding seem to be in complete denial about the future.
Is it fair to say TV broadcasters/production professionals were in danger of losing their jobs in that moment? Kind of, but TV broadcasters/production professionals were also the people in the best position to take advantage of the new advances.
Of course, that was predicated on being open to change and not clinging to the past.
Surely, anyone on HN talking about AI right now is in good shape.
We are inside the bubble. There is a huge % of even young people who have no interest in any of this. It is like 50% of 18-29yo haven't even used chatGPT themselves in the US.
Honestly AI works for writing a small function, and it's definitely superior to Google / SO when searching for code examples.
But in the context of a large app with more exceptions than business rules and where you have to take in to account legacy code & constraints ... I don't see an AI figuring that all out for the simple reason that it's too hard to explain to it the big picture.
Most of those tasks will be heavily changed by AI, but not replaced.
If you honestly think that statistics based AI can replace software engineers, then you either have no software engineering experience, don’t understand how AI works under the hood, or haven’t worked anywhere that does anything more than CRUD api development.
but that probably will take much longer.
That engineer probably can’t even be replaced by AI since every new business is a snowflake once the low hanging fruit is gone.
I don’t think our current form of statistical models will ever be able to generalize and get into specifics at the same time.
AI will change how individual engineers work by being a more proactive search engine, but will not be relied on, by engineers, to write code entirely.
I don't understand how brains work under the hood (does anyone?), but zoom into the brain and you get chemistry, zoom into the chemistry and you get quantum mechanics, and that quantum mechanics is statistical in nature.
I don't know if that truth matters or not, because I don't know which layer of abstraction is the most relevant one for our intelligence. And without knowing that, I don't know if these models we have now can or can't be scaled up to do what we do: if what we are really does depend on some microtubule quantum computation, then no, no classical computer can ever be like us (though it is, still, statistics); on the other hand, if everything we are comes from the strengths of synaptic connections and internal bias of our neurons, then any sufficiently complex model can absolutely do all that we can do, and much faster too.
Come on, really? Are you comparing using your brain to using an LLM.
I didn’t even need to read the rest to know it was all nonsense.
LLMs aren’t magic. If you understand how they work, then you can understand the limitations of the approach. You seem to not.
So, you're pattern matching without using careful logical analysis? Yes, this is a totally convincing demonstration of how humans are not at all like LLMs.
> LLMs aren’t magic.
Are humans?
I really liked the occult when I was a teenager. Despite trying, never found any real magic.
> Are you comparing using your brain to using an LLM.
Do you know where the name "neural network" comes from?
'course, the person I'm replying to probably isn't reading this anyway, given they said they stopped reading too soon the last time. This made me think: https://news.ycombinator.com/item?id=39504270
By that very loose standard, the matter of time is 2 years 6 months 18 days ago — 10th August 2021 was OpenAI's blog post about the Codex model, with a chat interface producing functional JavaScript: https://openai.com/blog/openai-codex
Right now, what I see coming out of these tools (and what I see in the jobs market) gives me the vibes these tools are very much at the level of "why do we need to hire interns and possibly also junior developers anyway?", but mid and senior levels are still better at seeing bigger pictures and subtle issues that both juniors and LLMs have a harder time with… and, indeed, standard new programmer questions like "why doesn't my code compile?".