"The" future of software engineering is a silly thing to predict. I might predict one substantial change is that we get our house a little more in order about universities and the private sector distinguishing between computer science, software engineering, and software development. Obviously they are not cleanly separated[1], but LLMs will affect each subfield very differently.
- The impact on computer science seems almost entirely negative so far: mostly the burden of academic wordslop, though an additional negative impact is AI sucking all the air out of the room. What's worse is how little interesting computer science has come out of the biggest technological development with computers in many years: in fact there has been a terrible and very sudden regression of scientific methodology and integrity, people rationalizing unscientific thinking and unprofessional behavior by pointing to economic success. I think it'll take decades to undo the damage, it's ideological.
- The impact on software development actually does seem a bit positive. I am not really a software developer at all. It always felt too frustrating :) However the easing of frustration might be offset by widespread devastation of new FOSS projects. I don't want to put my code online, even though I'm not monetizing it. I'm certainly not alone. That makes me really sad. But I watched ChatGPT copy-paste about 200 lines of F# straight from my own GitHub, without attribution. I'm not letting OpenAI steal my code again.
- Software engineering... it does not seem like any of these systems are actually capable of real software engineering, but we are also being adversely affected by an epidemic of unscientific thinking. Speaking of: I would like to see Mythos autonomously attempt a task as complex and serious as a C compiler. Opus 4.6 totally failed (even if popular coverage didn't portray it as such):
The resulting compiler has nearly reached the limits of Opus’s abilities. I tried (hard!) to fix several of the above limitations but wasn’t fully successful. New features and bugfixes frequently broke existing functionality.
"Future of software engineering" folks should stuff like this in mind. What model is going to undo Mythos's mess? What if that mess is your company's product? Hope you know some very patient humans!
[1] They should have different educational tracks. There is no reason why a big fancy school like MIT can't have computer scientists do something like SICP and software engineers do the applied Python class. Forcing every computer professional into "computer science" is just silly; half the students gripe about how useless this theory is, the other half gripe about how grubby the practice is. What really sucks here is that I think Big Tech would support the idea, we're just stuck in a weird social rut.
I feel like LLMs[1] are going to cause a kind of "divorce" between those who love making software and those who love selling software. It was difficult for these two groups to communicate and coordinate before, and now it is _excruciating_. What little mutual tolerance and slack there was, is practically gone.
Open source was always[2] a fragile arrangement based on the kind of trust that involves looking at things through one's fingers (turning a blind eye may be more idiomatic in English), and we are at the point where you just have to either shut your eyes, or otherwise stop pretending that the situation can be salvaged at all.
Just a thought I had: some people think that LLM-shaming is declasse, and maybe it is, but I think that perhaps we _should_ LLM-shame, until the AI-companies train their LLMs to actually give attribution, if nothing else (I mean if it can memorize entire blocks of code, why can't it memorize where it saw that code? Would this not, potentially, _improve_ the attribution-situation, to levels better than even the pre-LLM era? Oh right, because plagiarism might actually be the product).
[1]: Not blaming the tech itself, but rather the people who choose to use it recklessly, and an industry that is based almost entirely on getting mega-corporations to buy startups that, against the odds, have acquired a decent number of happy-ish customers, that can now be relentlessly locked-in and up-sold to.
To toss them because the level of damage they have done it's astounding. Tons of companies are still fixing the losses from vibe coding.
What we need it's better code analizers, lexers and the like. And LLM's are practically the opposite because they can't never, ever give a concise answer by design. Worse, they rot over time.
> Tons of companies are still fixing the losses from vibe coding.
Well, you have to separate "future of" from "ensuing damage". This is similar to the fishing industry. Fishermen in the past used spears, rods, small nets, nowadays annual national catch statistics are reported in kilotonnes. They are destroying the ocean floor, causing massive extinction of species, causing irreversible damage. Yet, you can't argue looking 100-150 years back that industrial fishing was not "the future of the fishing industry". That is also why programmers won't ever disappear because of AI progress. Just like we still need fishermen, we'd need programmers. The sad truth about this is that soon we truly may have no need for fishermen, because there's no fish left in the ocean.
"The" future of software engineering is a silly thing to predict. I might predict one substantial change is that we get our house a little more in order about universities and the private sector distinguishing between computer science, software engineering, and software development. Obviously they are not cleanly separated[1], but LLMs will affect each subfield very differently.
- The impact on computer science seems almost entirely negative so far: mostly the burden of academic wordslop, though an additional negative impact is AI sucking all the air out of the room. What's worse is how little interesting computer science has come out of the biggest technological development with computers in many years: in fact there has been a terrible and very sudden regression of scientific methodology and integrity, people rationalizing unscientific thinking and unprofessional behavior by pointing to economic success. I think it'll take decades to undo the damage, it's ideological.
- The impact on software development actually does seem a bit positive. I am not really a software developer at all. It always felt too frustrating :) However the easing of frustration might be offset by widespread devastation of new FOSS projects. I don't want to put my code online, even though I'm not monetizing it. I'm certainly not alone. That makes me really sad. But I watched ChatGPT copy-paste about 200 lines of F# straight from my own GitHub, without attribution. I'm not letting OpenAI steal my code again.
- Software engineering... it does not seem like any of these systems are actually capable of real software engineering, but we are also being adversely affected by an epidemic of unscientific thinking. Speaking of: I would like to see Mythos autonomously attempt a task as complex and serious as a C compiler. Opus 4.6 totally failed (even if popular coverage didn't portray it as such):
"Future of software engineering" folks should stuff like this in mind. What model is going to undo Mythos's mess? What if that mess is your company's product? Hope you know some very patient humans!
[1] They should have different educational tracks. There is no reason why a big fancy school like MIT can't have computer scientists do something like SICP and software engineers do the applied Python class. Forcing every computer professional into "computer science" is just silly; half the students gripe about how useless this theory is, the other half gripe about how grubby the practice is. What really sucks here is that I think Big Tech would support the idea, we're just stuck in a weird social rut.
We should start a support group.
I feel like LLMs[1] are going to cause a kind of "divorce" between those who love making software and those who love selling software. It was difficult for these two groups to communicate and coordinate before, and now it is _excruciating_. What little mutual tolerance and slack there was, is practically gone.
Open source was always[2] a fragile arrangement based on the kind of trust that involves looking at things through one's fingers (turning a blind eye may be more idiomatic in English), and we are at the point where you just have to either shut your eyes, or otherwise stop pretending that the situation can be salvaged at all.
Just a thought I had: some people think that LLM-shaming is declasse, and maybe it is, but I think that perhaps we _should_ LLM-shame, until the AI-companies train their LLMs to actually give attribution, if nothing else (I mean if it can memorize entire blocks of code, why can't it memorize where it saw that code? Would this not, potentially, _improve_ the attribution-situation, to levels better than even the pre-LLM era? Oh right, because plagiarism might actually be the product).
[1]: Not blaming the tech itself, but rather the people who choose to use it recklessly, and an industry that is based almost entirely on getting mega-corporations to buy startups that, against the odds, have acquired a decent number of happy-ish customers, that can now be relentlessly locked-in and up-sold to.
[2]: I mentioned a specific example of good old fashioned, pre-LLM, human plagiarism here: https://news.ycombinator.com/item?id=46540608
Is this satire? I can never tell anymore.
To toss them because the level of damage they have done it's astounding. Tons of companies are still fixing the losses from vibe coding.
What we need it's better code analizers, lexers and the like. And LLM's are practically the opposite because they can't never, ever give a concise answer by design. Worse, they rot over time.
https://smsk.dev/2026/04/26/ai-cannot-self-improve-and-math-...
> Tons of companies are still fixing the losses from vibe coding.
Well, you have to separate "future of" from "ensuing damage". This is similar to the fishing industry. Fishermen in the past used spears, rods, small nets, nowadays annual national catch statistics are reported in kilotonnes. They are destroying the ocean floor, causing massive extinction of species, causing irreversible damage. Yet, you can't argue looking 100-150 years back that industrial fishing was not "the future of the fishing industry". That is also why programmers won't ever disappear because of AI progress. Just like we still need fishermen, we'd need programmers. The sad truth about this is that soon we truly may have no need for fishermen, because there's no fish left in the ocean.
No, this is like fishing with dynamite.
1 reply →
That link doesn't support your statement. It's analysis is bad and irrelevant.
Why is the analysis bad? Burden is on you to explain that.
>> the level of damage they have done it's astounding. Tons of companies are still fixing the losses from vibe coding.
This sounds like unsubstantiated hyperbole - can we keep HN grounded in reality, please?
My alternative hypothesis - you don't like agentic coding or maybe LLMs in general. Not helpful for the group.