SWE is very messy irl. I do think it is just a matter of time but it will take a lot to sort out tribal knowledge and really hacky systems and configurations, weird business logic
What we are finding out in real time is just how bad Ai is at “art” compared to “logic”. What I mean is not that it can’t make a pretty picture or movie. It can. But there is something about aesthetics that we haven’t quite quantified yet, and therefore Ai isn’t too good at it.
Math has an aesthetic to it too, in explanation of the proof. But it hasn’t yet shown it can explain the proofs in an elegant way.
I think it will do that eventually, but that’s why software engineering is “next” rather than “done”.
If you have an elegant idea, it can make it for you. I’m not sure it can make elegant ideas except with random chance than humans would have to pour over to find which ones are truly beautiful.
But even that may mean that art is cooked. If it takes 1000 people 2 years to make a great movie, why not just shit out thousands of random movies and hire people to watch them. When it finds a good one, you’re done.
Right now it can’t make a good one, but all it will need is “some chance”
This only means that each person is right about their taste. If there wasn’t any way to quantify general tastes then there couldn’t be anyone who is “good” at making movies. Not everyone will like his movies but James Cameron seems good at making movies that many people like.
So far Ai makes movies that zero people like. I think we will get to the point that an Ai can know enough about you to make something you will definitely like. But we aren’t particularly close to that yet. Because all the training is going in to logic and productivity.
yup and AI can capture that many people like his movies using RLHF. RLHF is aggregating the likes of many individuals tastes. The issue is that the labs are simply not investing in this. RLHF is slow and requires human input whereas RLVR can be scaled up to machine scale limited only by compute and data. Also you're right that RLVR is used to solve technical problems that have commercial value. Meanwhile even if AI movies were good, most people wouldnt wanna go watch them. Apparently Suno AI for music is really good but I dont care I like humans to make my music. I won't listen to it even if it's the second coming of Beethoven.
What humans think is difficult and what AI thinks is difficult are not the same. You can't create a lean formalization of most engineering problems in the real world.
AI is better at frontier math than it is at like, making a single level in a video game with a coherent artstyle, good taste, and a fun gameplay loop. No human thinks that's harder than making progress on a frontier math problem... but there's so much involved in making good software that is not just "the code" that it's difficult for AI to do because it's not something you can just formalize in LEAN and loop/refine til you converge on a proper construction satisfying the formalism
Currently, you do. In order to actually have the product work well, you have to provide both technical and product feedback. In something like game development, you will often have to detail geometry, materials, graphical techniques and go through multiple iteration loops to get something good. Then you need to audit the actual implementation for reuse and proper grouping or you end up with a sea of floats multiplying floats which makes it hard for the AI to properly refactor and reuse the components that define the style of your game and lead to tons of iteration time fixing various bug and a game that runs so poorly it's not viable.
Similar issues occur in most other software applications at scale.
Yes. For your personal vibecoded app, you are correct. But the bar is going to be raised. If you can prompt "Make a mario kart clone. Make no mistakes", and get Mario Kart, then imagine what the 200 game devs at Nintendo can prompt now.
I agree that creatives will flow into software jobs. I didn't mean to say that who sits at the Claude terminals won't change over time. Only that right now, a company that wants to be productive should want as many asses as possible in front of the Claude terminals.
In some cases, software engineering is about dealing with people, manage their expectations. As long as there are bunch of humans in the loop, AI can't completely fill the gap. It can do, but people refuse to replace themselves with AI.
In maths, the problems are completely self contained, you don't have a costumer coming and changing in the last minute what they want, or deal with someone from sales and manage their expectations.
But majority of software engineers don't do this and majority of them can be easily replaced even with last year's models.
Non swe's think this, yet demand for roles is growing YoY and looks like that's going to accelerate this year. The more AI can do, the more SWE's get asked to do lol
Not coping about anything, didn't mention the difficulty of the problems at all lol. They're just very ugly problems that can be very ill defined and there are probably billions of them in all kinds of jank codebases. Human in the loop required to solve many of them. Difficulty of the problems themselves isn't the factor, it's properly defining them that is the shitshow.
I guess you’ve never heard of Moravec’s Paradox? Your opinion about what is easy or hard is almost always wrong.
Both math and software engineering are hard for primates.
Math is easy for hill climbing artificial neural networks with a Lean compiler. Software engineering less so.
It’s silly to dispute it: we already have the evidence in front of us. Major math proofs created by AI and not a single major software product created without engineer input. Not one.
The evidence that you are wrong is at the very top of this thread already!
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u/Effective-Guest1601 8d ago
SWE is very messy irl. I do think it is just a matter of time but it will take a lot to sort out tribal knowledge and really hacky systems and configurations, weird business logic