but the solution, ironically, is not learning more about ai, but learning more about good software engineering, so you can tell when the ai is not doing it
No, software engineering is fundamentally changed because of AI. No amount of digging our heads in the sand is going to undo that.
For example, the traditional best practice cycle of "small incremental change, code review, test, commit" is pretty much obsolete now. The way ten collaborating agents can make short work of a complex project is not something that fits in with our existing software engineering wisdom at all.
We are still trying to figure out the new science of software engineering. And the best way to get better now is to just figure out what works and what does not for your use case.
I'm not talking about the transient aspects of producing software; I'm happy to accept that AI will change that, but also I feel that it will change it in ways that really aren't very hard to learn, and truth be told the more time that passes the smaller the gap will get as the agents get more capable.
what I am talking about is principles that govern what good software looks like, what properties it has to satisfy in order to be extensible and maintainable and performant and all that other good stuff, and the AIs are not going to make that knowledge obsolete any time soon.
I think this will change quite a bit too. Code being readable is one of our core tenets. Functions fitting within, approximately, a screen of code used to be ideal.
Modern AI as already past solving that problem. You can give it a million line codebase, ask where something specific is happening, and it'll tell you in less than a minute.
If we can de-emphasize readability, what do we gain?
Custom hand rolled containers and data structures for your use cases are somewhat frowned upon unless really needed. Well, probably not anymore.
What about a manually inlined mega-function with loops unrolled that pre-empts some of the compiler's work? No way that would fly a couple of years ago. Already seeing this in performance sensitive code.
> reducing the skill required to operate AI agents
For accomplishing the same task, yes.
But given these tools straight out of science fiction, why on earth would you be stuck doing the same things? There's no point spending human thought over something an agent has just automated yesterday.
Think bigger, take on more ambitious projects that are perpetually at the limits of what you and AI can accomplish.
>No, software engineering is fundamentally changed because of AI. No amount of digging our heads in the sand is going to undo that.
Yet anyone who claims that fails to procure sufficient evidence or instruction on how exactly training the to-be software engineer in the age of AI should be. Until that happens, people still learn DSA, write code manually, and train their problem solving skills with programming exercises.
And I mean handwriting them, not ordering "one solution for Leetcode 1133 in Rust, please" so we can proclaim that we're writing Rust so fast that I don't have to read a book about it anymore.
> fails to procure sufficient evidence or instruction on how exactly training the to-be software engineer in the age of AI should be.
Of course there's no instruction on how to succeed in a rapidly changing new field.
Do you think someone is more likely to succeed by getting their hands dirty and trying things out or waiting around for 'instruction' to be available?
> people still learn DSA, write code manually, and train their problem solving skills with programming exercises.
Maybe you're confusing computer science with software engineering? I agree that you'd still need to learn about algorithms, just like calculators do not reduce the need of learning algebra and trigonometry.
Yeah I'm hoping AI can bring us back to software engineering of 20 years ago. Where studying the solution to a problem, finding clever solutions, getting everything to work without getting buried in little concerns is really important and "best practices" can just be a line in agents.md and the uninteresting part can just be handed off.
this reminds me of a debate about science education - somewhere in elementary school we had to study various proofs that the world was round, mostly with historical context. some people now argue that we don't need this to be part of the curriculum any more - the answer is "we have gone to space and seen it, here are the photos!"
one of the best things about it is not the proof per se, but the fact that mathematicians continue to work on the theorem. bodes well for interesting mathematical research not being killed by AI proofs.
I have found that claude (opus 4.8 and 5) can do a very good job of implementing good architecture and system design if I can just steer it right. left to its own devices it does produce less than optimal code, but if I just spend a few minutes explaining how some pattern will improve the code, claude will go do it the right way, and can even have a pretty sensible discussion about the tradeoffs involved. so it does know about good code architecture and patterns, it just doesn't have the taste and initiative to use them without being told.
And the next time your agent comes across the same problem, it will likely use the same previous inefficient way again (despite all attempts to codify the instruction in AGENTS.md, CLAUDE.md, skills, whatever)
there was an interesting retcon of that story in one of niven's later works, where it was pointed out that any spacefaring race would know instantly what killed him. it was just better PR to pretend that it was a huge mystery, and that their hull wasn't vulnerable to some stupidly obvious danger but rather to something no one could have foreseen.
not to take away from the author's appreciation of newly accessible formal proofs, but people have been talking about the savings in formalization effort for longer than they have been talking about the AI doing the actual proofs!
I once read a (possibly apocryphal) description of a swiss sign saying in english "please don't pick the flowers", in french "those who love nature leave the flowers alone", and in german "picking the flowers is forbidden"
reading that shopify supports users designing their own custom shopfronts really helped put the acquisition into context. makes a lot of sense to bet on tailwind for that.
reply