We’re about to learn a painful lesson about delayed gratification in software engineering.
New data from China, 26,811 students tracked January 2023 through June 2025. Students using AI for homework saw their scores jump 20 percent. Completion time dropped nearly half. They aced the assignments.
Then exam season came. Those same students scored 20 to 40 percent worse when they couldn’t use the tool.
The homework phase is over. The exam phase is coming.
We’re doing this in software right now. Vibe coding feels incredible. Features ship fast. Nobody’s asking what happens in Month 18 when the original dev has left and nobody understands the codebase.
Commercial pilots fly with autopilot for most of every flight. They’re required to maintain manual flying proficiency regardless. If the system fails mid-air and the pilot can’t take over, people die.
Most teams using AI right now have forgotten how to fly manually. They’ve become passengers in their own systems. The autopilot flies, nobody checks instruments, and the first sign of trouble will be a breach notice or outage.
Three rules:
- Command the mission. Define architecture before prompting. Ambiguity kills in code and in flight. Delegate selectively. Offload mechanical work. Keep design and security reviews human. Verify everything. Audit before production.
- Never trust the automation without checking instruments.
- Quick wins feel good. Sustainable engineering feels boring. Boring keeps systems standing.
Organisations surviving the next two years won’t ship the fastest. They’ll be the ones who remember how to fly without the aids.
people insisting that you actually be skilled, independently of your tools, doesn’t make them Luddites. Rather, being unable to do so makes you a phony.
The luddites had a point.
They weren’t opposed to technology, but the use of technology to remove skilled labor to produce inferior products.
Also, the pilot/autopilot argument is, kinda not applicable. The pilots aren’t just fucking around- autopilot systems only manage some aspects of flying, the pilots are still fully engaged.
The pilots absolutely can just fuck around for most of the flight, and even during the critical moments of takeoff and landing, the plane can do a lot of it automatically these days.
Pilots need to actively practice flying without autopilot to keep those skills up in case the autopilot fails.
the plane can do a lot of it automatically these days.
It can but nobody is out there flying CAT IIIc autoland approaches because its ‘easier’.
the luddites had a point… in the moment… kinda… but i think have largely been pretty conclusively proven wrong… clothing is now plentiful, and i doubt anyone would want to go back to paying taylors to make all their clothes for 10x more, even if the clothing would be much higher quality, which i even doubt: clothing quality doesn’t come down to artisan skill any more, it comes down to choices you make, and an artisan can still make cost cutting decisions on fabric, construction, etc
Maybe. I think a sizable group of people would rather put fast fashion back in the bag.
It’s funny watching this type of bellyaching play out like a loop over history.
People went through this EXACT same bellyaching when compilers first started showing up. The machine coders considered themselves superior and their skills indispensable. Now those people are extinct and modern people consider their compiler skills to be elite, not realizing they’re using the baby mode that people railed against in the past.
I have a hard time telling AI authored LinkedIn thought leadership apart from formulaic LinkedIn thought leadership sometimes, but this feels AI written, which makes it fairly amusing considering the point it’s making.
(Does vibe coding feel incredible? Also, “Nobody’s asking what happens in Month 18 when the original dev has left and nobody understands the codebase” implies that the vibe coder original dev understood the codebase at any point, which isn’t an argument I’d feel comfortable making for any of the ones I’ve worked with)
That’s what they’re doing for my SO’s big introductory class in the humanities. No homework, quizzes, or papers. Short answer exams done in a special testing center.
Really sucks for people who were decent at essays and turning in assignments on time but not great at exams.
yeah, but it’s great for those that hated busywork and were good at exams
I’m the “good at exams” type, I find paper writing (or novel writing… 😢) unpleasantly tedious. If we lose the “good at structuring complex thoughts in a way that can be coherently decoded by other humans” types, the “good at exams” types will suffer. We need people who can write good papers and people who can recall diverse facts and arrange them into simple shapes quickly.
Yeah I would have done much better in high school like this, though I don’t think AI will eliminate the poster projects unfortunately.
same, it almost makes me want to go back to uni
The vilification of the Luddites as cantankerous tech haters is a really good example of how malicious falsehoods can succeed, I think. I’d guess that most English speakers who know the word would define Luddite as “someone who hates technology”, and I think it resonates on some level because we all hate technology some of the time. The fact that Luddites didn’t indiscriminately hate technology, they just destroyed the means by which their oppressors oppressed them, is handily swept aside. And I never even questioned that narrative on Luddites until I happened to read up on them.
It’s sneaky, because before then “Luddite” didn’t feel like an important or politically charged term at all. It was simply a slang word for people who grump about technology. Calling people haters just short-circuits any examination of the so-called haters’ reasons. It’s exactly what people say about terrorists, except instead of technology its freedom. They just hate freedom. I wonder how many people have “terrorist = freedom hater” embedded so deeply they don’t even think about it.
they were absolutely not right… the modern world of plentiful clothing simply wouldn’t be possible without industrial clothing machinery (and i’m not talking about fast fashion and waste - though industrial clothing also makes those things possible, i think that’s an outcome of the plenty rather than an inevitable outcome of industrialised clothing)
artisans don’t magically make better clothing… in fact, modern machinery can and does produce much higher quality, complex clothing than a human alone would, and in much higher volumes
they had a moment when they had a point, when the machinery just wasn’t very good (and of course the child labour concerns)
clothing quality on the modern era comes down to choices far far more than the skill of the person making the clothing… artisans are still able to make cost cutting decisions
the point we should take away from the luddites is more about retraining than about their core point… this applies to coal miners and the green transition, and will at some point in the future apply to the logistics industry when driverless trucks become reliable: we can’t just toss an entire industry out of work and expect them to be okay with it (or for that matter expect the economy to absorb them)… but it’s a much better world when fewer people are required to achieve the same output
Nobody’s asking what happens in Month 18 when the original dev has left and nobody understands the codebase.
Throughout my career, I’ve often had to sync a git repository for some random project that I’ve never worked with before and then had to muddle through whatever was in there hoping that the documentation was vaguely complete and accurate.
Nowadays it’s actually much easier. If the documentation isn’t complete or accurate I just turn my coding agent loose on it and tell it to write the documentation.
I get the impression that the guy writing this hasn’t actually used modern coding agents, this is not a problem.
I see coding AI as being similar to a compiler. Before compilers came along programmers had to work in assembly language. Nowadays very few programmers ever do anything in assembly and that’s perfectly fine.
I’m no dev, but did do my HND in computing some 25 years ago. I have also tinkered with scripts to solve an itch and have has plenty of VBA and of late DAX and power query.
I did a project for myself around a year ago that was much larger than I normally would these days and I used Gemini. It was a constant battle with the LLM (man it’s hard not to gender and personify these LLMs) to keep it on track and not keep breaking shit all the time. It struggled to writ valid rules for it’s own firebase/firestore. It generally felt like a bad time.
This past week end I got codex to migrate the PWA from google’s services and database into a selfhostable docker stack. It was a pleasure, it documented the whole process map, built a full test environment, followed through and imported my data. It the suggested a few improvements. It even rewrote a a complex equation that Gemini could nust not get correct and added manufacture safe/max bounds.
all this to say ‘yes, modern agents do seem to do a good job of a codebase that they have never seen’
Yeah, I’ve been tinkering with coding agents for a while now and it feels like some sort of “phase transition” happened earlier this year - the models and their harnesses went from being the sort of clumsy barely-passable student coders that people make fun of to being actually highly competent. Lately even the small local models have reached that level - I’ve been using Qwen3.8 27B on my own machine and it’s been doing just fine. I suspect a lot of the folks making fun of them tried them early on and wrote them off, not giving the latest versions a second chance.
The compiler comparison works there too, IMO. I remember back when I was learning the tricks of the trade there were all sorts of ways you were supposed to write code to trick compilers into generating more efficient results. Coding standards would say to use ++i instead of i++ for incrementing loop indices, use x*0.1 instead of x/10 because division was way more expensive than multiplication, using memcpy instead of copying values with =, using int instead of bool, and so forth. Lots of stuff. Some of it was never useful, it was just folklore and superstition. Other stuff did make a difference with early compilers but modern ones know these tricks themselves and can often apply them better than the human programmer can. So the old-school greybeards who still insist on doing that stuff can actually make things worse these days (disclaimer: my beard is pretty grey these days too).
I expect so too will this “hah, vibe slop” attitude eventually pass away. AI is getting quite good quite quickly.
i’d say it’s not quite like a compiler because you still need to know what the code does… a compiler you largely don’t care, and it’s deterministic… an LLM hallucinates, so you can’t just trust it, which means you have to be able to assess when it’s doing the wrong thing
i agree that setting an agent going helping you learn a codebase is reasonable, largely because it can quickly point out connections in the code quicker than you can understand the architecture, and its guesses are usually just as good as your guesses until you get knowledgeable with the codebase
however, and that’s a very load-bearing however, i don’t think you should just jump into a codebase and just go ahead and tell the LLM to write new code without understanding what it’s done… the understanding is exactly what this graph is trying to show: actually learning is critical, so your review of the code becomes doubly important: you’re gaining institutional knowledge, and you’re making sure the output isn’t slop
