My biggest worry about AI is that it will do all the basic stuff, so people will never have a chance to learn and move on to the more complex stuff. I think there's a name for this, but I can't find it right now. In the hands of a tenured expert though, AI should be a big step up.
Similar to the pre-COVID coding bootcamps and crash-courses we’ll likely just end up with an even larger cohort of junior engineers who have a hard time growing their career because of the expectations they were given. This is a shame but still, if such a person has the wherewithal to learn, the resources to do so are more abundant and accessible than they’ve ever been. Even the LLM can be used to explain instead of answer.
LinkedIn is awash with posts about being a ‘product engineer’ and ‘vibe coding’ and building a $10m startup over a weekend with Claude 3.5 and a second trimester foetus as a cofounder, and the likely end result there is simply just another collection of startups whose founding team struggles to execute beyond that initial AI prototyping stage. They’ll mistake their prompting for actual experience not realising just how many assumptions the LLM will make on their behalf.
Won’t be long before we see the AI startup equivalent of a rug-pull there.
Played a game called Beyond a Steel Sky (sequel to the older beneath a steel sky).
In the starting section there was an "engineer" going around fixing stuff. He just pointed his AI tool at the thing, and followed the instructions, while not knowing what he's doing at any point. That's what I see happening
I just did that with Cursor/Claude where I asked it to port a major project.
No code just prompts. Right now after a week it has 4500 compilation errors with every single file having issues requiring me to now go back and actually understand what its gone and done. Debatable whether it has saved time or not.
I did the same, porting a huge python script that had grown way too unwieldy to Swift. It undoubtedly saved me time.
Your project sounds a lot bigger than mine, 4500 is a lot of compilation errors. If it’s not already split into modules, could be a good time to do it piece by piece. Port one little library at a time.
I think it goes the same way as compilers so bits -> assembly -> c -> jvm and now you don't need mostly care what happens at lower levels because stuff works. With AI we are now basically the bits -> assembly phase so you need to care a lot about what is happening at a lower level.
To be honest you don't need to know the lower level things. It's just removing the need to remember the occasional boilerplate.
If I need to parse a file I can just chuck it a couple lines, ask it to do it with a recommended library and get the output in 15 minutes total assuming I don't have a library in mind and have to find one I like.
Of course verification is still needed but I'd need to verify it even if I wrote it myself anyway, same for optimization. I'd even argue it's better since it's someone else's code so I'm more judgemental.
The issue comes when you start trying to do complex stuff with LLMs since you then tend to halfass the analysis part and get led down the development path the LLM chose, get a mish mash of the AIs codestyle and yours from the constant fixes and it becomes a mess. You can get things implemented quickly like that, which is cool, but it feels like it inevitably becomes spaghetti code and sometimes you can't even rewrite it easily since it used something that works but you don't entirely understand.
Do you worry about calculators preventing people to master big number multiplication? That's an interesting question actually. When I was a kid, calculators were not as widespread and I could easily multiply 4-digit numbers in my brain. Nowadays I'd be happy to multiply 2-digit numbers without mistakes. But I carry my smartphone with me, so there's just no need to do so...
So while learning basic stuff is definitely necessary just like it's necessary to have understanding how to multiply or divide numbers of any size (kids learn that nowadays, right?), actually mastering those skills may be wasted time?
> actually mastering those skills may be wasted time?
this question is, i’m pretty sure it is safe to assume, the absolute bane of every maths teacher’s existence.
if i don’t learn and master the fundamentals, i cannot learn and master more advanced concepts.
which means no fluid dynamics for me when i get to university because “what’s the point of learning algebra, i’m never gonna use it in real life” (i mean, i flunked fluid dynamics but it was because i was out drinking all the time).
i still remember how to calculate compound interest. do i need to know how to calculate compound interest today? no. did i need to learn and master it as an application of accumulation functions? absolutely.
just because i don’t need to apply something i learned to master before doesn’t mean i didn’t need to learn and master it in order to learn and master something else later.
mastery is a cumulative process in my experience. skipping out on it with early stuff makes it much harder to master later stuff.
> Do you worry about calculators preventing people to master big number multiplication?
Honestly, I think we already see that in wider society, where mental arithmetic has more or less disappeared. This is in general fine ofc, but it makes it much harder to check the output of a machine if you can't do approximate calculations in your head.
