> Also, when did we stop liking to learn?

I suspect it happened when we achieved a level of such constant stimulation (there is a pocket computer always on us with infinite effortless distraction) that we’re never bored and never engage the default mode network.

https://en.wikipedia.org/wiki/Default_mode_network

https://www.youtube.com/watch?v=orQKfIXMiA8

When you’re bored, your mind goes to places it wouldn’t otherwise go. Curiosity kicks in. Curiosity is a precursor to learning. Learning engages the brain and is fun. But it’s not fun all the time, some of it is challenging and frustrating (which is good, that’s the process that teaches you).

When you have the digital equivalent to infinite candy and the brain equivalent to a sweet tooth, it’s hard to resist the siren’s call. The consequence is the brain equivalent to a stomachache—depression and loss of meaning—but unfortunately it doesn’t hit you the same way so you don’t make the immediate connection to make yourself stop. When you think about it, it’s ridiculous from several angles: the candy is infinite, it’s never going to run out, so you don’t need to gorge! But then we justify ourselves as only a true addict would, that while the candy is infinite, the flavours are limited editions and always rotating, and what if I miss that really good one everyone is on?! Then you miss it, is the answer. No one will be talking about it in fifteen minutes anyway.

I agree with you on everything you said here except:

> when you know how the thing works and have that mental context, you will always be faster than an AI

That's just plain false, honestly. No one can type at the speed AI can code, even factoring in the time you need to spend to properly write out the spec & design rules the AI needs to follow when implementing your app/feature/whatever. And that gap will only increase as LLMs get more intelligent.

AI is just revealing the two types of people in this line of work. Those who don’t actually like software and just do it because it’s lucrative, and the actual nerds who care.

>Also, when did we stop liking to learn? Why is it a bad thing to know all the ins and outs of a programming language?

I do not know the inns and out of the assembly layer my high level code end up as. It's not because I don't like to learn, it's because I genuinely don't need to. At a certain level of AI performance, how will this be any different?

Fundamentally you need to start with "what am I trying to do?" and "given that goal, where is my time best spent?".

I made a checklist for my kids to stamp off items after they get back from school (sort bag, get changed, etc). I had two goals, 1) I was trying to solve a problem at home and would have pip installed a library that just straight up did this already and 2) I wanted to check out what the claude website outputs was like at the time. My time was best spent poking at claude a bit but mostly playing with my kids - so vibe coding it was.

Client test speedup issues, I'm trying to speed up tests for them and spend as little time as possible doing so. Vibe coded some analysis and visualisation tools, mostly AI but with some review guided multiple prototypes for timing and let it just fix whatever. More dedicated review for the actual solutions.

Learning a new thing - goal is to learn that thing. AI there is good for doing a lot of the work around that. Maybe I'm focussing on, say, Z3. AI there can help with debugging, finding docs, setting up an environment and leave me to do the central part.

I have been building an iOS app that I had kicking around in my head for years but never had time to build. I have been a frontend UX engineer for the better part of a decade and went through a handful of tutorials on Swift. The project definitely sits in this uncanny valley for me. I have test suites for every aspect of the app and have the agent using TDD to avoid cheating - this has gotten me pretty far without having to look too close at the output other than general structure. As I'm reaching a more mature stage of the project though, I'm finding that I want to tweak a lot by hand in the code to get the details right without burning tokens.

Let’s see if someone can point me towards some resources over the following.

The problem is mixing vibe-coding and agentic-eng, and switching the brain in 2 different modes (fast-feedback gratification vs deep-focus gratification).

There’s no clear cut rule on what works. Different people, different brains, and especially amongst devs some optimized low-key neurodivergence.

And then there’s waiting mode, those N seconds/minutes that agents take to think and write.

What’s the right mix? Keep a main focused project and … what do you do in the meantime? Vibe code something else? Hn? Social media? Draw lines on a paper sheet? Wood carving? Exercise? Rewatch some old tv series?

I have experimented….

There are side activities that help you go back to the task at hand in the correct mental framework for it. Not just for productivity, but for efficiency and enhancing critical thinking on the main task. Or whatever you choose to optimize for. Can anyone point me towards some people talking about this?

100% aggred, i learn coding by building stuff and breaking it when you let ai do everything you skip that pain and also skip the understanding.

> Why is it a bad thing to know all the ins and outs of a programming language? To write and make all the decisions yourself? That shit is fun.

It's not just fun (i agree it is), but it is also essential for creation.

What we have done with the 'AI' is to create a lot of ignorant morons who think they can create a lot of things without knowledge. This is not gonna end well.

When I started spending 40-60 hours a week programming and wanted to spend my remaining time doing other things.

Some people actually don't really like to learn new things. If the machine spits out plausible working code, they'd be perfectly happy with that. Personally I think AI is doing a lot more harm than good and I can't wait for the bubble to burst.

Agree except for this part

> If you're at work and they really care about getting something out of the door, do whatever you think is best.

If you don’t mind being jobless, sure do whatever you think is best. Not all of us can simply switch companies easily. Folks need to realise that AI in a company setting works for the benefit of the company, not for the individual.

Except those are the same people that will decide who is getting hired, and who gets layoff because of increasing productivity.

And no, this isn't playing what ifs.

I have seen it happening with offshoring, migration to cloud, serverless, SaaS and iPaaS products, and now AI powered automations via agents.

Less devops people, less backend devs , no translation team, no asset creation team,...

I have been layoff a few times, having to do competence transfer to offshoring teams, the quality of the output is something c suites don't care all.

Do you wanna bet what is behind Microslop, Apple Tahoe bugs and so forth?

thanks for this take, articulates what i've been feeling towards "AI" without my angst

100% agree!

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