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The risk of AI isn't making us lazy, but making "lazy" look productive

news.ycombinator.com

11–20 of 104 posts

Re: The risk of AI isn't making us lazy, but making "lazy" look productive

#11
I have some algorithms I absolutely must know. So I’m hand coding them and asking the agent to critique me.

I do a very similar thing in writing - I need feedback, don’t rewrite this!

In both cases I need the struggle of editing / failing to arrive at a deeper understanding.

The future dev will need to know when to hand code vs when to not waste your time. And the advantage will still go to the person willing to experience struggle to understand what they need to.

Re: The risk of AI isn't making us lazy, but making "lazy" look productive

#12
post #9

I find value in learning some things deeply but not all things. The ability to be more selective about where I attend deeply, while leveraging fast shallow learning to complete other tasks... That seems like a potential benefit and a nice choice to have in the toolbox.

trick is maintaining enough domain expertise... so we can actually audit those shallow outputs.

If the baseline knowledge drops too low we cannot tell when the AI is being lazy or wrong

Re: The risk of AI isn't making us lazy, but making "lazy" look productive

#13

So what is important is not that 10 or 20 times the work can be done, but that you are stressed out and exhausted while doing your work?

I burn through $5,000 a month in API tokens. I am the last person to romanticize manual toil.

The issue is the difference between using AI for shallow outsourcing ('summarize this') and deep cognitive work ('stress-test this architecture'). AI should be a cognitive amplifier for much harder problems, not a shortcut to bypass critical thinking entirely.

Re: The risk of AI isn't making us lazy, but making "lazy" look productive

#14
post #5

I'm convinced that at some point looking like being productive and being productive becomes the same thing.

There's a point where they meet, but "faking it until you make it" doesn't work for productivity in the same way it doesn't work for getting rich.

But there's a secret: just buy my $399 masterclass and I'll teach you 17 simple productivity hacks to 100x your income.

Re: The risk of AI isn't making us lazy, but making "lazy" look productive

#15
post #7

I have a nearly total opposite take. I can't tell you how many times I've read a book, a paper or something else and been confused by some ambiguity in the author's prose. Being able to drop the paper (or even the book!) into an LLM to dig into the precise meaning has been an unbelievable boost for me. Now I can actually get beyond conceptual misunderstanding or even ignorance and get to practice, which is how skills…

We actually don't disagree at all—you are perfectly illustrating my point.

Applying strict epistemic discipline (Popper, Russell) to resolve ambiguity and accelerate actual practice is the very definition of deep work. You aren't using AI as a shortcut to skip thinking; you're using it as a Socratic sparring partner to deepen it. This is exactly the paradigm shift I'm advocating for.

Re: The risk of AI isn't making us lazy, but making "lazy" look productive

#16

I don't think it's all that bad. There's definitely vibe coding that is "copy paste / throw away" programming on ultra steroids. But after vibe coding two products and then finding them essentially impossible to then actually get to a quality bar I considered ready to launch, I've been working on a more measured approach that leverages AI but in a way that simply speeds up traditional programming. I use it to save to…

Pure 'vibe coding' is essentially technical 'tittytainment'. Using AI for the horizontal spread while you enforce vertical architectural depth is true deep work.

Re: The risk of AI isn't making us lazy, but making "lazy" look productive

#17
Agreed. LLMs have helped me achieve much deeper reading, _when directed to do so_. Asking an LLM to “Teach me Socratically about this paper/code. One question at a time”, usually allows me to get a much deeper reading of the material than I would otherwise.

Re: The risk of AI isn't making us lazy, but making "lazy" look productive

#18
This was the issue with some the ads Apple was running when launching the iPhone 16. It showed the worst worker using Apple Intelligence to impress the boss and get promotions, which being generally lazy and terrible. I felt it was the wrong message to send. [0]

I don’t think AI is all bad for summaries though. I used to add stuff to a reading list with good intentions, but things went there to die. Hundreds of articles added, but with so much new content each day, I would never actually read any of it. Now, I use AI summaries to get more context on what the article is. If it sounds interesting and I want more info, I can read the whole thing in the moment. If I’m satisfied with the summary alone, I can move on with my life. No more pushing it off to a reading list that only generates guilt. I actually end up reading more articles due to this, not less.

[0] https://youtu.be/YP-ukrBVDH8 (this is sadly the best copy I can find)

Re: The risk of AI isn't making us lazy, but making "lazy" look productive

#19
That's a different take than I've been considering AI to be genuinely useful. I try to not use it for deep work, infact I try to use it minimally but frequently for short checks on my own understanding.

Using your research paper reading example, I would read the research paper, but then ask an AI tool specific questions about the work, frequently in new chats. Then at the end I might ask it to implement my description of the paper. I guess it's your 'debate with me' conclusion, the only difference is I would try to have multiple short conversations.

Re: The risk of AI isn't making us lazy, but making "lazy" look productive

#20
post #9

I find value in learning some things deeply but not all things. The ability to be more selective about where I attend deeply, while leveraging fast shallow learning to complete other tasks... That seems like a potential benefit and a nice choice to have in the toolbox.

trick is maintaining enough domain expertise... so we can actually audit those shallow outputs. If the baseline knowledge drops too low we cannot tell when the AI is being lazy or wrong

Spot on. The ultimate bottleneck is no longer generation; it's verification.

If you don't intrinsically know what 'right' looks like, AI simply helps you build the wrong thing faster. This internal compass is exactly what I meant by 'taste' in the original post.

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