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I miss thinking hard

jernesto.com

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Re: I miss thinking hard

#231

Post by BoostandEthanol »

I’d been feeling this until quite literally yesterday, where I sort of just forced myself to not touch an AI and grappled with the problem for hours. Got myself all mixed up with trig and angles until I got a headache and decided to back off a lot of the complexity. I doubt I got everything right, I’m sure I could’ve had a solution with near identical outputs using an AI in a fraction of the time.

But I feel better for not taking the efficient way. Having to be the one to make a decision at every step of the way, choosing the constraints and where I cut my losses on accuracy, I think has taught me more about the subject than even reading literature would’ve directly stated.

Re: I miss thinking hard

#232

Post by roadbuster »

w4yai wrote: post #132
beebmam wrote: post #85

Earlier quoted context omitted.

Comments like these are why I don't browse HN nearly ever anymore

Nothing new. Whenever a new layer of abstraction is added, people say it's worse and will never be as good as the old way. Though it's a totally biased opinion, we just have issues with giving up things we like as human being.

> Whenever a new layer of abstraction is added

LLMs aren't a "layer of abstraction."

99% of people writing in assembly don't have to drop down into manual cobbling of machine code. People who write in C rarely drop into assembly. Java developers typically treat the JVM as "the computer." In the OSI network stack, developers writing at level 7 (application layer) almost never drop to level 5 (session layer), and virtually no one even bothers to understand the magic at layers 1 & 2. These all represent successful, effective abstractions for developers.

In contrast, unless you believe 99% of "software development" is about to be replaced with "vibe coding", it's off the mark to describe LLMs as a new layer of abstraction.

Re: I miss thinking hard

#234

Post by hnlmorg »

oceanplexian wrote: post #186
gyomu wrote: post #32

This March 2025 post from Aral Balkan stuck with me: https://mastodon.ar.al/@aral/114160190826192080 "Coding is like taking a lump of clay and slowly working it into the thing you want it to become. It is this process, and your intimacy with the medium and the materials you’re shaping, that teaches you about what you’re making – its qualities, tolerances, and limits – even as you make it. You know the least about wha…

Coding is not at all like working a lump of clay unless you’re still writing assembly. You’re taking a bunch of pre-built abstractions written by other people on top of what the computer is actually doing and plugging them together like LEGOs. The artificial syntax that you use to move the bricks around is the thing you call coding. The human element of discovery is still there if a robot stacks the bricks based on a…

You’re both right. It just depends on the problems you’re solving and the languages you use.

I find languages like JavaScript promote the idea that of “Lego programming” because you’re encouraged to use a module for everything.

But when you start exploring ideas that haven’t been thoroughly explored already, and particularly in systems languages which are less zealous about DRY (don’t repeat yourself) methodologies, the you can feel a lot more like a sculptor.

Likewise if you’re building frameworks rather than reusing them.

So it really depends on the problems you’re solving.

For general day-to-day coding for your average 9-to-5 software engineering job, I can definitely relate to why people might think coding is basically “LEGO engineering”.

Re: I miss thinking hard

#235

Post by practal »

I see the current generation of AI very much as a thing in between. Opus 4.5 can think and code quite well, but it cannot do these "jumps of insight" yet. It also struggles with straightforward, but technically intricate things, where you have to max out your understanding of the problem.

Just a few days ago, I let it do something that I thought was straightforward, but it kept inserting bugs, and after a few hours of interaction it said itself it was running in circles. It took me a day to figure out what the problem was: an invariant I had given it was actually too strong, and needed to be weakened for a special case. If I had done all of it myself, I would have been faster, and discovered this quicker.

For a different task in the same project I used it to achieve a working version of something in a few days that would have taken me at least a week or two to achieve on my own. The result is not efficient enough for the long term, but for now it is good enough to proceed with other things. On the other hand, with just one (painful) week more, I would have coded a proper solution myself.

What I am looking forward to is being able to converse with the AI in terms of a hard logic. That will take care of the straightforward but technically intricate stuff that it cannot do yet properly, and it will also allow the AI to surface much quicker where a "jump of insight" is needed.

I am not sure what all of this means for us needing to think hard. Certainly thinking hard will be necessary for quite a while. I guess it comes down to when the AIs will be able to do these "jumps of insight" themselves, and for how long we can jump higher than they can.

Re: I miss thinking hard

#236

Post by exodust »

paladin314159 wrote: post #10
topspin wrote: post #8

I'm using LLMs to code and I'm still thinking hard. I'm not doing it wrong: I think about design choices: risks, constraints, technical debt, alternatives, possibilities... I'm thinking as hard as I've ever done.

I echo this sentiment. Even though I'm having Claude Code write 100% of the code for a personal project as an experiment, the need for thinking hard is very present. In fact, since I don't need to do low-thinking tasks like writing boilerplate or repetitive tests, I find my thinking ratio is actually higher than when I write code normally.

Agreed. My recent side projects involve lots of thinking over days and weeks.

With AI we can set high bars and do complex original stuff. Obviously boilerplate and common patterns are slop slap without much thinking. That's why you branch into new creative territory. The challenge then becomes visualising the mental map of modular pieces all working nicely together at the right time to achieve your original intent.

Re: I miss thinking hard

#238

Post by capl »

That’s funny cause I feel the opposite: LLMs can automate, in a sloppy fashion, building the first trivial draft. But what remains is still thinking hard about the non trivial parts.

Re: I miss thinking hard

#239

Post by isolli »

gyomu wrote: post #32

This March 2025 post from Aral Balkan stuck with me: https://mastodon.ar.al/@aral/114160190826192080 "Coding is like taking a lump of clay and slowly working it into the thing you want it to become. It is this process, and your intimacy with the medium and the materials you’re shaping, that teaches you about what you’re making – its qualities, tolerances, and limits – even as you make it. You know the least about wha…

This is very insightful, thanks. I had a similar thought regarding data science in particular. Writing those pandas expressions by hand during exploration means you get to know the data intimately. Getting AI to write them for you limits you to a superficial knowledge of said data (at least in my case).

Re: I miss thinking hard

#240

Post by dns_snek »

abm53 wrote: post #223
nunez wrote: post #194

Earlier quoted context omitted.

You _think_ you're thinking as hard. Reading code != writing it. Just like watching someone do a thing isn't the same as actually doing it.

Correct… reading code is a much more difficult and ultimately, productive, task. I suspect those using the tools in the best way are thinking harder than ever for this reason.

> reading code is a much more difficult

Not inherently, no. Reading it and getting a cursory understanding is easy, truly understanding what it does well, what it does poorly, what the unintended side effects might be, that's the difficult part.

In real life I've witnessed quite a few intelligent and experienced people who truly believe that they're thinking "really hard" and putting out work that's just as good as their previous, pre-AI work, and they're just not. In my experience it roughly correlates to how much time they think they're saving, those who think they're saving the most time are in fact cutting corners and putting out the sloppiest quality work.

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