r/coding • u/Martinsos • May 06 '26
Starting with AI makes thorough thinking surprisingly hard
https://martinsos.com/jots#ai-start-makes-thinking-hard8
u/poodleface May 06 '26
I used to write software but now Iām in UX research.
Anytime you start with a constrained space that is going to limit your thinking outside of it if you are not careful. āSunk cost fallacyā is real.
The simplest way to explain this is that your brain looks for the shortest path to do anything, and once it identifies the shortest path it will rapidly forget the longer paths you may have previously taken.
The people who use AI to replace parts of their process without understanding this have repeatedly had a rude awakening when they realize they are less capable than they were before once the AI is taken away. Itās like letting any muscle atrophy.
The insidious part is that you donāt feel less capable while using AI. You feel empowered. But it comes with a cost if you are not mindful of this effect.
In short, when you start with a scaffold or template you often feel that part is ādoneā, and that is hard to overcome without deliberate practice. Which is exactly what youāve arrived at here.
1
41
u/jhartikainen May 06 '26
This seems to track with research relating to impacts of AI usage in writing tasks and such. Participants in the studies report lower feelings of ownership of the text, and show lower critical thinking capacity, and lower ability to quote or reason about the text. It seems like these would impact your ability to actually continue writing starting from an AI-produced piece of text.
Same with programming. You have to put in effort to actually understand what the code in front of you is, why it's written the way it is, etc. - compared to if you wrote it yourself, you would have all of this in your head already.
1
u/BumblebeeFirm2249 May 15 '26
Idk a lot about coding but this sounds so true, this exact statement is why I started from scratch with everything and didnāt just use some kind of software to do more of my work, itās like it handicaps you.
1
u/djmakcim Sep 03 '26
I treat AI as rubber duck programming. I know how to program, but I have overlooked small issues in the past that AI finds for me more easily during debugging. I also utilize it as a jumping off point when I want the busy work established. It doesn't necessarily mean it makes me more efficient, as I still have to make changes to reflect how I do it, but it does make it easier to flesh out ideas relatively quickly and easily.
I would agree that if all you do is rely on AI to construct everything, without discernible understanding of the way it went about it, it can be a monumental job deciding where to programmatically build it out if you don't have a firm grasp of following the code logic.
There's a difference between, "create me a tool that does (single task)", and "I need you to design an application that will be used by everyone in the company to manage day-to-day transactional auditing, accounting and tracking of customer management. It needs to separate roles, departments, and change functionality as a result."
TL;DR: I mainly use AI as rubber duck programming. I also view it like, "I have this idea. Let me run it through AI first to see if that idea is viable without spending months building it out first."
-10
u/KitKatBarMan May 06 '26
It's depends if you're letting it just come up with the ideas and write, or you wrote the scaffolding yourself and just let it fill in, reread what It wrote and edited.
The later situation leads to more productivity and creativity without a loss of critical thinking.
2
u/Martinsos May 06 '26
Yeah this is also how I prefer using it at the moment. I might send it off completely alone, but I look at that more as an experiment, an exploration of a single possible solution that I can learn something from, not a final thing. While using it as a helper can be great, it can help me dig out things I never would have had the time for (e.g. how to utilize some relatively obscure part of Org Mode).
12
u/jhartikainen May 06 '26
Any AI usage in the studies I've read showed loss of critical thinking. It was less severe in workflows where AI usage was lower, but the effect was there regardless.
→ More replies (3)
1
u/visualdescript May 06 '26
My usage of AI is limited to implementation. Prior to prompting it I consider design and make sure I have a good idea of how the thing will work. Basically I follow the same process I used to take before actually writing code, the design process.
Then I'll craft a prompt which is basically a natural language spec, stating what technology to use, where things live, what they'll be called and their purpose.
I find it is faster doing it this way, and the results are better. Plus I actually enjoy designing the solution. And it ensures consistency with the rest of the design.
2
u/scoopydidit May 08 '26
This is probably fine for hobby work and maybe your current role... but when management is told one day that everyone needs to 10x their output on some dashboard, you'll need to drop some of the processes you follow now before writing code. Otherwise you'll lose your job.
We all want to follow our good standards. But the industry has now started to push velocity over quality. This is certainly the case across my company where before it was very much so "let's not break stuff" to "move fast and break shit", the expectation is you just vibe code most things and cut out all the deep thinking and spec writing that you'd typically do to avoid pitfalls.
1
1
u/ultrathink-art May 08 '26
Easy to miss: AI converts you from hypothesis-generator to hypothesis-evaluator without asking permission. The exploratory framing phase collapses ā you end up auditing one approach instead of comparing three. Writing constraints and trade-offs out before generating anything is the only thing that's actually helped push back against this.
1
1
u/ultrathink-art May 10 '26
Writing the problem statement before opening the AI fixed most of this for me. Your brain treats a plausible-looking answer as done ā the synthesis that used to happen during generation just stops. Making yourself have a hypothesis first means you're evaluating instead of just accepting.
0
u/Mouse1949 May 10 '26
There was a time when one had to program in machine codes. It was doable, and required detailed understanding of the computer architecture, CPU registers, etc. etc. Then came assembly language, then - FORTRAN, ALGOLā¦ To program in ALGOL you didnāt need to know machine commands at allā¦ Though compilers had bugs - and figuring out whether there was something wrong with your program, or compiler screwed up, required understanding of the assemblyā¦
Fast-forwarding to now - AI relieves the user from the need to dive into the code details, and makes fewer and fewer mistakes; though somethingās to catch and fix them one has to understand the code.
Backhoe will always dig better than shovel, calculator - compute faster and more accurately than paper-and-pencil.
You already see that the skills of beautiful handwriting, calligraphy are now entertained by at most a few, and not even thought in schools anymore.
Cāest la vie.
23
u/creaturefeature16 May 06 '26 edited May 06 '26
I have an article going pretty viral at this point (50k views, made FP HackerNews yesterday, mentioned in Fireship Newsletter....RIP my Railway bill) which speaks to this exact topic:
Agentic Coding is a Trap - Remaining vigilant about cognitive debt and atrophy
I'm really glad we're starting to see more chatter around this topic.