Comment by otabdeveloper4
6 days ago
> Still saves a lot of time vs typing everything from scratch
No it doesn't. Typing speed is never the bottleneck for an expert.
As an offline database of Google-tier knowledge, LLM's are useful. Though current LLM tech is half-baked, we need:
a) Cheap commodity hardware for running your own models locally. (And by "locally" I mean separate dedicated devices, not something that fights over your desktop's or laptop's resources.)
b) Standard bulletproof ways to fine-tune models on your own data. (Inference is already there mostly with things like llama.cpp, finetuning isn't.)
I realize I procrastinate less when using LLM to write code which I know I could write.
I've noticed this too.
I remember hearing somewhere that humans have a limited capacity in terms of number of decisions made in a day, and it seems to fit here: If I'm writing the code myself, I have to make several decisions on every line of code, and that's mentally tiring, so I tend to stop and procrastinate frequently.
If an LLM is handling a lot of the details, then I'm just making higher-level decisions, allowing me to make more progress.
Of course this is totally speculation and theories like this tend to be wrong, but it is at least consistent with how I feel.
I have a feeling that it's something that might help today but also something you might pay for later. When you have to maintain or bug fix that same code down the line the fact that you were the one making all those higher-level decisions and thinking through the details gives you an advantage. Just having everything structured and named in ways that make the most sense to you seems like it'd be helpful the next time you have to deal with the code.
While it's often a luxury, I'd much rather work on code I wrote than code somebody else wrote.
> No it doesn't. Typing speed is never the bottleneck for an expert
How could that possibly be true!? Seems like it'd be the same as suggesting being constrained to analog writing utensils wouldn't bottleneck the process of publishing a book or research paper. At the very least such a statement implies that people with ADHD can't be experts.
Completely agree with you. I was working on the front-end of an application and I prompted Claude the following: "The endpoint /foo/bar is returning the json below ##json goes here##, show this as cards inside the component FooBaz following the existing design system".
In less than 5 minutes Claude created code that: - encapsulated the api call - modeled the api response using Typescript - created a re-usable and responsive ui component for the card (including a load state) - included it in the right part of the page
Even if I typed at 200wpm I couldn't produce that much code from such a simple prompt.
I also had similar experiences/gains refactoring back-end code.
This being said, there are cases in which writing the code yourself is faster than writing a detailed enough prompt, BUT those cases are becoming exception with new LLM iteration. I noticed that after the jump from Claude 3.7 to Claude 4 my prompts can be way less technical.
The thing is... does your code end there? Would you put that code in production without a deep analysis of what Claude did?
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It seems fair to say that it is ~never the overall bottleneck? Maybe once you figure out what you want, typing speed briefly becomes the bottleneck, but does any expert finish a day thinking "If only I could type twice as fast, I'd have gotten twice as much work done?" That said, I don't think "faster typing" is the only benefit that AI assistance provides.
> How could that possibly be true!?
(I'll assume you're not joking, because your post is ridiculous enough to look like sarcasm.)
The answer is because programmers read code 10 times more (and think about code 100 times more) than they write it.
Yeah, but how fast can you write compared to how fast you think?
How many times have you read a story card and by the time you finished reading it you thought "It's an easy task, should take me 1 hour of work to write the code and tests"?
In my experience, in most of those cases the AI can do the same amount of code writing in under 10 minutes, leaving me the other 50 minutes to review the code, make/ask for any necessary adjustments, and move on to another task.
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I wasn't joking, it's a bottleneck sometimes, that's it. It's a bottleneck like comfort and any good tool is a bottleneck, like a slow computer is a bottleneck. It's silly to suggest that your ability to rapidly use a fundamental tool is never a bottleneck, no matter what other bits need to come into play during the course of your day.
My ability to review and understand intent behind code isn't a primarily bottleneck to me actually efficiently reviewing code when it's requested of me, the primary bottleneck is being notified at the right time that I have a waiting request to review code.
If compilers were never a bottleneck, why would we ever try to make them faster? If build tools were never a bottleneck, why would we ever optimize those? These are all just some of the things that can stand between the identification of a problem and producing a solution for it.
Maybe you type faster than me then :) I for sure type slower than Claude code. :)