[KallDrexx]

I have done a lot of introspection on this and realized that I'm very much driven by intrinsic rewards moreso than extrinsic.

I got into coding over a decade before it was my career because of the exploration, learning, and puzzle/challenge aspect.

Every time I have tried to be extrinsically driven (career or OSS wise) it's never worked out anyway. I could have done more to make it successful but I never cared about getting validation or getting users for my stuff (and the stress that brings).

I've been lucky that up until this point, the intrinsic rewards I have gotten from my job have aligned with company goals.

LLMs take all the intrinsic wins and leaves only the extrinsic ones. That makes me sad, but it is what it is I guess.

I have been thinking about a tool for months but didn't have the time. I finally gave in and built it at work in a week with LLM tokens. It worked fantastically. But I felt no accomplishment. It felt just the same as if I downloaded the tool from someone else's repo (and who had an overly eager maintainer that would implement my GitHub issue requests).

The hard part for me is ignoring LLMs in my free time to try and keep some of the intrinsic rewards to myself, without being annoyed that I could do it faster if I just "gave in".

[fasterik]

Hard agree about the intrinsic motivation. The intrinsic/extrinsic distinction is an unspoken assumption in a lot of conversations about AI and work in general. Not everyone is motivated by money and status.

I do believe you can use LLMs while maintaining the intrinsic rewards of programming. For me, right now that means writing code by hand and using LLMs primarily for research, documentation, and brainstorming. Sometimes I ask it to write a piece of code just so that I can see what it comes up with and maybe learn something from it. I'm also planning on experimenting with coding agents, but I will probably have it work in its own parallel repo and hand-pick the changes I want to keep.

I think a "late adopter" mindset is actually beneficial. It allows you to focus on fundamental skills that will never be outdated, and you get the benefits of new technologies once they mature.

[MrGilbert]

> But I felt no accomplishment. It felt just the same as if I downloaded the tool from someone else's repo (and who had an overly eager maintainer that would implement my GitHub issue requests).

I get that. I recently watched a "talking head" style video by javid9x, where he said something along the lines of disconnecting from the code emotionally [0]. He has to get into the code to understand that. I get the same feeling, however, for me, it feeds my curiosity and my need of exploration. At least for now, I might add.

[0]: https://youtu.be/1qjn1QRxlng?si=_75-J51UnZ0eJyb7&t=705

[ryandrake]

That’s exactly it! There is no feeling of accomplishment whatsoever, because we aren’t really accomplishing anything. The LLM is doing all the work. Out pops an application, but it might as well have been written by someone else, because it was, but also it wasn’t!

It’s great that an application now exists where there wasn’t one before, but it’s hollow because I didn’t make it. Nobody made it! It just exists now with nothing actually accomplished by anyone. It’s a very spooky way to conjure things up.

[realharo]

If that's how you feel, maybe the applications you're making are too simple to need any of your unique contribution.

The answer could be to just push further, and try solving harder problems.

[mettamage]

> LLMs take all the intrinsic wins and leaves only the extrinsic ones.

Not for me, but that's because I like playing around with software. So in web apps, the UX is done by me.

I'm not here to invalidate your experience. I get what you're saying and I feel it. I just also want to show the point of view where intrinsic motivation can still pop up (for some people at least).

But yea, it sucks if all of it is taken away from you. I'm sorry to hear that.

[robotbikes]

I have found the opposite to be true. I really like getting stuff done for people and struggled for years with all of the specific syntax and details of solving any particular problem. I have a relatively in-depth knowledge of computers and how they work and algorithms and the like but always struggled with the exact details of how to do something so it feels like a blessing to be able to spit ball some conceptual understanding and get back real code. I always struggled with making my ideas real before the novelty of the inspiration wore off unless I happened to get hyper focused on solving a particular problem.

Now I can step through everything in a way that it feels like a super power. I have enough sense and knowledge to I think intuit whether the solution being provided is bloated or perhaps even unnecessary and I can reiterate over it. I've just been using Cursor for work as I adopted a personal restriction to only use AI I can run on my own devices for personal use, but if I'm getting paid and the tools are provided I'm going to do my best to solve the problems that I'm confronted with and so far the LLM connected IDE has been helpful.

It's best in my experience when I use it as a tool to augment trouble shooting and brainstorming but when you are fixing one liner bugs in other people's side it's not like me typing the fix is very different from a machine auto completing it.

It might feel like cheating on a crossword puzzle but that is also something I do if I get stuck and the fun of solving the problem has become a time sink.

I think the real risk is if you don't understand conceptually what you are commiting anymore and I've tried to make sure that I always understand what and how the code is working and also understanding the pitfalls of being able to propose bullshit hypothesis that the agreeability of the LLM will go along with.

I've yet to seriously use a LLM for a personal project and when I tried to use Devstral that ran on my Nvidia 4090 it hallucinated so much that it wasn't super helpful but it still shot out boiler plate code that I could then spend time fixing and helped me overcome my own task paralysis regarding initiating.

[KallDrexx]

Yeah and that's totally fair!

We are all motivated by different things and being extrinsically motivated isn't a bad thing at all.

But being more interested in the problems rather than the solutions (and not wanting to "productize the solutions") is why LLMs are demotivating for me.

[munksbeer]

> I have done a lot of introspection on this and realized that I'm very much driven by intrinsic rewards moreso than extrinsic. > I got into coding over a decade before it was my career because of the exploration, learning, and puzzle/challenge aspect. .. > LLMs take all the intrinsic wins and leaves only the extrinsic ones.

I'm not sure I understand this. For me, programming was at first a tool to use to satisfy my curiousity. When I first started coding I knew nothing about software patterns, how I should be naming my variables, length of functions, DOD vs OOP, functional vs imperative, single responsibility principle, and on and on.

I wrote a mess of a program and got it to do very cool things (for me). I loved it.

Then I got taught more, got my first jobs, learned why programming large systems needs standards, patterns, etc. I became good at that, and have had a long lucrative career out of it.

But I cannot wait for the day when I no longer need to earn money from programming and I can go back to using it just to do "cool shit". At that point, whether I am hacking and slashing myself, or working with an LLM to do something, I don't care. It is the intrinsic goal of solving a puzzle and programming just happens to be the tool I use.

Thinking more deeply about your words, is it that you enjoy figuring out the instructions to use to solve a problem? In other words, figuring out the algorithm and writing the code out to create something? Would you feel if you just tell the LLM what you want to create and it does it, you've lost the enjoyment?

[KallDrexx]

> Thinking more deeply about your words, is it that you enjoy figuring out the instructions to use to solve a problem? In other words, figuring out the algorithm and writing the code out to create something? Would you feel if you just tell the LLM what you want to create and it does it, you've lost the enjoyment?

So there's a lot of nuance to the "is it that you enjoy figuring out the instructions to use to solve a problem".

At the surface I don't enjoy typing, I don't enjoy fighting syntax checkers, rust's borrow checker, or manual memory management in my personal C projects, typing out the HDL for nand2tetris problems, etc...

However, there have been studies done decades before this LLM boom about the psychological concept called the Generation Effect. While everyone is different and it's not completely black and white, the studies have found that people learn more by actual practice (the act of doing) than just by reading material. That's 100% the case for me.

I can read blogs and resources till the cows come home and I'll have a very surface understanding of a concept. Then I'll go to write the code to implement it and it rarely works right away because there are demonstrable gaps in my understanding. I'll debug it and iterate on it until it works, and that is what actually solidifies the mental model of what I was trying to learn in my mind. Not only can I say for sure that I remember it better, that seems to form connections in my brain that allows me to apply it in other use cases, or build fascinating technical tangents.

I not only get my high from that initial "Aha!" moment when I really feel like I understand a concept enough to actually apply it in other scenarios, but I also get my high from tangents that spawn off of that concept.

In many cases, I can map a direct line of my personal projects to a set of root projects that spawned them off because of ideas I came up with while actually implementing the projects. Since I tried real hard to optimize a C# game engine for an embedded platform, I realized where limitations were and it solidified my knowledge of how old game consoles worked.

This led me down to the interest of creating a GPU out of embedded device that I can pair with I/O constrained embedded devices. This taught me soooo much about the embedded space, and while I heavily improved my C writing abilities it also made me wish I could write C# on embedded.

Since I had learned C for the embedded project (and I knew MSIL from previous deep dives), I realized I can just translate MSIL into C and that would allow me to run C# anywhere (got C# working on an SNES, the linux kernel, and on an ESP32S3).

By implementing that by hand and coming face to face with many small decisions I had to make, that solidified a bunch of concepts in my head around intermediate representations and why they are a massive benefit. Those aha moments (among others) then led me down the path to implementing a just-in-time compilation engine for NES games and the C64 OS into the .net runtime.

The learnings from that have already spawned some other ideas in my mind, which is why I'm now learning Verilog and FPGA development.

None of these projects solved any useful problem (as in nothing was created that I or anyone else would use). The satisfaction and the high I got from them was having the curiosities of a problem, ideas of a solution, and persevering (partially due to being stubborn) through it and actually accomplishing it. The satisfaction that I actually understand the concepts at a foundational level, which actually ends up breeding excitement for a whole other tangent/problem.

These learnings have indirectly helped me in my day job as well. While I'm not working on anything that sophisticated or cool, all of these actual implementations I've learned have given me direct learnings I have been able to successfully use to create better software in other domains.

So it's not the actual typing I enjoy, but the whole picture of what comes out of the end through that typing. LLMs take most of that away. It lets me ideate on a vague solution and then it goes ahead and implements it for me. Even if I'm specific on the details of the algorithm it uses, it subtly fills in the blanks and the missing pieces that I haven't cemented in my brain yet thus making me miss out of the opportunity to do so.

And it steals the accomplishment of the final thing existing. I don't feel an accomplishment by typing in google "I need a C# to C transpiler" and just downloading it. That's what LLMs feel like, even if I'm trying to steer them at a lower architectural level. I don't have the aha moments, I don't have the learnings, and I'm disconnected from the code.

Thus it feels like it's stealing all the intrinsic rewards from me, only leaving the extrinsic ones. And those are not rewards I am particularly motivated by.