The question is why you care about that.

https://github.com/x3haloed/ascry

I don’t need my particular repo to be the one where this gets solved, but now that coding agents are really good, we shouldn’t have to put up with paying for shit software anymore, IMO.

The comment about hobby vs. work is correct, and it’s the crux of this.

OP is attempting to console themselves. “I shouldn’t have to change to avoid ‘falling behind.’ I like how I’m doing it. I’m good at what I do.”

The fact of the matter is the LLMs can be used to produce effective work faster than you. Yes. You are falling behind. And yes, it will reduce your value in the job market. Eventually it will be a dramatic reduction.

That doesn’t mean you must stop coding by hand, because you love it. But I don’t think you do love it. I think you love being praised for being smart. The pats on the head. That’s the most likely explanation for why your motivation for coding by hand has disappeared. Once the results stopped being a special output from your special brain, you stopped feeling special.

You have a choice now that the landscape is changing. You can find a way to produce unique and outstanding results that still matter, or you can slowly fade into a hardened stance of obsolescence and spend your time grumbling about the change.

Maybe software just needs to remain straightforward and focused, and we let the ChatGPT and Claude apps handle the AI part of things.

Would you commission a study about whether cars are really a faster form of locomotion before deciding to purchase one?

There is empirical data right in front of your face. You're just choosing to exclude it because of where you already stand.

That's exactly what Feynman was warning about.

And then... yeah. You got it exactly right. Once a problem or process is deterministic, that's the wrong application of an LLM.

But I had never quite thought of it in these exact terms. The way I've been thinking about it up until now is that the very best way to use LLMs is to have them produce tools. The tools get to stay reliable and predictable. They boost your performance. But I think you found the more general abstraction of the same idea. Tool-making is not deterministic. But the tools themselves can be. That's why it fits. Trying to stuff LLMs into what's otherwise a deterministic process is an absurd waste and error-prone.

Smart. I like it.

I think too often people fall completely on one side of this question or the other. I think it’s really complicated, and deserves a lot of nuance. I think it mostly comes down to having a right to exert control over how our data should be used, and I think most of it’s currently shaped by Section 230.

Generally speaking, platforms consider data to be owned by the platform. GDPR and CCPA/CPRA try to be the counter to that, but those are also too-crude a tool.

Let’s take an example: Reddit. Let’s say a user is asking for help and I post a solution that I’m proud of. In that act, I’m generally expecting to help the original person who asked the question, and since I’m aware that the post is public, I’m expecting it to help whoever comes next with the same question.

Now (correct me if I’m wrong, but) GDPR considers my public post to be my data. I’m allowed to request that Reddit return it to me or remove it from the website. But then with Reddit’s recent API policies, that data is also Reddit’s product. They’re selling access to it for … whatever purposes they outline in the use policy there. That’s pretty far outside what a user is thinking when they post on Reddit. And the other side of it as well — was my answer used to train a model that benefits from my writing and converts it into money for a model maker? (To name just an example).

I think ultimately, platforms have too much control, and users have too little specificity in declaring who should be allowed to use their content and for what purposes.

The tooling is just not there yet. Everyone is just stuck on supporting Docker still.