For me it feels like print statement debugging in a compiled language

Correct, provided you were the one who wrote an incredibly specific feature request that the pull request solved for you.

I’m a “LLM believer” in a sense, and not someone who derives joy from actually typing out the tokens in my code, but I also agree with you about the hype surrounding Claude Code and “agentic” systems in general. I have found the three positive use cases you mentioned to be transformative to my workflow on its own. I’m grateful that they exist even if they never get better than they are today.

> I didn't pay hundreds of dollars for a mechanical keyboard, tuned to make every keypress a joy, to push code around with a fucking mouse

Can’t you use vim controls?

> and hate how much extra bullshit I didn't ask for they always add to the output.

I can recommend for that problem to make the "jumps" smaller, e.g. "Add a react component for the profile section, just put a placeholder for now" instead of "add a user profile".

With coding LLMs there's a bit of a hidden "zoom" functionality by doing that, which can help calibrating the speed/involvment/thinking you and the LLM does.

> Try using it on something you just want to exist, not something you want to build or are interested in understanding.

I don't get any enjoyment from "building something without understanding" — what would I learn from such a thing? How could I trust it to be secure or to not fall over when i enter a weird character? How can I trust something I do not understand or have not read the foundations of? Furthermore, why would I consider myself to have built it?

When I enter a building, I know that an engineer with a degree, or even a team of them, have meticulously built this building taking into account the material stresses of the ground, the fault lines, the stresses of the materials of construction, the wear amounts, etc.

When I make a program, I do the same thing. Either I make something for understanding, OR I make something robust to be used. I want to trust the software I'm using to not contain weird bugs that are difficult to find, as best as I can ensure that. I want to ensure that the code is clean, because code is communication, and communication is an art form — so my code should be clean, readable, and communicative about the concepts that I use to build the thing. LLMs do not assure me of any of this, and the actively hamstring the communication aspect.

Finally, as someone surrounded by artists, who has made art herself, the "doing of it" has been drilled into me as the "making". I don't get the enjoyment of making something, because I wouldn't have made it! You can commission a painting from an artist, but it is hubris to point at a painting you bought or commissioned and go "I made that". But somehow it is acceptable to do this for LLMs. That is a baffling mindset to me!

I think the key thing here is in point 2.

I’ve wanted a good markdown editor with automatic synchronization. I used to used inkdrop. Which I stopped using when the developer/owner raised the price to $120/year.

In a couple hours with Claude code, I built a replacement that does everything I want, exactly the way I want. Plus, it integrates native AI chat to create/manage/refine notes and ideas, and it plugs into a knowledge RAG system that I also built using Claude code.

What more could I ask for? This is a tool I wanted for a long time but never wanted to spend the dozens of hours dealing with the various pieces of tech I simply don’t care about long-term.

This was my AI “enlightenment” moment.

I can say I feel that flow state sometimes when it all works but I certainly don't when it doesn't work.

The other day I was making changes to some CSS that I partially understood.

Without an LLM I would looked at the 50+ CSS spec documents and the 97% wrong answers on Stack Overflow and all the splogs and would have bumbled around and tried a lot of things and gotten it to work in the end and not really understood why and experienced a lot of stress.

As it was I had a conversation with Junie about "I observe ... why does it work this way?", "Should I do A or do B?", "What if I did C?" and came to understand the situation 100% and wrote a few lines of code by hand that did the right thing. After that I could have switched it to Code mode and said "Make it so!" but it was easy when I understood it. And the experience was not stressful at all.

Prompt one:

  imagine a game, like Galaxians but using tractor trailers,
  and as a first person shooter. Three.js in index.html

Prompt two:

  No, let's try it again with an army of bagpipers.

I'll be honest, the bagpiper 3D models were way better than I expected! That game's a bit too hard though, you have to run sideways pretty quickly to avoid being destroyed by incoming fire.

Here's the full transcript: https://gisthost.github.io/?73536b35206a1927f1df95b44f315d4c

There are multiple self driving car companies that are fully autonomous and operating in several cities in the US and China. Waymo has been operating for many years.

There are full self driving systems that have been in operation with human driver oversight from multiple companies.

And the capabilities of the LLMs in regards to your specific examples were demonstrated below.

The inability of the public to perceive or accept the actual state of technology due to bias or cognitive issues is holding back society.

For me the excitement is palpable when I've asked it to write a feature, then I go test it and it entirely works as expected. It's so cool.

Ditto. Coding isn't what i specifically do, but it's something i will choose to do when it's the most efficient solution to a problem. I have no problem describing what i need a program to do and how it should do so in a way that could be understandable even to a small child or clever golden retriever, but i'm not so great at the part where you pull out that syntactic sugar and get to turning people words into computer words. LLMs tend to do a pretty good job at translating languages regardless of whether i'm talking to a person or using a code editor, but i don't want them deciding what i wanted to say for me.

When you don't know the answer to a question you ask an LLM, do you verify it or do you trust it?

Like, if it tells you merge sort is better on that particular problem, do you trust it or do you go through an analysis to confirm it really is?

I have a hard time trusting what I don't understand. And even more so if I realize later I've been fooled. Note that it's the same with human though. I think I only trust technical decision I don't understand when I deem the risk of being wrong low enough. Overwise I'll invest in learning and understanding enough to trust the answer.