First, it's not cynicism but a more realistic approach than just following SV marketing blindly, and second, it's not "everything else", just GenAI, NFTs/ICOs/Web3, "Metaverse" (or Zucks interpretation of it), delf-driving cars ready today, maybe a bit Theranos.

I’ve recently written a message queue <> database connector in Go using Claude Code, checkpointing, recovery, all that stuff built in.

I’d say it made me around 2x as productive.

I don’t think the cynicism of HN is justified, but I think what people forget is that it takes several months of really investing a lot of time into learning how to use AI well. If I see some of the prompts people give, and expect it to work, yeah no wonder that only works for React-like apps.

I asked AI to create a basic autoencoder based deep learning architecture for classifying time series data. This AI is a boon.

The thing is cryptocurrency and metaverse stuff was obvious bullshit from day one while even GPT-3 was clearly a marvel from day one. It's a false pattern match.

okay but he literally does have a bridge that non-deterministically might take you to the wrong place to sell you

The original context of this sub-thread was Karpathy saying how AI coding tools were pretty useless for him when working on this particular project.

Indeed. And only Karpathy is entitled to say that AI tools produce wrong code for him. And he's only entitled to say it for this project only.

If anyone else says this, "the skepticism is exhausting", and their experience is completely irrelevant.

Go look at the comments on HN whenever someone posts about their AI coding workflow. It will be littered with negative comments that either imply or outright say that the poster is either shilling, ignorant or working only on toy examples.

The grievance attitude seems to exist in both directions and is actually what is exhausting.

> It will be littered with negative comments that either imply or outright say that the poster is either shilling, ignorant or working only on toy examples.

And they would be often be right. Coupled with the fact that most of the glowing "omg I only code with AI" posts don't even try to show what code or products they are working on.

And yes, the absolute vast majority of people who are skeptical are skeptical precisely because they use these tools every day themselves.

Just so we are clear, you are upset by people dismissing your experience gained skepticism but have no problem dismissing every positive comment as a shill, ignorant or simple?

You don’t see any dissonance in that? It’s only the positive people that are exhausting?

I myself post positive comments about AI from time to time.

I never pretend that AI is the be all end all of programming, don't claim that it can do all the magical things, or that it's capable of running hours on end just creating software with not proof like most positive posts do.

See the difference?

I'm all for positive posts. I'm against childish belief in magic: https://dmitriid.com/everything-around-llms-is-still-magical...

Show HNs about AI startups are littered with positive comments though. It's rare to see people calling out the submitter.

I mean Karpathy himself wrote that he could not use the AI tools for the project, so he had to handwrite most of it. I wonder why.

One of my hobby projects is an esoteric game engine oriented towards expressing simulation mechanics. I simply do not use agentic tools when editing the core code for this project (mostly rust and wgsl). It always stumbles, and leaves code that I need to fix up manually, and even then feel unsure about. I've tried a few different agents, including the current top of the line. The power is just not there yet.

At the same time, these tools have helped me reduce the development time on this project by orders of magnitude. There are two prominent examples.

--- Example 1:

The first relates to internal tooling. I was debugging a gnarly problem in an interpreter. At some point I had written code to do a step-by-step dump of the entire machine state to file (in json) and I was looking through it to figure out what was going wrong.

In a flash of insight, I asked my AI service (I'll leave names out since I'm not trying to promote one over another) to build a react UI for this information. Over the course of a single day, I (definitely not a frontend dev by history) worked with it to build out a beautiful, functional, easy to use interface for browsing step-data for my VM, with all sorts of creature comforts (like if you hover over a memory cell, and the memory cell's value happens to be a valid address to another memory cell, the target memory cell gets automatically highlighted).

This single tool has reduced my debugging time from hours or days to minutes. I never would have built the tool without AI support, because I'm simply not experienced enough in frontend stuff to build a functional UI quickly.. and this thing built an advanced UI for me based on a conversation. I was truly impressed.

--- Example 2:

As part of verifying correctness for my project, I wanted to generate a set of tests that validated the runtime behaviour. The task here consists of writing a large set of reference programs, and verifying that their behaviour was identical between a reference implementation and the real implementation.

Half decent coverage meant at least a hundred or so tests were required.

Here I was able to use agentic AI to reduce the testcase construction time from a month to about a week. I asked the AI to come up with a coverage plan and write the test case ideas to a markdown file in an organized, categorized way. Then I went through each category in the test case markdown and had the AI generate the test cases and integrate them into the code.

---

I was and remain a strong skeptic of the hype around this tech. It's not the singularity, it's not "thinking". It's all pattern matching and pattern extension, but in ways so sophisticated that it feels like magic sometimes.

But while the skeptical perspective is something I value, I can't deny that there is core utility in this tech that has a massive potential to contribute to efficiency of software development.

This is a tool that we as industry are still figuring out the shape of. In that landscape you have all sorts of people trying to evangelize these tools along their particular biases and perspectives. Some of them clearly read more into the tech than is there. Others seem to be allergically reacting to the hype and going in the other direction.

I can see that there is both noise, and fundamental value. It's worth it to try to figure out how to filter the noise out but still develop a decent sense of what the shape of that fundamental value is. It's a de-facto truth that these tools are in the future of every mainstream developer.

That's exactly why I said he would cringe at it. Seeing someone look at him saying "it's not able to make a good GPT clone" and going "yeah it's useless for anything besides React todo list demos" would definitely evoke some kind of reaction. He understands AI coding agents are neither geniuses nor worthless CRUD monkeys.

Hm, interesting point. So if he and other GenAI hotshots understand that, why do they keep seeling the tools as precisely no less than geniuses? Often with a bit of fear mongering about all the jobs that would be lost soon etc.?