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gloosx

So what is he even coding there all the time?

Does anybody have any info on what he is actually working on besides all the vibe-coding tweets?

There seems to be zero output from they guy for the past 2 years (except tweets)

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> There seems to be zero output from they guy for the past 2 years (except tweets)

Well, he made Nanochat public recently and has been improving it regularly [1]. This doesn't preclude that he might be working on other projects that aren't public yet (as part of his work at Eureka Labs).

1: https://github.com/karpathy/nanochat

So, it's generative pre-trained transformers again?

He's building Eureka Labs[1], an AI-first education company (can't wait to use it). He's both a strong researcher[2] and an unusually gifted technical communicator. His recent videos[3] are excellent educational material.

More broadly though: someone with his track record sharing firsthand observations about agentic coding shouldn't need to justify it by listing current projects. The observations either hold up or they don't.

[1] https://x.com/EurekaLabsAI

[2] PhD in DL, early OpenAI, founding head of AI at Tesla

[3] https://www.youtube.com/@AndrejKarpathy/videos

If LLM coding is a 10x productivity enhancer, why aren't we seeing 10x more software of the same quality level, or 100x as much shitty software?

Helper scripts for APIs for applications and tools I know well. LLMs have made my work bearable. Many software providers expose great apis, but expert use cases require data output/input that relies on 50-500 line scripts. Thanks to the models post gpt4.5 most requirements are solvable in 15 minutes when they could have taken multiple workdays to write and check by hand. The only major gap is safe ad-hoc environments to run these in. I provide these helper functions for clients that would love to keep the runtime in the same data environment as the tool, but not all popular software support FaaS style environments that provide something like a simple python env.

I don’t know, but it’s interesting that he and many others come up with this “we should act like LLMs are junior devs”. There is a reason why most junior devs work on fairly separate parts of products, most of the time parts which can be removed or replaced easily, and not an integral part of products: because their code is usually quite bad. Like every few lines contains issues, suboptimal solutions, and full with architectural problems. You basically never trust junior devs with core product features. Yet, we should pretend that an “LLM junior dev” is somehow different. These just signal to me that these people don’t work on serious code.

This is the first question I ask, and every time I get the answer of some monolith that supposedly solves something. Imo, this is completely fine for any personal thing, I am happy when someone says they made an API to compare weekly shopping prices from the stores around them, or some recipe, this makes sense.

However more often than not, someone is just building a monolithic construction that will never be looked at again. For example, someone found that HuggingFace dataloader was slow for some type of file size in combination with some disk. What does this warrant? A 300000+ line non-reviewed repo to fix this issue. Not a 200-line PR to HuggingFace, no you need to generate 20% of the existing repo and then slap your thing on there.

For me this is puzzling, because what is this for? Who is this for? Usually people built these things for practice, but now its generated, so its not for practice because you made very little effort on it. The only thing I can see that its some type of competence signaling, but here again, if the engineer/manager looking knows that this is generated, it does not have the type of value that would come with such signaling. Either I am naive and people still look at these repos and go "whoa this is amazing", or it's some kind of induced egotrip/delusion where the LLM has convinced you that you are the best builder.

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