[throwaway290]

And to all the LLM heads here, this is his work process:

> Yesterday I was browsing for a Deep Q Learning implementation in TensorFlow (to see how others deal with computing the numpy equivalent of Q[:, a], where a is an integer vector — turns out this trivial operation is not supported in TF). Anyway, I searched “dqn tensorflow”, clicked the first link, and found the core code. Here is an excerpt:

Notice how it's "browse" and "search" not just "I asked chatgpt". Notice how it made him notice a bug

[stingraycharles]

First of all, this is not a competition between “are LLMs better than search”.

Secondly, the article is from 2016, ChatGPT didn’t exist back then

[code51]

I doubt he's letting LLM creep in to his decision-making in 2025, aside from fun side projects (vibes). We don't ever come across Karpathy going to an LLM or expressing that an LLM helped in any of his Youtube videos about building LLMs.

He's just test driving LLMs, nothing more.

Nobody's asking this core question in podcasts. "How much and how exactly are you using LLMs in your daily flow?"

I'm guessing it's like actors not wanting to watch their own movies.

[mquander]

Karpathy talking for 2 hours about how he uses LLMs:

https://www.youtube.com/watch?v=EWvNQjAaOHw

[code51]

Vibing, not firing at his ML problems.

He's doing a capability check in this video (for the general audience, which is good of course), not attacking a hard problem in ML domain.

Despite this tweet: https://x.com/karpathy/status/1964020416139448359 , I've never seen him citing an LLM helped him out in ML work.

[soulofmischief]

You're free to believe whatever fantasy you wish, but as someone who frequently consults an LLM alongside other resources when thinking about complex and abstract problems, there is no way in hell that Karpathy intentionally limits his options by excluding LLMs when seeking knowledge or understanding.

If he did not believe in the capability of these models, he would be doing something else with his time.

[strogonoff]

One can believe in the capability of a technology but on principle refuse to use implementations of it built on ethically flawed approaches (e.g., violating GPL licensing laws and/or copyright, thus harming open source ecosystem).

[confirmmesenpai]

> Continuing the journey of optimal LLM-assisted coding experience. In particular, I find that instead of narrowing in on a perfect one thing my usage is increasingly diversifying

https://x.com/karpathy/status/1959703967694545296

[danielbln]

https://news.ycombinator.com/item?id=45788753

[confirmmesenpai]

what you did here is called confirmation bias.

> I think congrats again to OpenAI for cooking with GPT-5 Pro. This is the third time I've struggled on something complex/gnarly for an hour on and off with CC, then 5 Pro goes off for 10 minutes and comes back with code that works out of the box. I had CC read the 5 Pro version and it wrote up 2 paragraphs admiring it (very wholesome). If you're not giving it your hardest problems you're probably missing out.

https://x.com/karpathy/status/1964020416139448359

[away74etcie]

Yes, embedding .py code inside of a speedrun.sh to "simplify the [sic] bash scripts."

Eureka runs LLM101n, which is teaching software for pedagogic symbiosis.

[1]:https://eurekalabs.ai/