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Karpathy on Programming: “I've never felt this much behind”

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Re: Karpathy on Programming: “I've never felt this much behind”

#422
I think people need to chill out on this thread. LLMs are neither pure slop nor the end of the programming profession. They are immensely useful tools, particularly for tedious tasks or for quickly getting up to speed on a new API or syntax. They’re great for catching bugs too. Every now and again I’ll give an LLM a prompt and it will knock it out of the park, but that’s exceedingly rare. Most of the time, though, it just allows me to focus on the more interesting parts of my job. In short, for now at least, it is a big productivity booster, not a career ender.

Re: Karpathy on Programming: “I've never felt this much behind”

#423

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> If an LLM is typing that code - and it can maintain a test suite that shows everything works correctly - maybe we don't need that abstraction after all. But this is a highly non-trivial problem. How do you even possibly manually verify that the test suite is complete and tests all possible corner cases (of which there are so many because synchronizing state is a hard problem)? At least React solves this problem in…

You don't, same as for the "generate momentjs and use it". People now firmly believe they can use an LLM to build custom versions of these libraries and rewrite whole ecosystems out of nowhere because Claude said "here's the code". I've come to realize fighting this is useless, people will do this, its going to create large fuck ups and there will be heaps of money to be made on the cleanup jobs.

There's going to be lots of fuck ups, but with frontier models improving so much there's also going to be lots of great things made. Horrible, soul crushing technical debt addressed because it was offloaded to models rather than spending a person's thought and sanity on it.

I think overall for engineering this is going to be a net positive.

Re: Karpathy on Programming: “I've never felt this much behind”

#424
post #393
post #346

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I’m not sure that really answers the question? Or perhaps my interpretation of the question is different. If (say) the code generation technology of Anthropic is so good, why be in the business of selling access to AI systems? Why not instead conquer every other software industry overnight? Have Claude churn out the best office application suite ever. Have Claude make the best operating system ever. Have Claude make…

Im waiting for people to realise that software products are much more than just lines of code. Getting sick and tired of people talk about their productivity gains when not much is actually happening out there in terms of real value creation.

Just because you don't see it or refuse to believe people doesn't make you right and them liars. Maybe you're just wrong.

Re: Karpathy on Programming: “I've never felt this much behind”

#425
post #409

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Without commenting if parent is right or wrong. (I suspect it is correct) If its true, the market will soon reward it. Being able to competently write good code cheaper will be rewarded. People don't employ programmers because they care about them, they are employed to produce output. If someone can use llms to produce more output for less $$ they will quickly make the people that don't understand the technology less…

> more output for less $$ That's a trap: it's not obvious for those without experience in both business and engineering on how to estimate or later calculate this $$. The trap is in the cost of changes and fix budget when things will break. And things will break. Often. Also, the requirements will change often, that's normal (our world is not static). So the cost has some tendency to change (guess which direction). T…

Predicting costs may be tricky, but measuring them after the fact it's a fair bit easier.

Re: Karpathy on Programming: “I've never felt this much behind”

#426
post #177

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As far as I can tell as a heavy coding agent user: you don’t need to know any of this and that’s a testament to how good code agent TUIs have become. All I do to be productive with a coding agent is tell it to break a problem down into tasks, store it inside beads, and then make sure each step is approved by me. I also add in a TDD requirement where it needs to build tests that fail then eventually pass. Everything e…

This sounds like my complete and utter nightmare. No art or finesse in building the thing - only an exercise in torturing language to someone who at a fundamental level doesn't understand a thing.

I don’t really understand how you got that from my post. I can and do drop in to refactor or work on the interesting parts of a project. At every checkpoint where I require a review I can and do make medications by hand.

Are you complaining about code formatters or auto fix linters? What about codegen based on APIs specs? A code agent can do all of those and more. It can do all the boring parts while I get to focus on the interesting bits. It’s great.

Here’s another fantastic use case: have an agent gen the code, think about its prototype, delete, and then rewrite it. I did that on a project with huge success: https://github.com/neurosnap/zmx

Re: Karpathy on Programming: “I've never felt this much behind”

#427

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Is that really what he's saying here? He's not against the technology, I think he's just feeling like there's a lot of potential that he's not quite grasping yet.

This guy is one of the top names in AI. This is pure propaganda written to instill "fear of missing out" and encouraging people to buy into his platform, lest they become "obsolete."

on the other hand, it does currently feel like when angular and react were starting to come out, and there was a billion different javascript libraries to learn with a new one coming out every couple weeks, and you arent quite sure what you should spend your time on and how much, vs now where you just learn react, and maybe extend to next.js

LLM forward development has a lot of things going on, and it really isn't clear yet what is going be the common standard in a few years time in terms of dev ux, async tools, ci/cd tools, in production and offline workflows, etc.

its an easy time to hop down a wrong path picking subpar tools or not experimenting further, but if you just wait, the people who try the right tools are going to be way ahead on making products for their customers.

Re: Karpathy on Programming: “I've never felt this much behind”

#428

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I hardly ever open an IDE anymore. I use Claude Code and Cursor. What I do: - use statically typed languages: TypeScript, Go, Rust, Python w/ types - Setup linters. For TS I have a bunch of custom lint rules (authored by AI) for common feedback that I've given. ( https://github.com/shepherdjerred/monorepo/tree/main/package... ) - For Cursor, lots of feedback on my desired style. https://github.com/shepherdjerred/scou…

Thanks for sharing. So the dumb question - do you feel like Claude Code & Cursor have made you significantly more productive? You have an impressive list of personal projects, and I can see how a power user of AI tools can be very effective with green field projects. Does the productivity boost translate as well to your day job?

For personal projects, I have found it to be transformative. I've always struggled with perfection and doing the "boring parts". AI has allowed me to add lots of little nice-to-have features and focus less on the code.

I'm lucky enough that my workplace also uses Cursor + Claude Code, so my experience directly transfers. I most often use Cursor for day-to-day work. Claude has been great as a research assistant when analyzing how data flows between multiple repos. As an example I'm writing a design doc for a new feature and Claude has been helping me with the investigation. My workflow is more or less to say: "here are my repos, here is the DB schema, here are previous design docs, now how does system X work, what would happen if I did Y, etc."

AI is still fallible so you _do_ of course have to do lots of checking and validation which can be boring, but much easier if you add a prompt like "support every claim you make with a concrete reference".

When it comes to implementation, I generally give it smaller, more concrete pieces to work with. e.g. for a personal project I would say something like "here is everything I want to do, make a plan, do part 1, then do part 2, example: https://github.com/shepherdjerred/scout-for-lol/tree/227e784...)

At work, I tend to give it PR-sized units of work. e.g. something very well-scoped and defined. My workflow is: prompt, make a PR on GitHub, add comments on GitHub, tell Cursor "I left comments on your PR, address them", repeat. Essentially I treat AI as a coworker submitting code to me.

I don't really know that I can quantify the productive gain.. I can say that I am _much_ more motivated in the last few months because AI removes so much friction. I think it's backed up by my commit history since June/July which is when I started using Cursor heavily: https://github.com/shepherdjerred

Re: Karpathy on Programming: “I've never felt this much behind”

#429

Earlier quoted context omitted.

It's not something that suddenly changed. "I'll generate some code" is as nondeterministic as "I'll look for a library that does it", "I'll assign John to code this feature", or "I'll outsource this code to a consulting company". Even if you write yourself, you're pretty nondeterministic in your results - you're not going to write exactly the same code to solve a problem, even if you explicitly try.

No? If I use a library, I know it will do the same thing from the same inputs, every time. If I don't understand something about its behavior, then I can look to the documentation. Some are better about this, some are crap. But a good library will continuing doing what I want years or decades later. An LLM can't decide between one sentence and the next what to do.

The library is deterministic, but looking for the library isn't. In the same way that generating code is not deterministic, but the generated code normally is.
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