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Andrej Karpathy: Software in the era of AI [video]

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Re: Andrej Karpathy: Software in the era of AI [video]

#171

Post by diggan »

OvbiousError wrote: post #160
abdullin wrote: post #102

Tight feedback loops are the key in working productively with software. I see that in codebases up to 700k lines of code (legacy 30yo 4GL ERP systems). The best part is that AI-driven systems are fine with running even more tight loops than what a sane human would tolerate. Eg. running full linting, testing and E2E/simulation suite after any minor change. Or generating 4 versions of PR for the same task so that the h…

I don't think the human is the problem here, but the time it takes to run the full testing suite.

It is kind of a human problem too, although that the full testing suite takes X hours to run is also not fun, but it makes the human problem larger.

Say you're Human A, working on a feature. Running the full testing suite takes 2 hours from start to finish. Every change you do to existing code needs to be confirmed to not break existing stuff with the full testing suite, so some changes it takes 2 hours before you have 100% understanding that it doesn't break other things. How quickly do you lose interest, and at what point do you give up to either improve the testing suite, or just skip that feature/implement it some other way?

Now say you're Robot A working on the same task. The robot doesn't care if each change takes 2 hours to appear on their screen, the context is exactly the same, and they're still "a helpful assistant" 48 hours later when they still try to get the feature put together without breaking anything.

If you're feeling brave, you start Robot B and C at the same time.

Re: Andrej Karpathy: Software in the era of AI [video]

#172

Post by ramon156 »

mentalgear wrote: post #157

Meanwhile, I asked this morning Claude 4 to write a simple EXIF normalizer. After two rounds of prompting it to double-check its code, I still had to point out that it makes no sense to load the entire image for re-orientating if the EXIF orientation is fine in the first place. Vibe vs reality, and anyone actually working in the space daily can attest how brittle these systems are. Maybe this changes in SWE with more…

The real question is how long it'll take until they're not brittle

Re: Andrej Karpathy: Software in the era of AI [video]

#173

Post by informal007 »

wjohn wrote: post #19

The comparison of our current methods of interacting with LLMs (back and forth text) to old-school terminals is pretty interesting. I think there's still a lot work to be done to optimize how we interact with these models, especially for non-dev consumers.

Audio maybe the better option.

Re: Andrej Karpathy: Software in the era of AI [video]

#174

Post by kubb »

ramon156 wrote: post #172
mentalgear wrote: post #157

Meanwhile, I asked this morning Claude 4 to write a simple EXIF normalizer. After two rounds of prompting it to double-check its code, I still had to point out that it makes no sense to load the entire image for re-orientating if the EXIF orientation is fine in the first place. Vibe vs reality, and anyone actually working in the space daily can attest how brittle these systems are. Maybe this changes in SWE with more…

The real question is how long it'll take until they're not brittle

Or will they ever be reliable. Your question is already making an assumption.

Re: Andrej Karpathy: Software in the era of AI [video]

#175

Post by londons_explore »

OvbiousError wrote: post #160
abdullin wrote: post #102

Tight feedback loops are the key in working productively with software. I see that in codebases up to 700k lines of code (legacy 30yo 4GL ERP systems). The best part is that AI-driven systems are fine with running even more tight loops than what a sane human would tolerate. Eg. running full linting, testing and E2E/simulation suite after any minor change. Or generating 4 versions of PR for the same task so that the h…

I don't think the human is the problem here, but the time it takes to run the full testing suite.

The full test suite is probably tens of thousands of tests.

But AI will do a pretty decent job of telling you which tests are most likely to fail on a given PR. Just run those ones, then commit. Cuts your test time from hours down to seconds.

Then run the full test suite only periodically and automatically bisect to find out the cause of any regressions.

Dramatically cuts the compute costs of tests too, which in big codebase can easily become whole-engineers worth of costs.

Re: Andrej Karpathy: Software in the era of AI [video]

#176

Post by guappa »

ramon156 wrote: post #172
mentalgear wrote: post #157

Meanwhile, I asked this morning Claude 4 to write a simple EXIF normalizer. After two rounds of prompting it to double-check its code, I still had to point out that it makes no sense to load the entire image for re-orientating if the EXIF orientation is fine in the first place. Vibe vs reality, and anyone actually working in the space daily can attest how brittle these systems are. Maybe this changes in SWE with more…

The real question is how long it'll take until they're not brittle

∞

Re: Andrej Karpathy: Software in the era of AI [video]

#178

Post by imiric »

It's fascinating to see his gears grinding at 22:55 when acknowledging that a human still has to review the thousand lines of LLM-generated code for bugs and security issues if they're "actually trying to get work done". Yet these are the tools that are supposed to make us hyperproductive? This is "Software 3.0"? Give me a break.

Re: Andrej Karpathy: Software in the era of AI [video]

#179

Post by ApeWithCompiler »

mentalgear wrote: post #157

Meanwhile, I asked this morning Claude 4 to write a simple EXIF normalizer. After two rounds of prompting it to double-check its code, I still had to point out that it makes no sense to load the entire image for re-orientating if the EXIF orientation is fine in the first place. Vibe vs reality, and anyone actually working in the space daily can attest how brittle these systems are. Maybe this changes in SWE with more…

A manager in our company introduced Gemini as a chat bot coupled to our documentation.

> It failed to write out our company name.The rest was flawed with hallucinations also, hardly worth to mention.

I wish this is a rage bait towards others, but what should me feelings be? After all this is the tool thats sold to me, I am expected to work with.

Re: Andrej Karpathy: Software in the era of AI [video]

#180

Post by guappa »

shakna wrote: post #167
guappa wrote: post #158

Earlier quoted context omitted.

In a way he's making sense. If the "code" is the prompt, the output of the llm is an intermediate artifact, like the intermediate steps of gcc. So why should we still need gcc? The answer is of course, that we need it because llm's output is shit 90% of the time and debugging assembly or binary directly is even harder, so putting asides the difficulties of training the model, the output would be unusable.

Probably too much snark from me. But the gulf between interpreter and compiler can be decades of work, often discovering new mathematical principles along the way. The idea that you're fine to risk everything, in the way agentic things allow [0], and want that messing around with raw memory is... A return to DOS' crashes, but with HAL along for the ride. [0] https://msrc.microsoft.com/update-guide/vulnerability/CVE-2…

Ah don't worry, llms are a return to crashes as it is :)

The other day it managed to produce code that made python segfault.

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