Claude was able to write a NES emulator for my engine from scratch, on 3rd try
The port I couldn't ship
31–40 of 101 posts
Re: The port I couldn't ship
#32While there's not a lot of meat on the bone for this post, one section of it reflects the overall problem with the idea of Claude-as-everything: > I spent weeks casually trying to replicate what took years to build. My inability to assess the complexity of the source material was matched by the inability of the models to understand what it was generating. When the trough of disillusionment hits, I anticipate this wil…
If LLMs stopped improving today I’m sure you would be correct- as it is I think it’s very hard to predict what the future holds and where the advancements take us. I don’t see a particularly good reason why LLMs wouldn’t be able to do most programming tasks, with the limitation being our ability to specify the problem sufficiently well.
I feel like we’ve been hearing this for 4 years now. The improvements to programming (IME) haven’t come from improved models, they’ve come from agents, tooling, and environment integrations.
Re: The port I couldn't ship
#33Claude was able to write a NES emulator for my engine from scratch, on 3rd try https://github.com/willtobyte/NES
Only because humans before Claude wrote many NES emulators…
Re: The port I couldn't ship
#34While there's not a lot of meat on the bone for this post, one section of it reflects the overall problem with the idea of Claude-as-everything: > I spent weeks casually trying to replicate what took years to build. My inability to assess the complexity of the source material was matched by the inability of the models to understand what it was generating. When the trough of disillusionment hits, I anticipate this wil…
If LLMs stopped improving today I’m sure you would be correct- as it is I think it’s very hard to predict what the future holds and where the advancements take us. I don’t see a particularly good reason why LLMs wouldn’t be able to do most programming tasks, with the limitation being our ability to specify the problem sufficiently well.
LLM capability improvement is hitting a plateau with recent advancements mostly relying on accessing context locally (RAG), or remotely (MCP), with a lot of extra tokens (read: drinking water and energy), being spent prompting models for "reasoning". Foundation-wise, observed improvements are incremental, not exponential.
> able to do most programming tasks, with the limitation being our ability to specify the problem sufficiently well
We've spent 80 years trying to figure that out. I'm not sure why anyone would think we're going to crack this one anytime in the next few years.
Re: The port I couldn't ship
#35How many hours until someone else is able to get it to work? I consider myself a bit of an expert vibe engineer and the challenge is alluring :D
Looking forward to seeing how you get on ;-)
Re: The port I couldn't ship
#36Earlier quoted context omitted.
If LLMs stopped improving today I’m sure you would be correct- as it is I think it’s very hard to predict what the future holds and where the advancements take us. I don’t see a particularly good reason why LLMs wouldn’t be able to do most programming tasks, with the limitation being our ability to specify the problem sufficiently well.
I feel like we’ve been hearing this for 4 years now. The improvements to programming (IME) haven’t come from improved models, they’ve come from agents, tooling, and environment integrations.
Both is true, models have also been significantly improved in the last year alone, let's not even talk about 4 years ago. Agents, tooling and other sugar on top is just that - enabling more efficient and creative usage, but let's not undermine how much better models today are compared to what was available in the past.
Re: The port I couldn't ship
#37You don't ship a port. You ship to a port.
Re: The port I couldn't ship
#38Funny to see this show up today since coincidentally I've had Claude code running for the past ~15 hours attempting to port MicroQuickJS to pure dependency-free Python, mainly as an experiment in how far a porting project can go but also because a sandboxed (memory constrained, to us time limits) JavaScript interpreter that runs in Python is something I really want to exist. I'm currently torn on whether to actually…
You should release it, it'd be quite useful.
Re: The port I couldn't ship
#39I won't deny OP learned something in this process, but I can't help but wonder: if they spent the same time and effort just porting the code themselves, how much more would they have learned? Specially considering that the output would be essentially the same: a bunch of code that doesn't work.
That may be true, but it does seem like OP's intent was to learn something about how LLM agents perform on complex engineering tasks, rather than learning about ASCII creation logic. A different but perhaps still worthy experiment.
Re: The port I couldn't ship
#40Earlier quoted context omitted.
If LLMs stopped improving today I’m sure you would be correct- as it is I think it’s very hard to predict what the future holds and where the advancements take us. I don’t see a particularly good reason why LLMs wouldn’t be able to do most programming tasks, with the limitation being our ability to specify the problem sufficiently well.
LLM capability improvement is hitting a plateau with recent advancements mostly relying on accessing context locally (RAG), or remotely (MCP), with a lot of extra tokens (read: drinking water and energy), being spent prompting models for "reasoning". Foundation-wise, observed improvements are incremental, not exponential. > able to do most programming tasks, with the limitation being our ability to specify the proble…
> Foundation-wise, observed improvements are incremental, not exponential.
Incremental gains are fine. I suspect capability of models scales roughly as the logarithm of their training effort.
> (read: drinking water and energy)
Water is not much of a concern in most of the world. And you can cool without using water, if you need to. (And it doesn't have to be drinking water anyway.)
Yes, energy is a limiting factor. But the big sink is in training. And we are still getting more energy efficient. At least to reach any given capability level; of course in total we will be spending more and more energy to reach ever higher levels.