WingNews logo WingNews
top | item 43308534

(no title)

slooonz | 11 months ago

I decided to try seriously the Sonnet 3.7. I started with a simple prompt on claude.ai ("Do you know claude code ? Can you do a simple implementation for me ?"). After minimal tweaking from me, it gave me this : https://gist.github.com/sloonz/3eb7d7582c33e95f2b000a0920016...

After interacting with this tool, I decided it would be nice if the tool could edit itself, so I asked (him ? it ?) to create its next version. It came up with a non-working version of this https://gist.github.com/sloonz/3eb7d7582c33e95f2b000a0920016.... I fixed the bug manually, but it started an interactive loop : I could now describe what I wanted, describe the bugs, and the tool will add the features/fix the bugs itself.

I decided to rewrite it in Typescript (by that I mean: can you rewrite yourself in typescript). And then add other tools (by that: create tools and unit tests for the tools). https://gist.github.com/sloonz/3eb7d7582c33e95f2b000a0920016... and https://gist.github.com/sloonz/3eb7d7582c33e95f2b000a0920016... have been created by the tool itself, without any manual fix from me. Setting up the testing/mock framework ? Done by the tool itself too.

In one day (and $20), I essentially had recreated claude-code. That I could improve just by asking "Please add feature XXX". $2 a feature, with unit tests, on average.

discuss

order

WD-42|11 months ago

So you’re telling me you spent 20 dollars and an entire day for 200 lines of JavaScript and 75 lines of python and this to you constitutes a working re-creation of Claude Code?

This is why expectations are all out of whack.

BeetleB|11 months ago

That amount of output is comparable to what many professional engineers produce in a given day, and they are a lot more expensive.

Keep in mind this is the commenters first attempt. And I'm surprised he paid so much.

Using Aider and Sonnet I've on multiple occasions produced 100+ lines of code in 1-2 hours, for under $2. Most of that time is hunting down one bug it couldn't fix by itself (reflective of real world programming experience).

There were many other bugs, but I would just point out the failures I was seeing and it would fix it itself. For particularly difficult bugs it would at times even produce a full new script just to aid with debugging. I would run it and it would spit out diagnostics which I fed back into the chat.

The code was decent quality - better than what some of my colleagues write.

I could probably have it be even more productive if I didn't insist on reading the code it produced.

slooonz|11 months ago

2200 lines. Half of them unit tests I would probably have been too lazy to write myself even for a "more real" project. Yes, I consider $20 cheap for that, considering:

1. It’s a learning experience 2. Looking at the chat transcripts, many of those dollars are burned for stupid reasons (Claude often fails with the insertLines/replaceLines functions and break files due to miss-by-1 offset) that are probably fixable 3. Remember that Claude started from a really rudimentary base with few tools — the bootstrapping was especially inefficient

Next experiment will be on an existing codebase, but that’s probably for next weekend.

Silhouette|11 months ago

Thanks for writing up your experience and sharing the real code. It is fascinating to see how close these tools can now get to producing useful, working software by themselves.

That said - I'm wary of reading too much into results at this scale. There isn't enough code in such a simple application to need anything more sophisticated than churning out a few lines of boilerplate that produce the correct result.

It probably won't be practical for the current state of the art in code generators to write large-scale production applications for a while anyway just because of the amount of CPU time and RAM they'd need. But assuming we solve the performance issues one way or another eventually it will be interesting to see whether the same kind of code generators can cope with managing projects at larger scales where usually the hard problems have little to do with efficiently churning out boilerplate code.