Once I had the basics bootstrapped, it was really a matter of getting tests passing, and then getting more and more libraries to run on it which allowed me to exercise their own tests. And that's what really made the whole thing possible. It's sort of the ideal scenario where you have very well specified inputs and outputs, and a ton of existing tests to ensure you are implementing the behaviors correctly.
The only other aspect here is performance, and that's addressed by having an extensive benchmark harness which compares with JVM timings. This allows me to see where performance gaps are, and focus on addressing them.
I would be careful in extending my experience of being able to port Clojure to Chez Scheme runtime to working with LLMs in general because in most cases you don't have such well defined parameters when you start.
I love the expression "the hammock time has already been spent": it is actually very accurate and I'm very grateful to the Clojure team and community for spending that time!
However, you're right to point out that the development is moving really fast.
I'm building a Clojure compiler for machine learning (https://github.com/sheaf-lang/sheaf), and after 9 months, it's still very far from being production-ready.
If a dev is competent and has enough experience actually writing code and making good design decisions, I see no reason to judge their work on the basis of what tools they used to get the job done. However, it may still put me off, since I find it hard to value LLM-written code the same way I value human-written code, even though it may be equally good or even better in quality.
What would you call 2k commits in 2 months by a single committer if not slop?
I don't think "2k commits in 2 months" is enough to dismiss as slop when it's being developed by a competent Clojure dev.
One very quick "slop or not?" test is to see if em dashes are used in the source code where they literally never make sense. It's not a great test, but it's one that consistently turns out to be good enough. The results should speak for themselves: https://github.com/search?q=repo%3Ajolt-lang%2Fjolt+%E2%80%9...
But in my case I think there are levels. In this case, the author has the expertise needed to properly design the work and assess the quality of the output. And it seems they intend to maintain and evolve the library actively and long term.
Would I prefer a serious Clojure on chez that's all hand-written, for sure, but beggars can't be choosers.
If you have specific comments about the quality of the code then I'd be happy to discuss that. Attacking other people's work because they used tools you don't understand is just toxic trolling. And the fact that you judge code quality by the number of em dashes in the comments really speaks volumes.
Maybe spend a bit of time figuring out how to use new tools effectively instead of harping on what other people are doing.
It's very telling that whenever somebody starts braying about slop, they never have anything of substance to say. All the noise you add to discussions people are trying to have is the real slop.
> What would you call 2k commits in 2 months by a single committer if not slop?
Productivity. Slop is when you push a huge volume of garbage or mediocre stuff, no?
The caveat is that this isn't typical AI slop. The author knows the subject deeply, designed the system themselves, has extensive Clojure test suites to validate against, and has basically been working on it 24/7.
Can you trust it like a compiler someone spent 7 years writing and knows line by line? Probably not. But it's closer to alpha software than useless slop. As more people use it, we'll find out how robust it is, and whatever issues exist can be fixed as they're found.
So ya, I agree you shouldn't be asked to review AI generated code the author didn't review themselves. I think the ask here is more to try it and see how complete and robust it actually is. And even that only makes sense because the author is a known expert who appears to be steering the model carefully.