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Human-written. I was trying to be short and straight to the point.

LLM-powered rewrites and huge refactors are better done using 1 additional step "convert the code to <something> that represents it best".

The simplest example is, for a CRUD app it can be swagger description. The more complex behaviour exhibit the app, the more raw information should be provided.

Like ontologies, "A is a child of B" model can derive and enforce that "B is a parent of A", and so on.

On top of that, I write that Fable is reasonably cheap if one uses it solely for agent orchestration.



I found this part to be interesting/clever:

1. Extract the data representation

Ask the LLM to represent your code as any combination of:

    graphs
    ontologies
    hierarchical state machines
    UML process charts
    constraints
    math formulae
2 Operate on the representations

3 Convert representations back to code


Do we think that was necessary? What would have happened if OP had just asked it to rewrite and test/validate each piece as it went until everything is verified and complete?

My gut feeling is this is doing way too much, and it would've figured it out.


But we know, Bun was 535496 lines for $165000.

The whole point of this experiment was to try and make the rewrite as cheap as possible.



True, the main problem is how to split the work. They decided to go file by file.

To be fair, I haven't try exactly "rewrite in Rust" prompt, but I cannot imagine for this to work.


converting code to more abstract and denser representations and then manipulating them makes sense to me. Finding better representations is like half of mathematics.


Is code being converted to / represented in maths that much more helpful for an LLM that deals in language primarily, by definition? I have no idea, interesting though!


this is the meat, yes.


honestly it is hard to believe that seeing your replies and this heading: "The secret sauce".

Giving the benefit of doubt, we all might be writing a bit like claude nowadays.

If that is the case, I'd recommend reviewing the content before publishing to see if it sounds like a LLM.

Or if you are trying to create "better" AI slop and think that is enough to say the text is human-written, don't do that, just say it was AI-generated or assisted.


I wrote this elsewhere. Reading so much LLM output may have affected how I write.

Probably I need some fresh air and a good fiction book.


We'll all be writing this way before long ...




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