3 ms·

what did i read? genuinely? its only a few words, and even that had to be AI written. The topic in the title barely was mentioned.

aka-rider 25d ago
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.
- UltraSane 25d ago
  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
  - aka-rider 25d ago
    this is the meat, yes.
  - richstokes 25d ago
    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.
    - aka-rider 25d ago
      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.
      - never_inline 24d ago
        Oh no, bun had quite a bit of machinery: https://bun.com/blog/bun-in-rust#loops-that-write-review-code https://bun.com/blog/bun-in-rust#loops-that-write-review-cod...
        aka-rider 24d ago
        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.
    - UltraSane 25d ago
      converting code to more abstract and denser representations and then manipulating them makes sense to me. Finding better representations is like half of mathematics.
      - richstokes 23d ago
        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!
- brazukadev 25d ago
  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.
  - aka-rider 25d ago
    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.
    - abrookewood 24d ago
      We'll all be writing this way before long ...
whateveracct 24d ago
pangram says 100% human

aka-rider 25d ago

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.

UltraSane 25d ago
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
- aka-rider 25d ago
  this is the meat, yes.
- richstokes 25d ago
  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.
  - aka-rider 25d ago
    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.
    - never_inline 24d ago
      Oh no, bun had quite a bit of machinery: https://bun.com/blog/bun-in-rust#loops-that-write-review-code https://bun.com/blog/bun-in-rust#loops-that-write-review-cod...
      - aka-rider 24d ago
        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.
  - UltraSane 25d ago
    converting code to more abstract and denser representations and then manipulating them makes sense to me. Finding better representations is like half of mathematics.
    - richstokes 23d ago
      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!
brazukadev 25d ago
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.
- aka-rider 25d ago
  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.
  - abrookewood 24d ago
    We'll all be writing this way before long ...

whateveracct 24d ago

pangram says 100% human