81–90 of 225 posts
Earlier quoted context omitted.
LLMs aren't people. They don't reason. They're token generators, a black box. Your analogy falls on its face with any scrutiny.
it's an analogy, it didnt fall on its face at all. it's just a comparison to highlight the point being made was nonsensical. example: you're just a next action generator controlled by trillions of cells and subconscious dna-based behavior. a black box.
We're working on a large Rust codebase, heavily assisted development with Claude and Codex, and one critical workflow is after you have written a spec, have the other LLM critique it thoroughly. This back and forth will take quite a while, but the resulting implementation plan will be 10x better than the original. You can automate this by giving Codex a goal, and a skill to call Claude to review the implementation sp…
I hate how seriously people take the output of an LLMs or how reliable they think it is. Have Claude produce that spec 10 times, use the same prompt and same context. Identical requests, but you'll get 10 unique answers that wil contradict each other with each response seeming extermely confident. Its scary how confident you people are in these outputs.
Earlier quoted context omitted.
If you ask 10 different humans to produce the spec with the same information (prompt and context) they will also produce 10 unique answers that will contradict each other and (depending on who you asked) may be just as confident. There are real decisions to be made when going from a vague prompt to a spec. It's not surprising that an LLM would produce different specs for the same work on different runs. If the prompt…
LLMs aren't people. They don't reason. They're token generators, a black box. Your analogy falls on its face with any scrutiny.
If the behavior of the llm is the same as the behavior of reasonable people then the behavior of the llm is reasonable, regardless of how black of a box they generate tokens out of.
Reasonable people will generate divergent specs for the same prompt. Thus it is reasonable for an LLM to generate divergent specs out of the same prompt.
Edit: I use “reasonable” here in the legal sense of the “reasonable person” standard, not to imply any reasoning process.
Earlier quoted context omitted.
If you ask 10 different humans to produce the spec with the same information (prompt and context) they will also produce 10 unique answers that will contradict each other and (depending on who you asked) may be just as confident. There are real decisions to be made when going from a vague prompt to a spec. It's not surprising that an LLM would produce different specs for the same work on different runs. If the prompt…
LLMs aren't people. They don't reason. They're token generators, a black box. Your analogy falls on its face with any scrutiny.
I assure you I've met many devs and "engineers" that reason less than LLMs, and are black boxes, especially in terms of the code they write.
Earlier quoted context omitted.
LLMs aren't people. They don't reason. They're token generators, a black box. Your analogy falls on its face with any scrutiny.
it's an analogy, it didnt fall on its face at all. it's just a comparison to highlight the point being made was nonsensical. example: you're just a next action generator controlled by trillions of cells and subconscious dna-based behavior. a black box.
With moral agency and the ability to learn (even if we presume you are correct, which I don't think you are).
We're working on a large Rust codebase, heavily assisted development with Claude and Codex, and one critical workflow is after you have written a spec, have the other LLM critique it thoroughly. This back and forth will take quite a while, but the resulting implementation plan will be 10x better than the original. You can automate this by giving Codex a goal, and a skill to call Claude to review the implementation sp…
Earlier quoted context omitted.
LLMs aren't people. They don't reason. They're token generators, a black box. Your analogy falls on its face with any scrutiny.
I didn’t claim that LLMs are people or that they reason. If the behavior of the llm is the same as the behavior of reasonable people then the behavior of the llm is reasonable, regardless of how black of a box they generate tokens out of. Reasonable people will generate divergent specs for the same prompt. Thus it is reasonable for an LLM to generate divergent specs out of the same prompt. Edit: I use “reasonable” he…
Rust code generation consumes lot of token Go is much better target, i've observed rails/ruby code is also much easier for AI to spit out. And Haskell flies with AI
Yes, but it comes with much better “built-in” guardrails to rein in the autocomplete. Especially if compared to something runtime-surprise-prone-if-lovable like Ruby.
Rust doesn't add anything over Go for LLM coding.
This is great example of AI slop and a big problem with AI coding. Original RSL library has 36 KLoC across C++ source and headers files. Rust supposed to be more expressive and concise. Yet, AI generated 130k LoCs. I guess nobody understands how this code works and nobody can tell if it actually works.