71–80 of 225 posts
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Honestly Rust is an UGLY language. For whatever powers it possesses in memory safety, its cryptic symbology is reminiscent of assembly. This is a problem when language designers are mathematicians and don’t understand typographical nuance and visual weights.
To me it looks clean and concise
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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.
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…
Earlier quoted context omitted.
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.
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…
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tsz is an experiment in giving coding agents full control. On my day job I am a lot more careful. But I've moved on from manually approving every change and instead review the final diff. I noticed manually approving was counterproductive.
Right, I'm giving my agents full control too, but not sure why that'd exclude putting them in a sandbox?
Earlier quoted context omitted.
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.
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…
What has always mattered is how you decide the specs, not the specs in themselves.
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.
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Have you split your 100k loc codebases into smaller crates? If you take a look at eg gitoxide's repo, they've split it in many smaller crates. I think that might help with keeping the scope for the ai small and maybe help with keeping contracts tight and well-defined.
Yes, that absolutely helps (and yes, doing that :) ), I'm going even further and basically hard-enforcing a LOC limit per file too, which helps a lot as well. The complexities LLMs end up putting themselves in is more about the bigger architecture/design of the program, rather than concrete lines, where things end up so tangled that every change requires 10s of changes across the repository, you know, typical "avoid…
this. create pre-commit hooks that enforce project conventions, code quality checks, and regression testing. it saves you so much headache
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.
Lessons. There's no such thing as learnings.
A lesson would be a specific learning activity happening at a specific place and time, administered by a person more knowledgeable than you; like a teacher or mentor "giving a lesson". If you're fine with the generalized form "learned a lesson", then surely "learnings" is fine too. There's no point in trying to police a completely normal and sensible use of language.
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.