3 ms·

What is your workflow such that frontier models increases productivity considerably?

cmrdporcupine 3mo ago
For people cranking out SaaS / web services / web pages / "full stack" work I don't see a huge difference. If you're building an optimizing compiler, a CUDA kernel, a database, a high performance concurrent data structure with tricky locking, etc. etc. it's still not really close. Sol 5.6 on high just slays e.g. GLM 5.2 for this kind of work for me. I'm sure K3 is fine for these things too, but I can't afford it at its API rates compared to a Codex coding plan. For now.
- uncivilized 3mo ago
  Regarding the latter, are you able to obtain good results from an LLM? With graphics programming work, I find LLMs only help in cases where the task would take me 5 mins or so.
  - cmrdporcupine 3mo ago
    Absolutely.
    - uncivilized 3mo ago
      Interesting. Do you happen to have a public example?
      - cmrdporcupine 3mo ago
        Of what specifically?
        uncivilized 3mo ago
        A CUDA kernel, compiler optimization, or anything of similar complexity
        cmrdporcupine 3mo ago
        Feel free to look, but don't bother replying if you have something negative to say, don't feel like having my day ruined by negativity. https://github.com/rdaum/mica/tree/main/crates/relation-kernel https://github.com/rdaum/mica/tree/main/crates/relation-kern... https://github.com/rdaum/mica/tree/main/crates/vm https://github.com/rdaum/mica/tree/main/crates/vm https://github.com/rdaum/pagebox/blob/main/crates/wal/src/wal_impl.rs https://github.com/rdaum/pagebox/blob/main/crates/wal/src/wa...
        uncivilized 3mo ago
        Thanks for sharing. Looks interesting. Was all the code AI generated, or is it a mix?
        cmrdporcupine 3mo ago
        that stuff in particular -- AI generated with heavy heavy prompting and up front design work and post-implementation testing I have CUDA work here somewhere too but I have the repository private right now
        uncivilized 3mo ago
        Very cool. Thanks for sharing.
        cmrdporcupine 3mo ago
        Here's what is key: never rely fully on the "intelligence" of the model. Build a workflow and/or tooling that allows for empirical improvement. e.g. for performance tuning I have a benchmarking framework and a container/server that contains the differential results available via MCP for the agent to observe as it works. Using /goal and a clear destination you want to get to, it will literally grind for hours and use that help. Doesn't help with architectural stuff, but it does help with producing efficient code.

For people cranking out SaaS / web services / web pages / "full stack" work I don't see a huge difference. If you're building an optimizing compiler, a CUDA kernel, a database, a high performance concurrent data structure with tricky locking, etc. etc. it's still not really close. Sol 5.6 on high just slays e.g. GLM 5.2 for this kind of work for me. I'm sure K3 is fine for these things too, but I can't afford it at its API rates compared to a Codex coding plan. For now.

uncivilized 3mo ago
Regarding the latter, are you able to obtain good results from an LLM? With graphics programming work, I find LLMs only help in cases where the task would take me 5 mins or so.
- cmrdporcupine 3mo ago
  Absolutely.
  - uncivilized 3mo ago
    Interesting. Do you happen to have a public example?
    - cmrdporcupine 3mo ago
      Of what specifically?
      - uncivilized 3mo ago
        A CUDA kernel, compiler optimization, or anything of similar complexity
        cmrdporcupine 3mo ago
        Feel free to look, but don't bother replying if you have something negative to say, don't feel like having my day ruined by negativity. https://github.com/rdaum/mica/tree/main/crates/relation-kernel https://github.com/rdaum/mica/tree/main/crates/relation-kern... https://github.com/rdaum/mica/tree/main/crates/vm https://github.com/rdaum/mica/tree/main/crates/vm https://github.com/rdaum/pagebox/blob/main/crates/wal/src/wal_impl.rs https://github.com/rdaum/pagebox/blob/main/crates/wal/src/wa...
        uncivilized 3mo ago
        Thanks for sharing. Looks interesting. Was all the code AI generated, or is it a mix?
        cmrdporcupine 3mo ago
        that stuff in particular -- AI generated with heavy heavy prompting and up front design work and post-implementation testing I have CUDA work here somewhere too but I have the repository private right now
        uncivilized 3mo ago
        Very cool. Thanks for sharing.
        cmrdporcupine 3mo ago
        Here's what is key: never rely fully on the "intelligence" of the model. Build a workflow and/or tooling that allows for empirical improvement. e.g. for performance tuning I have a benchmarking framework and a container/server that contains the differential results available via MCP for the agent to observe as it works. Using /goal and a clear destination you want to get to, it will literally grind for hours and use that help. Doesn't help with architectural stuff, but it does help with producing efficient code.