Comment by jvuygbbkuurx

15 days ago

Isn't this the whole reason they became viable in the last 6 months? The system prompt and harness is improving. It's less and less essential every day to roll your own.

9 comments

jvuygbbkuurx

Reply
embedding-shape  15 days ago

I don't think there is a single reason. Models are improving, so are the harnesses, prompts and we who use them a lot also get more proficient and learn where they can be used effectively vs not, so lots of improvements all over the ecosystem, brought together.

Latest big change is probably how feasible local models are becoming, like Qwen 3.6 and Gemma 4, they're no longer easily getting stuck in loops and repetition, although on lower quantizations they still pretty much suck for agentic usage.

  • deadbabe  15 days ago

    > we who use them a lot also get more proficient and learn where they can be used effectively vs not

    I think it’s always been obvious where an LLM could be used effectively and where it cannot, if you understand how they work and don’t see them as magical.

    The “increase in proficiency” is mostly people coming back to reality and being more intentional about LLM usage. There are no surprise discoveries here. One does not need to use an LLM a lot to get effective with them. A total noob could become effective on day 1 with proper guidance.

    • ofjcihen  15 days ago

      I think you hit the nail on the head. I had been in this space for a little bit before it really became popular. I haven’t seen incredible gains in model competency. What I have seen though is people figuring out what works and what doesn’t.

      4 replies →

ekidd  15 days ago

The models also have far more intelligence built in. For example, the pi.dev agent harness has a system prompt which fits on a single page, and includes only 4 or 5 tools. Running with a small coding model like Qwen3.6 27B, this setup is completely capable of agentic coding.