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Aside 2: Anecdotally we found that Pi performs more or less on par with native harnesses at lower cost on decently specified prompts. It is also phenomenal at
by redmalang 2mo ago
Aside 2:
Anecdotally we found that Pi performs more or less on par with native harnesses at lower cost on decently specified prompts. It is also phenomenal at context cacheing especially on Deepseek models (its hard to precisely attribute credit here are my understanding is this is a DS speciality).
But it fails much worse on poorly drafted prompts. I'm generalising but native harnesses seem to be better kind of flailing along on those.
- swingboy 2mo agoIs it because Pi’s default system prompt is so simple?
- cyanydeez 2mo agoof course it is; these entire systems are about priming the LLM to perform X task; if it's a coding harness, giving it very little priming for a task is going to make it grasp at straws.
- sgc 2mo agoCan anybody share a tested system prompt they use for general coding tasks in pi?
- cyanydeez 2mo agoclone opencode and ask your ai yo find it. i did that then just wrote my own primary open code agent.
- sgc 2mo agoA bit late, but I followed up on this useful tip and found a gist that breaks down the opencode methodology: https://gist.github.com/rmk40/cde7a98c1c90614a27478216cc01551f https://gist.github.com/rmk40/cde7a98c1c90614a27478216cc0155... The gist led me to the opencode session / prompt control folder: https://github.com/anomalyco/opencode/tree/dev/packages/opencode/src/session https://github.com/anomalyco/opencode/tree/dev/packages/open...