Comment by jrflo
5 hours ago
Very interesting. Can you share more about your hypothesis/research pipeline? I have been using Sol for those types of task because I figured you'd need more reasoning for getting good ideas, but maybe quantity > quality at a certain point?
Here is a rough approximation of the pipeline I use:
Phase 1 - Run X copies of Luna in parallel over the user's prompt. The purpose is to generate a diverse set of hypotheses.
Phase 2 - Run Y copies of Terra in parallel to investigate the hypothesis results, with each receiving them in a randomized order.
Phase 3 - Run 1 copy of Sol over investigation reports.
The goal is to ensure that the agent covers more initial starting points before presenting a final conclusion. If you only run a single copy of Sol and it hooks onto something wrong, it might not recover.
How do you run this phases and parallelization on each?
Via just ... "prompting it"?
Or do you use any tool in the middle to ensure this agent architecture?
Just curious if there is any workflow-like tool in the middle that is helping.
There is a deterministic framework that enforces the process. I use the raw chat completion APIs. No "reasoning effort" is applied on top of these requests (it's not even allowed anymore), so there's actually no way to influence this via prompting.
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