> Then spin up a new agent to decide which approach of the three is best on the merits. Repeat this analysis in fresh contexts and sample until there is clear consensus on one.
If there are several agents doing analysis of solutions, how do you define a consensus? Should it be unanimous or above some threshold? Are agents scores soft or hard? How threshold is defined if scores are soft? There is a whole lot of science in voting approaches, which voting approach is best here?
Is it possible for analyzing agents to choose the best of wrong solutions? E.g., longest remembered table of FizzBuzz answers amongst remembered tables of FizzBuzz answers.
We have a voting algorithm that we use, but we're not at the level of confidential disclosure if we proceed further in this discussion. There's lots of research out there into unbiased voting algorithms for consensus systems.
You conveniently decided not to answer my question about quality of the solutions to vote on (ranking FizzBuzz memorization).
To me, our discussion shows that what you presented as a simple thing is not simple at all, even voting is complex, and actually getting a good result is so hard it warrants omitting answer altogether.
I had no expectations at all, I just asked questions, expecting answers. At the very beginning the tone of your comment, as I read it, was "agentic coding is nothing but simple, look they vote." Now answers to simple but important questions are "confidential IP."
Okay then, agentic coding is nothing but complex task requiring knowledge of unbiased voting (what is this thing really?) and, apparently, use of necessarily heavy test suite and/or theorem provers.
Is it possible for analyzing agents to choose the best of wrong solutions? E.g., longest remembered table of FizzBuzz answers amongst remembered tables of FizzBuzz answers.