I’ve been experimenting with two things on this:

- multi-model consensus, with multiple cross-review rounds. Obviously, the number of inference tasks explodes with the number of models. Led to some interesting results [^0].

- giving an agent "stray thoughts" produced by the same model, or another, giving the second model a selection of the agent’s context, with different triggers (random, loop detection,…)[^1]. So far has proven very helpful and much cheaper than the first.

[0]: https://github.com/lightless-labs/refinery

[1]: https://github.com/Lightless-Labs/skunkworks/tree/main/flux