It is explicitly not a foreman, task routing, or an orchestrator agent. It has a bias toward direct action and is instructed to only delegate when necessary.

I've found that this approach yields significantly faster results, without much of a quality trade-off, than an agent whose primary impulse is to delegate.

In contrast, HydraFusion starts with a task routing step, then sequential planning, execution, and review stages. My guess is that this workflow is best for people who are prioritizing cost over speed for the same level of quality.

Multiple model vendors is key here, the cascade pattern doesn't need it, but the critique pattern does.

Last Nov, my team wrote a paper ("Team of Rivals") on the difference between using an OpenAI model to Critique an Anthropic model's output vs running a self-review agent loop on the same vendor.

The ablations [1] proved that neither company alone was better than using both.

The paper was a general response to "What does your company do that Anthropic can't?" but more so a demonstration of how to make something 90%+ good with models which eval at 60% or so (& Gas Town post unblocked our "this is a trade secret" argument about the paper).

[1] - https://github.com/t3rmin4t0r/critique-evals