ReAct is a common agent loop. What's the standard for System One decision models (Jev or a local alternative) + an LLM + tool calling? The examples I've been reading seem to split in two directions: confidence cascades in REFLEX and JevAgentHarness, and planner + chooser in the Hermes/Astra + Jev Minecraft agents. Is there an accepted pattern yet, or are these still separate approaches? I'm interested in the control loop: who creates the candidate actions, when the LLM replans, and when a low-confidence decision falls back to it. For anyone using local decision models alongside a larger LLM, what architecture has actually been useful? Papers or public implementations would help. References: REFLEX: https://arxiv.org/abs/2609.26532 JevAgentHarness: https://arxiv.org/abs/2610.21412 Hermes + Jev: https://github.com/teknium1/hermes-and-jev-play-minecraft Astra + Jev: https://github.com/rmalde/minecraft-agent English wording refined with AI.   submitted by   /u/emersoftware [link]   [comments]