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JacqOS replaces autonomous observe-decide-act loops with candidate and proposal relays gated by ontology rules and shared derived state.
Where this approach helps
ReAct loops are effective when the goal is broad tool exploration with relatively soft failure costs.
Teams can learn quickly when they do not yet need strong replay, audit, or authority boundaries.
Where it breaks down
Once the loop owns observation, planning, and action, it is hard to separate good reasoning from dangerous authority.
The causal path is often smeared across prompts, tool calls, and mutable scratchpads.
Each agent develops its own working story about the world instead of reading one durable truth surface.
What JacqOS changes
The core difference is not cosmetic. JacqOS changes the system's authority model so the LLM can participate without becoming the unbounded driver of truth and action.
Model interpretations of the world stay provisional until the ontology accepts them.
Model-generated actions stay proposals until explicit domain rules ratify them.
Real-world execution comes back into the system as new observations, keeping truth append-only and replayable.
You want a flexible reasoning loop and the cost of a wrong action is low enough to absorb.
You need the model inside the system, but you do not want the model to be the system's authority boundary.
Technical walkthrough of candidate and proposal relays.
Explore → Related path Compare OverviewSee the broader category-level framing before the deep dive.
Explore → Related path Healthcare OperationsA concrete example of candidate facts and human acceptance in practice.
Explore →Next step
Category language is useful, but conviction usually comes from a specific example or evaluation path. Take the comparison into something inspectable.
