Openflows is a repeatable sequence for turning distributed input into durable shared understanding.
Method sequence
Pre-flow
Before people meet, contributions accumulate asynchronously: questions, tensions, observations, and artifacts. The objective is divergence, expanding what might matter without forcing early alignment.
Mediation
Patterning happens here. AI may assist with grouping themes or surfacing contradictions, while interpretation remains human. Significant mediation is documented so participants can see where agency sits.
Convergence
People meet in physical space for work that requires bodies: sensemaking, emotional truth, productive disagreement, and collective reframing. This is high-intensity work that cannot be reduced to presentation culture.
Synthesis
Openflows avoids false closure. Instead of definitive conclusions, synthesis captures what changed, what remains unresolved, what tensions sharpened, and which questions became clearer.
Redistribution
Fragments circulate back into communities and networks as short texts, prompts, patterns, or diagrams. The goal is continuity, so future cognition can begin from a stronger baseline.