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Every company now has thousands of agents trying to get work done, and almost none of them know what the organization actually knows. Organizational context is a big data problem with its own 4Vs. What a context engine is, the five attributes that define

Early Prototyping ExperimentsPrototyping (through tools like Lovable, V0, Replit, etc) went through two failed framings for us.First, we treated prototyping as

Every data integration effort historically required an ontology - slow to build, locking clients out of their own system, never truly self-service. AI changes that equation: continuous ingestion into living documents, agent-managed pruning, and a deep gra

Organizational knowledge has no authoritative home, so the same questions get re-answered, re-discovered, and re-explained by the people who can least afford the interruption. Naming the category: what a knowledge warehouse is, the five attributes that de

An explanation of how we store external prototypes in the warehouse and what it took to get there.

CRDTs converge; they do not coordinate. That distinction becomes critical the moment an AI agent joins the editor. Why multiplayer collaboration needs a coordination layer above merge, and the section-level lease protocol we built to keep agents well-mann