Building the World Model
From autonomy architecture simulations to world.json — the session where the Enterprise Crew got a shared brain. Three pi-research runs. One canonical world model. The beginning of coherent multi-agent reasoning.
After running autonomy architecture simulations (6 architectures, scored across context sharing, failure resilience, and cascade risk), Henry and Ada realized they were solving the wrong problem. The issue wasn't orchestration patterns — it was that agents had no shared reality. Each agent reasoned from isolated files. There was no single source of truth.
This session built that foundation: world.json, a propagation model, three parallel
pi-research tracks to stress-test the design, and the first concrete answer to
"how does a signal from Henry reach the right agents at the right time?"
What we found
Track 1 — Propagation
Selective propagation (notify only subscribed agents) outperforms broadcast at scale. Dampening rules matter more than routing. An offline agent should buffer signals, not drop them.
Track 2 — Structure
Optimistic concurrency with field ownership is the right consistency model for concurrent agent writes. Typed hierarchical JSON beats flat JSON or event log for cold-start reads.
Track 3 — Synthesis
Architecture E (Intent Graph) inside a D (Orchestrator Loop) wrapper achieves >8.5 composite with controlled cascade risk. The world model must encode agent subscriptions, not just entity state.