community_stress_test_v2
stress_test.
proposals.
before_launch.
Arena is a multi-agent simulation that models how a community might respond to your project. It uses real demographic data to create statistically accurate virtual personas who interact, share concerns, and develop sentiment over time.
Identify friction points, discover hidden concerns, and benchmark your engagement strategy in a controlled digital wind-tunnel.
tick_interval
15min → 4hrs sim
simulation_horizon
days-to-weeks
agent_backbone
web + scopomap + news
persona_activation
event-driven hooks
active_simulation_monitor
Registry loaded and waiting. Launch a scenario to see live simulation data.
observer_state
standby
no persisted benchmark run yet
configured_models
9
arena registry available
surface_mode
watch_first
ui replaces route-level inspection
backend_infrastructure
02_how_it_works
from_census_to_sentiment
Step 1
Scenario Definition
Planners define a scenario by providing a proposal and selecting a study area. This 'blueprint' serves as the foundation for the simulation.
Step 2
Persona Synthesis
Arena generates a statistically accurate cohort of virtual personas reflecting the local community's unique demographic profile.
Step 3
Autonomous Simulation
Personas interact with the proposal and each other on their own schedules, surfaces authentic community sentiment and friction points.
Step 4
Political Risk Scoring
The system identifies key risks, including polarization and trust collapse, allowing planners to iterate before going live.
the_persona_logic.
We don't just simulate 'people'. We simulate statistically grounded residents. Each persona carries an activity schedule, specific housing status, and core values derived from the actual demographics of the study area.
{
"persona_id": "SA1_045_A",
"name": "Liam",
"age": 32,
"housing_status": "Renting",
"occupation_category": "Professional",
"core_value": "Walkability and public transport access",
"baseline_emotions": {
"anger": 2,
"sympathy": 5,
"excitement": 6
},
"activity_schedule": {
"morning": ["reads_local_paper", "checks_email"],
"evening": ["checks_facebook", "attends_town_halls"],
"channel_preferences": ["facebook", "letterbox", "qr_code"]
},
"communication_style": "Concise, slightly cynical, uses modern slang"
}03_scoring_metrics
quantifying_community_impact
Risk Assessment
Political Risk
A composite index measuring the likelihood of project delay or cancellation due to community opposition.
Social Cohesion
Polarization
Tracking how much the proposal is dividing the community into opposing camps vs. finding common ground.
Sentiment Drift
Trust Velocity
Measuring the rate at which community trust is being built or eroded over the course of the engagement.
Inclusion
Demographic Hit
Verifying if all segments of the community are being heard, or if certain groups are being left out.
our_methodology
No 'Black Box' results—every agent thought and reaction is traceable and inspectable.
Grounded in Census data—personas aren't random; they are statistically representative of the area.
Designed for practitioners—the goal is to find friction points before they become real-world crises.
ready_to_observe?
The observer console provides a real-time view into the simulation. Watch agents post, track sentiment drift, and identify political risks before they manifest in the real world.