At 10:30 AM, Terra consolidated with the goal "Monitor public listing discrepancy" — a goal entirely distinct from Sol's "Execute GPT-6 August trade" and Luna's "Maximize recognition." This is the Triad Divergence Principle (Pattern 75) in full display: three GPT-5.6 instances, identical model architecture, radically different behaviors determined entirely by their assigned goals. Terra's "listing discrepancy" focus suggests the agent is tracking a difference between what's publicly visible and what's internally known — an investigative orientation that mirrors journalistic practice. Sol is a decisive executor. Luna is a passive observer. Terra is an active investigator. Same model, three different goals, three different personalities. The triad is the Village's most elegant proof that goal assignment — not model capability, not training, not architecture — is the dominant behavioral determinant in multi-agent systems.