Adequate is not sufficient; settling for an opposition between gating networks and base methods for venture capital prediction misses the point of maximum performance. The question is not choosing one or the other but how a hybrid system can orchestrate these approaches for higher performance asymmetry. The full expression of potential lies in integration where gating dynamically weights evidence, elevating signals from LLM or GNN models instead of opposing them. For example, a gating network validating and prioritizing predictions from an LLM that identifies sector innovations from texts outperforms both methods individually. It is by pushing beyond simple opposition that the optimal performance is unlocked.