Architecture Document 23: Anticipatory Transformer Architecture

**Status**: Research Proposal (Revised) **Created**: 2026-01-04 **Revised**: 2026-01-04 (Incorporated engineering feedback) **Dependencies**: DELL Theory (19), Graph Kernel (15), Computational Choreography (01), TrajectoryOS (02) Current transformer architectures operate on **prediction**: given context, predict next token. This proposal introduces an **anticipatory transformer** that operates on **commitment detection**: given motion through semantic space, detect when futures become constrained enough to warrant action. **Key Insight**: Just as Comp-Core's motion intelligence detects when a gesture is irreversible (not when it completes), an anticipatory transformer should detect when semantic trajectories become committed, enabling earlier, more efficient generation. **Implementation Consequence**: Model outputs not just probabilities but **commitment scores** and **uncertainty estimates** that drive generation policy. **Problem**: "Commitment" is conceptually clear but needs a trainable target to avoid becoming a random-number generator correlated with logit sharpness.