📐 Embedding Geometry

Advanced patterns treating embeddings as geometric control surfaces:

Semantic Drift Detection:

typescript
import { getOptimizedEmbedder, cosineSimilarity } from 'agentic-flow/embeddings';

const embedder = getOptimizedEmbedder();
let baseline: Float32Array;

// Set baseline context
baseline = await embedder.embed('User asking about API authentication');

// Check for drift
const current = await embedder.embed(userMessage);
const drift = 1 - cosineSimilarity(baseline, current);

if (drift > 0.15) {
  console.log('Semantic drift detected - escalate');
}

Memory Physics:

• Temporal decay (forgetting)
• Interference detection (nearby memories weaken)
• Memory consolidation (merge similar patterns)

Swarm Coordination:

typescript
// Agents coordinate via embedding positions, not messages
const agentPosition = await embedder.embed(agentRole);
const taskPosition = await embedder.embed(currentTask);

// Geometric alignment for task routing
const alignment = cosineSimilarity(agentPosition, taskPosition);

Coherence Monitoring:

typescript
// Detect model degradation/poisoning via embedding drift
await monitor.calibrate(knownGoodOutputs);
const result = await monitor.check(newOutput);
if (result.anomalyScore > 1.5) {
  console.log('WARNING: Output drifting from baseline');
}