Intelligence - Optimization Loop

Recursive Self-Improvement (RSI)

RSI is the automated mechanism that prevents AI system entropy and ensures the platform gets smarter with every build.

Observe

Analyzes entries in the Evidence Ledger to identify successful vs failed build patterns.

Synthesize

Generates updated prompt primitives and hypervector weights based on human approval signals.

Optimize

Applies optimizations back to core engines (Forge, Sentinel, P-Axis) in real-time.

Fighting AI Entropy

Without RSI, AI systems tend to degrade as they encounter "drift"—changes in codebase conventions or model API updates. AGI-HIVE's RSI loop acts as a counter-force, continuously recalibrating the collective intelligence to match the latest engineering standards.

✓ Prevents operational drift
✓ Learns custom team conventions
✓ Reduces hallucination rates
✓ Increases build confidence scores

How It Works

The RSI pipeline runs prompt mutation, eval suites, and Sentinel-gated acceptance testing. Efficiency metrics are tracked per-cycle in the Evidence Ledger and displayed on the RSI engine dashboard.