Thursday, April 2, 2026

Enhanced AI Agent Waste Reporting for Structural Observations: Loop Detection and Failure Prediction at Step 10 (AUC = 0.814) – Validated on 80K Real Sessions | caum.systems · GitHub

Unlocking Enhanced AI Performance with CAUM

CAUM is a cutting-edge observation layer for AI agents, designed to detect inefficiencies like loops, stagnation, and wasted compute—without analyzing prompts or payloads. It’s all about structural observation!

Key Features:

  • Comprehensive Monitoring: Tracks tool call diversity, trajectory geometry, and regime transitions.
  • No Decision-Making: CAUM strictly records data, empowering you with insights without bias.
  • Validated Efficiency: Tested on 80,036 real agent sessions, delivering impressive metrics:
    • AUC @ full session: 0.814
    • Compute savings: $1.7M/year with 10K runs/day.

Implementation Modes:

  • Forensic Analysis: Batch analysis for compliance.
  • Live Monitoring: Real-time alerts with webhooks.
  • Enterprise SDK: Seamless integration into your infrastructure.

Experience the future of AI efficiency! Upload your trajectory today for a free structural observation report at caum.systems/upload.

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