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Structural observation for AI agents. Detects loops and predicts failure at step 10 with AUC=0.814. Validated on 80K real sessions. caum.systems
1 stars
CAUM – 80K AI agent sessions analyzed. 88.7% loops fail. AUC=0.814
by Caum·Apr 1, 2026·1 point·0 comments
AI Analysis
●●SolidBig BrainNiche Gem
Predicts agent failure at step 10 without reading prompts or payloads.
Strengths
- •80K real session validation across Llama 8B, 70B, and 405B models.
- •Structural observation preserves privacy by not inspecting prompts or data.
- •Five metrics like Tool Coherence Ratio provide actionable debugging signals.
Weaknesses
- •Research findings without a production-ready monitoring tool to integrate.
- •No clear integration path for existing agent frameworks like LangChain.
Category
Target Audience
AI researchers and agent platform builders
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