Traditional SRE metrics—availability, latency, error rate—measure whether systems are up, not whether they’re useful. A 99.4% uptime dashboard once masked an AI agent returning HTTP 200s while generating unusable reports, a silent regression from a cheaper model swap. This gap between infrastructure health and task completion drives the three-layer SLO …
Editorial team 
Multi-Agent Reliability: 85% Per Step, 20% at Step 10
The Compound Failure Equation Here is the math that most teams deploying multi-agent AI systems have never computed: if each agent step succeeds 85% of the time — a rate most vendors would call impressive — a 10-step workflow completes successfully just 19.7% of the time. That is 0.8510 = …
Context Engineering: Why AI Agents Fail at Step 47
o3 Drops 34 Points Across Turns OpenAI’s o3 model scores 98.1 on single-turn benchmarks. Distribute the same information across multi-turn exchanges — the way actual agents work — and that score collapses to 64.1. That’s a 34-point absolute drop, and it’s not an outlier. Across all tested models, multi-turn context …