The Importance of LLM Monitoring
Автор: AnswerRocket
Загружено: 2025-10-09
Просмотров: 18
Описание:
Your AI system passed all your test cases, so you deployed it to production. But here's what most teams miss: they only tested the questions they expected to work. They never provoked the system, never looked for boundaries, never checked if failures were stacking up across multiple interactions.
In this essential discussion, the gang reveals why monitoring AI in production is like checking in on a teenager—you need to look beyond what they tell you. You'll discover why subtle failures compound over multi-turn conversations, how to detect drift before it becomes a crisis, and why visibility into every step of an agent's reasoning is critical for maintaining quality over time.
In this video, you'll learn:
✅ The teenager analogy: Why surface-level monitoring misses critical issues
✅ Why you must test the "anti questions"—things you expect to fail
✅ How tiny errors stack across multiple agent turns (the telephone game effect)
✅ The difference between active monitoring and passive check-ins
✅ Why monitoring start and end points isn't enough for complex agents
✅ Building test harnesses that detect drift and outliers in real-time
Follow the Gang
Mike Finley, CTO, AnswerRocket - / mikefinley
Pete Reilly, COO, AnswerRocket - / petereilly
Andy Sweet, VP Enterprise AI Solutions, AnswerRocket - / andrewdsweet
Stew Chisam, Operating Partner, StellarIQ - / stewart-chisam-7242543
Chapters:
00:00 The Teenager Test: Looking Beyond Surface Answers
01:29 Active Maintenance: What Production AI Really Requires
01:43 Automated Evals vs. Real-World Monitoring
02:30 The Stacking Failure Problem: When Small Errors Compound
03:45 Chain Visibility: Why You Must Monitor Every Turn
How are you monitoring your AI systems in production? What's caught you by surprise?
#AIMonitoring #ProductionAI #AIQuality #AgenticAI #MLOps #AITesting #ModelDrift
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AI, Actually is produced by AnswerRocket. Since 2013, our enterprise AI solutions have helped Fortune 500 companies achieve measurable results through their AI transformations. This podcast is where we share what we’ve learned.
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