May 7
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#aiagents #guardianagents #aisupervision #aichatbot #aiobservability #observability #llms #agentmanager #aimanager AI Agent Observability is Not Enough. They Need Active Supervision. Like all software, observability is also used for AI agents to tell you when there are functional errors and simple monitoring alerts. But AI agents operate differently, being probabilistic vs. deterministic, so typical observability approaches aren’t sufficient. In this discussion, Wayfound’s CEO and co-founder Tatyana Mamut describes why you need to go beyond just observability for AI agents and bring in active supervision from a guardian agent solution. Timestamps of the discussion: 01:00 = What is observability as it applies to AI agents? 02:00 = Why observability falls short for managing agents and creates unnecessary burdens on humans 03:14 = When does it become clear you need more than basic observability and pull in a guardian agent solution? Thinking about AI agents like managing employees. 04:55 = What a guardian agent solution brings that observability doesn’t and validation from Gartner. 05:51 = Examples of benefits customers see from active, guardian agent supervision vs. just simple observability, including 3X time to deployment and high confidence in agent performance especially for compliance. 08:32 = Making a build vs. buy decision for active agent supervision and why it’s not feasible to try to DIY this vs. choosing a solution on the market like Wayfound. For those relying on traditional observability approaches applied to AI agents, they will be in for surprises when it falls short. Active, guardian agents from Wayfound provide the performance supervision and closed-loop continuous improvement that can be managed by non-technical users and with minimal burden. Read the cost analysis referenced in the discussion about build vs. buy: https://www.wayfound.ai/post/the-hidden-cost-of-diy-agent-monitoring-and-supervision Follow Wayfound on LinkedIn: https://www.linkedin.com/company/wayfound-ai