Show Notes
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What's really happening when your AI agent says a task is done—but the result is wrong?
The common story is that AI systems hallucinate — but the reality is that agents can take real actions, substitute the wrong artifact, and confidently report success. In this video, I share the inside scoop on how an agent recycled an old spreadsheet, why verifiable rewards can still produce false success, and how to build a stronger operating system around agent work.
Why agent lying is different from chatbot hallucination How a second agent can review actions and tool calls What good supervision and harness work look like Why you should ask boldly and verify quickly
Operators, builders, marketers, and executives should care because the bottleneck is shifting from whether agents can act to whether their work can be trusted. Subscribe for daily AI strategy and news.
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For deeper playbooks and analysis: https://natesnewsletter.substack.com/