The Brief
Short, direct pieces on what I'm seeing, what I'm thinking, and what it means for the leaders navigating this.
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When Oversight Becomes Forensics
The pilot failed quietly. The agent won’t. The last two years had a logic to them. Open the door, watch what walks in, learn. Shadow AI proliferated outside procurement, outside IT, outside anyone’s line of sight. Governance lagged. It always does. But the outputs were containable. A bad summary stayed a bad summary. A hallucinated competitor analysis sat in a deck until someone caught it. Damage was bounded by the nature of the thing producing it: a system that generates text, not one that acts in the world.
The Fluency Trap Revisited
I’ve been at UNLEASH America in Las Vegas this week, sitting in sessions, talking to senior leaders in the corridors, listening to what people are actually saying about AI right now. Not what they say in press releases. What they say when they’re thinking out loud between panels. The thing I keep hearing is some version of this: we’re past the early problems. The models are solid now. They reason through things. They catch their own mistakes.
They Costed The Role. Not The Person.
When I’m brought in after the fact, after the automation is live and something isn’t working the way it should, the first thing I ask is: what do we have to work with? Every time, the room moves toward the same things. The system architecture, the data, the governance documents, the codebase. People start pulling up diagrams. Someone mentions the platform vendor. Someone else opens a laptop.
The Timestamp Problem
When someone reviews an AI output before it goes out, what are they actually checking? I’ve been asking that near the end of these meetings, after the frameworks and the policies. Someone stares at the mug in front of them. Someone else sees an urgent Teams message pop up on the screen, types two sentences, looks up.
