The Hidden Cost of Fast AI Inference
The promise of faster AI inference is simple: get answers quicker, spend less per call, and scale without breaking budgets. The human reason it matters is plain. In a world where decisions h
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9 Governance Decisions to Make Before an AI System Goes Live
The pressure is real. The demo looked glorious, but the user will press go the moment the clock ticks. The staff who keep the lights on will lean on this system, not the slide deck. I want a
Designing AI for the Person Who Must Correct It
I start with the need I meet every morning: a demo that promised polish but arrived wearing a rough edge. The project is billed as a gleaming AI assistant, yet I live with the person who mus
Which Jobs Change First When Companies Adopt AI?
The first shift is not a firing frenzy. It’s a reshaping of daily tasks. In the early days of any AI rollout, the change is visible in the work people do, not just in who keeps their chair w
How to Build an AI Budget That Includes the Costs Nobody Demos
The human problem is simple and loud: we want fast AI results with clean numbers, but the real costs hide in plain sight. The demo glosses over data prep, governance, and the quiet, ongoing
The Total Cost of Ownership Behind an Enterprise AI Project
I’ve spent decades watching an AI demo glitter in the executive briefing, then settle into a slower, less cinematic reality once the room clears. The truth is often hiding in plain sight: th
Why Cheap Generative AI Can Produce an Expensive Workflow
The claim is simple: cheap per-token prices mean cheap workflows. The human reason it matters is that organizations defend budgets by showing fast, small numbers, even when the full cost pic
Build or Buy an AI System: The Tradeoff Beyond the Demo
I’ve stood in the glare of a vendor demo and watched the room lean in. The lights dim, the dashboard glows, and the sales sheet promises outcomes in weeks, not months. Then the follow-up que
How Model Choice, Deployment, and Scale Change the AI Cost Curve
I’ve watched this game from the back of the room, where the budget folks stand with their notebooks and the engineers stand with their charts. I’m 52, I’ve run operations in Chicago, and I’v
The AI Team You Need After the First Prototype
Pressure comes before hope. After the demo, you see a line of work you didn’t expect to stress. The machine does something useful, but the system around it is brittle in ways you can’t ignor
8 Governance Controls That Cost Less Than an AI Failure
The pressure is real. I’ve watched a dozen projects crash not from the engine but from the edges. Misunderstood risks, fuzzy ownership, and the blunt force of a bad decision. The choice isn’