Paul Lacey's Blog Posts
Paul leads product marketing and AI engineering teams at Galileo (now a part of Cisco). As a former hardware and software engineer, he focuses on helping teams deploy AI agents with comprehensive observability and guardrails. Prior to Cisco, Paul led marketing teams at several Data & AI companies. He holds a degree in Electrical Engineering from Cal Poly, San Luis Obispo.
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When You Repatriate AI, the Invoice Disappears – The Cost Doesn’t
Here's how to measure GPU, memory, and token cost together so you know what your AI really costs.
Effective Cost, Not Token Count: How To Tell if Your Tokens Are Paying Off
Token count tells you how much AI you used, not whether it was worth it. Here's why effective cost, measured against quality with evals, is the metric that matters.
The Hidden Cost of Agentic AI: Why Most Projects Still Die Before Production
Five costs hide between your demo and production: tokens, data, evals, guardrails, and a pricing model that punishes you for checking the other four.
AI Is Amazing, the Bills Are Not: Why Tokenomics Is the New FinOps
Agentic AI spends unpredictably and providers are repricing toward the meter. Here's why enterprises are repatriating AI to their own hardware, and what it takes.