About
I kept watching companies buy AI without knowing how to use it.
I started Blue Ribbon Ops because I kept seeing the same two problems — and nobody was solving the gap between them.
I spent over seven years in enterprise SaaS, selling AI-powered platforms and complex technical solutions to companies like Kellogg's, Grupo Bimbo, Beiersdorf, and Panera. I had hundreds of conversations with VP and C-suite buyers about how AI could transform their operations. And across all of those conversations, two patterns kept repeating.
The first: companies that assumed AI was out of reach. They'd heard the hype, seen the headlines, and concluded that meaningful AI adoption required millions of dollars in infrastructure, a team of data scientists, and a year-long implementation timeline. So they did nothing. They stayed on the sidelines while the technology matured around them — not because they didn't see the potential, but because they thought the barrier to entry was far higher than it actually was.
The second: companies that went all-in on the wrong things. Leadership would get excited, greenlight a six-figure platform purchase, and roll it out across the organization. But nobody asked the teams who'd actually use it whether it solved a real problem. Nobody invested in enablement. Six months later, the tool was sitting there with 10% adoption and a lot of frustrated employees who saw it as one more thing they were told to use but never taught how.
The gap between those two extremes is where the real opportunity lives. Most companies don't need a massive AI transformation. They need someone who can walk their team through what's actually possible with tools they can start using this week, identify the specific workflows where AI will make a measurable difference, and build enough capability internally that the organization doesn't need to rely on outside help forever.
That's what Blue Ribbon Ops does. I don't sell software. I don't build custom AI models. I help your team get competent with AI, prove value on real work, and scale what's working — in weeks, not quarters.
"The companies winning with AI aren't the ones spending the most. They're the ones whose people actually know what to do with it."
Selected Work
What real engagements look like.
Every engagement starts with understanding how your team actually works — then building AI capability around that reality.
AI-Powered Customer Intelligence
Designed a system where customer support and success calls are analyzed by an LLM immediately after each conversation. When the AI flags dissatisfaction, churn signals, or product feedback, it's automatically routed to a private Slack channel with VP/Directors of Support, Sales, Product, and Engineering — so every stakeholder is on the same page without relying on individual reps to escalate.
Compliance Messaging Automation
Built a retrieval-augmented generation (RAG) system to automate compliance messaging workflows. The system pulls from approved regulatory documentation to generate compliant content, reducing manual review cycles and ensuring consistency across all communications.
How I Think About This
Principles that guide the work.
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People before platforms
The best AI tool in the world is useless if nobody on your team knows how to use it. Training isn't the last step — it's the first one.
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Prove it small, then scale it
I don't build 90-day roadmaps based on assumptions. We start with one high-impact workflow, prove it works, and expand from there.
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Capability transfer, not dependency
When I leave, your team owns the workflows, the prompt libraries, and the knowledge. The goal is to make myself unnecessary.
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Honest about what AI can't do
Not every process should be automated. Not every team needs AI. Part of my job is telling you where AI doesn't fit — and saving you from spending money on it.
Let's talk about what AI can do for your team.
30 minutes. No pitch. Just a real conversation.
Book a strategy call →