Blue Ribbon Ops

AI spend is up 60% this year.
Most of it is shelfware.

Your company is spending more on AI than ever. The board mandated it. The tools got purchased. But the onboarding stalled, the workflows never got redesigned, and now the CFO wants to see ROI on a line item that hasn't produced any. I close the gap between buying AI and getting value from it.

Book a strategy call

Let me explain

The tools aren't the bottleneck. The implementation is.

Here's what I see every time. A company buys an enterprise AI platform. Leadership sends a Slack message: "This is going to change how we work." Three months later, the tool is sitting there. A few power users adopted it. Everyone else went back to doing things the old way. The platform isn't broken. Nobody redesigned the workflows, trained the team, or built the guardrails to make it operational.

The companies pulling ahead aren't the ones spending the most on AI. They're the ones extracting value from what they already bought. They mapped the right model to each task, restructured the processes around it, and built internal capability so their teams own the system. The laggards bought the same tools and got shelfware. That gap is where I work.


Here's how I think about it

Three things have to happen in order. Most companies skip the first two.

01

Find out what's actually worth automating

I audit your workflows against your stack and tell you where AI creates measurable leverage. Not "AI could help with X." Specific tasks, specific models, specific dollar impact. Most companies are running their most expensive model on every task. That's the first thing I fix.

02

Prove it works before you scale it

We pick the 20% of processes where AI delivers outsized returns and run them for real. Documented results your CFO can read. No pilot that quietly disappears. If it doesn't earn its keep in the proof, it doesn't make it to production.

03

Build it so your team owns it permanently

Automated workflows your team runs without me. Internal documentation they can maintain. Cross-functional systems like customer intelligence pipelines and compliance automation, designed so the capability stays when the engagement ends.

But you're probably wondering

How fast does this actually move?

Most AI consulting engagements take a quarter just to produce a slide deck. Mine produce a working result in the first week. Every phase starts with your people doing real work, not watching a presentation about real work.

See the full framework
  • Week one: your team ships something real

    I audit your current workflows, identify the highest-value opportunities, and run hands-on training built around your team's actual tasks. Not a demo with sample data. Your people complete their first AI-assisted deliverable before the week is out.

  • Weeks two through four: it starts compounding

    Department-specific workflows built on real processes. Custom prompt libraries and templates designed for the way your team already thinks. Performance tracking so you know exactly what's working and what's not worth keeping.

  • Month two: you don't need me anymore

    Automated workflows running on validated, high-impact processes. Internal documentation your team wrote, not me. The goal of every engagement is the same: build the capability into your organization so it stays when I leave.

Your CFO is about to ask what the AI spend produced. Let's make sure you have an answer.

30 minutes. No slide deck. I'll ask about your stack, your team, and where things stalled. You'll leave with a clear picture of what's worth fixing first.

Book a strategy call