Earlier this year, after a long run at Uhray and CDLLife, I set out to help build a company around AI-powered contact center data solutions. It was called EndeavorCX, and for a few intense months, I dove deep into that problem space. But along the way, I realized something the opportunity — and my own excitement — was far bigger than one vertical. That realization became WUNN Labs.

Where This Starts

I began my career in data science… I loved the logic, the power, and the potential.

But I saw numerous time where cool insights result in “I already knew that” or “That’s not really true, because <insert nuance here>.”

And I started to realize something: Insight without context is noise. Data without judgment is dangerous.

I moved into building software … not because I loved code, but because I was tired of good analysis dying in slide decks. Software by default went to work.

New Tools, Same Story with AI

I’m seeing that same trend again. AI agents discussed everywhere. Everyone’s excited.

But…

If we don’t embed context and nuance into these agents, we’re just going to automate the same shallow decisions. We will not scale intelligence. We’ll scale ignorance … faster.

You’ll have agents:

• Generating answers that don’t matter
• Surfacing patterns no one trusts
• Producing volume instead of value

And worse: people will think they’re making progress …. But activity is not impact and output is not outcome.

The Two Ladders That Matter

I think a lot about two ladders of decision making.

Ladder One:

Data → Information → Knowledge → Insight → Wisdom → Impact

Ladder Two:

What happened? → Why did it happen? → What will happen? → What should I do?

Most systems or people climb halfway and stall. They tell you what happened. Maybe why.
But they don’t tell you what to do and they definitely don’t understand.

That kind of judgment lives in conversation and experience.
Not in tables. Not in dashboards. Not in postmortems.

What I’m Building at WUNN

At WUNN Labs, we’re building the infrastructure that I believe will prevent the “yeah so what” problem of much data analysis, KPIs, and dashboards: A system that listens like a human, thinks like an operator, and acts with the clarity of someone who’s been in the room before … a thousand times.

Why Me, Why Now

I loved working at CDLLife because adtech for a consumer segment allowed me to put realtime, at-scale data-decision making into practice. Ad-tech has uniquely acted upon high-leverage decisions from data in real-time. Which ad? To who? When? Why? For what bid? (I will stay involved at CDLLife … I’m on the board and an advisor).

I want to leverage what I learned there: We don’t need more dashboards. We need systems that understand nuance. That can listen like humans, act with judgment, and learn fast.

I’m here to help build that.