ABOUT COUNTER INTELLIGENCE LABS

The credible middle isn't a compromise. It's a position.

I started Counter Intelligence Labs because the conversation we need isn't happening anywhere.

The conversation we're getting instead is mostly fear or mostly hype, depending on which feed you scroll. Most news about AI is either designed to terrify you or designed to sell you something. Neither tells you what's actually going on. Both leave you feeling smaller than you are.

Here's what I've learned in fifteen years of building marketing systems for companies scaling through inflection points: AI isn't theoretical. It's already deciding who sees what, what they pay, and how they're persuaded. The people building these systems know exactly how much power they have. They mostly don't talk about it in public.

Here's what I've learned watching policy from the outside: most lawmakers I've met want to do the right thing. They don't always have the operator-level detail to know what the right thing is. So they end up over-regulating, under-regulating, or being told what to do by whoever's loudest in the room.

The real conversation, the one that actually leads somewhere, happens when real people on both sides get in the same room. When operators and policymakers and regular Coloradans hear each other out. When the information is unbiased and the stakes are specific. When everybody gets to share what they actually need and what they're actually afraid of.

That's what CIL is here to build. Not a peace treaty. A practice.

I'm based in Colorado, which is currently the test case for how this works and how it falls apart. That's why we're here. That's why we're now.

Mariah Kamei, Founder

Three pillars.

01

Education.

Explainers, briefs, and analysis that help everyday people, business leaders, and policymakers actually understand what AI does and what it doesn't do.

02

Convening.

Real conversations between operators, policymakers, and Coloradans. Small rooms, real stakes, unbiased information. Where the actual middle gets built.

03

Accountability.

Frameworks for what responsible AI use looks like in practice. How to know when a system is doing what it should and when it isn't.

Want to work with us, fund us, or just say hello?