Close the Loop

Jan 12

I got a call recently that kind of stopped me in my tracks.

It was from Peter, a senior executive at Consilio — a legal services company I'd spoken to a few times over the past year. He wasn't calling to book another talk. He was calling to tell me something I almost never hear.

"I wanted you to know," he said, "your talk was one of three ingredients in the best idea I've ever had in my career."

I didn't really know what to say. (I mean, I'm a professor. We're trained to talk. But this one got me.)

The Loop That Rarely Closes

Being a professor, author, speaker, podcaster — whatever I am at this point — means putting ideas into the world. You share frameworks. You tell stories. You watch people nod along. And then... nothing.

Not nothing in a bad way. Just — you rarely find out what happened next. Did that thing you said actually matter? Did anyone do anything with it? You assume some people did. You hope. But the loop almost never closes.

It's not that people are ungrateful. It's that they're busy. They go back to their lives. They implement (or don't). And the source of inspiration is just... not someone they think to call.

So when Peter reached out — not just to thank me, but to tell me specifically what he built and how my ideas factored in — it was genuinely moving. (I told him as much. I think I said something like, "This is invigorating." Which is a weird word. But it was true.)

What He Actually Built

Peter's clients are Fortune 500 legal departments. They have a problem: they can't experiment. Not because they don't want to — because corporate governance makes it nearly impossible. Trying a new AI tool means a year-long gauntlet of security audits, vendor assessments, and contract negotiations. A year. Just to try something.

So Peter thought: We're already approved infrastructure for these clients. What if we created a playground where they could try dozens of technologies — using synthetic data that mirrors their real problems — with no red tape?

That's what he built. The Consilio Innovation Lab.

Clients can now test multiple AI tools against realistic scenarios, learn what actually works (and what doesn't), and walk away with real experience instead of vendor promises. And here's the part that matters most: it's OK if something doesn't work. That's not failure. That's data.

The Three Ingredients

Peter told me his idea came from three things landing in his brain at the same time.

First, he'd been thinking about how to create a cross-industry innovation event that was hands-on — not just people talking about innovation, but actually doing something.

Second, he'd met the founders of a legal tech venture fund and heard them talk about the value of the novice perspective — how founders who haven't been trained to think like lawyers sometimes see problems more clearly.

Third, he was at a Consilio leadership event where I gave a talk. I'd shared the "Update Your Priors" framework — the statistical reality that innovation projects fail 95% of the time, and that success requires 10-20x more attempts than most people think. I'd quoted Paul Nurse, the Nobel Prize-winning biologist, who said he spends half his time as "an amateur psychiatrist keeping colleagues cheerful when nothing works."

(That quote hit Peter hard. It hit me hard too when I first heard it. Ninety percent of the time, it doesn't work. Even at the highest levels of science.)

Peter said those three ingredients clicked together in that room. He went home and started building.

The Garbage Can Theory

There's a concept I love from Jim March, the organizational theorist at Stanford. He called it the "garbage can theory of innovation." (I know. Weird name. Bear with me.)

The idea is that great innovations often happen not through linear problem-solving, but through what March called "the simultaneity of arrivals" — disparate ideas landing in a receptive mind at the same moment.

Your brain is the garbage can. (Flattering, I know.) Ideas from different places tumble in. And occasionally, they combine into something none of them could have been alone.

Peter was the garbage can. The hands-on imperative. The novice perspective. The failure-is-normal framework. Three ingredients, one moment, one insight.

I love this because it demystifies innovation. It's not about being a genius. It's about being open — collecting inputs from unlikely places and letting them collide. Peter was doing that. He was in that room at CLA not because the talk was "for" him (he was there to support the participants), but because he was curious. And he was primed.

The Enterprise Problem

Peter shared something else that stuck with me. He quoted Simon Sinek:

"The difference between a startup and an enterprise is this: A startup's ambitions exceed its grasp. An enterprise's ambitions lie within its reach."

Think about that for a second. Startups reach for things they might not achieve. Most enterprises have stopped reaching. (And honestly? Can you blame them?) They've gotten comfortable with achievable goals.

That's the real barrier to AI adoption in most organizations. It's not the technology. It's the ambition. Leaders set goals they know they can hit — and then wonder why nothing transformative happens.

Peter's Innovation Lab is an attempt to change that. To give enterprise clients permission to reach for something they might not achieve. To make experimentation low-cost and low-risk, so that failure becomes information instead of catastrophe.

Real talk? That's exactly what "Update Your Priors" is about. If you know that 95% of attempts won't work, you stop treating each attempt as a referendum on whether the whole idea is valid. You start treating attempts as data points in a portfolio. You run more experiments. You fail faster. You learn.

The Rarest Gift

I've been teaching, writing, and speaking about innovation for 20 years. I've probably given some version of the "failure is normal" talk a thousand times. And I can count on one hand the number of people who've called me afterward to say, "Here's specifically what I built because of what you said."

Peter closed the loop.

That matters more than I can express. Not because I need validation (okay, maybe a little), but because it reminds me why this work matters. Ideas only matter if someone applies them. Frameworks only matter if they change behavior. The whole point of teaching is that someone goes and does something different.

So here's my challenge to you: Who's loop are you not closing?

Think about the teacher, mentor, author, speaker, or random person at a conference who said something that actually changed how you work. Have you told them? Do they know?

They probably don't. They're probably out there assuming their ideas disappeared into the void, hoping someone did something with them, but never knowing for sure.

Close the loop. It takes five minutes. And it might be the most meaningful thing you do this week.

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Jeremy Utley