Success also means being present for the people waiting at home, alongside the conferences and the time on the road. The goal is to be intentional about travel and make the most of it, spend fewer days away, and make more room for family and the moments that matter.

FOMU beats FOMO. Fear of missing out is about losses that happen when you do nothing. Fear of messing up is about losses that happen when you do something. The second one is the better place to operate from. FOMO is borrowed. It's a reaction to what everyone else appears to be doing, and it drives teams to adopt tools and ship features because a competitor did, not because a customer needed it. FOMU means you're already in motion. You've made a real decision, and perhaps it didn’t work out. But now you have the information necessary, thanks to that failure, to pivot and try again. This time, with a higher likelihood of success. Action produces information. Information you can’t find anywhere else. Because your circumstances are unique to you. No LLM or internet forum can answer for you.  So acknowledge your fears and take action anyway. Nobody else will do it for you.

The grass always looks greener when you're looking at someone else's business from the outside, but every business model comes with its own challenges. As AI makes it easier to automate more of the customer journey, the bigger question is whether we're simplifying for efficiency... or removing the human element that makes the relationship valuable.

Systems thinking and design systems go hand in hand… but there’s a lot more to the story. A design system is bigger than a component library. But the useful part is that nobody has to debate that button again. The same principle applies to far more than UI. One clear ICP means one sales deck, one go-to-market plan, and one set of places to show up. One reliable customer feedback loop means the team isn't reinventing how it learns all the time. These are all small decisions, and small decisions get discounted because they look small in isolation. But when the decision becomes a standard, it compounds through every person and every workflow that follows. That's what I mean by "one decision that makes a thousand." The best systems remove work people never needed to be doing in the first place.

Startup advice assumes information is the bottleneck. It isn't anymore. Every framework and case study a founder could want is findable in an afternoon. What isn't findable is the specific person who already solved the exact problem in front of you, in a similar market, at a similar stage. I've helped run the startup community in Wisconsin for years, and I see this over and over again. Founders show up wanting to talk on stage. What actually makes the event worthwhile is the conversations they have with people after the fact. That's what the community is for. There are things you can’t possibly learn without the help of others. Just the way it is.

The most valuable thing a partner can tell you is that you're wrong. But most service relationships aren't built for that. The incentive runs toward agreement, because agreement keeps the engagement comfortable. So a client proposes a direction, the team has real doubts, but nothing gets said. Six months later everyone can see the problem, and by then the cost of changing course is enormous. I'd rather have the uncomfortable conversation in week two. When that happens, the work gets dramatically better. I think just about everyone knows this, but so few are actually willing to go out of their comfort zone. Eat the frog.

Years ago I worked on a project where 3 teams had each built their own version of the same workflow. Funny enough… none of them knew the others existed. Each had solved the problem competently. Each had made slightly different choices. All three were now in production, and customers were hitting whichever one their entry point happened to route them to. Nobody was careless. Everyone was doing their job well. The failure was communication. That's the argument for systems thinking that I find most convincing, and it has nothing to do with efficiency. It's that individually good decisions, made in isolation, reliably add up to a product nobody designed.

The more complex the problem, the more important it is to slow down, define the problem clearly, and understand what success looks like. AI can dramatically accelerate focused work like analyzing user research and identifying patterns. But without customer context, clear goals, and meaningful metrics, it can't replace the human judgment needed to reach the right outcome.

This couldn’t be more true: “The only way to win is to learn faster than anyone else.” ~Eric Ries Software, business, doesn’t matter. This applies everywhere.  Everyone’s learning. It’s just a question of what they’re learning, and how fast. The easiest way to learn is by taking action, making mistakes, and paying others for information. Find a reasonable way to pull that off over time, and you’ll eclipse everyone else.

High-performing teams are built on mutual care, direct feedback, and a shared commitment to getting better. When people address issues openly instead of whispering behind the scenes, accountability becomes a tool for trust, growth, and collective success.

Wild loophole to have to put 13” laptop away but a 13” iPad with case (heavier) is all good during takeoff and landing.

The worst sports teams I played on weren't short on talent. Someone would say one thing in front of the group, then say something different in a one-on-one afterward.  People whispering in the shadows. Nothing brought into the light. That's what actually breaks a team, and it looks nothing like a skill issue. Without real accountability and a willingness to be fully transparent, you get people playing a political game for their own position. Everyone has something to gain in this world. What separates people is what they do when they could take the easier route and choose the disciplined one instead. That choice tends to tell the rest of someone's story.

My high school colors were red.  College was purple. Indoor football was green. Then I got past all of that and had nothing dictating what I wore. So I picked black, and now everything I buy is black. The remaining decision is just weather and context.  Short sleeve or long. Hoodie or not. Charcoal blazer if it's a business event. White sneaker or leather boot depending on how much I'm dressing it up. I've been drawn to reducing decisions since long before I had a word for it. If you enjoy deciding what to wear, cool. But if you don't, here’s your reminder that you don’t have to.

The easiest thing to do with AI is hand off everything and see what happens. You’ll find the problems with that idea real quick. The tasks people offload first are usually the ones that need the most context, not the least.  What the company is trying to do. What's been tried before. What failure looks like. That's the same context you'd give a person before delegating anything meaningful. With complex problems, the highest-leverage move is to slow down, define the problem, and define what success actually means. Which, ironically enough, is exactly what teams should’ve been doing for humans all along.

Every business model looks simpler from the outside. I used to think that if Headway had a cleaner model, something truly productized and off the shelf, I'd be less involved and have more time away from work. Then you talk to the people running those businesses and find out theirs is hard too. Different problems, same difficulty.  Just a classic case of thinking the grass is greener elsewhere when it really isn’t. Which means the question isn't which model is easier. It's what you actually want. I'd rather work with someone on their real problem and be accountable for the outcome than look for something easier elsewhere. Help the product succeed, coach the team up. That sort of thing. That's messier. It's harder to earn trust when people have been burned before. But once it's there, the relationship is worth the cost. Everything has tradeoffs. Pick the ones you actually want to live with.

AI is compressing the distance between design and production, with designers and coding agents increasingly able to turn ideas into production-ready front-end code. The right tools will keep evolving, and the bigger shift is rethinking the entire design-to-development workflow around what AI makes possible.

The most useful sales conversations I have aren't even really sales conversations. We're doing repositioning work right now, and instead of guessing at how our buyers think, we're asking them. Fifteen or twenty minutes with VPs of technology and peers who've actually hired firms like ours. The explicit framing is that we want to understand how you evaluate a partner and what you're looking for. People are more willing to have these conversations than to say yes to a demo, because you're asking for their expertise rather than their budget. You learn the language your market actually uses. And you end the call having built something with someone instead of having asked them for something.

Love the use case, design systems are the biggest foundational unlock for the future of not just apps, but presentations, videos, and more.