When Playing It Safe Is the Riskiest Move

Most teams agree that learning is key to reducing risk. But not all learning happens during implementation. And not all approaches to product discovery are as iterative as we like to think.

In many orgs, there’s a tendency to treat product discovery and design work as a way to front-load certainty. Research gets packaged into polished prototypes. User flows are vetted, click-through demos reviewed, copy finalized. Boxes have been checked, sign offs are obtained, success feels inevitable. By the time development begins, there’s a sense that the hard part—the learning—is done.

From there, teams move into delivery mode. They build incrementally, they iterate on implementation, they follow agile rhythms. But the product thinking has already solidified. What gets built may be sliced small, but the underlying decisions are no longer being questioned.

It creates the comfort of “knowing” while giving the appearance of agility.

But it’s not agility. It’s choreography.

And when things shift—as they inevitably do—it becomes clear how little room we left ourselves to adapt.

Certainty Feels Safe. Learning Is Safer.

When we invest heavily in up-front discovery, it can feel like we’ve reduced risk. We’ve anticipated edge cases, validated with users, aligned on a vision. But that confidence is only real if we keep validating as we go.

No matter how thorough your discovery process is, the most reliable learning still happens where software meets customer. Early. Often. In context.

The further discovery is from that point of contact, the more assumptions sneak in. The tighter the prototype, the harder it is to change course. And the longer we go without user feedback on the live experience, the more fragile our work becomes—no matter how good it looked in design reviews.

Treat Discovery Like Delivery

The healthiest product teams don’t just iterate on implementation. They iterate on understanding.

They approach product discovery the same way they approach development: in small, testable steps. They release early prototypes not just to stakeholders, but to real users. They fold learning from production back into their product thinking. They augment initial discovery learnings with live product analytics, customer feedback, and satisfaction surveys (to name a few) as input to adjust and improve on what they've delivered. And they keep discovery going through delivery—not just before it.

This is what continuous discovery looks like. Not a separate phase, but an ongoing practice.

Instead of trying to eliminate risk through “getting it right,” they reduce risk by learning faster and adjusting sooner.

Make the Learning Loop Short

The teams that adapt best are the ones with the shortest feedback loops. They don’t pretend to be certain—they design their work so they don’t have to be.

They test assumptions quickly. They validate throughout the development and delivery cycle, not just after launch. They expect their early thinking to evolve. And because they’ve built that expectation into how they work, change doesn’t feel like failure—it feels like progress.

What’s Next

If your product process feels stuck—if discovery happens all at once and delivery happens in isolation—it’s worth asking: when was the last time we changed our minds?

Not because we were wrong. But because we learned something new.

Why ‘Best Practices’ Don’t Exist

Why ‘Best Practices’ Don’t Exist

The problem with the term best practice is not always the practice itself—it’s the perspective the phrase invites. Best is steeped in finality. It implies that nothing better exists, or ever will. That the thinking is over. And while we may not mean it that way, language shapes thought. When we call something “best,” we stop asking “is it still working?”

Doubling Down on Diversity

Doubling Down on Diversity

These days, it seems like even talking about diversity and inclusion can spark a political debate. But here’s the thing—it doesn’t need to be political. This isn’t about left or right. It’s about people. It’s about teams. It’s about building environments where different perspectives aren’t just welcomed, but seen as essential.

Because they are.

In tech, in product, in leadership—diverse teams consistently outperform homogeneous ones. Not because it feels good, but because it works better. This is a business discussion. A design discussion. A collaboration discussion.

So let’s talk about it.

Composition Isn’t Just About Code

Composition Isn’t Just About Code

The way your teams are structured shapes the software you build—and vice versa. In this article, we explore the profound connection between team and software composition through the lens of Conway’s Law, uncovering how misalignment leads to chaos and inefficiency, while thoughtful alignment drives collaboration, modularity, and adaptability. Learn why your true architecture isn’t in diagrams but in the code itself, and discover actionable steps to align your teams and software for better outcomes.

Why I Joined Test Double

Why I Joined Test Double

When I say I’m joining Test Double as their new VP of Delivery, I’m not just making a career move—I’m making an alignment move. This is a company that already values the things I value. They’ve built a strong culture, a strong team, and a strong set of practices. I’m not joining to overhaul anything. I’m joining to help make something great even better.

Small Deployments; Big Impact

Small Deployments; Big Impact

When teams hear about small, frequent deployments, they often picture chaos: code breaking, users complaining, and developers scrambling to fix issues. But in reality, small deployments do the opposite. They reduce complexity, amplify feedback, and create a smoother experience for both users and developers.

Fixing Full-Stack Teams; Specialization Required

Fixing Full-Stack Teams; Specialization Required

Full-stack teams are a brilliant concept. They’re designed to have everything a team needs to solve problems in a given domain—front-end, back-end, database, security, you name it. When done right, these teams are little microcosms of outcome achievement, creativity, and autonomy. They blur skill boundaries, enabling faster delivery and real-time learning across disciplines. Sounds great, right?

But there’s a catch. Somewhere along the way, we started confusing “full-stack teams” with “teams of full-stack engineers.” When I say we, I mean it. I did this too. I was on the full-stack teams of full-stack engineers bandwagon. But that shift—over time—has cost us. By prioritizing generalists at the expense of specialists, we’ve inadvertently traded depth for breadth and innovation for adequacy. Let me explain.

Collaboration Contracts beta release

Collaboration Contracts beta release

Today, I’m excited to announce the beta launch of Collaboration Contracts, a lightweight app designed to help teams—especially distributed ones—quickly define and manage their roles in decisions. Whether you're using it to bring clarity to one-off decisions or baking it into how your team operates every day, the app is built to support alignment, accountability, and smoother collaboration.

Making the Flow of Work Visible with Cumulative Flow Diagrams

Making the Flow of Work Visible with Cumulative Flow Diagrams

When we talk about making the work visible, there are two key aspects - what is the work and how is the work progressing. In this article, we are going to focus on how the work is progressing. Specifically, we are going to look at Cumulative Flow Diagrams as a means of visualizing work progress.

Frequent releases improve outcomes

Frequent releases improve outcomes

Whether you’re still figuring out your general product offering or you are enhancing and adding capabilities to a well established product, the ultimate test of whether or not you’ve hit the mark (or are at least trending in the right direction), is how your audience engages with what you’ve created. Yes, you can (and should) do market research before designing and coding up a potential solution to an identified problem, but the only way to know for certain, is to see what happens when your concepts come in contact with your audience.

Before you Judge and Jettison, Compare and Combine

So you’ve got some problem you’re trying to solve (Know the problem you are solving). You’ve agreed to work together on coming up with a solution. So you call a meeting and ask everyone to bring some ideas.

The objective of the meeting is to select the “best” option among the ideas presented.

In my observation, most folks tend toward an approach I call “Judge and Jettison”.

Opportunity Solution Trees

Opportunity Solution Trees

In this article, I want to go more in depth on Opportunity Solution Trees; what they are, how they are used, how to create one, and how I think about them slightly differently (but only slightly) than folks like Teresa Torres who really introduced them broadly to the Product community in her book “Continuous Discovery Habits”. This book, by the way, is a must have for anyone who works in software product development - not just folks in product-specific roles.