A product executive, former software engineer, entrepreneur, and lifelong builder.

I have spent my career building software, leading product organizations, starting businesses, and helping companies figure out what to build next and how to build it better. I started as a software engineer before eventually finding my way into Product Management, although I have never completely stopped thinking like a builder. I still enjoy getting close to a problem, talking with customers, working through ideas, building prototypes, and discovering whether something that sounds great in a meeting actually works in the real world.

My experience has taken me through startups, growth-stage companies, and larger software organizations, and across product, engineering, data, analytics, platforms, and artificial intelligence. I have built new products from scratch, inherited products that needed a new direction, led teams through periods of significant change, started software businesses of my own, and made more than enough mistakes along the way to develop some fairly strong opinions about how products should, and should not, be built.

Those experiences have shaped the way I think about Product Management today. I believe great product teams begin with problems and outcomes rather than features and roadmaps. They develop hypotheses, find inexpensive ways to test what they believe, and allow evidence to influence what happens next. Frameworks and processes can help, but they should support good judgment rather than replace it. The objective is not to become exceptionally good at producing software. It is to become exceptionally good at figuring out which problems are worth solving and whether the things we build actually solve them.

Artificial intelligence has made that distinction even more important. The economics of building software are changing quickly, and many of the constraints that shaped how we organized product and engineering teams are beginning to change with them. I am particularly interested in what happens when the cost of turning an idea into something we can test drops dramatically. I believe the bigger opportunity with AI is not simply doing the things we already do faster. It is reconsidering some of the assumptions about how products are discovered, built, operated, and improved in the first place.

That is largely what this site is about. I write about Product Management, AI, product strategy, leadership, organizational design, experimentation, and the changing nature of software development. Some of what I write comes from things I have learned over the course of my career. Some comes from things I am building or experimenting with today. And sometimes I write because I have an idea rattling around in my head and writing is the best way I know to figure out what I actually think about it.

I do not expect every idea here to age perfectly. In fact, I hope some of them do not. If we are genuinely learning, our thinking should change as the evidence changes. That is why I think of this site as Thinking Out Loud. It is a place to explore ideas, challenge some of the conventional wisdom in our industry, and share what I am learning while I am still learning it.

When I am not writing, I am usually building something, experimenting with new technology, mentoring product professionals, or working with organizations through Vector North Advisory. Vector North is where I apply many of these ideas more formally through product leadership, AI strategy, organizational transformation, and product incubation. This site is more personal. It is where the ideas get room to breathe before anyone decides they need a framework and an acronym.

If something I have written makes you think differently, gives you an idea, or makes you want to tell me why I am completely wrong, feel free to reach out. Some of the best things I have learned started with exactly that kind of conversation.

Thanks for visiting, and all the best
Mike

A Note About AI and My Writing

This site has been around for more than six years, which means much of what you will find here was written well before generative AI became part of our everyday lives. If you go back through the archive, you will probably notice that my writing style has not changed all that much. For better or worse, this is how I have always written.

I use AI regularly today, including as part of my writing process. It is useful for editing, challenging an argument, finding a better way to phrase something, or helping me see where an idea is not as clear as I thought it was. It is also considerably more patient when I decide to rewrite the same paragraph twelve times.

What I do not use AI for is deciding what I think.

The ideas, arguments, experiences, opinions, and conclusions on this site are mine. They usually begin with something I have experienced, observed, built, questioned, or found myself thinking about for longer than is probably healthy. AI may occasionally help me express those thoughts more clearly, but the thinking behind them comes from me.

There is a lot of conversation right now about AI-generated content and what it might mean for human creativity. I think that is an important conversation, particularly as it becomes increasingly difficult to tell whether something represents a person’s actual thinking or simply a well-constructed prompt. I use AI extensively and believe strongly in its potential, but I also believe there is value in knowing that the person whose name appears on an idea actually believes it.

Everything published here represents my thinking at the time I wrote it. You are welcome to agree with it, disagree with it, or go far enough back in the archive to find something I no longer agree with myself.

That part is human too.

And yes, all of these thoughts really did come out of my brain. Scary as that might be.