I help leaders design how their teams work with AI, from first assessment to sustainable methods.
AI opens possibilities that weren't on the table a few years ago — new products, new ways of working, entirely new value in places you already operate. Seeing what's actually available to your organization, and finding the path that takes you there, is where I come in — to sharpen the view of what's possible for you, and bring the methodical depth that turns possibility into a concrete path.
Three engagement formats for product organizations, each grounded in analytical depth and the understanding that AI is a strategic design challenge.
Where does AI actually create value in your organization? Which processes need to be rethought — and which possibilities emerge that weren't open before? The Opportunity Assessment maps that territory with you: where AI can sharpen processes you already have, and where it opens entirely new value in your business. Stakeholder conversations, value chain mapping, technology audits — the methods adapt to your situation. What you come away with is a clear, prioritized view of where AI takes your organization forward.
Good AI strategy depends on asking the relevant questions — but those questions only come into view when the underlying analysis is sound. AI Strategy Development provides both sides of that work: the expert analyses and concepts that set the ground for real strategic thinking, and the work of developing your strategy from there. The format adapts to what your situation calls for, from focused working sessions to written positions on specific questions. The work is rigorous, and what we develop together stays with your team.
Turning AI opportunity into everyday working practice is where the real value lands. Framework Design builds that together with you: processes that make AI a reliable part of how your team works, the tools and integrations that support them, documented practices your team can follow, and training that makes the framework usable from day one. The starting point is always how your organization actually operates today — the framework is designed around that, not imposed on it.
I write regularly about AI, organizations, and the changing nature of software development. The articles below reflect how I approach the field — analytically and from the ground up.
Argues that AI-driven development does not kill agile but delivers its core principle more completely than any sprint ever did. Deconstructs the 'waterfall is back' narrative by separating agile principle from Scrum ceremony, and showing that faster feedback loops make AI-era development the most agile in history.
Have you ever received the same answer from an AI twice? Not approximately the same — exactly the same. If you've used a large language model for anything beyond trivial queries, you already know the answer is no. This article examines what the probabilistic turn means for how we work with machines, and what it demands of us.
Why intelligence and experience determine whether AI helps or harms. An examination of how cognitive load, expertise, and personality shape the outcome of working with large language models.
First we commoditized music. Then knowledge. Then relationships. Now intelligence. What's left? A reflection on what AI is doing to the structures of meaning that human life has historically relied on.
Every engagement starts with understanding. I want to know how your organization works, where the real tensions are, and what has been tried before. That understanding is the foundation for everything that follows.
What you get from me are documents your team can work from — structured analyses, methodical frameworks, concrete recommendations.
I work independently. That means you work directly with me throughout the engagement, with the continuity and focus that brings. I work with a small number of clients at a time, which lets me give each engagement the depth of attention it needs.
I've spent more than two decades in product and technology work across publishing, education, insurance, energy, and healthcare — most of that time in senior roles as business analyst and product owner, with deep involvement in how complex organizations design, build, and evolve their digital products.
My focus shifted to AI with the arrival of the current generation of large language models and agent-based systems. Since then, I've worked hands-on with these technologies and written regularly about them — the writing and the client work feed each other, and both are in service of the same question: how organizations actually work with AI, rather than around it.
If you're shaping how your teams work with AI and want a sparring partner who brings both analytical depth and methodological rigor, I'd be glad to hear from you.
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