In over thirty years in business, two technological shifts have fundamentally changed my work. The first was the web in the mid 1990s, which led me to leave architecture and focus on what we now call UX. The second is happening now – and it may be bigger. AI is poised to reshape how we interact with information, much as the web did – perhaps more so. This isn’t just another technological shift. It’s a fundamental change in how people understand their world and how businesses create value. But without structure, AI risks creating more confusion than clarity. That’s why I’m pivoting my consulting practice to what I’m calling Architecture for Intelligence. The phrase is intentionally ambiguous. Is the target human intelligence or artificial intelligence? The answer is “yes.” Thoughtfully structured information amplifies intelligence, human or artificial. Done right, it creates a virtuous cycle: smarter humans design smarter systems, which make humans smarter. But it won’t happen out of the box. I’ve worked enough with current AI systems to understand their capabilities and constraints. They’re astonishing in many ways, but they struggle to create stable, cohesive information environments – which people need to make skillful decisions. At least not without help. And that’s why I’m so excited: Because with a bit of structure, AI-powered systems can unlock previously unimaginable abilities — including the ability to produce smarter information environments. This sounds a bit academic, but the implications are huge. Our expectations about what constitutes good service will change. The speed, scale, and degree of personalization will be different. Businesses will need to rethink their strategies as the market shifts to the new paradigm. Those who do it well stand to benefit like never before. But individual humans must benefit too. This shift should bring value to people first; creating value for customers will create value for businesses. And here again is why we need Architecture for Intelligence. Architects don’t design structures for their own sake; we do it to serve human needs. This simple idea risks being lost in the mad rush to implement AI-powered systems. But AI doesn’t reduce complexity out of the box. It doesn’t generate clear reference frames for people to get their bearings. And done poorly, it can significantly degrade trust – or worse. AI doesn’t change the fact that clear, usable, and strategically aligned products require architecture. If anything, it increases the need for carefully considered structures. The shift goes both ways: AI needs information architecture in order to be usable, understandable, and trustworthy. IA itself is being transformed by AI. My new focus embraces both angles by 1) helping clients design more intelligent systems and 2) developing tools and methods to architect information more intelligently. All in service to amplifying human intelligence – from somebody with firsthand experience with the technology and over three decades of perspective. Specifically, I’m offering three kinds of engagements: Strategic consulting: Advising leaders on how to structure information to support AI-driven systems that drive real value. Product & web IA: Helping internal design and product teams deliver AI-driven products and websites that are easier to navigate, use, and maintain. Training: Showing teams how to use IA principles to design better smarter products and make better strategic decisions. I’m also working on AI-powered tools to do information architecture more effectively. And of course, you can expect the bulk of my writings and presentations to focus on AI from now on. (As they’ve done for much of the last year.) Which is to say, like AI itself, this change isn’t coming: it’s already here. Organizations that architect intelligence are poised to benefit like never before. And by centering human needs, you can ensure the benefits are felt widely. But you must start now. I’m more excited to be in tech now than at any time in the last thirty years. AI’s potential – for good and bad – is vast. Let’s make it good. If this resonates, please get in touch.

Today is Peter Gabriel’s 75th birthday. He’s contributed much through his music and by bringing people together through the arts. But today, I want to celebrate one of his songs that’s had a profound impact on my life: Solsbury Hill. Solsbury Hill was Gabriel’s debut single as a solo artist. That’s significant because of what the song is about. Before this, Gabriel was the lead singer of prog rock band Genesis. He left the band at a peak in their artistic and commercial development. They were highly regarded. So it was a risky move. But his personal and professional development demanded that he strike out on his own. And that’s the subject of Solsbury Hill: the scary and exciting moment when you’ve decided that further development requires you to move on, and you’ve taken decisive steps to do so. It’s scary because you’ll let people down. They’ve come to depend on you in your current guise. Now, you won’t be there anymore. It’s also scary because you’re leaving a known (and therefore, “safe”) situation to face uncertainty and doubt. What if the solo record doesn’t chart? What if people don’t turn out for the show? What if I can’t produce at the same level without my bandmates? Imposter syndrome affects even the highest performers. But the shift is also exciting. The new context allows more freedom: you don’t have to run decisions past bandmates anymore. You can also build on the experience and potential you’ve gathered so far and take it to the next level, leaving behind the baggage. The future is open. You can see far into the distance, as you would atop a hill on a clear day. And you can see what you’re leaving behind. As Gabriel put it, the song is about “being prepared to lose what you have for what you might get … It’s about letting go.” There are rare moments in life when you can choose a different path. They’re often not the perfect moment. (That’s why it’s scary!) But deep down you know you’ll regret letting it pass. Solsbury Hill doesn’t celebrate success. Gabriel wasn’t yet a successful solo artist when he recorded it. Instead, it celebrates the elation you feel after getting on the new path. Of having the courage and conviction to calmly say, “it’s time to move on” – and then doing it. I did not believe the information – Peter Gabriel, Solsbury Hill

Co-Intelligence: Living and Working with AI by Ethan Mollick Portfolio, 2024 Over the weekend, I caught up with a friend I hadn’t seen in years. When I explained that most of my work these days is focused on AI, he asked if there was one book he could read to understand how to better use AI. This is the book I recommended. Why? Because it offers a clear explanation of how the technology works, thoughtful explorations of what it means for us, and practical suggestions for using it to help with common tasks. AI isn’t like other technologies. As Mollick puts it, We have invented technologies, from axes to helicopters, that boost our physical capabilities; and others, like spreadsheets, that automate complex tasks; but we have never built a generally applicable technology that can boost our intelligence. The book is divided into two parts. The first explains the fundamentals, including how transformers work and the challenges inherent in aligning AI goals with human goals. Mollick lays out four principles for working effectively with AI: Always invite it to the table: AI is a general-purpose technology; it behooves you to try it for different ends. Be the human in the loop: assume AI will need supervision and guidance; provide it. Treat AI like a person, but tell it what kind of person it is: don’t fall into the trap of anthropomorphizing AI – but it’s helpful to suspend your disbelief. Assume this is the worst AI you’ll ever use: the technology is improving fast; assume the things that are difficult or impossible today will be doable in the future. The second part explains how to use AI effectively by seeing it through the lens of five possible roles: As person: even though we should remember AIs aren’t people, it can be useful to ask it to simulate human attributes such as personality and particular expertise. As creative: AI can assist us in our creative efforts or replace our creative functions outright. You’ll be better served by using AI for creative augmentation rather than replacement. As coworker: AIs can handle information tasks at much greater speed and scale than people. Knowing what they can and can’t do well can help you get the most out of them in a work context. As tutor: AIs can offer personalized instruction and draw from a larger corpus than what any human can. That said, they can also hallucinate. As coach: AIs can help us find patterns in data and help nudge us towards accomplishing our goals. In all five cases, the emphasis is on collaborating with AI as a partner rather than a replacement. The book offers concrete examples of prompts and the subsequent responses. Some are about the writing of the book itself, a nice meta-touch. The last chapter speculates about four possible futures, ranging from a scenario where the technology stalls to the opposite extreme where AI becomes all-powerful. The middle scenarios – slow growth and exponential growth – seem likeliest to me. As I implied above, this is the best primer I’ve found on what most people currently understand by AI. The book is clear about the risks and challenges inherent in the technology, but also practical, informative, and philosophical. Much of its advice validates my experiences with the technology. Co-Intelligence: Living and Working With AI

In episode 3 of the Traction Heroes podcast, Harry and I discussed the relationship between decision-making and data. Is it ok for some decisions to be made intuitively? What role do emotions play in decision-making? How do you deal with stakeholders who demand that decisions be backed with data? Tune in to find out!