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What Stockholm knows about trust, and why it is the real AI moat

When everyone can prompt the same model, raw capability stops being a differentiator. The scarce assets become diversity of perspective and the trust that draws it out.

LeadershipAmazonTrustAre Right A LotStockholmInnovation

Last week I sat on a panel at K-Märkt Garnisonen in Stockholm for the launch of INNOVATE™ Stockholm, a book mapping the people and organisations behind this city's innovation ecosystem. Albert Bengtsson of Innovation Pioneers moderated. Next to me sat a deliberately mixed group, spanning fields that do not usually meet on the same stage: Philip von Segebaden, building a fusion reactor at Novatron; Katarina Gospic, a neuroscientist; Stefan Moritz from Max Matthiessen on the enterprise side; and Marie Claire Maxwell from Hack for Earth and Business Sweden, working the government and impact angle. My own corner was AI and innovation.

I know Albert, Stefan, and Marie Claire well, and we have crossed paths many times. But Philip and Katarina I had never spoken to before that day. Even for someone who has been part of this scene for years, the book and the event put two completely new people in front of me, from fields I rarely touch. That, in miniature, is why a community like this matters. It takes you past your own boundaries.

Albert asked what makes Stockholm special, and we each offered our observations. It was not the capital, and it was not even the science, that people talked about. It was trust, and a culture of generosity. Lyllian Abrahamsson, who curated the book, put it best in her own words. Stockholm works because of "the collaboration between entrepreneurs, startups, investors, corporations, academia, government organisations, and ecosystem enablers," a place where "people genuinely want to help one another succeed." The room itself was the proof. People who already knew each other and people meeting for the first time, sharing freely, because that is simply how things are done here.

Two leadership principles describe what was happening

Two of Amazon's Leadership Principles describe what was happening on that stage and in the room.

The first is Are Right, A Lot: "Leaders are right a lot. They have strong judgment and good instincts. They seek diverse perspectives and work to disconfirm their beliefs." The second is Earn Trust: "Leaders listen attentively, speak candidly, and treat others respectfully."

Together they describe how a healthy community works. Good judgment comes from many different perspectives, and you only get those perspectives when there is enough trust for people to share what they know. The two principles are usually discussed in isolation, but the panel made their dependency obvious. One feeds the other.

This is bigger than the panel we held in Stockholm. It matters for any leader, and it matters more now than it did three years ago.

Why capability stopped being the differentiator

When everyone has access to the same frontier models, raw capability can no longer be the differentiator. Your competitor can prompt the same Claude or GPT as you can. The model will even give each of you more or less the same confident, plausible answer, drawn from the same training distribution.

What AI cannot give you is the fusion physicist who tells you why your timeline is fantasy, or the neuroscientist who reframes your "engagement" problem as an attention problem, or the public-sector leader who sees the regulatory wall you are about to run into. Those perspectives live in other people, and you get to hear them only if those people trust you enough to be candid.

So the scarce assets in the AI era are diversity of perspective, and the trust that draws it out. That is the moat when capability is becoming commoditised. It is also why the "Are Right, A Lot" principle reads differently now. The job has changed. More of it is now about assembling the judgment that no single tool can hold, and less about being the smartest person with the best tool. I wrote more about that shift, and the trap of an AI that always agrees with you, in when AI can't tell you you're wrong.

The Bloomberg "Silicon Valhalla" segment on Sweden's tech scene makes the same point. The thing people highlight as the country's edge is the culture: founders who help the next generation of founders, long-term thinking, teams that stay together and build for the decade rather than the next quarter. As one of the founders in the video puts it, it is the way "previous founders help the new generation of founders."

It is not all optimism, and we did not pretend it was on the panel. Europe under-invests relative to the United States. In deep tech, only about 54% of larger rounds are funded from within Europe, against roughly 80% in the US, and much of the late-stage capital for European deep tech comes from outside the continent. Capital is a real gap. But the asset Stockholm has in abundance, which is hard to copy, is the trust and the willingness to build together.

How I am translating this into my own work

This is how I am putting it to use, and how you might too.

Put a range of different minds in the room. A panel of five marketers is not diversity. Five people from fusion, neuroscience, finance, government, and AI is. Seek the perspective you would not have thought to ask for.

Share first. Trust compounds, and someone has to start the ball rolling. The founders who help the next generation, the book curator who spends a year gathering people and making introductions, the panelist who gives away their playbook, all of them are opening a door before they know what comes back through it.

Use AI to disconfirm, and use people to surprise. I use AI to argue against my own position and stress-test my thinking. It is good at that. But people bring the knowledge I did not know existed, which is a different and more valuable thing. Earning that candour is its own discipline, and I dug into how leaders practise it in vocal self-criticism in the age of AI.

Treat collaboration as infrastructure. In the past three years I have met dozens, if not hundreds, of people out of curiosity and a general intention to collaborate. In some cases it did not turn into anything specific. In others, the people I met ended up working with me on projects, invited me to speak with their teams, gave me feedback on a product I was building, or became my friends. That web is the infrastructure for anything I do at scale.

One caution. Seeking diverse perspectives does not mean assembling a diverse-looking panel for the photo and then ignoring what they say. Earning trust does not mean chasing consensus until every sharp edge is sanded off. The point of bringing in someone from a different domain is that they might tell you something you do not want to hear. If everyone in your room agrees with you, you have collected mirrors, not perspectives, and AI will not make up the difference.

Your action step

When Albert asked the panel for one takeaway, I made a commitment out loud, so here it is in writing too. This week I am opening the INNOVATE™ Stockholm book, finding a few people I have never collaborated with, from fields that are not mine, and reaching out to invite them for fika, the Swedish coffee-and-conversation ritual, with no agenda.

Do the same, and do it as a leader rather than only as an individual. Pick one person from a discipline far from yours and invite them for a coffee this week. Then make "reach out to someone from a different field or a different kind of organisation" an explicit expectation for your team, written into how you work so it outlasts your own enthusiasm for it. I know three of the people on that panel well, but it took the book to put the other two in front of me. Communities like it exist precisely to carry us past our own boundaries. Leading in this age means crossing them on purpose, and bringing your people with you.

This is also the quiet reason translation matters so much right now. The perspectives are only useful if the people holding them can actually engage with the work, which is the subject of this issue's piece on speaking the language of your audience.

If you would like help building this kind of cross-disciplinary practice into how your leadership team works, or you want a keynote that makes the business case for trust as a competitive asset, reach out. It is one of my favourite conversations to have.

Frequently Asked Questions

What does the Are Right, A Lot principle mean in the age of AI?
It means seeking diverse perspectives and working to disconfirm your own beliefs. In the age of AI, good judgment no longer comes from raw capability, because everyone can prompt the same model. It comes from the range of human perspectives you can gather, which depends on how much people trust you enough to be candid.
Why is trust a competitive advantage when everyone has the same AI models?
Frontier models are available to you and your competitors alike, and they return similar confident answers drawn from the same training data. What a model cannot give you is the physicist who tells you your timeline is fantasy or the public-sector leader who sees the regulation you are about to hit. Those perspectives live in people, and you only hear them if there is enough trust for candour.
How can leaders build diverse perspectives into their teams?
Put a real mix of minds in the room instead of five people from the same function, share your own thinking first so trust can compound, and make reaching out to someone from a different field an explicit expectation for your team, something written into how you work.

Originally published in Think Big Newsletter #33 on Amir Elion's Think Big Newsletter.

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