Protecting Passion in a Changing World

You are not being pulled back in by accident. AI just makes it obvious. Work comes back. Decisions reopen. You step back in. “I thought we fixed that.” But it shows up again. This week Most founders look at the team. Someone missed something. Someone needs clearer instructions. Someone needs chasing. Maybe. But growth usually exposes something else. The work moved but never fully left you. The decision was made but never fully held. The team progressed it but never fully carried it. So the same pressure shows up again. Same work. Same decisions. Same pressure. Just now it is visible. In real time. That is how I use AI. Not to generate more answers. To see where work actually gets stuck. Where decisions sit. Where work slows. Where things pause until you step in. Because that is the signal. Even after hiring. Even after process. Even after new tools. If everything still comes through you, the problem was never capacity. And the cost is not just your time. It is slower delivery. Work that looks finished but isn’t. Clients starting to feel the delay. AI will show you the pattern faster. But you still have to close it. What is still waiting on you today that shouldn’t?

What does a happy team look like in the AI era? I recently spoke with a team fully using AI tools. Productivity was up. Speed was up. Output was up. But when I asked how people felt… The answer was more complex: “More efficient. Not necessarily happier.” That stayed with me. Because AI is changing everything. - How we work. - How fast we work. - How decisions get made. But happiness is not automatically improving. In most teams I see the same pattern: People feel empowered by AI. But also under pressure to keep up. They save time. But don’t always feel more fulfilled. One thing is becoming very clear: People are more comfortable when they understand the right balance between AI and human work in their daily flow. How their day-to-day job actually looks now. That clarity is becoming essential. Personally, having led large organisations, I’ve always worked with one priority in mind: Build happy teams. Because happiness is not a “soft” metric. It directly impacts performance and work-life balance. And in my experience: Happier teams consistently perform better. So what actually makes a team happy in the AI era? A few things stand out: - Clarity What is AI doing? What are you doing? When this is unclear, anxiety grows fast. - Trust People should not hide AI usage. They should feel safe using it openly. - Progress Change is constant. Teams need to feel they are evolving, not falling behind. - Meaningful work AI should remove the repetitive. Not the work people care about most. - Direction Without leadership, AI creates noise. With it, it creates momentum. What I’m realising is this: AI doesn’t automatically make teams happier. It makes what’s missing more visible. And in the end: A happy team in the AI era is not the most advanced one. It’s the one where people feel confident. Useful. And clear about how they fit into what’s next. Curious: What makes a team truly happy in your experience?

I tell my team the same thing every day. Be the hero in someone's day. A teammate's. A client's. Anyone who needs it. That one belief is the foundation of every team culture I have built. And with AI, we now have more capacity than ever to make it happen. Faster insights. Earlier risk signals. More time for the conversations that actually matter. But the hero part? That is still entirely human. AI has changed what is possible for CS teams. Automated workflows. Real-time health scoring. Faster risk detection. More accounts covered with fewer manual touchpoints. The technology is genuinely remarkable and evolving at lightning speed. Any CS leader not using it is already behind. But here is what AI cannot do. It cannot make your team feel seen. It cannot replace the one-on-one where someone finally tells you what is really going on. It cannot create the moment where a teammate covers for someone who is struggling, or where a client feels like someone genuinely cares about their success and not just their renewal date. That is culture. And culture is still entirely a human experience. Clear expectations so people know what winning looks like. Honest feedback delivered with care and consistency. Real investment in growth so people can see their own trajectory. Public recognition that makes people feel their effort matters. A remote environment built with enough intention that people feel connected even when they are not in the same room. Get those things right and something remarkable happens. Your team shows up for each other and when they show up for each other, they show up for clients. I have seen it firsthand and marvel at what they can do when you give them the tools and trust. AI gives you the capacity. Culture is what supports them in that journey and turns amazing people into heroes.

I went into a 250-person company to roll out Mindstone Rebel thinking AI transformation was about the product. I had the decks ready.   I had the use cases ready.   I was deep in the Rebel product and felt ready. Then I sat down with the first person, automated about 30% of their role in six minutes and expected delight. Instead, I saw grief. That changed how I approach supporting humans working with AI Because AI transformation is not a tooling problem. It is an identity problem. When someone has been the go-to person for a task for years and that task disappears in front of them, the first thing they lose is not efficiency. It is certainty. Status. Familiarity. Sometimes even a piece of who they think they are at work. That changed how I think about rollout completely. Yes, you need tools.   Yes, you need training.   But you also need enablement, the human part. A few things I’ve seen matter most: - no mandates, start with opt-in champions - leadership has to model AI use openly - people need explicit permission to fail and test - teams need psychological safety, not forced enthusiasm - celebrate automation wins - ask people what they would do with 30% of their time back That last question changes everything. One person told me he’d get home in time for bath and bedtime.   Another said she’d finally have time to train and upskill her team. That is the shift I care about. Not just automating work.   Reinventing work so humans get to do more of the human bits. #AITransformation #FutureOfWork https://lnkd.in/eDyWm7td

One of the biggest lessons in business: Ideas are cheap. Execution is everything. Almost every “great idea” has probably already crossed someone else’s mind before. The difference is whether someone actually does something about it. What’s interesting now is AI is changing execution itself. A small team today can execute faster than entire companies could a few years ago. You’re no longer limited the same way by time, team size, or technical ability. We’re entering a world where execution is becoming more accessible which makes speed, adaptability, and consistency even more important.

Are you easy to work with? I’ve started to think AI systems are training us to value agreement more than honesty. A lot of genAI is designed to feel frictionless. The illusion of being a coach, but only ever accentuating the positive. Which means it is like a sycophantic team member: confirming instincts, softening challenge, mirroring opinions back. Humans do this too, of course. AI learned it from somewhere. We learn which parts of ourselves get rewarded: being agreeable, not making things awkward, not questioning the direction everyone else already seems comfortable with. Being a team player. You can see the same instinct on the world stage too: the belief that difficult people can be managed by keeping them sweet. It rarely works. To be honest, “easy to work with” can quickly come to mean predictable and harmless. At Toffee Hammer we’re good at disagreeing. Sometimes I know I come across as difficult: “I think we’re missing something.” “I’m not convinced.” The team challenge me and each other: we’d far rather talk it through than accept or settle for something “good enough”. The people I trust most are not the people who agree with me fastest. They’re the people who help me think more clearly, even when that creates a little friction. What about you?

🔴 Your team's most productive-looking meeting might be its most dangerous one. The Mirage: high comfort, low safety. AI smooths the surface. The flawed strategy gets nodded through. Nobody pushes back because nobody feels the stakes. ❗ Edmondson's research is clear --> Psychological safety predicts performance. Psychological comfort predicts compliance. AI accelerates whichever one your culture already has.

Arriving to work in style… 🚲 Today’s feature: Sandy Armstrong In data and AI, seniority is too often mistaken for titles or tenure clocked 5-9. In reality, it’s about vision, resilience, and an A-players mindset — the ability to see further, push harder, and elevate everyone around you. Sandy sets that standard. The monocycle just makes it visible. Building a team like this is a genuine pleasure. Transmission Dynamics; Redefining the Status Quo #Aplayers #AmazingTeam #Inspiration

She automated 30% of someone's job in 6 minutes. Their reaction wasn't excitement — it was grief.That moment stopped Emma Rees in her tracks. And it completely changed how she approaches AI transformation. At our Mindstone London Meetup last week, Emma gave one of the most grounded talks we've hosted on what actually makes AI adoption work inside companies. The short answer: it's almost never the technology. Here's what landed: 🔹  Identity shift is real — and it comes first When someone has been 'the person' for a task for years, automating it doesn't feel like efficiency. It feels like loss. If your rollout strategy doesn't account for that, you're already facing resistance you didn't plan for. 🔹  Champions beat mandates Emma's team stopped mandating AI use entirely. Instead, they built a small, opt-in group of champions — curious people across functions and levels who'd already seen results. Peer-led rollouts land better because colleagues carry context that outsiders never will. 🔹  Leaders have to model it visibly A coach told Emma that someone stood up in front of 150 people and said: 'I feel like I'm cheating when I use AI.' If leadership isn't openly talking about their own AI use, the rest of the team won't move. Emma now signs her work: 'In collaboration with AI, executed by Rebel.' 🔹  Say 'permission to fail' out loud You can't just imply experimentation is okay. With people worried about job security and identity, you have to give explicit permission to test, make mistakes, and iterate. 🔹  Ask a better question Instead of focusing on what's being automated, Emma started asking: 'What would you do with 30% of your time back?' A new dad said he'd finally make it home for bedtime. A manager said she'd finally have time to properly train her team. That question shifts the whole conversation. For context: Emma has automated around 45% of her own role. What she's doing with the time saved? Deeper customer relationships, more strategic thinking, and the work that actually needs a human. She also ran a live demo of Rebel — asking it to pull from her existing memory and produce a transformation methodology one-pager on the spot. It took about 3 minutes. Well worth watching. If you're leading or supporting an AI rollout right now, this one's practical and honest in equal measure.  Full recording here:  https://lnkd.in/gam8RAWQ #PracticalAI #FutureOfWork #AIAdoption