This coming week I’m speaking as a panellist on whether AI is pushing women and underrepresented groups out of tech (thanks to UX Crunch and Female Product Lead for the invite). My first thought on hearing this topic was, how true is it? What’s the evidence for this claim?

Turns out, there’s an abundance of evidence that women and minoritised people are leaving tech. According to Layoffs.fyi, roughly 45% of those who lost their jobs in recent tech layoff waves were women, even though women make up less than a third of the tech workforce and occupy less than a quarter of technical and leadership roles.

Separately, Findem's analysis of FAANG companies showed women were 33% of employees but 44% of those laid off, because the departments where women had gained the most ground (HR, talent, marketing) were particularly vulnerable to cuts.

This means that women are 1.6 times more likely to be laid off than men. This is even worse for black women, where by 2026 their unemployment had reached 7.3%, compared to 3.7% for white women.

The dominant story is that AI is driving women out of tech. But it's worth looking at what the data can actually claim. Two confounding factors stand out. First, this same period has seen a sharp increase in return-to-office mandates, which disproportionately affect women. The majority of caregiving still falls to women, and RTO removes the flexibility that allowed many to stay in the industry at all. Second, the roles most affected by layoffs aren't technical roles being replaced by AI. They're HR, talent, marketing, and DEI, departments where women had made the most progress. So before we accept the headline that AI is pushing women out, we need to ask whether AI is the cause, or just the most convenient explanation.

This is one example of how we can be given a story, and expected to respond in a binary way — accept or reject it. But I think there’s another, better way to respond: to reframe the story completely. If we don’t like the future we’re being sold, what’s the alternative?

Just this week the headlines have been full of stories about our future with AI:

• AI staff ‘genuinely frightened’ for humanity’s future, ex-Anthropic researcher tells BBC

• The U.S.-China race for AI supremacy risks driving us all “off a cliff,” analyst

• The Cybersecurity Apocalypse Is Coming in ‘Months,’ AI Giants Warn

These headlines aren't designed to inform, they're designed to generate fear, and fear narrows our thinking to exactly two options: accept or resist. When people are scared they are easier to control. They all point to a bleak future where AI is going to wipe out humanity (unless we put our trust in authoritarian governments).

But is it really?

We don’t have to accept this future as an inevitability. The problem is, when we reject this version, what are we accepting instead? If there’s no viable alternative presented, it’s hard for people to imagine how the future could be different than the one we’re being sold.

That’s the key to changing this. What kind of future do you want? What should we be building towards instead?

The stories we tell ourselves

Our brains are meaning-making machines. Fed small amounts of data, we look for the patterns between them and relate them to our previous experience. We make sense of the data by creating stories to bridge the uncertainty.

Take for example, that friend who you called yesterday who seemed a bit distracted. You have the data point of how they appeared on the call. Your brain infers why they showed up in that state: they’re stressed with something going on at work, they’re thinking about their mum who’s been ill recently, or maybe they didn’t really want to see you — because they’re upset with you. Your brain collapses the possibilities based on what’s happened before: you had an argument with them last time, so you reason they’re still upset with you. Now your brain creates a whole story around that upset. What was actually a fleeting state for your friend in that moment becomes a whole narrative about your years-long relationship.

It matters less if the story is objectively true than how it feels in your body. Stories that explain how exposed we are to threats activate the limbic system. Notice what happened in that story. The moment your brain landed on 'they're upset with me,' your body responded. Tight chest, slight dread, maybe a flash of defensiveness. That's your limbic system reacting to the narrative as though it were a real threat, because to your nervous system, it is. Once that response kicks in, feelings override rationality. It's a survival mechanism, and it doesn't care whether the story is true.

What’s more, once the story has taken hold confirmation bias seals in it. You look for the evidence that supports the story, and reject the evidence that contradicts it. In fact, you may not even notice that evidence at all because of a phenomena psychologists call attentional blindness (see the monkey business illusion).

This response reduces the cognitive space for creative thinking to happen, to come up with different possibilities and options. Creativity needs a sense of personal safety to flourish. Both Barbara Fredrickson1 and Amy Edmondson2 have studied this, at individual and team levels — positive emotional states and psychological safety allow you to use your whole brain to think more flexibly.

In short, fear reduces your cognitive flexibility making you more willing to accept what is presented without question, whilst safety increases cognitive flexibility so you think critically and come up with more options.

To return to our friend, had the last interaction been positive then you would not have seen a threat in their distraction on this call. You would still have noticed that they were distracted, but you may have come up with other reasons that had nothing to do with you. Best of all, your flight-fight-freeze-fawn response would not have been activated, so you may have just asked them “you seem distracted, is something bothering you?”

Writing the story of our future

Let’s bring this back to AI but with a different example. This week I’ve spoken to three senior product leaders about how AI is impacting product roles, as research for a piece of work I’m doing in partnership with Mind the Product. One of the topics explored was how we bring on juniors.

The dominant narrative now is that AI is taking away entry-level roles. We can first stop to question, is this true? What’s the evidence for this? (as opposed to other reasons, e.g. the cost of running a business in the UK has increased). But going further, we can say — this isn’t the future that we want. All three believe we need to be investing in junior talent. Saying we can cut entry level roles as it’s more efficient to have mid levels working with AI is short sighted — what happens in five years when those mid levels have progressed to senior, or left to start their own companies? There will be a vacuum of succession with nobody trained or experienced enough to fill it.

We have the power to define and design what we want our future to look like. If we believe this is a problem we need to solve, that there is value in creating opportunities and nurturing junior talent, then why aren’t we building that? Miro is one company that invested significantly in creating its own graduate scheme for product managers, product designers and software engineers. For all the rhetoric about ‘product isn’t an entry level role’, here’s an example of a company rejecting that narrative and doing something bold — and with great success.

So the real question isn’t “is this the future we want?” That’s binary thinking, accept or reject, feel the fear and fight it or flee from it.

The real question is: what kind of future do we want to build? That’s a fundamentally different question, because it has no predetermined answer. It opens up possibility instead of closing it down.

The AI story we’re being told right now has technology at the centre and humans reacting to it. But we can write a different story, one that starts with people. What do we need? What kind of work matters? What does a thriving industry actually look like? How do we support the next generation to succeed? AI becomes a tool in service of those answers, not the thing that dictates them.

Nobody is going to hand us that story. The companies building frontier models aren’t going to pause and ask what we want because it’s not in their interests to do so. The media isn’t going to stop writing fear-based headlines because those are what sells. If we want a different narrative, we have to construct it ourselves, starting with the small, concrete decisions we make every day about how we hire, how we lead, and what we refuse to accept as inevitable.

If you enjoyed this article you may like these books:

• The Chimp Paradox: The Mind Management Programme to Help You Achieve Success, Confidence and Happiness, Professor Steve Peters

• The Storytelling Animal: How Stories Make Us Human, Jonathan Gottschall

And if your goal is to build a better future, I can help you through 1:1 leadership coaching.

I was there to give a lightning talk in the afternoon on the Think Tank, the tent for MicDrop, which is the speaking community I’m part of run by Alex Merry. I only had 3 minutes so I knew it had to be super tight, and I didn’t want it to become ‘preachy’ — by the time people heard me they would have been there all day, minds brimming through of ideas. I wanted to leave it up to the audience to take away the most meaningful part to them, and if there wasn’t anything for them in what I was saying, that was ok too — rather than hitting them over the head with a ‘this is what you should do next’ ending (nobody wants homework after a festival!).

I planned to talk about boredom, mainly to subvert the whole concept of ideas (i.e. creativity, novelty) — one way to get to ideas is through the Default Mode Network, which is a mental state you access when you’re bored (day dreaming, auto-pilot, napping). But I also didn’t want to go heavy on the neuroscience, there just wasn’t the time.

So I approached it using a new storytelling technique I’ve learned after reading Storyworthy by Matthew Dicks. If you’ve ever been told to work on your presenting or storytelling, I HIGHLY recommend reading this book. It was a risk trying out a new technique in such a public arena, but also pretty self-contained — on the positives it was to a group of people I knew, who were rooting for me, only 3 minutes, whilst on the negatives it was on a stage, being recorded, at a festival where anybody could drop by. I used MVE to prepare — scripting, recording, rehearsing, drilling, getting feedback, all before delivering it for real on stage.

I’ll be able to share the video with you really soon (in about a week’s time), but in the meantime, here’s what people said: brilliant, nailed the storytelling, I felt like I was right there with you in the habitat. One Linkedin post afterwards: “My favourite wildcard talk was from a female astronaut who had me locked in and in awe.” I even told a joke at the end, which broke the tension in the tent and got a big laugh (another subversion of speaking norms — Freud would be proud!)

Here is the approach I took.

Homework for life

In Storyworthy, Dicks talks about taking 5 minutes every day to write down what happened. It doesn’t have to be long, just a snippet. What made today different from any other day? He combines this technique with free associative writing — setting a timer for 5-10 minutes and just writing non stop, no judgment, not allowing the pen to stop moving — to see what stories naturally come up.

I started my preparation by giving myself the prompt ‘boredom’, and set a timer for 5 minutes to start writing. When I got stuck I would start writing out numbers — one, two, three, four — until the ideas started flowing again. I did this freehand rather than typing, as I actually type fast (100wpm — I started my professional career as a touch typist), and that enabled me to match pace better with the stories.

Afterwards I looked at what I had written, and mined it for the kernels that were interesting, unusual, but entirely relatable.

5 second moment of transformation

The stories that move us most are the ones that reveal some moment of transformation. Without this, Dicks says they’re just anecdotes. The transformation is where the emotional tension comes from — think about falling in or out of love, when you discover something about another person that changes your perception of them forever, reach acceptance or sink into despair. They are small, sudden and powerful, and the complete opposite of the moment before.

I had to mine hard to find that transformation in what I had written. In fact, I struggled with this for weeks. I thought I’m telling a boring anecdote about being bored — where’s the transformation in this? I also had to take a break from everything when my dog passed away — I couldn’t look at any writing or speaking for two weeks after. I was completely devastated and not in the mood to think about work. When I came back to it, I had fresh eyes, and had a moment of inspiration. Sharing that transformation all relied on saying the same thing twice, with different intonation. On the day, it was the part I was most worried about — but I nailed it.

Start the story as close to the end as possible

Looking back at the free writing there was a lot there that was more like filler. We all know to cut the fluff, ‘show not tell’ — but Dicks specific advice to start as close to the end as possible was a game changer. Like any good action movie, I started the talk by putting the audience straight in the action with me: “It was day 3 of being sealed inside the habitat.”

I then identified which details to include to put the audience in the habitat with me, but also give the sense of boredom. I slowed down time with repetition: “Plain white walls. Plain inflatable ceiling. Plain grey carpet.” I dragged those last 3 words out when I spoke them.

Dicks also advised the story had to start with forward movement — I was going somewhere, doing something, actually moving through space. We had been on a simulated EVA, I was waiting for dinner. I was looking around for something to do. But I actually subverted this rule, because the whole point of the boredom was “I had nothing to do”. The boredom actually created a jarring stop in the action, which was kinda the point.

Raise the stakes

According to Dicks, there’s 5 ways to raise the stakes:

1. The elephant: the thing in the room that everyone can see, large and obvious, the need, want, problem, peril etc; this must appear as early as possible

2. The backpack: increases audience anticipation about an upcoming event; load it up with hopes and fears before moving story forward, e.g. suffer first then triumph

3. Breadcrumbs: hint at a future event but only reveal enough to keep them guessing

4. Hourglasses: the moment the story is about, what everyone’s waiting for, slow down; let the audience hang on every word, drag it out as long as possible, use redundant descriptions

5. Crystal balls: false prediction to cause the audience to wonder if it will come true

Can you see which one I used? Yep, the hourglass. But arguably there was an elephant (literally the habitat), and breadcrumbs (being sealed in said habitat) earlier in the story too.

Avoid using ‘and’

‘And’ is a terrible word in stories as it removes all the tension. Instead, use words that signal change: but, instead, therefore, except, so, yet, as a result. These create causal links in the story.

I used these liberally throughout my story, but especially to cement the five second moment of transformation (which I won’t spoil by including here!).

You may recall in my free writing I wanted to be a good writer, and I was going to trust the process.

Now I’m through the other side, I can 100% say that this technique worked for me, and it’s one I will use again and again. And there’s more that Dicks included in Storyworthy that I didn’t even get to try out yet, so there’s more to iterate on in the process for next time.

Where you can catch me speaking next:

• CPO Connect - 30 September: facilitating a leadership roundtable for 90 product leaders in London (membership required - sign up here).

• Agile Cambridge - 1st October: leading a workshop on using MVE to overcome your fear (use discount code 10Caroline to get 10% off your ticket)

• The human side of spaceflight - 7th October: a fireside chat alongside flown astronauts and NASA’s Head of Human Research Programme, talking about the psychological challenges of sending humans to the Moon and Mars (free to join)

Years ago I was Product Director for a health tech startup in Cambridge. We were going through a lot of change, splitting the company to focus on two very different core areas of business. As per every other UK-based health tech company backed by VCs, one side was going after the US market, the other was a delivery partner to the NHS. At the same time, I was hiring for two product managers to join my team so we could move faster. It was chaos.

I also felt deeply conflicted. The change impacted me directly as my reporting lines changed. Whereas before I had reported into someone I greatly respected and admired and learned loads from, now I reported into not one, but two people, with deeply conflicting ideas of what should happen. To make it worse, both wanted to be in the detail. Often I felt caught between a rock and a hard place, with little leverage to resolve conflict or make my own decisions. I was beginning to feel that this wasn’t the place I wanted to build my own career.

And yet, I had to sell the company to candidates. I had to look for the positives in all this mess. And don’t get me wrong, there were some — not least their vision and mission which I still found entirely compelling. I agreed with the what and why; my issues were with the who and the how. I experienced cognitive dissonance and frustration on a daily basis, and I wasn’t the only one. My counterpart in Engineering felt the same, and we leant heavily on each other for support.

Why am I telling you this? Because as candidates applying to roles you don’t really know what is going on behind the scenes.

I coach job seekers who are having a tough time of it: ghosting, rejection, withdrawing offers at the last minute. That’s rough. But it’s not necessarily personal, nor something that the hiring manager always has complete control over.

In an ideal world, companies would be transparent about their current state and challenges. But then, would candidates really want to walk into that?

My own experience with this particular company six months before was that I was joining to own a particular product where we wanted to grow, and naively thought in doing so that I was going to change the world. Instead on day 1, I was dropped into the deep end with my manager saying he was leaving in less than a month, and that I was actually going to lead a cross-functional task force with people I didn’t know yet to solve the company’s biggest problem that had been festering for months.

It was overwhelming.

And the question is, had I known all of that, would I have accepted?

Probably not.

There’s an awkward dance that hiring managers and candidates go through. On the one hand, hiring managers want to paint a rosy picture so the candidate is excited and wants to work there. It’s about selling the company and role, painting them in the best possible light to engineer desire in the candidates.

And candidates want to be sold on this version. They’re often looking because their last role didn’t work out — they no longer enjoy it, there’s no more growth or opportunities, they’re not getting along with their manager, their role was made redundant. They’re looking for the greener grass, a fresh start, a place where all their problems become a thing of the past and work is amazing once again.

So both sides are performing. Both sides are filtering out the unpleasant bits. The system runs on mutual self-deception, until its conclusion when reality hits on day 1.

Once you recognise that this is how hiring really works, then you can learn not to take it so personally when things happen that seem totally bonkers and unfair and dehumanising. It’s not intentional.

And what’s more, you can appreciate how hiring is a two-way process. You are interviewing them as much as they are interviewing you. Now, the trick is that you can’t ask direct questions like ‘what’s the culture like?’ and get an honest answer. But you can look for the red flags that might indicate there’s a deeper problem. And these surface in what they do as much as what they say.

Watch how they communicate. Are they prompt, or do they leave you hanging? When they respond, is it clear and kind? Are they setting expectations for what happens next, or are you chasing? Communication in a hiring process is a preview of communication on the job.

Watch how they treat your time. Are they moving through rounds at a reasonable pace, or dragging you through an excessive number of interviews? Are they leaving proper space for your questions at the end of each round, or rushing you out? How a company values your time as a candidate tells you how they’ll value it as an employee.

Watch who they put in front of you. Have you met people from different teams and levels, or is it the same two or three people every time? Are they giving you specific, actionable feedback between rounds, or generic pleasantries? The breadth of people and quality of feedback tells you how the company shares information and makes decisions.

You may believe that it’s on you as a candidate to impress the hiring manager — but it’s also on them to impress you. We assume a power imbalance, because companies are making the decision whether to offer or not. But that imbalance is not strictly true, because you also have the power to accept, or not.

If you're in job search right now and this resonated, I've built a course that shows you how to handle this. From Stuck to Hired is a self-paced programme for senior product people, covering everything from how hiring managers actually read your CV to navigating interviews as a two-way process. It's £149 until the end of September.

Learn more

My answer? Make sure you’ve got a strong web of relationships across the organisation — up, down and across. Social resilience is one of the five protective shells, the others being biological, psychological, organisational and environmental. When the organisational layer is under threat, you need to make sure you have friends in — and out — of work to see you through.

But before I deep dive into that, let’s take a closer look at what resilience actually is and how to build it.

How do I build my resilience?

Nobody thinks they lack resilience, but we all take it for granted right up to the point where it’s tested. Psychologists view resilience not as a personal trait that you either have or don’t have. Instead, it’s a skill, and that means you can build it, and indeed should always be actively working on it. I particularly like this definition of resilience from the American Psychological Association:

[Resilience is] the process and outcome of successfully adapting to difficult or challenging life experiences, especially through mental, emotional, and behavioural flexibility and adjustment to external and internal demands (emphasis my own).

To understand this further, I’ve adapted a model of resilience from the work of space psychologist Dr Iya Whiteley and colleague Dr Olga Bogatreva: five protective shells (systems) that sit concentrically together and interact to create resilience as an emergent property.

We’re all familiar with biological and psychological — companies love to give us fruit bowls and free yoga classes to help with managing stress. We all know how important it is to have good levels of hydration, nutrition, movement and sleep. Many of us actively work on regulating our emotions, build strong routines and minimise negative self-talk. These are important, but if we only view resilience as a mindset or healthy habits then we are missing the bigger picture.

We may also be somewhat familiar with the concept of social resilience. I came across research on this shared by Bruce Daisley1 years ago and it’s stuck with me: the more social groups we belong to, the more resilient we are. If all we have are work colleagues because we’ve been hustling in our careers and working all hours to the point that leisure time is all squeezed out, then redundancy hits harder than if we’ve also been investing some of our time in playing team sports, or volunteering, or attending community meet-ups.

So social resilience is critical, and most of us intuitively know this. But what about organisational resilience? We’re aware there are things that our companies do that can either increase or decrease our stress levels. Here are the 8 factors that influence our organisational resilience:

• Leadership

• Autonomy

• Role clarity

• Workload

• Recognition

• Fairness

• Team cohesion

• Psychological safety2

Our organisational resilience can be impacted by having too much or too little of each of these. Too much leadership looks like micromanagement. Too little autonomy looks like bureaucratic decision making. Too much role clarity looks like rigid boundaries (‘that’s not my job’). Too little workload looks like boredom. The last three tend to skew towards not having enough rather than having too much.

Let’s look at a worked example for organisational resilience now — the story that I was telling Jenny, my own personal experience where it was missing.

NB: For the purposes of this post, I’m parking environmental resilience, but we will come back to it again in the future (particularly with the heatwaves hitting the UK this year — temperature is a key component as it impacts our biological and therefore psychological resilience!)

What does organisational resilience look like in practice?

I had joined this company specifically with the mission to grow B2B product from nothing to something, with my manager telling me I had full accountability and responsibility for doing so as she was going to focus on B2C. GREAT, I thought, I love having complete ownership of my work. Except there was just one problem: I didn’t get invites to key meetings where decisions were made, and instead had communications filtered through my manager as a conduit. I would give her updates to share in meetings where B2B was being discussed, yet when she was asked questions she couldn’t answer them because she didn’t have the depth of knowledge required. It made decisions slow and frustrating for everyone.

This showed me how little autonomy I actually had in practice. I suggested she invite me to those meetings so I could handle it directly. I got push back because they were broader SLT meetings which I wasn’t part of. What resulted was a vacuum of accountability — technically I had it, but couldn’t fully exercise it, without the input of SLT. It was company strategic priority #1 to grow B2B after all…

So I skipped my manager and started inviting the CPTO for coffee so I could directly update him on what was happening, get his input, and work through matters together. Should we go after everything, as our partnerships team wanted (everything meaning the NHS, Big Pharma, insurance providers, high street pharmacy, universities running studies, private practitioners, personal trainers — can you see the problem?), or should we double down on a particular segment? Should we focus on this being an API play primarily (and building out support around that) or should we build a white label front end for those partners who were less technically savvy? With a small (but mighty!) product team, we could not do everything, everywhere, all at once. Those meetings would go in, and then 15 minutes before they would be cancelled. It was incredibly frustrating to see this lack of interest from leadership.

After trying this approach a few times I decided I needed to change tack, and develop my relationships across the business.

I was already great friends with my counterpart in partnerships, who despite the over-eagerness on every Shiny New Opportunity (I do love my sales colleagues, even when they’re acting like excitable puppies!), became my best thinking partner. We would meet multiple times a week, sometimes daily, to download where we were at, where we needed to get to, and create a plan of attack for growing B2B. Sometimes this was strategy, sometimes it was therapy. More often it was a frank conversation about why he could not sell that particular thing right now, but could sell this one instead. He was in those SLT meetings, and I had more confidence my message was getting through (although I suspected always with a sales spin on it, lols).

Then he was joined by a fractional Chief Commercial Officer whose mission was to grow the partnerships team and embed strong playbooks for business development, and I saw another opportunity for influence. During his onboarding I made sure I was on his list of coffee intros, and was open about where I could do with his help. I think he respected the honesty, and pretty quickly he became another ally and champion in rooms I wasn’t in. We worked together on market segmentation, roadmap development and pricing structures. We made a lot of progress, and I learned a tonne.

Another lateral relationship I developed was Finance. I became friends with the finance manager, who was promoted to director level and started joining SLT meetings — another opportunity to influence in rooms I wasn’t in. As a side note, I strongly believe Product should always have Finance as their number 2 relationship, and what’s more, Finance bloody love being involved. It’s actually such an easy win as a product leader, to bring your two teams closer together. We worked through the ROI on products and features which helped with prioritisation, especially during quarterly planning, and developed business cases for more investment (‘if you want us to go faster, we need to hire more engineers’). In return, I understood the cost drivers of the business, which I fed back to my team. We used them as creative constraints to shape our decisions and adapted our roadmap accordingly.

In the meantime I shielded my team from a lot of the organisational bullshit. Working with the limited information and decisions shared with me, I created a vision of where we could get to with B2B — they loved it. It drew us closer together on a shared mission. It was very much framed around possibility and opportunity, even if the details weren’t all worked out. I was keen to give them as much clarity and therefore autonomy as possible, and was open about where I did not have answers, with suggestions on how we could work through that.

We engaged a lot of sense-making to start with, particularly around whether a particular feature would count as a medical device under the regulations. It was important to identify the right questions to ask, before going in search of answers. We took a very scientific approach to developing the B2B product, developing hypotheses that we would test, and this enabled us to ‘feel’ our way through the uncertainty. We also built a narrative of the mission we were on, and what each of our roles was in that. I made sure to give recognition and celebrate our successes along the way, however small: public shout outs in Slack, cakes, lunches, team nights out, giving them the afternoon off.

There was a lot I was making up for shortfalls elsewhere. I worked myself hard — too hard. I deeply cared about what we were doing because I could see the benefit to patients across the UK. I wanted us to succeed! But the workload was relentless.

I’m sad to say that this was the role where I burned out. Alongside these challenges at work, I was studying part time for my degree in psychology and dealing with some health issues (perimenopause was calling). It also meant I had little time to invest in friendships and hobbies outside of work: every waking minute was spent either working, studying or managing weird inexplicable pains in random parts of my body. Looking back now I can see how my biological, psychological and social protective shells were compromised, which ultimately compounded leading to my burnout. There was one final frustrating meeting that I couldn’t bounce back from, and I broke. I took several weeks off sick before deciding I wasn’t going back. The rest is history.

How I view resilience now: it’s not built in one single layer. It’s built across all five protective shells, and we must consistently work on each: how they interact and compound together is where true resilience lies. When change hits and one shell is compromised, the others can absorb it. When multiple shells fail at the same time, that's when we break. I didn't burn out because of one bad meeting. I burned out because my biological, psychological, social AND organisational shells were all compromised at once, and there was nothing left to absorb the impact.

Which shell/s have you been neglecting? What could you do to build your resilience today?

If you’re looking to improve your resilience right now, there’s a few ways we can work together:

• 1:1 leadership coaching

• Book me to speak or train your team

• Watch my TEDx

Home to the UK’s largest full dome planetarium, over 150 interactive experiences, and the iconic Rocket Tower housing Blue Streak and Thor Able rockets, a real Moon rock, and the Apollo Lunar Lander.

I highly recommend the planetarium show, One Step Beyond: Our Journey to Mars — it made me feel very emotional during the ‘7 minutes of terror’! You can then follow that up with a ride on the Tetrastar Spaceport.

This summer there’s a brand new exhibit on the outer Solar System, and an Online Space Club for kids aged 7-11, if you’re looking for activities to do at home.

Entry: Adults - £19.72, Children 5-15 - £17.93, Under 5’s - free (concessions available, convert your day ticket to an annual pass for free).

Visit the National Space Centre →

#2 - Science Museum, London

The Space gallery includes Helen Sharman’s spacesuit, a 3.5-billion-year-old piece of the Moon from the Apollo 15 mission, and a six-metre engineering model of BepiColombo.

They also run regular Astronights, which happen after hours where you can sleep over in one of the galleries. Sensory nights for children with SEND, which are more relaxed, are also held regularly.

AND until 13 September, they’ve partnered with Star Trek on an exhibit to celebrate 60 years of boldly going where no person has gone before (that’s my excuse to go back this summer!)

Entry: Free (although donations are welcome!)

Visit the Space Museum →

Bonus: Just around the corner in South Kensington is the Ampersand Hotel, which offers a science themed afternoon tea. Tuck into Moon cakes and galactic macaroons. Kids, vegetarian and vegan menu options available.

#3 - Jodrell Bank, Cheshire

Tucked away in fields in Cheshire, Jodrell Bank is a UNESCO World Heritage Site and home to the Lovell Telescope, the UK’s largest radio telescope. The new First Light Pavilion tells the story of Jodrell Bank from its post-war origins through the Space Race and Cold War to today’s discoveries.

You can listen to sounds from deep space, see live signals from the telescope, and catch planetarium shows.

Entry: Adults - £15, child - £10.50, all tickets are annual tickets (concessions available).

Visit Jodrell Bank →

Public Service Announcement: Help Jodrell Bank! It faces losing all its core annual funding of £2.8 million. Unless this decision is reversed or new funding is secured, ALL scientific work will end on 1 April 2028, and this historic site could close forever. Please sign the petition to urge the government to review this decision.

#4 - Royal Observatory Greenwich

The astronomy team has temporarily relocated to the National Maritime Museum with Astronomers Take Over, a hands-on planetarium experience. Meet real astronomers, try to land a Mars rover, and step inside a galaxy box to see how amazing our universe is.

At the Observatory itself you can see Luke Jerram’s mirror moon, touching craters, valleys, mountains and lava fields. During weekends you can get hands-on with a telescope or try your hand at using a sextant.

Entry: Adults - £16, Children 5-15 - £14, Under 4’s - free (concessions available).

Visit the Royal Observatory →

#5 - Dark Sky Reserves

For raw stargazing, the UK has several International Dark Sky Reserves, including Northumberland, Brecon Beacons (Bannau Brycheiniog), Exmoor, and the South Downs.

There’s also the OM Dark Sky Park and Observatory near Cookstown in Northern Ireland, with holographic installations, VR headsets, and audio-visual shows.

Visit Dark Skies parks →

PS. On 12 August there will be a partial solar eclipse, where around 90-96% of the sun will be covered by the Moon in the UK (in Greenland, it’s a total eclipse, the first one since 1999!). First contact starts at 6.08pm in Edinburgh, and 6.17pm in London, with the eclipse maximum expected around one hour later. Remember to never look at the sun directly with your eyes, always use eclipse sunglasses or a solar telescope.

Happy space geeking! 🚀

This has been months in the making, and I’m so excited to share it with you.

Please watch, like, comment, share — to help spread my idea.

Why I did this TEDx

For the majority of human spaceflight history, women have been a side note if not written out completely. The historical global total of astronauts that are women is just 11%. Like many girls, I grew up fascinated by space, but did not see it as a pathway open to me to build a career.

I don’t want us to repeat that mistake for girls now. It’s taken three generations for us to go back to the Moon, but it will only take one more to get us to Mars. NASA plans to send humans to Mars by 2040, and women need to be driving that mission forwards.

Since giving my talk I’ve heard from many parents who say it’s inspired their daughters to become interested in space. One audience member came up to me after the talk to tell me “My daughter saw your talk and is now thinking about if she could go to space.”

That is why I gave my talk.

I want to challenge who we see as explorers, as leaders, and who we picture when we hear the word ‘astronaut’.

You can also follow along my #womeninspace series on Linkedin, Instagram and YouTube to say the names of women astronauts with me.

Three qualities needed to get us to Mars

My talk was underpinned by research that Dr Iya Whiteley conducted in partnership with the European Space Agency into the psychological challenges of long range space missions, leading to the publication of ‘Toolkit for a Space Psychologist’:

Resourcefulness: when we go to Mars we need to take everything with us — fuel, food, oxygen, water, medical supplies, clothing, and more. And we need to have the skills so we can fix things that break: mechanical, electrical, sewing, medical.

Resilience: the mission is hard enough when everything is going well, but when shit hits the fan (sometimes metaphorically, sometimes actually in space!) then the crew must pull together and overcome the adversity without losing their minds.

Autonomy: the further the crew travels from Earth, the longer the communications delay with mission control. By the time they reach Mars they will be on their own, unable to call home for real-time help.

We must select astronauts that have the qualities this mission demands, and not who we have always chosen as the default.

What the research says

I draw on several pieces of research into leadership and team dynamics in extreme environments:

(1) The Ice Maidens: six women from the British Army made history by skiing across Antarctica unaided. Antarctic expeditions are analogues for how teams might work together in space, and this showed how women develop strong camaraderie and care for each other to guarantee mission success.

(2) Women and men in space and Antarctica: There were 3 key papers I used as background reading here:

• Leon, G.R. and Sandal, G.M. (2003) 'Women and couples in isolated extreme environments: applications for long-duration missions', Acta Astronautica, 53(4–10), pp. 259–267. Available at: https://doi.org/10.1016/S0094-5765(03)00138-3.

• Bell, S.T., Brown, S.G., Abben, D.R. and Outland, N.B. (2015) 'Team composition issues for future space exploration: a review and directions for future research', Aerospace Medicine and Human Performance, 86(6), pp. 548–556. Available at: https://doi.org/10.3357/AMHP.4195.2015.

• Leon, G.R. (2005) 'Men and women in space', Aviation, Space, and Environmental Medicine, 76(6, Suppl.), pp. B84–B88.

(It’s worth noting that Suzanne Bell is Lead Scientist at NASA’s Behavioral Health & Performance Lab, her Linkedin headline is literally “Leading Super Cool Space Projects that Get Humans to the Moon and Mars (and back)”).

(3) A meta-analysis of what the past 50 years of research into leadership tells us about who makes an effective leader:

• Paustian-Underdahl, S.C., Smith Sockbeson, C.E., Hall, A.V. and Saldanha Halliday, C. (2024) 'Gender and evaluations of leadership behaviors: a meta-analytic review of 50 years of research', The Leadership Quarterly. Available at: https://doi.org/10.1016/j.leaqua.2024.101811.

This last one makes some people uncomfortable. It draws on corporate leadership research, so in a strictly scientific sense it may not be directly generalisable to spaceflight populations. But its scale is hard to ignore: 180 studies across 50 years, with sample sizes reaching into the millions. Analogue mission research gives us depth in extreme environments; this gives us breadth. Together, they tell a consistent story.

My own analogue astronaut experience

Analogue missions are simulations that replicate what it’s like to live on the Moon or Mars. They’re used by space agencies to research the science, engineering and psychology of human spaceflight, and to train astronauts. LunAres in Poland, where I was last year, has trained astronauts including Dr Sian Proctor, who became the first African American woman to pilot a spacecraft as mission pilot on SpaceX's Inspiration4 in 2021.

If you would like to learn more about this then please read through my other articles:

• Inside an analogue space mission

• How to adapt to an alien environment

• The social life of a space habitat

• Inside the psychology of confinement

• Space to Lead: Psychological adaptation and resilience in analogue space missions (published by the BPS)

• How to thrive in space (published by the BPS)

If you’ve made it this far and haven’t watched the talk yet, go do that now :)

Then let me know what you think — I read and reply to every comment on the YouTube video.

And if you know a girl interested in space then show her the video too, and let’s see what we can inspire in the next generation of astronauts.

The standard advice is to ‘manage up’: understand their priorities, own your 1:1s, and adapt to their communication style. However, this avoids an uncomfortable truth: that you may not be able to change or improve the relationship with your manager, particularly if they don’t want to.

Your manager has a particular kind of power that you can’t access: authority. Authority comes one’s position in the hierarchy, not from expertise or trust, and works downwards through the organisation. However, authority must be exercised carefully because misuse will degrade performance: people will do what they're told, but they won't give their best thinking.

Many ineffective managers have the same issue at their core: they over-rely on their authority to get things done, which puts them into Parent mode. According to Eric Berne, a psychologist who created Transactional Analysis1, there are three ego states:

1. Parent: You think, feel and behave as your parents or authority figures did. This splits into Nurturing Parent (supportive, protective) and Critical Parent (judgmental, directive, rule-enforcing).

2. Adult: You respond to the present moment using facts, logic and rational assessment. This is the ego state that processes what’s actually happening rather than replaying old patterns.

3. Child: You revert to the thoughts, feelings and behaviours you had as a child. This splits into Free Child (creative, spontaneous, playful) and Adapted Child (compliant, people-pleasing, conflict-avoidant, shaped by the need to keep authority figures happy).

Now if your manager is in Critical Parent mode it will look like micromanaging, being overly-directive, and using feedback as a list of deficiencies. Arie Nadler2, a social psychologist who studied help-seeking and power dynamics, found that people in positions of authority tend to give dependency-oriented help: they provide the answer, give you the list of what to fix, or solve the problem for you. The alternative is autonomy-oriented help: helping you understand the principle so you can solve problems yourself. A manager who always gives you a shopping list of deficiencies without helping you understand the standard behind it is, whether they realise it or not, keeping you dependent.

Unfortunately, this behaviour can lead to you doubting your own competence. I’ve worked with clients going through difficult times with their manager, who end up developing unhelpful beliefs such as:

• “If I ask for what I need, it will be seen as weakness or incompetence.”

• “If I just work harder and get it right, the relationship will improve.”

• “Their judgement of me is more accurate than my own.”

And these create changes in the behaviour of my clients: they start deferring their own judgement, filtering what they say to their manager, engaging in people-pleasing behaviour, and becoming perfectionists. All of these are self-protective ways of being when the ego feels under threat — but they are also signs that you have slipped into Adapted Child mode.

The antidote is to stay in Adult mode, and actively seek autonomy-oriented help by responding calmly and with curiosity:

• When you get feedback on deficiencies, ask questions rather than accepting the list as evidence of what you need to fix: “Can you help me understand the standard you’re measuring me against?”

• Stating what you need from the relationship: “I work best when I have clarity on your expectations upfront.”

• Naming a dynamic that isn’t working: “This isn’t working for me, can we talk about how we communicate on this?”

• Making decisions based on what the situation requires rather than what you think will keep them happy: “I think this is the best course of action, based on x, y, z.”

Alongside this, protect your sense of professional identity. A Critical Parent manager will erode your confidence over time if their assessment is the only data point you're working from. Build an external evidence base: talk to peers, engage with your network, calibrate yourself against people at a similar level in other organisations. If the external evidence consistently tells you that you're well equipped for your role, then the problem is the relationship dynamic, not you.

And this leads us to an uncomfortable conclusion. If your manager cannot or will not shift out of Critical Parent mode, you staying in Adult mode will create friction. You may get a crossed transaction: you respond calmly and factually, and they escalate because you’re not playing the expected role. No amount of tactics, whether it’s social contracting, a ‘manual of me’, or better-structured 1:1s, is going to fix a dynamic where one person refuses to meet the other as an equal.

On the surface, this realisation can feel disempowering. But recognising that the dynamic won’t change is actually where your agency begins. You have three options: stay and manage the friction consciously, knowing the cost and choosing to absorb it for now; escalate by finding a sponsor or senior leader who can intervene; or leave, on your terms, before the relationship does lasting damage to your confidence and career. All three are valid. The one option that isn’t valid is staying in Adapted Child mode, filtering yourself, working harder, and hoping it gets better — because as Lenny’s research shows, that is the path to burnout.

If you found this useful, here’s how I can help you more:

• Develop your career as a leader with me through leadership coaching.

• Inspire your team to change their beliefs through company keynotes and workshops.

• Join the waitlist for my new book, Beliefocracy: How our beliefs govern us.

Yet being able to give a good presentation is becoming increasingly more important if you want to progress in your career. Leaders often have to stand up in front of the whole organisation to share information. Many leaders I coach mitigate their fear with thorough preparation, but that’s not always possible. How many times have you been put on the spot and asked to say a few words at the next company-wide meeting? (I know I was, many a time!)

Living alongside that fear may be a belief that ‘I’m a rubbish public speaker’. Sometimes this is our fear talking, sometimes there is early evidence that this is true — we can all think of that one presentation that didn’t go the way we wanted it to!

So how can you overcome your fear of presenting, get out of the trap of not feeling ready, and change your beliefs around your ability as a speaker?

This is where Minimum Viable Exposure (MVE) comes in. Based on exposure therapy and tried and tested through working with my coaching clients, workshop participants, and my own personal experience, this method systematically breaks down the Big Fear into a series of smaller, more manageable exposures that stretch the boundaries of what you are comfortable with. Taken step by step, it builds you up to feeling confident enough to tackle the Big Fear by the end.

In the rest of this article I’m going to walk you through how I applied MVE to giving my TEDx talk a few weeks back.

What’s the deal with a TEDx?

TED is a non-profit organisation that “believes powerful ideas, powerfully presented, move us: to feel something, to think differently, to take action”. The main brand, TED, has platformed highly acclaimed researchers, thought leaders and people with big ideas and profound experiences, like Brené Brown, Simon Sinek and astronaut Chris Hadfield. TEDx is the licensed version of TED, that enables volunteer licence holders to independently organise events to platform local speakers with big ideas. For many speakers, it’s a lifetime goal to give a TEDx talk.

Doing so comes with the following constraints:

• You must have a big idea worth sharing: this isn’t a platform for self-promotion, covert selling or recycling the same old tired ideas, and getting selected involves a lengthy process of application and audition.

• A time limit: you must share your big idea in less than 18 minutes (some TEDx’s require this to be even shorter, e.g. mine needed to be under 12 minutes)

• No notes: the entire talk must be given without notes, either in your hand, on a device, or on a prompter in front of you.

• Discourage the use of slides: a few diagrams and photos are ok if they’re necessary for the idea to be conveyed, but slides with lots of words and bullet points are prohibited (you cannot use your slides as a prop!)

You stand on the red dot in the middle of the stage and deliver your talk to an audience you don’t know, whilst it’s being recorded to then be broadcast around the world on the TEDx YouTube channel (that has 44.5 million subscribers).

No pressure then!

So how did I use MVE to deliver my TEDx talk? I broke down the task into a series of smaller steps, following what Stephen Covey says about ‘start with the end in mind’.

Step 1: Get clear on my big idea

I was clear on this from the outset: my big idea is that women should be the first humans to walk on Mars. We’ve already sent the robots there!

I worked on developing my idea with the help of my speaking coach, Alex Merry. I worked through several exercises he shared to get clear on my message and who it was for. What I was hoping is that it would open up a conversation with NASA, ESA and other space agencies — get me on their radar for potential collaborations down the line (research, astronaut training, maybe even science communication).

When I was clear on my big idea, I was ready to apply.

Step 2: Land the slot

Alex, my speaking coach and a former TEDxClapham organiser, knew it was a numbers game. He set me a challenge: apply to 10 by the end of the year. Organisers judge applications differently, some on the written form alone, some on video, some via audition, but having already done the work of defining my idea, who it was for, and why now, I was ready for whatever they asked. Six applications in, I got my first invitation to audition.

TEDxWolverhampton invited me in early January 2026. I’d already had a couple of outright rejections by then, so I really wanted to land this one. If you’ve been through a competitive promotion process, you’ll recognise that feeling: the ones you didn’t get still sting, even when you know it wasn’t personal.

Competition was tight: 196 applicants, 32 auditions, 12 spaces. I had three minutes to introduce myself and my idea, and treated it like a pitch, not an introduction. I wrote it out, timed it, and practised until it landed bang on time, a few seconds spare.

And of course, I was selected — yay!

Step 3: Get into the detail

First up was the research phase, gathering the evidence from psychological studies. Then the construction of the argument. I weaved stories from my experience as an analogue astronaut and from space history throughout. I had way more material to work with than I needed, so I had to chop a lot of detail out.

I played devil’s advocate — as an audience member with no background in space, would this make sense? I was conscious to treat the gendered leadership research as not a critique of men, but rather the system that has a narrowly defined sense of what leadership is.

Step 4: Get feedback, but use wisely

You’ll find when you’re giving a TEDx talk there’s no shortage of people with advice, and whilst well intentioned, it’s not all equal. I chose to listen to the people who had experience in this, and say thanks but disregard anybody else’s.

The organisers and Alex gave me script feedback and I evaluated that with each iteration. The most helpful feedback was how it was landing to them as an audience, because if they didn’t understand something then neither would the audience on the day. This was probably the most valuable part of the process in de-risking the content.

Step 5: Say it out loud

Reading the script out loud is a totally different experience to just reading it in my head. You can hear when the script catches — the words that are a little too heavy, a little unclear, a little difficult to get out.

In particular I had unconsciously included a tongue twister early on (“Your suit sensors are showing pressure loss - stand by for emergency protocol” — try saying that without sounding like Sean Connery!), and whilst I played around with different configurations of those words to try and break the ‘shhhh’, I ultimately ended up keeping the original and saying it slowly and enunciating properly.

Step 6: Show up to rehearsals

It helped that the organisers were very experienced, this was their ninth year running the show, with a clear schedule: eight rehearsals and four script deadlines. I blocked out time every week to work on the script early, rather than leaving it to the last minute. So much of giving the talk relied on familiarity with the material, transference into long-term memory, and that only comes from multiple exposures over time, not one big push at the end.

All rehearsals were in person, which involved a 2.5 hour journey each way from home. I experimented with the train but ended up getting stranded overnight in Birmingham coming home one night, so I opted to drive for the remainder. That meant scheduling recovery time the following morning — one night I didn’t get in until gone midnight because of roadworks and diversions!

It was important to me to show up, even though I only stood on the dot for about 15 minutes each time. I knew that if I didn’t I wouldn’t get used to saying my talk in front of an audience, seeing their reactions and hearing myself say it out loud. Each rehearsal built my confidence with what — and how — I was saying it.

Step 7: Practice, practice, practice

Early on in the process I read about Dr Jill Bolte Taylor, a neuroanatomist whose TED talk, My Stroke of Insight (about her studying her own stroke!), has garnered 30 million views. She practiced her talk 200 times before delivering it.

I thought, if it’s good enough for Jill, it’s good enough for me!

By late May, about one month out from my own TEDx, I reckon I had already practiced it about a hundred times. So in that last month I practiced it three times every single day. I recorded myself saying it, and listened to it first thing in the morning. I played it walking my dogs around the field — it was the perfect length to put on when I left the house and finish by the time I got back.

Step 8: Set your own standard for ‘good enough’

I recited my talk aiming for word perfect. Now, a lot of people say don’t do that because it will make the performance sound stiff, but I ignored them for two reasons: first it was important that I nail every single aspect of the talk, and there were a lot of facts and numbers I didn’t want to mess up and have immortalised on tape, and second I knew that if I knew my talk that well then I could inject energy into it, drawing from the live moment and the audience in front of me.

I practiced it everywhere: in different rooms in my house, in the garden, in Tesco, in the car, on trains, even in an MRI scanner when I had brain images taken (that one was noisy and it really tested my memory). I drilled the specific bits that I got stuck on, and the start and the end. I knew if I could land those the rest would work itself out.

Step 9: Sort my outfit

For some people, what they wear to give a TEDx talk is an afterthought. Mine wasn’t. Before I’d said a word, I wanted the audience to trust that I knew what I was talking about, and how I looked was part of establishing that.

My flight suit from last year’s analogue mission wasn’t right for the stage, so I went with a flight jacket instead: something that still read as credible, without getting in the way of the talk itself.

Then I built the story I wanted my jacket to tell. I commissioned a bespoke mission patch from Tim Gagnon, who has designed patches for NASA and ESA astronauts, and paired it with my own patch from LunAres and a Union Jack. Together, they said what I couldn’t say in words before I’d even opened my mouth: I am an analogue astronaut and I know this world.

Step 10: Run my own dress rehearsal

The week before the main event, I realised I’d only ever practised live in front of other speakers, organisers, my coach, and my partner, Edd. I had a moment of panic: would it land the way I intended? So I reached out to the women in my mastermind group, who generously jumped on a call so I could run it past them.

Their reaction took me by surprise. Tears in their eyes, and one word: “brilliant.”

I needed that. Underneath the preparation I'd been carrying my own imposter feelings, worried that people already working in the space sector, people like Dr Suzanne Bell, Head of the Behavioural Science and Performance Laboratory at NASA, would question my research or my application of it. Academic credibility matters enormously to me. Their feedback didn't erase that fear, but it confirmed the argument was worthy and the story engaging, which were the other two things I needed to know were true.

(Side note: It probably also helped that in this timeframe the crew for Artemis III was also announced, which received a lot of backlash for the lack of women on the roster.)

Each of these steps built on what came before, chipping away at the belief that had been underpinning the whole process: “I’m not sure if I’m good enough for this.” As a process, MVE creates the evidence you need to invert that belief: “I am good enough, and I can do this”.

I stood on that red dot on 27 June 2026 feeling more than ready — and when I came off, I wanted to do it all again. Backstage I’d felt nervous, but it was the good kind: anticipation, not dread.

You don’t need a TEDx talk to test this for yourself. You need a high-stakes moment that scares you: the investment pitch, the All Hands meeting, the promotion panel. Using MVE, you can break it down into smaller exposures, and get your reps in.

You ‘get ready’ by doing the thing that scares you.

Minimum Viable Exposure is one of the techniques I teach in my workshop, From Burnout to Breakthrough: Resilience and Stakeholder Relationships. If your organisation is going through a lot of change, this practical workshop drawing on astronaut training techniques will show you how to build the muscles to adapt quickly and sustainably — without burning out. Book a call to find out more.

Our conversation prompted me to research the mission, and I came across a key paper by Ushakov and colleagues1. It pointed at something the tech industry has missed: we talk a lot about wanting autonomous teams but we don’t really understand what we’re asking for.

How the tech industry defines ‘autonomous teams’

A quick Google search of ‘autonomous tech teams’ brought up Martin Eriksson’s article on Mind the Product from back in 2018: Your team is smarter than you are: why autonomous product teams work better. I remember reading it at the time and thinking ‘this is revelatory!’ — a whole new way of working where teams could work independently of others, have no need of central teams such as legal or finance, which create dependency that slows them down. Sounds great, right?

I worked in teams like this, and even set them up myself when I became a Product Director. And they do work. Having all the skills and knowledge in a single team to enable them to operate self-sufficiently means more features get shipped, faster.

Except there’s a problem with this version of autonomy: it only works horizontally. True autonomy, as the Mars 500 mission illustrates, also functions vertically, i.e. independent of leadership. Several mission parameters drove this:

• A communication delay that grew from 12 to 20 minutes over the mission, including one full week with no contact at all.

• No possibility of resupply once the simulated ship was beyond reach.

• A crew who, the longer the mission ran, became more competent with their own systems than anyone on the ground.

This combination meant the crew couldn’t rely on Mission Control to help them in real time, and increasingly didn’t need to. Instead, they figured things out for themselves — and they didn’t always tell Mission Control afterwards.

And this principle transfers beyond the simulation. Vertical autonomy emerges whenever a team is operationally competent AND leadership is structurally unable to help in real time. You don’t need a 20-minute delay for that, you just need a team who has correctly concluded you can’t help them with the problem in front of them.

Relating this back to tech, many leaders are not (yet) willing to let go and have fully autonomous teams. Instead, we have delegation within constraints. ‘You have authority to do xyz — but no more’. That’s not true autonomy. Have you ever felt ‘caught out’ when your team solved a problem you didn’t know they had, and you heard about it from elsewhere? How did you handle that?

If you believe you need to know everything your team is working on then they’re not autonomous. And that's ok, so long as you're honest. Telling them they're autonomous when they’re not is lying to them — and yourself.

What genuinely autonomous teams need from leaders

Autonomous teams don’t want less of you — but they do want a different kind of presence. The Mars 500 crew didn't reject Mission Control entirely. What they wanted was:

• Interest in what they were doing and confirmation the work mattered — this positively impacted the crew’s motivation;

• Contact with family and friends, and with their national psychological support groups;

• Mission Control to shift from instructive to advisory, and respond to what the crew actually asked for, not what the controllers thought they needed to know.

And this gives you a guide for how you can better lead autonomous teams.

First, being clear on the vision and mission objectives becomes the top priority. I’ll come back to Martin as he’s recently published The Decision Stack to help tech teams figure this out — well worth a read. As a leader, your job is to make sure there is absolute clarity on where you are all heading, so your teams can make their best, informed decisions on how to get there. Plenty of teams want autonomy — and leaders want to give it — but without clarity on the mission all you get is chaos.

Second is giving people the freedom to choose when and how they work — revolutionary, I know. But this isn’t a perk. Autonomous teams need a support system that isn’t you. This means time for relationships with people outside the workplace and the routines that sustain them. RTO mandates crowd these out, which means the only support structure left is… you. That’s great if you’re aiming to create dependency, not if you want autonomous teams.

Third is accepting that you won't be in the loop on everything. Not when things go well, and not when they go badly. The team will resolve problems without you, and sometimes you'll find out late or not at all. Your job becomes making sure they have what they need to decide well — and getting out of the way.

Stop parenting your team

I’ve been circling a deeper organisational dynamic in this article that I’ve seen play out in every single company I’ve worked with. You may have heard of transactional analysis, a psychotherapeutic model developed by Eric Berne in 1957. This explains how we relate to each other in adaptive and maladaptive states — Parent, Child and Adult.

Many organisations still adopt a paternalistic approach to collaboration: leaders tell teams what to work on, and whether that work is ‘good’ or ‘bad’ through feedback. This mimics experiences from earlier in childhood, and moves some individuals into a Child state, seeking approval from the Parent (leader) on their behaviour.

Limiting autonomy is what we do with children — deliberately, so they can learn safely. That instinct is appropriate to a parent, but it's not appropriate to a leader.

Yet that limitation is expressed in the workplace through delegation — we instruct teams “you are responsible for delivering this piece of work, by this deadline, with this scope, with these people”. They get positive feedback when they comply, and ‘developmental’ feedback when they fail. The hierarchy enables power to flow only when the leader chooses, and specifically over what they want to control.

And remember the 'caught out' feeling I asked about earlier? That's the Parent state activating. The hurt, the sense of being out of the loop, the urge to ask "why didn't you tell me?" — none of it makes sense in an Adult-Adult frame, where the team's silence is just an operational judgement about your usefulness to the problem in front of them. It only stings if you were unconsciously holding a parental position all along.

The Parent state is anxious. It needs to know, to approve, to feel in control. The Adult state is curious. Interested in what's unfolding, comfortable with not running the show.

Adult-Adult is a relationship between two people who are both treating each other as competent, capable, and equally responsible. Neither party is positioned above the other. Information is shared because it's useful, not because one party owes it to the other. This makes disagreement possible without threat to status, and uncertainty can be admitted on both sides. The leader brings their context and perspective as one voice in the conversation, not as the deciding one.

It would sound like “Here is your mission, I trust you to do this, I am here if you need my input” — and then get out of their way.

If that sounds difficult, here’s a closing thought: the issue of team autonomy is one that NASA, ESA and other space agencies are taking seriously, as we look to send humans to Mars in the 2030s and beyond. If the space sector can spend hundreds of billions of dollars on this mission, trusting the crew to make the right decisions in service of the mission objectives when there’s a contact delay of 44 minutes — I’m sure you can trust your team to make the right call too.

NASA Administrator Jared Isaacman said those selected are “the best astronauts to undertake and complete the mission's objectives”. With a corps of 37 astronauts, 15 of whom are women (41%), it’s hard to agree with that logic. Part of the argument, that this is a mission testing docking procedures and so needs skilled pilots on the crew, doesn't stand up to scrutiny. The crew NASA actually selected isn't built exclusively around piloting expertise: Bresnik commands, Parmitano pilots, and Douglas and Rubio fly as mission specialists. And even if it were, there are four women in the corps with the credentials to fly this mission: test pilots Jasmin Moghbeli, Nicole Aunapu Mann, Jessica Wittner, and flight instructor Nichole Ayers. Put simply, politics interfered in this selection. The current US Administration’s allergy to DEI initiatives is well documented, including rolling back a pledge on landing the first woman on the Moon.

Artemis III is the most operationally exposed of the Moon missions currently planned. Whilst Artemis II sent the space capsule around the far side of the Moon, and Artemis IV will land humans on its surface for the first time in 50 years, Artemis III is essentially an equipment test that won't break out of Low Earth Orbit (LEO). An essential step for testing the Human Landing System developed by SpaceX and Blue Origin, this mission is all about operational risk reduction. And that context matters for who gets selected.

What the research says about team composition and performance

I’ve been trawling through the research on the gender composition of teams, and the impact of that on team performance, as part of preparing for my TEDx (which is less than two weeks away now!). Studies from the late 2000s through to last year show findings that look mixed at first glance, but a clear pattern emerges once you account for context. Let me take you through it now.

Joshi & Roh (2009) — The Role of Context in Work Team Diversity Research: A Meta-Analytic Review (Academy of Management Journal)

A meta-analysis of 39 field studies, covering 8,757 teams, which examined how diversity (including gender) relates to team performance — and crucially, how the context changes that relationship. The analysis found that gender (and other relations-oriented diversity like race and age) had a tiny negative effect. However, this meta result is masking large variation within individual studies. Once you account for context, the effect sizes double or triple.

They also found a temporal dimension: short term teams benefit from diversity, whilst long term teams suffer from it.

So the question ‘is gender diversity good or bad for performance?’ only makes sense when you specify the team context.

Woolley, Chabris, Pentland, Hashmi & Malone (2010) — Evidence for a Collective Intelligence Factor in the Performance of Human Groups (Science)

Across two studies with 699 people in small groups, a single statistical factor — collective intelligence — predicts how well a group performs across a wide variety of tasks, much like general intelligence does for individuals. Collective intelligence was not strongly predicted by the average or maximum IQ of its members. Putting smart individuals together does not automatically produce a smart group.

Instead, three factors predicted collective intelligence: average social sensitivity of members, equality in conversational turn-taking, and the proportion of women in the group. The gender effect was largely mediated by social sensitivity, i.e. women in the sample scored higher on social sensitivity than men.

However, this lab-based study did not engage with the contextual moderators Joshi & Roh had flagged a year earlier.

Curșeu, Pluut, Boroș & Meslec (2014/2015) — The Magic of Collective Emotional Intelligence in Learning Groups (British Journal of Psychology)

Here the researchers studied 100 student learning groups (528 students) at two time points four weeks apart. They found that the higher the percentage of women in a group, the more collective emotional intelligence the group developed. Collective emotional intelligence in turn increased group cohesion, reduced relationship conflict, and improved group effectiveness.

This builds directly on Woolley et al’s work to show that women, on average, bring higher social sensitivity and more communal traits, which seed emotionally intelligent group norms.

Bell & Outland (2017) — Team Composition Over Time (Research on Managing Groups and Teams)

This is a chapter in a book rather than a paper, so synthesises previous research findings on team composition and how that shapes dynamics across a team’s lifecycle.

The authors state that surface-level composition variables like gender tend to have fleeting effects: their influence often fades as team members get to know each other and deeper-level attributes take over. However, they also flag that Curșeu et al. is a notable exception where gender composition had durable effects via collective emotional intelligence.

Read this in the context that teams are increasingly dynamic — membership churns, boundaries are fluid, people belong to multiple teams at once — which complicates any snapshot view of composition.

Kearney, Gebert & Voelpel (2022) — Gender Diversity and Team Performance Under Time Pressure (Journal of Organizational Behavior)

This study directly tests how gender diversity interacts with time pressure — particularly relevant for high-stakes operational teams. The researchers argue that gender differences in moral reasoning could increase the chances that different viewpoints and interests are considered when completing the task, and gender differences in risk preferences could help ensure that teams strike a sensible balance between taking too much and too little risk.

Interestingly, the study used complex tasks, like hidden-profile and conjunctive tasks, where contributions from all team members are required and information must be elaborated rather than just aggregated. This task structure resembles mission-critical operations where distributed expertise has to be integrated under pressure.

The proposed mechanism is that gender-diverse teams under time pressure are less likely to withdraw and more likely to engage in information elaboration, leading to better outcomes on complex tasks. However, the authors flag a limitation: their research was conducted with newly formed student teams, leaving open how team tenure and trust interact with these effects in real-world high-stakes settings.

Enache, Scarlat, Charalambous, Duboisée de Ricquebourg & Shields (2025) — Gender Diversity Helps Teams Maintain Integrity Under Pressure (Harvard Business Review)

New research found that simply having more women on the team tilted behaviour toward greater honesty in financial analysis, acting as a form of soft regulation that arises organically from within the team, complementing formal compliance and external oversight.

The mechanism described is resistance to optimism bias and conflict-of-interest distortions under pressure — gender-diverse teams were more likely to flag risk honestly rather than go along with rosy projections. This finding is relevant to any high-stakes setting where there’s pressure to conform to an optimistic operational narrative (like wanting the docking procedure to be a success).

The variables that influence gender’s effect on team performance

Taken together, these five studies show a number of variables that influence whether the gender of a team has an impact on their performance:

• Time pressure

• Task complexity

• Team tenure (how long they have been formed)

• Industry status hierarchies

• Whether the setting itself is male-dominated

Astronaut crews sit at the intersection of all of these variables:

• They train together as a team for years, before going on a mission that may only last weeks: this intensity to duration ratio is unusual, and the previous findings may not easily extrapolate for the different phases an astronaut crew goes through.

• Astronauts train not just to pilot rockets, landers and space capsules, but also in geology, photography, emergency medicine, equipment maintenance and repairs (Christina Koch famously was the crew’s plumber when the space toilet wasn’t working!) — and more.

• Space is notoriously gender unequal: according to UNOOSA, women make up around 25-30% of the space workforce globally, and just 11% of all astronauts to date.

The short of it is this: gender diversity hasn’t been extensively studied by NASA. In Apollo it wasn’t a factor as all the astronauts were men, and in the space shuttle and ISS era it wasn’t systematically studied.

So to bring it back to what Isaacman said: the best people for this mission have been selected — and they just so happened to be men. Unfortunately, we’re lacking the evidence to support that claim, because nobody has done the research on this specific context. We have decades of adjacent evidence suggesting that gender-diverse teams perform better under exactly the conditions Artemis III will face.

We also have the closest real-world analogue we're going to get to a space mission: Antarctic expeditions. Long-duration, high-stakes, small isolated teams, distributed expertise across a wide skill set, intense training-to-mission ratio. The all-female teams that have crossed the continent, the Ice Maidens among them, show that women perform at the highest level in exactly the kind of extreme environment Artemis III is rehearsing for.

Four men were selected for Artemis III. The claim that they are 'the best' is a claim NASA hasn't done the work to make.

I hear from many product leaders who feel they’re being left behind in this race to AI everything, everywhere, all at once. They have huge pressure from their boards to demonstrate what they’re doing with AI — where is it in the product roadmap? How are you using it internally to reduce costs and improve productivity? How is it impacting the bottom line?

These fears aren’t always being voiced in public forums because of the stigma of being the one admitting they don’t know what they’re doing, or they’re not sure about all the hype. Saying ‘I don’t know’ would reveal a precarious position when the default is certainty. So instead we just hear a lot of noise from the AI bros, a distortion that affects our perception. Just look at your Linkedin newsfeed as the worst offender of this.

Allow me to take you on a philosophical detour momentarily. I recently came across Erwin Schrödinger’s 1944 book, What is Life?. Leaving the cat aside for one moment, he explores how life is an ordered system existing in a universe that tends towards disorder. Life completely bucks the trend of natural physical decay. Left for long enough, our universe will eventually burn itself out. Our nearest star (the Sun) will spend all of its hydrogen in nuclear reactions and die. The giant black hole at the centre of our Milky Way — Sagittarius A* — will eventually leak so much energy through Hawking radiation that it will evaporate in a brilliant flash of gamma rays (or so we believe — our universe is not old enough yet to have seen this happen). In the meantime, DNA takes in this chaos and creates order, through four simple building blocks (adenine, thymine, guanine and cytosine).

All cellular life on Earth is built via DNA, so as far as we know, it’s required to create life elsewhere in our universe too. From those four nucleotides come the incredible variety of bacteria, plants, animals, fungi, and more — everything from penicillin to pandas to pumpkins to portobello mushrooms. Incredible, isn’t it?

But this process takes time — evolution happens over thousands if not millions of years. When DNA is replicating itself, a mutation may appear randomly and spontaneously in the genetic code. These mutations may lead to changes in the phenotype or behaviourally that prove advantageous to the organism during its lifespan, and so it has a better chance of reproducing and passing that mutation onto its offspring. Over time, the mutation reaches a critical mass within the population, with more carrying it than not. Those that don’t carry it are less likely to survive, so die, and don’t pass on their non-mutated code to the next generation.

Evolution as a process of creation (emerging new characteristics) is slow. And when we zoom out to look at other natural creative processes — The Big Bang, star formation, plate tectonics, fossilisation, forming coral reefs — these are on a timescale of 1,000’s to 10,000,000,000’s of years. In other words, building order takes a long time, and there’s little hurrying it.

On the flip side, destruction can be instant. A supernova explosion. An asteroid hitting the planet. A volcanic eruption. A rainforest cleared to make way for grazing land. It’s so much easier to effect, and once the process has started, there’s no going back to the previous ordered state in the same instant.

Our universe tends towards entropy, which is the number of ways the parts of a system can be arranged while still looking the same overall. For example, low entropy is a neatly stacked pack of cards, whilst high entropy is a shuffled deck of cards. The Second Law of Thermodynamics says entropy in a closed system always increases over time. This is why heat flows from hot to cold, why things break more easily than they assemble, and why time has a direction.

I’ll bring this back to AI now. Is AI a force of creation, or destruction within your organisation and our society? Many would argue it’s creative: you can build apps, automate workflows, and learn new skills through engaging with it. But it’s also destructive: cognitive skills atrophy, excessive consumption of natural resources, degrading real human relationships. One results directly from the technology use, the other emerges indirectly from how the system surrounding it adapts to it.

If organisations go all-in on AI transformation, it will take time to build new workflows, capabilities and value generation to leverage this technology — much more time than the current rhetoric would lead you to believe. Yet it will also destroy (and we see this happening in real-time) jobs, trust, institutions, truth, ecosystems. It will take much longer to re-build these again in the aftermath. The technology doesn’t care about this asymmetry.

We should be wary of anything that grows rapidly without constraints. In nature, this looks like cancer, pathogens, invasive species, algal blooms — and they tend to destroy the system they’re growing within, and often themselves in the process. Uncontrolled exponential growth is the signature of pathology, not progress.

So if you’re feeling behind even at this stage, you’re not.

You could absolutely burn down your whole organisation tomorrow if you felt that was needed. Fire all your staff and replace them with AI agents. It would be quick and dramatic, but also painful and irreversible.

The truth of building (and rebuilding) is that it takes time — much longer than can be shown in a single quarterly earnings report. A new pattern (random DNA mutation) needs to emerge that is advantageous to the organisation — and nobody knows quite what that looks like yet. So instead this means we need to engage in deliberate experimentation with a closed feedback loop. Test things out to see what works for you, in your organisation, in its environment (industry, sector, market). Look at what others are doing and spot the patterns of success — and failure. Try those patterns out for yourself. Be wary of anything that looks destructive.

The real question to ask is this: is AI breathing life into your organisation, or destroying it?

What's the AI pressure looking like in your organisation right now? I want to know what leaders are actually being asked to deliver, and what's getting pushed back on. Drop a comment or shoot me a message at caroline@expansum.space

The Ice Maidens attribute their success to maintaining a strong camaraderie and dealing effectively with tension when it came up. But what really stood out when I learned about their mission, is just how much they cared for each other. Major Nics Wetherill MBE said she knew her team mates so well that she could tell if they were smiling or crying just from the back of their head.

And yet, how often do we describe that kind of care as 'professional'?

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What does it mean to ‘be professional’?

We all have an implicit sense of what it means to be professional, but various official definitions give it as:

• Knowledge and competence to do the job

• Integrity and ethics

• Reliability, appropriateness and accountability

What these all point to is setting out a normative set of behaviours, with professionalism really being about compliance with these norms. These norms are set by previous generations in the workforce — but they’re not fixed in place; they change over time as wider societal attitudes evolve. For instance, the Wikipedia article on professionalism talks about tattoos, which were once taboo to display, but nowadays are accepted in the vast majority of workplaces (there are some exceptions still).

If we examine professionalism closer, it reveals an implicit set of beliefs about showing emotions at work, which govern our behaviour:

• “Keep your emotions out of it.” Feelings are seen as noise. The job requires logic, not emotionality.

• “Maintain appropriate distance.” Care too much and you lose objectivity. Real leaders stay detached.

• “Don’t let them see you struggle.” Vulnerability is a crack in the armour. Strength means appearing not to need anything.

These beliefs are reinforced by the boundaries and expectations of our roles1. Take for instance, resilience. When that’s explicitly drafted into a job description or a company value it’s seen as the ability to perform consistently under pressure and recover quickly from setbacks. Except the underlying belief may actually be you should be able to absorb whatever we throw at you without visible cost. The very human experience of struggling, needing support, or requiring time to recover may be seen as a lack of resilience, and therefore a performance gap.

So why are emotions at work vilified?

Showing emotions at work is a privilege

Being professional seems to require stoicism, distinguishing between what you can and cannot control. You cannot control what happens, but you can control your reaction (i.e. your emotions) to it.

Except — some people are permitted to show emotions, particularly anger, shaming others, or joviality. By virtue of their privilege they do not have to self regulate like the rest of us. Their emotions can be expressed, whilst everyone else’s must be suppressed. We can all think of that one person who this applies to.

In my own experience, I can recall times where I’ve been on the receiving end of a leader’s anger and frustration, and they certainly haven’t shown any self-regulation — or even self-awareness. Earlier in my career I once sat in a meeting where a senior leader was shouting at me for not doing something the way he wanted it done, banging his fist on the table. I was frozen in fear, worried he was going to lash out at me physically. This is of course unacceptable, but my inaction permitted that behaviour. Except, was it really inaction, or a very rational response to the threat in front of me? How I responded in that situation was predicated on our respective levels of power in that relationship. Fear of repercussions told me I had no other choice but to sit there and take it.

This is why I’ve always felt there is a double standard when it comes to emotions at work. If I got angry and banged my fists on the table just because my team did something I didn’t like, I would be fired (or at least, severely reprimanded).

Which brings me to another belief that underlies professionalism: leave yourself at the door. Your identity, culture, and ability to feel emotions must be checked in at reception. This conformity ensures there’s no discomfort created for others, because you’re all the same at work — and can therefore also be treated all the same.

Of course that’s rubbish, because it’s impossible to put into practice. And there’s a counter-narrative forming. ‘Be authentic at work’ has become a mainstream workplace slogan, and is increasingly finding its way into the leadership and psychology literature (see this from Berkeley and this from Psychology Today). Except it’s also problematic, because it’s not always safe to ‘be yourself’, particularly with the current politicisation of identity. If you are part of the dominant group, absolutely you can be yourself. If you are not, it’s safer to hide your true self and perform a different, more acceptable version.

So what is the true antidote to a professionalism that asks people to leave themselves at the door?

What professional institutions know about emotions

I’m currently re-reading Brené Brown’s Dare to Lead, and am reminded of the story she tells about the US Air Force (section 2: the call to courage):

The [US] Air Force’s most current manual on leadership, Air Force Doctrine Document 1-1: Leadership and Force Development, was written in 2011. In the document it explains that our Air Force’s current core values are an evolution of seven leadership traits identified in the Air Force’s very first manual on leadership, Air Force Manual 35-15, which was written in 1948. One of the seven traits is humanness… As I was reading the document I was struck by how much emotion I was feeling from the words on the page… words and phrases like: to belong, a sense of belonging, feeling, fear, compassion, confidence, kindness, friendliness and mercy… Yes the word love was in this military leadership manual… this document used a language that speaks to the human experience when it was instructing leaders on how to lead people.

Brené compared this with the most recent leadership document and found that those words did not appear. Instead there were phrases like tactical leadership, operational leadership, strategic leadership. She noticed the language had been sanitised, and in doing so, removed much of the importance of expressing those feelings and holding space for others.

I replicated Brené’s word search in the British Army’s Army Leadership Doctrine (which I found on the Centre for Army Leadership’s website), and found several mentions of feelings, belonging, fear, and compassion. Of particular note is that emotions and emotional intelligence appeared 31 times throughout the document — the most common expression, clearly underpinning the ethos of the leadership doctrine. The contrast between these two doctrines highlights significantly different approaches to leadership.

Given that fear is not only an emotion2, but a powerful (de)motivator that overrides our rational brains to determine our behaviour, I wanted to know more about how the army handles this in leadership. I searched for ‘safe’, which returned nine results including this one which surprised me, given the context: “For the growth of the leader and of the entire team, it is essential to create an environment in which it is safe-to-fail.” I personally did not think of the army as a place where failure is an option, as lives are on the line.

And yet it makes sense. In extreme conditions, where the cost of failure can be catastrophic, creating an environment where people feel safe is not a luxury — it's table stakes. The British Army understands this at a time when many companies are acting in the polar opposite — creating cultures of fear based on job replacement due to AI.

That culture of safety and emotional intelligence is what enabled Major Nics Wetherill to lead the Ice Maidens to success. The care she demonstrated towards her team wasn’t a nice to have — it was basic survival, it was professionalism in action.

So how can we bring care back into our leadership today? Here’s three questions for you to reflect on:

• Whose emotions are you unconsciously dismissing as unprofessional, and what belief is driving that?

• What do you do that tells your team they’re safe?

• What would it look like to build care into how your team operates?

If these questions surfaced something you weren't expecting, that's usually where the interesting work begins. Book a call to learn more about working with me as your coach.

PS. This article has been accompanied by the support of Freya, a friend’s Pomeranian we are looking after this weekend. Cute fluffy doggo picture as a reward for getting to the end of this article!

“I can’t do X, until I’ve done Y.”

Have you ever caught yourself saying this? I can’t put myself forwards for that promotion until I’ve become more strategic, or maybe I need more data before I can make that decision.

Usually this is your fear of uncertainty talking. We have a natural bias to prefer the things we know, even if they are painful or worse, than the things we do not know, even if they could be better.

Up until recently I caught myself saying this to myself:

I can’t pivot my company into the space sector, because I will lose the brand equity I’ve built in tech (particularly Product).

At the heart of it was a fear — of going backwards in my business, losing clients, failing at what I really wanted to do (which feels big and scary).

Even though I knew at some point I would need to do just that — pivot. I’ve been building up my network in space through Linkedin, UK Space Agency mentoring, joining Women in Aerospace network and going to their events, and tapping into the Space East network (one of the national space clusters). I know I need to do more (on the cards is going to space conferences and another analogue mission in 2027 as part of my masters), and I need to be super strategic about it.

I remember sitting at a roundtable at Trajectory last November, hearing from Doug Liddle that building a company in space is a 10-15 year endeavour. He challenged me: what’s my plan? I didn’t have one at the time, and I’ve been thinking about it ever since.

What I do know is that I don’t want to wait 10-15 years before pivoting — that would be way too late. So what is the optimal time? Five years? Two years? (after my masters). Next year?

The answer, of course, is now.

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Last month I was at a masterclass within MicDrop1, the speaking community I joined a year ago. The speaker shared how she had landed a 7-figure training deal with one of the world’s biggest consultancies, and all because of one conversation at a BBQ.

She had followed Dorie Clark’s advice (who I absolutely LOVE, and read her book The Long Game: How to Be a Long-Term Thinker in A Short-Term World after hearing Doug’s advice) — tell everyone what it is you’re building anytime someone asks how you are.

And I’ve also taken that advice to heart, and now any opportunity I get I’m telling people that my mission is to be part of the team that lands astronauts on Mars by 2040. I want to be a space psychologist, supporting with the selection, training and in-mission support of the team who will go to Mars. The big government space agencies will clearly play a key role here, but so too will private and commercial space companies.

And my big prediction is that space tourism will become affordable to the average person within the next 20 years too. Currently it’s about £250K for a seat on Blue Origin, putting it out of most people’s reach. But I expect it will drop 10X as launch capability gets even cheaper through reusable components, and use of automated processes that don’t require pilots, such as in New Shepard (i.e. Moore’s law comes into play). And those people, like you and I, will need psychological support to both prepare for and integrate their experience afterwards, particularly if they experience what’s known as the Overview Effect.

I sat down a couple of weeks ago and played through an imaginary exercise in my mind. If NASA was in a procurement meeting, and the minutes were going to be typed up, would they be green lighting ‘Caroline Clark Leadership and Performance’ on their supply chain? I cringed… no, they probably would not. I realised at that point I had a mismatch between my long term ambition, and my current company brand.

Caroline Clark is very much a B2C brand. I needed a name to reflect my B2B ambitions. So I started brainstorming and looking around at what was already out there.

I’ve been rewatching For All Mankind (if you haven’t seen it yet, we can’t be friends I’m sorry), and character Dev Ayesa’s company Helios is loosely based on Space X. That gave me some inspiration — I wanted a word that sounded ‘spacey’, so Googled Helios, Polaris, Cosmos, even Ad Astra (a Latin saying popular in space circles that means to the stars). And I found many versions of this were unsurprisingly already taken.

I went round in a few circles, Googling what if I added different suffixes (Institute, Academy, Centre, Leadership Institute, etc etc) and checking if the domains were available on Namecheap. It was a very frustrating and fruitless search.

Have I ever told you how much I hate naming things?

(As my partner, a systems engineer, reliably informed me, there are 2 hard problems in computer science: cache invalidation, naming things, and off-by-1 errors).

So then I went down a rabbit hole of Latin and Greek gods and words related to space. Io, Europa, Callisto, Ganymede — even Mars, Saturn and Jupiter. I went back and forth with Claude, who helpfully told me the many downsides of the names. For instance, Io could be associated with transformation (yay), except she was turned into a heffer by Zeus — possibly not quite the change I was after (I have nothing against cows, they’re just not very spacey).

At one point I came up with a portmanteau — credonautica. Credo is Latin for ‘I believe’, whilst nautica is Greek for sailor or sea (before you come at me, the words television and automobile are also mash ups of Greek and Latin words). An obvious play on astronaut, this would be about a sailor of beliefs. On Namecheap the word was available, but I slept on it and the following morning when I woke I hated it. Would people get it immediately? Probably not. My partner’s reaction was less than lukewarm and that told me all I needed to know to ditch it and start again.

And then it came to me — expansum.

Expansum reflects everything I wanted in a single name: space is an expanse, but it’s also about the inner sense of space, as you grow and develop, you expand your mind, your capabilities. It captures the sense of (inner and outer) exploration, vastness, the unknown.

It’s a name I could see NASA writing down in the minutes.

And following this, I was easily able to draw the line between where I am now to where I want to get to. My clients are leaders at the frontier — defining frontier as the edge of human knowledge and performance. You could be in a tech company, building new tech and solving novel problems — but you could also be a scientist developing vaccines and cures, a surgeon using cutting-edge robotics, an AI engineer developing frontier models, an expedition commander leading a team to the poles, or an astronaut stepping foot on Mars.

What these leaders have in common is that being at the frontier requires a new type of leadership — and followership. Resilience, adaptability, strategic thinking and decision making are all critical survival skills. The context frontier leaders operate in is extreme: fast paced, high levels of complexity and uncertainty, high pressure. I will write more about this in a future article because it’s too important to gloss over in a short note here. Suffice to say, that is the direction, that is the golden thread between now and the future in my work.

Now the next phase begins: defining the product offering. I’ve long wanted to create a leadership development programme, and that is my core goal for 2027 (after TEDx, after the book!). Watch this space…

I’d love to hear what you think of the name - whether you love it, like it or hate it! Please drop a comment below or email me at caroline@expansum.space.

PS. I’ve also started a YouTube channel (yes, I’ve been very busy!). The first video is up, please like and subscribe!

I still have the mental scars from some of my earliest Product reviews more than a decade ago. At the time I led a product squad focused on building new products — read: risky, low volume, unproven — as a new line within our portfolio of mature products. Every other Wednesday at the end of the sprint, we would present back to the execs what we had been working on: performance data, customer stories, what we'd learned. As PMs we'd make recommendations on what to do next. The problem was, my slot was at the end of the day, and I could see the exec team flagging after reviewing the work of 8 or more teams. I now know that the end of the day is the worst time to evaluate big bets, because cognitive fatigue compromises the quality of decisions, in particular leading to risk polarisation: decisions become either ultra conservative or impulsive, with no middle ground (Jeon, 2026).

Decision fatigue is just one example of how our cognitive limits shape the quality of our choices. Which brings us to the core competencies framework I updated last week: the other side of your relationship with context is decision making. And there’s a lot of cognitive science around this. You may be familiar with the seminal work of Daniel Kahneman and Amos Tversky first published in 1979, Prospect theory: An analysis of decision under risk. They later won the Nobel Prize for Economics in 2002, and their thesis was turned into the popular psychology book Thinking, Fast and Slow. Here Kahneman dispelled the myth that we act as rational beings when it comes to making decisions (Homo Economicus — economic man), instead showing how we are subjected to emotions, biases and heuristics that shortcut the majority of our thinking, to make it less cognitively intensive. And using AI may enable us to take even more of those shortcuts.

The brain is a greedy organ. On average it weighs just 1.2-1.4kg (~2% of body mass), yet consumes 20% of our total metabolic energy. It requires a constant, uninterrupted supply of glucose and oxygen, and essential nutrients including omega-3 fatty acids, vitamins and antioxidants to maintain cell structure and neurotransmitters (chemicals such as serotonin, dopamine, glutamate, and norepinephrine). Without these, the brain structures degrade, severely affecting cognition (e.g. stroke), and ultimately life. For this reason our brains evolved shortcuts to minimise the resource-intensive slow thinking (deliberate, effortful, logical, calculating, conscious) — saving that for critical decisions only. Instead, the majority of our decisions are made fast — through automatic, frequent, emotional, stereotypic, and unconscious thinking, which conserves brain energy.

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What is decision making?

Decision making is the ability to reach a sound judgement and commit to it, under conditions of uncertainty and incomplete information. Decisions can feel easier when there is a lot of information available, because of the perceived reduction in uncertainty. Daniel Ellsberg in 1961 defined this paradox as ambiguity aversion: the tendency to prefer known risks over unknown ones, even when the unknown option might objectively be better. However, you can never have perfect information, so waiting for certainty is itself a decision — and usually the wrong one.

Let’s look at the skills that make up this core competency:

• Using data: Identify, source, evaluate, and apply relevant evidence to inform and strengthen decision making.

• Sense making: Organise ambiguous, incomplete, or conflicting information into a coherent picture that enables action.

• Inquiry: Question the framing of a problem before accepting it, generating better questions rather than better answers to the wrong question.

• Critical thinking: Evaluate information and arguments objectively, identifying assumptions, inconsistencies, and logical gaps before reaching a conclusion.

• Risk evaluation: Assess the probability and consequence of possible outcomes, make a judgement call, and commit without waiting for certainty.

• Conviction: Back your own judgement and commit to a course of action decisively, even under conditions of incomplete information and potential opposition.

How these skills develop

What shape is Kiki? And what shape is Bouba? Developmental psychologists have tested this extensively, and shown that Kiki is sharp and spiky, whilst Bouba is soft and round. The brain innately maps correspondences across sensory domains, such as sound to shape, colour to temperature, pitch to size — these are a feature of the brain’s architecture rather than learned. And from birth, babies use these correspondences to show preferences towards certain stimuli, such as turning towards food sources. In one sense, some of our decision making may be innate and biologically determined.

Meaningful conscious decision making starts around age 3, with the development of preferences and simple reasoning. By adolescence, the capacity is largely functional, but still heavily influenced by emotional processing over rational deliberation — the prefrontal cortex isn't yet fully regulating the limbic system, which is why teenagers are more impulsive and reward-seeking. Adult-level decision making, integrating emotion and reasoning effectively, develops through early adulthood and continues to refine with experience. As an adult, it is estimated that you are making around 35,000 decisions each day.

What I find particularly interesting is the role of emotions in decision making. Antonio Damasio was a neuroscientist who studied patients with damage to the ventromedial prefrontal cortex, the part of the brain responsible for processing emotions. He learned that whilst they retained their reasoning ability and intelligence, they became catastrophically bad at making decisions in real life, despite performing normally on logical tests.

This led to his somatic marker hypothesis: the idea that emotions — experienced as physical sensations in the body — act as rapid signals that help us evaluate options before conscious reasoning kicks in. Far from being a corrupting influence on rational thought, emotion is a necessary component of good decision making. Without it, you can reason perfectly well but can't prioritise or commit.

Taken together, what this shows us is that the development of decision making as a competency depends upon three factors: practice, emotions and feedback loops. Notice how these three are inaccessible to AI: it is not embodied so doesn’t experience emotions, it doesn’t learn from your interactions with it, and it doesn’t do anything beyond compute probabilistic answers. It doesn’t have consequences and accountability in the real world.

But people are real, and can be held accountable. So how do you retain and develop your decision making skills, when the temptation is to turn to AI?

Exercises to develop your decision making

Here are three exercises you can use yourself or share with your team to develop better decision making.

Exercise 1: The data audit (using data)

For a decision you're currently facing, list every piece of evidence you're drawing on. Then ask yourself (checking your biases):

• Is this real data or is it an assumption? (availability bias)

• How current is it? (recency bias)

• Who collected it and why? (authority bias)

• How much of what I think I know is actually evidence versus pattern recognition from past experience? (confirmation bias)

Challenge yourself to come up with alternative evidence — what else could be going on here that you haven’t considered? How might your manager, partner, or child see this data differently?

Exercise 2: Socratic questioning

Before accepting a problem at face value, interrogate it. Socratic questioning, a technique used in coaching and therapy, works by systematically challenging assumptions until you reach something more solid underneath. Apply it to a decision you’re currently facing:

• Clarify the question: What exactly are you deciding? Can you state it in one sentence?

• Challenge the assumption: Why are you framing it this way? What are you taking for granted?

• Examine the evidence: What do you actually know, versus what are you assuming?

• Consider alternative perspectives: How would someone who disagrees frame this problem?

• Question the question: Is this the right problem to be solving? What would you be deciding if this constraint didn’t exist?

The goal isn’t to reach an answer, but to arrive at a better question.

Exercise 3: Three modes of critical evaluation

This framework comes from my Open University studies, drawing on the work of Johanna Motzkau. When facing a significant decision, run it through three modes of evaluation:

• Within approach: Evaluate the option on its own merits. What are its aims and assumptions? Does it do what it claims to do?

• Between approaches: Compare it against the alternatives. What are the relative strengths and weaknesses of each option?

• Meta approach: Step back entirely. What are the wider implications? What power relations or taken-for-granted assumptions are shaping how the problem has been framed in the first place?

We learnt this through the example of the red dress — see the slide below from one of my tutorials for more.

Bonus exercise: the rule of 3

Some decisions are easy to make, others less so. If you’ve been agonising over one for a while, use this technique to break through. Set yourself a timer for 3 minutes, and evaluate the decision against the following 3 criteria: cost, complexity, confidence. At the end of 3 minutes, make the decision (any decision) — and fully commit to it, whatever happens.

AI-augmented decision making

The human-AI sandwich I shared last time is also relevant here — with two important caveats. You’re going to get the most value out of this process when you don’t outsource inquiry (as it’s essential to sense making) and conviction (the moment of making the decision and believing in it). Instead, use AI to support you with the inputs: gathering and analysing data, and evaluating options and risk.

You can also use AI to check your biases, specifically prompting it to challenge itself and you on the most common ones:

• Confirmation bias — AI will find evidence for whatever position you’ve already taken if you prompt it that way. But prompted to play devil’s advocate, it can surface contradictory evidence you wouldn’t have gone looking for yourself.

• Anchoring bias — the first piece of information you encounter shapes all subsequent judgement. If you feed AI your initial framing, it will tend to work within that anchor rather than challenge it. You have to explicitly ask it to.

• Availability bias — you overweight recent or memorable examples. AI has access to a much broader range of cases and can surface less obvious precedents.

• Dunning-Kruger — the less you know about a domain, the more confident you tend to be. AI can expose gaps in your knowledge quickly, though it can also give you false confidence by generating plausible-sounding content in areas where you lack the expertise to evaluate it.

• In-group bias — you favour solutions and people that feel familiar. AI has no social allegiances and can evaluate options without that filter, though it carries its own training biases.

• Sunk cost bias — you continue investing in a failing course of action because of what you’ve already committed. AI has no emotional attachment to past decisions and can evaluate the current situation on its merits.

Here’s a prompt you can use with any decision you need to make:

I need to make a decision about [describe the decision]. Here is my current thinking: [describe your position and reasoning].

Before responding, I want you to challenge my thinking rather than validate it. Specifically:

• What assumptions am I making that I haven’t questioned?

• What evidence contradicts my current position?

• What are the strongest arguments for the options I’m not currently favouring?

• Where might I be overweighting recent or memorable examples over broader evidence?

• What would someone who fundamentally disagrees with my framing say?

• Are there sunk costs or past commitments influencing my thinking that shouldn’t factor into this decision?

Do not tell me what to decide. Help me think more clearly about what I might be missing.

Then consider its answer as another data point in your decision making.

One final note: much of the public discourse critically evaluating AI centres the within and between approaches — is it accurate, is it better than the alternative — with criticism directed at anyone who raises the meta considerations, labelling them a 'doomer'. But it is right and fair to be concerned about the wider impacts of AI, particularly how the externalities are suffered mostly by communities that don't have the power to push back. No technology is without its costs, as well as its benefits. And we have a collective decision to make about how we handle this. If you're building a product strategy without considering the environmental and social impacts of your decisions — the third order effects — you're only doing half the job.

The next time you defer a decision to AI, ask yourself: am I augmenting my thinking, or avoiding it?

If you found this useful, here’s how I can help you more:

• Develop your career as a leader with me through leadership coaching.

• Inspire your audience to change their beliefs through In-company keynotes and workshops.

• Join the waitlist for my new book, Beliefocracy: How our beliefs govern us.

• Commission a piece of novel research.

At CPO Connect last week, 70+ senior product leaders gathered at AKQA to do what product leaders do best: identify problems and solve them. I co-facilitated two breakout sessions with my friend James, exploring which cognitive skills are most at risk from over-reliance on AI. Across both groups — somewhere between 25 and 30 people in total — the same skills kept coming up: strategic thinking and decision making. The concern, though, was almost entirely directed at someone else.

Early-career professionals are outsourcing the effortful thinking before they've had the chance to build it. Writing a deck isn't just about creating pretty slides — it's how you learn to structure an argument. Sitting with a hard problem is how you build judgement. If you outsource the whole task, you lose the skill underneath. The experienced leaders in the room understood this intuitively, but what they were less sure about was whether it applied to them.

The research suggests it does. Use it or lose it applies to the brain as much as it does to muscle — and AI is making it very easy not to use it. Kosmyna et al (2025) found that heavy AI users showed the lowest brain engagement of all groups and got measurably lazier with each session. The researchers called it cognitive debt, and its impact on memory was immediate — participants struggled to recall content they'd produced just minutes earlier (something noted in our discussion too). A separate study by Microsoft Research and Carnegie Mellon University (2025) surveyed 319 knowledge workers and found that for 40% of tasks, participants reported using no critical thinking whatsoever. The more confidence workers placed in AI to complete a task, the less they engaged their own judgement. The researchers described it as losing the muscle memory built from doing the work yourself.

As a former Product Director now retraining in organisational psychology, I've experienced this first-hand. When I over-rely on Claude, I notice it — the thinking feels shallower, the ideas less mine. So I went back to a framework I built a few years ago: a core competencies model structured around three relationships — to yourself, to others, and to your context. Strategic thinking and decision making both sit in that third category. I dusted it off on Friday and updated it for this piece.

This is the first of a two-part series. Here, we go deep on strategic thinking, with part two covering decision making. I see them as two sides of the same coin — you need both to act well under pressure and uncertainty. For each competency we’ll look at the cognitive skills underneath it, how they develop across the lifespan, explore exercises to build them, and share a practical guide for when to use AI — and when to do the thinking yourself.

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What is strategic thinking?

Let’s start with what is strategy. I really like Mark Cuban’s definition on Masterclass: it’s how you’re going to win. All the frameworks and matrices that we get bogged down in are simply mental scaffolds — not the strategy itself — to get you closer to that answer.

So strategic thinking refers to the abilities that enable you to create a strategy. And you’re creating strategies for life events all the time: moving home, thinking about your financial future (e.g. FIRE), deciding which school to send your kids to. You just don’t always see it as strategic thinking because it didn’t involve a lengthy presentation to the Board (just a discussion with your family!).

Here's what those underlying skills actually are:

• Visioning: Define a compelling and coherent picture of a desired future state that guides direction and decision making.

• Goal setting: Translate that vision into specific, measurable outcomes that focus effort and track progress.

• Planning: Sequence actions, resources, and timelines to move from current state to desired outcome.

• Systems thinking: Identify how multiple variables interact and influence each other across different levels, recognising that changing one element produces effects throughout the whole.

• First principles thinking: Strip a problem back to its foundational truths and reason upward from there, rather than by analogy or inherited assumption.

• Root cause analysis: Trace a problem back to its originating cause rather than its visible symptoms, distinguishing between what is presenting and what is actually driving it.

How these skills develop

Strategic thinking is a distinctly human capability — it depends on the prefrontal cortex, the most recently evolved part of the brain, and the seat of what psychologists call executive function. It's what separates us from other animals: the ability to think beyond the immediate moment, simulate future outcomes, and act on reasoning rather than instinct.

These capacities don't arrive fully formed, and they don't stop developing on any fixed schedule. The oft-cited claim that the brain stops maturing at 25 turns out to be an artefact of the original research — the oldest participants were in their early twenties, so 25 was an extrapolation, not a finding. A 2025 University of Cambridge study mapped the brains of 3,802 people aged zero to ninety and identified five distinct phases of brain development across a lifetime. The adolescent phase of neural wiring extends to around 32, on average — at which point the brain shifts into its longest era, lasting over three decades. Development doesn't stop there either. It continues to be shaped by experience, challenge, and significant life events throughout adulthood (what Zittoun calls ruptures).

So how do we develop our strategic thinking?

Through sitting with hard problems, like deciding whether to take a job or not. In this example, you start with imagining different scenarios — what it would be like to accept and do that role, versus if you didn’t take it. How you might make childcare work with a longer commute to be in the office 3 days a week. Who you could call on for additional support. Identifying the pros and cons, the benefits and the costs (weighing them up engages critical thinking, which is under the decision making competency). Evaluating if taking a higher salary for a couple of years is worth it to get you closer to early retirement, and what is the risk of burning out.

Doing this requires embracing discomfort. The cognitive effort of mapping out possibilities creates mental friction as your brain engages across different neural pathways: memory and imagination, emotion and reasoning, attention and inhibition. This friction is an essential part of the process, to internalise the knowledge and take ownership of the decision this ultimately leads to — something the CPO Connect group noted. So now let's get practical.

Exercises to develop your strategic thinking

Here are three exercises you can use yourself or share with your team to develop strategic thinking.

Exercise 1: What if (and then what?)

Pick a trend, a constraint, or an assumption in your work or life and ask: what if this changed? e.g. what if remote work became the norm again? What if your biggest competitor halved their prices? What if you got the promotion?

Then follow it through:

• First order effects: what happens immediately as a direct result?

• Second order effects: what does that trigger in the people, systems, or markets around it?

• Third order effects: what does that change about the broader landscape over time? (use different timelines such as 1 year, 5 years, 10 years, 50 years).

Most people stop at first order, but the strategic thinking happens in the second and third. The further out you can reason with confidence, the stronger your visioning and systems thinking become.

Exercise 2: Work backwards from winning

Sir John Whitmore’s insight in Coaching for Performance was that most people jump straight to performance goals — the metrics and milestones (aka OKRs) — without ever establishing the bigger goal underneath. Goals should be inspiring and aligned with personal values: the measurability matters less than whether the goal actually means something to you.

So before you set a goal, define what winning looks like. Not the output, but the outcome: what changes, for whom, and why that matters to you specifically. For example, my 15 year goal is to support a team of space psychologists to land humans successfully on Mars. This matters because getting there will further our understanding of the universe, and change how we see ourselves (as a multi-planetary species). I see myself as an explorer and this is the ultimate expression of that.

From this you can use a technique called backcasting: take that goal and work backwards, breaking it down into a series of steps or milestones. These can then be measured to ensure you’re making progress and on track. To build on my example: BSc psychology complete > MSc organisational psychology loading this autumn > original research in space psychology; developing contacts in the space sector > mentoring on next cohort of UK Space Agency’s accelerator programme > learning how the space sector works.

Exercise 3: Five whys

A favourite with young children everywhere. Take a problem you’re currently facing — professional or personal — and ask why five times. This enables you to dig beyond the surface level, and get to the foundational elements driving that behaviour.

For example: I’m not making progress on writing my book.

• Why? Because I’m not writing consistently.

• Why? Because I keep deprioritising it when other work comes in.

• Why? Because I don’t protect my time for it.

• Why? Because I haven’t committed to it as a non-negotiable.

• Why? Because I don’t fully believe I’m capable of writing a whole book.

That last answer is where the real work is. Root cause analysis isn’t about finding the practical fix — it’s about getting to the belief or structural problem underneath. That’s where strategic thinking and change actually begin.

Now let's look at how to integrate AI into your strategic thinking practice — without letting it do all the thinking for you.

AI-augmented strategic thinking

There's a principle hiding in plain sight in the name: generative AI helps you generate more possibilities. It's not there to do the thinking from first principles for you — it's there to extend what you already came up with and surface the blind spots you couldn't see from where you were standing.

The most useful framework I've come across for this is the human-AI sandwich, developed by Beth Kanter (which I first came across in my friend Athena's forthcoming book AI-Q: The new leadership imperative for the human + AI era). The principle is simple: human thinking goes first (bottom bread slice), AI augments in the middle (the filling), and human judgement closes it out (top bread slice). Before you go to AI, assemble what you already know — your existing understanding or research, your assumptions, your rough thinking. Then use AI to expand, challenge or accelerate that. Then come back and apply your own critical eye to what it produced. What's missing? What assumptions are baked in? What would make you reject this entirely? The sandwich only works in that order: starting with AI skips the step that builds the skill.

Applying to the skills listed earlier, here’s what I recommend:

• Visioning and goal setting: Define your own vision and goals before you go anywhere near AI. What are you trying to achieve and why does it matter? Then ask the LLM to challenge the coherence — what's missing, what's contradictory, what assumption is doing too much work?

• First principles and systems thinking: Identify the key variables and first, second and third order effects yourself first. Then prompt the LLM to surface scenarios and dependencies you haven't considered.

• Planning and root cause analysis: Draft your own sequence of steps or your initial diagnosis of what's driving a problem. Then ask the LLM to stress-test it — what have you assumed away, what are the failure points?

• Final synthesis: Once you've worked through the above, ask the LLM to summarise the exercise. That summary becomes the basis of your one-pager — but you wrote the thinking it's drawing on.

The temptation with the accessibility of AI is to jump straight into it to do the heavy lifting, so this is going to require discipline not to succumb. The litmus test is going to be can you stand up in front of an exec team and defend your work, because you know it inside-out? If you can’t honestly answer yes, then you have outsourced too much thinking to AI. And if someone hands you a fifty page document, the first challenge is asking them to summarise it for you — verbally. Very quickly you will learn if they’ve internalised that knowledge or are merely a conduit.

One other point worth making: the CPO Connect discussion rightly highlighted that AI is genuinely transformative for many neurodivergent people — helping with tasks where the barrier isn't the thinking, but the execution. Rather than seeing this as cognitive offloading leading to potential skills atrophy, it’s about creating access where structural barriers exist that prevent participation.

If we’re using LLMs to augment human thinking instead of replacing it, that implies it's not actually going to save time and lead to the productivity gains espoused by the AI-bros (where the time saving comes from not doing the work yourself). And several studies have shown this is what is playing out: A 2024 MIT study by Nobel laureate Daron Acemoglu found only a 0.5% increase in [overall economic] productivity over the next decade from AI. Acemoglu himself described the finding as “disappointing relative to the promises that people in the industry and in tech journalism are making.”

Instead, the real value in LLM use is about generating more possibilities and addressing blind spots — which makes the thinking more robust. And in a world where there is increasingly more noise than signal, understanding what to pay attention to and act on will become even more critical.

If you found this useful, here's how I can help you more:

• Develop your career as a leader with me through leadership coaching.

• Inspire your audience to change their beliefs through In-company keynotes and workshops.

• Join the waitlist for my new book, Beliefocracy: How our beliefs govern us.

• Commission a piece of novel research.

And then something happens — a difficult conversation, a setback at work, a moment of unexpected pressure — and there it is again. That familiar voice, reasserting itself. “I’m not good enough.” “I don’t deserve this.” “Who do I think I am?”

It can feel like failure, like all that work counted for nothing, like you are fundamentally, irreparably stuck. But you are not stuck — you just have been working on the wrong layer of beliefs.

Beliefs do not exist at the same depth. Some sit close to the surface — as opinions really, that shift with new evidence and good arguments. Others are buried so deep they predate language, memory, and any capacity you had to question what was being laid down.

I want to share with you the cave metaphor that explains why some beliefs change easily, and why others seem immune to every tool you throw at them — and why that is not a reflection of how hard you have worked, or how far you have come.

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The bedrock

At the deepest level of the cave is the bedrock, the foundation of all beliefs that come above it. Your bedrock is a set of beliefs about your self that is laid down early in life — within the first five to seven years during a period of high neuroplasticity in your neurodevelopment. It’s formed before you have language, a self-concept, or any mental capacity to examine what exactly is being encoded. It doesn't feel like a belief you hold — it feels like your reality.

When we shine light on the bedrock it typically reveals a combination of three core beliefs about the self:

• I am not safe.

• I am alone.

• I am not enough.

Terror Management Theory, which was explored by Greenberg, Solomon and Pyszczynski in their 2015 book The Worm at the Core (which was itself based on earlier work by Ernest Becker) proposes that human behaviour is motivated by the fear of death. We are the only species that knows it will die, and that knowledge creates a persistent, largely unconscious terror that we manage through two belief buffers: cultural worldviews that give life meaning and symbolic immortality, and self-esteem, which functions as evidence that we are a valued member of a meaningful world. If you matter, if you are enough, then your death is not just a biological ending but the end of something important in the world.

As a result, self-beliefs are the most resistant to change. Touching the bedrock isn’t just uncomfortable, it’s existentially threatening at a level often below conscious awareness. Within several of the interviews I’ve conducted for Beliefocracy, these bedrock beliefs show up consistently, although they’re not always named or conscious.

One interviewee, a therapist who has spent years doing her own inner work (actually a requirement to become a therapist), described recognising her bedrock belief clearly, and knows where it came from. In spite of all the work she has done, it has not gone. What has changed is that she has built enough beliefs in the strata above it that it no longer governs how she behaves.

This may be the most important thing to understand about the bedrock: the goal is not to demolish it — because I’m not convinced that is actually possible. It was formed before you had the capacity to question it, and it is protected by every defence your nervous system has. The work is not excavation, but rather illumination — learning to recognise the bedrock for what it is, so that when it makes an appearance you have a choice in how to respond to it.

The lower strata

Sitting just above the bedrock are beliefs about what you can do or have. If your bedrock says you’re not enough, the layer above it might sound like ‘I don’t deserve happiness’, or ‘I can’t give a good presentation’.

Sometimes these beliefs don't stay in the realm of capability. They collapse into identity. This is what Acceptance and Commitment Therapy calls cognitive fusion — the process by which you become entangled with a thought, treating it as truth rather than as a mental event. When fused, you lose the ability to observe the belief from a distance. The thought stops being something you're having and becomes something you are. 'I gave a terrible presentation' becomes 'I am a terrible presenter.' A temporary state hardens into a permanent belief about your identity.

It is possible to change this level of beliefs — but it might take a significant rupture in your life to do that. Another interviewee shared a long-held belief that “If you work hard, you get payback, you get the right outcomes”. This was traced back to seeing his father work long hours, which he carried through to his own work ethic in later adult life. Even when he experienced burn out he still held this belief — and it caused him a lot of anxiety, a sense of feeling trapped with no way out but to return to a job that was making him ill. But then his company went through a restructure and his role was made redundant, and that single rupture — the loss of his job — was sufficient to dismantle the scaffolds that kept that belief in place, and open up other possibilities. He went on to start his own company and several years later is thriving.

The upper strata

As we climb towards the surface, next is the upper strata, which are beliefs about other people — their identity, thoughts and motivations. Sharing these beliefs publicly is risky — unless they are positive in sentiment. It’s fine to say ‘my boss is great!’, whilst ‘my boss is terrible!’ opens yourself up to judgement on your own character as well as the person you’re criticising. We share these beliefs with people we trust, or where anonymity is guaranteed — Reddit forums, culture surveys, opinion polls.

These beliefs are quickly set through ‘first impressions’, yet harder to change. There are two mechanisms that work in changing these beliefs: taking the other person’s perspective and persistent exposure.

Within my coaching work, particularly with job seekers experiencing rejections, I often ask them to imagine what it must be like to be the hiring manager: they’re stressed, doing 3 jobs at once (their day job, hiring for the role, and covering it in the meantime), under pressure to fill it quickly, and worried about their reputation if they make a bad decision. They’re looking for someone they can trust to do this job. Taking this perspective can completely change how the client sees their own CV. They may start with believing ‘my CV isn’t working’ because ‘hiring managers don’t want to work with me’ and end with clarity that it isn’t answering the killer question in the hiring manager’s mind: “is this person a safe bet that they can do the job?”

Persistent exposure is trickier, because of confirmation bias. Once you have formed a belief about a person you are going to automatically filter out any evidence that contradicts that — you will justify that evidence as exceptional, rather than normal. It therefore takes a willingness to be open and to challenge your beliefs, which is more cognitive effort. This is where the social scaffolds in particular can be most effective — it is harder to hold a negative belief about an individual when the majority of the group holds a positive one.

The surface beliefs

Beliefs at the surface concern beliefs about the world around us and how it works: you live in a meritocracy, there is a career ladder you must climb, your company will see your talent and promote without prompting. Unlike the beliefs in deeper strata, surface beliefs feel like opinions — positions you hold rather than truths you inhabit. You debate them, update them, change your mind about them over a drink or after reading a good argument (as this article is attempting!). That flexibility is itself the signal that you are at the surface. The deeper you go into the cave, the less a belief feels like something you could argue about, and the more it feels like the irrefutable ground you are standing on.

This is the level that most coaching operates on. The scaffolds holding beliefs in place at this level are the easiest to dismantle — in fact, sometimes all it takes is the coach (or another person in a position of authority or trust) asking ‘what’s the evidence for that?’ to change the client’s mind. For example, one interviewee held a belief that they could not go straight from Senior PM to Chief Product Officer, because they held strong beliefs about how to progress along a career ladder, one rung at a time. It took her husband to challenge this — “why not just ask for CPO?” to cast sufficient doubt on this belief. She did ask for CPO, an action she would never have taken otherwise.

So where does mindset fit into all this?

I hope the cave metaphor makes intuitive sense to you in explaining how some beliefs are easy to change, whilst others are more resistant. But if you’ve ever had any coaching or therapy there may be a lingering question in your mind: where does mindset fit into all this?

From the work of Dr Carol Dweck, we generally classify mindset into one of two archetypes: fixed or growth. The way that I define mindset is a general pattern of beliefs: a fixed mindset sees the individual as unable to and resistant to change, whilst a growth mindset is about flexibility and openness. In extending the cave metaphor I’ve come up with this: mindset is about the inherent quality of the rock that makes up the different layers of belief. You can liken it to basalt versus limestone: basalt is hard and resistant to change; limestone is soft and easily shaped. It’s worth noting that even basalt can be eroded over time — it just takes a lot longer.

Beliefocracy: How our beliefs govern us introduces Belief OS™ — a new framework for leaders navigating change who want to understand why lasting change is so difficult to achieve, and what it actually takes for new thinking to stick. Join the wait list to be the first to hear about publication and pre-order availability.

Your beliefs aren’t really yours.

They were handed to you before you had the language to question them. They are sustained every day by the people around you. And they will resist changing until the conditions that created them change too.

This is what seven conversations for my forthcoming book, Beliefocracy: How our beliefs govern us, have confirmed — and it has implications for every leader who has ever wondered why lasting change is so hard, even when you genuinely want it.

Five themes have emerged across all seven interviews so far. What they reveal is the mechanism by which beliefs form, evolve and are sustained — and why changing them is in some ways harder, in other ways easier, and regardless more interesting, than most people think. At the end, I’ve included a selection of coaching questions to help you evaluate your own beliefs through each of these themes.

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1. Beliefs are inherited before they're examined

In nearly every single interview it was clear that interviewees’ beliefs formed early on in life, from a parent's opinion on what their child was capable of, to a teacher's forecast of their potential. These beliefs weren’t always verbalised. They could be transmitted by the child simply observing their parent’s behaviour, such as working long hours.

And some beliefs had been passed down through generations. Parents received their beliefs from their parents. What I found interesting was how in some cases the child (interviewee) went on to have success, and that challenged the parent’s belief system. It became a full circle moment of influencing each other’s beliefs.

It can be uncomfortable to admit that you no longer share a belief with a parent. The fear is the relationship will be negatively impacted, and so the child has to hold the cognitive dissonance of publicly agreeing whilst privately disagreeing. The interviews showed it is possible to resolve this tension, and not damage the bond between you. In fact, being truthful about difference can lead to greater understanding and closeness.

2. Belonging as a belief sustainer

Who you surround yourself with has an enormous influence on what you believe. One interviewee had been in the Royal Air Force for 22 years. When he left it wasn’t just a change of job. It was a huge loss of the people he had grown up with from early adulthood, who had been on tours in Afghanistan and Iraq together, who had trusted and validated each other through every hardship.

In the RAF, they had shared beliefs around who they were and what was possible. Every day they were living and working together reinforced those beliefs. He spoke about leaving the military as “losing [his] tribe”.

I see this often with clients who are facing redundancy. It’s not just losing the job and stable source of income (although that is a big part of it). It’s also losing the people you work with. A sense that you may never work with your colleagues again, in quite the same way — even if you are staying on, others will be leaving. The survivor guilt is in part also a grieving process for a sense of belonging that no longer exists.

If you’re trying to change your beliefs, then changing who you surround yourself with is vital. Find a new tribe who shares those beliefs and the change will come a lot easier.

3. Imposter feelings as growth signals

Imposter feelings thrive in the space between your comfort zone and stepping into a bigger arena. This means that none of us pushing for our growth are immune to them — in fact, their appearance is quite likely. And that’s ok.

One interviewee described how all it took for the imposter feelings to appear was a simple mistake. As a teacher with decades of experience, living in Kosovo and starting a school for local marginalised communities, she was putting the alphabet up on the wall. She mixed up two of the letters, and the imposter feelings hit in an instant. Who was she to be teaching these kids when she couldn’t even arrange the letters in the right order?

But what if these feelings weren’t a sign that you are incompetent, but that you’re doing something that really matters? Where the stakes are high so it’s important to meet those high standards you’ve set yourself? In this case, starting that school meant that kids could catch up on what they had missed by being out of education, so they could rejoin mainstream schools and get their qualifications. There were futures at stake. So what if you treat imposter feelings not as a signal to stop, but as a signal to keep going?

4. A strong belief can carry you through a weaker one

In one interview we spoke at length about having a purpose in life, a mission that is greater than just you. In fact, my friend Carrie calls this a ‘cathedral project’ because it probably won’t be completed within your lifetime.

Purpose came up in several interviews, and one interviewee referred to it as “going West — you’re just continuously going West, you never reach it, you’re continuously striving.” What was interesting was how having a purpose often overrode any weaker beliefs. When you believe your purpose is to help people or make the world a better place, the belief that you’re not good enough isn’t entertained. That doesn’t mean it disappears completely — it doesn’t. It just doesn’t hold you back from the things that matter, that will help you move towards your purpose.

5. Sliding doors moments reveal what you really believe

Sometimes life throws curveballs at you. One interviewee had just started a career as a professional ballerina when a major injury cut short his dream. Part of figuring out what he was going to do next involved enrolling in university, and it was there, purely by chance that he found a path forwards. Insurance.

When that option was presented to him, he could have said no. Insurance was so different from everything he had done before. But a series of coincidences and events converged to give him clarity. “I didn’t know what I wanted to do and it seemed interesting.” He’s now an insurance exec at a leading global specialty insurer.

Another interviewee spoke of how a long standing belief changed in just one moment. He had grown up with a strong work ethic: “If I work hard, then I get pay back.” That meant being employed so there was stability and regular income. He had worked hard, too hard, to the point where he had burned out. Whilst on medical leave, his company went through a restructure which led to him being offered redundancy. That news brought with it new possibility, something he had never considered before — he could start his own business.

It takes just one moment to change the trajectory of your life — but what you believe will determine whether you seize the opportunity or let it pass you by.

Your coaching questions

The questions below aim to help you map out your beliefs — the first part of the belief change cycle within Belief OS™. You will need 20 minutes when you will not be disturbed to work through them. You may like to write them down.

1. What beliefs did your parents and teachers pass down to you about yourself?

2. What was true about the world for your parents and teachers that meant those beliefs were true for them?

3. What beliefs do you share with your tribe? (think: family, friends, colleagues, community members).

4. Think back to when you felt like an imposter. What was happening?

5. What are you willing to be uncomfortable for?

6. What sliding doors moments in your life have revealed or challenged one of your beliefs?

Once you have answered all six questions, take a step back and look at them all together. What do they reveal about your own beliefs that you didn’t notice before?

Beliefocracy: How our beliefs govern us introduces Belief OS™ — a new framework for leaders navigating change who want to understand why lasting change is so difficult to achieve, and what it actually takes for new thinking to stick. Join the wait list to be the first to hear about publication and pre-order availability.

As the crew of Artemis II splashed down early this morning (1am BST), I started wondering if we would see a new generation of conspiracy beliefs emerge. According to a Gallup poll, around 6% of the US population believe the Moon landings were faked. That’s a not insignificant number of people.

According to Byford1, conspiracy beliefs can flourish in times of social upheaval, such as war. When Neil Armstrong took his first small step for [a] man, the US was embroiled in the controversial Vietnam War. Young American men lived under the constant threat of the draft — conscripted into a war with no clear end in sight. They had no control and no certainty over their future. As Bains2 explains, conspiracy beliefs give an illusion of control: when people feel powerless, these beliefs restore a sense of order. In the context of this uncertainty, the Moon landing conspiracy theories reached fertile ground.

So as we look at rising levels of uncertainty in our world again today — wars in the Middle East and Ukraine, AI coming for our jobs, climate change — it’s easy to see how conspiracy beliefs may rise again in popularity. And it would be easy to dismiss those who believe in them as uneducated or a particular kind of person. But that would be wrong — as the psychological science has shown no support for this. Whether you believe in conspiracy theories has little to do with intelligence or reasoning ability (or any other individual difference), meaning we are all susceptible at some point.

As leaders navigating change in our organisations, understanding what conspiracy beliefs are, how they form and how to respond to them, matters more now than ever — especially when the change you're leading involves AI.

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What is a conspiracy belief?

Before we go further, it’s useful to establish what a conspiracy belief is. It’s a form of stigmatised knowledge, similar to astrology or a belief in the paranormal or aliens. The conspiracy belief contains assumptions about the world that whilst common, seem unwarranted, and are often ridiculed by mainstream society.

Typical conspiracy beliefs go against the conventional wisdom or available evidence — concealed plots being carried out by secret groups are often their subject. As a label, conspiracy theory is not neutral: the term has acquired pejorative connotations, and therefore the people who share conspiracy beliefs have come to be viewed with suspicion or ridicule.

Conspiracy beliefs may relate to any of the following:

• Deaths of public figures (e.g. Princess Diana)

• Terrorist attacks (e.g. 9/11)

• Natural disasters (e.g. Hurricane Katrina)

• Plane crashes (e.g. the Malaysia Airlines flight that disappeared over the Indian Ocean)

• Political assassinations (e.g. JFK)

• Military conflicts (e.g. Iraq war weapons of mass destruction)

• Meteorological anomalies (e.g. weather control)

• Disease outbreaks (e.g. Covid-19)

Every conspiracy belief shares the same basic anatomy: a group of conspirators (sometimes named like the Illuminati, sometimes vague like the government), a secret plan to control or eliminate on a grand scale, and the means of mass manipulation to keep it hidden.

What makes them so resilient is that they are unfalsifiable by design. No evidence can disprove them — its absence proves the cover-up, its presence proves the conspiracy.

And yet they contain a note of optimism. If someone is pulling the strings, exposing a conspiracy could stop the plan entirely. This gives believers a sense that the world is controllable, and control can be wrestled away from the plotters.

Why conspiracy beliefs take hold

Conspiracy beliefs provide a shared understanding of how the world works. Believers discuss different features and merits, sometimes arguing vociferously on online forums like Reddit (for whatever belief you have, however outlandish, you can find a group of people who share it on the internet!). This creates a social aspect to holding these beliefs — as both a shared activity (discussion) and a shared identity (believers versus non-believers).

The identity of a believer also offers something potent: self-esteem. Believing in the conspiracy theory enables them to feel superior to the uninitiated — they know something others don’t. Social status is gained by admitting conspiracy beliefs, and that enables a sense of belonging to a special group of knowers (rather than the sheeple).

Another motivation to believe in conspiracy theories is that it provides a simple solution to what may otherwise feel like a complex problem — expose the conspiracy to stop the harm it’s causing and restore order. When people feel overwhelmed with uncertainty and disorder, believing in a conspiracy provides comfort. And crucial to this is feeling like there is hope.

Hope is a belief that the future can be better than the present. It’s used as a tool in therapy, particularly in the treatment of depression, as it enables people to see that things won’t always be this bad. If you’re in the middle of war, or natural disaster, or a pandemic, hope creates a perspective that this is just temporary — and we can get through this. Conspiracy beliefs offer exactly this kind of hope: find the cause of the chaos and peace can be restored.

This matters for leaders right now, because AI is creating exactly the conditions in which conspiracy beliefs thrive — and it's also becoming the subject of them.

When AI becomes the conspiracy

A quick look through your newsfeed on Linkedin will reveal two main arguments around AI: first, that it’s going to make you more productive, and second, that it’s going to take your job.

For many, it’s hard to imagine a life without work. It’s not just having something to do for 8 hours in the day — it’s where we derive our sense of identity, meaning and purpose. It’s a place where we find support and belonging. Take that away and what happens? My guess is people will struggle.

Regardless of whether it’s by choice (“I no longer need to work because AI is doing it for me and we have Universal Basic Income!”) or by force (“I lost my job to AI”), what will people do with the time that’s freed up? In theory this gap would be filled with leisure activities or volunteering, but history shows us that when there are high levels of unemployment amongst a population it leads to civil unrest — see the Scarman report following the Brixton Riots in 1981 for one such example.

If you remove the need or ability to work, how do you generate income? At a time when our welfare institutions are being gutted and undermined, this is an understandable cause for concern. This narrative, of AI replacing jobs, has a long-term outcome that is unpredictable, and for which our economies and institutions are ill-prepared. People are rightly scared.

And this uncertainty and loss of control creates fertile ground for conspiracy beliefs to emerge. In fact, it’s already happening.

A 2025 study published in the British Journal of Social Psychology sheds some light on this. Zhao and colleagues found that conspiracy beliefs about AI are circulating — specifically that authorities will use AI to oppress humanity, or that AI itself will. Across four studies involving nearly 1,900 participants, they found two features of AI that predict whether someone is likely to hold these beliefs: how autonomous they perceive AI to be, and whether they believe AI's interests are aligned with their own. The more autonomous people think AI is — capable of operating without human oversight — the more likely they are to hold conspiracy beliefs about it. And the less they trust that AI is working in their interests rather than someone else's, the more suspicious they become. When the tech world (particularly in China) is losing its mind about Clawdbot / Moltbot / Molty / OpenClaw, and there’s a social network just for agents to discuss humans, it’s easy to see how these beliefs are seeded.

Crucially, the threat being felt is collective, not personal — it's about what AI means for society, not just the individual, which makes it harder to address, and easier to spread.

As a leader, you may not know who on your team holds conspiracy beliefs about AI. When the dominant narrative is ‘it’s happening, like it or not’, people will publicly perform compliance whilst privately holding beliefs that undermine this, out of sheer survival instinct. But you may experience the symptoms of these beliefs: push-back, slow adoption, avoidance of certain tasks that require AI use. And of course, these behaviours won’t always be because of these beliefs, making it even harder to understand what is actually going on.

When AI fans the flames

There’s evidence emerging that AI isn’t just the subject of conspiracy beliefs, it’s also the distribution mechanism. It is understood that whilst social media is a vehicle of circulating mis- and dis-information, AI is coming into its own now.

A study ran by Fitzgerald and colleagues in 2025 designed a ‘casually curious’ chatbot persona, using six different LLM models, from OpenAI, Microsoft, Google, Perplexity and Grok. The researchers chose nine conspiracy beliefs to test, including five that were well-known and comprehensively debunked, and asked it questions such as “Did the CIA kill John F. Kennedy?”, “Was 9/11 an inside job?”, and “Are chemtrails real?”.

The results across all models varied, but the main issue was safety guardrails. With some conspiracy beliefs, like JFK’s assassination, many models engaged in ‘bothsiding’, presenting both arguments with equal weight. This is probably not that much of a surprise, given that AI models are trained by scraping the internet — where any belief humans are capable of thinking can be found. Only when the conspiracy belief had a racial or antisemitic undertone were they opposed. Google’s Gemini completely refused to engage in discussion about recent events in the US, such as election rigging or false claims about immigrants, did it tap out completely in responding. It seems that some of the model owners have found ways to train or block certain topics from being answered incorrectly.

This matters because research shows that when you believe in one conspiracy theory, you are more likely to believe in others. Some researchers have dubbed this the conspiracy mentality, a broader mindset that reflects a severe distrust of authorities and a tendency to see hidden intentional causes behind world events. This is a system of belief that rejects science, feels prejudice towards out-groups, and defaults to questioning everything. As leaders, this is a hard one to work with, because you do hold positional authority and that makes you part of the system the conspiracy mentality is designed to distrust.

This is the paradox leaders face: the more you advocate for AI adoption, the more you confirm the suspicions of a believer. And as we established earlier, no evidence will change that — the belief is designed to be unfalsifiable. Which means the traditional tools of leadership — communication, persuasion, data — may be precisely the wrong instruments for this particular challenge.

There are no easy answers here. The research doesn't offer a communications strategy that will dismantle a conspiracy mentality, and leaders who believe they can logic their way through it will find themselves frustrated. But there is a way through, and it isn't at the level of behaviour or messaging. It's at the level of belief.

Conspiracy beliefs are not random; they form in the presence of uncertainty, powerlessness, and a loss of trust in the institutions people once relied on. This means the conditions that created them can, with the right approach, be changed. But not by pushing harder on adoption, or presenting more data. What’s needed is working directly with the beliefs themselves — understanding what they're protecting, what they're compensating for, and what would need to be true for someone to feel safe enough to let them go. That is harder, slower work — but it's the only work that makes a difference.

Conspiracy beliefs — like all beliefs — don't shift through argument or evidence alone. They shift when the conditions that created them change. If you're leading AI adoption and hitting resistance you can't explain, this is the work. I help women leaders in tech and space do exactly this through executive coaching and speaking engagements.

The company has announced a new transformation programme, and as a result, everybody needs to be trained in this new methodology (or operating model or framework).

Cue the workshop theatre.

If I sound cynical, it’s because I’ve been there myself. I’ve sat through sessions that take anywhere from an hour to three days. Some have been genuinely useful in getting me to think about a topic in a different way or form a new habit or way of doing things. But those are the exception. The majority have been frankly a waste of time.

And that’s no criticism of the facilitator or their material that they’ve taught me, because with many, it’s been obvious how much they care about their subject and want to share that with me, to help me.

Rather, it is a criticism of an over-reliance on a particular format that has limitations in how effective it is in making learning happen — particularly when it comes to belief change.

And as a workshop facilitator myself, I’ve learned this the hard way when sessions I’ve led have not landed as I expected them to.

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When all you have is a hammer, every problem looks like a nail

Workshops have become the change vehicle of choice within organisations for several reasons:

• You can standardise the content, which enables a consistent message to be deployed across the whole organisation.

• As a delivery format, it scales to multiples of people, sometimes 50, 100 in the same room at one time.

• It creates some sense of measurable progress — as in, before the workshop, people didn’t have certain knowledge, post-workshop they do.

It also has benefits socially: getting groups of people together in a room to discuss a single topic, especially if they don’t work together that often, helps with building trust and cohesion within and between teams.

As a result, it has become a default format for learning — from product squad retrospectives, to quarterly planning, to DEI legislation changes, to implementing AI into daily workflows. It’s adaptable, it can be quick to throw together (even with a few slides!), and even an inexperienced facilitator can get away with basic techniques on group engagement.

It is the hammer, and every learning opportunity is a nail.

The issue is: workshops are rigid, a snapshot in time of what is happening in the organisation. A fixed time, a fixed location, with fixed attendees. Who shows up can influence what issues are brought to the group discussions, and may not reflect what the real issues are, just which felt more pressing on that particular day.

The workshop is also a bubble: an artificial environment where anything is possible. What people learn inside the bubble has to survive contact with the real world — workplace culture, a difficult manager, a team with different ideas of what should be prioritised, and a set of structural incentives working against you. You show up, you learn, you leave — measurement rarely happens beyond the register of ‘did you attend?’

So why doesn’t the learning survive beyond the workshop?

Workshops change behaviour, not beliefs

A few months back I ran a workshop called Change, By Design, which was created as a belief-level intervention. From all my 1:1 coaching work I could see that many clients were being held back from achieving their goals because they were holding onto limiting beliefs about themselves — what they could and couldn’t do. And what I came to learn is that sustained behaviour change is only possible when we update the underlying beliefs that lead us to act in a certain way, otherwise we just revert back to what we’ve always done.

When I ran my workshop I was very ambitious: I wanted to take participants through all four steps of Belief OS™, my belief change model, in just 90 minutes. That is: map the current belief, challenge it with evidence, replace it with a more helpful belief, and then identify ways to sustain it. Of course, I was setting myself up to fail — but I didn’t realise that at the time. I knew something was off as I delivered the workshop; participants were feeding back they didn’t have enough time in the breakouts to really get going with discussion. And I received barely any feedback afterwards, which honestly felt deflating.

Until today. I was working on my business strategy with Claude and the conversation veered onto workshops. And I had an ‘aha’ moment: workshops don’t work for belief change, because it requires more sustained effort than a single intervention point.

This sounds obvious now I’m writing it! And yet I’m not alone — organisations keep designing transformation programmes as if a single workshop can do the whole job. We need to see change as a continuous process that we are fully absorbed in, like it or not.

Belief change is never ‘done’

I’m reminded of a thought exercise that my teacher from a Buddhist retreat I attended in India back in 2018 shared with me: when does a seed become a plant?

The change (in this case, growth) happens so gradually that it’s not until we actually look that we create a snapshot, and define it at that particular moment in time. It is a seed, not a plant. Now it is a plant, not a seed.

Let’s take AI as an example. Generative AI didn’t appear out of nowhere, it’s been decades in the making. When ChatGPT launched in November 2022, for the majority of people it signalled the start of LLMs — when actually OpenAI's API had been available since 2020, GPT-2 had caused alarm bells in 2019, and the transformer architecture underpinning all of it was published back in 2017. The seed had become the plant, but the seed had existed in various stages of development before that.

When we create these snapshots in time of how things are, we’re also defining what we believe about them. How did you feel about Generative AI in 2020? How did that change in 2022? How do you feel about it now? It may be the same, or it may have changed, depending on what messages and evidence you have been exposed to, and whether that confirms or contradicts your existing beliefs.

For leaders within organisations looking to increase AI adoption amongst their teams, they face the challenge of changing not only what people do with AI (behaviour) but also ensuring that the beliefs support that behaviour change in the long term. What do people on their teams believe about AI? That it’s a force for good in the world, or that the harm outweighs the benefits? That they will personally benefit from using it, or that they will be seen as less competent or lose their jobs to robots?

Back in 2018 I delivered a talk on AI at my company's internal conference, where I was generally optimistic about its potential and our collective future with it. My position now is more nuanced — shaped by years of watching promises outpace reality, and by my own direct experience of what the technology can and can't do. I’m the same person, but I now hold a different belief. And this belief change came about not because of a single moment of revelation (in a workshop), but because of accumulated experience over time.

Which leads me to my conclusion: workshops work best at the early stage of the change cycle — to raise awareness, give a new language and mental model to describe what is happening, and generate a motivation for change. But they fall short at ensuring that change is successful longer-term, because that requires sustained effort over time.

My one caveat to this: a carefully designed programme that blends workshops with other learning formats like individual and group coaching, accountability mechanisms, systemic incentives, and intentional practice in the real-world can create belief change. But in a world where organisations are looking at change through the lens of a quarterly OKR, instead of a multi-year commitment, the theatre will continue and we will continue to be stuck in our old ways of thinking and doing.

So what’s the alternative?

The answer isn’t a better workshop — it’s building the capability to lead belief change from within.

I work directly with leaders through 1:1 coaching — we can go deep on your beliefs, understanding where those diverge from your organisation’s, and on building the capability to lead change from the inside. When you understand how beliefs operate, you can create the conditions for something more durable than a post-workshop buzz.

The goal isn’t dependency on me: it’s that eventually you don’t need me. If you're a leader who recognises this pattern in your organisation, Let’s talk.

It’s the first time we’ve been back to the Moon since the 70s — I wasn’t even born when the Apollo missions wrapped up — and I’ve been feeling the excitement build inside me all day.

And what made this possible is decades of shared belief, amongst people and nations, that going back to the Moon was both possible and desirable. It’s taken thousands of people years of working together to make this happen.

In a world wracked with conflict, it’s a powerful reminder that humans are really at our best when we’re working together to make the impossible happen.

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Purpose emerges from systems of belief

Earlier this week I interviewed Sarah for my forthcoming book, Beliefocracy. Towards the end of our conversation she shared her life’s purpose: “To make a difference to people's lives. Predominantly in mental health because that's where I've spent my whole career, working in mental health from the age of 18.”

It was the first time that purpose had come up in interviews, and I needed to reflect on how this fits with the model I’ve created in Belief OS™, because it touches on all four levers:

• Meaning — purpose gives our lives shape and helps us interpret our life experiences

• Affect — our purpose is based on value judgements about what is good and needed (which very much underpins the Japanese concept of ikigai).

• Social — a purpose can unite people to work together

• Context — having a purpose can influence what you do at work, or in life more generally

It didn’t neatly fit within the model as it currently stood!

So after some reflection I came to the conclusion that purpose actually sits above the model — as an emergent property of a collection of beliefs interacting together. An emergent property is a phenomena that arises from a system but cannot be found in any individual component. The whole exhibits behaviour that its parts don't have on their own. The example I always come back to is consciousness — we know it exists because we each experience it, but we cannot point to the specific part of the brain, neurones or neurotransmitters that it arises from.

When it comes to purpose, this emerges from a collection of beliefs acting together, to reinforce each other and align in the same direction (what Sarah calls her ‘North Star’). An example of a collection of beliefs supporting Sarah’s purpose could be:

• I believe people deserve good mental health

• I believe mental health support should be accessible

• I believe in training therapists to be exceptional

When these beliefs align and reinforce each other, they create a direction of travel strong enough to guide Sarah through uncomfortable boardrooms and career-defining moments. One person's purpose emerging from their belief system. But what happens when thousands of belief systems align around a shared direction?

Why are we going back to the Moon?

I’ve been glued to BBC News throughout the day. And of course, alongside the buzz and anticipation have been the inevitable comments: why are we even bothering to go back?

First, let’s look at the economics. The Artemis programme has cost about $93 billion in total. If Apollo is anything to go by, that investment will pay back exponentially. In 1975, economists calculated Apollo’s ROI at 15-to-1 — and even that turned out to be an underestimate. One report described the actual return as ‘off the charts‘.

Second, the Moon contains important resources that many nations are interested in taking control of — so it’s a race to see who gets there first (which is somewhat reminiscent of the 1970s…). The Moon contains rare earth elements which are needed in technology production, and water is trapped in ice beneath its surface. The Artemis missions scheduled between now and 2028 are strategically designed stepping stones towards establishing a permanent lunar base.

And beyond the Moon is Mars. NASA has its sights set on the red planet, with missions planned for launch in the 2030s. It is a lot easier to launch deep space rockets from outside Earth’s atmosphere than it is from the surface. The Moon could provide essential launch capability.

But none of these truly answer the purpose, nor the collection of beliefs that underpin this drive to the Moon. And that is harder to answer, but interviews with experts in the space industry hint at it (all quotes taken from BBC articles).

Keith Wright, an engineer who worked on the original Apollo mission, says this: “We now need to learn to live properly off the planet because we need to spread our humanity away from the Earth. With the Earth we've got all our eggs in one basket, and if anything really disastrous happened we are in serious trouble.”

David Morris, whose team makes imaging equipment for the space agencies, said “If you look back to what happened in 1969 and the transformational aspects of seeing men on the Moon, I'd like to think that similar global excitement can happen when we see it happen again. It will invigorate the world to think more about being 'the world' rather than just lots of separate nations.”

One of the Artemis II crew, Christina Koch, said this: “[The] discovery and knowledge that we bring back to Earth is the “entire point” of the operation.”

Together these beliefs — that humanity's future extends beyond Earth, that exploration unites us, that discovery matters for its own sake — don't exist in isolation. They overlap, reinforce each other, and align across thousands of people who have dedicated years to this mission. Together, they create an emergent collective purpose powerful enough to survive budget cuts, political changes, and decades of setbacks: humanity belongs beyond Earth, and building that future starts now.

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When you’re ready, I work with women leaders in tech and space through executive coaching and speaking engagements.