Time to Think

There is a rhythm that takes over when you spend days in the saddle. The world narrows to the width of the road, the steady turning of the pedals, and the sound of the English countryside—rain included.

The purpose of my cycling journey across England was simple: to visit my newborn grand-niece, Florence (born on the same day as Florence Nightingale). I also wanted the journey to carry a second thread—reflection on thinking, learning, and attention. I took Nancy Kline’s Time to Think with me.

Newborn Florence. What a beautiful, pure and curious soul she is!

A mobile laboratory

Kline’s premise is simple: the quality of everything we do depends on the quality of the thinking we do first—and good thinking requires space and attention.

A bicycle tour turns out to be an unusually effective laboratory for this. No meetings. No notifications. No agenda beyond the next village. Just repetition, motion, and a mind disconnecting from noise.

Well, mostly. There was rain, there were more punctures than expected, and the traffic was occasionally overconfident in its interpretation of physics. But even that becomes part of the rhythm, eventually.

An unpaved section of National Cycle Route #1!

Places that hold thought

As I moved through England, I began to notice how often thought seems to gather in certain places.

Oxford and Stratford-upon-Avon are saturated with it. You feel it in the density of books, weight of stone, and arguments made over the centuries.

Oxford

But deep thought doesn’t only happen in institutions. Further north, at Woolsthorpe Manor, Newton’s birthplace, the story goes that much of his transformative thinking on gravity and calculus took shape not in Cambridge, but in his family’s orchard during the plague years. Whether exact or embellished, the image stays with you: revolutionary ideas generated not in a frantic hub of activity but in stillness.

That contrast stayed with me as I rode on.

Newton’s Orchard and Home

Lincoln

Standing beneath the vaulted ceilings of Lincoln Cathedral, I was struck by the scale of what people can build across generations. Stone laid upon stone, intention upon intention, each generation adding something lasting to something far larger than itself.

It made me wonder: building things that outlast us requires ultra-long-form attention that seems incompatible with today’s ‘notification economy’.

Lincoln Cathedral

The real distance

The kilometres on the bike were only the visible measure of the journey. They were scaffolding.

The real distance was mental: the slow clearing that comes from sustained movement and an open uncluttered mind.

Whether in Newton’s orchard, beneath the dreaming spires of Oxford, inside the stone vastness of Lincoln Cathedral, or in the quiet presence of Florence, the same idea kept returning in different forms:

We think best—and perhaps live best—when we step out of the noise and give ourselves time and space.

Human Literacy

Foundational literacies

For much of my professional life, I have been committed to enabling teaching and learning, particularly the foundational literacies that help people thrive: reading and writing, numeracy, scientific and cultural literacies. These are the building blocks upon which so much else depends.

Human Literacy

As AI becomes increasingly capable—and may soon outperform us in many of these traditional literacies—another literacy is moving to the foreground: human literacy.

Human literacy: the ability to understand and regulate ourselves, relate effectively with others, and continue to learn, grow, and flourish.

If traditional literacies help us engage with knowledge, human literacy helps us engage with ourselves and one another.

Environment of Trust

Cultivating this literacy isn’t just an academic exercise, it requires intentional practice. This realisation was one of the reasons I enrolled in a nine-month coaching programme at Henley.

I expected to spend my time learning coaching theories, frameworks, tools, and techniques. What I did not fully anticipate was the importance of the environment in which that learning would take place.

One of the most striking aspects of the programme has been the sense of trust, safety, and support created among participants and faculty. Coaching requires openness, curiosity, self-awareness, and, at times, vulnerability. These qualities cannot be forced; they emerge when people feel respected and free to experiment without fear of judgement. They become more rather than less important as AI takes on a growing share of analytical and knowledge-based work.

It was remarkable how quickly accomplished professionals became willing to share uncertainties, experiment with unfamiliar approaches, and offer candid feedback. This has established a community that feels deeply collaborative rather than competitive. Credit to the faculty and team for creating this!

Personal Struggle

One of the most challenging aspects of the programme for me has been learning to step out of the driving seat. My instinct is often to steer people reach a conclusion, but effective coaching requires creating the conditions for the coachee to find their own way forward. Before joining the programme, I assumed I would be most drawn to structured, solution-focused approaches. I was surprised to find myself appreciating more humanistic and systemic perspectives. They often created a greater sense of calm and presence in the conversation, which in turn seemed to help the coachee open up and explore more freely.

It has been a useful reminder to me that some of the most valuable learning comes from the approaches we initially resist. It’s a lesson I hope to carry beyond coaching.

Learning Partnership

The connection between coaching and learning has been the most valuable insight for me so far. Good coaching is not about providing answers. It is about creating the environment in which learning can happen—cultivating trust and psychological safety, encouraging curiosity and reflection, offering challenge alongside support, and enabling continuous growth.

At its best, coaching is a learning partnership. It helps people think more clearly, discover new possibilities, and move forward with greater confidence and purpose.

I expected the course to be the project. Instead, I have found that I am the project.

Coaching and Mentoring

Today was my last day as Chairman of Infinitas Learning — and the end of an important chapter for me in educational publishing, following my earlier years as CEO of Sanoma Learning.

Those who know me well know how passionate I am about learning, and about the role organisations like Infinitas and Sanoma play in supporting learner outcomes and helping teachers in their vitally important work.

Following its acquisition by NPM Capital as lead investor, we have doubled the size of the business, including expanding into Portugal and Poland. Working on that growth — alongside the company’s digital and, more recently, its AI transformations — has been especially rewarding. There are enormous opportunities ahead to better support both teachers and students.

Most of all, I’ve valued the people. My colleagues at Infinitas and NPM Capital have been outstanding, and I’m genuinely grateful to have been part of the journey. I wish them every success for the future.

Over the past 15 years leading and chairing organisations in edtech and learning, I’ve accumulated hard-won experience in leadership, transformation, and what it takes to grow — both as an organisation and as a person. And I’m still very much learning. What continues to fascinate me is how much of leadership ultimately comes down to learning.

In the next phase, I want to put that experience to work more directly through coaching and mentoring, alongside my ongoing board commitments in edtech, including as Chairman of Ovivio.

Where I’d most like to help:
Executive transition coaching — supporting leaders stepping into C-suite or senior roles for the first time.
Strategic leadership — working through the real complexity of leading organisations through change.
Personal effectiveness — helping leaders perform at their best.

For mentoring, my focus will naturally remain close to education and edtech (while avoiding conflicts with Infinitas or Ovivio). For coaching, the methodology is different, and I am keen to work more broadly across sectors — including healthtech and business services.

If any of this resonates, or if you simply want to catch up, feel free to reach out here or directly at: johnmartin@contentconnected.com

Looking forward to what comes next.

#learning #education #edtech #coaching #mentoring

Mentorship opportunity for emerging leaders

Over the years, I’ve enjoyed working with younger leaders as they step into bigger roles.

I’ve been fortunate to have some great people in my life who gave me space to reflect and shared perspective. I’m grateful for their support and would like to help others to make progress in their careers.

I’m interested to support one or two developing leaders as a mentor or coach – a sparring partner and sounding board. If this resonates, or you know someone who might benefit, let’s connect.

Feel free to contact me at johnmartin@contentconnected.com

Is the teacher still the ‘killer app’ in the age of AI?

AI in education is often framed as a battle between humans and machines. Based on conversations with teachers, founders and investors over the past year, I believe the real opportunities lie in partnership, not replacement.

The OECD’s Digital Education Outlook 2026 frames AI’s role in relation to teachers across three paradigms: replacement, complementarity and augmentation. But there’s a second often overlooked dimension: institutional embedding.  Moats in education aren’t built on technology or data alone, but on alignment with pedagogical goals, curricula, regulations & governance, procurement processes and professional practice.

1. Replacement — The Productivity Play

In replacement, AI automates tasks historically done by teachers. For example, grading, summarising texts, preparing lessons, generating worksheets and providing basic feedback loops.

This is where much of today’s AI attention is focused. Tasks that were once labour-intensive can now be executed quickly using general-purpose large language models.

However,  technology that replaces discrete tasks can be easy to replicate.  Application-layer companies that don’t control workflow, data or distribution potentially become interchangeable.

2. Complementarity — Enhancing the Teacher

Complementarity is where AI does not replace teachers but meaningfully enhances their capacity. For example:

  • turning classroom data into real-time insights
  • tracking student progress against goals
  • flagging risks and opportunities
  • designing targeted interventions

Here, teachers retain judgement while AI expands insights and  sharpens execution. The result? More impactful and stickier solutions because:

  • the solution integrates with daily workflows
  • the value is tied to teacher judgement, not automation
  • switching costs rise as the technology adapts to context
  • integration with existing systems (LMS, assessment frameworks, schedules) deepens.

In Europe especially, where education systems are fragmented by language, standards and national curriculum requirements, this tailored integration is the key to durability.

3. Augmentation — Supercharging the Teacher

Augmentation involves human–AI co‑evolution: AI learns from teacher feedback over time, adapts to their pedagogical style, and augments their professional practice in ways that produce outcomes neither could achieve alone.

In theory, this is the next frontier.

But the evidence suggests caution. Recent cross‑sector analyses have found that human–AI teams often underperform the better solo performer — not because AI is weak, but because synergy is hard to design and requires:

  • structured feedback loops
  • task‑specific modelling
  • data that is pedagogically meaningful
  • long‑term usage and refinement.

These conditions are relatively rare — and do not emerge automatically from generic chatbots. Consequently, many augmentation efforts risk failing before a few succeed spectacularly.

This layer will be hard to build, slow to monetise, but potentially transformative if it materialises. The Holy Grail, but not for the faint-hearted investor.

But even the most advanced augmentation tools will fail if they don’t address a deeper challenge: institutional embedding.

The Overlooked Dimension: Institutional Embedding

If replacement, complementarity and augmentation describe how AI interacts with the teacher, the moat is arguably how deeply a solution embeds in the system.

Edtech solutions thrive where:

  • curriculum alignment exists
  • pedagogical norms reinforce its use
  • there are many rules and regulations
  • procurement frameworks are understood and effective go-to-market capabilities are developed and in place
  • teacher support boosts adoption
  • governance structures (schools, districts, ministries) endorse and fund it

Know-how about working with institutions and alignment with standards determine durability.

This is particularly true in Europe, where:

  • education is governed nationally and regionally
  • language and curriculum diversity creates product differentiation challenges
  • procurement cycles are long and complex
  • teacher autonomy is the norm.

A solution that is embedded institutionally — even if technically less advanced — will often outlive and outperform one that is technically stronger but misses the expertise around the institutions it is designed to serve.

This is where real moats are built.

The next edtech winners won’t rely on algorithms alone.  They’ll succeed by understanding that the best AI doesn’t replace teachers or even just work for them. It works with them.

Where do you see the biggest opportunities?

Looking forward >>