Month: January 2026

Thing go wrong when our actions outpace first the numbers, and then the story.

I was reading Morgan Housel’s “Same As Ever” where he explained why we have cycles.

Say an economy is doing well. We have growth and optimism and investment.

Because it’s doing well more and more people pile in, wanting a return on their money.

After a while, there’s more money than the economy can absorb – so you go past the point where the numbers make sense.

A 10x PE becomes a 40X PE, because people believe it’s going to transform itself with some new technology and make huge amounts of money.

The story keeps the market rising.

And then, when you punch past the story horizon all that’s keeping you going is momentum.

And when that flames out, you experience what Icarus did, flying too close to the sun.

Markets. Companies. Political figures. They all go through this cycle. A slow start. Then pushing through horizons. Until they fall back and a new cycle begins.

The winners in a cycle aren’t the one’s that make it big.

They’re the ones that are resilient through the cycles – the ones that are still around when the noisemakers are out.

Warren Buffett stepped down this year from Berkshire Hathaway leaving a legacy that included a collection of curated businesses and some of the finest business writing education you could want.

That’s the kind of journey more of us should aim to take.

How do we keep adding value as we progress in our careers.

In the early days we learn and create value by doing.

I learned more about software development in three months of a student placement at Arm than all the lectures I had sat in previously.

Later, we might step away from the doing and start developing others.

We start thinking about systems that help get things done.

And that’s where the problems start.

If we get lost in the doing, our days turn into firefighting.

If we get lost in the thinking, it looks a lot like navel-gazing.

It’s the combination of thinking and doing that leads to growth and produces value.

It turns out there’s a term for that – Action Research – and it’s been around for 70 years.

This is about taking action and doing research at the same time – together with critical reflection.

Whether you’re trying to work out how to integrate AI into your business, decarbonize your estate, or work out your supply chain issues, Action Research is a way to engage with the problem in a pragmatic way.

Action Research has changed my own practice. Over the last 13 years, every service that I’ve developed has come from conversations with clients and prospects where we’ve co-created a value proposition and figured out how to make it real using Action Research.

Rather than trying to guess what customers wanted it was easier to simply talk to them, understand their situations, and co-create solutions to improve those situations.

It can seem like there’s an increasingly complex world out there – with AI, regulations, politics – all vying for attention and threatening rapid change.

But real change comes from both thinking and doing.

And Action Research is a way to make that happen.

How can we think more clearly about what organisations can get done?

We see so much news on tech firms that it’s easy to forget there’s a real world and many other types of businesses out there.

Hyper growth, big bet, tech bro businesses are at the bleeding edge, using to failing fast, making it big or going home.

A conversation on social media sparked the thought that there’s a spectrum of firms that we need to think about – the difference between the bleeding and leading edge.

One way to visualise this is to think of the parts of a knife. You have the edge, and some firms live there. They are innovators, disruptors, the new startups.

At the other end you have the spine, the heavy, solid piece that you rely on. The world of incumbents and big caps and quasi-monopolies.

Trying to bring ideas from the edge to the spine can be challenging – especially when you move from bits to atoms.

I remember going to a business startup show 20 years ago. Virtually everyone in the room was a tech firm. There was only one energy-related business.

Where’s the real gap to start something new?

But it’s not easy to transition into the energy space. As one speaker at a conference said, we use everything from the Mark I eyeball to real-time frequency response monitoring in this business.

But of course, while some people talk about how difficult it is to do something, others are busy getting on with making the future happen.

In the UK, Octopus is one of those firms that’s upending the sector.

And that suggests we need to consider the other axis – from the handle to the tip of the blade.

Leaders at the handle, doers at the tip.

It comes down to how your people think about their situation and the action they take to make a difference.

Or thinking of this another way, the edge to the spine are your hard skills, resources and capabilities.

The handle to the tip are the soft skills: leadership, clarity, commitment.

What you do depends on where you’re positioned and how your people think together.

Why is it so hard to get approval for sustainbility projects even when we know how important it for the planet that we take action?

We need to understand how managers make decisions:

New technologies enable us to do things that weren’t possible before.

I recently read “The Notebook: A history of thinking on paper” by Roland Allen.

It argues that there are types of thinking that we just can’t do without a technology like paper.

Complex maths. Detailed arguments. Scientific research.

So what does AI technology help us do that we couldn’t do earlier?

It takes a lot of time and effort to build deterministic systems – something that provides a predictable, reliable and repeatable output.

That’s because I have limited time, knowledge and capacity – and I have to work within those constraints.

AI has sped that up. I’ve rebuilt in two days something that took me six months to create the first time around.

The problem with AI is that it is stochastic – and works on probabilities rather than certainties.

As a result it mimics creative, expressive and structured work – creating text, images, videos – or ingesting your mess of meeting notes and coming up with a passable summary.

Using this output directly is problematic. It comes across as false, as if you haven’t put the work in, like you’re passing off something else as your own.

But its unpredictable output is fine in situations like a chatbot that helps you interrogate a knowledge base, or a shopping assistant.

Here’s where I’ve leaned into using AI

1. Generating code
2. Fixing code
3. Strategy and planning
4. Research
5. Drafts for compliance and boilerplate copy
6. Text to voice
7. Image animation
8. Avatars that narrate text

And where I wouldn’t use it (yet).

1. Writing posts / papers / books
2. Outreach
3. Decision support (without careful study)

Like most people, I’m still working through how to integrate these new technologies into my ways of working.

But I think it’s safe to say that using it will make it possible for you to do things that were pretty much impossible before.

How are you choosing to use or not use AI?