Month: July 2025

I’ve been making a conscious decision to put the phone away and read more – and I’ve just finished James Shapiro’s 1599 – A year in the life of Shakespeare.

This was an incredibly productive period for Shakespeare. He wrote Henry the Fifth, Julius Caeser, As You Like It, and drafted Hamlet.

The backdrop to his writing is equally interesting. An ageing tyrant was in power, the first Queen Elizabeth. The country was under threat of an armada from Spain and faltering under an Irish Rebellion – and the Queen was relying on a brash young noble, the Earl of Essex, to go in and sort it all out.

I wondered aloud to a friend if the world of today had parallels to the world of 426 years ago.

My friend, a history teacher, reminded me that such backdrops have existed for most of history – power and politics change little because people change little.

Shakespeare had to tread a fine line between saying things that had to be said – that were important to hear – and getting in trouble.

It was a world of censorship, one where books and plays were seized and destroyed if they were considered dangerous.

We know very little about how Shakepeare navigated the politics of the day or his personal views on anything – the richness of his surviving work is only equalled by the lack of information on him as a person.

He must have been good at what he did, however, because he did the work – he wrote his plays, he acted in them, he ran a business – and what he created still helps us make sense of the world.

If you have things to do, for example as Hamlet did, you’ll succeed if and because you have cause and will and strength and means.

In real life the good guys don’t always win.

But sometimes they get the chance to do some good.

My timeline is full of people talking about just how hard it is to carry on the work of sustainability in organisations.

It’s not like the heady days of 2020-22, when we thought everything would change and money poured into ESG funds.

People said, they insisted, that ESG had alpha – that firms with strong ESG would outperform the market.

And that looked like it was the case, for a while.

But, would you bet your life’s savings on a thesis – on an expected future?

Life has an unwelcome habit of attacking you in the rear.

I’m quite conservative. I think sustainability is important – and embedding it in everything we do is the sensible thing to do.

But I’m not naive enough to think that the world works the way I wish it would.

I made my bet on the market. Just hold the index. If ESG firms do well, they will make up more and more of your portfolio. If something else does, you won’t lose out.

And that’s precisely what happened.

Few people – no one I knew – predicted that Russia would invade Ukraine in 2022. Sanctions would mean that a quarter of Europe’s energy imports vanished from the supply side.

The boom that followed was in the oil and gas sector, not in the clean and green one.

The last 6-12 months have been about geopolitics, about nationalism, protectionism and a backlash against regulation, starting with elements of ESG.

So, is all hope lost? Should we just give up?

Of course not. A simple constant in life is that one thing happens after another.

As long as I have worked, there has been crisis after crisis – all we know for sure is that something will happen that we didn’t or couldn’t predict.

Things happen in cycles. And being responsible for cleaning up our mess will come back into fashion.

In the meantime, businesses would do well to batten down the hatches, to run lean and figure out how they can do more with what they already have.

For a long time, everything I saw suggested that people in organisations rise until they reach a sustainable level of incompetence.

For the first time, I think that’s no longer the case.

The idea, as you probably know, is based on the Peter principle, developed by Laurence J. Peter that suggested that success leads to promotions until you reach a point where you are no longer competent – and this is where you plateau.

But why would you plateau?

There are two reasons.

First, you’re too senior to do the work so you hire others to do it for you and oversee what they do.

Inevitably, your skills fall behind, until one day you no longer know enough to understand what others are doing.

You did that to someone else, and one day it will happen to you.

The second is that as you rise in an organisation success is less about the work and more about the politics.

This is a well-understood, well-researched phenomenon that derails the best laid plans of well-meaning leaders.

They spend so much time on the politics of their organisations that’s there’s no time left to learn and develop their own capabilities.

So what’s different now?

It’s that you now have a friendly AI to help – to be there and support your learning journey – a supportive system that has your back.

It means that you can figure out how to do something in a few hours that would have taken you six months the old way – where you had to hunt down the information.

I cannot begin to express how transformational this can be – if you use it right.

The key is using these tools to help supercharge your learning rather than seeing them as tools that you can offload work onto.

Why did you hire someone to help you in the first place – presumably because there was a task to be done that was taking too much of your time and the value equation didn’t add up?

But now, if you can spend less time to solve that problem than it will take to go through the pain of recruiting someone – shouldn’t you just do that?

But there’s one more thing that will make the difference between doing this well and getting overwhelmed.

When you can learn anything – you should focus all your time and energy on what you can do best and partner with others on what they do best.

That, I think, is the future of teams – in companies, boutique consultancies and all kinds of organisations.

The concept of a chasm that we must cross was introduced by Geoffrey A. Moore in 1991 to explain the adoption challenge faced by people marketing innovative new products.

This may be a useful model to help us figure out how to adopt AI – and maybe make it work.

You might have seen a version of the saying that goes around where a man says to a horse, “A tractor won’t take your job, but a horse using a tractor will.”

I have a feeling that some of us might be horses when it comes to AI.

At the recent EURO conference Nici Zimmerman said that building AI was a computer science problem – deploying it was operational research.

The huge amounts of capital and technical talent poured into the computer science bit means that a huge number of people – billions now – have access to free or low-cost AI.

The next step is deployment – and we’re all figuring out how that’s going to work for us.

Let’s look at three use cases and I’d be interested in your reactions.

1. Using AI images and video in posts

As you know, I draw all my blog and LI pictures and write the text myself.

So, I may be biased, but I find myself scanning text and images and if I think they are AI generated I am less likely to click or engage with them.

There’s one or two that stand out – the Schein critique, for example – but on the whole I’m not interested.

1. Using AI to create applications or long-form documents

These tools are great at outputting large amounts of content – whether that’s code or text – and it looks like something useful is going on.

There’s another observation going around – if you have 50 lines of code to review, then you’ll probably look at it and have comments. If it’s 5,000 – then meh, it’s probably fine.

Big stuff takes time to proof, and if you don’t know enough to do that or aren’t willing to hire someone to do it then it’s likely that stuff gets shipped that is flawed.

For big projects, I’m currently betting that resource levels don’t go down. Instead they shift from building stuff to shoring up broken stuff and getting increasingly frustrated.

1. Professional Services

This is where AI is having an impact, as far as I can see.

You have someone that has to take responsibility – a lawyer, a consultant – and as part of that they need to review and understand material.

AI can help do that. It can take a first pass and help you figure out where to look.

It means that you, as a senior, experienced person, don’t need a junior or assistant any more.

That’s an important distinction. Many people look at jobs and think that they just exist, that’s there’s a fixed stock of jobs out there, something like a fixed stock of gold.

That’s not the case. Jobs are made. That job you’re doing didn’t exist once. Someone created it.

And AI will mean that some jobs are no longer created. They’re just not required any more.

But new ones are.

And the most important one, one Ethan Mollick suggested, is that of “sin eater”.

Someone that takes responsibility to take what AI makes, and make sure it’s usable.

In the age of AI, we’ll have to be more responsible if we want to continue to exist.

This week marks perhaps the most important milestone in my life.

My youngest son will finish junior school.

If you know me, you will know that I have spent the last 20+ years obsessed with decision making.

And what I’ve learned comes down to the thing that my son’s teacher said she shouted while running after him.

“Make good choices”

If you have young children, pre-school, perhaps, here are two pieces of advice that I will never have cause to regret.

The first comes from a blog post I read by Tim Urban of WaitButWhy.

He wrote that people don’t realise that by the time we turn 18 and leave home for the next stage of our adult lives we’ve spent 93% of all the in-person time we’ll spend with our parents. It’s already the tail end of your time together.

If your kids are 3, that’s 15 more summers. 15 holidays if you go away somewhere with them once a year, before they pull away from you.

I am quite tight, but it was a simple decision to say we should at least do two experiences a year. More if possible. Double or triple our stock of memories with the kids.

Not expensive stuff. It’s not about money. It’s about having more time with your children.

The second thing is that if you put work first you’ll miss the first 10 years of your kids’ lives as well.

Leave at 7.30, come back at 7 and do that for long enough, and the years will go by. And you’ll miss really important stuff. You’ll miss them growing up.

I tried very hard to construct the kind of working life where I could move from commuting every day to being at home.

I’ve managed to have around 6 years of walking my kids to school. Six years of four minutes twice a day. Walking up and down, hand in hand.

One day, as comedian John Bishop said, one day they’ll let go of your hand and never hold it again.

And it ends this week.

But I was there for it.

These two decisions will be, as far as I am concerned, the best choices I ever made.

And if you are in that stage of life, with children that are still young, I would strongly advise that you consider making them too.

I was trying out the new Gemini cli coding assistant on the weekend and it feels like something truly new – worryingly so.

It could be the equivalent of bringing a digger to a spade fight.

We needed our garden doing for years. The space was hard to access and the early quotes we got were astronomical because they involved a couple of folks with spades digging out all the soil for a few days.

So we waited until we were doing larger renovations, and got a digger around, which flattened everything in a few hours.

And that’s the sort of difference I see that working with a coding assistant in the command line can bring.

It’s foundational.

You can ask it to work out a plan for a an application, set out the folders in a modular way, and start creating the skeleton of the application.

It hurries along, setting things up, testing them, seeing there are errors and fixing them.

You get to the point where the workspace is flat and prepped and ready to go pretty quickly.

And that speeds up your ability to create tools that help – and figure out which ones work and which ones don’t.

I could build (or have the AI build for me) a couple of tools that just worked in the time it takes to go and make a cup of tea.

Another attempt at a more complex tool didn’t work out quite like I wanted but it reminded me that I had another approach that worked ok.

For a developer, speeding up the time between idea, code and execution is important.

The sooner you have working code, the sooner you can tell whether you’re on the right track with a solution or not.

I know there’s a massive debate about whether AI is simply doing things that artists should be doing by taking and remixing their work without permission.

But in software development this is starting to feel like an emergent phenomenon, a shift from a coding language to a natural language development pattern, something that is a throw back to the dreams of literate programming.

In this space, anyway, it feels like something new and important is happening.

There’s a model that I first came across ten years ago – that helped me make sense of the ten years before that.

And I now think it’s a helpful tool for anyone looking to position themselves for the next ten years by figuring out what kind of operation you’re running.

This is what I learned.

Once upon a time, there were butchers, bakers and candlestick makers.

In this pre-modern world you didn’t need to know about flour to operate a forge, or wax to make a loaf.

Individual professionals did their own thing with simple machines – hands, heat, hammers – and coexisted.

Then we had the industrial revolution and a step change in the way we made things.

Capital was deployed into factories and the modern world was born.

It was a world of strong machines, with workers that served the machines. The workers were ordered, structured, placed. They were interchangeable, replaceable, pieces on a board to be positioned and played by management.

Our modern hierarchy, command and control style operating structure comes from this world.

And then, sometime in the last century, the post-modern world came into existence.

This was a world of smart machines. An information age. Of networks and connections. Where the links between things mattered as much as the things themselves.

And there are obvious differences.

If I have a hammer and I give it to you, now you have a hammer and I have nothing.

If I know how to do something and I teach it to you, we both know this thing. I lose nothing.

So, what kind of business do you operate? Are you a lone genius that does your own thing? Do you have a job in a corporation? Or are you part of a network?

Knowing this gets even more important in this age of AI.

Now, the smart machines are everywhere. Anyone can have them.

Many people still think that they have to use modern methods to build organisations – using techniques to control and motivate people that are at least a hundred years old.

The observant ones will notice that it’s now about teams – small groups of people that want to work with each other and use smart machines to supercharge what they do.

What kind of operation makes this possible? Who’s doing this already? What does great look like?

That’s the change that’s coming. Ready or not.

I get concerned sometimes that the information I am exposed to is so highly curated that I learn nothing new at all.

We need to create conditions that allow us to be surprised.

There are three approaches that work for me.

The first is to frequent charity shops.

Books in a charity shop offer a glimpse of what others, who may be very different from you, find interesting.

For example, I came across Austin Kleon’s “Steal like an artist” in a charity shop, which then led me to Lynda Barry and Ivan Brunetti’s work on cartooning.

The second approach is to read the paper.

It’s much easier to go with free media but if you have library access and can get hold of titles like the Economist you get some really interesting perspectives.

The mix of stories in a newspaper are written without knowing you – so there’s a good chance there’s something in there that will be different and interesting.

The third approach is to get recommendations.

In a world where AI can help people pump out material designed for virality rather than substance personal recommendations get ever more important.

If you rely on just social media, then the algorithm seems to feed you what it thinks you would like – and the content seems to converge pretty quickly.

There are good posts but they can disappear as you scroll along, so I make a point of saving the good ones – so I can share them later.

And perhaps surprise someone else.

If you hang around academics for a bit you notice that they use a kind of shorthand.

Take the way we normally talk about AI in businesses.

We look at the way in which we’re going to use it to speed up coding. How we can create documents more quickly. How we can summarise information. How we can make games more accessible quickly.

And we go on about the implications. At length.

And then you listen to a good researcher who says five words.

“The epistemology is efficiency logic”

I always have to look up the meaning of epistemology. Wikipedia is helpful for this but the article is a rabbit hole and one should probably stay away from it.

In a nutshell, however, it’s about the theory of knowledge. How we know what we know.

And in this case – when it comes to AI – we’re trying to think about what we think it can do.

And that’s to make us more efficient. More productive. Able to do more with the same resources.

Hence, efficiency logic.

And that’s really all you have to say about that. You can now move on to the next point, if there is one.

The great thing about a well written paper is that each sentence is worth reading. Each one adds knowledge rather than regurgitating what has already been said.

You know how some books are really one idea spread over 300 pages.

A good paper has a hundred good ideas – expressed clearly and efficiently.

It’s not something that can be summarised. It’s already as compact as it needs to be. Any less, and you lose something.

This post is not a good example of that. It’s exploratory, ruminative and far from distilled.

If you had to summarise what I’m trying to say in a phrase, it might be back to Strunk and White’s timeless advice.

“Omit needless words”