Technology was never the constraint. Now it really isn't.

I've spent most of my career helping organisations create value with technology. Start-ups. FTSE businesses. PE-backed companies. Large transformations. Product businesses. M&A. If that time has taught me one thing, it's this: technology has rarely been the limiting factor.

Time is. Investment is. Complexity is. The organisation's appetite for change and innovation is. And above all, the cost of finding out whether an idea actually works.

Which is why the last twelve months have caught me off guard. I've been around technology long enough to have lived through most of the major hype cycles of the past twenty years, and very little genuinely surprises me anymore. This has.

Not because AI can write emails or generate images. Those are party tricks compared to what's actually happening. The real story is what AI has done to the economics of building: products, businesses, and solutions to problems that have sat untouched in backlogs for years.

The friction has disappeared

Historically, taking an idea from concept to working reality was expensive. You needed product managers, architects, engineers, infrastructure, test environments, security reviews, budget approval, and months of coordination before anyone could tell you whether the idea was any good.

Most ideas died in PowerPoint. Not because they were wrong, but because proving them cost too much.

That equation has collapsed. A single person with domain expertise and product thinking can now take an idea to a working prototype in days. Not a slide describing the thing. The thing itself. Workflows. Internal tools. Automations. Entire applications.

I know because I've been doing it. Over the past year I've spent evenings and weekends building with these tools: working applications, automations and products that, not long ago, would have required funding approval, specialist teams and months of delivery effort. Some of it worked. Some of it broke in instructive ways. All of it changed how I think.

And when the cost of experimentation collapses, something interesting happens: thousands of problems that were previously "too small to solve" suddenly become economically viable.

That changes everything.

The real opportunity isn't AI. It's leverage.

Many people are still looking at AI through a technology lens. I increasingly see an economic one. A leverage story. A productivity story. A business model story.

When the cost of building falls this dramatically, you don't just do the same things more cheaply. You do things that were never worth doing before. More experiments. More products. More swings at more problems. More value creation.

The organisations that internalise this first will operate at a pace that will look completely unreasonable to their competitors.

But expertise matters more than ever

A misconception is taking hold: that because AI can generate code, technology expertise somehow matters less.

I think the opposite is true.

The internet is already filling up with AI-generated applications that look impressive and are fundamentally flawed. Poor security. Weak architecture. No governance, no resilience, no operational thinking, no understanding of enterprise reality. AI can produce software extraordinarily quickly. It can produce technical debt even faster.

The differentiator is judgement: understanding architecture, risk, scale and operating models. Knowing what good actually looks like. Knowing when to build, when to buy, and when to partner. AI has made those instincts more valuable, not less, because they're now the scarce ingredient.

The constraint is moving

Throughout my career I've found myself obsessing over the same questions when attempting to innovate.

What's the job to be done? Where's the pain and gain? What happens immediately before this problem, and immediately after it? Why does this exist at all? Keep asking why, why, why...

Those questions matter more now than they ever have, because implementation is getting easier by the month while knowing where the value sits remains as hard as it's always been.

The constraint is shifting away from technology and towards imagination, judgement and execution.

Which is why I think every senior leader should be building

Not because they need to become engineers. Not because their organisation's next product should be built this way. But because you cannot fully understand what's happening from a strategy paper, a vendor demo or a conference keynote.

You have to feel it. You have to experience how fast an idea can move. You have to see where it breaks, where the risks sit, and what these tools still do badly. You have to develop your own sense of the art of the possible, because that sense is precisely what changes your perception and your outlook.

Once you've built something, anything at all, you start seeing differently. Processes that shouldn't exist. Products that are suddenly viable. Business models that can be reimagined. And you start questioning assumptions about how digital products get built that have held for twenty years and may simply no longer be true.

And none of this means building everything yourself. Often the smartest move is still to buy, or to partner with people who do it brilliantly. But you make that call far better once you've built a few things and felt where these tools are strong and where they quietly fall apart. That kind of judgement is earned, not read.

Final thought

I don't think AI is replacing product leaders, architects or technology executives. I think it's making the very best ones exponentially more effective.

Technology has always been an input. Value creation has always been the outcome. AI has simply rewritten the economics of getting from one to the other, and I suspect we're still at the very beginning.

So if you're a senior leader and you haven't yet built anything with these tools: pick a problem that annoys you and give it a weekend. Not for the output.

For what it does to how you see and feel.

In the spirit of the piece, a disclosure: AI helped me write this. AI didn't provide the thinking. It simply amplified my ability to express it.