20 posts tagged with "AI"

As I have written about recently, the job market is in a state of significant change and uncertainty at the moment, and my personal circumstances are a reflection of that.

At the end of this week and after 7½ years, I will be leaving Deltatre for, well, nothing right now, and while that is scary and liberating in roughly equal measure I think it's also an opportunity.

One thing that I think is genuinely changing is the type — or shape — of individual that brings the most value, and I think (and hope) that this favours people like me.

The T-shaped individual has been a stalwart of tech teams for years (decades, even), but I think it's time to change the typographic analogy. It's time to be more tree-shaped.

I let AI help me think out loud, then didn't like how it sounded​

Confession time, though it's not much of one, because I don't think anyone reading regularly was fooled: the last few posts I've written about AI — the team-shape one, the judgement one, the whole "Whose Future Is It Anyway?" run — were drafted with heavy AI assistance[^1].

Not "AI wrote them and I hit publish." More that I was trying to build a proper thesis in real time, out loud, across several posts, and the fastest way I found to drag the shape of an idea out of my own head was to argue it out with ChatGPT first and edit the result after.

It worked, in the sense that the thesis is genuinely mine and I stand behind it. It also produced some of the most oddly flat writing I've put on this blog in a very long time of doing this[^2], and I couldn't immediately tell you why, because I was too close to it.

Across this series, I've traced a clear, compounding trajectory.

Uneven global access feeds into platform dependency, which rapidly hardens into Asymmetric Corporate Expansion — a reality where a tiny handful of commercial boardrooms dictate the boundaries of global productivity.

None of this points to a single inevitable outcome.

It points to a system under pressure.

In the previous posts, I looked at how AI is reshaping access and dependency.

Capability is unevenly distributed across countries, platforms are becoming control points within them, and what starts as leverage can easily become dependency.

What happens when capability, access, and dependency all concentrate in the same place?

In the first two posts, I looked at how AI is reshaping outcomes at a global level.

• Accelerating disruption and opportunity at the same time
• Concentrating capability in a small number of countries and organisations
• Creating real risk of exclusion for those without access

But this dynamic doesn’t just play out between countries, it plays out within them, because even where access exists, control is uneven.

In the first post, I looked at the idea that AI is pulling us in two directions at once.

Massively accelerated disruption on one side, and the promise of prosperity on the other.

What both framings gloss over is a more uncomfortable question:

Who actually gets access to that prosperity?

Because AI isn't arriving evenly.

There’s a framing I’ve been coming back to recently, borrowed from Mo Gawdat.

During the Cold War, the dominant paradigm was MAD — Mutually Assured Destruction — but Gawdat suggests that with AI, we have the potential for something different:

MAP — Mutually Assured Prosperity.

It’s a neat idea, but I’m not convinced it’s that simple.

Over the last few posts, I’ve been writing about AI from a fairly close range — how it changes engineering teams, delivery dynamics, capability development, and the shape of organisations.

In other words, the micro view — what happens inside teams when capability, speed, and decision-making all shift at once.

But the more I’ve thought about it, the harder it’s becoming to ignore the bigger picture, as the same forces are playing out at a much larger scale.

Most discussions about AI focus on capability — what it can do, how fast it's improving, and where it might go next.

My last post focused on the fact that less attention is paid to something more subtle, but arguably more disruptive.

Time.

Not just in the sense of speed, but in how time is experienced across different parts of a system.

Because one of the emerging challenges is that time is no longer behaving consistently.

In my most recent posts, I’ve explored how AI is starting to reshape both the structure of engineering teams and the shape of individual capability.

• Teams shifting from pyramids to more diamond-like structures
• Individuals moving from T-shaped profiles towards multi-pillar depth

There’s a third dimension that sits across both: Time.