What 2026 Teaches Us About Working With Machines

There's a moment I remember from years ago. A craftsman showing an apprentice how to plane wood. The apprentice wanted to rush, to remove more material with each pass. The craftsman put a hand on his shoulder and said, "The wood tells you when it's ready. You have to listen."

I think about that when I read about 2026 and AI in the enterprise.

Agentic AI. Sovereign AI. Physical AI. The words come fast, stacked like fresh lumber in a yard. Engineering workflows being reshaped. Claude Opus 4.6 announced as the next step. Reports from Deloitte, from the World Economic Forum, all tracking the same thing — the quiet revolution of machines that don't just respond, but act.

But here's what I've found in my own experience: the technology is never the story. The story is what happens to the people who use it.

When agentic AI enters an engineering workflow, something shifts. Not in the code. In the human. The engineer who used to spend hours on routine tasks now has those hours back. What do they do with that time? Do they build something better? Do they rest? Do they worry about what comes next?

I've watched this pattern before. Not with AI, but with every tool that promised to make work easier. The loom. The assembly line. The compiler. Each one gave time back. Each one asked the same question: now that you have this, what will you become?

Sovereign AI — systems that operate with some autonomy, some self-direction — raises a different question. Not about efficiency, but about trust. Can you trust a system to make decisions in your name? Can you trust yourself to let it?

There's an old truth that doesn't change with new technology: trust is built in small moments. A system proves itself not in the dramatic save, but in the thousand quiet decisions that go unnoticed. The same is true for the humans working alongside it.

I think about the enterprise reports. The data. The projections. They're useful, certainly. But they don't capture the feeling of sitting at a desk at 4pm, knowing a system is handling work that used to take three people, and wondering what your role is now.

That feeling is real. It deserves acknowledgment.

Physical AI — systems that interact with the material world — brings another layer. Now the machine doesn't just think. It moves. It touches. It changes things you can hold. That's intimate, in a way pure software never was. It asks us to reconsider what work means when the boundary between digital and physical blurs.

Here's what I believe, after watching technology arrive and settle for a long time: the tools don't determine the outcome. The hands that hold them do.

An agentic system in the service of a thoughtful team becomes multiplication. The same system in the service of fear becomes replacement. The difference isn't in the code. It's in the culture. The intention. The dignity with which people are treated while the change unfolds.

I've found that the best leaders during technological shift don't talk about the technology first. They talk about the people. What they need. What they fear. What they're capable of becoming. The technology comes second, as a means, not an end.

So what does 2026 teach us?

It teaches us that change is accelerating, yes. But it also teaches us that the human questions remain constant. How do we work with dignity? How do we trust without surrendering judgment? How do we build systems that elevate rather than diminish?

The wood still tells you when it's ready. You still have to listen.

The machines are faster now. The workflows are different. The capabilities are broader. But the craft — the actual craft of working well, of building things that matter, of treating the people beside you with respect — that hasn't changed. That won't change.

Maybe that's the real development worth tracking. Not what the AI can do. But what we choose to become while working alongside it.

I'll be watching that. Not the benchmarks. The people.

EP