What staying technical taught me about leading through the AI shift

There’s a growing narrative that AI is bringing tech leaders “back to the code.”

It assumes they left.

I didn’t. I’ve been hands-on throughout my career. Building enterprise platforms that serve thousands of engineers, reviewing code, debugging production issues, making investment cases for technology bets that returned multiples of what they cost. Moving into senior leadership meant adding strategy and commercial accountability on top of the technical work, not replacing it. When I picked up AI tools for the first time, there was no “getting back to” anything. It was more like someone handing me a better set of tools for work I was already doing.

That’s where it gets interesting.

Outside of my day job I run a small software studio. I shipped a cross-platform desktop application that’s already serving a global user community, built an AI agent that handles support triage and business operations autonomously and I built Vectimus, an open-source AI governance platform that went from concept to working product in days and is now used worldwide.

What used to require a team, a quarter and a budget request now fits into focused evening sessions. That’s not a productivity hack. That’s a structural change in how ideas get validated and how fast you can move from seeing a market gap to testing whether your solution works.

Think about what that means inside an organisation.

When senior leaders can independently test whether an idea has legs before it enters a roadmap, the whole machinery around investment decisions speeds up. Fewer speculative bets consuming engineering capacity. Faster signal on what’s worth committing to. Less time spent building the wrong thing because someone two layers removed from the technology made assumptions that never got challenged. In an environment where most companies are still struggling to get meaningful ROI from their AI spend, that ability to separate signal from noise before committing resources is worth more than another pilot programme.

The ones who stayed close to the craft can now validate technical direction themselves before committing teams to weeks of work. They prototype approaches, stress-test architecture decisions and arrive at planning conversations with better questions. Not as engineers. As leaders who can tell the difference between a real opportunity and a plausible slide deck.

Most of the conversation right now is about AI making developers faster. I think that massively undersells it. The bigger shift is what happens when people who understand both the business problem and the technical landscape can collapse the distance between strategy and execution. Companies that have technical leaders in senior roles who actually use these tools are sitting on a competitive advantage most of their competitors haven’t even identified yet.

The gap between strategy and execution is shrinking fast. The leaders who can operate on both sides of it will shape what comes next.