What Tech Leaders Need to Unlearn
In the AI era
By Future of Teams · 7 min read
A year ago, I told my boss that AI tools couldn’t understand our complex legacy codebase.
I was wrong, about both the tools and my job.
This isn’t about learning the newest AI model, it’s about unlearning habits and personal biases that hold you back. After 25 years in tech leadership, I’ve seen more waves of transformation than I can count. The constant shift between centralised and decentralised architectures, client side web scripts versus server side, and lets not forget the fundamental shift from Web to Apps in the mobile era. The list goes on.
As tech leaders, we now find ourselves in an unprecedented time with the speed and intelligence arc of AI and LLM models. This shift rocks us to our core at both the possibilities as well as the pace of change. I firmly believe (after going through my own period of wrestling and resisting for a while) that its our key responsibility as leaders in tech to enable this transition. However this shift is not something that happens overnight, at least it didn’t for me.
Resistance to change
Change fatigue is real. Every wave of technology promises transformation, yet for many teams, it just means another migration, another new tool, another training session to survive.
The pace and rise of gernAI is incredible. Numerous statistical examples like the one above from Metr.org clearly show this. But the pace of AI is not the only noticeable difference. AI doesn’t just change what we build, it changes how we think about building. And that triggers resistance at a deeper level, it threatens our identity. When the tools we’ve mastered for decades start doing the work for us, it can feel like we’re losing part of ourselves.
AI Adoption and Use is at 90% at work, up 14% from 2024
— 2025 Google DORA Report
As a tech leader, I realised I couldn’t ignore the pace, but perhaps just as important for me was to not ignore the emotional undercurrent that came with it. I had to normalize discomfort and make space for my team to feel uncertain, without letting that uncertainty freeze progress. It became clear that our job as tech leaders isn’t to have every answer, it’s to hold the space between what’s known and what’s next, and to be able to paint a picture of how the future could look and help others to navigate towards the future.
Change isn’t new. But leading through uncertainty, with flexibility, that’s the real skill of this era.
Good vs. Evil
Spend five minutes on a tech forum and it feels like we’re living in a comic book: AI is the villain, developers are the heroes, and the future of our jobs hangs in the balance.
Scroll through any comment thread and you’ll see the same storyline:
- “AI will take my job.”
- “We’re just training our replacements.”
- “14 year old launches product after fully vibe coding with no development experience”
It’s a familiar fear, and definitely not an irrational one. Generative AI can already write code, generate test cases, and create documentation faster than most of us ever could. Whilst this enables a previously out of reach capability to general public, its not too much of a leap to wonder why would we then need developers at all?
The villain is real, but maybe it’s been miscast. If you look closer, AI isn’t actually evil but rather it’s a mirror, reflecting the parts of our work we’ve allowed to become mechanical. The parts that no longer demand creativity, judgment, or empathy. That realisation was uncomfortable for me to admit, and perhaps too for others, especially for those for us who have built careers on mastering complexity. But the truth is, what’s being automated first isn’t our mastered skills, it’s our repetition. The real danger isn’t AI replacing developers. It’s developers not reimagining what their role could become when the repetitive tasks disappear.
Imagine a world where your coding assistant writes the test scaffolding and documentation, freeing you to focus on architecture, human experience, and innovation, the higher-level decisions that move a company forward. That’s not a demotion, that’s evolution. We can’t predict exactly what the “developer of the future” will look like, but we can shape it. The developers who thrive won’t be the ones defending the old way of working, they’ll be the ones using AI as leverage to expand their impact.
The story we tell ourselves matters. If we keep casting AI as the villain, we’ll keep acting like victims. But if we reframe it as a powerful (and occasionally unruly) sidekick, the hero’s journey starts to look very different.
Shift in Perspective
For leaders, this is where vision becomes non-negotiable. Your team looks to you for orientation and a sense of direction in the fog. When the narrative around AI becomes fear-based, our role is to rewrite it, and to help the team see what’s possible beyond the headlines.
Leaders must frame AI not as a threat to identity, but as a catalyst for reinvention, a tool that elevates human creativity rather than erases it. That requires both empathy and conviction: acknowledging the fear while still pointing toward the horizon. We deal with uncertainty every day, that is the job, therefore our responsibility is to guide our teams to make the unknown achievable.
Practical Takeaways
If you’re leading through this transition, start here:
- Lead through discomfort: Your role as a leader isnt too remove all challenges for your team, but to guide them through or around them. Discomfort is often where growth happens
- Experiment in public: Try AI tools yourself and share what you learn. Your transparency will create safety for others to follow. I started by introducing Devin.ai to the team by leveraging the Wiki feature first. This helped ask some questions of our codebase.
- Find allies: Create a small coalition of curious people inside your company who can model the change. A follow on from the point above, one of the key developers saw they could also ask questions and get good answers, so they started saying how good it was and sharing
- Make it fun: Create a competition of who can submit the most AI code, or the most creative idea.
- Build light governance Write simple AI guidelines that encourage exploration while protecting trust and privacy. An AIA Lite governance that fosters trialling with enough governance to avoid the biggest risks in your particular domain.
Closing / Call to Reflection
The paradox of leadership in the AI era is that the more we try to control, the more we slow down the very innovation we’re trying to enable. Instead, our focus should be on creating systems that can change safely, clear principles, transparent goals, and empowered teams who know why their work matters.
When we let go of control, we gain something far more valuable: adaptability. Teams learn faster, experiment more confidently, and produce insights that no single leader could have predicted.
AI is forcing this shift whether we’re ready or not. The leaders who thrive won’t be the ones who tighten their grip, they’ll be the ones who reframe leadership itself.
Leadership in the AI era isn’t about controlling complexity; it’s about cultivating capacity. Our job is to grow teams who can think, adapt, and lead alongside us, even when the future is uncertain.