The anxiety is real. I've heard it in one-on-ones, in retrospectives, in the quiet conversations after meetings. Engineers who've spent years building expertise are watching AI tools do in seconds what used to take them hours, and they're wondering: how long until it does everything I do?

Some leaders dismiss this anxiety as irrational. "AI is just a tool," they say. "It'll make you more productive, not replace you." That's probably true in the medium term, but dismissing the concern doesn't make it go away, it just teaches people not to voice it. And unvoiced anxiety doesn't disappear. It festers into disengagement, resistance to AI adoption, and quiet job searching.

Having the Honest Conversation

The honest conversation starts with acknowledging what's true: AI is changing what engineering work looks like, and some of the tasks that engineers currently do will be automated. That's not speculation, it's already happening with boilerplate code generation, routine testing, and documentation.

But it's equally honest to say: the tasks being automated are generally the least interesting parts of the job. The parts that require judgement, context, creativity, and human understanding, system design, problem framing, debugging complex interactions, understanding user needs, are not close to being automated. And the demand for people who can do those things well is increasing, not decreasing.

The framing that's worked best for me is: AI is changing what we do, not whether we're needed. The engineers who adapt, who learn to work with AI tools, who develop the skills that AI can't replicate, who focus on the judgement and context that make them valuable, will be more in demand than ever. The engineers who refuse to engage with AI tools will find themselves increasingly less effective relative to their peers.

That's honest without being dismissive, and it gives people agency rather than leaving them feeling helpless.

Investing in Reskilling

Honest conversations aren't enough on their own. If you tell your team that they need to develop new skills but don't invest in helping them do so, you've just added anxiety without providing a path forward.

Practical investments I've made:

Time for experimentation. Dedicated time, not "when you have a spare moment" but actual allocated time, for engineers to explore AI tools, experiment with new workflows, and share what they learn. This normalises AI adoption and reduces the fear of the unknown.

Skill development focused on AI-resistant capabilities. System design, architectural thinking, security analysis, user research, debugging complex distributed systems, these are the skills that AI augments rather than replaces. Investing in them is investing in your team's long-term value.

Pairing AI-enthusiastic engineers with AI-sceptical ones. Not to convert the sceptics, but to give them hands-on experience in a supportive context. The fear often diminishes significantly once someone has actually used the tools and seen both their capabilities and their limitations firsthand.

Transparent career conversations. Talking openly about how roles might evolve, what skills will be valued in the future, and how the organisation plans to support people through the transition. Uncertainty is less frightening when you're not facing it alone.

What Not to Do

Don't pretend nothing is changing. Your team can see the same headlines you can. Pretending AI isn't going to affect their work insults their intelligence and erodes trust.

Don't use AI as a threat. "If you don't improve your productivity, we'll just use AI instead" is a management failure. It creates fear rather than motivation, and it poisons the team's relationship with AI tools.

Don't make promises you can't keep. "Nobody's job is at risk" might not be true in the long term, and saying it when you're not certain damages your credibility. Better to say "I don't know exactly how this will play out, but I'm committed to investing in this team's development and navigating this together."

Don't ignore the emotional dimension. For many engineers, their technical skills are core to their identity. The suggestion that those skills might become less valuable is threatening at a deep level. Acknowledging that emotional reality, not just the practical one, matters.

The Leadership Responsibility

As a technical leader, you have a responsibility to your team that goes beyond quarterly delivery targets. You have a responsibility to help them build careers that are resilient to technological change. That means investing in their development, being honest about what's coming, and creating an environment where adapting to AI is seen as growth rather than surrender.

The engineers who come through this transition well will be the ones whose leaders took the time to guide them through it. Don't leave your team to figure this out alone.