Prompts & People: Leading Engineering Teams Through Change

Sep 9

Part of our “People & Prompts Series” about the impact of AI in the workplace and the future of work.

The surge of AI in engineering has brought both promise and pressure. Most leaders know they can’t afford to ignore the technology - but that doesn’t mean it will integrate smoothly into their teams.

In fast-moving environments, even strong engineering cultures can feel stretched. Communication patterns fray. Productivity fluctuates. Teams wrestle with increasing complexity and unclear expectations. And when a new layer like AI enters the picture, it can quietly magnify the existing signals.

This isn’t a crisis - it’s a turning point. How you lead through it makes all the difference.

The Human Side of AI

AI doesn’t slot neatly into existing workflows. It reshapes how work gets done. And that shift can stir uncertainty, even among high-performing teams. Engineers may wonder how their roles will evolve. Some will lean in with curiosity; others may hold back, unsure of what it all means.

That’s why the real challenge isn’t just technical enablement. It’s human alignment.

Leadership teams who succeed in navigating this shift don’t just roll out tools. They bring clarity, context, and confidence. They create space for learning. They communicate why AI is being introduced - and how it complements the team’s existing strengths rather than threatening them. Research shows that when leadership articulates a clear AI vision, employees are 1.4× more likely to feel management communicates a clear future [1].

The result is not just adoption, but engagement.

When engineers see AI as a way to unlock creativity - by automating repetition and freeing up time for deeper problem solving - it becomes a force multiplier, not a point of tension. Microsoft found that 90% of developers using AI tools report greater productivity, and 80% said they would be disappointed if those tools were taken away [2].

Culture Shapes the Outcome

Technical change, on its own, doesn’t improve velocity or innovation.

It’s how teams respond to that change that defines the outcome.

Startups and growth-stage companies understand this intuitively. They’ve seen how clarity, trust, and shared purpose can create momentum, and how quickly misalignment can slow everything down. Atlassian’s 2025 DevEx report highlighted that while developers saved over 10 hours a week using AI, they lost nearly the same amount due to communication breakdowns and organizational inefficiencies [3].

In this context, tools are important. But behavior and mindset still do the heavy lifting.

Even the best systems won’t help if curiosity, humility, and collaboration aren’t present on the team. And as AI accelerates the pace of development, those qualities become even more important, not less.

That’s where leadership and hiring intersect. It’s not just about who can code. It’s about who can adapt.

The Leadership Imperative

Engineering leaders today are being asked to do two things at once:

Adopt AI in meaningful ways, and keep their teams confident, curious, and focused.

That balance isn’t easy, but it’s where great leadership shows up.

The CTOs who navigate this well won’t be the ones who deploy the most tools the fastest. They’ll be the ones who shape teams that are resilient, self-directed, and motivated to grow. Teams that understand how to apply AI in context. Teams that know when to automate and when to lean in. Teams that trust each other enough to change together.

Because in the end, AI can accelerate a good team, but it can’t create one.

Call to Action

If you're thinking about how to integrate AI into your product, process, or team, start by asking: Do we have the right people - not just to implement AI, but to make it great?

That’s the question that will separate those who scale sustainably from those who stall.

If you would like to start a conversation, please send me an email.