Amanda Du Toit 9/9/25 Amanda Du Toit 9/9/25

Prompts & People: Leading Engineering Teams Through Change

AI in engineering has brought both promise and pressure. Leaders know they can’t afford to ignore it but integrating smoothly into a team enviroment is a bigger challenge than you think.

by Amanda Du Toit - Search Partner

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.

People & Prompts: Why AI Pilots Are Failing, and Sales Still Needs Humans

Despite the hype, 95% of generative AI pilots fail to deliver ROI. The problem? Companies are playing it too safe—testing AI in low-impact areas like marketing emails and chatbots, where people actually matter most.

By Darrell Bowman, Search Partner

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

A recent study from MIT found that 95 percent of generative AI pilot projects in companies are failing to deliver meaningful results. Despite all the hype, most organizations are struggling to generate ROI from their AI investments. The problem isn’t the technology itself. It’s where and how companies are choosing to deploy it.

Companies are hesitant to integrate AI into mission-critical systems like accounting, logistics, or compliance. These areas are deeply embedded, high-risk, and expensive to change. Many have already undergone complex transformations to reach their current state. The memory of those difficult transitions, including layoffs, budget overruns, and operational disruptions, makes teams understandably cautious. When something works, no one wants to be the person who breaks it.

Instead, organizations are piloting AI in low-risk, low-impact areas, especially in sales and marketing. They test it in places where mistakes won’t affect existing customer relationships or operations. This usually means top-of-funnel activities like outbound emails, prospecting bots, or basic customer service interactions. These are safe zones. But ironically, they are also the places where people matter most.

AI might be able to write an email or answer a question, but the top of the funnel is where trust is built. First impressions still matter, and clumsy automation does more harm than good. It’s one thing to get ignored by a prospect. It’s another to be dismissed because you sounded like a robot.

Here’s the deeper issue: AI is designed to give the safest, most statistically probable answer. It works by identifying patterns across large data sets and selecting the response that best reflects the center of the distribution. But new ideas, especially the ones that are truly innovative or high-impact, don’t come from the center. They live in the long tail, in the edge cases and outliers. This is where humans thrive.

Great salespeople don’t just repeat what’s worked before. They challenge assumptions, read between the lines, and pick up on the subtle cues that signal an opportunity. They hear what’s not being said. They pivot in the moment. And they do it all in real time. These are not tasks that can be easily scripted or automated. They require emotional intelligence, strategic thinking, and situational awareness. These are skills that AI simply doesn’t possess.

Marketing is no different. The best campaigns aren’t generated by prompts. They come from deep human insight: understanding the buyer’s psychology, identifying hidden motivations, and knowing when to break the rules. AI can be a useful assistant, but it cannot originate strategy. It can remix ideas, but it cannot generate new ones with context and meaning.

Now that the economy is showing signs of contraction, some leaders are eyeing AI as a way to cut costs. Scaling back on people and betting on automation instead may sound efficient, but it’s a dangerous bet. Cutting your top-of-funnel team and replacing them with a prompt stack is like firing your best players and handing the game plan to an intern with a spreadsheet.

AI is a tool. It can help with efficiency, summarization, and scale. But it cannot replace the strategic advantage of a strong human team, especially in sales, marketing, and customer engagement. If 95 percent of pilots are failing, that’s not a technology problem. That’s a deployment problem. It is often a leadership problem too.

As you plan your next move, ask yourself: Are you using AI to support your people, or to replace them? Are you trying to eliminate complexity, or understand it better? The companies that win in this next cycle won’t be the ones who automate first. They will be the ones who know when not to.

Because when it comes to building trust, spotting opportunity, and creating real customer value, people still outperform prompts. Every time.

Feel free to share your thoughts with me via email