“AI is not just another tech trend. It’s a new way of thinking about how work gets done.”
— Satya Nadella, CEO of Microsoft
My Approach to AI Leadership in Engineering (2023–2025)
AI isn’t just a shiny new tool or an optional experiment—it’s a skill every member of our product and engineering teams needs to build. That includes not just our software engineers, but also our Agile Delivery Managers and Quality Assurance team members. Whether the output is fully accurate yet isn’t the main issue. What matters is that we start learning how to use it now.
Smart adoption and experimenting with AI is key to staying relevant and competitive—not just as individuals, but as a team. It’s about building fluency, not waiting for perfection.
My goal is simple:
I want to see 80% of our developers actively using AI through one or more of the following:
- Code Assist – fully operational
- Code Review – fully operational
- Coding Agents – early experimentation
But this isn’t just about developers.
- Agile Delivery Managers should begin exploring how AI can assist in backlog refinement, sprint planning insights, dependency detection, or summarizing standups and team health signals.
- Quality Assurance team members can begin using AI to suggest test cases, identify potential risk areas, and even support automated test generation and exploratory test planning.
AI is advancing quickly, and so must we. Early results are promising: two weeks of work done in two days, with solid quality. Engineers still played a key role, correcting AI output and removing unwanted changes. Even with oversight, this isn’t just a productivity boost—it’s a shift in how we deliver value.
But the real value isn’t just in what AI does—it’s in how we learn to work with it. That means:
- Learning which prompts produce the best results
- Recognizing and correcting hallucinations
- Knowing when to accept or reject suggestions
- Committing frequently to maintain control
- Respecting governance, IP, and data privacy boundaries
This isn’t about perfect adoption—it’s about steady progress.
Even if the tools aren’t flawless, our people can be empowered with the mindset and muscle memory to use them wisely.
I believe the key to leading in the AI era is through practical experimentation, continuous learning, and thoughtful implementation—not hype. This is not just about how AI fits into our work today, but how we build the adaptability and fluency to thrive in whatever comes next.
“AI won’t replace your team—but the teams who learn to harness AI will outpace those who don’t. Our job as leaders isn’t just to adopt the tools—it’s to build the fluency and mindset that make transformation possible.”
— Phil Clark, VP of Technology