Managing software development teams across time zones has become standard practice for many tech companies. With tools advancing rapidly, especially in AI, new challenges and opportunities are reshaping how leaders approach distributed team management. John Campbell Crighton has spent years overseeing teams of more than 100 developers scattered around the globe, implementing cutting-edge solutions while maintaining essential human connections.
Clear Communication Drives Remote Success
When asked about his number one rule for maintaining cohesion in distributed teams, John doesn’t hesitate. “Good communication is the number one thing,” he says. His teams rely heavily on video conferencing and AI-enabled code tracking tools to keep everyone aligned despite physical distance.
Software development priorities shift frequently, making consistent communication crucial. “Priorities can change pretty often depending on the requirements of the organization,” John explains. He emphasizes keeping team members informed about changing needs, tracking progress, and addressing potential roadblocks before they derail projects. This transparent approach helps maintain momentum even when teams can’t meet face-to-face.
Balancing AI Automation with Human Touch
John’s teams have embraced AI for streamlining DevOps, but not without careful consideration. “Most of our AI agents have been carefully calibrated and tested before they’re made live,” he notes. Their process includes extensive logging to track AI-driven changes, with regular human reviews to ensure quality control. This approach allows his teams to automate routine tasks without sacrificing oversight. “We’re taking away the immediacy of the need for human involvement,” John says. “The environment is being maintained more efficiently with less human resources.” Rather than replacing people, AI helps them focus on higher-value work that requires human judgment and creativity.
John takes a practical approach to staffing distributed projects. “A lot of the work we do with talent is with agencies. They’re bringing us whole teams versus individuals,” he shares. This strategy simplifies recruitment while providing ready-made teams that already work well together. The key to success with this model lies in thorough onboarding. New teams must quickly adapt to established processes and communication patterns. “We need all our teams to follow the same processes for tracking purposes and for maintaining a predictable result,” John explains. Consistent methodologies create a foundation for success, regardless of where team members are located.
Managing Tech Resources in the AI Era
Like most technology leaders, John constantly balances maintaining existing systems with investing in emerging technologies. He sees generative AI as simply another tool in this ongoing juggling act. “Gen AI is just a new technology that’s enabling us to move a lot quicker,” he explains. While the tools are evolving rapidly, the fundamental challenge remains the same – determining where to focus limited resources for maximum impact. John’s teams continuously evaluate how AI can reduce manual effort while improving outcomes for clients.
Working in health tech brings additional considerations around AI implementation. John acknowledges the technology’s limitations based on training data limitations. “The main ethical considerations are that Gen AI tools have been trained on a very limited subset of data,” he points out. His team addresses potential biases through a governance board that reviews AI outputs. They also compare results across different AI platforms to identify the best tools for specific needs. “We’re working through that with a governance board that reviews the responses coming out of Gen AI to make sure biases we become aware of are notated,” John says. This careful approach helps protect patients while leveraging AI’s advantages.
Learning from Team Performance Challenges
Even experienced leaders face occasional team performance issues. John relies heavily on metrics to spot problems quickly. “We monitor everything via KPIs so you understand the expected outcome versus what you’re getting,” he explains.
In one recent situation, his team noticed performance declining after a vendor changed project managers. By addressing this directly with senior management, they resolved the issue within two sprint cycles. “You have to be aware of team dynamics and how somebody who’s not the right fit can have a big impact on output,” John notes. No amount of technology can replace this human awareness. For John, the ultimate goal with AI isn’t replacing people, but enhancing their capabilities: “We’re focusing on taking away the scud work nobody is excited about and getting people focused on doing the creative work that most developers enjoy more to begin with.”
Connect with John Campbell Crighton on LinkedIn to explore more of his leadership insights.
