AI Engineering Manager in 2027: How to Lead 20+ People With No Burnout

Your teams adopted AI and got faster. Your calendar did not. An engineering manager I mentor went from 8 people in one team to 26 in three teams between 2025 and 2026, on the same hours. His teams shipped about 30% faster; his double-booked hours went up 2.5x. The bottleneck moved from writing code to coordination, and the manager is the coordination. The talk walks through what he changed: the four routines he repeated every week (chasing status, collecting context, spotting risk, preparing 1:1s), the question he asked about each one (which part can AI do, which part needs me), and the roughly 100 plain-English rules he wrote down so a script could apply them. The script runs every four hours. AI gets called only where judgement is needed. Anything that touches people waits for his yes. We also cover the afternoon Claude rebuilt his 26 recurring 1:1s and one report's agent complained to his agent.

You walk out with the first AI management workflow to try next week (pick one repetitive task, write how you decide it as 3 to 5 rules, let AI apply them, fix the rules where it is wrong) and with the career-fork table from my 2027 post, so you can see which of the three manager shapes you are already drifting toward.

Most talks about AI and management stop at tools: here is Copilot, here is a prompt for your status update. This one starts from a manager's week and the number that changed it: 2.5x more double-booked hours after his teams got 30% faster. It is the story of an engineering manager I mentor, told with his numbers, and I add what I see in mentoring: the same coordination squeeze in the calendars of the 300+ leaders I have worked with, whatever the company.

Built for engineering managers whose span went up this year and whose hours did not. As a keynote it covers the routines, the rules and the two things that broke. As a workshop every manager leaves with their own first rule file written, for one task they do every week.