AI will automate the flow of information and context, a traditional management function. This frees managers to focus on higher-level work: designing how work gets done and coordinating the roles and responsibilities between human team members and AI agents.

As AI tools become operable via plain English, the key skill shifts from technical implementation to effective management. People managers excel at providing context, defining roles, giving feedback, and reporting on performance—all crucial for orchestrating a "team" of AI agents. Their skills will become more valuable than pure AI expertise.

AI tools disproportionately amplify the productivity of top performers, making them exceptional. A manager's highest leverage activity is to focus the majority of their time on unblocking and supporting these individuals to maximize the team's overall output.

Top-performing engineering teams are evolving from hands-on coding to a managerial role. Their primary job is to define tasks, kick off multiple AI agents in parallel, review plans, and approve the final output, rather than implementing the details themselves.

An effective engineering manager acts like the support team in an operating room. Their primary role is to empower their top engineers (the "surgeons") by looking around corners, anticipating organizational hurdles, and having solutions ready before they are even asked.

The most critical skill for founders and engineers is now managing large numbers of AI agents effectively. This requires new organizational paradigms, like using prioritized folders (P0, P1, Bugs) and other management techniques, mirroring how executives manage large human teams.

The role of a top engineer is shifting from writing code to orchestrating multiple AI agents simultaneously. Notion's co-founder now queues tasks for AIs to work on while he's away, becoming a manager of AI talent rather than just an individual contributor, dramatically multiplying his leverage.

High-achieving managers delegate 32% more coordination work to AI, not to replace management but to eliminate administrative tasks. This frees them up for high-value work like coaching, which in turn doubles their team's trust in using AI for sensitive decisions like performance reviews.

AI lowers the activation energy for managers to contribute code. They can now easily fix bugs or make optimizations without taking on critical projects. This keeps them technically sharp, helps the team, and reduces burnout from administrative "paperwork."