As AI automates entry-level knowledge work, human roles will shift towards management. The critical skill will no longer be doing the work, but effectively delegating to and coordinating a team of autonomous AI agents. This places a new premium on traditional management skills like project planning and quality control.

As AI evolves from single-task tools to autonomous agents, the human role transforms. Instead of simply using AI, professionals will need to manage and oversee multiple AI agents, ensuring their actions are safe, ethical, and aligned with business goals, acting as a critical control layer.

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.

The process of guiding an AI agent to a successful outcome mirrors traditional management. The key skills are not just technical, but involve specifying clear goals, providing context, breaking down tasks, and giving constructive feedback. Effective AI users must think like effective managers.

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.

The adoption of powerful AI agents will fundamentally shift knowledge work. Instead of executing tasks, humans will be responsible for directing agents, providing crucial context, managing escalations, and coordinating between different AI systems. The primary job will evolve from 'doing' to 'managing and guiding'.

Instead of asking an AI for a single answer, Reid Hoffman advocates for "role prompting"—creating a team of AI agents with different expert perspectives (critic, historian, etc.). This simulates a board of advisors and represents a shift from individual contribution to managing AI teams.

The next frontier in AI is not just developing individual agents, but orchestrating teams of them. Users will move from dialoguing with a single chatbot to managing multiple agents working in parallel on complex, long-running workflows. This becomes a new core skill for knowledge workers.

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.