Platforms like Nebula allow founders to move beyond simple automation. By providing a high-level directive and connecting services, AI agents can run entire business functions, like a content blog that researches, writes, and publishes daily with minimal human intervention.

The next wave of AI productivity won't come from crafting the perfect prompt. Instead, professionals must adopt a manager's mindset: defining outcomes, assembling AI agent teams, providing context, and reviewing their work, transforming everyone into an "agent orchestrator."

Shift your mindset from using AI as a tool for a specific function (e.g., a scheduler) to creating an AI agent as an employee who owns an entire outcome (e.g., 'run my marketing'). This changes the interaction from using software to delegating goals to an autonomous agent.

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.

Managing numerous AI agents is like managing a team of people, creating a single point of failure. This necessitates a new dedicated role, a "Chief Agent Officer," with a blend of technical and marketing skills to oversee operations, prevent system failure, and ensure continuity.

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.

The era of giving AI simple, discrete tasks like "write a blog post" is ending. To effectively use emerging agentic AI teams, you must shift to providing high-level outcomes, such as "develop a content strategy to grow our audience by 30%," and let the AI orchestrate the necessary steps.

Don't view AI tools as just software; treat them like junior team members. Apply management principles: 'hire' the right model for the job (People), define how it should work through structured prompts (Process), and give it a clear, narrow goal (Purpose). This mental model maximizes their effectiveness.

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.