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."

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.

According to Goldman's CIO, working effectively with AI agents requires skills traditionally associated with managers: the ability to clearly explain goals, delegate tasks, and supervise output. This is fundamentally changing the talent profile companies need to hire.

Successfully using AI agents is less about technical skill and more about applying management principles. Scoping roles, providing clear instructions, establishing communication protocols, and building trust progressively are the same skills needed to manage human employees. This "manager's mindset" unlocks agent potential.

The principles AI requires, such as breaking work into discrete tasks, are not revolutionary; they are foundational management concepts. AI simply makes these practices mandatory, exposing companies with poor management structures that previously relied on giving human employees vague mandates.

The most significant change AI brings to management is not tool proficiency. It's the shift to becoming a governance actor who must interpret machine outputs, ensure procedural fairness, challenge unreliable recommendations, and explain decisions, acting as the human interface for algorithmic systems.

'AI Slop' flourishes when leaders don't explicitly define what 'good' looks like. This failure, combined with decentralized tool usage and a lack of a central source of truth, allows low-quality, AI-generated work to become the default standard within an organization.

As AI democratizes technical capabilities, competitive advantage will no longer come from superior technology. Instead, it will come from superior management: building strong teams, making quality decisions, and running operations well. Fundamentals become the key differentiator when technology is a commodity.

AI is bifurcating managers into two groups: 'deep craftspeople' who scale their expertise, and 'context carriers' who just move information. AI automates the latter's role, revealing their lack of craft and making them the primary source of low-quality 'AI slop.'