AI compresses teams, turning managers into hybrid roles where coordination, purpose setting and process design fall to high-agency individuals; leaders must balance stability and flexibility while using AI tools for communication and decision-making.
The core insight is that AI is shrinking team layers, so the traditional manager role collapses into a hybrid where individual contributors must pick up coordination, purpose definition, and process design. The headcount shrinks but the need to manage work stays, forcing a shift of management levers-purpose, people, process-onto anyone who can act.
The article breaks down those three levers. Purpose becomes an explicit prompt for AI, requiring clear success metrics. People turn into model selection, matching the quirks of different AI systems to tasks. Process evolves into prompt engineering and evaluation pipelines, where you trust the output but verify it with structured checks.
Practical examples show AI drafting direct-yet-kind scripts for tough conversations, generating exec-level summaries, and role-playing feedback sessions. These tools let leaders spend less time on rote communication and more on strategic alignment, while also giving individual contributors a way to self-coach.
At the same time, the piece warns that the human side of leadership is harder than ever. Leaders must stabilize anxious teams, showing both confidence and vulnerability, because the rapid change can trigger cynicism. Balancing steadiness with flexibility becomes the most important skill in this AI-augmented era.
The timeless part of management-setting purpose, building trust, helping people grow-remains, but the mechanisms shift. High-agency individuals equipped with AI can fill gaps left by fewer pure managers, turning the organization into a fast-moving improv where roles blur and the focus stays on outcomes.
Check out the full stdlib collection for more frameworks, templates, and guides to accelerate your technical leadership journey.