From Code to Culture: How Engineers Move Into Leadership Without a Traditional Path

Pauline Jepp, an engineering leader, uses rock climbing as a lens for understanding what leadership really means—particularly for those who didn't follow the conventional career ladder into management.

The core insight surfaces early: climbing, though it feels like a solo pursuit, depends entirely on the person holding the rope. That dynamic—where trust enables risk-taking and experienced climbers offer small, well-timed suggestions rather than prescriptive solutions—mirrors the kind of engineering leadership she's built over her career across Canada, France, Scotland, and the Netherlands.

Moving Into Leadership Unconventionally#

Jepp didn't set out to lead. Like many strong engineers, she assumed she lacked the interpersonal skills for management and preferred talking to computers over people. Her journey started unexpectedly while working in smaller organizations where role boundaries were fuzzy and interesting problems could be picked up by whoever had capacity. There, she discovered that leadership isn't necessarily about titles—it's about thinking beyond the engineering problem itself to the system around it, including the people who enable that system to succeed.

Her approach challenges the notion that engineers must choose between technical depth and people leadership. Instead, she argues that pattern-matching, systems thinking, and the ability to debug code translate directly into understanding organizational dynamics.

Learning from Swarm Behavior#

Drawing on research from her PhD in multi-agent systems, Jepp maps flocking behavior onto engineering team dynamics. Flocking emerges from three simple rules:

• Separation: maintain autonomy so individuals don't crash into each other
• Alignment: move roughly in the same direction (strategy alignment)
• Cohesion: stick together through shared knowledge and psychological safety

Applied to an engineering department, these rules mean trusting engineers to make decisions, aligning teams around company goals, and building mentorship and psychological safety. As she notes, it's not about control—it's about tuning parameters to enable emergent behavior.

The One-Step Sell Flow Case Study#

A concrete example illustrates these principles at TicketSwap, the secondary ticketing marketplace where she works. When ChatGPT's image recognition capabilities matured in 2023, the team spotted an opportunity to let users sell tickets with zero manual data entry by extracting event details from photos automatically. The catch: the project was too exciting to wait for its natural owners (the sell-flow team), who were already committed to high-priority work. The buy-flow team had capacity.