Coding Agents Don't Scale Themselves. Neither Do Your Teams. — Patrick Debois, Tessl

Organizational success in the era of autonomous AI agents requires shifting from individual developer workflows to shared, system-level strategies. Rather than focusing on solo prompt engineering, teams should prioritize building robust harnesses, reusable context, and modular tooling that minimize human intervention. Platform teams play a critical role by establishing "paved paths"—standardized, secure, and testable components—that prevent sprawl and enable organizational scaling. Measuring success moves beyond simple productivity metrics to tracking the reduction of human touches and the multiplier effect of shared system improvements. Ultimately, transitioning to an autonomous "dark factory" model demands a cultural shift toward continuous learning, where engineering practices like testing, documentation, and rigorous planning remain essential to maintain reliability while accelerating delivery.