AI Engineering Is Easy. Changing How We Work Is Hard

The integration of AI into software development is shifting the focus from mere coding to the entire engineering lifecycle. While AI tools can now assist with requirements, architecture, and validation, the author argues that the real challenge lies in adapting human workflows. Current development processes often suffer from bottlenecks like unclear requirements, oversized tickets, and inefficient handoffs between product, UX, and engineering teams. To truly benefit from AI, teams must move toward iterative collaboration and better-structured documentation that allows agents to navigate systems effectively. The author suggests that an 'AI harness'—an environment encompassing how work is defined, organized, and validated—is more critical than the AI models themselves. Ultimately, the speed of development will not be determined by the AI's ability to write code, but by our ability to refine the organizational processes that surround it.