Part 15/16:
Martin Fowler’s insights underscore that AI’s impact parallels the historic shift from assembly to high-level languages—a leap requiring new mental models and workflows. While many practices will evolve, core principles like clarity, learning, and human oversight remain vital.
As we stand at this inflection point, embracing tighter feedback loops, robust abstractions, and continuous learning will be crucial for navigating a landscape of non-deterministic, AI-augmented systems.