Steven Sinofsky argues that the current wave of AI transformation in software development mirrors past technological shifts but differs fundamentally. He reflects on three significant transitions: the rise of personal computers and graphical interfaces, the evolution of retail, and the media industry's evolution. Each shift faced skepticism about its potential to replace existing systems, yet they all resulted in larger ecosystems than anyone anticipated. For instance, the prediction that PCs would eliminate mainframe computing proved wrong; instead, the installed base of PCs surged from under 100 million to nearly 1 billion, leading to an expansion of data centers rather than their demise. Sinofsky highlights that despite the narrative around AI, the demand for software is increasing, not decreasing. He emphasizes that historical fears of technological obsolescence—like the supposed death of retail—were overstated. Retail has continually evolved through various formats, from standalone stores to online giants like Amazon. Many companies adapted successfully, while others, like Sun and Lotus, failed. In media, the rise of streaming platforms like Netflix reshaped consumption patterns, leading to a proliferation of content and the emergence of new business models, even as traditional media struggled. The article illustrates that while these transitions may seem disruptive, they often result in a more complex and robust landscape. Companies that adapt creatively thrive, while those that cling to outdated models risk obsolescence. Sinofsky’s insights remind us that technological change is a journey, not a moment, and that understanding these patterns can inform our approach to the future of software and business.