The author reflects on how the landscape of software development has shifted dramatically, particularly with the rise of large language models (LLMs). Previously, the ability to execute an idea was what differentiated skilled software developers from mere dreamers. After spending 15 years in coding, the author notes that this distinction is collapsing. During a recent break, they built three fully functioning tools using AI assistance, highlighting how quickly ideas can now be turned into products. The ease with which LLMs can generate code has made traditional skills feel less valuable. The author expresses both nostalgia for the past, when coding required deep understanding and significant effort, and excitement about the new possibilities. They emphasize that while execution is no longer the key differentiator, new priorities have emerged. Speed of iteration, taste in product selection, and effective distribution have become crucial. With the proliferation of tools that enable rapid development, the most successful teams will be those that quickly learn from user feedback and adapt. The core challenge now lies in identifying the right problems to solve, as the barrier to building software has lowered significantly. This shift means that the role of a software engineer is evolving. The skills that once defined value in the field are changing, and the ability to write code may no longer be enough. Instead, the focus will be on problem selection, networking for distribution, and making informed judgments about what should be built. The author concludes that the essence of software development is now more about strategic thinking and rapid adaptation than the technicalities of coding itself.