AI is reshaping the software industry, making code production rapid and inexpensive. As a result, the focus is shifting from writing code to decision-making and operational management. Large software teams, once necessary due to the complexity and cost of development, are now losing their justification. The era of cheap capital encouraged companies to hire aggressively, leading to bloated teams and a drop in talent density. With software becoming easier to produce, the incentive to maintain large teams for coordination is weakening. As competition intensifies and feature parity becomes easier to achieve, companies face dwindling margins. Those that cling to outdated structures designed for a costly production environment risk internal disruption. Smaller teams are likely to become the norm, with a focus on agility and efficiency. This shift could streamline hiring processes and reduce compensation expectations, particularly for roles that are easier to fill. However, as teams take on broader responsibilities, the risk of operational failures increases, necessitating stronger governance and oversight. The concept of disposable software is gaining traction. For internal tools and experiments, low expectations of longevity make it acceptable to prioritize low costs over long-term maintenance. Software that deals with critical aspects like money or safety requires ongoing investment and attention to avoid accumulating technical debt. The next wave of disruption is expected to come from collaborations between software engineers and industry experts who can rethink workflows fundamentally. This partnership model could transform traditional sectors like law and healthcare, where existing processes are often bogged down by inefficiencies. AI tools are not just an add-on; they can fundamentally change how work is structured and delivered.