A developer identified as Alberto Denia described a shift in software creation that emerged after November 2025. He noted that before this point, modifying code required significant effort akin to carving stone, where even minor adjustments often involved extensive rework. Larger changes demanded substantial planning and risk mitigation. Since then, the rise of agentic coding tools has altered this dynamic. These systems enable rapid iteration by allowing developers to generate, test, and refine code with minimal overhead. The cost of experimentation has dropped, making code more malleable. Denia compared this shift to working with clay rather than stone. With clay, initial structures can be shaped quickly, iterated upon, and restructured without the same constraints. This approach supports both exploratory development and large-scale refactoring. For instance, a developer might prototype a feature in a single session, test its functionality, and adjust based on real-time feedback. Similarly, teams could pivot entire product components within days, using automated checks to validate changes. The distinction between rapid prototyping and deliberate engineering remains critical. While the speed of iteration lowers barriers to experimentation, determining the right direction still requires careful analysis. Two primary workflows have emerged. One emphasizes continuous human involvement, where developers guide each iteration with contextual judgment. This method suits projects requiring nuanced design or user experience refinement. The other prioritizes automated systems that handle repetitive tasks, such as generating standardized code or enforcing quality controls. These pipelines operate with minimal human input, intervening only when predefined criteria are unmet. Both models retain human oversight but differ in timing and scope. Large-scale applications often blend these approaches, using automation for routine work while reserving creative problem-solving for complex challenges. The transition reflects a broader evolution in software development, where tools increasingly support flexible, adaptive workflows. Whether through iterative refinement or structured automation, the focus remains on balancing efficiency with intentional design. The implications extend beyond technical practice, influencing how teams approach problem-solving and innovation. As these tools mature, their integration will likely depend on aligning methodology with project goals.