The piece argues that the cost of building software has dramatically decreased, potentially by as much as 90%, due to advancements in AI coding tools, specifically agentic coding. The author, who has nearly two decades of experience in software development, recalls how the landscape has changed from expensive licenses for databases to the complexities of modern software engineering. He emphasizes that while traditional development has become labor-intensive with practices like TDD and microservices, AI tools can now streamline the process significantly. For instance, a project that might have taken a month can now be completed in a week, thanks to AI effectively handling tasks like generating test suites and writing APIs. The discussion also touches on the economic implications of these changes. Drawing from Jevons Paradox, the author suggests that as software becomes cheaper to produce, demand will increase. Many organizations that have relied on cumbersome Excel sheets could benefit from software solutions that are now more affordable. The author highlights that the true value lies in domain knowledge and human oversight, as AI tools still require guidance to ensure quality. A skilled developer, paired with these tools, can address business challenges efficiently, leading to a faster, more iterative development process. Concerns about AI's reliability, particularly its accuracy and ability to handle legacy code, are acknowledged but countered with examples of how AI can enhance productivity. The author encourages engineers to embrace this shift, especially within smaller organizations that can adapt quickly. He warns that those who resist change may find themselves left behind, much like past technology transitions. Overall, the potential for AI in software development is substantial, and the pace of change is likely to escalate leading up to 2026.