The paper "Future of Software Development with Generative AI" by Jaakko Sauvola, Sasu Tarkoma, Mika Klemettinen, Jukka Riekki, and David Doermann explores the impact of generative AI on software development. The authors highlight that generative AI, with its rapidly expanding capabilities, is a significant disruption in the field, offering opportunities in creative dimensions and automating repetitive tasks. They propose four primary scenarios for future software development paths: Traditional Software Development Operations (S1), AI in Loop (S2), AI Assumes Role(s) (S3), and Human-in-the-Loop (S4). Each scenario reflects different levels of automation and human-AI interaction. The paper analyzes these scenarios in the context of different Software Development Organizations (SDOs), including legacy systems, clean slates, networked applications, and special SDOs. It discusses the potential benefits, such as increased productivity, resource optimization, and cost savings, as well as challenges and ethical considerations, including job displacement, intellectual property issues, and cybersecurity. The authors emphasize the need for guidelines and continuous education to adapt to the evolving landscape of software development with generative AI.The paper "Future of Software Development with Generative AI" by Jaakko Sauvola, Sasu Tarkoma, Mika Klemettinen, Jukka Riekki, and David Doermann explores the impact of generative AI on software development. The authors highlight that generative AI, with its rapidly expanding capabilities, is a significant disruption in the field, offering opportunities in creative dimensions and automating repetitive tasks. They propose four primary scenarios for future software development paths: Traditional Software Development Operations (S1), AI in Loop (S2), AI Assumes Role(s) (S3), and Human-in-the-Loop (S4). Each scenario reflects different levels of automation and human-AI interaction. The paper analyzes these scenarios in the context of different Software Development Organizations (SDOs), including legacy systems, clean slates, networked applications, and special SDOs. It discusses the potential benefits, such as increased productivity, resource optimization, and cost savings, as well as challenges and ethical considerations, including job displacement, intellectual property issues, and cybersecurity. The authors emphasize the need for guidelines and continuous education to adapt to the evolving landscape of software development with generative AI.