The field of software development and automation is witnessing a significant shift towards leveraging artificial intelligence (AI) and large language models (LLMs) to enhance efficiency, accuracy, and innovation. Recent developments indicate a strong focus on automating tasks such as report generation, software architecture description, and code creation, aiming to reduce manual effort and improve maintainability. The integration of LLMs with other technologies like graph-based retrieval and semantic knowledge graphs is opening up new avenues for improving the quality and reliability of generated content. Furthermore, the application of AI in areas like geotechnical reporting, board game programming, and pediatric speech-language pathology is showcasing the versatility and potential of these technologies. Noteworthy papers in this area are proposing novel methodologies and tools that demonstrate significant advancements in automated software development and AI-driven automation. For instance, some studies highlight the effectiveness of LLMs in generating high-quality software architecture descriptions and code, while others focus on developing specialized chatbots for digital adoption platforms and creating innovative solutions for the automatic digitization of gas plants. Overall, these advancements are poised to transform the landscape of software development and automation, enabling faster, more accurate, and more innovative solutions across various domains.