As one of the next frontiers of software engineering, agile development at scale has attracted more and more research interests and efforts. When following the existing autonomy-focused and goal-driven lessons and guidelines to scale agile development for a large astronomy project, however, we encountered surprising tech stack sprawl and spreading team coordination issues. By revisiting the unique features of our project (e.g., the data processing-intensive nature and the frequent team member changes), and by identifying a fractal pattern from various data processing logic and processes, we defined disciplined agile teams to clone the best practices of pioneer agile teams, and to work on similar system modules with similar user stories. Such a targeted strategy effectively relieved the tech stack sprawl and facilitated teamwork handover, at least for refactoring and growing the data processing modules in our project. Based on this emerging result and our reflections, we distinguish this targeted strategy as scaling out agile development from the existing agile scaling approaches that are generally in a scaling-up fashion. Considering the popularity of data processing-intensive projects, and also considering the pervasive fractal patterns in modern businesses and organisations, we claim that this targeted strategy still has broad application opportunities. Therefore, developing a well-defined methodology for scaling out agility, and combining both scaling up and scaling out agility, will deserve attentions and new research efforts in the future.