Collaborative software development, whether synchronous or asynchronous, is a creative, integrative process in which something new comes into being through the joint engagement, something new that did not fully exist in the mind of any one person prior to the engagement. One can view this engagement from a macro-level perspective, focusing on large scale development efforts of 100 or more developers, organized into sub-teams, producing collections complex software products like Mozilla. Past work in the area of software engineering has explored the symbiosis between the management structure of a software team and the module structure of the resulting software. In this talk, we focus instead on small scale software teams of between 2 and 5 developers, working on smaller-scale efforts of between one hour and 9 months, through more fine grained analysis of collaborative processes and collaborative products. In this more tightly coupled engagement within small groups, we see again a symbiosis between people, processes, and products. This talk bridges between the field of Computer-Supported Collaborative Learning and the study of software teams in the field of Software Engineering by investigating the inner-workings of small scale collaborative software development. Building on over a decade of AI-enabled collaborative learning experiences in the classroom and online, in this talk we report our work in progress beginning with classroom studies in large online software courses with substantial teamwork components. In our classroom work, we have adapted an industry standard team practice referred to as Mob Programming into a paradigm called Online Mob Programming (OMP) for the purpose of encouraging teams to reflect on concepts and share work in the midst of their project experience. At the core of this work are process mining technologies that enable real time monitoring and just-in-time support for learning during productive work. Recent work on deep-learning approaches to program understanding bridge between investigations of processes and products.