The growth of Web 2.0 and fundamental theoretical breakthroughs have led to an avalanche of interest in social networks. This paper focuses on the problem of modeling how social networks accomplish tasks through peer production style collaboration. We propose a general interaction model for the underlying social networks and then a specific model (iLink) for social search and message routing. A key contribution here is the development of a general learning framework for making such online peer production systems work at scale. The iLink model has been used to develop a system for FAQ generation in a social network (FAQtory), and experience with its application in the context of a full-scale learning-driven workflow application (CALO) is reported. We also discuss methods of adapting iLink technology for use in military knowledge sharing portals and other message routing systems. Finally, the paper shows the connection of iLink to SQM, a theoretical model for social search that is a generalization of Markov Decision Processes and the popular Pagerank model.