Over the past 20 years, social network analysis (SNA) has transformed our conceptualization of crime and delinquency. Criminological theories that place the social factor front and center can now be tested with better data and measures, providing a more sophisticated demonstration of the mechanisms involved. Yet, the impact of SNA has arguably been felt the strongest in the field of gangs and organized crime, the focus of this talk. After all, gangs are a prime example of cooperative behavior under stressful conditions. The higher stakes involved in many gang crimes, and the requirement for continuity imply a higher need for secrecy and trust in one’s associates as a driver of action. The talk focuses on four lessons learned on gangs and networks, formulated as testable empirical statements: 1) Gang boundaries are messy but best measured via networks; 2) Gang members routinely work and interact with non-members. Yet, for high stakes crime, members select their own; 3) Gang cohesion matters for survival. Smaller gangs benefit from outside alliances while larger gangs benefit from keeping ties within; 4) Social networks are the strongest predictors of gang violence.