Increased layers of review in a team can significantly slow down workflow, with coordination overhead causing a decrease in speed that is not linear with team size. Effective organizational design is crucial to minimize this overhead and maintain efficiency.

Large language models (LLMs) are being deployed in teams, raising questions about their effectiveness, optimal team size, structural impact on performance, and comparative advantages over individual models. A principled framework is needed to address these key issues in the context of multiagent systems.

Shipping multiple features rapidly can lead to cognitive debt, where understanding and maintaining the code becomes challenging. High velocity in development may result in a lack of comprehension about the code's architecture and interactions, complicating future modifications.