In collaboration with the Villagers team, a proof-of-concept was developed to simulate multi-agent social networks using LangSmith, demonstrating the potential of language-based human interactions in various fields such as economics, politics, and sociology. The project focused on creating realistic simulations of Twitter/X users by building agents that mimic user behaviors based on historical data, such as tweeting and engaging with content. This simulation platform aimed to predict user engagement and behavior changes in response to different stimuli, like ad campaigns and political statements. A significant challenge was managing the complexity of prompt engineering and debugging due to the large number of interacting agents, but LangSmith provided valuable tools for automatic tracing and efficient prompt iteration, which accelerated development and enhanced confidence in the prompts' quality.