MOSAICO: A Multi-agent Infrastructure for Collaborative LLM-Powered Software Engineering

Abstract

Modern software engineering tasks increasingly call for Artificial Intelligence (AI) assistance that goes beyond a single large language model (LLM) acting alone. We present MOSAICO, an infrastructure for building and orchestrating communities of LLM-powered agents that collaborate to solve software engineering tasks. MOSAICO provides a reference client, a reference agent, and a set of task-specialised agent roles (solution, supervision, and consensus agents) that a collaboration agent invokes according to a workflow to complete a task. We showcase MOSAICO through three concrete demonstrations: a metamodelling use case, where a team of four agents jointly construct and validate a domain metamodel; a UML generation use case, where an agent converts a diagram image into textual notation; and a code documentation use case, where an agent uses client-side tools to generate documentation for existing code. Together, these demonstrations illustrate the generality of MOSAICO: a single, role-based agent infrastructure can support structurally different software engineering tasks with minimal reconfiguration.