Concurrent Multi-Agent Approach Faces Skepticism

Multi-agent systems earn their keep by hiding latency and splitting separable tasks like research and test execution, rather than simply acting as a smarter solo coder. While git worktrees and small task cards help tame complexity, the coordination cost of unsupervised agents can quickly outweigh the gains if they drift without constant observation and rollback capabilities. Ultimately, for coupled refactors or ambiguous objectives, a single supervised agent typically outperforms a small swarm.