Anyone here using Claude Code with a multi-model setup where Opus acts as the planner/orchestrator while models like Qwen and GLM act as specialized workers, each running in their own Claude Code instance? The architecture I’m exploring looks roughly like this: Opus handles: planning task decomposition repo-wide reasoning orchestration and routing reviewing and merging outputs Worker models handle: isolated implementation tasks fast iterations framework or domain-specific coding writing tests and docs refactors and small focused changes Curious how people are structuring this in practice: How do you handle context sharing between instances? Do you keep any shared memory/state layer or keep everything stateless? What does your task handoff format look like? How do you validate worker outputs before merging? How do you prevent drift or incorrect assumptions across workers? Any practical setups for reducing cost and latency? Also interested if anyone is using: MCP tools git worktrees sandboxed environments separate agent processes task queues or orchestration layers Trying to understand what actually works beyond small experiments. submitted by /u/MrSpammer87
Originally posted by u/MrSpammer87 on r/ClaudeCode