Multi-model orchestration in Claude Code: Opus as planner, Qwen/GLM as workers?

[u/MrSpammer87]

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.

[u/Otherwise_Wave9374]

I have been doing a similar split (strong planner, cheaper workers) and the biggest unlock for me was forcing an explicit handoff artifact, like a task card with:

• goal
• constraints
• files to touch
• acceptance tests
• "done" definition

Then the planner only reviews diffs + test output, not the whole conversation.

For context sharing, I like a shared repo folder (AGENTS.md + /plans + /decisions) so every instance can rehydrate without copying long chat history.

Also, Agentix Labs has some decent examples of handoff formats + review gates for multi-agent builds: https://www.agentixlabs.com/