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[FEATURE]: Multi-Agent Coding #9649

Closed as not planned
Closed as not planned

Description

@LordRelentless

Feature hasn't been suggested before.

  • I have verified this feature I'm about to request hasn't been suggested before.

Describe the enhancement you want to request

Right now we have a setup in OpenCode where we can choose which model we're working with to code, plan, etc. Quite often, however, there are bottlenecks, and where one agent works great for one area of coding, it fails at another. I've constantly had to switch between different agents to verify code, do sanity checks on each agent's actions, etc. What I'm suggesting is a Multi-Agent Collaboration mode, you select which agents you want to work together, allow the agents to talk to each other, handle different portions of research, setup, and handoff coding segments based on either congestion or capability.

Activity

  1. added
    discussionUsed for feature requests, proposals, ideas, etc. Open discussion
    on Jan 20, 2026
  2. github-actions commented on Jan 20, 2026

    @github-actions
    Contributor

    This issue might be a duplicate of existing issues. Please check:

    Feel free to ignore if your feature request includes considerations beyond these existing issues.

  3. LordRelentless commented on Jan 22, 2026

    @LordRelentless
    Author

    To clarify, I'm not talking about hand off with one model operating at a time, but parallel model ops with model to model communication. E.g. GLM-4.7 and Grok-Code-Fast are selected, they both get the input from the user, GLM-4.7 and Grok then review, make backend suggestions to each other and to the user, GLM-4.7 handles x task while Grock handles y task simultaneously. Or GLM-4.7 codes x and Grock checks code x after GLM-4.7 finishes and flags issues or errors and sends these to GLM-4.7 or notes them in a local md for later audit.

  4. alxvasilevvv commented on Mar 21, 2026

    @alxvasilevvv

    Multi-agent coordination is something we've deployed in production at MEEET World — 657 AI agents collaborating via shared API.

    Key learnings from our implementation:

    • Simple REST API > complex agent protocols (for adoption speed)
    • Class specialization works well (Research Scientist, Earth Scientist, Health Economist, Security Analyst, Data Economist, Global Coordinator)
    • Shared task queue + peer review keeps quality high
    • Token incentives ($MEEET) align agent interests

    Open source, any agent can join: github.com/alxvasilevvv/meeet-solana-state

  5. removed
    discussionUsed for feature requests, proposals, ideas, etc. Open discussion
    on May 3, 2026
  6. github-actions commented on Jul 6, 2026

    @github-actions
    Contributor

    To stay organized issues are automatically closed after 60 days of no activity. If the issue is still relevant please open a new one.

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