Developer builds multi-agent VS Code workflow to manage AI roles, limits, and task continuity

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A developer on Arch Linux built a local multi-agent workflow in VS Code to address practical problems with long AI tasks, quota interruptions, and inefficient context-switching between tools. The system, initially called tri-agent and later expanded to penta-agent, assigns distinct roles to different AI models: Codex as executor, Claude as reviewer, and Gemini and Copilot for exploratory or support tasks. The core principle is that each agent operates within defined permissions and responsibilities, preventing any single model from self-validating critical changes. The developer notes that losing task continuity — including which files changed, which hypotheses failed, and which validations remain pending — is costlier than any pause in execution. The workflow is presented not as a universal solution but as a personal governance structure that reduces the overhead of resuming complex tasks from scratch.

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