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网站：https://ttal.guion.io 706次提交，38个合并的PR，5个代码库，5天。一个人最多进行5个Claude Code会话。技术栈：Taskwarrior作为任务队列，Zellij作为会话管理器，Claude Code作为工作者。每个CC会话在一个Zellij窗格中运行，并分配一个任务。当一个会话完成时，下一个优先级最高的任务会通过Taskwarrior的钩子自动启动。你管理的是任务，而不是会话。周四我遇到了API速率限制，吞吐量下降了75%。这就是证据——系统是瓶颈，而不是我。关键设计：按需的人机协作。代理从不因等待我而阻塞。它们接手任务，完成工作，提交，然后继续前进。我在准备好时审查PR并做出决策——而不是在代理需要我时。这就是消除人作为瓶颈问题的方法。当没有会话在等待你时，5个会话就足够了。完整的设置已在网站上记录。架构并不局限于Claude Code——Zellij会话不在乎里面运行的是哪个CLI代理。

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Site: https://ttal.guion.io706 commits, 38 PRs merged, 5 repos, 5 days. One person with max 5 Claude Code sessions.The stack: Taskwarrior as the task queue, Zellij as the session manager, Claude Code as the worker. Each CC session runs in a Zellij pane with a task assigned. When a session finishes, the next highest-urgency task auto-starts via Taskwarrior hooks. You manage tasks, not sessions.Thursday I got API rate-limited and throughput dropped 75%. That's the proof - the system was the bottleneck, not me.The key design: on-demand human-in-the-loop. Agents never block waiting for me. They pick up tasks, do the work, commit, and move on. I review PRs and make decisions when I'm ready - not when the agent needs me. That's what eliminates the human-as-bottleneck problem. 5 sessions is plenty when none of them are waiting on you.The full setup is documented on the site. Architecture isn't locked to Claude Code - Zellij sessions don't care what CLI agent runs inside them.

我在5天内通过Taskwarrior和Claude Code完成了706次提交。