Claude Code 团队内部技巧首次公开，做复杂自动化或长任务开发的可以直接套用 /goal 和 Workflows，大幅减少人工干预。
Claude Code 团队成员 Thariq 分享了一系列使用技巧，帮助开发者更高效地利用 Claude Code。核心建议包括：从验证“是否做对”转向验证“是否做对的事”；在实现前让 Claude 参与思考过程，通过小规格文档和访谈式对话明确细节；使用 /goal 命令让模型持续工作直到目标完成；利用 Workflows 并行任务、自我验证并生成报告。这些方法能显著提升 Claude Code 在复杂项目中的表现，甚至完成此前被认为不可能的任务。
Some really cool recommendation for pushing Claude…
Some really cool recommendation for pushing Claude Code to its full potential. By Thariq (@trq212) from Claude Code team.
(Noted from his video by Grok)
- Shift from verifying whether Claude did the work right to verifying whether Claude is doing the right work.
- Treat Claude Fable 5 like a true thought partner by giving it the full context it needs upfront, rather than jumping straight into implementation.
- Involve Claude early in the thinking process by starting with a small spec and asking it to interview you about the implementation details before finalizing the spec file.
- Ask Claude to explore multiple directions for an idea and generate quick mockups (such as in HTML) for review, which helps catch misalignment before any code is written.
- Provide Claude with rich context instead of rigid constraints—for example, explain that a feature is an experiment likely to be deleted in a month so it avoids building anything painful to throw away.
- Give Claude explicit goals and verification methods once the direction is clear, especially for ambitious problems.
- Use the new /goal command in Claude Code, which helps the model keep working until the objective is fully complete.
- Use Workflows in Claude Code to let the model parallelize tasks, verify its own output, and prepare a report on what was implemented versus what differed from the plan.
- Prompt Claude with a combined instruction such as: “Set a goal to implement the spec fully, then use a workflow to verify each part of the plan, and prepare a report on what was implemented and if anything differed.”
- Be far more ambitious with Claude Fable 5 by assigning it tasks previously assumed to be impossible for LLMs, as the model now runs for hours, self-tests, and often produces higher-quality code than manual efforts.
Experiment boldly—for instance, I edited this entire video using Claude Fable 5—because the model raises the bar on what developers can realistically achieve in a single session.