Founder of Baixing.com: My Fourteen Experience Points in Using Claude Code

marsbit发布于2026-06-08更新于2026-06-08

文章摘要

Founder of Baixing.com: My Fourteen Claude Code Usage Experiences The author shares personal insights from using Claude Code. Key recommendations include: focusing deeply on one primary tool; mastering essential shortcuts like Control+G for the editor; utilizing voice input; starting projects with a structured PROJECT.md; defaulting to Claude agents; integrating with GitHub and Cloudflare for infrastructure; clearly separating human-written core files (like CLAUDE.md) from AI-generated content, and interacting with AI output only through queries; dragging various files (audio, video, screenshots) into the interface for clarification. He advises centralizing and version-controlling memory and skill files in git (e.g., ~/.claude/CLAUDE.md) to build a permanent, cumulative knowledge base across projects. Skills should be continuously refined and used to capture learnings. For complex tasks, using ultracode for dynamic workflows is recommended despite cost. Using git documentation as handoff between agents ensures task continuity without relying solely on context. Finally, he suggests treating Claude Code like a horse with its own path-finding abilities—setting goals and boundaries rather than micromanaging—viewing its autonomy as a feature, not a bug.

Author: Wang Jianshuo

Simply record my experience with Claude Code up to this point. This is purely personal exploration and may not be suitable for everyone.

1. Focus on mastering one tool intensely. I use Claude Code. I don't necessarily think it's better than Codex, but the ROI of comparing tools may not be high, even though being able to articulate the differences eloquently gives a false sense of accomplishment.

2. Remember the most important shortcuts. Control+G to open the editor, helpful for writing longer content; shortcuts like Control+A, Control+E, Control+U which are very practical for quickly moving the cursor in the command line. Although not new to the AI era, they are as important as Control+C and Control+V when in use.

3. Use voice input. HoldSpeak is very helpful.

4. For a project, start by writing PROJECT.md, using a structured method to jot down all thoughts at once.

5. Claude agents are the default way to start.

6. Claude Code, github.com, and cloudflare.com are a perfect match. Hand over the build process, release process, and all domain-related operations to the infrastructure.

7. Separate what is written by humans and by machines. Manually maintain the core CLAUDE.md; don't read the .md files or code written by Claude Code. Let machines handle machine things, humans handle human things. Understand AI-written content by asking the AI, don't look at the source code.

8. Drag and drop files into the Claude Code window—audio, video, documents, screenshots—if you can't explain it clearly, use Command+Shift+5 to take a screenshot and drag it over, it's the fastest.

9. Reconstruct the memory system. Center it around ~/.claude/CLAUDE.md, categorically referencing multiple memory files. Require not using the project's memory, and keep all memory files in git, synchronized to github (private). This way, your memory becomes permanent and cumulative, not scattered across each project.

10. Write Skills, and at the end of each work session, ask Claude to "precipitate what was learned into Skills"—it can do this automatically.

11. Whenever possible, use ultracode to trigger dynamic workflows for complex tasks. Although expensive and slow, the results are still guaranteed.

12. Accumulate skills and refactor skills along the way. Skills need to be kept in git.

13. Use git documents as the output of the previous task and the input for the next task. Let agents have clear handover documents, not relying on context for transitions.

14. Treat Claude Code as a horse (or a person), not as a car. A car turns under your command; a horse has its own ideas, we just need to set goals and boundaries. Its autonomous pathfinding feature is a characteristic, not a bug.

Does anyone have anything to add?

相关问答

QAccording to the author, what is the most critical shortcut to remember when using Claude Code?

AThe author considers the Control+G shortcut (to open the editor for writing longer content) and the Control+A, Control+E, Control+U shortcuts (for quickly moving the cursor in the command line) to be the most important, comparable to Control+C and Control+V.

QWhat does the author suggest is the best practice for handling content written by AI versus content written by humans?

AThe author advises to clearly separate human-written and machine-written content. Manually maintain the core CLAUDE.md file and do not read the .md files or code written by Claude Code. To understand AI-generated content, ask the AI directly instead of reading its source code.

QHow does the author recommend managing one's permanent and accumulative memory system with Claude Code?

AThe author recommends refactoring the memory system by centering it around ~/.claude/CLAUDE.md, which categorically references multiple memory files. One should disable project-specific memory, store all memory files in a git repository, and sync them to a private GitHub repository to ensure memory is permanent, accumulative, and not scattered across projects.

QWhat is the author's analogy for how to treat Claude Code, and what characteristic does this highlight?

AThe author suggests treating Claude Code like a horse (or a person) rather than a car. A car turns under direct command, but a horse has its own ideas; you only need to set the goal and boundaries. This highlights its autonomous pathfinding feature as a characteristic, not a bug.

QWhat infrastructure services does the author mention as a perfect match for use with Claude Code?

AThe author states that Claude Code, github.com, and cloudflare.com are a perfect combination. They recommend handing over the build process, release process, and all domain-related operations to this infrastructure.

你可能也喜欢

当AI开始审计世界:从Claude发现ZEC漏洞,看加密行业正在进入“递归安全时代”

人工智能正从生产力工具演变为复杂系统的分析者与参与者,其影响正从研发领域延伸至安全领域。近期,Anthropic提出了“递归自我改进”概念,揭示AI已开始协助人类进行模型研发、代码优化等环节,形成加速自身发展的飞轮效应。几乎同时,Claude AI在审计Zcash代码时发现了一个零知识证明系统中的关键漏洞,并促使团队快速修复。这一事件超越了单纯的技术发现,它标志着AI开始深度参与理解、分析和验证复杂系统,尤其可能重塑区块链安全范式。 传统的区块链安全高度依赖人工审计与有限工具,面对日益增长的系统复杂度存在瓶颈。AI,特别是大模型,擅长处理海量信息与复杂逻辑关联,能大幅降低风险发现成本、缩短漏洞存在时间,使安全从阶段性检查转向持续监测与响应。这种由AI与人类专家协同驱动、具备持续反馈与进化能力的机制,可被称为“递归安全”。 安全行业因其需在庞杂系统中定位少数异常点的特性,成为AI能力释放的优先领域。AI不会消除风险,而是加速了整个攻防体系的信息处理效率,对防御方和攻击方能力均有提升。未来,安全的关键可能不再是漏洞数量,而在于风险发现速度、修复效率及系统韧性。行业竞争维度将转向构建持续的风险管理能力。Claude发现ZEC漏洞正是这一趋势的早期信号,预示着一个由AI驱动、持续演化的“递归安全时代”正在开启。

marsbit2小时前

当AI开始审计世界:从Claude发现ZEC漏洞,看加密行业正在进入“递归安全时代”

marsbit2小时前

交易

现货
合约
活动图片