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

marsbitPubblicato 2026-06-08Pubblicato ultima volta 2026-06-08

Introduzione

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?

Domande pertinenti

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.

Letture associate

In Conversation with Ray Dalio: We Are Currently in an AI Bubble, with 1% of My Portfolio in Bitcoin

Ray Dalio, founder of Bridgewater Associates, warns in an interview that the current AI boom shows classic bubble characteristics, which could lead to significant economic downturns as seen in past cycles like 1929 or 2000. He explains that speculative enthusiasm, fueled by debt and overvaluation, often precedes a crash when rising rates or taxation force asset sales, causing widespread losses and recession. Dalio also outlines his "Big Cycle" theory, describing an approximate 80-year pattern where widening wealth gaps, massive government deficits, and shifting geopolitical power (like China's rise) create internal conflict and global instability. He emphasizes that we are in a late-cycle, transitional phase where traditional powers like the US and UK face decline. For personal wealth protection, Dalio advises diversification beyond cash into assets like stocks, bonds, real estate, and particularly gold, which he prefers over Bitcoin. While he holds about 1% of his portfolio in Bitcoin as a non-printable hard asset, he views gold as more secure from technological or governmental threats. Regarding AI's impact, Dalio believes it will disproportionately benefit capital owners, worsening inequality by replacing both physical and cognitive labor. He suggests that human intuition and emotional intelligence, combined with AI, will be key for future workers. On taxation, Dalio argues that wealth taxes are impractical and risk triggering asset sell-offs, reducing productive investment. He points to the UK as a cautionary example of debt, low productivity, and political strife. Geopolitically, Dalio foresees a more regionalized world, with the US showing weakness in prolonged conflicts like with Iran, akin to past imperial declines. The ideal outcome, he suggests, is coexisting powerful blocs (e.g., Americas, China-Asia Pacific) without major war.

marsbit47 min fa

In Conversation with Ray Dalio: We Are Currently in an AI Bubble, with 1% of My Portfolio in Bitcoin

marsbit47 min fa

Daily 7.2 Trillion KRW: Foreign Capital's Record Net Buying on Friday! Wall Street Says Headwinds for Korean Stock Fund Flows Have Subsided

South Korean stock market sees a dramatic shift in fund flows. On July 31, foreign investors made a record net purchase of approximately KRW 7.2 trillion in KOSPI stocks, marking a fundamental reversal from the persistent large-scale net outflows seen in previous months. This contributed to a significant narrowing of foreign net selling in July to KRW 9.8 trillion, down sharply from KRW 48.4 trillion in June and KRW 44.5 trillion in May. Simultaneously, domestic institutional pressure eased. South Korean pension funds and asset managers turned to a net buying position in July, purchasing KRW 1.0 trillion worth of KOSPI shares, contrasting with net sales in May and June. Market volatility is expected to be dampened by new financial regulations. Effective July 31, the Financial Services Commission tightened access for retail investors to single-stock leveraged ETFs by raising the minimum cash deposit requirement. Trading volumes for these products subsequently dropped to about 50% of their monthly average. Citigroup Research maintains its year-end KOSPI target of 10,000 points. The firm cites several supportive factors: the substantial easing of headwinds from capital outflows, a robust fundamental outlook for the semiconductor sector, historically low market valuations, strong economic fundamentals, and the potential for policy support from financial authorities if needed.

marsbit47 min fa

Daily 7.2 Trillion KRW: Foreign Capital's Record Net Buying on Friday! Wall Street Says Headwinds for Korean Stock Fund Flows Have Subsided

marsbit47 min fa

Thanks to Dice Rolls, Bitcoin Keys Are Stored Offline, But Not Everyone Will Do It

The article discusses using dice rolls to generate secure Bitcoin wallet seeds, providing entropy independent of potentially flawed hardware random number generators. It explains that each fair dice roll offers about 2.585 bits of entropy, with around 50 rolls needed for a standard 12-word seed phrase and 99+ recommended for higher security. This method gained attention after a vulnerability was revealed in some Coldcard hardware wallets, where a faulty firmware RNG (dating back to 2021) compromised generated keys. The analysis notes that while a dice-generated main seed was safe from this specific flaw, other Coldcard functions (like creating paper wallets, backup keys, or passwords) could still be vulnerable if they used the defective RNG. The piece argues that while dice-based entropy is technically robust, the manual process is error-prone, tedious, and unrealistic for most new users, who might make mistakes in recording or inputting rolls. It concludes that while manual entropy generation should remain an option for advanced users, the long-term goal is to develop reliable, user-friendly hardware and software that securely generates randomness without requiring specialized knowledge. Coldcard users are advised to check their firmware version and replace any secondary secrets (like paper wallet keys) created with vulnerable devices, while also considering multi-signature setups with devices from different manufacturers for added security.

cryptonews.ru6 h fa

Thanks to Dice Rolls, Bitcoin Keys Are Stored Offline, But Not Everyone Will Do It

cryptonews.ru6 h fa

Trading

Spot
活动图片