ClaudeCode best practices: Part 1: Provide clear context just like communicating with people.
First of all, the first and most important core concept shared by the official is: **Treat Claude as a "person"**.
To be more specific, think of it like a new coworker who is super smart but knows nothing about your project.
You can't expect him to guess your code logic and project background out of thin air as soon as he comes, right?
So, the first key point is: **provide complete context**.
Think about it, if you asked a new colleague to fix a bug, would you tell him what the bug is, which file it is in, and what the relevant code looks like?
The same goes for working with Claude.
You need to give it a "big picture view".
For example, what are the key parts of your code base?
What is the overall architecture?
You can even feed it your entire code base or key files.
When the context window is large enough, Claude can understand the full picture of the code like a real team member, instead of seeing the forest for the trees.
In this way, the suggestions it gives and the code it generates will be more accurate and more suitable for your project.
Part 2: Carefully design your "prompt words" to guide high-quality output.
The second core is **Carefully design your prompts (Prompt)**.
This can be said to be the art of collaboration with AI.
This is also emphasized in the official article.
We can follow a “SME-GPT” framework, which means “ask like a domain expert”.
* **第一步：明确角色和目标。
** You can first tell Claude: "You are now a senior Python engineer, and your task is to help me optimize a piece of code and improve its operating efficiency." * **Step 2: Provide detailed steps and constraints.
** 不要只说“帮我改代码”，而是给出清晰的指令，比如：“首先，请分析这段代码的逻辑。然后，找出可以重构的部分。最后，使用更高效的算法来改写它，并确保代码风格遵循PEP 8 specifications.
" * **Step 3: Provide "good" examples.** If you want it to generate code in a specific style or structure, then give it an example.
For example, you can say: "Please follow the format of this function and write a new function for me." ” It’s like giving it a template and it will learn very quickly.
This way, you're not "requesting" the code, but "guiding" it to generate the code you want.
Part Three: Iteration and Decomposition - The Power of Simplifying Complexity No matter how powerful the AI is, it is difficult to perfectly solve a large and complex problem in one go.
So, the third key point is: **Iteration and Decomposition**.
Rather than asking Claude to build a complete application all at once, it is better to break the task into small modules.
For example, you can first let it help you design the database model, then the API interface, and then the front-end components.
Take it step by step, testing and validating each step.
This "small steps and fast running" method not only has a higher success rate, but also makes it easier to locate and correct problems.
Don't be discouraged when you encounter imperfect or incorrect code.
Feedback the error message and relevant code to Claude so that he can fix it.
This cycle of "questioning-feedback-correction" is the most effective way to collaborate with AI to solve complex problems.
Part 4: Beyond Code Generation—Let AI Be Your “Navigator” Finally, the official guide also reveals a more advanced gameplay: Claude’s abilities go far beyond writing code.
We can use it for higher level tasks.
* **Use it to learn**: When you encounter a new technology or framework, you can have Claude explain the core concepts for you, and even generate a learning roadmap and introductory examples.
* **Use it to design**: In the early stages of the project, you can brainstorm with Claude to explore different architectural solutions and evaluate the advantages and disadvantages.
* **Use it for testing and review**: Let Claude help you write unit tests, integration tests, or act like a senior colleague and review your code to identify potential bugs and bad smells.
Promoting Claude from a "code farmer" to your "technical navigator" is the more advanced collaboration model we should pursue.