Boost Your Coding Efficiency 200% with AI: Proven Prompting & Cursor Tips

1. Soul‑searching – “AI boosts efficiency 200%? I don’t buy it!”

Many developers complain that AI‑generated code is low quality and that asking AI feels like talking to a wall.

The problem is not AI’s capability but how we use it, just like learning IDEs or Git.

Three common reasons for poor results:

1. Prompt is not precise enough

Vague commands like “write a login code” don’t work; AI needs a clear task, e.g., “Using Spring Boot with MySQL and BCrypt, generate a user login feature with username/password validation, failure messages, and session management.”

2. Improper usage

AI should not replace thinking. Effective workflow: (1) generate 80% of boilerplate with prompts; (2) manually add core business logic.

3. Wrong tool choice

General large‑model AI tools often require many back‑and‑forth interactions; specialized coding assistants are more efficient.

2. Cursor’s secret weapon – not a Q&A bot but a coding collaborator

It “sees” your code

Cursor is more than a completion tool; it is an IDE that integrates with your codebase, allowing you to drag files or folders into its chat and receive context‑aware code.

Task autonomy: from instruction to delivery

Unlike generic models that only output snippets, Cursor can create project structure, generate tests, run them, suggest fixes, and iterate until the code works.

Example: generating a simple weather scraper, Cursor produces code, runs tests, suggests fixes, and finally the scraper runs successfully.

Risk control: Cursor‑driven code review

Cursor can enforce review rules, automatically suggest and apply fixes based on user‑defined guidelines. Example prompt for a review is shown below.

使用下面的git命令, 输出当前分支与远程主分支的差异, 输出到cr.diff 文件中
git diff origin/master  > cr.diff
扫描diff 文件中的差异代码。reviwe 的规则如下

1. 方法体行数应少于100行, 不包括空行,和注释
2. 枚举定义需要有两个以上属性, code, name, 并且需要有通过code获取枚举项的方法
3. 接口返回 false , 前端是否有对 false 进行处理 
4. throw 了异常的位置, 一定要打 log 日志 
5. 所有的public 公有方法都要打印入参log.info日志 
6. 所有的public 公有方法, 结束都要打印结束日志 
7. 所有调用rpc的方法, 都要打印日志
8. 所有方法都要有方法级别的注释
9. try catch异常后, 如果在catch 中又抛出了新创建的异常时, 需要将原异常赋值给新异常, 案例如下:
    ```java
    try {
        ApiResult<String> result = uploadService.getUploadId(uploadIdDTO);
        log.info("UploadServiceHelper#getUploadId result:{}", JsonUtils.toJsonWithoutNull(result));
        if (result.isSuccess()){
            return result.getData();
        }
    }catch (Exception e){
        log.error("UploadServiceHelper#getUploadId 调用uploadService.getUploadId失败", e);
        throw new MyException("调用uploadService.getUploadId失败", e);
    }
    ```
10. 不能调用被标记@Deprecated 的属性或方法或类
11. 定义的常量值, 给出清晰的注释说明用途, 避免硬编码
12. 标注了@transactional的方法要明确回滚异常类型, 对于只读操作要标注只读readOnly=true 提高性能
13. 3次以上字符串拼接使用StringBuilder代替字符串拼接
14. 检查是否存在其他破坏兼容性的改动或逻辑上的错误

遍历所有规则, 一个规则一个规则的去检查增量代码的规范性, 每个规则进行Review时, 使用独立的上下文, 最后归纳所有的Review结果.
输出违反规则的文件位置, 并修改对应文件 符合规范
cr 结束后将cr.diff 文件删除

Cursor then displays the review results.

These capabilities can shrink a one‑day task to three or four hours, truly doubling productivity.

4. Key reminder – leverage strengths, avoid weaknesses

It’s not magic but a tool: best for well‑defined, pattern‑based tasks, not for replacing design or core business logic.

Core principle: Review, Review, Review! Generated code must be inspected.

Clear instructions are crucial: describe requirements as you would to a smart intern.

5. Conclusion – embrace evolution to become a stronger developer

Adopting AI is a strategic evolution, not a downgrade. It frees developers to focus on design, architecture, complex business, and innovation, just as power tools amplify a craftsman’s efficiency.