Cursor Doc Dev: A New Paradigm for the AI Age
Discover why documentation is crucial in the AI era. It bridges human-AI collaboration, reduces errors, and enhances code understanding beyond automation.
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Do We Still Need to Spend Time Writing Documentation When the Cursor Can Automatically Write Code?
The answer is definitely yes, and it's more important than ever before!
Take a look at the example below.
AI can understand code logic, but it cannot comprehend business intent, design decisions, and contextual background. For instance:
def calculate_user_score(age, income, credit_history):
return (age * 0.3 + income * 0.5 + credit_history * 0.2) * 100
AI can tell you this is a calculation function, but it doesn't know whether it's used for credit assessment or user profiling, and it certainly doesn't know why the age weight is 0.3 instead of 0.4.
If we had documentation:
## User Credit Scoring Algorithm
### Business Background
This algorithm is used for risk assessment in P2P lending platforms, with weight allocation determined based on regulatory requirements and historical data analysis.
### Weight Design Principles
- Age weight (0.3): Based on statistical analysis, users aged 25-45 have the lowest default rates
- Income weight (0.5): Income is the most direct indicator of repayment ability, hence the highest weight
- Credit history weight (0.2): Although important, considering the new user demographic, the weight is moderate
### Risk Control
Users with scores below 60 require manual review