In this module, you'll learn to identify and avoid common inefficiencies in automation by recognizing anti-patterns that compromise flexibility and performance. The video covers pitfalls such as hardcoded values, over-fetching data, and redundant calculations—issues that can slow down your processes and increase complexity. By addressing these anti-patterns, you can build leaner, faster, and easier-to-maintain workflows.
Video (6:39 minutes)
Why this matters
Hardcoded values and redundant calculations make workflows inflexible and harder to maintain.
Over-fetching data slows down processes and increases complexity.
Addressing these anti-patterns improves efficiency, readability, and scalability.
Magic string anti-pattern
What it is: Hardcoding specific values (e.g., email addresses, numbers) instead of using variables.
Why it’s a problem: It makes workflows rigid, harder to modify, and unclear.
How to avoid it: Use variables instead of fixed values to improve flexibility and readability.
Over-fetching data
What it is: Retrieving more data than needed (e.g., pulling full user objects when only an ID is required).
Why it’s a problem: It increases processing time and complexity, especially at scale.
How to avoid it: Use filters to limit data retrieval and select only the necessary fields.
Redundant calculations
What it is: Repeating the same calculations multiple times, often in loops.
Why it’s a problem: It wastes processing power and slows down execution.
How to avoid it: Use hoisting—move calculations outside of loops—and store repeated values in variables to avoid recalculation.
How to apply this in automation
Replace hardcoded values with variables for clarity and flexibility.
Limit data retrieval using filters and selecting only the needed fields.
Optimize calculations by reducing redundant computations inside loops.
By eliminating these anti-patterns, you'll create automation workflows that are leaner, faster, and much easier to maintain.
