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You're going to learn every edge case
learningprocessAI

What It Means

Manual work reveals the complex exceptions and special cases that automated systems must handle

Why It Matters

Edge cases are what make or break AI implementations - they're invisible until you experience them firsthand

When It's True

When building automation for complex business processes with many variables

When It's Risky

When you think you can understand a process without doing it yourself

How to Apply

1

Document every unusual situation encountered during manual work

2

Build AI systems that can handle the edge cases you've personally seen

3

Test AI performance specifically on edge cases, not just happy path

Example Scenario

Building AI for expense report processing, you discover through manual work that 15% of receipts are handwritten, some are in foreign languages, and corporate cards sometimes have weird merchant names - all edge cases your AI must handle.

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