Lesson 1.2 - What AI Actually Is (For Testers)

Learning objective

Build a simple, practical understanding of AI without theory overload.

Chapter 2 / Objective 2

You don't need to understand machine learning algorithms to use AI effectively as a tester.

Here's the mental model you do need:

Modern AI tools are advanced pattern recognizers trained on large amounts of text and code.

They:

• Predict likely answers
• Do not "know" truth
• Do not understand your product
• Do not test your application

Think of AI like:

• A very fast junior tester
• Who has read a lot
• But has never seen your system before

That means:

• AI can suggest test scenarios
• AI cannot decide which tests matter most
• AI can explain code
• AI cannot guarantee correctness

Common misconception

"If AI generates test cases, they must be correct."

False.
AI output always requires human validation.

Key takeaway

AI produces plausible output, not verified truth. Treat it as input, not authority.