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Training Practical series

Six free lessons · About 70 minutes

Testing and quality control in the age of AI

AI can make a first draft fast. This series is about finding out whether the result actually works, whether its claims have support, and what should happen before anyone relies on it.

Start part one Beginner-friendly; code example optional

The idea

Trust needs checkpoints.

A polished website, a busy campaign, and a confident AI review can all hide a broken result. The answer is not to stop using AI. It is to give the work a few checks that are clear enough for a teammate to repeat.

We begin with the whole visitor or user journey, expand the cases a team can afford to test, add a focused reviewing agent, and place checks at risky handoffs. Then we show how experienced quality teams can use AI for more reach and how to set stable rules for accepting variable output. Every lesson has a realistic teaching scenario, a cartoon, and a small assignment.

What you can use right away

Leave with a test brief, a broader coverage plan, a source-review prompt, and a stop rule for your next release. A passing check alone does not prove every AI output is true or every customer journey works. The habit is to name the risk, test the outcome, keep the evidence, and know when a person must decide.