Test AI with Something You Already Know: The Simple Validation Trick

Why this matters

Before you hand over important work to any AI tool, you need to know what it's actually good at—and where it might stumble. The smartest way to figure this out? Give it a test where you already know the right answer. Think of it like checking a new calculator: you'd test it with 2+2 before trusting it with your taxes.

The validation technique that works

This approach is beautifully simple. Pick something you're already an expert on—your job, your hobby, your favourite book, or even basic facts about your hometown. Then ask the AI to help with a task related to that topic.

Here's how to do it:

Step 1: Choose your test topic

Pick something you know inside and out. If you're a teacher, test it on lesson planning. If you love cooking, ask for recipe modifications. If you're a small business owner, request marketing copy for your actual business.

Step 2: Ask a realistic question

Don't make it too easy or too hard. Ask the kind of question you might actually use the AI for later. For example: "Help me write an email to customers about a shipping delay" or "Suggest three ways to improve my morning routine."

Step 3: Evaluate the response carefully

This is the crucial part. Since you know the topic well, you can spot problems immediately. Look for factual errors, missing context, or suggestions that wouldn't work in real life. Pay attention to what it gets right too—those are its strengths.

Step 4: Test the boundaries

Try a few variations of your question. Ask follow-up questions. See how it handles specific details versus general requests. This helps you understand not just what it knows, but how it thinks.

What you'll discover

Most people are surprised by this exercise. They often find that AI tools are excellent at certain types of tasks—like drafting initial versions of text or brainstorming ideas—but struggle with others, like understanding specific industry nuances or local context.

For instance, you might discover that ChatGPT writes decent marketing copy but doesn't understand your customers' specific pain points. Or that it's great at outlining presentations but needs help with technical accuracy.

This isn't about finding flaws—it's about understanding capabilities. Every tool has limitations, including the ones we use every day. The difference is that with AI, those limitations aren't always obvious upfront.

Building trust through testing

Once you understand an AI tool's strengths and weaknesses in familiar territory, you can use it more confidently in new areas. You'll know when to double-check its work, what types of tasks to avoid, and how to phrase your requests for better results.

This testing approach works with any AI tool—writing assistants, image generators, coding helpers, or research tools. The principle stays the same: start with what you know.

Try it today

Pick an AI tool you've been curious about and test it with something from your area of expertise. Spend 10 minutes asking it questions you already know the answers to. You'll learn more about the tool's capabilities in those 10 minutes than you would in hours of random experimentation.

Remember: the goal isn't to stump the AI or prove it wrong. It's to understand how it can help you—and where you need to stay in the driver's seat.