Why Testing AI Products Is Different: A Guide for Builders

In the evolving world of AI, traditional testing approaches fall short. Here's how to adapt your testing to ensure your AI products deliver value while handling the unpredictable nature of gengenerati

AI is changing everything about how we build products. If you've started creating AI tools, you've likely discovered that testing them feels completely different from testing regular software.

If you've started building with AI, you've probably noticed this already. You type the same question twice and get different answers. Your perfectly working AI app suddenly gives weird responses when a new model version is released. It can feel like trying to hit a moving target.

It can feel like trying to hit a moving target, but there are better approaches to testing. We've seen a lot of builders struggle with this challenge, and we want to share insights on what works and what doesn't.

Input and Output Consistency

Traditional Products: When a user clicks a button or fills out a form, you get the same result every time. It's predictable.

AI Products: Ask the same question twice, get two different answers. This is by design, but it makes traditional testing tricky!

User Experience Structure

Traditional Products: Users follow specific paths you've created for them. You know exactly where they'll go next.

AI Products: Every user can have a completely different conversation with your AI. The paths are countless and impossible to predict fully.

Performance Stability

Traditional Products: Once you test it and it works, it generally keeps working the same way.

AI Products: The underlying AI models are constantly updating and improving. What works perfectly today might be different next month as models evolve.

Interaction Possibilities

Traditional Products: Users interact in specific ways you've designed for. Type here, click there.

AI Products: Users can interact through text, voice, images, different languages, or combinations we didn't plan for. They guide the experience in unexpected ways.

Why Old-School Testing Doesn't Work with AI

Traditional testing is all about making sure specific actions lead to specific results, every time. You create a test scenario, run through steps, and check that the results match what you expect. This works great when you know all the possible paths users might take.

But with AI, there are infinite possible inputs and outputs. You simply can't test every possible conversation or prompt. And even if you could, the AI might respond differently tomorrow than it does today.

As one AI developer told us: "I would test my app, fix all the issues, and feel confident about launching. Then a week later, the underlying model would update, and suddenly everything was different. It was like starting over."

A Better Way to Test AI Products

Instead of fighting against the changing nature of AI, we need to work with it. Here's how to shift your thinking:

1. Test Patterns, Not Specifics

Rather than checking if specific prompts give specific answers, look at patterns. Does your AI generally provide helpful responses? Does it maintain the right tone? Does it accomplish the main goal you set out to achieve?

2. Get Comfortable with Breaking Things

With AI products, something will always "break" as models change or users try unexpected things. The goal isn't to prevent all breaks but to learn from each one and adapt quickly, just like waves reforming after they break on the shore.

3. Test with Different Types of People

Since AI can be used in countless ways, you need feedback from different perspectives:

• People who would love your product: Your target users who will help you find what's working best

• People outside your target audience: They'll point out things that make no sense that you might miss

• People who think differently: They'll try things you never expected and give you new ideas

This variety helps you discover how your AI product behaves in all kinds of situations.

Simple Ways to Test Your AI Product

Try Different Versions

Create a few different versions of your AI prompts or settings and see which one works better. This helps you improve without expecting exact matches every time.

Find Diverse Testers

Test with people of different ages, backgrounds, and experiences. AI products can handle different languages and cultural references, so diversity in testing is super important.

Try to Break It (On Purpose)

Intentionally use your product in ways it wasn't designed for. This helps you see how your AI handles the unexpected.

Ask Yourself These Questions

When planning your testing:

1. What do you really need to know? Is it about whether the product works, provides value, makes sense to users, or something else?

2. What kind of feedback do you need? Numbers and stats, or detailed user experiences?

3. How will you sort through feedback? Not everything needs to be fixed right away.

What to Do with Test Results

After testing, you'll have lots of information to sort through:

1. Focus on what matters most: What needs fixing now versus later? What can you ignore?

2. Look at both numbers and stories: Quantitative data tells you what's happening, but user stories tell you why.

3. Be open to surprises: Testing might reveal unexpected opportunities, but stay focused on your main goals.

Getting Started Today

The simplest way to start is to just do it. Find three people this week to test your AI product:

1. Someone who fits your ideal user profile

2. Someone who isn't your typical user but might find value in what you've built

3. Someone who approaches problems differently than you do

Share your product with them, listen to their feedback, and make improvements. The biggest mistake we see is people waiting until their product is "perfect" before testing it.

As many successful AI builders have learned: "Perfect is the enemy of done."

Wrapping Up

Testing AI products means embracing change, listening to different perspectives, and looking for patterns rather than exact matches. By approaching testing this way, you can build AI products that truly help people while handling the natural unpredictability of AI.

Want to learn more about AI testing? Watch the replay of our workshop, where we share practical techniques for testing and improving your AI applications.

Remember, in AI development, we don't need to be perfect. We just need to be willing to learn and adapt as we go.