LambdaTest KaneAI vs QAby.AI: Why Modern Testing Needs More Than Generated Scripts

Every week, another AI testing tool promises to revolutionize QA. "Write tests in plain English!" they say. "Let AI handle the automation!" they promise.

But here's what they don't tell you: most of these tools are just using AI to automate the old problems. They generate the same brittle, maintenance-heavy test scripts that have plagued QA teams for years.

We recently had a customer show us LambdaTest's KaneAI platform, excited about its promise of AI-powered testing. After diving deep into how it actually works, we discovered something that perfectly illustrates the divide between yesterday's AI testing and tomorrow's.

The fundamental question isn't whether AI can generate test code. It's whether we should be generating test code at all.

How LambdaTest KaneAI Works: The Promise and The Reality

KaneAI follows a seemingly logical approach. You describe your test case in natural language—what you want to test, what data to use, what constraints to apply, what to verify. Their AI agent then processes this description and generates a complete test case for you.

Sounds great, right? Here's where it gets interesting.

The output is a Selenium script. Yes, Selenium—the testing framework that was cutting-edge when the iPhone 3G was the hot new device.

But it gets worse. The generated scripts include patterns like:

click_button();
wait_for_5_seconds();
verify_element();

If you've been in testing for more than a few years, you just cringed. Hard-coded waits are the calling card of unreliable tests. They're either too short (test fails randomly) or too long (test suite takes forever). There's no winning.

The Fundamental Flaw: Generating Yesterday's Technology

Let's be clear about what's happening here. KaneAI is using today's AI to generate yesterday's testing code. It's like using GPT-4 to write COBOL—technically possible, but missing the point entirely.

Why Selenium in 2025 Is a Non-Starter

Selenium was revolutionary in 2004. But the web has evolved, and so have testing needs:

• No auto-waiting: Modern frameworks like Playwright automatically wait for elements to be ready. Selenium? You're manually adding sleep statements and hoping for the best.
• Flaky by design: Without intelligent waiting, tests break when servers are slightly slower or networks have minor hiccups.
• Maintenance nightmare: Every UI change requires updating selectors, adjusting wait times, and praying nothing else broke.

The worst part? When KaneAI generates these Selenium scripts, you inherit all these problems. The AI might write the initial script, but guess who's debugging it at 2 AM when it fails in CI/CD?

The "Generated Code" Trap

Here's what happens in practice with generated test scripts:

1. Week 1: AI generates your test suite. Everyone's impressed.
2. Week 2: First UI update. Half the tests break.
3. Week 3: You're manually fixing generated code, trying to understand what the AI was thinking.
4. Week 4: You realize you're maintaining auto-generated spaghetti code that no one fully understands.

You haven't eliminated the complexity—you've just moved it. Instead of writing test code, you're now debugging AI-generated test code, which is arguably worse.

The QAby.AI Philosophy: No Scripts, No Problems

We took a completely different approach. Instead of using AI to generate better test scripts, we asked: what if we didn't generate scripts at all?

With QAby.AI, you write test steps in plain English:

1. Navigate to login page
2. Enter valid credentials
3. Click submit
4. Verify dashboard appears with user's name

That's it. No Selenium. No Playwright. No generated code whatsoever.

Our AI doesn't generate a script that then executes these steps. Instead, it dynamically interprets and executes them in real-time. When your UI changes, our AI adapts on the fly. When timing varies, it intelligently waits. When elements move, it finds them.

This isn't just an incremental improvement. It's a fundamental rethinking of how AI should be applied to testing.

Test Generation: Reading Descriptions vs. Reading Code

Both platforms offer test scenario generation, but the depth is dramatically different.

KaneAI's approach: You describe what you want to test (e.g., "test the login module"), and it generates test scenarios based on common patterns and your description. It's educated guessing—often good, but limited by what you remember to describe.

QAby.AI's approach: Point us to your application or integrate your frontend code. We analyze the actual implementation to create test scenarios. We see the edge cases in your code, the error states you've handled, the validation rules you've implemented.

The difference? KaneAI generates what you asked for. QAby.AI generates what you need—including the edge cases you forgot existed.

The Real-World Impact: What This Means for Your Team

Let's talk about what actually matters to engineering leadership:

For the Skeptics: "But What About Playwright?"

Some of you are thinking, "Selenium is outdated, but what about modern frameworks like Playwright?"

Fair question. Playwright is excellent—miles ahead of Selenium. If you're committed to code-based testing, it's the best choice. We've actually written a detailed comparison between Playwright and QAby.AI for those interested.

But here's the thing: even Playwright tests are still code that needs maintenance. They're still scripts that break. There's still complexity that only some team members can handle.

The question isn't "Selenium or Playwright?" It's "Scripts or no scripts?"

The Path Forward: Testing That Scales with Your Team

The future of testing isn't about generating better scripts—it's about eliminating scripts entirely. When your product manager can write tests as easily as your QA lead, when tests adapt to changes automatically, when maintenance means updating English descriptions instead of debugging code—that's when testing truly scales.

LambdaTest KaneAI represents the old paradigm with new tools: using AI to generate traditional test scripts faster. It's an improvement, but it's optimizing the wrong thing.

QAby.AI represents a new paradigm: AI that tests dynamically, adapting in real-time, with no generated code to maintain.

Ready to See the Difference?

We're confident enough in our approach that we invite direct comparison. Take your most flaky Selenium test—the one that fails every other run, the one with twelve different wait statements, the one everyone avoids touching.

Rewrite it as simple English steps in QAby.AI. Watch it run reliably. Watch it adapt to UI changes. Watch your team members who've never written a line of code contribute test cases.

That's the difference between generating test scripts with AI and actually using AI to test.

Try QAby.AI free for 14 days or Book a demo to see how modern AI testing actually works.

P.S. For teams currently using Selenium-based tools: we're not saying your tests are bad. We're saying they don't have to be that hard. There's a better way, and we'd love to show you.