You Can Test Your Software with AI Auto-Generated Test Cases

Ship faster. Break less. Let AI generate your test cases!

Author

Umer Khan
November 30, 2025 • Estimated Reading Time: 15 minutes

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Welcome, AI Entrepreneurs!

Ready to test your software automatically—without writing a single test case?


I’m so excited to tell you in today’s issue about how you can use Testim AI to auto-generate tests that adapt as your product evolves.


It’s like having a QA engineer who never sleeps, never misses a bug, and learns your app inside out.

In today’s AIpreneurs Insights: 

  • Spotlight Tool of the Week: Testim AI: Auto-Generated Test Cases for Bulletproof Software

  • Become the Human in the Loop in Healthcare AI: Basics 3-1: Master Artificial Intelligence Model Architecture in Healthcare

  • Top 3 AI Business Search Trends of the Week

  • Top 5 AI Tools Every Developer Needs for Bug-Free Releases

  • Free Resource: The AI QA Starter Kit

Testim AI: Auto-Generated Test Cases for Bulletproof Software

Discover how Testim AI can transform your QA process by creating, maintaining, and running reliable test cases on autopilot.

Our walkthrough shows how AI identifies user flows, builds tests instantly, and updates them as your UI changes—so you ship with confidence every single time. See how AI-powered testing can eliminate manual QA bottlenecks and speed up your release cycle.

Don’t miss the product demo.


Explore more at: https://www.testim.io/ 🚀


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Big News: Our New Program Is Live!!!

Healthcare is changing faster than ever. From AI tools that process claims in seconds, to predictive models that identify high-risk patients before complications happen, the message is clear: AI is already reshaping care delivery.

But here’s the challenge:

  • Many AI tools are overhyped without evidence.

  • Implementation often fails because leaders don’t understand the unique complexities of healthcare.

  • Ethical and trust concerns still remain at the center.

That’s exactly why I created Become the Human in the Loop in Healthcare AI — a program designed for health leaders, executives, and non-technical professionals who want to lead responsibly in this new era.

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1. Is Wall Street losing faith in AI?

Tech stocks just experienced their worst week in years, raising questions about whether the AI boom is beginning to cool. The Nasdaq fell 3%, and major AI-heavy companies saw steep losses, suggesting that investor expectations may finally be too high for even strong earnings to satisfy.

The Details:

  • The Nasdaq Composite declined 3%, marking its roughest week since 2018 and signaling broad weakness in the tech sector.

  • Palantir, Oracle, and Nvidia all dropped sharply, with losses of 11%, 9%, and 7% respectively.

  • Meta and Microsoft fell about 4% even after reporting continued heavy investments in AI, showing that positive AI spending is no longer enough to boost confidence.

  • Economic pressures such as the government shutdown, weak consumer sentiment, and ongoing layoffs are adding further drag to an already strained market.

Why it Matters: 

This may be the first time in the AI boom where Wall Street is openly questioning sustainability instead of celebrating potential. Investors are no longer rewarding “AI spending” unless it comes with clear profitability. If this trend continues, we may see a shift from hype-driven valuations to real performance-driven expectations. The companies with true AI revenue, real use cases, and operational resilience will stand out — and the rest may get exposed.

2. Is OpenAI Losing Money on Every Response? Leaks Suggest the Math Isn’t Pretty

Leaked documents show how much OpenAI is actually paying Microsoft — and how expensive it is to run the world’s most powerful AI models. With nearly $1.4 billion in revenue-share payouts to Microsoft in under two years and rising inference costs that may exceed revenue, the financial pressures behind the AI boom are sharper than ever.

The Details:

  • OpenAI paid Microsoft an estimated $493.8 million in 2024 and $865.8 million in the first three quarters of 2025, based on a 20% revenue-share agreement.

  • Microsoft also pays OpenAI a share of Bing and Azure OpenAI revenue, but these offsets are not included in the leaked numbers, making the true balance unclear.

  • Inference costs — the cash required to run AI responses — may have reached $3.8 billion in 2024 and $8.65 billion in the first nine months of 2025.

  • These figures suggest OpenAI could be spending more to run its models than it currently earns, raising questions about the long-term economics of frontier AI.

Why it Matters: 

Behind the dazzling demos and billion-dollar valuations, AI has a very real cost — and the financial math is starting to look brutal. If OpenAI, the industry leader with Microsoft’s backing and massive scale, is struggling to make inference profitable, what does that mean for every smaller AI startup chasing the same dream? These leaks add fuel to growing concerns that the AI boom may be outpacing the business models needed to sustain it. And as compute demands keep rising, this financial pressure could reshape the entire AI ecosystem.

3. The Only Rule in AI Investing Now? There Are No Rules

Venture capitalists say AI has pushed startup investing into a completely new era—one where old rules no longer apply. With some AI companies hitting $100M revenue in a year and others struggling despite fast early growth, investors are rewriting their playbooks to prioritize data, defensibility, and relentless product velocity over traditional metrics.

The Details:

  • Investors say AI startups are growing so explosively that standard benchmarks no longer fit, pushing the industry into what VCs call a “funky time.”

  • Series A firms now evaluate founders on data generation, technical depth, founder history, and competitive moats rather than revenue alone.

  • Seed-stage companies are being judged with the same rigor once reserved for mature startups, especially around sales and go-to-market strategy.

  • AI founders are under pressure to ship updates at OpenAI- or Anthropic-level speed, while the market still has no clear “winner,” leaving room for newcomers to dethrone incumbents.

Why it Matters:

AI is reshaping not just technology but the economics of innovation itself. Investors are no longer looking for slow, steady growth—they’re hunting for teams that can move at frontier-model velocity while still building defensible moats. This shift will determine which founders get funded, which ideas survive, and how fast the next generation of AI products reaches the market. In this “funky time,” execution speed, technical depth, and customer obsession matter more than ever, and the winners may not be who everyone expects.

Stay tuned for more updates in our next newsletter!

Top 5 AI Tools Every Developer Needs for Bug-Free Releases

1. Perfecto

Perfecto offers AI-powered test automation for web and mobile apps with cloud-based real device testing. Its smart test analytics, heatmaps, and self-healing scripts make debugging and scaling tests far easier. Free trial available.

2. Mabl

Mabl empowers teams with AI-powered end-to-end testing, auto-healing scripts, and intelligent test coverage insights. Perfect for QA and DevOps teams building CI/CD pipelines. Free trial available.

3. Functionize

Functionize combines machine learning + natural language test creation so you can design tests using plain English. It automatically updates tests when your UI changes, reducing maintenance problems. Offers a free community edition.

4. Katalon

Katalon integrates AI-assisted test creation, smart locators, and test maintenance across web, mobile, API, and desktop apps. Its free version provides plenty of features for small teams and beginners.

5. Applitools

Applitools uses visual AI to detect UI bugs that traditional tests miss — layout shifts, color issues, broken elements, and responsiveness problems. Free plan available for individuals and open source contributors.

𝐈 𝐥𝐞𝐚𝐫𝐧𝐞𝐝 𝐭𝐡𝐢𝐬 𝐭𝐡𝐞 𝐡𝐚𝐫𝐝 𝐰𝐚𝐲…

𝐀 𝐦𝐨𝐝𝐞𝐥’𝐬 𝐜𝐨𝐧𝐟𝐢𝐝𝐞𝐧𝐜𝐞
𝐝𝐨𝐞𝐬𝐧’𝐭 𝐞𝐪𝐮𝐚𝐥 𝐢𝐭𝐬 𝐜𝐨𝐦𝐩𝐞𝐭𝐞𝐧𝐜𝐞.

AI will give you answers
with absolute certainty…
Even when it’s completely wrong.

It won’t hesitate.
It won’t second-guess.

It won’t say,
“Let me think about that again.”

In medicine, that’s dangerous.
Because confidence feels comforting.

But competence?
That’s what keeps patients alive.

And this is where people get fooled —
AI sounds sure.

Humans assume that means
it must be right.

But in reality…

A model can hallucinate confidently.
Predict inaccurately.
Miss edge cases.
Overfit patterns.
Misread context.

It can be 99% sure…
and still 100% wrong for your patient.

So the future of healthcare AI
won’t belong to the people who trust AI the most.
It’ll belong to the people
who understand its limits the best.

Because confidence is loud.
Competence is quiet.

And safety lives in the space between the two.



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𝐌𝐞: “𝐁𝐑𝐔𝐇𝐇𝐇… 𝐁𝐄 𝐒𝐄𝐑𝐈𝐎𝐔𝐒! | Umer Khan M.

AI: “No need to escalate.” The chart: looks like a crime scene investigation board 𝐌𝐞: “𝐁𝐑𝐔𝐇𝐇𝐇… 𝐁𝐄 𝐒𝐄𝐑𝐈𝐎𝐔𝐒!"

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⏱️ Stop wasting hours on manual testing.

Download your AI QA Starter Kit and learn how to use AI-generated test cases to strengthen your software instantly.

The AI QA Starter Kit.pdf76.07 KB • PDF File

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