CEOs Are Blinded by the AI Hype

CEOs think AI will magically make developers code faster. Spoiler: it won’t.

👋 Hello, this is Valentina with the free edition of the Optivem Journal. I help Engineering Leaders & Senior Software Developers apply TDD in Legacy Code.

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Everyone’s talking about AI adoption — Copilot, ChatGPT, or other coding tools. The promise sounds irresistible:

“Developers will code faster → we’ll deliver more → profit!”

CEOs see the headlines, get excited, and push AI adoption as the top priority. But there’s a hidden trap…

The Real Bottleneck

The speed of coding is not the bottleneck. The real blocker? Regression bugs.

“We spend most of our time fixing stuff that used to work!”

Without proper automated tests, faster coding just means faster bug creation, leading to longer debugging cycles and slower delivery.

AI Can’t Fix This Alone

Sure, you could try “let AI write the tests.” But:

The problem is, AI tools are trained on public datasets and code samples - often badly written tests.

• AI often produces fragile or irrelevant tests—the problem is, it’s trained on public datasets and code samples, which are often badly written.

• Tests may pass but don’t verify the right behavior

• AI may change tests just to make code pass, instead of fixing the bug

The result? Green tests that give false confidence and are expensive to maintain.

The Missing Foundation: ATDD

In order to use AI to truly accelerate delivery, we need to adopt ATDD:

1. Write acceptance tests first

2. Use AI to implement code to make the tests pass

With this foundation:

✅ Regression bugs are caught within hours, not weeks

✅ AI can help safely accelerate coding

✅ Tests remain maintainable and reliable

Takeaway

Adopt ATDD before chasing AI coding speed.

Code-first AI without ATDD = faster coding, slower delivery.

🚀 Get Started with ATDD

I’m opening the ATDD Accelerator 2026 to help teams set up acceptance tests and safely integrate AI: atdd.optivem.com