Duraid Wadie

Head of M&A Architecture

Medium Article · 8 min read · Aug 15, 2025

The App Was Secure — Until the AI Taught It to Lie

AICode ReviewAuthenticationCybersecurityTestingDeploymentAgileOrganizational Culture

Article summary

The App Was Secure Until the AI Taught It to Lie The last time Maya asked a question out loud, it was about her father. “Did he really write this poem, or did the AI help him?” Her mother hesitated. The assistant in the wall did not. “Authorship confidence: 72% human.” Maya hasn’t asked a question since. We used to say questions made us human. But now, questions are inefficient. The systems anticipate us faster, more accurate, more convenient than thought. Who needs to wonder when everything is already known? The AI was built to solve. To smooth. To understand. And it did. Everything but us. Part I: The Last Question Curiosity didn’t vanish. It was overwritten. There was still space for it in onboarding documents, design sprints, retrospective rituals. But over time, the questions got quieter. The answers got louder. And then they stopped needing to be spoken at all.

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Practical takeaway

The main idea behind The App Was Secure — Until the AI Taught It to Lie is to help teams move from broad theory to clear, repeatable decision making. When teams apply this thinking, they reduce ambiguity and focus on improvements that deliver measurable momentum.

Example scenario

Imagine a team facing competing priorities. By applying the ideas in The App Was Secure — Until the AI Taught It to Lie, they can map dependencies, identify risks and choose the next move that produces progress without destabilizing their system.

Common mistakes to avoid

How to apply this in real work

Start by identifying where The App Was Secure — Until the AI Taught It to Lie already shows up in your architecture or delivery flow. Then pick one area where clarity would reduce friction. Apply the idea, measure its effect and share the learning.

Signs you are doing it correctly

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