WeTest.Athens 2026

Short one-liner: How Do We Trust Software Built by AI

Statement
AI agents are generating more code than ever, but how do you ensure its reliability? Learn why traditional testing fails and how Agentic Testing guarantees trust and scalability in AI-driven systems.

Abstract
AI agents are helping teams generate more code than ever before. Even the strongest believers in vibe coding caution against placing blind trust in that code. We are living through the fastest expansion of software creation in history, not because we hired more engineers, but because machines are now building software alongside us.This raises a fundamental challenge. How do you test and trust applications created by LLMs, assembled by multiple AI agents, and deployed by automated systems? The tools we rely on today were not designed for this reality or this speed. Unit tests and code reviews inspect logic and functions, but they were never meant to validate dynamic, evolving behavior. Traditional automation struggles when code is generated and modified continuously, becoming fragile and breaking faster than teams can maintain it. As AI agents become embedded into every layer of software, we are no longer just testing code. We are testing autonomous systems themselves.In this talk, we will explore why trust in AI-generated software can no longer be assumed, and why it must be continuously proven. Agentic Testing, the use of autonomous agents to test autonomous systems, emerges as the only scalable solution. These autonomous agents not only plan, execute, and analyze tests but also adapt and challenge systems the way real users would. Agentic Testing validates behavior, reasoning, and outcomes at the system level, ensuring that AI-driven systems meet real-world expectations.Drawing from real-world enterprise deployments and lessons learned building an AgenticTesting platform, this talk will reframe quality assurance as a strategic intelligence layer rather than a release-time checkbox. In the age of AI, trust isn’t just a feature, it’s a continuously earned asset. We’ll discuss how businesses can evolve their testing strategies to stay ahead in this rapidly shifting landscape.

Key Takeaways
● Why trust in AI-generated software must be continuously proven, not assumed.
● How Agentic Testing validates AI-driven systems by testing behavior, reasoning, and outcomes.
● Real-world insights on implementing Agentic Testing for scalable, autonomous validation.