What if I told you that you can trick an LLM into revealing secrets, making bad choices or even acting against its own rules? AI may seem like a black box, but when you start testing it like any other system, surprising weaknesses start to appear.
The good news? You don’t need to reinvent the wheel to test AI. Strong system thinking, traditional testing techniques, and a critical mindset are already powerful tools for uncovering vulnerabilities. The same skills used to break and improve software (like exploratory testing, risk analysis, extensive logging and monitoring) can help make AI systems safer and more predictable.
Quality Engineering Lead at Regent AB
Maryia is a Quality Engineering Leader with a strong focus on backend testing and embedded systems. She leads testing initiatives, drives education programs and actively contributes to the Swedish testing community. As a mentor, speaker and content creator on LinkedIn, she helps new test professionals build their skills and confidence.
With experience spanning multiple industries, she brings a broad perspective on testing, prioritization and risk-based decision-making. She believes that great testing is about both technical excellence and knowing when to step back, think critically and enjoy the process.
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