Scaling Trust, Not Automation - Rethinking Quality for the AI Era
As AI reshapes how software systems are developed and delivered, most organizations still ask how to scale automation faster. In doing so they overlook a deeper challenge: AI doesn't merely automate tasks, it delegates judgment and decision-making in ways conventional systems never did.
Unlike traditional automation, which fails loudly and predictably, AI systems often fail silently — confident but incorrect outputs, context drift, and culturally misaligned responses that erode confidence over time. These failure modes demand a new approach to quality that goes beyond test coverage and accuracy metrics.
This session reframes quality engineering for AI-driven systems by treating trust as a first-class architectural concern. Attendees will learn why correctness must be defined in context, why benchmarks and pass/fail tests are insufficient, and how to design practical evaluation frameworks that scale with real-world complexity.
Key Takeaways:
A clear distinction between scaling automation and scaling trust.
Understanding AI-native failure modes missed by traditional QA.
A framework for defining correctness in complex, context-dependent systems.
Practical guidance on assigning accountability for AI decisions.
About the speaker
Walter Zimerman:
Walter Zimerman is a Senior Software Development Engineer in Test with extensive experience designing and validating large-scale, distributed systems. His work focuses on quality engineering, test architecture, and trust at scale, particularly in environments where automation, AI, and complex decision-making intersect. Over the years, Walter has worked on high-impact systems where correctness, reliability, and user trust are critical, helping teams move beyond traditional pass/fail testing toward more resilient and evaluative quality practices. He has deep experience with automation frameworks, system-level testing, and designing guardrails for highly dynamic, data-driven systems. Walter explores how quality engineering must evolve when systems no longer simply execute instructions but generate answers users are expected to trust. Walter regularly speaks with engineers and quality leaders about scaling quality responsibly in modern systems, advocating for trust as a first-class architectural concern rather than a byproduct of automation.
About
TestMu Conf
Testμ (TestMu) is the world’s largest virtual conference on agentic engineering and quality, built by the community, for the community. As AI reshapes how we build, test, and ship software, Testμ Conf is where you connect, grow, and lead: agentic workflows, autonomous quality, battle-tested AI playbooks, hands-on workshops, and the engineering culture driving it all.
More Sessions
Join the builders, testers, and innovators shaping the next generation of web experiences.
Testμ Conf 2026 is where they meet.
