Conference Schedule
Full day of sessions, workshops, and networking opportunities.
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Ensuring Software Quality in the world of AI Developers
Like it or not, AI agents can now turn a loosely written paragraph of requirements into a pull request that looks production-ready in minutes. That’s impressive — and horrifying. When code is being generated faster than humans can fully internalize it, QA becomes the last line of defense between “seems fine” and a 2 a.m. incident caused by a misunderstood requirement or a bad database migration. In this session, we’ll explore how quality practices must evolve in a world where teams treat AI agents like new junior developers. We’ll talk about strengthening test plans so they validate intent instead of just implementation, expanding automated coverage to catch AI-specific failure modes, and partnering closely with developers whose familiarity with the generated code may be thinner than in years past. We’ll look at redefining code and feature review processes, improving requirement clarity to reduce ambiguity before it becomes defects, documenting our new vibe coded enterprise systems, and adding guardrails so AI-authored changes can’t slip past quality gates unchecked. By the end, you’ll have a clear understanding of the new risks AI introduces — and practical strategies to help your team move fast without letting AI-generated pull requests quietly YOLO their way into prod.
Matthew-Hope Eland
The Day Testing Died — And Quality Evolved
Twenty years ago, my job was to break software. I was trained to think in edge cases, failure paths, and regression suites. If something slipped into production, it meant I missed something. Back then, quality meant testing. Then the world changed. Agile arrived. DevOps arrived. Continuous delivery arrived. And I realized something uncomfortable: quality was never about the test cases. It was about the system behind them. And now AI has changed the ground again. Today, code is written by machines. Tests are generated by copilots. Reviews are assisted by algorithms. So if machines can write the tests… Who is responsible for trust? That question is why we must evolve — from testers, to quality champions, to AI validation designers.
Tatyana Arbouzova