As pixel-by-pixel testing erodes under brittle release cycles and unpredictable LLM outputs, teams face a critical stability gap. This roundtable moves past the AI hype to deliver stable, hybrid testing architectures, providing practical frameworks to merge image-based and object-based automation without sacrificing deterministic regression pipelines.
Upcoming Web Seminars
AI-accelerated development is forcing a fundamental shift in software governance. This session examines how engineering and QA teams must redefine traditional handoff models, team structures, and release criteria when manual code review cannot keep pace, ultimately transforming the QA function from an execution gatekeeper into a strategic quality orchestrator.
Accelerate deployment without sacrificing quality. This live demo explores how to leverage AI tools like Amazon Bedrock within your QA workflow to close critical test coverage gaps. Learn to manage the unique risks of AI-generated code, unify manual and automated testing, and instantly turn test data into natural-language release signals.
Tired of brittle tests and endless selector maintenance? Discover how image-based automation and self-healing scripts keep your tests running even when UI elements move. This quick, technical demo compares Selenium with Keysight Eggplant to show you how to build resilient, cross-application test automation that scales.
When AI accelerates code generation, the entire software delivery lifecycle changes. Discover how to build modern software teams where specialized agents and humans collaborate side by side. Learn how specifications replace traditional backlogs as the source of truth, and gain a concrete model for integrating autonomous agent execution into your workflows.
Rapid AI code generation creates massive testing bottlenecks across test creation, pipeline execution, and failure triage. Utilizing AI agents to orchestrate pipelines, automate root-cause analysis, and resolve test failures allows engineering teams to accelerate quality and scale delivery without sacrificing system reliability or control.