The Future of Software Quality: SD Times Announces “AI in Test” 2026 Supercast Series
As software environments grow increasingly complex, the role of Artificial Intelligence in quality assurance is transitioning from a futuristic concept to an operational necessity. To address this shift, SD Times has unveiled its 2026 Supercast Series: AI in Test, a year-long program designed to help organizations navigate the integration of AI-driven automation, autonomous agents, and emerging protocols.
The series kicks off on February 5, 2026, with a deep dive into AI-Driven Testing: Context, Agents, and the Model Context Protocol (MCP). This session focuses on how context-aware AI and standardized protocols like MCP can solve the persistent challenges of testing distributed systems and maintaining quality in legacy codebases.
A Roadmap for the AI-Augmented Tester
The Supercast series is structured as a quarterly progression, guiding you through different facets of the AI revolution:
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May 7 – The ROI of Intelligent Quality: A look at the business side of AI, focusing on how to measure productivity gains and justify the investment in intelligent testing tools.
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August 6 – The AI-Augmented Tester: This session shifts to the human element, exploring the specific tools, skills, and techniques testers need to thrive alongside AI.
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November 5 – The Strategic Test Future: The series concludes with a vision of autonomous agents and the evolving nature of human-AI collaboration.
Bridging the Gap Between Hype and Value
Led by industry experts including David Rubinstein (Editorial Director of SD Times) and Arthur Hicken (Senior Software Evangelist at Parasoft), the series aims to move beyond industry buzzwords. We will explore practical applications such as AI-driven API testing, contract testing, virtualization, and the use of “Deep Code Quality” agents.
As organizations strive for reliable Continuous Testing, the “AI in Test” series provides a unified framework for delivering value. Registration is currently open for software leaders and practitioners looking to stay ahead of the curve in an AI-first development lifecycle.
