mabl Announces Next-Generation Agent-Based Testing Platform for the AI Development Era

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mabl has announced "Active Coverage," a next-generation agent-based testing platform for the AI development era. This new suite of features is designed to address quality challenges in rapid AI coding agent development and support continuous quality assurance.

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mabl has announced "Active Coverage," a next-generation agent-based testing platform for the AI development era. This new suite of features is designed to address quality challenges in rapid AI coding agent development and support continuous quality assurance.

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Source: https://prtimes.jp/main/html/rd/p/000000016.000104559.html | Date: Date unavailable

This release introduces mabl's "Active Coverage" feature, a quality verification capability designed to maximize the speed of AI coding agent development without hindering it, addressing challenges highlighted in the company's "2026 State of Quality Engineering Report." May 12, 2026 — As an AI-native company that has provided enterprise testing platforms since 2017, mabl today released a new set of features designed to maximize the speed of "agent-based development," which has garnered significant attention recently, from the perspective of continuous quality assurance. This new feature set, called "Active Coverage," provides essential capabilities for enterprise quality assurance as the speed and scale of AI-driven code generation continue to rapidly expand within organizations across all industries. This feature release coincides with the announcement of the findings from mabl's "2026 State of Quality Engineering Report," a survey of approximately 1,000 software professionals. The report confirms a widening gap between the speed of code generation and quality verification. The report reveals that opinions are almost evenly split among teams currently using AI coding agents: 41% reported that "AI improved code quality," while 37% stated that "code generation speed improved, but quality declined," highlighting that the biggest factor determining whether AI improves or degrades quality lies in a team's quality foundation. Dan Belcher, co-founder of mabl, states: "Coding agents can write and release code faster than any development team in the past, but it's also true that agents evaluating their own work have a bias towards prioritizing release over quality. Our enterprise customers told us that the quality management layer must be independent of development and must not impede its speed at all. We have rebuilt mabl as that foundational layer. This is an 'Agent-based Quality Platform' that tests both human-created and AI-generated code with the same rigor as an indep

mabl Announces Next-Generation Agent-Based Testing Platform for the AI Development Era

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