The Quality Triad and GATING Methodology provide a powerful framework for ensuring high-quality software products. By making products easy to test, understand, and maintain, organizations can improve product quality, reduce risks, and accelerate time-to-market.

•  Testability: By setting quality gates at various stages of the development lifecycle, it's possible to identify and address testability issues early on.
•  Observability: It ensure that products are instrumented with the necessary logging, monitoring, and tracing capabilities to provide visibility into their internal state. This makes it easier to diagnose issues and troubleshoot problems.
• Sustainability: GATING can help to ensure that products are designed and built to be maintainable, scalable, and resilient.

AI/ML-driven Quality Engineering is transforming the way software is tested, offering significant benefits in terms of efficiency, effectiveness, and accuracy. Here are some key areas where AI/ML is making a significant impact:

• Automated testing improves efficiency, accuracy, and speed by automating repetitive tasks, reducing human errors, and accelerating the testing process.
• Predictive analytics empowers proactive testing by anticipating potential problems, reducing risks, and efficiently allocating testing resources.
• Intelligent test case generation using AI/ML automates test case creation, ensures comprehensive coverage, and adapts to code changes.

iAgami's Full-Stack Quality Engineers are instrumental in delivering exceptional product quality.

•  Quality Assurance to Quality Engineering: The transition from QA to QE represents a significant shift in approach to ensuring software quality. QE adopts a more proactive and engineering-centric perspective.
•  Test Management to Quality Orchestration:This shift likely involves moving beyond simple test case management to a more comprehensive approach that integrates testing activities across the entire development lifecycle, including planning, execution, and reporting.
• Quality Metrics and Analytics: By defining and tracking key performance indicators (KPIs) and analyzing data, we gain valuable insights into our quality efforts.