The software testing profession has been around for approximately 70 years, yet nothing has fundamentally transformed it to deliver on what it was always capable of. The majority of our industry has delivered "glorified clerical work" in the name of testing. Industry reports show that almost 70% of testing capacity is spent on testing-related activities, while only 30% is devoted to actual testing that creates real value.Organizations have been trying to automate away all things testing for decades. It never worked because the real value of testing comes from the intellectual part i.e. asking the right questions, critical evaluation, risk analysis, deep exploration, and informed decision-making. But mastering this craft requires years of investment that organizations see as overhead. Hence, the widespread acceptance of "testing as artefact-building" - easy to automate, but without substantial value.What if you could deliver at scale and speed without compromising the value real testing creates? Agentic Quality Engineering gives every tester access to expert-level thinking without years of investment. AI agents built on 47 years of combined practitioner experience based on the award-winning QCSD (Quality Conscious Software Delivery) framework, context-driven approaches, risk-based thinking, deep exploration techniques - all encoded into 41 specialized skills and 30 purpose-built agents. The agents are self-learning, building institutional knowledge over time. They collaborate with other agents, with humans, and with existing systems. This isn't automation replacing testers; it's accumulated wisdom amplifying what testers can do from day one.
Key takeaways:
- Expert Thinking, Accessible: Leverage decades of encoded testing expertise without years of personal skill developmentHands-On Agent Orchestration: Configure, understand and run multi-agent pipelines that involve AI agents to support test activities across the entire SDLC. It includes 6 Core Agents, 2 Performance Agents, 3 Strategic Agents, 4 Advanced and 3 Specialized agents. More yet, 11 purpose-built agents for widespread coverage of important testing activities.
- The PACT Framework: Evaluate agentic quality systems using Proactive, Autonomous, Collaborative, Targeted principles
- Self-Learning & Collaborative Systems: Understand with practical hands-on how these agents build institutional knowledge and collaborate with humans and systemsProduction-Ready Tools: Leave with a configured environment and open-source framework (MIT license) — nothing held backPersonal Adoption Roadmap: Design a concrete plan tailored to your context with clear first steps
