An open-source agentic QA harness with memory.

This submission presents an open-source agentic QA harness. The core value proposition lies in automating quality assurance processes using AI agents, specifically incorporating "memory" to enhance their effectiveness. This addresses a critical pain point in software development: the labor-intensive and error-prone nature of manual QA. The trend towards agentic systems for operational tasks is accelerating, driven by the promise of increased efficiency and reduced human intervention. Open-source distribution lowers adoption barriers, fostering community contributions and rapid iteration. For B2B SaaS, this signals a growing market for specialized AI agents and frameworks that integrate into existing development workflows, particularly in testing and validation, where reliability and context retention are paramount.