More The EvilTester Show episodes
Published 12 Feb 2026
Duration: 00:57:35
Agentic AI is transforming software development with autonomous agents that observe, collect data, reason, and perform actions to achieve goals, enhancing task success rates and switching focus from manual code inspection to output validation and quality assurance.
This podcast episode is a chat with Dragan Spiridonov who created the Agentic QE fleet. Agentic AI for Quality Engineering. It can work with code, or...
The podcast explores the concept of agentic AI in software development, highlighting its distinct approach compared to traditional large language models (LLMs). Agentic AI integrates autonomous agents that can observe, gather data, reason, and perform actions to achieve specific objectives, enhancing automation and decision-making in complex workflows. The discussion traces the evolution of agentic AI from simple prompt engineering to more sophisticated context engineering and full agentic development, which has led to significantly higher task success rates.
A key focus of the conversation is the agentic QE system, a quality-oriented orchestration tool designed to support the entire software development lifecycle. This system includes functionalities such as test planning, test case generation, and evaluating test effectiveness, and it operates as a fleet of specialized agents that handle different aspects of testing. These agents provide deeper insights and broader expertise than individual testers could achieve alone. The system is built using orchestration frameworks like Claude Flow and is designed to be vendor-independent, enabling integration with various LLMs and supporting multiple environments.
The podcast also emphasizes the role of human oversight and expert evaluation in maintaining the reliability of agentic AI systems. Continuous performance assessment ensures that the agents remain effective and aligned with quality goals. As agentic AI advances, it is expected to shift responsibilities in software development, focusing more on output validation and quality assurance rather than manual code inspection, potentially transforming the roles of developers and testers.
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