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Agentic Testing

Agentic testing is a quality assurance approach where autonomous AI agents plan, execute, and refine test workflows without prewritten scripts. Powered by large language models, these agents perceive application UIs, reason through workflows, and self-heal when the software underneath them changes — operating closer to how a human tester works than to how a traditional automation framework runs.

5 articles

  • Three-layer Pipeline diagram showing MCP Server Testing with DeepEval, Pytest, and TestQuality CLI

    Agentic QA

    How to Test MCP Servers with DeepEval

    MCP server testing is the practice of validating that a Model Context Protocol server exposes the right tools, passes the right context, preserves session state across turns, and returns…

    Jose Amoros · · 20 min read

  • How Does AI-Driven Test Creation Reduce QA Workload?

    Agentic QA

    How Does AI-Driven Test Creation Reduce QA Workload?

    AI-driven test creation cuts the most time-consuming parts of QA, freeing engineers to focus on strategy, exploration, and edge cases instead of typing the same scenarios over and over. If…

    Jose Amoros · · 9 min read

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