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AI-Driven Autonomous Testing

1 post · Jun 2026

What this trail covers

LinkedIn has developed a Quality Assurance (QA) Agent, an AI-driven autonomous testing system that reimagines software quality. This system leverages generative AI and Vision-Language Models (VLMs) to create agents capable of navigating and testing mobile and web applications. The agent uses a hybrid architecture combining deterministic replay (System 1) for stable flows and VLM-based planning (System 2) for dynamic scenarios. Evaluators act as guardrails, and a human-in-the-loop process allows for natural language test authoring and verification. The system has successfully identified bugs and regressions, and aims to democratize quality ownership.

All LinkedIn trails
  1. Quality Assurance Agent: Reimagining Software Quality with AI-Driven Autonomous TestingThis post details the engineering effort behind LinkedIn's QA Agent, an AI-driven autonomous testing system. It describes the hybrid architecture combining System 1 (deterministic replay) and System 2 (VLM-based planning) to balance cost, latency, speed, and reliability. Key technical contributions include the multi-model approach for different cognitive tasks (planning, analytical reasoning, visual grounding), the use of view trees and action history for state representation, and the implementation of evaluators (View Tree, Tracking Log, Action History) and an Error Detection Pipeline as guardrails. The post also highlights the novel approach to democratizing quality by using an LLM to synthesize raw user interactions into high-level, semantic natural language instructions for test authoring.