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AI Testing Lab
The AI Testing Lab by JS Testing Academy
Learn, prototype and implement AI in software testing – from AI test agents and self-healing automation to testing LLM, RAG and MCP-based systems.
What we cover
AI for testing – and testing of AI
AI Testing
Where AI adds real value across test design, automation, execution and reporting.
AI Test Agents
Agents that read requirements, explore the app, generate and run tests, and report findings.
GenAI for QA
Prompt patterns for test cases, test data, bug reports, reviews and documentation.
Self-Healing Automation
Resilient locators and recovery strategies that keep suites green through UI changes.
AI Test Case Generation
Generate test cases from user stories, API specs and existing tests – reviewed by humans.
AI Test Data Generation
Synthetic, masked and boundary-value data at scale.
AI Defect Prediction
Use history and code-change signals to focus testing where defects are likely.
LLM Testing
Evaluate accuracy, hallucination, bias, safety and regression of LLM features.
RAG Testing
Test retrieval quality, grounding and answer faithfulness in RAG pipelines.
MCP for Test Automation
Connect AI assistants to browsers, APIs and test tools with the Model Context Protocol.
AI Testing Projects
Hands-on projects: AI-generated Playwright suites, test agents, LLM evaluation harnesses.
AI Testing POCs
A short, focused proof-of-concept of AI-assisted testing on your application.
Track 3 — AI Testing
Python + LLM + AI Agents + MCP + RAG
Our AI Testing project track takes testers from prompt basics to building and testing real AI-powered systems.
- Prompt engineering for testers
- AI-assisted Playwright / Selenium automation
- Building a simple AI test agent
- MCP servers for browser and API testing
- Evaluating LLM and RAG applications
Bring AI into your QA process
Training for your team or a POC on your product – start with a conversation.