AI-Ready SDET Training
50 Hands-On Labs
Explore the complete set of practical labs across AI-assisted testing, automation, agents, MCP, APIs, databases, CI/CD, n8n and RAG.
Complete Lab Catalogue
All 50 labs in one place.
The labs progress from focused AI-assisted activities to connected workflows, agents and engineering solutions.
01Build an End-to-End Jira-to-GitHub QA WorkflowRetrieve requirement → analyze → generate tests → automate →
review → commit.
02Build a Collaborative Multi-Agent QA TeamCreate specialized AI agents that collaborate to complete an
end-to-end testing task.
03Generate a New Playwright Test Inside an Existing
FrameworkCreate automation that follows existing Page Objects, fixtures,
utilities and coding standards.
04Debug a Failed UI Test End-to-EndCombine browser state, network traffic and console evidence to
identify the likely root cause.
05Build an Autonomous QA Workflow with n8nOrchestrate AI, Jira, APIs, GitHub and notifications in one
workflow.
06Build an AI Requirement Analysis AssistantAnalyze requirements for ambiguity, missing acceptance
criteria, risks and testability.
07Build a Playwright Automation AgentCreate an agent specialized in implementing automation inside
an existing framework.
08Generate API Tests from an OpenAPI ContractTurn API specifications into positive, negative and boundary
tests.
09Generate Playwright API Automation with AICreate automated API tests directly from API contracts and
business requirements.
10Generate a CI/CD Pipeline with AIUse an AI agent to create or improve GitHub Actions for test
execution.
11Add AI-Powered Debugging to CI/CDAutomatically analyze logs, screenshots and traces when tests
fail.
12Build an AI Failure-Triage AgentAnalyze test evidence and identify likely application,
automation or environment failures.
13Build a Domain-Aware Debugging AgentRun a failed test and use project documentation to diagnose the
issue.
14Create Reusable Claude Code QA SkillsPackage project-specific QA knowledge into reusable AI
capabilities.
15Analyze Network Requests with AIInvestigate failed, slow or unexpected API calls directly from
a running browser flow.
16Turn an Ambiguous Requirement into a Complete Test SuiteUse AI to identify gaps, ask clarifying questions and generate
stronger test coverage.
17Find Test Coverage Gaps with AIMap tests to requirements and risks and identify missing
coverage.
18Build an Automation Healing FlowDetect a broken automation test, propose a repair and require
approval before changing code.
19Design a RAG-Based QA ArchitectureUnderstand how documents, embeddings, retrieval and LLMs work
together.
20Choose the Right AI Approach for a QA ProblemDecide whether the problem needs prompting, project
instructions, a Skill, an Agent, MCP, n8n or RAG.
21Repair a Poor AI-Generated Test SuiteDetect missing, duplicate, invalid and hallucinated test cases
and improve the AI output.
22Generate a Risk-Based Test StrategyUse AI to identify what should be tested first and why.
23Generate a Risk-Focused Test Plan with AITurn project or release information into a concise,
risk-focused test plan.
24Optimize Test Data Combinations with AIProduce useful data combinations while eliminating redundant
coverage.
25Prioritize Regression Testing with AIIdentify Must Run, Should Run and Can Defer tests when
execution time is limited.
26Generate Actionable Test Execution Reports with AITurn raw test results into concise engineering and management
summaries.
27Make AI Understand an Existing Automation FrameworkLet Copilot analyze repository architecture, conventions and
reusable components before writing code.
28Refactor Automation into Page Object / Component
ArchitectureUse AI to improve structure, reuse and maintainability.
29Transform Playwright Codegen into Production-Quality
AutomationTransform recorded browser code into maintainable enterprise
automation.
30Audit an Automation Framework with AIDetect inconsistent locators, waits, assertions, utilities and
design practices.
31Review AI-Generated Automation CodeUse AI to detect framework violations and poor automation
practices.
32Debug and Repair Playwright Tests with AIDiagnose automation failures using test code and runtime
evidence.
33Modernize Legacy Selenium Tests with AIImprove old locators, waits, Page Objects and duplicated
code.
34Diagnose Selenium Project and Configuration Errors with
AIUse AI to investigate framework, build and runtime
failures.
35Test Application Behavior Under Slow Network ConditionsUse browser tooling and AI to inspect timeouts, loading states
and error handling.
36Build an AI-Powered API Testing ToolGive an AI agent controlled access to APIs for testing and
validation.
37Build an AI-Powered Code Review ToolConnect AI to code/repository context and generate structured
review findings.
38Build an Independent Code Review AgentCreate an independent reviewer that validates AI-generated
automation.
39Build a Lead QA AgentOrchestrate multiple specialist agents and manage handoffs and
rework.
40Analyze Complex JSON Responses with AIUnderstand deeply nested API responses and identify meaningful
validation points.
41Generate DTOs / POJOs / Typed API Models with AIAutomatically create reusable data models from complex
JSON.
42Generate Complex SQL Queries with AITurn business validation questions into SQL for database
verification.
43Build a Playwright Best-Practices SkillMake Claude consistently generate automation according to your
framework standards.
44Run Automated Tests in an AI-Generated PipelineExecute Playwright/API/Selenium tests and preserve reports and
diagnostic evidence.
45Classify Pipeline Failures with AIDetermine whether failures are product defects, automation
issues, environment problems or test-data issues.
46Generate Actionable Test Execution Summaries with AITurn noisy CI output into concise actionable QA
summaries.
47Automatically Draft Jira Defects from Failed TestsConvert test evidence into a defect draft for approval.
48Run Private QA Tasks with a Local LLMExperience private local AI execution for testing
scenarios.
49Design a Stateful QA Workflow with LangGraphModel requirement analysis, test generation, review and rework
as an agent workflow.
50Optimize Token Usage and AI CostsReduce unnecessary context, redundant model calls and
uncontrolled agent loops.