Claude Code for Quality Management
Advanced AI-Assisted Testing, Code Review & Quality Engineering
Programme Objectives
- Develop advanced expertise in using Claude Code across software testing, quality engineering, code review, defect investigation, regression assurance, and release validation.
- Architect reusable AI-assisted quality workflows covering requirements, test strategy, automated testing, defect resolution, security review, and quality gates.
- Integrate Claude Code with repositories, CI/CD processes, external QA tools, and enterprise systems through GitHub Actions and MCP.
- Automate repetitive quality-engineering activities while maintaining traceability, permissions, validation, and human approval.
- Establish scalable governance practices for using agentic AI safely within enterprise software-quality processes.
Tools covered
Who should attend
- Quality Engineering Managers
- Software Quality Managers
- QA Leads
- Quality Assurance Engineers
- Software Development Engineers in Test
- Automation Test Engineers
- Software Test Architects
- Senior Test Engineers
- Software Validation Professionals
- DevOps Quality Engineers
- Application Quality Professionals
- Technical Quality Leads
- Release Quality Managers
- Software Engineering Leads
Prerequisites & Participant Readiness
- Working knowledge of software testing and quality-engineering concepts
- Familiarity with functional, integration, regression, and automated testing
- Basic programming or scripting proficiency
- Familiarity with Git, repositories, and software-development workflows
- Experience with command-line or IDE environments is recommended
- Basic understanding of CI/CD pipelines is beneficial
- Previous Claude Code training is not required
TOC Modules
- Understanding Claude Code as an agentic coding environment for software-quality workflows
- Mapping Claude Code capabilities across requirements, testing, debugging, review, and release assurance
- Understanding autonomous actions, tool use, permissions, and human approval boundaries
- Analysing a sample repository from a quality-engineering perspective
- Building an end-to-end Claude Code-assisted QA workflow for the project
Scenarios
Enterprise Feature from Requirement to Quality Release
Participants use Claude Code across the complete software-quality lifecycle, building traceability from requirements through testing, defect resolution, regression assurance, and final release approval.
Production Defect to Automated Quality Improvement
Participants investigate a complex production defect, implement and validate corrective changes, strengthen automated coverage, and convert lessons learned into a reusable quality-engineering workflow.
*Claude Code currently supports project instructions through CLAUDE.md, CLI-based agentic workflows and tool permissions, MCP connections to external systems, and GitHub Actions automation for tasks such as code review, issue handling, pull-request creation, and bug fixing.*
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