Role-Based Programme
RB0345

Windsurf for Quality Management

Strengthen Software Quality, Testing & Release Assurance with AI

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Duration
16 Hours
Level
Intermediate
Delivery
Instructor-Led
Format
Capability Training

Programme Objectives

  • Develop functional proficiency in using Windsurf across software-quality analysis, test design, defect investigation, regression testing, and release assurance.
  • Apply AI-assisted codebase understanding to identify quality risks, affected components, dependencies, and areas requiring deeper testing.
  • Build reusable workflows for test generation, debugging, code-quality review, defect remediation, and regression validation.
  • Use structured quality criteria and engineering evidence to validate AI-generated code changes before release.
  • Apply secure coding, human review, traceability, governance, and responsible AI practices across software-quality workflows.

Tools covered

Windsurf / Devin DesktopCascadeFast ContextIntegrated IDE & Debugging ToolsRulesAGENTS.mdWorkflowsSkillsTerminalMCP Integrations

Who should attend

  • Quality Managers – Software / Digital Products
  • Quality Assurance Managers
  • Software Quality Engineers
  • QA Engineers
  • Test Engineers
  • Automation Test Engineers
  • SDET Professionals
  • Quality Analysts
  • Application Quality Professionals
  • Software Test Leads
  • Release Quality Professionals
  • Quality Engineering Team Leads

Prerequisites & Participant Readiness

  • Working understanding of software quality assurance and testing
  • Familiarity with software requirements, defects, test cases, and release processes
  • Basic understanding of source code and software-development workflows
  • Familiarity with Git or version-control concepts is helpful
  • Basic programming or test-automation knowledge is beneficial
  • General awareness of generative AI is helpful
  • No previous Windsurf course completion required

TOC Modules

Concepts
  • Understanding AI-assisted software development and its impact on software-quality practices
  • Exploring Windsurf/Cascade for code analysis, editing, debugging, terminal operations, and contextual assistance
  • Understanding Fast Context for locating relevant files and code areas within large repositories
  • Mapping AI support across Requirements → Build → Test → Review → Release
Practical activities
  • Exploring a representative application and identifying its major quality-critical components
  • Mapping Quality Activity → Windsurf Capability → Human Validation → Quality Outcome

Scenarios

Feature Change to Governed Release Quality Gate

Business Requirement → Acceptance Criteria → Codebase Impact Analysis → AI-Assisted Code Change → Unit & Integration Tests → Defect Resolution → Regression Testing → Quality Evidence → Release Review

Participants validate a realistic software enhancement from requirement through release readiness while ensuring that AI-generated changes and tests are independently reviewed against defined quality criteria.

Production Defect to Preventive Quality Improvement

Production Issue → Logs & Code Context → AI-Assisted Investigation → Root-Cause Validation → Controlled Fix → Targeted Tests → Regression Suite → Quality Rule / Workflow Update → Release Assurance

Participants investigate a recurring software defect, validate the corrective change, and convert lessons learned into reusable quality controls to reduce the probability of similar defects in future releases.

[1]: https://windsurf.com/editor?utm_source=chatgpt.com ""Devin Desktop | Devin""
[2]: https://docs.windsurf.com/ro/windsurf/cascade/memories?utm_source=chatgpt.com ""Cascade Memories""
[3]: https://docs.windsurf.com/zh/windsurf/cascade/cascade?utm_source=chatgpt.com ""Windsurf - Cascade""
[4]: https://windsurf.com/docs/MSA.pdf?utm_source=chatgpt.com ""Windsurf
Data Use Guidelines
(specific to Exaf"

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