Role-Based Programme
RB0609

JetBrains AI Assistant for Product & Service Management

Technical Discovery, Requirement Validation & Product Delivery

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Duration
4 Hours
Level
Awareness
Delivery
Instructor-Led
Format
Awareness Session

Programme Objectives

  • Understand how JetBrains AI Assistant can help product and service teams collaborate more effectively with software-development teams.
  • Explore AI-assisted code explanation, project-context analysis, technical questioning, and development-workflow understanding.
  • Experience converting product requirements and engineering artefacts into clearer technical discussions and acceptance expectations.
  • Discover practical applications for technical discovery, feature validation, defect understanding, and delivery coordination.
  • Recognise the importance of engineering validation, security, confidentiality, and human review when using AI-generated technical information.

Tools covered

JetBrains AI AssistantAI ChatProject ContextExplain CodeAI ActionsCoding AgentsDocumentation AssistanceTest GenerationCode Insights

Who should attend

  • Product Managers
  • Product Owners
  • Technical Product Managers
  • Digital Product Managers
  • Service Managers
  • Product Operations Professionals
  • Product Analysts
  • Business Analysts
  • Technical Business Analysts
  • Product Programme Managers
  • Product & Engineering Coordinators
  • Product / Service Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of product or service-management processes
  • Familiarity with requirements, user stories, acceptance criteria, or software-delivery workflows
  • Basic awareness of software-development terminology is helpful
  • Programming expertise is not required
  • No previous JetBrains AI Assistant experience required
  • Hands-on activities require access to a supported JetBrains IDE with AI Assistant enabled

TOC Modules

Concepts
  • Understanding JetBrains AI Assistant within IDE-based development workflows
  • Exploring AI Chat, project context, code explanation, AI Actions, and coding agents
  • Identifying relevant product-management use cases across discovery, development, validation, and delivery
  • Understanding the boundary between AI-assisted technical understanding and engineering authority
Practical activities
  • Exploring AI Assistant using a sample software project
  • Asking project-context questions about the application's purpose and structure
  • Creating a concise product-level summary of a technical component

Scenarios

Product Requirement to Engineering Discussion

Customer Need → Product Requirement → JetBrains AI Assistant → Existing Code / Project Context → Technical Questions → Engineering Validation → Refined Acceptance Criteria

Participants use AI Assistant to better understand how a proposed feature relates to an existing application and prepare more informed questions for engineering without treating AI output as an approved technical decision.

Customer-Reported Issue to Product Decision

Customer Issue → Reproduction Information → Relevant Code / Error Context → AI-Assisted Explanation → Engineering Validation → Customer Impact → Product Priority

Participants analyse a realistic product issue, translate technical information into business impact, and prepare the evidence needed for prioritisation and cross-functional resolution.

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