Role-Based Programme
RB0430

Meta AI & Manus for Product & Service Management

Build AI-Assisted Discovery, Planning & Product Workflows

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Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Build foundational capability in using Meta AI and Manus across product discovery, research, requirements, planning, and stakeholder communication.
  • Analyse customer, market, competitor, product, and service information to identify themes, opportunities, and validation questions.
  • Create structured requirements, product briefs, prioritisation frameworks, research reports, and management deliverables.
  • Apply agentic AI to execute multi-step product-management tasks while maintaining appropriate human checkpoints.
  • Maintain evidence validation, customer-data privacy, intellectual-property awareness, and human ownership of product decisions.

Tools covered

Meta AIManus AIDeep ResearchFile & Data AnalysisDocument & Presentation GenerationAI AgentsWeb-Based Research & Task Execution

Who should attend

  • Product Managers
  • Product Owners
  • Service Managers
  • Digital Product Managers
  • Product Analysts
  • Product Operations Professionals
  • Product Strategy Professionals
  • Service Design Professionals
  • Customer Experience Managers
  • Product Innovation Professionals
  • Product & Service Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of product or service management
  • Familiarity with customer needs, product requirements, research, roadmaps, or product reviews
  • General awareness of generative AI is helpful
  • Basic experience working with business documents and spreadsheets is beneficial
  • No coding or AI-development expertise required
  • No previous Meta AI or Manus course completion required

TOC Modules

Concepts
  • Understanding conversational AI, research assistants, and autonomous AI agents
  • Comparing Meta AI for rapid research, reasoning, file analysis, and content creation with Manus for delegated multi-step task execution
  • Mapping AI support across Discover → Define → Prioritise → Plan → Deliver → Improve
  • Differentiating AI-generated recommendations from accountable product decisions
Practical activities
  • Exploring representative product and service-management requests in both tools
  • Mapping Product Activity → Meta AI / Manus Capability → Expected Outcome

Scenarios

Customer Problem to Prioritised Product Opportunity

Customer Feedback → AI-Assisted Analysis → Market & Competitor Research → Problem Definition → Product Requirements → Prioritisation Matrix → Product Review → Roadmap Recommendation

Participants convert fragmented customer and market information into a structured product opportunity while retaining human ownership of evidence validation, prioritisation, and roadmap decisions.

Product Opportunity to Agent-Generated Decision Package

Product Objective → Manus Task Delegation → Research → Information Analysis → Product Brief → Presentation → Product Manager Review → Refinement → Stakeholder Decision

Participants delegate a multi-step product assignment to an AI agent and evaluate the resulting deliverables for accuracy, relevance, assumptions, and business value before stakeholder use.

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