Role-Based Programme
RB0432

Meta AI & Manus for Product / Service Management

Advanced Product Intelligence, Agentic Research & AI-Assisted Lifecycle Execution

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Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced expertise in using Meta AI and Manus across product discovery, market research, requirements, prioritization, roadmap planning, launch, adoption, and service improvement.
  • Apply conversational and agentic AI to investigate complex product questions, synthesize customer and market evidence, and produce decision-ready deliverables.
  • Build structured multi-step workflows for product research, competitive intelligence, requirement development, product analysis, stakeholder communication, and lifecycle management.
  • Use AI agents to execute substantial research and documentation tasks while maintaining clear checkpoints, source validation, and human product ownership.
  • Apply customer privacy, intellectual-property protection, factual validation, responsible AI, and governance throughout AI-assisted product workflows.

Tools covered

Meta AIManus AIConversational AIAgent ModeDeep / Wide ResearchWeb & Source ResearchFile & Document AnalysisMultimodal AnalysisAI-Assisted WritingData AnalysisPresentation CreationStructured DeliverablesMulti-Step Agentic TasksBrowser-Based ResearchTask Planning & Reusable Product Workflows

Who should attend

  • Senior Product Managers
  • Product Directors
  • Group Product Managers
  • Product Owners
  • Technical Product Managers
  • Digital Product Managers
  • AI Product Managers
  • Service Managers
  • Product Strategy Professionals
  • Product Operations Professionals
  • Product Analysts
  • Customer Experience Professionals
  • Innovation Managers
  • Portfolio Management Professionals
  • Product & Service Transformation Leaders

Prerequisites & Participant Readiness

  • Working knowledge of product or service-management practices
  • Experience with product discovery, requirements, roadmaps, customer feedback, launches, or product reviews
  • Familiarity with business research, documents, spreadsheets, presentations, and digital information
  • Basic understanding of generative AI tools and prompting is helpful
  • Ability to critically validate AI-generated research and recommendations
  • No programming expertise required
  • No previous Meta AI or Manus course required

TOC Modules

Concepts
  • Understanding conversational AI, reasoning assistance, autonomous agents, and multi-step task execution
  • Mapping Meta AI and Manus capabilities across the end-to-end product and service lifecycle
  • Differentiating quick AI assistance, research-intensive work, and autonomous agent execution
  • Understanding human product ownership across strategy, prioritization, customer commitments, and roadmap decisions
Practical activities
  • Comparing conversational and agentic approaches for the same product-management task
  • Mapping current product workflows to appropriate AI modes
  • Creating a reusable Objective → Context → Sources → Constraints → Deliverable framework

Scenarios

Customer Problem to Product Investment Decision

Customer Feedback & Research → Meta AI / Manus Synthesis → Market & Competitor Analysis → Product Opportunity → PRD → Prioritization → Product Strategy → Business Recommendation → Leadership Review → Human Investment Decision

Participants use conversational and agentic AI to transform customer and market evidence into structured product decision support while keeping prioritization, investment, and roadmap commitments under accountable human ownership.

Product Launch to Continuous Improvement

Approved Product Strategy → Launch Plan → Cross-Functional Readiness → Customer Adoption & Feedback → AI-Assisted Performance Analysis → Improvement Opportunities → Roadmap Options → Product Leadership Review → Human Decision

Participants build an advanced AI-assisted product lifecycle workflow that connects launch execution, adoption intelligence, customer feedback, and roadmap improvement while preserving human ownership of product and customer-impacting decisions.

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