Role-Based Programme
RB0387

Ollama for Product & Service Management

Private AI for Product Research, Requirements & Decision Support

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Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Build foundational capability to use Ollama for private/local AI-assisted product research, customer-feedback analysis, requirements development, and product documentation.
  • Select suitable models based on product-task requirements, capability, infrastructure, privacy, and performance considerations.
  • Convert customer feedback, research notes, product documents, and service information into structured insights and requirements.
  • Explore structured outputs, embeddings, and tool-enabled workflows for repeatable product-management applications.
  • Apply human validation, product judgement, access controls, data confidentiality, and responsible AI practices when using locally or externally hosted models.

Tools covered

OllamaOllama Model LibraryLocal & Cloud ModelsOllama CLIOllama APIModelfileStructured OutputsEmbeddingsTool CallingVision-Capable Models

Who should attend

  • Product Managers
  • Product Owners
  • Technical Product Managers
  • Digital Product Managers
  • Service Managers
  • Product Operations Professionals
  • Product Analysts
  • Business Analysts
  • Product Strategy Professionals
  • Service Design Professionals
  • Innovation Managers
  • Product / Service Management Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of product or service-management processes
  • Familiarity with customer feedback, product requirements, roadmaps, or service-improvement activities
  • Basic familiarity with generative AI is helpful but not mandatory
  • No advanced programming expertise required
  • Guided technical exercises may use basic command-line or API examples
  • No previous Ollama experience required
  • Appropriate organisational approval should be obtained before using confidential, regulated, personal, or proprietary information

TOC Modules

Concepts
  • Understanding Ollama as a platform for running and working with different AI models
  • Exploring local versus cloud model execution and implications for product workflows
  • Understanding model differences across text, reasoning, vision, tool use, and embedding tasks
  • Mapping product activities across Discover → Analyse → Define → Prioritise → Communicate
Practical activities
  • Exploring the Ollama environment and available model catalogue
  • Running a selected model against a simple product-management question
  • Comparing outputs from different model choices
  • Mapping product tasks to appropriate model capabilities

Scenarios

Customer Feedback to Prioritised Product Improvement

Customer Feedback → Ollama Local Model → Theme Classification → Problem Statements → Structured Requirements → Product Comparison → Product-Team Validation → Prioritisation Input

Participants use a controlled AI workflow to transform customer feedback into structured product insights and requirement drafts while retaining final prioritisation with accountable product stakeholders.

Product Knowledge to Internal Product Assistant

Product Documentation → Embeddings / Knowledge Retrieval → Ollama Model → User Question → Grounded Response → Product-Team Validation → Reusable Internal Assistant

Participants explore how Ollama can support a product knowledge assistant that retrieves relevant information from approved product documentation and generates responses for internal product or service-management use.

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