Role-Based Programme
RB0386

Ollama for Product & Service Management

Explore Private AI Prototyping, Model Evaluation & Product Workflows

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

Programme Objectives

  • Understand how Ollama enables product teams to experiment with different AI models through local and cloud execution options.
  • Explore product use cases involving summarisation, customer insight, knowledge assistants, structured outputs, and AI-enabled workflows.
  • Identify suitable models and capabilities for different product requirements, privacy expectations, performance needs, and user experiences.
  • Experience the process of moving from an AI product idea to a simple proof of concept and validation plan.
  • Recognise security, data privacy, model-quality, evaluation, and human-oversight requirements before introducing AI features into products or services.

Tools covered

OllamaOllama Model LibraryLocal & Cloud ModelsOllama APIEmbeddingsStructured OutputsTool Calling

Who should attend

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

Prerequisites & Participant Readiness

  • Basic understanding of product or service management
  • Familiarity with customer needs, requirements, product features, or digital services
  • General awareness of generative AI is helpful
  • Basic understanding of APIs or software products is beneficial but not mandatory
  • No programming expertise required
  • No previous Ollama experience required

TOC Modules

Concepts
  • Understanding Ollama as a platform for running and interacting with multiple AI models
  • Comparing local model execution with optional cloud-model execution
  • Mapping AI opportunities across Discover → Prototype → Validate → Integrate → Improve
  • Understanding why model choice can influence capability, speed, infrastructure needs, and product experience
Practical activities
  • Exploring available models and running a representative product-management prompt
  • Mapping Product Need → AI Capability → Model Option → Expected Outcome

Scenarios

Product Documentation to AI Knowledge Assistant Concept

Approved Product Documents → Embeddings / Retrieval Concept → Ollama Model → Source-Grounded Response → Product-Team Validation → User Experience Prototype

Participants explore how a controlled product-knowledge experience can answer user questions using approved information while defining quality, privacy, source-validation, and human-review requirements.

AI Feature Idea to Product Evaluation Decision

Customer Need → AI Feature Requirement → Candidate Ollama Models → Output Comparison → Quality / Latency / Privacy Evaluation → Product Review → Pilot Decision

Participants evaluate multiple model options against defined product criteria and prepare a structured recommendation for whether the proposed AI feature should proceed to a controlled pilot.

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