Designing AI Powered Products

SKU: NTV-QADAIPP

178.350 kr.

This course equips professionals with the skills to design, evaluate, and plan AI-enabled products with intelligent agents at their core. Participants will move from identifying opportunities through to building a pilot roadmap without writing any code.

Using a mix of demos, collaborative exercises, and design sprints, learners will understand how AI agents think (brain), remember (memory), and act (tools). They will explore how to map these capabilities into user journeys, build guardrails for safety and trust, and ensure solutions deliver real organisational and user value.

Forkröfur

Participants should have:

  • A basic understanding of AI concepts and applications
  • An interest in user experience and product design
  • No coding experience required

Target audience

This course is designed for:

  • Product managers and innovation leads exploring AI capability integration
  • UX and service designers shaping AI-enabled user experiences
  • Business analysts and strategists evaluating AI opportunities
  • Stakeholders involved in cross-functional product delivery teams

Nemandi mun læra eftirfarandi

By the end of this course, learners will be able to:

  • Frame AI opportunities in alignment with organisational goals and user needs.
  • Map the brain–memory–tools model to product features and integration points.
  • Apply human–AI interaction models (co-creation, augmentation, delegation) in design.
  • Evaluate AI outputs for accuracy, bias, usability, and trustworthiness.
  • Design and implement guardrails for responsible and ethical use.
  • Translate product concepts into blueprints and MVP delivery roadmaps.
  • Collaborate effectively with cross-functional teams, bridging product and technical roles.

Samantekt

Module 1: AI in Product Design

  • What AI agents are (and how they differ from automation and chatbots)
  • The Brain–Memory–Tools model for AI capability design
  • Strategic alignment: Linking AI features to organisational goals
  • Exercise 1 – AI Alignment Case Study: Assess whether features create value for users and organisations

Module 2: Designing AI-enabled Features

  • Principles of user-centred AI product design
  • Mapping AI capabilities into the user journey
  • Human–AI interaction models for different contexts
  • Exercise 2 – Redesign with AI Agent Capability: Map “before/after” workflows and layer in AI features

Module 3: No-code AI Agent Build

  • Facilitator demo: Building an AI agent in n8n (trigger, brain, memory, tools, guardrails)
  • Case example: Outlook + Teams + task tracker → Relaiy agent
  • Lessons learned: integration, tone, scheduling, escalation rules
  • Discussion: How this demo translates into product planning

Module 4: From Concept to Blueprint

  • Structuring product blueprints with AI touchpoints
  • Exercise 3 – Product Design Sprint with AI Blueprint: Build end-to-end concepts (personas, journey, AI features, guardrails, metrics)
  • Team sharing and reflections

Module 5: Evaluating AI Features for Quality & Trust

  • Testing for accuracy, bias, and usability
  • Spotting hallucinations and designing for graceful failure
  • Building feedback loops and controls into product design
  • Exercise 4 – Black Mirror Test: Stress-test your AI concept against “bad headline” failure scenarios

Module 6: AI Pilot Plan

  • Moving from blueprint to MVP and pilot design
  • Defining pilot scope, data needs, and success measures
  • Outlining delivery dependencies and cross-functional roles
  • Exercise 5 – AI Pilot Plan: Teams draft pilot charters

Exams and assessments

There are no formal exams in this course. Participants will complete guided exercises, group challenges, and a final capstone project to apply their knowledge and receive peer and instructor feedback.

Hands-on learning

  • Real-time demonstrations of generative AI API usage
  • Guided prompt engineering and prototyping sessions
  • Group projects using real-world case study inspiration
  • Peer-led presentations and instructor feedback on solution design