Overview

In an age where AI-driven interactions are shaping how people engage with brands and services, the ability to design clear, helpful, and human-centered conversations is a vital skill. This course focuses on conversation design—crafting voice and chatbot interactions that feel natural, intuitive, and inclusive. Throughout this course, learners will discover how to apply principles from UX design, linguistics, and human-computer interaction to create digital dialogues that resonate. From identifying user intent to designing personalities and multi-turn pathways, this course delivers actionable strategies for building better bots and voice interfaces. What sets this course apart is its unique blend of theoretical foundations and hands-on, real-world practices. You'll not only learn how to craft effective prompts and responses but also how to document, prototype, and test conversations that users love. This course is ideal for designers, developers, writers, and product professionals working on conversational interfaces. While no prior experience is required, a background in UX or content strategy will be helpful. Copyright © 2021 Diana Diebel and Rebecca Evanhoe. All rights reserved. Originally published by Rosenfeld Media, LLC. This course edition is published by Packt Publishing under license from Rosenfeld Media, LLC. No part of this material may be reproduced, distributed, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without prior written permission from the author or the publisher.

Syllabus

Why Conversation Design?

In this section, we examine structured conversation design, outlining core designer responsibilities and demonstrating how organized dialogue, tone, and turn-taking optimize voice and chat experiences, boosting efficiency, confidence, and satisfaction.

Talking Like a Person

In this section, we compare human and mechanical speech chains, analyze turn-taking signals-timing, overlap, repair-and examine cultural influences like accommodation, politeness, and code-switching to inform natural conversational system design.

Crafting Trustworthy Personalities

In this section, we connect interaction goals, personification depth, and power dynamics to design trustworthy AI personas, selecting tone and safeguards that avoid bias and support respectful, authentic conversations.

Designing Prompts

In this section, we design concise voice UI prompts by selecting open, menu, or yes/no questions, ordering words precisely, and removing jargon to reduce cognitive load and increase response accuracy.

Defining User Intent

In this section, convert user utterances to clear intents, add rich slots for fine-grained data, and apply iterative tuning to boost production Natural Language Understanding accuracy.

Documenting Conversational Pathways

In this section, we craft sample scripts to uncover user intents, translate them into audience-appropriate flow diagrams, and refine prompts to minimize NLU errors, ensuring aligned, reliable conversational designs.

Building Context

In this section, we map user memory tiers, temporal-spatial signals and device data to build adaptive, context-aware UIs, while defining ethical policies that protect sensitive information.

Complex Conversations

In this section, we design multimodal conversational flows that synchronize speech with on-screen states, ensure accessible multichannel experiences, and coordinate multiperson, multisession interactions across devices and languages.

Researching and Prototyping

In this section, connect market discovery to generative user experience (UX) research, craft low fidelity prototypes, run Wizard of Oz tests, and convert early feedback into clear, data backed design decisions.

Launching the Conversation

In this section, explore a step-by-step workflow for building and launching conversations, covering iterative design, team coordination, asset control, usability reviews, and data-guided testing.

Designing Inclusive Conversations

In this section, we surface implicit biases shaping design conversations and question 'edge case' assumptions, then apply codesign with diverse contributors to create inclusive, equitable product experiences.