Free Lesson

Turn User Messages into AI Assistant Flows

Hosted by Dr. Carmen Martinez

Wed, Jul 8, 2026

4:00 PM UTC (1 hour)

Virtual (Zoom)

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What you'll learn

Map messy user requests

Use AI to identify user goals, recurring intents, and patterns in real conversational data.

Design assistant response paths

Turn user intents into answer, clarification, repair, and handoff options for an AI assistant.

Create a reusable flow blueprint

Build a lightweight conversation design blueprint for chatbots, copilots, and AI-powered products.

Why this topic matters

Most AI assistants do not fail because the wording is slightly off. They fail because teams have not translated user language into system behavior. In this lesson, you’ll learn a practical workflow for turning messy user requests into intents, response paths, repair moments, and escalation logic for AI products.

You'll learn from

Dr. Carmen Martinez

Conversational AI & Agentic UX strategist, author, and educator

I have a PhD in Applied Linguistics, a technical foundation in Data Science and AI, and 8+ years of experience designing AI-powered customer experiences across chatbots, voicebots, IVR, automation, LLM-based assistants, and multi-agent systems.

I’ve worked on real-world AI products for companies including Flix, Philip Morris International, and Deutsche Telekom. My work sits where language becomes product behavior: intent classification, routing, uncertainty, repair, escalation, memory, tool use, and human handoff.

I teach practitioners how to move beyond surface-level copy and design useful, trustworthy AI products: defining what systems should do, how much autonomy they should have, and how users remain informed and in control.

Previously at

Flix
Deutsche Telekom
Philip Morris International
Jimdo
See all products from Carmen

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