Stefan’s mission is to inspire enterprises and technical writers around the world and show how to create compelling technical communication content with the Adobe Technical Communication solutions. Stefan is a certified Quality Management Professional (TÜV), ISO 9001/EN 15038 auditor, ISO 31000 Risk Management expert, and Six Sigma Champion. As a sought-after keynote speaker and moderator at conferences around the world, he has lived technical communication for more than 25 years.
Besides that, he has been the European Ambassador for GALA for many years, a member of the tekom Conference Advisory Board, and is a founding member of the iiRDS working group and the OASIS DITA Adoption Committee. Stefan is also the mastermind behind Adobe DITAWORLD, the world’s largest annual virtual event for technical communication. He was awarded by MindTouch as one of the Top 25 Leading Content Strategist Influencers in the world and one of the Top 25 Content Experience Influencers.
Who Are We Writing For? Rethinking Technical Communication for an AI-First Future
Co-presented with: Herb Toews
AI is transforming more than content creation—it is reshaping how technical information is managed, discovered, delivered, and consumed. As users increasingly rely on AI assistants instead of search engines and documentation portals, a fundamental question emerges: Are we still writing for humans, or are we creating knowledge for AI?
Join Herb Toews and Stefan Gentz for a fireside chat exploring what an AI-first world means for technical communication. They discuss why structured, accurate, and trusted content is becoming the foundation for AI-driven experiences, and how AI is changing content assessment, migration, creation, and delivery. The conversation also looks beyond technology to examine the evolving role of content professionals—from writers to architects and stewards of enterprise knowledge—and the skills organizations need to prepare for the future.
Here’s what you’ll learn in this session:
- Preparing content for AI: Understand why structured, accurate, consistent, and trustworthy source content is essential for reliable AI-powered experiences.
- Transforming content operations: Explore how AI can support content analysis, cleanup, consolidation, migration, creation, and delivery across the content lifecycle.
- Adapting to new consumption patterns: Learn how AI-mediated discovery is changing the way customers access information—and what that means for traditional content channels and customer journeys.
- Redefining the content professional: Consider how technical communicators can evolve from content creators into architects and orchestrators of knowledge and intelligent systems.
- Taking action today: Identify practical priorities that can help content teams prepare for the next generation of human and machine content consumers.
The Human Layer: Designing Content for Humans, Machines, and Everything Between
The role of technical communicators is undergoing a significant transformation. As AI systems increasingly generate, process, and deliver content, the question isn’t whether your job will change—it’s whether you’ll lead that change. This session challenges conventional thinking about documentation, arguing that traditional content delivery channels are being replaced by conversational interfaces and LLM-powered chat applications that retrieve and synthesize your content. But here’s the opportunity: someone must architect this new ecosystem.
Content now serves dual audiences—humans and machines. This demands new competencies: structured authoring, content APIs, and machine-consumable protocols. Yet the irreplaceable human layer remains: ethical judgment, user empathy, information architecture, and the strategic thinking that determines what content exists and why. This session equips you to thrive in this new landscape—not as a survivor, but as an architect of what comes next.
Here’s what you’ll learn in this session:
- Content must be designed for human readers and LLM consumption.
- Traditional delivery channels are shifting to conversational and voice interfaces.
- Structured content formats and APIs are essential new competencies.
- Human judgment, ethics, and empathy remain irreplaceable differentiators.
- Technical communicators are positioned to become content ecosystem architects.
You Can’t Prompt Your Way to Trust — Why trusted AI answers start with structured, governed knowledge
Generative AI can produce convincing answers, but no prompt can fix outdated sources, restore missing context, or resolve conflicts. As people and AI agents increasingly rely on conversational answers, trust must come from a governed knowledge foundation—especially when an incorrect content can lead to costly decisions. Building on DITA, metadata, taxonomies, knowledge graphs, and guardrails, Stefan Gentz explores how structured content becomes an operational knowledge system and discusses the anatomy of a trusted answer from governed source content through retrieval and reasoning to evidence, attribution, and controlled access. A trustworthy system must recognize when evidence is insufficient and refuse to invent answers. Stefan shows how unanswered questions, content-quality signals, human feedback, analytics, and evaluations create a continuous improvement loop—and why Technical Communication plays a critical role in building reliable knowledge for both humans and AI agents.
Here’s what you’ll learn in this session:
- Trust starts below the prompt: Understand why prompting alone cannot compensate for missing structure, context, provenance, or governance.
- Structure becomes knowledge: Explore how metadata, versions, taxonomies, and relationships enable contextual and multi-step reasoning.
- Trust by design: Learn how evidence, attribution, filtering, access control, and refusal reduce the risk of plausible but incorrect answers.
- One foundation, two audiences: See how governed knowledge can serve both humans and AI agents through conversational experiences, APIs, and MCP.
- Content gets a feedback loop: Discover how unanswered questions, analytics, feedback, and evaluations can expose knowledge gaps and drive continuous content improvement.
