The Content Wrangler webinar channel is serving up another strong slate of one-hour educational events for technical writers and other information development professionals who want help making sense of where content strategy, technical communication, AI, structured content, metadata, localization, and knowledge management are headed next.
The lineup features an impressive range of experts, including Sharon Burton, Rob Hanna, Ed Grzetich, Rahel Bailie, Sarah O’Keefe, Katie Williamson Sebkhi, Susan Kraft-Yorke, Anne Malinda, Justyna Hietala, Jason Kaufman, Torsten Machert, Wendy Lewis, Mark Pepper, and Louise Stengard Kristiansen.
Together, these professionals explore everything from AI-powered retrieval and messaging misalignment to traceable knowledge, documentation quality, semantic layers, structured content, localization strategy, and the hidden role metadata plays in helping people find and trust the information they need.
Hear untold stories that shaped technical communication as Sharon Burton, content strategist and editor, takes you behind the scenes of her new anthology, Women in Technical Communication (2026 XML Press). Discover how this groundbreaking collection came to life—and why documenting our history matters now more than ever.
Register
Rob Hanna, CEO and Co-Founder of Precision Content, will dissect the critical role that source material plays in determining whether your AI delivers value or disappointment. Explore the real reasons behind “bad content in, bad content out” and discover practical steps you can take to ensure your AI-generated output meets expectations. You’ll gain actionable insights on how to identify weak points in your existing content pipeline and strategies for transforming flawed inputs into high-quality results.
Register
Join Ed Grzetich, Technical Documentation Specialist, as he shares research from over 21,000 integration tests revealing a surprising insight: documentation format impacts AI-generated code quality more than which model you use. You’ll see why the wrong format can cause smaller models to fail completely, while optimized formats empower both advanced and basic AI tools to deliver better results.
Register
