First, Understand … the Mess

Before we organize, we must understand. Before we build the structure, we must sit with the mess. This theme is a return to IA’s foundational practice: deep, careful comprehension of a problem space before any design decision is made. In an era when tools generate structure faster than humans can evaluate it, “first, understand” is both a discipline and a form of resistance: a commitment to the kind of slow, attentive work that produces structures that actually fit the people who use them.

The dominant model of IA practice assumes a known problem space: you research, you model, you build, you test. But increasingly, practitioners are asked to design systems for content that hasn’t been created, users who haven’t been identified, and contexts that are actively changing. IA has always been a discipline of sensemaking, but the pressures of modern product development increasingly push practitioners to skip the understanding phase and go straight to structure. AI-generated content, multi-modal interfaces, and rapidly shifting organizational priorities all challenge the idea that good IA produces stable, enduring structures. How to understand when things are unpredictable, technology is shifting fast, and AI generated models are involved, where designers aim to design something stable–or flexible, before structure.

This theme creates space for talks on research methods, stakeholder listening, content discovery, domain expertise, and the specific kinds of understanding that only come from sustained attention, not from prompting a model. It also raises the question of what “understanding” means across cultures, languages, and communities.