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UXinsight Festival 2026: Getting Honest About UX Research
The festival challenged the myth of the neutral researcher and questioned what "rigour" really means. Insights often die in organizations, and democratization happened without proper infrastructure. AI mirrors old unsolved problems. The core question — what is a UX researcher in 2026? — remains open, and sitting with that uncertainty is a sign of a field paying attention
The next five years of research: A reality check
Five questions: synthetic users (useful for low-risk, but sycophancy bias); evaluation (traditional metrics fail AI); role expansion (generalist or deep methodologist — avoid middle); speed (judgment is scarce, not artifacts); data layer (knowing which question matters is the skill). AI collapses production — value migrates to judgment and credibility
NNG: How to Get Research Recommendations on the Roadmap
To influence the roadmap: join planning early, learn constraints, tie research to PM metrics, and give clear recommendations at the right time
AI: The permalink problem in AI chat
AI chat products have a fatal flaw: conversations have URLs, but individual messages don't — making valuable answers ephemeral. This is messaging-app architecture applied to knowledge work. Users resort to copying into notes or endless scrolling. The fix: per-message URLs, bookmarks, copy-link — treat the message as addressable. One fix resolves multiple failures
Experience: ResearchOps - How we organize UX Research Operations
ResearchOps is the set of practices that make UX research sustainable, organized, and repeatable: participant management, data storage (recordings, transcripts), and standardized templates (guides, reports). Benefits: better planning, consistent quality, traceability, and collaboration. Key habits: document early, define standards, organize data, stay flexible. ResearchOps is how you care about sharing knowledge and working as a team
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