Designing AI-first products on top of a rapidly evolving technology
This video is featured in the AI and UX playlist.
Summary
This talk addresses the distinct challenges of designing AI-first products when the foundational technology is advancing at an unprecedented pace. We will discuss the practical implications of this rapid evolution on the design process and share our insights into creating effective user experiences in such a dynamic environment.
Key Insights
-
•
AI models evolve faster than previous tech revolutions, requiring adaptive product development.
-
•
Effective AI products use evals—automated tests on real data—to continuously measure quality.
-
•
Retrieval augmented generation and tool use are practical architectural tricks to reduce AI hallucination.
-
•
AI experiences must account for user trust despite AI’s confident but sometimes inaccurate outputs.
-
•
Human factors like worker anxiety about job security are critical to address in AI adoption.
-
•
Cross-disciplinary teams are essential in AI design due to the space’s novelty and uncertainty.
-
•
Prompt engineering skills grow best through extensive real use rather than frozen techniques.
-
•
Planning AI products with expectations of improved capabilities 6-9 months ahead optimizes outcomes.
-
•
Cultural acceptance of AI use inside organizations must be actively encouraged to avoid user hiding.
-
•
User testing of AI products still requires old-school observation combined with analytics and evals.
Notable Quotes
"You can’t have good AI without good information architecture."
"Everything’s changing really quickly—if you don’t revise your plan in a few months, you’re building for a world that’s already outdated."
"Hallucinations are when AI makes up stuff—it's a fundamental property of these models."
"Retrieval augmented generation is just adding results from a search into the model’s context to make it more grounded."
"Agents are models using tools in the loop, calling normal software functions as part of their process."
"People tend to trust AI a lot because it seems very confident—even when it’s not always accurate."
"Workers are often worried about layoffs and their value when AI speeds up their process, while executives like the efficiency gains."
"You should get good at prompt engineering by using AI a lot, not by memorizing outdated tricks."
"Building evals is like building tests to know if your AI system is good enough, and you can rerun them as models improve."
"User testing for AI still means watching people use it, plus collecting analytics and running evaluations."
Or choose a question:
More Videos
"Processing limits and licensing terms currently restrict how much video and audio these AI tools can handle."
Llewyn Paine[Demo] Deploying AI doppelgangers to de-identify user research recordings
June 5, 2024
"About 200,000 digital health products exist, but only 1% of 1% have FDA clearance for accuracy."
Daniel J. RosenbergDigital Medicine Design
September 26, 2019
"One of the core questions of research strategy is how do you decide what research to do when demand exceeds resources."
Chris Geison Cristen Torrey Eric MahlstedtWhat is Research Strategy?: A Panel of Research Leaders Discuss this Emergent Question
March 4, 2021
"Understanding the problem independent of the solution is key to finding the solution that somebody will actually adopt."
Jim KalbachJobs To Be Done
February 25, 2021
"An error might not be immediate; data can be fine when collected but deteriorate over time and cause problems later."
Caroline JarrettGarbage in, garbage out? Measuring error rates to get ready for AI
January 8, 2026
"Can you testify right now that all your digital properties are accessible to disabled users?"
Suzan Bednarz Hilary SunderlandAccessibilityOps for All
January 8, 2024
"Over-enforced design system adoption bred resentment and low morale, despite good adoption metrics."
Rachael Greene Alison DavisBuilding a Design Ops Practice that Really Works (Most of the Time)
October 2, 2025
"Someone who thinks a study will run perfectly every time probably isn’t very experienced or realistic."
Steve Portigal Susan Simon-Daniels Tamara Hale Randolph Duke IIWar Stories LIVE! Q&A-Discussion
March 30, 2020
"People tend to support what they actively help create."
Laura WeissThere is No Playbook: Leader as Coach During Challenging Times
April 26, 2024
