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changing really quickly—if you don’t revise your plan in a few months, you’re building for a world that’s already outdated."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"You should get good at prompt engineering by using AI a lot, not by memorizing outdated tricks."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
"There was a feeling at Brex that research was sometimes conducted for the sake of research, not resulting in impactful insights."
Ned Dwyer Emily Stewart James WallisThe Intersection of Design and ResearchOps
September 24, 2024
"Identity is not monolithic; policies should address layered experiences."
Reginé GilbertAsking the Right Questions: Life, Hope and Moving Forward During the Pandemic
June 10, 2022
"Corporate capture of research has brought amazing good things but changed the truth to power role."
Steve PortigalLooking Back…to Look Ahead
March 26, 2024
"We moved from versioning the entire system quarterly to individually versioning components, so changes are easier to track and prioritize."
PJ Buddhari Nate BaldwinMeet Spectrum, Adobe’s Design System
June 9, 2021
"Everyone has a customer — whether external users, third-party vendors, or internal colleagues; those humans consuming your product are your customers."
Jeff GothelfWho does what by how much?
November 20, 2025
"We created AI OKRs allowing our team members to experiment and then share their findings with the team."
Ebru NamaldiDesigning the Designer’s Journey: Scaling Teams, Culture, and Growth Through DesignOps
September 11, 2025
"We cannot remove barriers we aren’t aware of."
Samuel ProulxDesigning beyond caricatures: Embracing real, diverse user needs
December 4, 2024
"You can have an effect size that matters in practice but isn’t statistically significant, like five users failing a key task in usability testing."
Caroline Jarrett Erin WeigelHave fun with statistics?
December 12, 2024
"Managing up and across started with lots of coffees and questions to build a mental model of the organization."
Rob Mitzel Sébastien MaloThe Tale of Two Companies: Building a Successful UX Practice in a Century-Old Enterprise
January 8, 2024
