About this episode
Are you prepared for the hidden UX taxes that AI and LLM features might be imposing on your B2B customers—without your knowledge? Are you certain that your AI product or features are truly delivering value, or are there unseen taxes that are working against your users and your product / business? In this episode, I’m delving into some of UX challenges that I think need to be addressed when implementing LLM and AI features into B2B products.
While AI seems to offer the change for significantly enhanced productivity, it also introduces a new layer of complexity for UX design. This complexity is not limited to the challenges of designing in a probabilistic medium (i.e. ML/AI), but also in being able to define what “quality” means. When the product team does not have a shared understanding of what a measurably better UX outcome means, improved sales and user adoption are less likely to follow.
I’ll also discuss aspects of designing for AI that may be invisible on the surface. How might AI-powered products change the work of B2B users? What are some of the traps I see some startup clients and founders I advise in MIT’s Sandbox venture fund fall into?
If you’re a product leader in B2B / enterprise software and want to make sure your AI capabilities don’t end up creating more damage than value for users, this episode will help!
Highlights/ Skip to
Improving your AI model accuracy improves outputs—but customers only care about outcomes (4:02)
AI-driven productivity gains also put the customer’s “next problem” into their face sooner. Are you addressing the most urgent problem they now have—or used to have? (7:35)
Products that win will combine AI with tastefully designed deterministic-software—because doing everything for everyone well is impossible and most models alone aren’t products (12:55)
Just because your AI app or LLM feature can do ”X” doesn't mean people will want it or change their behavior (16:26)
AI Agents sound great—but there is a human UX too, and it must enable trust and intervention at the right times (22:14)
Not overheard from customers: “I would buy this/use this if it had AI” (26:52)
Adaptive UIs sound like they’ll solve everything—but to reduce friction, they need to adapt to the person, not just the format of model outputs (30:20)
Introducing AI introduces more states and scenarios that your product may need to support that may not be obvious right away (37:56)
Quotes from Today’s Episode
Product leaders have to decide how much effort and resources you should put into model improvements versus improving a user’s experience. Obviously, m
