UX Evolved - Strategically fusing UX+AI

Whitney's back. Third time on the couch, which officially makes her the Andy Richter to my Conan.
I went into this one wanting to talk about knowledge hoarding. You know the instinct: if I'm the only one who knows how to do this, they can't get rid of me. Take my Tinker Toys and go home. Whitney flipped that on me pretty quickly. On her team, nobody's hiding anything on purpose. They're moving so fast they're building the conveyor belt while standing on it, and they're drowning in documentation. The people who can cut through that noise and get everyone on the same page are the ones she needs most right now.
We got into why her team is documenting more than ever, and why designers have had to accept they aren't the only ones responsible for design quality anymore. We talked about what happens when a PM drops a screen they built in Claude on your desk and logs off for the day, what engineers are teaching designers about constraints that don't exist anymore, and why a rebrand you can ship with the flip of a switch still might not be ready to ship. (I'm still recovering from a single hex value change to a calendar color. Long story.)
Whitney also shared how she trains her team on AI like she's handing down a family recipe, and why "I don't know" is one of the bravest things a leader can say, once you've earned the trust to say it. Stick around for the end. A road trip conversation with ChatGPT changed how she thinks about what AI can and can't do, and it's the reason she'd protect one design ritual above all others.
0:00 Whitney returns for episode three 0:36 How people respond when AI changes the job 2:03 How AI know-how travels on Whitney's team 4:15 Afraid of AI, or afraid of a colleague using AI? 6:17 Are design teams documenting more or less? 8:41 Design craft moves into systems and AI training 9:28 Hoarding or just moving too fast? 11:32 Vibe coding and the signals that count 13:12 When a PM hands you a screen built in Claude 15:50 What engineers teach designers about old constraints 19:14 A rebrand on the heels of a redesign 21:24 Does shared understanding survive a world of agents? 23:39 The family recipe approach to AI training 25:50 Saying "I don't know" in front of your team 28:29 The one ritual worth saving 29:36 Why AI can't design for delight 32:12 Wrap-up

Every AI feature makes a promise it can't fully keep: trust me, even when I'm wrong. Users rarely see a confidence score. They never see a training set. All they get is the interface in front of them.

In this episode of UX Evolved, host Eric Ellis sits down with Heidi Chow — a product manager by way of UX design — to unpack what trust in AI actually looks like at the interface level. Heidi has spent her career designing for the moments users have to decide whether to believe what a system is telling them: from an AI-powered feature that scanned users' teeth to confirm treatment fit, to her current work building AI tools that ground answers in real source material instead of asking users to take them on faith.

Eric and Heidi get tactical about the patterns that build (or break) user confidence in AI-driven products: the copy choices that signal certainty versus possibility, when and how to bring a human into the loop, what to show a user versus what to keep behind the scenes, and why designing trust in after the fact rarely works as well as designing it in from day one.

Chapters:
00:00 – Intro: AI trust from an experience angle, not just a tech angle
01:08 – Welcome & background: from recruiter to anthropology to UX bootcamp
04:10 – Heuristics that still hold up in the AI era: why feedback and transparency matter
08:00 – Case study: the Byte AI aligner fit scan
09:20 – The "may" vs. "can" distinction — subtle copy, real trust implications
16:08 – Human-in-the-loop: opt-in checks, user agency, and avoiding "AI slop"
18:01 – Confidence scores: what clinicians saw vs. what users saw
21:17 – Legal, regulatory, and copy decisions in a health context
23:12 – Testing AI-driven copy: evaluative research and A/B reactions
24:53 – Building Prequel: surfacing compliance requirements with AI agents
26:58 – Founder life: judging AI output quality without an expert safety net
29:10 – Can trust be retrofitted into an "AI-first" product?
29:46 – The "layer cake" model of trust: UI, data, and system-prompt layers
32:18 – Where UX designers still add value as UI work gets commoditized
33:22 – Vibe-coding in Claude Design: a product-detail-page example
34:19 – Closing thought: AI gets you 80% there — humanity closes the gap
35:47 – Final question: what would you redesign in the universe?

UX Evolved is a show about how AI is reshaping the practice of user experience — hosted by Eric Ellis. Guests are practitioners who've lived the trade-offs firsthand — designers, PMs, and founders building real AI-powered products.

What if the clearest view of where UX is headed isn't inside our industry — but outside of it?
Dr. Travis Bell spent 12 years in broadcast journalism before stepping back to study what happens when technology reshapes a profession from the inside out.
As an Associate Professor of Digital and Sports Media at the University of South Florida and a researcher focused on media framing, he's watched sports journalism get automated, consolidated, and fragmented — and he's drawn some uncomfortable conclusions about what gets lost when we let algorithms do the storytelling.
Sound familiar?
This conversation goes places most UX podcasts never do. We use sports media as a mirror to examine what's actually happening in design and product — the automation of craft, the return of the one-person band, the fragmentation of trusted sources, and the deep risk of AI trained on historically biased data presenting its output as objective truth.
Dr. Bell closes out Season 1 of UX Evolved. It's a fitting end to a season built on the premise that UX is evolving — not disappearing — and that the practitioners who will thrive are the ones willing to look beyond the tools and interrogate the craft itself.
Guest: Dr. Travis Bell, Associate Professor of Digital & Sports Media, Director of Graduate Programs & Research, Zimmerman School of Advertising and Mass Communications, University of South Florida
Host: Eric Ellis, UX Evolved
📩 Newsletter: https://ericwebdesigner.substack.com/
💼 Connect with Eric: https://www.linkedin.com/in/ericellisdesign
#UXDesign #AIAndDesign #UXEvolved #MediaFraming #ProductDesign

Whitney Tolley was our first-ever returning guest on UX Evolved — and for good reason. When she joined us last time, she left us with a line that stuck: if designers keep seeing themselves as UI generators, they'll be replaced. A lot has happened since then.
Figma MCP is real. Agentic workflows are real. And Whitney — Design Director at Cloudbeds — has been living inside all of it. In this conversation, we go beyond the hype to talk about what's actually changing on design teams right now: how power dynamics between designers and engineers are shifting, why synthetic user research is a legitimate pre-screening layer (not a replacement for real humans), and what the role of design looks like when the cost of building collapses.
Her closing answer alone is worth the listen: she wasn't using AI wrong — she was using it to speed up a broken process instead of questioning whether that process needed to exist at all.
In this episode:
00:00 — Introduction
01:22 — Has the definition of what designers own changed?
02:57 — Figma MCP and escaping "polish and fix" mode
04:38 — How AI is shifting power dynamics between design and engineering
06:11 — A real example: AI agents closing backlog bugs in 15 minutes
07:20 — What a designer's week actually looks like now
08:20 — Designers as trust builders in an AI-slop world
09:26 — AI collapses the build cycle — does prioritization change?
10:00 — Designing with context, not just coverage
12:09 — Is human judgment in research changing?
12:33 — How Whitney uses synthetic AI users in lean research
14:55 — AI-assisted heuristic evaluation: speed without replacing instinct
17:23 — The growing overlap between UX and product management
18:31 — Where does UX fit in agentic enterprise SaaS?
19:11 — The UX maturity model as a survival framework
20:52 — Does Figma have a future?
25:06 — Are your products agent-friendly? The question every team should be asking
26:10 — Who are we hiring in 2027? (Spoiler: unicorns)
29:18 — Specialization isn't dead — it's a quality gate
30:08 — "Fail fast" vs. "fail forward"
31:34 — Closing question: what do you wish you'd known when we first recorded?
32:16 — The biggest unlock: stop optimizing broken processes, rebuild them
Connect with Whitney Tolley:LinkedIn: https://www.linkedin.com/in/whitneydoyle/Claire Vo's podcast (referenced in episode): https://www.youtube.com/watch?v=I5X4_mYoiM8Connect with UX Evolved:Substack: https://ericwebdesigner.substack.com/LinkedIn: https://www.linkedin.com/company/uxevolvedUX Evolved is a podcast for UX professionals navigating the AI transformation of design. New episodes drop monthly.

"The biggest thing PMs get wrong about UX? That it's just about the UI. It's actually about psychology."
Blanca Barragan — PM at Versapay, Forbes Technology Council member — knows that the best product decisions happen when there's healthy tension between disciplines.
In this episode, we get into what actually happens when PMs and UX leads collaborate on AI products.
What we cover:→ Why Blanca loves when designers tell her she's completely wrong→ The real PM/UX collaboration cadence (not the org chart version)→ Who owns the decision when AI can't deliver what the design promised→ What's happening when PMs start prototyping themselves→ The traditional UX skills AI teams are undervaluing→ Direct advice for UX leads worried about becoming irrelevant
Guest: Blanca Barragan, Product Manager at Versapay & Forbes Technology Council Member
Host: Eric Ellis, UX Leader with 20+ years navigating technology disruptions
For UX professionals worried about their relevance in an AI-first world: Blanca's betting on the psychology, the human insight, and the creative tension you bring to the table. Not the UI you generate.