Product Talk

Nikita Miller spent 15 years building products before becoming President of Product and Technology at Perk, an AI platform for business travel and spend management. She made the move from the U.S. to Barcelona about a year ago, arriving right in the middle of Perk's transition from a single travel product to a multi-product platform. The timing meant navigating that transformation while also rethinking how product teams work in an era where AI has changed almost everything about how work gets done. In this episode, host Cassio Sampaio sits down with Nikita to talk about the UX renaissance she sees happening in B2B, the concept of shadow work and why removing it is one of the biggest product opportunities right now, why she thinks the most important PM skill in the AI era is discernment rather than taste, and what she tells early-career product managers who are trying to figure out where to invest in themselves when the landscape keeps shifting.
In this episode, we cover:
(1:32) What surprised Nikita most about moving from the U.S. to Barcelona and leading an international team at Perk
(3:27) How AI changed the structure and pace of her product teams: smaller teams, cross-functional flexibility, designers doing front-end coding
(7:55) Travel as a massive wedge: why winning in B2B travel is harder than it looks and how it opens the door to spend, events, and more
(13:26) The UX renaissance in B2B: why B2C expectations have permanently raised the bar for enterprise product
(17:31) Whether AI helps disruptors or actually empowers incumbents more
(19:21) How Perk is actively thinking about disrupting itself
(20:10) Discernment over taste: why the ability to judge which problems to solve and when is more important than ever
(22:44) Shadow work: the framework for identifying what can be automated so customers can focus on what matters
(24:31) Where the interface goes from here: MCP, voice, visual, and why it probably will not collapse to just one thing
(28:27) Advice for early-career PMs: what persists across every wave of technology change
Blog and detailed workflow walkthroughs from this episode: [link]

Joanna Strober is the co-founder and CEO of Midi Health, a virtual menopause and perimenopause care company serving patients in all 50 states, covered by insurance. She spent 15 years as a venture and private equity investor, then founded and sold a digital health company called Kerbo, before her own perimenopause experience made the care gap impossible to ignore. When she finally found a clinician who understood what she was going through, that expert was an hour away and cost a fortune out of pocket. In 2021, she co-founded Midi with Sharon Mears to bring expert menopause and perimenopause care to every woman virtually, in 50 states, covered by insurance. In this episode of Product Talk, host and Planned Parenthood Direct Chief Product Officer Hannah Park sits down with Joanna to talk about what her investor background gave her as an operator, how Midi thinks about trust as a product decision rather than a brand value, and what it actually looks like to scale care quality to hundreds of thousands of patients without letting it slip.
In this episode, we cover:
(2:22) What 15 years of investing taught Joanna about building product, and what pure operators miss
(3:46) What tells her a product org is healthy, and the CEO/product leader tension she manages every day
(9:29) What trust actually looks like inside a product decision at Midi, and where they fell down early
(13:24) MIDI University: how they scaled expert clinical knowledge to hundreds of nurse practitioners
(16:39) Why AI models are often wrong about women's health, and what that means for Midi's care protocols
(18:13) How Midi uses AI to scan charts and identify which providers have patients who keep coming back
(21:40) What Midi will and will not do, and how they decide where the scope ends
(26:25) Why insurance coverage was non-negotiable from day one when cash pay would have been so much easier
(28:35) How the equity mission holds up inside commercial decisions
(31:02) The AI advisory board: AI John Doerr on OKRs, AI Dan Ariely on text message rewrites
(32:36) How Midi uses AI without recreating the feeling that got women dismissed in the first place
(37:23) Lightning round: prevention over optimization, and what the next generation of women's health founders should build
Blog and detailed workflow walkthroughs from this episode: [link]

Saee Pansare started her career not in software but in a lab, studying food engineering and imagining a future developing flavors and ingredients. What she discovered instead was that she had the instincts of a product manager all along; she just happened to be building physical products. After stints at Kraft Heinz, Amazon, and Whole Foods, she landed at DoorDash where she now leads the DoorDash for Business charter, building group order and large order systems for corporate clients. In this episode of Products That Count, podcast host and Chief AI Product Officer at Boston New Technology Shweta Agrawal sits down with Saee to unpack what food product development taught her about software PM, why she believes domain expertise beats technical background when switching industries, and how she navigated the trust-building challenge that every career changer eventually faces.
In this episode, we cover:
(2:08) Saee's path from food engineering undergrad to MBA to product management
(4:33) What a food engineer actually does, and why it looks a lot like software development
(6:05) Managing the P&L for cheese powders and marshmallows at Kraft Heinz
(10:28) How Saee ran customer discovery and prototype testing for physical food products
(15:21) How pre-COVID, COVID, and post-COVID eating habits are completely different, and what that means for food businesses
(18:05) Why time to commercialization pushed her out of food and into software
(23:21) How she applied for PM roles without a technical background, and what strategy worked
(27:00) The hardest part of the transition: building trust with software engineers
(30:36) Job search advice for career switchers: what a resume alone cannot do
(32:07) What the DoorDash for Business charter actually is, and what the day to day looks like
(34:54) DoorDash versus Amazon: how company size shapes the speed of everything
(37:12) Advice for anyone transitioning from physical products into software PM right now
Blog and detailed workflow walkthroughs from this episode: [link]

Ghazal Badiozamani is the SVP of Product Management at Cengage, one of the world's largest education companies with roots in publishing that go back over 100 years. Before Cengage, she spent eight years at Elsevier helping legacy businesses understand and adopt emerging technology, starting with machine learning before it was mainstream, eventually building a digital team from scratch and launching a digital authoring system from nothing. In this episode of the CPO Rising series, Products That Count Resident Chief Product Officer Renee Niemi sits down with Ghazal to talk about what it takes to lead product inside a company that has existed for over a century, why the squad model may be approaching a fork in the road, and her take on the most pressing question in AI-era product development: what does product even mean now?
In this episode, we cover: 
(1:11) Ghazal's path from strategy to product at Elsevier, and what prompted the move to Cengage
(4:32) What it actually feels like to lead product inside a company that's been around for generations
(6:08) Why product problems always end as people problems, and why that's the most interesting part of the job
(7:28) How design principles and core values serve as anchors through both digital transformation and AI adoption
(12:59) AI's progression: from efficiency tool to fundamental question about what product even is
(14:55) Why building for nonlinear human thinking is the new product challenge
(16:58) Team structure today and two very different futures for the squad model
(19:46) Why removing design from the triad is a mistake, and what each personality type actually contributes
(23:23) Development speed: from 3 to 5 months down to 2, and why customer absorption is now the real constraint
(27:14) The CPO alpha effect: the two capabilities that are almost never found in the same person
(30:45) The funnel-based product analytics dashboard Ghazal checks almost every day
Blog and detailed workflow walkthroughs from this episode: https://productsthatcount.com/the-question-ai-still-cant-answer-about-product-management-cengage-product-svp/

Rob Ferguson is the VP of Technology and Strategy at Fireworks AI, a company that makes frontier AI infrastructure accessible to any organization that wants to own its own models rather than depend on someone else's. He started studying machine learning before it was called AI, worked on Pro Tools and AI systems for a music streaming service, helped design Amazon Go's grab-and-go technology, and built startup programs at AWS and Microsoft. Now he is at what he calls the front row of AI, sitting between applied research and go-to-market and translating what the technology can actually do into things companies can actually buy and build on. In this episode of Product Talk, iDonate VP of Product and Engineering Nacho Andrade sits down with Rob to talk about why speed is the AI feature no one asks for but everyone needs once they see it, how AI training went from lab-only to cheap as a cup of coffee, and his hot take that we are at the end of SaaS and entering an era he calls workwear.
In this episode, we cover:
(0:48) Rob's background from music and machine learning to Pro Tools, Artio, Amazon Go, and Fireworks
(3:43) What it means to sit at the intersection of applied research and go-to-market
(11:41) What Fireworks AI actually does: inference infrastructure and model training in one place
(14:11) Who Fireworks serves and how the customer has changed as training costs have dropped
(16:52) Speed as a hidden AI feature: why nobody asks for it and everyone needs it once they see it
(20:18) The shift from AI as talkers to AI as doers, and what that means for product
(21:24) AI independence vs AI dependence: why owning your model changes what you can build
(23:27) The most common problem Rob sees: agents that work but cost thousands of dollars to run
(26:25) Drawing the line in the sand: why doing less deeply beats promising everything
(27:41) Hot take: we're at the end of SaaS and entering the era of workwear
(31:55) Why domain experts and liberal arts thinkers become more valuable as surface-level software commoditizes
(33:04) What the AI industry gets wrong about itself and the case for openness and independent scrutiny
(38:24) The voice tech stack Rob is obsessed with and uses every day
Blog and detailed workflow walkthroughs from this episode: https://productsthatcount.com/why-speed-is-the-ai-feature-no-one-asks-for-but-everyone-needs/