Product Thinking

In this solo episode of the Product Thinking Podcast, Melissa Perri shares the results of the State of AI in Product 2026 survey of 309 product leaders, co-published with Product Circle. The tools are everywhere, but the work has not changed. Melissa walks through five findings and what they mean for you.
Adoption is nearly universal, yet only a third of leaders say AI is strengthening their operating model. Melissa explains why the bottleneck is still upstream in discovery and decisions, and why AI acts as a multiplier rather than an equalizer, helping mature organizations and exposing the cracks in everyone else.
She unpacks the dataset's largest gap, between executives who think an AI strategy exists and the PMs who never see it reach their work, and what leaders and PMs should do about it. Melissa also shares some news: the podcast is taking a pause after this episode, though she is not going far.

You'll hear me talk about:
The tools changed, but the work did not
Almost every team has adopted AI tools, but only a third say it is strengthening how they work. Melissa shows why delivery got faster while decisions did not, and why the real bottleneck has moved upstream into discovery, prioritization, and review, not another coding assistant.
Why AI multiplies your operating model and skips your strategy
AI is a multiplier, not an equalizer. Mature operating models convert it into results while broken ones get worse, and smaller teams often outpace far larger ones. Melissa also covers the biggest gap in the data: executives believe an AI strategy exists, but it never reaches the PM's work.
What to do next
Melissa lays out the moves that matter: redesign workflows instead of buying tools, translate strategy into rules PMs can use, measure outcomes over adoption, and train product, design, and engineering together.

Episode resources:
Check our courses: https://productinstitute.com/
State of AI in Product 2026 (full report):https://productcircle.co/state-of-ai-2026
Recommended while we're on pause:
Episode 211: The Power of Team Topologies with Matthew Skeltonhttps://www.produxlabs.com/product-thinking-blog/episode-211-matthew-skelton-team-topologies
Episode 42: Making the Case for Product Operations with Denise Tilleshttps://www.produxlabs.com/product-thinking-blog/episode-42-denise-tilles
Melissa Perri on LinkedIn:https://www.linkedin.com/in/melissaperri/
Product Circle:https://www.linkedin.com/company/product-circle/

What does it actually take for experimentation to stick inside a product organization? In this compilation episode of the Product Thinking Podcast, Melissa Perri brings together three perspectives on the leadership behaviors, portfolio decisions, and iteration loops that separate real experimentation from theater.

David Bland, author of Testing Business Ideas, opens with what he has seen go wrong in well-funded companies that treat experimentation as a checkbox. He follows with a story about programs that died when leadership stopped reinforcing them, and the difference between living in a company's bloodstream versus its DNA.

Monica Lewis, VP of Product at LinkedIn, shares the leadership habits that make teams feel safe to test, and the 70/20/10 portfolio framework she uses. Mario Rodriguez, Chief Product Officer at GitHub, closes with how Copilot was built through failures and an outcome that surprised even him.

You'll hear us talk about:
Why experimentation programs quietly die
David Bland describes the checkbox mentality that turns experimentation into a process to navigate, not a way to de-risk. He shares a story of a company whose program lived in their bloodstream but never reached their DNA, and what happened when leadership stopped reinforcing it.
The leadership behaviors that make test-and-learn stick
Monica Lewis explains how she builds a team that feels safe to experiment, starting with owning mistakes publicly at the all-hands. She walks through her 70/20/10 framework for splitting investment across sure bets, strategic bets, and venture bets, and when to shift the mix.
How Copilot was built through failures
Mario Rodriguez takes us inside the iteration loop that produced GitHub Copilot. He describes a product that shipped with a 20 to 30 percent acceptance rate but was beloved by users, and how repeated UX failures led to the fill-in-the-middle behavior that defined the product.

Episode resources:
Check our courses: https://productinstitute.com/
Episode 44: Testing Your Ideas with David Blandhttps://www.produxlabs.com/product-thinking-blog/episode-44-david-bland
Episode 227: Inside LinkedIn's Product Strategy Culture with Monica Lewishttps://www.produxlabs.com/product-thinking-blog/episode-227-linkedin-strategy-monica-lewis
Episode 223: Behind the Rise of GitHub Copilot with Mario Rodriguezhttps://www.produxlabs.com/product-thinking-blog/episode-223-ai-github-copilot
David Bland on LinkedIn:https://www.linkedin.com/in/davidjbland/
Monica Lewis on LinkedIn:https://www.linkedin.com/in/monicamlewis/
Mario Rodriguez on LinkedIn:https://www.linkedin.com/in/mariorodriguez3/

Continuous discovery sounds simple and breaks down constantly in practice. In this compilation episode of the Product Thinking Podcast, Melissa Perri brings together three perspectives on what it actually takes to build the habit and why slowing down on discovery is still the fastest path to shipping the right thing.
Teresa Torres, author of Continuous Discovery Habits, breaks down the structure underneath every method: outcome, opportunity, and solution. Teams doing this right never have to stop and replan. Christina Wodtke, lecturer at Stanford and formerly at Zynga, follows with the weekly playtesting rhythm she now teaches.
Julia Austin, former senior lecturer at Harvard Business School, closes the episode by pushing back on the temptation to skip discovery in the age of AI. Her 80/20 rule: spend most of your time on foundation work, because the false security AI offers cannot replace real conversations with real customers.

You'll hear us talk about:
The structure underneath every discovery method
Teresa Torres walks through the three-part backbone of all discovery work: outcome, opportunity, and solution. She explains why teams doing this right never have to stop and replan: the next roadmap item emerges from ongoing customer conversations, not annual planning exercises.
Building a weekly testing rhythm that sticks
Christina Wodtke describes the weekly playtesting rhythm she carried from Zynga into her Stanford classes. She also walks through the scaffolded path from solo testing to designers, friends and family, and finally strangers, so teams build the muscle without exposing rough work too soon.
Going slow on discovery in the age of AI
Julia Austin makes the case for spending 80% of your time on foundation work and discovery before building anything. She explains why the temptation to skip this step in the age of AI is a trap, and why products that fail and get blamed on marketing usually failed in discovery first.

Episode resources:
Try Granola today: http://granola.ai/productinstitute
(Use the code PRODUCTINSTITUTE to get 3 months free)
Check our courses: https://productinstitute.com/
Episode 30: Understanding Continuous Discovery With Teresa Torreshttps://www.produxlabs.com/product-thinking-blog/episode-30-teresa-torres
Episode 226: Why Every Product Team Needs a Playtesting Mindset with Christina Wodtkehttps://www.produxlabs.com/product-thinking-blog/episode-226-christina-wotdke-game-design
Episode 231: Laying the Groundwork for Startup Success with Julia Austinhttps://www.produxlabs.com/product-thinking-blog/episode-231-julia-austin-startup-success-idea
Teresa Torres on LinkedIn:https://www.linkedin.com/in/teresatorres/
Christina Wodtke on LinkedIn:https://www.linkedin.com/in/christinawodtke/
Julia Austin on LinkedIn:https://www.linkedin.com/in/juliaaustin/

What does it mean for a product to actually be “done”? Not code in production, but customers buying, using, and loving it. In this compilation episode of the Product Thinking Podcast, Melissa Perri brings together three product leaders to explore the systems that make whole product launches consistent.
Trisha Price, then Chief Product Officer at Pendo, argues for shifting the team's definition of done from "code complete" to "whole product complete." She reframes product marketing as a strategic voice in discovery, not a translation layer at launch, and shares how cadences keep the work moving.
Kate Towsey, an independent research ops advisor with experience at BBC and Atlassian, frames organizational knowledge as water that needs a dam to stop it leaking away. Jessica Soroky, then Senior Director of Product Operations at Pendo, closes with what whole product launch and cadences look like in practice.

You'll hear us talk about:
Whole product complete, not just code complete
Trisha Price on shifting the definition of done from "code shipped" to "customers using and loving the product." She explains why a feature isn't done until product marketing, support, sales enablement, and go-to-market are aligned, and how product ops orchestrates the launch.
Knowledge as a managed asset
Kate Towsey on why organizations claim knowledge is their most valuable asset but let it leak through tributaries no one is mapping. She lays out how research ops, product ops, and design ops can work as one system for capturing and reusing what teams learn.
Cadences that keep product orgs aligned
Jessica Soroky on the operating cadences that make whole product launches predictable. She walks through Pendo's six-week product impact meetings, monthly roadmap reviews, and weekly leadership data rituals that reduce surprises and keep strategy connected to customer behavior.

Episode resources:
Check our courses: https://productinstitute.com/
Try Granola today: http://granola.ai/productinstitute
(Use the code PRODUCTINSTITUTE to get 3 months free)
Episode 184: Building Products for Product Managers with Trisha Pricehttps://www.produxlabs.com/product-thinking-blog/2024/8/14/episode-184-building-products-for-product-managers-with-trisha-price?rq=trisha Price
Episode 208: Scaling Research Ops to Drive Organizational Change with Kate Towseyhttps://www.produxlabs.com/product-thinking-blog/episode-208-kate-towsey-research-ops?rq=Kate Towsey
Episode 217: Behind the Scenes of Pendo's Product Operations Evolution with Jessica Sorokyhttps://www.produxlabs.com/product-thinking-blog/episode-217-jessica-soroky-pendo-product-operations?rq=Jessica Soroky
Trisha Price on LinkedIn:https://www.linkedin.com/in/trisha-price-3063081/
Kate Towsey on LinkedIn:https://www.linkedin.com/in/katetowsey/
Jessica Soroky on LinkedIn:https://www.linkedin.com/in/jessicasoroky/

AI is moving quickly from experimentation into real products, but in regulated and high-trust environments the stakes are much higher. In this compilation episode of the Product Thinking Podcast, host Melissa Perri brings together perspectives from multiple product leaders to explore what it really takes to ship AI responsibly when accuracy, trust, and risk management matter.
You will hear from Maryam Ashoori, who works at IBM and was involved in building Watsonx. She explains what AI agents actually are, why large language models hallucinate, and how guardrails and human oversight help teams manage calculated risk as systems become more autonomous.
The episode also features Magda Armbruster, Head of Product at Natural Cycles, and Jessica Hall, Chief Product Officer at Just Eat Takeaway. Together they share how embedding regulation, prioritizing data privacy, and being honest about cost, governance, and capability building can turn compliance and trust into enablers rather than blockers for AI-driven products.

You’ll hear us talk about:
What AI agents can and cannot do
Maryam breaks down how agents reason, plan, and take action, and why their probabilistic nature leads to hallucinations. She explains why this behavior is acceptable in low-risk contexts but dangerous in high-stakes domains without proper safeguards.
Managing risk with guardrails and humans in the loop
The conversation explores how teams can design agentic guardrails and decision flows that keep AI systems close to verified truth, while escalating sensitive or high-risk situations to humans for review.
Embedding regulation and privacy into product development
Magda shares how Natural Cycles integrates quality assurance, regulatory, and compliance partners directly into day-to-day product work, and why strong privacy practices and user control are core product strategy rather than afterthoughts.
The real cost of AI and long-term responsibility
Jessica discusses the often underestimated costs of building and running AI systems, from unit economics to team capability, and why product leaders must balance simplicity, governance, bias mitigation, and customer trust instead of chasing hype.

Episode resources:
Check our courses: https://productinstitute.com/
Maryam Ashoori LinkedIn: https://www.linkedin.com/in/mashoori/
Magda Armbruster LinkedIn: https://www.linkedin.com/in/magda-armbruster-326692a/
Jessica Hall LinkedIn: https://www.linkedin.com/in/jessica-hall-4223b0/
Product Thinking Podcast Episode 241: https://www.produxlabs.com/product-thinking-blog/episode-241-ai-strategy
Product Thinking Podcast Episode 251: https://www.produxlabs.com/product-thinking-blog/episode-251-femtech-innovation
Product Thinking Podcast Episode 199: https://www.produxlabs.com/product-thinking-blog/2024/11/27/episode-199-the-true-cost-of-ai-beyond-the-hype-and-into-reality-with-jessica-hall