Podcasts about Chief product officer

The model is not the expensive part of your AI stack. The missing context is. That is the argument at the centre of everything Glean announced this week, and I got into it with Emrecan Dogan, Chief Product Officer at Glean, on site at Glean:GO on The Ravit Show in San Francisco. Here is why it matters beyond one vendor's launch.When AI does not know how your company works, every task starts from zero. It hunts for files. It asks for background. A person stops what they are doing and feeds it the same context again. Glean's research puts that at 6.4 hours a week per worker, which is most of a working day spent supervising a tool that was supposed to save time.That is also why the productivity numbers keep disappointing executives. 75% of workers say AI makes them faster. Only 13% say their company is performing better because of it. Individual speed is not organizational output, and no amount of model upgrade closes that on its own.So the interesting question is not which model is smartest this quarter. It is what your AI already knows about your business before you ask it anything.Emrecan and I covered where that leaves enterprise buyers, what happens to AI spend as agents start doing multi step work, and how teams keep a growing pile of AI tools from turning into sprawl.#data #ai #glean #enterpriseai #ai #artificialintelligence #cio #agenticai #theravitshow

In this episode, Alex & Annie sit down with Vinny Dicarlo, CEO of Ciirus, and Josh Parry, Chief Product Officer, for a conversation about the philosophy that has shaped the company over nearly two decades.Founded as a family business, Ciirus has taken a deliberately measured approach to growth. Rather than building around outside investment or pressure to scale at all costs, Vinny and Josh explain how the company has focused on long-term customer relationships, continued investment in its technology, and human support that keeps the team closely connected to the property managers it serves.That approach opens up a broader conversation about what operators should expect from a technology partner today. Vinny and Josh share why they believe there are limits to how much vacation rental operations can be automated, where AI can genuinely help, and why human involvement still matters in an industry where every property, owner, guest, and stay can look different.Episode Chapters:11:14 - Building customer relationships designed to last17:15 - Why Ciirus has chosen measured growth over growth at all costs18:28 - How independent ownership shapes investment in customers and technology22:38 - Why vacation rental operations cannot automate everything27:39 - Building a global team around specialized talent32:49 - Helping property managers get more from their technology38:14 - Why customer and employee satisfaction matter together39:55 - Ciirus' new mobile app, owner tools, and Booking.com integration46:03 - How LoveRentals helps property managers expand their capabilities54:59 - Finding vacation rental demand beyond the major OTAs57:55 - Reaching guests through travel agents, wholesalers, and international markets1:02:24 - What is next for the Ciirus platformIf you are evaluating your tech stack, thinking about sustainable growth, or looking for new ways to reach guests, this episode offers a closer look at what a strong technology partnership can bring to your business.Connect with Josh & VinnyJosh Parry: https://www.linkedin.com/in/josh-parry-47165997/ Vinny Dicarlo: https://www.linkedin.com/in/vincenzo-dicarlo/ Connect with CiirusWebsite: https://ciirus.com/✨ Exclusive Offers to Alex & Annie Listeners:Alex & Annie listeners can receive their first three months of Ciirus subscription fees waived when joining the platform.Visit https://ciirus.com/ and let the team know you heard about Ciirus through the Alex & Annie Podcast.Thinking about the next chapter for your vacation rental business? Connect with Monarch Collective to explore what growth could look like with the right platform behind you.

Jonathan Evens is a product lead at Google DeepMind, where he has spent more than a decade applying machine learning and AI across industries — from the smart grid at AutoGrid, to detecting roads and buildings from satellite imagery at Planet, to recommender systems, Google Search's AI Overviews and AI Mode, and now live avatars. He is also an advisor to the Evens Foundation, where he is building a "digital citizenry": a democracy sandbox that uses synthetic citizens to pre-test how the public might react to a policy before it is written.Jonathan returns to The Product Experience, where hosts Lily Smith and Randy Silver pick up the conversation they started at MTPcon London, to dig further into what actually separates an AI product manager from a product manager who simply uses AI tools, why product principles have to come before evaluations, and how synthetic users can help — and mislead — at very different scales of product.We discuss:1. Why "AI product manager" has become a near-meaningless label, and the two distinct roles hiding underneath it: the modelling product manager working on core model capabilities, and the AI feature product manager building AI-powered products2. Why using an LLM as a thinking partner or a coding assistant does not make someone an AI product manager — it makes them a product manager using AI tools, full stop3. How Google Search's North Star metrics have stayed constant even as the proxy metrics beneath them — side-by-side win rates, user ratings, RLHF signals — have had to be rebuilt from scratch4. Why product principles, not evaluations, are the real starting point for any AI feature, and how Google Search resolved the problem of trustworthy sources disagreeing on basic facts5. How Google Search builds trust into its AI Overviews through sourcing, citation placement and UX cues such as highlighting, so users can judge at a glance what to verify6. Where synthetic users genuinely help — cold-start problems, privacy-sensitive research, automated regression testing — and where they fall short7. Building the Evens Foundation's "digital citizenry", and the core technical problem behind it: AI-generated personas that are less diverse and more extreme than real people8. How team size and structure differ between a fully resourced lab like Google DeepMind and a resource-constrained non-profit team, and why Jonathan resists a single answer for the "right" team size9. How the product manager's job is shifting as engineers absorb more of the evaluation work themselves through prompting and iteration10. Jonathan's advice for product managers building AI features, and his case for following the Makers Manifesto Key takeaways"AI product manager" covers two distinct jobs. The modelling product manager defines and measures a model's core capabilities — factuality, reasoning, long context — and that role is concentrated almost entirely inside frontier labs. The AI feature product manager builds a product or feature on top of an existing model, and needs domain expertise and user empathy far more than technical depth. Conflating the two is why the title has become so diluted.Using an LLM to think faster or write code faster does not make someone an AI product manager. It makes them a product manager using AI as part of their toolkit — the same as any other knowledge worker. The distinction matters because it clarifies what skills are actually being tested.Product principles have to come before evaluations, not after. Before Jonathan starts building an eval set for a new product, he first asks what the product is meant to feel like and what values it should encode. Google Search's response to sources disagreeing on a monument's construction date, or to large language models hallucinating at scale, came from principles about trustworthiness established before any metric was built.Trust in an AI feature is built through sourcing and interface design as much as through the model itself. Google Search's AI Overviews are constrained to draw only from ranked, trustworthy documents rather than the model's own memory, and users are given UX signals — citation placement, highlighting — that let them judge at a glance how much to verify.Synthetic users add genuine value in cold-start scenarios, privacy-sensitive research and automated regression testing. Where they fall short is diversity: AI-generated personas tend to be less varied and more extreme than real people, which is the central technical problem behind the Evens Foundation's digital citizenry project.There is no fixed answer to the right team size. Jonathan sees a gradient, from a senior developer working entirely alone, up to the Evens Foundation's single product manager with AI-assisted development skills, up to a fully staffed Google team — with the deciding factor being how unsolved the underlying problem is, not company size.As engineers absorb more evaluation work themselves through prompting and iteration, roles are blending. What still sits with product management is the judgement calls that follow from product principles — deciding, for example, which technical trade-offs actually matter to the use case, rather than which are easiest to measure.Features links- Evens Foundation — https://evensfoundation.eu- Makers Manifesto — https://makersmanifesto.org- Google DeepMind — https://deepmind.google- AutoGrid — smart grid AI company where Jonathan began applying machine learning to industry- Planet — satellite imagery company where Jonathan worked on automated road and building detectionWe're refreshing The Product Experience and want your input. Take our two-minute survey and help shape where the show goes next! Our HostsLily Smith enjoys working as a consultant product manager with early-stage and growing startups and as a mentor to other product managers. She's currently Chief Product Officer at BBC Maestro, and has spent 13 years in the tech industry working with startups in the SaaS and mobile space. Randy Silver is a Leadership & Product Coach and Consultant. He gets teams unstuck, helping you to supercharge your results. Randy's held interim CPO and Leadership roles at scale-ups and SMEs, advised start-ups, and been Head of Product at HSBC and Sainsbury's. He participated in Silicon Valley Product Group's Coaching the Coaches forum, and speaks frequently at conferences and events. You can join one of communities he runs for CPOs (CPO Circles), Product Managers (Product In the {A}ether) and Product Coaches. He's the author of What Do We Do Now? A Product Manager's Guide to Strategy in the Time of COVID-19. A recovering music journalist and editor, Randy also launched Amazon's music stores in the US & UK.

This episode is focused around the growing challenges of securing federal systems against ransomware, emerging AI agents, and unpatchable legacy infrastructure. Steve Cooperman, President, SCOOP Cyber and Bob Blakey Co-Founder and Chief Product Officer, MIMIC, will discuss how known-good enforcement, virtual patching, and AI agent governance can help organizations move beyond detection-based security and prevent unauthorized activity before it executes.

What could your team achieve if a document that previously took two hours could be created in eight minutes? In this episode of Tech Talks Daily, I speak with Oskar Konstantyner, Chief Product Officer at Templafy, about the rapid adoption of AI agents across enterprise document workflows and what those productivity gains mean for knowledge workers. According to Templafy's proprietary usage data, AI agent adoption among its enterprise users grew from virtually zero in October 2025 to 53% by June 2026. Its analysis found that documents created without agents had a median completion time of two hours and an average of 5.6 hours across 16,000 sessions. With AI agents, the median fell to eight minutes and the average to 27 minutes across 14,000 sessions. The most common documents included pitch decks, company communications, sales materials, and product roadmaps. However, Oskar cautions against treating speed as the final measure of AI productivity. We discuss an accounting firm that could not respond to thousands of tenders because it lacked the capacity to create enough proposals. Faster document production could allow that business to participate in additional opportunities while applying its knowledge about what makes a winning submission. The benefit comes from increased commercial capacity and stronger results, rather than counting recovered hours alone. Oskar also explains what happens during those eight minutes. AI can locate relevant information, find approved content, recommend a presentation structure, apply previous lessons, and complete much of the production work. Humans remain responsible for original thinking, client judgment, factual accuracy, and final approval. In many cases, the agent may produce 60% to 90% of the document, but the beginning and end of the process remain human-led. The conversation also considers the growing volume of generic AI documents. A business already has approved slides, company descriptions, brand assets, legal statements, and sales messages. Regenerating all that material wastes tokens and risks inconsistency. Oskar argues that agents should determine when existing content should be reused, when rules should be applied, and when something genuinely new needs to be created. We also discuss why AI adoption improves when agents appear inside PowerPoint, Claude, OpenAI, and Copilot. Most employees are unlikely to abandon familiar workflows every time another AI application arrives. Is your company measuring AI success through minutes saved, or through the additional business those minutes make possible? Listen to the conversation and share your thoughts with me.

At the IBC show in Amsterdam, Avid is unveiling a raft of new ways in which it is driving innovation in the media business. Get all the latest news in this special edition of Making the Media.Avid product leaders Kenna Hilburn and Guillaume Aubuchon join host Craig Wilson to delve into the key announcements from the show and the strategy behind the features and workflows.In the episode they discuss how connected planning, modern rundown, production, and publishing workflows across Avid Content Core, MediaCentral and Wolftech News, help teams accelerate content delivery across every platform.And in the world of post production, they focus on agentic editing, a new web-based Media Composer and outline Avid Content Core's media intelligence.Plus they set out why Avid's approach to AI differs from others in the market, supporting the creative community.Our guests this episode: Kenna Hilburn, Chief Product Officer, AvidKenna heads the Avid Product Management Team, responsible for the entire Avid product portfolio. As chief product officer, she is focused on turning vision into outcomes that matter. Recognized for leading transformational change, building and scaling high-performing teams, and simplifying complexity into clear strategies, she is experienced in guiding organizations through growth and transition while fostering cultures of accountability, collaboration, and impact.Guillaume Aubuchon, Avid VP of Product ManagementGuillaume leads product for the editorial and newsroom core at Avid—the tools professional editors and broadcasters use to make the content you watch. He is working to bring agentic AI into that workflow without breaking what makes it trustworthy. The first of these shipped at NAB 2026: Google Gemini integrated directly inside Avid Media Composer, driving persona-driven editor workflows and an AI recommendation engine that accelerates content discovery and rough-cut assembly inside editors' native environment.  More ResourcesFor more on this topic, check outAvid at IBC – Get the key announcementsRegister Now – Two new webinars for news andpostproduction. Ideal if you could not make it to the showAvid Content Core – Discover more about Avid's award-winning Content Data Platform for media productionAvid for News – Trusted by the world's leading news organisations.Video Post Production – Find out how Media Composer is enabling AI-powered workflowsAvid NEXIS storage solutions – Tried and tested storage solution for the most demanding production environments  Contact UsQuestions? Comments? Cool ideas? Get in touch:makingthemedia@avid.com. Follow Avid at @avid.CreditsHost: Craig WilsonProduction team: Owen Lynch and Wim van den BroeckTheme Music: Greg “Stryke” Chin

Kirsten Mann is a board director, product leader and, with this episode, a three-time guest on the podcast. Last time she was here, she was building Vizory, an AI tool that helps company directors get through board packs. This time she's back to explain why she isn't building it any more. Talking to Randy Silver, she walks through exiting Vizory, the friction tests she ran before writing a line of code, and why she now believes distribution, not the build, is where most AI products actually die.We're refreshing The Product Experience and want your input. Take our two-minute survey and help shape where the show goes next! Key takeawaysBefore writing a line of code, Mann tested for force rather than sentiment: she asked directors for two confidential board packs and an audio recording of themselves reviewing one, and only started building once 10 people agreed to do it. Coffee-shop enthusiasm is cheap; handing over a company's most sensitive document is not.Vizory's most-loved feature in demos, cross-pack search, was barely used once shipped. Directors said they wanted it and reacted strongly when they saw it, but in practice they went straight to an automated triage view instead — a clean case of stated preference diverging from revealed preference.Board software runs on quarterly, not weekly, cycles, and trust compounds slower than value does. Mann modelled two review cycles before directors would rely on the tool; in practice it took three, meaning some customers on quarterly boards needed close to a year before the value became obvious, a timeline no 30-day trial can accommodate.Pricing got caught in a double anchoring trap. Directors first benchmarked Vizory against the $20-a-month ChatGPT and Claude price point, so Mann positioned against the cost of a governance failure instead, then created a second anchor by pricing early pilots at $150 a seat against a $300 target, which made the later increase read as a 100% price rise.Cutting friction is the wrong instinct early on. Mann deliberately added friction, asking for sensitive documents and charging as early as possible, to separate real demand from polite interest, arguing that most founders run tests designed to confirm they're right rather than to find a reason to stop.Mann's main lesson for other founders is that distribution is now the product problem. AI has collapsed the cost of building software but done nothing to the cost of reaching people who trust you, which is why she pushed to add distribution, adoption and willingness to pay as a third discipline in the Makers' Manifesto, alongside building the right thing and building it right.Multi-model products carry a new operational risk. One of Vizory's AI "judges" silently stopped being selected because the underlying model had been deprecated overnight without warning, a reminder that model drift means the QA and evals work never really stops, however fast the initial build was.We're refreshing The Product Experience and want your input. Take our two-minute survey and help shape where the show goes next! Our HostsLily Smith enjoys working as a consultant product manager with early-stage and growing startups and as a mentor to other product managers. She's currently Chief Product Officer at BBC Maestro, and has spent 13 years in the tech industry working with startups in the SaaS and mobile space. Randy Silver is a Leadership & Product Coach and Consultant. He gets teams unstuck, helping you to supercharge your results. Randy's held interim CPO and Leadership roles at scale-ups and SMEs, advised start-ups, and been Head of Product at HSBC and Sainsbury's. He participated in Silicon Valley Product Group's Coaching the Coaches forum, and speaks frequently at conferences and events. You can join one of communities he runs for CPOs (CPO Circles), Product Managers (Product In the {A}ether) and Product Coaches. He's the author of What Do We Do Now? A Product Manager's Guide to Strategy in the Time of COVID-19. A recovering music journalist and editor, Randy also launched Amazon's music stores in the US & UK.

Jordan Tigani helped create Google BigQuery, then got fired as Chief Product Officer on a Friday morning. He planned to hack on DuckDB to learn Rust. Investors offered to fund it before he'd decided to start a company. That company became MotherDuckIn this episode, we cover:The DuckDB Labs partnership: why MotherDuck gave the open-source creators a co-founder share instead of going open-coreFrom alpha to paid product: 11 founders, 3 to 4 months to alpha, two years to something people would pay forAI on top of the data warehouse: vibe-coded dashboards (Dives), pipelines (Flights), a context layer (Guides), and why business users catch mistakes analysts missAre dashboards dead? Jordan wrote "Big Data Is Dead"; his answer on dashboards is differentCareer advice: why you shouldn't want to work on the query optimizer, and the skill Jordan says matters moreFor engineers curious about database and infrastructure companies, open-source business models, and how AI is changing who gets to ask questions of data.Timestamps:00:00:00 - Intro00:00:32 - Fired on a Friday: how MotherDuck accidentally started00:04:50 - Giving DuckDB Labs a co-founder share of the company00:07:43 - Why most open-source SaaS products are just "managed"00:09:31 - Why VCs said yes: Snowflake, DuckDB, and BigQuery credibility00:10:50 - The 11-person founding team that skipped the wrong designs00:12:20 - Alpha in 4 months, beta in a year, paid in two00:15:20 - Vibe-coded BI: Dives, Flights, Guides, and an agent harness00:20:10 - The questions business users ask that analysts never do00:24:14 - Are dashboards dead in the age of agents?00:27:57 - Everybody wants to work on the optimizer (don't)00:31:23 - The engineer superpower most engineers look down on00:33:20 - Writing: the one skill Jordan would learn (and still hates)00:36:05 - Does contributing to DuckDB get you hired at MotherDuck?00:37:20 - Why a database company leaned into the duck#MotherDuck #DuckDB #SoftwareEngineering

In this episode, Hilmarie sits down with Sergei Kukharev to explore how technology can reduce stress instead of creating it. Drawing on more than 15 years of experience in fintech and payments, Sergei explains why the future of AI isn't about replacing people, but helping business owners make better decisions with greater confidence.The conversation explores the shift that transformed his career, moving from building payment infrastructure to understanding the people behind every transaction. After spending time with small business owners, Sergei realized that merchants don't care about complex technology. They care about saving time, reducing operational stress, and running their businesses more effectively. That insight reshaped how he approaches product development, leading him to prioritize simplicity, empathy, and practical outcomes over flashy features.A defining moment in the episode is Sergei's Green Pill realization that successful products are built by solving human problems, not technical ones. He shares valuable lessons from products that failed, why emotional friction often prevents adoption more than technical limitations, and how involving engineers directly with customers creates better solutions. He also discusses AI's growing role as a trusted assistant that helps small businesses gain clarity without replacing human judgment.At its core, this episode is about empathy, thoughtful innovation, and building technology that genuinely improves people's lives. Sergei's journey is a reminder that the best products aren't the ones with the most features, but the ones that quietly remove complexity so people can focus on what matters most.About The GuestSergei Kukharev is the Chief Product Officer at Fortis, where he leads the development of AI-powered payment and commerce solutions that help small and medium-sized businesses simplify operations and make smarter decisions. With over 15 years of experience in fintech, digital payments, and product leadership, he has built solutions focused on improving merchant experiences across the GCC.Throughout his career, Sergei has championed a human-centered approach to product development, believing that the most successful technology is measured not by its complexity but by the confidence and clarity it gives its users. By combining data, artificial intelligence, and customer empathy, he continues to create practical solutions that help businesses reduce operational stress, improve efficiency, and grow with confidenceQuotes4:17 - Designing for stress reduction means designing for clarity, simplicity, and confidence in daily operations.10:24 - Spend more time absorbing real user behavior and less time building based on someone's assumptions. 12:42 - The most interesting future is not AI creating some noise, but helping small business owners and business owners actually feel more in control.13:26 - AI cannot replace judgment, for example. Yeah, its the human thing, and only we can judge the decisions, what AI, for example, suggesting to us.22:22 - We decided to stay focused on the merchants we could serve better. And I think it was an important to us an important reminder that long-term trust matters more than chasing scale too early.24:25 - Empathy is vital to actually thrive and be successful.Useful LinksWebsite:https://www.wefortis.comInstagram:https://www.instagram.com/fortis.uae/Linkedin:https://www.linkedin.com/in/ser-kukharev/The Matrix Green Pill Podcast: https://thematrixgreenpill.com/Please review us: https://g.page/r/CS8IW35GvlraEAI/review

AI delivers value in the revenue cycle when it is built into well-designed workflows supported by reliable data, governance, and clear measures of performance. Navaneeth Nair, Chief Product Officer at Infinx Healthcare, joins Stuart Newsome to discuss where AI is working today, from prior authorization and coding to denial prevention, recovery, and enterprise workflow orchestration.

Nexus sells driver's license scans on the dark web. OpenAI says its models have reached a “Critical” capability threshold. International law enforcement disrupts a decades-old botnet. AI hallucinations fuel “slop squatting.” Plus, urgent patches for Cleo Harmony and Virtualizor, a Texas healthcare breach, and a Russian national accused of targeting thousands of freelancers with remote-access malware. Maria Varmazis shares the latest space-cyber news. Our guest is Rob Allen, Chief Product Officer at Threat Locker, talking about protecting against AI in the workplace. AI threatens the government's bug supply. Remember to leave us a 5-star rating and review in your favorite podcast app. Miss an episode? Sign-up for our daily intelligence roundup, Daily Briefing, and you'll never miss a beat. And be sure to follow CyberWire Daily on LinkedIn. CyberWire Guest On today's Industry Voices we are joined by Rob Allen, Chief Product Officer at Threat Locker, talking about protecting against AI in the workplace. If you enjoyed this conversation, be sure to check out the full interview here. Selected Reading FBI Probes Service Selling 153M+ Drivers Licenses (Krebs on Security) OpenAI's Astra Becomes First Model to Cross Critical Cybersecurity Threshold (SecurityWeek) Sality botnet infrastructure dismantled in joint global takedown (Bleeping Computer) Crooks Are Learning to Love AI Hallucinations (IEEE Spectrum) MSSA Reference Architecture 2.0 (Mobile Satellite Services Association (MSSA)) Exploit Published for Fresh Cleo Harmony Vulnerability (SecurityWeek) Malicious Virtualizor Update Served via BGP Hijacking (SecurityWeek) Nutex Health Says Patient Data Stolen, Hackers Threaten Leak (Infosecurity Magazine) US charges Russian for infecting 80,000 freelancers with malware (Bleeping Computer) How AI could make it harder for governments to use hacking tools (TechCrunch) Share your feedback. What do you think about CyberWire Daily? Please take a few minutes to share your thoughts with us by completing our brief listener survey. Thank you for helping us continue to improve our show. Want to hear your company in the show? N2K CyberWire helps you reach the industry's most influential leaders and operators, while building visibility, authority, and connectivity across the cybersecurity community. Learn more at sponsor.thecyberwire.com. The CyberWire is a production of N2K Networks, your source for strategic workforce intelligence. © N2K Networks, Inc.

Today's show features: - Rob Ruth, President / Owner at Bob Ruth Ford - Shane Helms, Founder / CEO at TrueView Media Group - Matthew Zabawa, Chief Product Officer at WebBuy Digital Retailing - Steve Moroz, Managing Partner/GSM at EZ Nissan This episode is brought to you by: Carmax – CarMax Auctions. Access thousands of cars weekly at 50+ locations nationwide through our 100% online auctions. From high-end to high mileage, CarMax Auctions has the inventory you need to source smarter and accelerate sales. Register now for free at carmaxauctions.com/CDG. TrueView Media Group – TrueView Media Group — TrueView Media Group is a CTV technology company built for automotive retail. We plan, buy, and measure streaming for individual rooftops on our own platform, continually engineering more effective ways to buy impressions and showing every store exactly where its money went: every app, every impression, every dollar — measured to the outcomes a store actually feels, like site visits, VDP views, and sales. Visit trueviewmediagroup.com/cdg First up, Rob Ruth, President and Owner of Bob Ruth Ford in Dillsburg, Pennsylvania. Rob made a bet on building his own buying center — and it's reshaping how his store grows. Why is that the move he'd double down on? He'll tell us. Then, Shane Helms, Founder and CEO of TrueView Media Group. Shane says the entire marketing ecosystem dealers depend on is broken — and get this, he claims Tier 2 has flat-out vanished at brands like Mazda, Subaru, VW, and Mercedes. What changed, and what does it mean for your store? You'll want to hear this one. Next, Matthew Zabawa, Chief Product Officer at WebBuy Digital Retailing, on where digital retailing is really headed — and what's still missing. And rounding things out, Steve Moroz, Managing Partner and GSM at EZ Nissan, bringing the dealer's-eye view on digitizing the showroom. Can you actually bring the online experience onto the sales floor without breaking it? Steve's got the battle scars and the answers. Check out Car Dealership Guy's stuff: CDG Circles ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://cdgcircles.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ CDG News ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://news.dealershipguy.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ CDG Jobs ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://jobs.dealershipguy.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ CDG Recruiting ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.cdgrecruiting.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ My Socials: X ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.twitter.com/GuyDealership⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Instagram ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/cardealershipguy/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ TikTok ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.tiktok.com/@guydealership⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ LinkedIn ➤⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ https://www.linkedin.com/company/cardealershipguy/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Threads ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.threads.net/@cardealershipguy⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Facebook ➤⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ https://www.facebook.com/profile.php?id=100077402857683⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Everything else ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠dealershipguy.com⁠⁠

April Dunford is the positioning expert behind Obviously Awesome and a former repeat vice-president of marketing across seven venture-backed startups, most of which were acquired. Over the past decade she has advised roughly 300 B2B technology companies, all with sales teams, on how to position themselves against the competition. In this episode she joins hosts Lily Smith and Randy Silver to explain why so many companies are repositioning at once, how a strong point of view on the future underpins good positioning, and why the story a company tells about itself is a decision for product and sales, not just marketing.Key takeawaysPositioning is a company-wide decision, not a marketing exercise. Dunford's own experience repositioning a spreadsheet tool as an embeddable database shows how it reshapes pricing, sales motion and even the product roadmap, not just the words on a website.Major shifts such as the move to AI force widespread repositioning because customers no longer have a stable set of alternatives to judge value or price against, and both AI-native companies and traditional SaaS businesses are wrestling with where they now sit.Intercom's rebuild of its support product around Fin shows how staying anchored to the customer's underlying job, resolving a ticket, can guide a genuine AI-first redesign rather than a bolt-on feature.Companies need a clear, credible point of view on the future of their market, or customers facing genuine uncertainty will simply freeze and delay buying decisions.A compelling vision of the future has to flow from a company's real differentiated value, not be reverse-engineered to flatter its current position.Selling too far into a hyped future risks stalling deals, so the message needs a maturity model that shows customers a credible, low-risk path from where they are today to where the market is heading.Positioning should be revisited on a disciplined schedule rather than settled by whoever argues loudest in the room, and Dunford recommends a structured check every six months on competitors, differentiators and value themes.Customer advisory boards, quarterly executive account calls and a company's own sales team are the most reliable early-warning systems for shifts in budget, buying process and competitive threats, long before they show up as lost deals.Chapters(00:00) Introduction to April Dunford (01:53) The story behind Obviously Awesome (05:33) Positioning as a cross-functional decision (07:23) Why everyone is repositioning right now (09:32) Intercom, Fin and the AI-native rebuild (11:53) Building a point of view of the future (16:52) Is the vision genuine or self-serving (18:00) How to develop your point of view (22:13) Stack Overflow, Salesforce and staying silent (23:45) Hyping the future without stalling sales (27:01) When positioning needs to change (28:42) Running a regular positioning check-in (30:29) Customer advisory boards and voice of customer (34:47) Predicting change after covid and AI (37:20) Wrap-upOur HostsLily Smith enjoys working as a consultant product manager with early-stage and growing startups and as a mentor to other product managers. She's currently Chief Product Officer at BBC Maestro, and has spent 13 years in the tech industry working with startups in the SaaS and mobile space. She's worked on a diverse range of products – leading the product teams through discovery, prototyping, testing and delivery. Lily also founded ProductTank Bristol and runs ProductCamp in Bristol and Bath.Randy Silver is a Leadership & Product Coach and Consultant. He gets teams unstuck, helping you to supercharge your results. Randy's held interim CPO and Leadership roles at scale-ups and SMEs, advised start-ups, and been Head of Product at HSBC and Sainsbury's. He participated in Silicon Valley Product Group's Coaching the Coaches forum, and speaks frequently at conferences and events. You can join one of communities he runs for CPOs (CPO Circles), Product Managers (Product In the {A}ether) and Product Coaches. He's the author of What Do We Do Now? A Product Manager's Guide to Strategy in the Time of COVID-19. A recovering music journalist and editor, Randy also launched Amazon's music stores in the US & UK.

"When something becomes a measurement, it stops becoming a good target." In a world obsessed with digital efficiency and quick fixes, the real currency of a meaningful life remains independent thought, presence, and intentional effort. In this episode of Gratitude Through Hard Times, host Chris Schembra sits down with Nishat Mehta, CEO of Lexitas. A Harvard-trained mathematician and computer scientist turned executive, Nishat breaks down how leaders can navigate rapid change by embracing dialectical thinking—holding two seemingly competing truths at the same time. From balancing bottom-line performance with human empathy to shifting parenting styles as children grow, Nishat shares key insights on Goodhart's Law, confident humility, and finding extraordinary meaning in ordinary moments. 10 Memorable Quotes: "The new normal is that it will just keep changing. It really comes down to the ability to accept the change yourself and then lead the change amongst those around you." — Nishat Mehta "Confident humility balances high confidence in one's ability to figure things out with low ego regarding one's own current knowledge." — Chris Schembra "When something becomes a measurement, it stops becoming a good target." — Nishat Mehta "Always find the extraordinary in the ordinary." — Chris Schembra "Everything is on a spectrum... the edges of the spectrum are rarely the right answer." — Nishat Mehta "Efficiency increases consumption if you're not careful." — Chris Schembra "The journey is far more important than the destination... if we are constantly changing, it's because we are succeeding at the things we needed to do before." — Nishat Mehta "We must step out of the tyranny of the 'or' and into the genius of the 'and'." — Chris Schembra "Great work is something you're supposed to do, but recognizing what might seem ordinary is worthy of extraordinary gratitude." — Nishat Mehta "Gratitude doesn't change your circumstances; it changes your capacity to carry them." — Chris Schembra 10 Key Takeaways: Practicing Confident Humility: Balancing low ego regarding current knowledge with high confidence in a team's adaptability to solve complex, unfamiliar problems. Overcoming Goodhart's Law: Why single metrics distort business outcomes, and how pairing competing targets (like quantity vs. quality) maintains operational integrity. The "Genius of the 'And'": Replacing rigid "either/or" tradeoffs with dialectical thinking that unites radical acceptance with proactive change. Navigating Shifts in Family & Parenting: Transitioning from physical, hands-on care for young children to emotional, social mentorship as they grow into independence. Understanding Jevons Paradox in Modern Work: Recognizing how efficiency gains from AI can be swallowed by routine busyness unless leaders intentionally safeguard time for human connection. Harnessing "Collective Effervescence": Leveraging physical experiences, shared sports, and community gatherings to foster genuine human harmony and connection. Lowering Barriers to Access Justice: Applying technology and low-level AI guidance to make legal support more affordable, equitable, and fair. Change Management as a Core Leadership Skill: Shifting focus from day-to-day tactical execution toward building organizational consensus and motivating teams through continuous evolution. Finding Extraordinary Meaning in Ordinary Moments: Cultivating daily awareness to appreciate quiet family routines and ordinary acts of care that are often taken for granted. Embracing the Business Journey Over Destinations: Accepting that strategic goals evolve naturally as progress is made, making the growth process the ultimate measure of success. About our Guest: Nishat Mehta is the Chief Executive Officer of Lexitas, a leading national provider of technology-enabled litigation services and an Apax portfolio company based in Houston, Texas. He stepped into the CEO seat on January 1, 2025, having originally joined the company as President and Chief Operating Officer in March 2024. Under his leadership, Lexitas is launching AI-enabled deposition analysis, expanding its eLaw case-tracking platform, and continuing to serve law firms, insurance companies, and corporations across all 50 states. Nishat brings more than two decades of leadership across data, analytics, and enterprise technology. He most recently served as President of Global Products and Solutions and Chief Product Officer at Circana (formed from the merger of IRI and The NPD Group), where he ran the firm's global media, analytics, e-commerce, software, and consulting divisions. Prior to Circana, he led the customer communications team at 84.51° (Kroger's data-science and personalization arm), directed strategic partnerships at dunnhumby, and spent 15 years at MicroStrategy. He also serves on the Board of Directors of The E.W. Scripps Company (NASDAQ: SSP) and on the Board of Advisors of Adelaide Metrics. Nishat holds a Bachelor's degree in Applied Mathematics and a Master's degree in Computer Science, both from Harvard University. He lives in New York with his wife, Shalini, and their three children. His guiding quote, from John Wooden: ability may get you to the top, but it takes character to keep you there.

Mike Sullivan, Co-Founder & Chief Growth Officer at OneDigital and Vinay Gidwaney, Chief Product Officer also at OneDigital joins Enterprise Radio. They are co-authors … Read more The post Workforce Intelligence: The People-First Playbook for Leading Your Company Through AI Transformation appeared first on Top Entrepreneurs Podcast | Enterprise Podcast Network.

AI platforms increasingly reward customer-focused product content over technical specifications. Lucas Tieleman, co-founder and CEO of Optiversal and former Chief Product Officer at Bazaarvoice, has helped enterprise retailers convert static product catalogs into machine-readable content that performs across traditional search and AI-driven discovery. The conversation covers why answer engine optimization depends on strong underlying SEO fundamentals, how AI is reshaping the way brands approach search visibility, and why translating product specifications into customer benefits matters more than increasing content volume.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this Engineering Matters Awards episode, we celebrate the winner of the Net Zero Champion category, which recognises projects, processes, and tools that make a real contribution to reducing carbon emissions. The highest awards were to be given to those entries that demonstrate significant impact or widespread scope, or that overcome a specific challenge. Our gold-level award-winning entrant was Ceres Power for its solid oxide technology, which can generate electricity with high efficiency while avoiding the combustion and associated emissions of conventional power generation. We explore how Ceres' technology could help meet rapidly growing electricity demand, including from data centres, while supporting the transition to a lower-carbon energy system. Guest Nick Lawrence, Chief Product Officer, Ceres Power Resources For McKinsey's report, Global Energy Perspective 2025, click here For more information about the Ceres Endura and more from Ceres Power, click here

เปิดแถลงการณ์ฉบับเต็ม กนง.มีมติ ‘เอกฉันท์' ให้คงอัตราดอกเบี้ยนโยบายไว้ที่ระดับ 1.00% ต่อปี อนาคต ‘ดอกเบี้ยไทย' กับเศรษฐกิจไทย จะไปต่อทางไหน พูดคุยกับ ดร.จิติพล พฤกษาเมธานันท์ Chief Product Officer  บล. ฟินันเซีย ไซรัสรัฐบาลทรัมป์ เตรียมยกเลิกวีซ่าครั้งใหญ่ที่สุดในประวัติศาสตร์ ใครได้รับผลกระทบบ้าง 

Volume-based keyword content is quietly undermining search performance. Lucas Tieleman, CEO and co-founder of Optiversal, has helped major enterprise retailers convert static product catalogs into machine-readable content that performs across both search and AI platforms, building on experience as former Chief Product Officer at Bazaarvoice. The conversation breaks down why "sloptimization"—churning out keyword-driven posts without added value—undermines both rankings and revenue, why answer engine optimization depends on strong underlying SEO fundamentals rather than replacing them, and how transforming product data into structured, machine-readable assets drives visibility across traditional and AI-driven search.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Visual collaboration is missing from the AI era. That's the provocation Elaina O'Mahoney, Chief Product Officer at Mural, brings to this episode of The Product Podcast with Carlos (CEO at Product School). We spend all day alone in our tools, typing or talking to an LLM, and when it's time to collaborate we drop words into a doc instead of thinking together visually. Elaina makes the case that AI has quietly turned work into "solo-player mode," and that the teams who win next will be the ones who rebuild shared context and multiplayer collaboration on top of it.Elaina and Carlos get into why ideas are now cheap (you can go from a thought to a working prototype in hours) and why that makes shared context, not idea generation, the real bottleneck. She argues that everyone is a designer at heart, that product leaders should replace the five-page strategy doc with a fast prototype that conveys the North Star, and that "shipping" can mean a workflow or an agent, not just a production release. They also dig into the crowded "where work happens" landscape (Slack, Teams, Jira, Linear, Notion) and the blank-canvas gap around how and why decisions actually get made, how to create safe spaces for people to try AI and fail inside large enterprises, and the pricing tension between legacy seat-based SaaS and AI-native usage models.What you'll learn:- Why Elaina says visual collaboration is "absent" in the AI era, and why that matters- The "solo-player mode" problem: how AI made work lonely, and what multiplayer should look like- Why ideas are now cheap, and how that shifts the bottleneck to shared context and faster decisions- Why the real blank space isn't planning or chat, but how and why decisions get made- The case that everyone is a designer, and how visual thinking speeds up decisions- How a CPO ships to demo a direction (a prototype instead of a strategy doc)- What's still scarce in an AI world: data science, taste, and synthesizing analytics- How to create safe, low-risk spaces for teams to try AI and fail inside big enterprises- Why smaller "champion" teams beat top-down rollouts, and how internal builders spread practices- The pricing dilemma: seat-based SaaS vs. AI-native usage modelsChapters:00:00 Intro00:59 Intro: Elaina O'Mahoney, CPO at Mural01:31 Mural's origin as a collaboration canvas03:01 Multiplayer vs. AI's solo-player mode04:23 Ideas are cheap now: idea to prototype in hours05:44 The competitive landscape and convergence08:31 The blank space nobody owns: how decisions get made09:22 Lowering the bar so everyone can design11:33 Everybody should be shipping now12:25 Shipping to demo, not to production14:04 Creating safe spaces to try AI in the enterprise17:10 Forward-deployed engineers19:14 Building a community around Mural22:11 The pricing dilemma: SaaS vs. AI-native usage24:07 Measuring real AI impact26:19 How Elaina structures her team28:20 The innovator's dilemma30:03 From annual QBRs to monthly loops31:05 Ten years of Mural, and a World Cup sign-offConnect with the Guest:Elaina O'Mahoney, Chief Product Officer, MuralLinkedIn: https://www.linkedin.com/in/eomahoney/Host: Carlos, CEO at Product SchoolLinkedIn: https://www.linkedin.com/in/villaumbrosia/About Mural: Mural is a visual collaboration platform built for teams to brainstorm, converge, and make decisions together on a shared canvas. Originally created by co-founders in Argentina, it scaled rapidly during the shift to remote work.About the Product Podcast: Product School's podcast brings you candid conversations with the founders and product leaders shaping tech.Social Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

Julia Barham leads a CX acquisition team at Progressive Insurance and is the author of The Product Management Playbook, published by Rosenfeld Media in July 2026. She wrote it to close what she sees as a coaching gap in the profession: a decade of product transformations has produced far more people with the title than people who have been taught end-to-end craft. In this episode she makes the case for treating ambiguity as a condition of the job rather than a problem to be solved, and walks through the things that quietly break when a product starts to scale.Key takeawaysFrameworks come and go, but the questions endure. Julia structured her book around why something matters, who it is for, what needs building and when, because no methodology eliminates ambiguity, it only reduces it.Organisational ambiguity is the least discussed of the four ambiguities PMs face, and the one that separates individual contributors from leaders. Waiting for the perfect operating model, funding model or team shape is a way of not moving.If you have to be in every room to answer every question, you are scaling chaos. Durable artefacts, bug severity rubrics and self-service dashboards let the team make calls without you.Synthesis is where shared context gets built, and offloading it to an AI tool quietly removes the thing that made it valuable. Do it together, monthly, with the customer, platform and business data in the same room.Chasing growth before product market fit turns your economics upside down. Products commonly take two years to find fit, sometimes five, and retention is the strongest signal that you have it.Julia spent nine months fixing latency on an inherited platform because of shortcuts taken at launch. The cost was measured in millions of lost revenue, not just engineering time.Attaching a monetary value to technical debt is what turns a product manager from a stick in the mud into a steward of the business. Treat your product like a P&L whether you own one or not.A product at scale needs a portfolio, not a backlog: optimisation, strategic bets, capability work, and honest capacity set aside for run-the-business support.AI belongs in the toolkit, not in the chair. If you cannot call BS on the output, you do not know enough to be doing the job.Chapters(00:00) Don't scale chaos(01:01) Introducing Julia Barham(03:01) The coaching gap that prompted the book(03:57) Why the book is built around questions, not frameworks(06:06) Has product management ever been deterministic?(07:47) The four ambiguities every product manager faces(10:00) Does organisational ambiguity change with company size?(12:57) The 21 plays and how to use them(15:35) Getting your reps in across the product lifecycle(17:07) What breaks when products and teams scale(17:59) Mistake one: needing to be in every room(20:30) Building shared context across distributed teams(23:51) The ways of working exercise(24:19) Mistake two: chasing growth before product market fit(25:56) How to measure product market fit(27:16) Mistake three: scaling expensive problems(29:42) Putting a price on technical debt(31:54) When taking on debt is the right call(34:22) Naming the mode your product is in(35:09) Mistake four: running your product as a portfolio(37:39) The one problem Julia would make disappear(39:25) What AI changes, and what it does not(42:26) Wrap-upReferencedThe Product Management Playbook, Julia Barham, Rosenfeld Media: https://rosenfeldmedia.com/books/product-management-playbook/Use discount code MTP20 for 20% off at Rosenfeld MediaSample chapter: https://rosenfeldmedia.com/sample-chapter-the-product-management-playbook/Dan Olsen and the product market fit pyramid: https://dan-olsen.comTesting Business Ideas, David BlandProgressive Insurance: https://www.progressive.comPioneers, settlers and town planners, Simon Wardley: https://blog.gardeviance.org/2015/03/on-pioneers-settlers-town-planners-and.htmlOur HostsLily Smith enjoys working as a consultant product manager with early-stage and growing startups and as a mentor to other product managers. She's currently Chief Product Officer at BBC Maestro, and has spent 13 years in the tech industry working with startups in the SaaS and mobile space. She's worked on a diverse range of products – leading the product teams through discovery, prototyping, testing and delivery. Lily also founded ProductTank Bristol and runs ProductCamp in Bristol and Bath.Randy Silver is a Leadership & Product Coach and Consultant. He gets teams unstuck, helping you to supercharge your results. Randy's held interim CPO and Leadership roles at scale-ups and SMEs, advised start-ups, and been Head of Product at HSBC and Sainsbury's. He participated in Silicon Valley Product Group's Coaching the Coaches forum, and speaks frequently at conferences and events. You can join one of communities he runs for CPOs (CPO Circles), Product Managers (Product In the {A}ether) and Product Coaches. He's the author of What Do We Do Now? A Product Manager's Guide to Strategy in the Time of COVID-19. A recovering music journalist and editor, Randy also launched Amazon's music stores in the US & UK.

Podcast: CYBR.SEC.CAST (LS 25 · TOP 10% what is this?)Episode: Pulling Pranks with Roman ArutyunovPub date: 2026-08-19Get Podcast Transcript →powered by Listen411 - fast audio-to-text and summarizationIn this episode of CYBR.SEC.CAST, Michael and Sam sit down with Roman Arutyunov, Co-Founder and Chief Product Officer at Xage, to explore how cybersecurity must evolve in the age of agentic AI. Roman shares his journey from early cybersecurity work to protecting critical infrastructure and explains why Zero Trust is more important than ever as AI agents gain greater access to systems, data, and critical resources. Roman also covers practical ways organizations can implement Zero Trust without creating a complex patchwork of security tools - and why protecting interactions at every layer is becoming essential.This episode is sponsored by XageThings Mentioned:Xage - https://xage.com/Mirai Virus - https://en.wikipedia.org/wiki/Mirai_(malware)Agentic AI Is Pushing Zero Trust Into Its Next Phase - https://www.cybrsecmedia.com/agentic-ai-is-pushing-zero-trust-into-its-next-phase/Do you have a question for the hosts? Reach out to us at media@cscgroupllc.com In this episode:Host: Michael FarnumHost: Sam Van RyderGuest: Roman ArutyunovDirector: Bill BrennerProducer: Lauren AndrusMusic by: August HoneyKeep up with our Conferences and Events:LinkedInXFacebookInstagramTikTokCYBR.SEC.CON.OT.SEC.CON.CYBR.HAK.CON.Keep up with CYBR.SEC.Media:LinkedInXFacebookInstagramTikTokYouTubeLearn About CYBR.SEC.Careers Non-Profit EffortsCYBR.SEC.CareersSubscribe to the podcast: AppleSpotifyYouTubeListen to our other shows:CYBR.HAK.CASTCYBR.MindedCYBR.Signal Thank you to our Media Partners:CYBR.SEC.CON.Breaking Through in Cybersecurity MarketingCYBR.SEC.CON. and OT.SEC.CON. OGGN (Oil & Gas Global Network)UtilSecPacket PushersCYBR.SEC.CON. and CYBR.HAK.CON. BarCode PodcastCyber Distortion PodcastKill Chain RadioThe Phillip Wylie ShowVulnerable UThe podcast and artwork embedded on this page are from CYBR.SEC.Media, which is the property of its owner and not affiliated with or endorsed by Listen Notes, Inc.

In this special episode, we are joined by Mike Sullivan, Co-Founder and Chief Growth Officer at OneDigital, and Vinay Gidwaney, OneDigital's Chief Product Officer, to discuss their new book, Workforce Intelligence: The People-First Playbook for Leading Your Company Through AI Transformation. Together, they offer a practical, pro-human framework for navigating a future where artificial intelligence becomes deeply embedded in how organizations operate.   We explore why leaders should focus on tasks rather than headcount, how AI can amplify uniquely human capabilities, and why companies may need to rethink how they manage their workforce. Mike and Vinay explain their concepts of reducible and irreducible skills, AI coworkers, workforce intelligence, collaborative AI use, and the importance of building an organizational intelligence layer. They also share practical lessons from OneDigital's own AI transformation—including why leadership activation, trust, reskilling, and a partnership between technical and non-technical leaders are essential.   This conversation offers an alternative to the prevailing narrative of AI-driven job elimination. Instead, it asks a bigger question: if AI can take on more of the work we currently do, what might humans become capable of doing next?   Key Points From This Episode: (0:00:00) Highlights. (0:00:25) Introduction. (0:01:23) Why AI adoption affects employers, employees, and financial markets—and why the conversation is relevant far beyond technology. (0:02:27) Two possible paths for companies: replacing people with AI or using AI to amplify human capabilities. (0:03:53) How PWL is already using AI to help financial planners and portfolio managers work more strategically and serve clients better. (0:06:22) Mike and Vinay's five-year partnership around deploying AI inside OneDigital. (0:09:07) The "radiating red dot": Why Mike's analysis suggested that up to 25% of OneDigital's workforce could be disrupted by AI. (0:11:09) "See faces, not headcount": The decision to pursue transformation by amplifying people rather than simply reducing jobs. (0:12:19) Why Mike and Vinay felt a responsibility to offer a more practical, human-first narrative about AI and work. (0:13:40) Vinay's realization that widespread access to AI makes human differentiation even more important. (0:17:22) Mike's first experience with an AI coworker—and the endless possibilities it unlocked for curiosity and exploration. (0:18:22) Human intelligence versus artificial intelligence: Why AI's greatest value may be its ability to help people think differently. (0:22:19) Why the future of work should be analyzed at the task level rather than through predictions about jobs disappearing. (0:23:58) The coming reskilling challenge—and why the allocation of work between AI and humans needs to be more deliberate. (0:25:12) Why Vinay believes companies that discard their human talent could lose their most important competitive differentiation. (0:26:30) Why AI transformation should be viewed as a "movie, not a snapshot," with work continually being reshaped. (0:28:10) What "workforce intelligence" means: Managing the combined intelligence of human talent and AI talent. (0:30:07) Why Mike and Vinay believe HR—not just IT—must play a central role in leading the transition to a blended workforce. (0:31:54) Reducible versus irreducible skills: Letting AI handle work that can be broken into processes while humans spend more time on judgment, experience, and other "squishy" capabilities. (0:34:10) Applying the framework to financial planning: AI for modeling and information processing, humans for judgment, relationships, and helping clients navigate life decisions. (0:37:00) How AI can reduce meeting preparation from hours to minutes while generating insights that would otherwise be missed. (0:37:48) The importance of trust and communication as employees try to understand what AI means for their future. (0:39:53) The Workforce Intelligence score: Treating AI as talent and measuring the evolving mix of human and AI work. (0:42:09) Transactional versus collaborative AI use—and why collaboration can be more amplifying for both people and organizations. (0:45:40) Why companies need agency over their AI systems and should think carefully about intelligence lock-in. (0:48:47) Codifying organizational intelligence: Building systems where human expertise improves AI, which in turn helps humans become more capable. (0:50:24) What it means to become "activated" by AI—and how using AI as a coach and teacher can expand human potential. (0:52:44) Ambient AI: Systems that continuously observe information and surface patterns when human judgment is needed. (0:54:11) The Charlotte-Denver redundancy and the challenge of making the best organizational intelligence available to everyone. (0:57:26) OneDigital's five-tier fluency model for developing AI capabilities across employees, advanced users, managers, and builders. (1:00:13) Why democratized software development creates a new governance challenge—and how AI may help manage it. (1:00:54) Why OneDigital gives AI coworkers names, faces, profiles, skill sets, and human managers. (1:04:01) Mike's belief in the dignity of work—and why employers need to approach the AI transition with humanity and care. (1:06:53) Vinay's belief in human potential and why the goal should be to expand what people are capable of doing. (1:08:56) Why organizations should avoid measuring AI success solely through cost cutting and instead consider human amplification. (1:12:41) The four questions for Monday morning: Turning big ideas about AI transformation into practical actions leaders can take immediately. (1:13:55) Why AI transformation needs leadership from the top and a partnership between someone who understands technology and someone who deeply understands the business. (1:15:40) Leadership activation: Why organizations are unlikely to change until their leaders personally experience how AI can transform their own work. (1:17:44) What we still don't know about AI—and why the guests believe we are still in the very early innings of this transformation. (1:18:55) The three-minute-mile analogy: AI may optimize human minds in ways we cannot yet imagine. (1:20:00) A final call for a pro-humanity, blended workforce—and the need to move faster in adapting to what AI makes possible.   Links From Today's Episode: Meet with PWL Capital: https://calendly.com/d/3vm-t2j-h3p Rational Reminder on iTunes — https://itunes.apple.com/ca/podcast/the-rational-reminder-podcast/id1426530582. Rational Reminder on Instagram — https://www.instagram.com/rationalreminder/ Rational Reminder on YouTube — https://www.youtube.com/channel/ Benjamin Felix — https://pwlcapital.com/our-team/ Benjamin on X — https://x.com/benjaminwfelix Benjamin on LinkedIn — https://www.linkedin.com/in/benjaminwfelix/   Editing and post-production work for this episode was provided by The Podcast Consultant (https://thepodcastconsultant.com)

What would change if a customer could return three days later through a different channel and continue the same conversation without repeating a single detail? In this episode of Tech Talks Daily, I speak with Paul Adams, Chief Product Officer at Fin, the company previously known as Intercom. Paul has spent almost 13 years with the business and provides a candid account of how it abandoned its previous roadmap, placed a company-wide bet on AI, and rebuilt its products and working practices around AI agents. Our conversation begins with Fin's move from a customer service agent toward what Paul calls a single customer agent. The idea is that customers do not care whether their request belongs to sales, service, or customer success. They want the company to understand their situation and help them complete the task. Paul explains how AI agents can bring customer history, company knowledge, operational data, and business goals into the same conversation. This could allow an agent to resolve an issue, support a purchase, recognize a valuable customer, or transfer the conversation to a human without losing the context already provided. We also examine the economics behind poor customer service. Many companies are not ignoring customers through a lack of concern. They are receiving volumes of requests that cannot economically be handled by adding people alone. Paul says some Fin customers are resolving between 70 and 90 percent of customer queries through AI. Rather than seeing entire teams disappear, he is observing employees move into customer success, knowledge management, AI supervision, and higher-touch services. The episode also provides an unusually candid account of what it took to rebuild an established SaaS company around AI. Paul describes the process as brutal. Strategies were discarded, familiar processes were removed, and some people decided the new direction was not for them. His advice is to prioritize speed, place smaller experiments in front of real customers, and learn from evidence rather than waiting for every internal condition to become perfect. Paul also recalls working on early versions of mobile YouTube and Gmail when colleagues questioned whether anyone would watch video or answer email on a phone. Those stories provide a timely warning about judging new technology by its early limitations. Could AI agents finally give customers continuity across sales, service, and support, or will internal company structures remain the greater obstacle? Listen to the conversation and share your thoughts with me.

Two identical searches now return different results across AI platforms, upending ranking logic.Lucas Tieleman, co-founder and CEO of Optiversal and former Chief Product Officer at Bazaarvoice, helps enterprise retailers convert static product catalogs into machine-readable content optimized for AI-driven discovery. He argues that answer engine optimization depends on strong SEO fundamentals rather than a separate discipline, and that success now hinges on content relevance to individual searchers rather than fixed position rankings. Tieleman outlines how brands can use performance data to validate whether their content actually serves shopper intent, shifting content strategy from volume-based production to measurable relevance.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Innovation comes in many areas, and compliance professionals need to not only be ready for it but also embrace it. Join Tom Fox, the Voice of Compliance, as he visits with top innovative minds, thinkers, and creators in the award-winning Innovation in Compliance podcast. In this episode, host Tom visits with Brian Holyfield, Co-Founder & Chief Product Officer at SendSafely. Holyfield discusses why the right compliance question on cybersecurity is not whether a breach will happen but when and what data will be exposed, often through vendors. He explains “blast radius” as the scope of access and data reachable during an incident and argues organizations should prioritize architecture, data minimization, and retention controls alongside prevention. He also highlights risks from accumulated file attachments, overbroad user access, interconnected systems using OAuth tokens, and “standing access” via long-lived machine credentials that can be abused without obvious login anomalies. Holyfield discusses examples involving ServiceNow and Salesforce that illustrate platform vulnerabilities, trusted upstream vendor connections, and end-user compromise, and advises leaders to inventory connections, define retention/archiving, and move sensitive data out of frontline platforms; SendSafely positions itself as an end-to-end encrypted trust layer, including for AI chatbot attachments. Key highlights: Assume the Breach Blast Radius Explained ServiceNow and Salesforce Lessons Board-Level Questions AI Changes the Game Compliance and Governance Fit Resources: SendSafely Brian Holyfield on LinkedIn Innovation in Compliance was recently honored as the Number 4 podcast in Risk Management by 1,000,000 Podcasts

How much of your technology stack is being held together by people swiveling between screens, copying information, and quietly compensating for systems that cannot communicate? In this episode, I speak with John Foreman, Chief Product Officer at Clio, about what he calls the "swivel chair problem." John previously served as Chief Product Officer at Mailchimp and Podium, and now helps guide product development at a company seeking to support the complete operation of a law firm. We discuss why legal professionals have moved from understandable caution around AI toward increasingly sophisticated daily use. John explains why concerns about client confidentiality, intellectual property, model training, and data access initially slowed adoption, as well as why lawyers are now helping set the pace for responsible professional AI use. Our conversation also examines why disconnected technology stacks make AI appear far less capable. People can interpret information across documents, billing platforms, case management tools, email, and court systems. An AI system cannot perform the same work unless it receives the necessary context and access. John also explains why the familiar chatbot may be the wrong interface for many jobs. Some AI tasks should happen quietly, while work involving legal filings and client records requires structured review, accountability, and human approval. With lawyers spending an average of 62% of their time on nonbillable work, the immediate opportunity could include intake, billing, timekeeping, reviews, document processing, and filing. These lessons extend well beyond legal services. Where is the swivel chair problem hiding inside your organization? Listen to the conversation and share your thoughts with me.

The 2026 Small Business Owner Perspective Survey by U.S. Bank gets to the heart of how technology, demographic shifts and world news have affected the attitudes and performance of SMBs everywhere. Shruti Patel, U.S. Bank's Executive Vice President & GM, Business Banking, Chief Product Officer, discusses the findings and makes a case for across-the-board optimism in tough economic times.

Artificial intelligence has quickly evolved from a productivity tool into an active participant in many organizations' daily operations. As organizations give AI greater autonomy within their environment, they're also granting them access to sensitive systems and data. That creates a new challenge for IT and security teams: How do you enable AI to assist productivity without compromising security? Rob Allen, Chief Product Officer at ThreatLocker, joins Business Security Weekly to discuss how zero trust principles can prevent an AI breakout. Rather than relying solely on the AI tool's built-in safeguards, organizations can choose to enforce security policies using ThreatLocker. Rob will discuss how ThreatLocker can enforce AI boundaries through Allowlisting, Ringfencing™, Endpoint Firewall, and Web Content Control, with Community Policies that govern what agentic AI tools can run, do, access, and reach. Segment resources: - https://www.threatlocker.com/blog/the-principle-of-least-privilege-for-ai-agents - https://www.threatlocker.com/blog/applying-threatlocker-to-agentic-ai-tools - https://www.threatlocker.com/blog/why-the-five-eyes-alliance-sees-zero-trust-as-the-best-defense-against-agentic-ai-threats This segment is sponsored by ThreatLocker. Visit https://securityweekly.com/threatlocker to learn more about them! In the leadership and communications segment, 3 cybersecurity issues that should keep every CEO awake at night, You Don't Find Your Leadership Style. You Mentor Your Way Into It., Cybersecurity Starts With Communication – And We May Be Getting It Wrong, and more! Visit https://www.securityweekly.com/bsw for all the latest episodes! Show Notes: https://securityweekly.com/bsw-461

In this episode of Lab Rats to Unicorns, John Flavin sits down with Manish Singh, co-founder and Chief Product Officer, and Sean Sullivan, co-founder and Chief Technology Officer of MemQ to explore the science, infrastructure, and entrepreneurship shaping the future of quantum technology. Manish and Sean share the very different paths that brought them into quantum. Manish reflects on moving from chemical engineering in India to semiconductor R&D at TSMC in Taiwan before pursuing quantum research in Chicago. Sean discusses his background in materials science, his transition into quantum information technologies at Argonne National Laboratory, and the collaborative environment that ultimately brought the two founders together. Throughout the conversation, Manish and Sean break down what quantum computing actually is, why networking will be critical to scaling useful quantum systems, and how MemQ is developing technology to connect quantum processors across different qubit types. They also discuss building a frontier technology startup, proving manufacturability at industrial scale, working with DARPA, attracting multidisciplinary talent, and why Chicago has become an important center for the emerging quantum industry.

Tiama Hanson-Drury is CPTO at Opus 2, the legal technology company behind the systems that run some of the world's largest and most high-stakes litigation. She started her career in sales, moved into product in 2010 and has spent the last 16 years split roughly evenly between individual contributor and leadership roles. Her verdict on AI in product organisations is neither evangelism nor scepticism: the tooling has removed software as a bottleneck, but the markers of quality that mattered before AI have not changed, and teams that forget them end up shipping slop and burning out. In this episode, we discuss:Why a sales background is better preparation for product than an engineering one, and how to lead engineers without pretending to be an expertHow the promise of doing more with AI is producing overload and burnout, and what leaders owe their teams in responseWhy high AI adoption scores mean nothing if pull request sizes are ballooning and someone else has to review the outputThe three things Tiama looks for in her teams now: outcome focus over craft, curiosity, and a culture of sharing failure as readily as successWhy the right move is not to hand three of your seven steps to AI, but to start again from the outcome you wantHow Opus 2 went from shipping every six to 12 weeks to shipping daily, and why that made documentation and planning more important, not lessThe case for betting on humans in the loop when your customers explicitly prefer itWhy Opus 2 is still hiring juniors, and how to build commercial judgment when the groundwork can be skippedThe one situation where Tiama tells people to let AI write the first draft rather than the secondChapters(01:31) From sales to product(03:24) Why the move is less obvious than it sounds(04:34) Leading engineering without an engineering background(06:28) How outsider questions sharpen engineering teams(07:36) What AI has changed for a CPTO(08:16) Overload, burnout and the pressure to token max(10:32) Adoption scores versus quality signals(11:39) What AI adoption actually looks like inside law firms(12:42) Outcomes over output(14:07) How Opus 2 built its AI strategy(16:07) Removing friction from an AI rollout(16:53) Partnering with AI instead of splitting up the steps(18:08) A message from Mike Belsito(19:40) Three things AI asks of a team(21:47) More agency, and why planning matters more(23:51) Scaling a team on conflicting evidence(26:09) Betting on humans in the loop(27:36) Why Opus 2 keeps hiring juniors(29:44) Building judgment when the work moves faster(32:36) Sharing your own AI operating system(33:22) AI slop, CVs and the hiring algorithm(36:17) Top tips for a product career in the age of AI(38:36) Wrap-upReferencedOpus 2: https://www.opus2.comOpus 2 announces addition of Tiama Hanson-Drury as chief product and technology officer: https://www.opus2.com/news/opus-2-announces-cpto-tiama-hanson-drury/Minna Technologies, where Tiama was previously chief product officer: https://minnatechnologies.comDX, the developer intelligence platform used to track squad performance: https://getdx.comDORA metrics: https://dora.devVote for Mike Belsito's South by Southwest 2027 session: https://tinyurl.com/belsitosxswWhere to find Tiama Hanson-DruryLinkedIn: https://www.linkedin.com/in/tiamahansondruryOur HostsLily Smith enjoys working as a consultant product manager with early-stage and growing startups and as a mentor to other product managers. She's currently Chief Product Officer at BBC Maestro, and has spent 13 years in the tech industry working with startups in the SaaS and mobile space. She's worked on a diverse range of products – leading the product teams through discovery, prototyping, testing and delivery. Lily also founded ProductTank Bristol and runs ProductCamp in Bristol and Bath.Randy Silver is a Leadership & Product Coach and Consultant. He gets teams unstuck, helping you to supercharge your results. Randy's held interim CPO and Leadership roles at scale-ups and SMEs, advised start-ups, and been Head of Product at HSBC and Sainsbury's. He participated in Silicon Valley Product Group's Coaching the Coaches forum, and speaks frequently at conferences and events. You can join one of communities he runs for CPOs (CPO Circles), Product Managers (Product In the {A}ether) and Product Coaches. He's the author of What Do We Do Now? A Product Manager's Guide to Strategy in the Time of COVID-19. A recovering music journalist and editor, Randy also launched Amazon's music stores in the US & UK.

Artificial intelligence has quickly evolved from a productivity tool into an active participant in many organizations' daily operations. As organizations give AI greater autonomy within their environment, they're also granting them access to sensitive systems and data. That creates a new challenge for IT and security teams: How do you enable AI to assist productivity without compromising security? Rob Allen, Chief Product Officer at ThreatLocker, joins Business Security Weekly to discuss how zero trust principles can prevent an AI breakout. Rather than relying solely on the AI tool's built-in safeguards, organizations can choose to enforce security policies using ThreatLocker. Rob will discuss how ThreatLocker can enforce AI boundaries through Allowlisting, Ringfencing™, Endpoint Firewall, and Web Content Control, with Community Policies that govern what agentic AI tools can run, do, access, and reach. Segment resources: - https://www.threatlocker.com/blog/the-principle-of-least-privilege-for-ai-agents - https://www.threatlocker.com/blog/applying-threatlocker-to-agentic-ai-tools - https://www.threatlocker.com/blog/why-the-five-eyes-alliance-sees-zero-trust-as-the-best-defense-against-agentic-ai-threats This segment is sponsored by ThreatLocker. Visit https://securityweekly.com/threatlocker to learn more about them! In the leadership and communications segment, 3 cybersecurity issues that should keep every CEO awake at night, You Don't Find Your Leadership Style. You Mentor Your Way Into It., Cybersecurity Starts With Communication – And We May Be Getting It Wrong, and more! Show Notes: https://securityweekly.com/bsw-461

Artificial intelligence has quickly evolved from a productivity tool into an active participant in many organizations' daily operations. As organizations give AI greater autonomy within their environment, they're also granting them access to sensitive systems and data. That creates a new challenge for IT and security teams: How do you enable AI to assist productivity without compromising security? Rob Allen, Chief Product Officer at ThreatLocker, joins Business Security Weekly to discuss how zero trust principles can prevent an AI breakout. Rather than relying solely on the AI tool's built-in safeguards, organizations can choose to enforce security policies using ThreatLocker. Rob will discuss how ThreatLocker can enforce AI boundaries through Allowlisting, Ringfencing™, Endpoint Firewall, and Web Content Control, with Community Policies that govern what agentic AI tools can run, do, access, and reach. Segment resources: - https://www.threatlocker.com/blog/the-principle-of-least-privilege-for-ai-agents - https://www.threatlocker.com/blog/applying-threatlocker-to-agentic-ai-tools - https://www.threatlocker.com/blog/why-the-five-eyes-alliance-sees-zero-trust-as-the-best-defense-against-agentic-ai-threats This segment is sponsored by ThreatLocker. Visit https://securityweekly.com/threatlocker to learn more about them! In the leadership and communications segment, 3 cybersecurity issues that should keep every CEO awake at night, You Don't Find Your Leadership Style. You Mentor Your Way Into It., Cybersecurity Starts With Communication – And We May Be Getting It Wrong, and more! Visit https://www.securityweekly.com/bsw for all the latest episodes! Show Notes: https://securityweekly.com/bsw-461

All sorts of cybersecurity disciplines are adopting agents to help humans save time and automate routine activities. Sai Kiran Uppu describes his work on creating a platform for agents to analyze external threat intel, examine internal systems, and present triage decisions to operators. This type of work is especially useful to orgs that deal with petabytes of data and thousands of systems. And, as Kiran notes, it's important to keep that scale from blowing up your budget or turning triage into a procession of false positives. Ideally, this kind of threat intel that's paying attention to attack trends and searching internal systems for evidence of compromise also turns into proactive defenses. We talk about some of the ways to engage developers to improve security visibility into their services and harden their designs against common attacks. After that discussion we're running two sponsored interviews from Black Hat. AI Pentesting and the Future of Cybersecurity: Black Hat interview with Chris Wallis, Founder and CEO of Intruder This segment discusses how AI addresses the long-standing gap between traditional pentesting and automated vulnerability scanning. Intruder CEO and founder Chris Wallis dives into the nuances of AI-enabled security and how these offerings will impact mid-market security teams. Segment Resources: https://www.intruder.io/platform/ai-pentesting https://www.intruder.io/blog/ai-pentesting-the-depth-of-a-pentest-on-demand https://www.intruder.io/blog/ai-web-app-pentesting-test-on-every-major-release Intruder's continuous exposure management platform helps security, IT, and engineering teams stop breaches before they start. For more information about Intruder's products and services, please visit https://securityweekly.com/intruderbh. How Menlo Security Is Securing AI Agents from Prompt Injection: Black Hat Interview with Ramin Farassat, Chief Product Officer of Menlo Enterprises are deploying AI agents like Microsoft Copilot, Google Gemini, and Claude Code faster than they can secure them, and attackers are exploiting that gap through prompt injection. Hidden instructions get buried in web pages, files, and even images that a human would never notice but an AI agent reads and acts on. Menlo Security is building Menlo Agent Runtime Security (MARS) to close that gap, running every agent session in an isolated cloud that sanitizes content before an agent can act on it. Ramin Farassat, Menlo Security's Chief Product Officer, will discuss why the exposure lives in the connectors and integrations around the model rather than the model itself, and how security teams can put controls on the agent attack surface without blocking agentic AI outright. Segment Resources: https://www.menlosecurity.com/product/ai-agent-security MARS is now available today, please visit https://securityweekly.com/menlobh Visit https://www.securityweekly.com/asw for all the latest episodes! Show Notes: https://securityweekly.com/asw-396

All sorts of cybersecurity disciplines are adopting agents to help humans save time and automate routine activities. Sai Kiran Uppu describes his work on creating a platform for agents to analyze external threat intel, examine internal systems, and present triage decisions to operators. This type of work is especially useful to orgs that deal with petabytes of data and thousands of systems. And, as Kiran notes, it's important to keep that scale from blowing up your budget or turning triage into a procession of false positives. Ideally, this kind of threat intel that's paying attention to attack trends and searching internal systems for evidence of compromise also turns into proactive defenses. We talk about some of the ways to engage developers to improve security visibility into their services and harden their designs against common attacks. After that discussion we're running two sponsored interviews from Black Hat. AI Pentesting and the Future of Cybersecurity: Black Hat interview with Chris Wallis, Founder and CEO of Intruder This segment discusses how AI addresses the long-standing gap between traditional pentesting and automated vulnerability scanning. Intruder CEO and founder Chris Wallis dives into the nuances of AI-enabled security and how these offerings will impact mid-market security teams. Segment Resources: https://www.intruder.io/platform/ai-pentesting https://www.intruder.io/blog/ai-pentesting-the-depth-of-a-pentest-on-demand https://www.intruder.io/blog/ai-web-app-pentesting-test-on-every-major-release Intruder's continuous exposure management platform helps security, IT, and engineering teams stop breaches before they start. For more information about Intruder's products and services, please visit https://securityweekly.com/intruderbh. How Menlo Security Is Securing AI Agents from Prompt Injection: Black Hat Interview with Ramin Farassat, Chief Product Officer of Menlo Enterprises are deploying AI agents like Microsoft Copilot, Google Gemini, and Claude Code faster than they can secure them, and attackers are exploiting that gap through prompt injection. Hidden instructions get buried in web pages, files, and even images that a human would never notice but an AI agent reads and acts on. Menlo Security is building Menlo Agent Runtime Security (MARS) to close that gap, running every agent session in an isolated cloud that sanitizes content before an agent can act on it. Ramin Farassat, Menlo Security's Chief Product Officer, will discuss why the exposure lives in the connectors and integrations around the model rather than the model itself, and how security teams can put controls on the agent attack surface without blocking agentic AI outright. Segment Resources: https://www.menlosecurity.com/product/ai-agent-security MARS is now available today, please visit https://securityweekly.com/menlobh Show Notes: https://securityweekly.com/asw-396

All sorts of cybersecurity disciplines are adopting agents to help humans save time and automate routine activities. Sai Kiran Uppu describes his work on creating a platform for agents to analyze external threat intel, examine internal systems, and present triage decisions to operators. This type of work is especially useful to orgs that deal with petabytes of data and thousands of systems. And, as Kiran notes, it's important to keep that scale from blowing up your budget or turning triage into a procession of false positives. Ideally, this kind of threat intel that's paying attention to attack trends and searching internal systems for evidence of compromise also turns into proactive defenses. We talk about some of the ways to engage developers to improve security visibility into their services and harden their designs against common attacks. After that discussion we're running two sponsored interviews from Black Hat. AI Pentesting and the Future of Cybersecurity: Black Hat interview with Chris Wallis, Founder and CEO of Intruder This segment discusses how AI addresses the long-standing gap between traditional pentesting and automated vulnerability scanning. Intruder CEO and founder Chris Wallis dives into the nuances of AI-enabled security and how these offerings will impact mid-market security teams. Segment Resources: https://www.intruder.io/platform/ai-pentesting https://www.intruder.io/blog/ai-pentesting-the-depth-of-a-pentest-on-demand https://www.intruder.io/blog/ai-web-app-pentesting-test-on-every-major-release Intruder's continuous exposure management platform helps security, IT, and engineering teams stop breaches before they start. For more information about Intruder's products and services, please visit https://securityweekly.com/intruderbh. How Menlo Security Is Securing AI Agents from Prompt Injection: Black Hat Interview with Ramin Farassat, Chief Product Officer of Menlo Enterprises are deploying AI agents like Microsoft Copilot, Google Gemini, and Claude Code faster than they can secure them, and attackers are exploiting that gap through prompt injection. Hidden instructions get buried in web pages, files, and even images that a human would never notice but an AI agent reads and acts on. Menlo Security is building Menlo Agent Runtime Security (MARS) to close that gap, running every agent session in an isolated cloud that sanitizes content before an agent can act on it. Ramin Farassat, Menlo Security's Chief Product Officer, will discuss why the exposure lives in the connectors and integrations around the model rather than the model itself, and how security teams can put controls on the agent attack surface without blocking agentic AI outright. Segment Resources: https://www.menlosecurity.com/product/ai-agent-security MARS is now available today, please visit https://securityweekly.com/menlobh Visit https://www.securityweekly.com/asw for all the latest episodes! Show Notes: https://securityweekly.com/asw-396

For twenty-five years we sent the struggling kid to the back of the room with headphones on. Todd Brekhus of Renaissance explains why that model broke personalized learning, and how teacher-facing AI hands the room back to you. Todd Brekhus is Chief Product Officer at Renaissance, General Manager of Nearpod, a former English teacher and technology director, and the creator of the myON literacy platform. We recorded this conversation at ISTE 2026. In this episode, you'll learn: - Why "personalized learning" quietly pushed teachers out of the loop, and what changes when you say "personalized teaching and learning" instead - How to pull last year's skill-level data and plan two paths before tomorrow's lesson - Why back-of-the-room intervention stigmatizes kids, and how to differentiate inside the core lesson - The case for a formative check every six to eight minutes without leaving your slides - Why Renaissance deliberately chose not to build student-facing AI, and what productive struggle has to do with it This episode is sponsored by Renaissance. Renaissance Intelligence connects the loop across assessment, curriculum, instruction, practice and proficiency, so educators can act on student needs in real time. Learn more at renaissance.com/intelligence Full show notes, resources, and the complete transcript: https://www.coolcatteacher.com/e968  If this episode gave you something you can use tomorrow, leave a rating and review wherever you're listening — it helps other teachers find the show. And share it with a teacher friend who's tired of the screen-time argument. Disclosure of Material Connection: This is a sponsored episode. Renaissance has compensated me to share information about Renaissance Intelligence. However, all opinions expressed are my own. I have personally reviewed these resources and only recommend tools I believe offer genuine value to classroom teachers. My endorsement is limited to the educational products and services discussed in this episode. I am disclosing this in accordance with the Federal Trade Commission's 16 CFR, Part 255: "Guides Concerning the Use of Endorsements and Testimonials in Advertising." The sponsor has no impact on the editorial content of this show.

Missy Tannen spent five years teaching third grade and a decade as a stay-at-home mom before she ever thought about starting a company. But when she couldn't find bedding that was high-quality, ethically sourced, and traceable, she and her husband Scott started Boll & Branch out of pure frustration. On this episode of She Pivots, Missy talks about betting the family's life savings on an idea, borrowing against their own house even while sales were taking off, and what it took to scale from a garage operation to a 200-person company without losing what made it different in the first place. She's brutally honest about the mess behind the milestones (a full batch of ivory sheets that came out green!) and about running a family business—that’s now worth over $250 million—with her husband while raising their kids. Chapters: 00:00 Welcome to She Pivots 01:32 From Teacher to Entrepreneur: Missy Tannen 09:23 Stay-at-home-mom 13:04 The Birth of Boll & Branch 26:15 The Wall Street Journal Breakthrough 33:54 Growing the Business and Family Involvement 39:24 Building a Sustainable Supply Chain 41:25 The Power of Community 42:32 The Tariff Challenge 45:54 Reflecting on Missy's Journey 47:09 Production Credits Check out Boll & Branch at www.bollandbranch.com Be sure to subscribe so you never miss a pivot story, leave us a rating (it really helps!), and share this episode with a woman in your life who you think needs a little inspiration. She Pivots is a podcast created by host Emily Tisch Sussman to highlight influential women voices, share stories of bold career moves, and inspire women with interviews about career reinvention and how personal pivots can redefine professional success. Join our Substack community! Subscribe here for exclusive content and to connect with other pivoters: shepivots.substack.com Learn more about the inspiring women in our pivoter community by following us on instagram @ShePivotsThePodcast, and check out our website shepivotspod.com for resources and updates. She Pivots is proud to be an iheart podcast.Support the show: https://www.shepivotsthepodcast.com/See omnystudio.com/listener for privacy information.

Has enterprise AI finally reached the point where impressive demonstrations are no longer enough? In this episode of Tech Talks Daily, I speak with Bruce McMahon, Chief Product Officer at CallMiner, about what he describes as the industrialization of AI: the move from experimentation and excitement toward repeatable processes, measurable ROI, better customer experiences, and technology that can operate reliably at enterprise scale. Bruce explains why business leaders are increasingly asking a much simpler question about AI: how is this going to create value? Drawing on CallMiner's experience analyzing hundreds of thousands of hours of customer interactions every day, Bruce discusses how AI can surface operational inefficiencies and customer insights that were previously difficult to identify. The opportunity is not simply generating more data. Organizations need processes that get the right insight to the right person so something actually changes as a result. We also discuss how AI is changing workforce expectations. Bruce sees curiosity and adaptability becoming increasingly valuable, particularly among technical teams. As AI takes on more routine work, employees who question outputs, experiment with new approaches, and apply human judgment can become more valuable than those who rely solely on established technical knowledge. The economics of enterprise AI present another challenge. Foundation models, capabilities, and pricing continue to change rapidly, creating questions around vendor dependency and long-term costs. Bruce explains why companies may increasingly use a mixture of commercial, open-source, fine-tuned, self-hosted, and proprietary models rather than relying on one provider for everything. Governance becomes even more important as AI agents begin interacting directly with customers. We discuss red teaming, bias testing, compliance, data protection, monitoring, and why organizations need to decide which actions can be fully automated and which decisions must remain accountable to a human. Bruce also examines how AI is changing customer experience and the BPO industry. Rather than choosing between humans and AI agents, he sees value in designing systems where both can work together, with people handling interactions requiring judgment while AI manages high-volume and repetitive work. For CIOs, CTOs, COOs, customer experience leaders, and anyone responsible for enterprise AI strategy, this conversation provides a practical look at moving beyond AI pilots and turning the technology into a dependable part of business operations.  

Building a food brand around the belief that food is healing — that's the magic ✨ On The Kara Goldin Show, I sit down with Neka Pasquale, Founder and Chief Product Officer of Urban Remedy — a company on a mission to reimagine the food system and teach the world that food is healing. We talk about how Neka's background in acupuncture, Chinese medicine, nutrition, and lifestyle medicine led her to create Urban Remedy, and how wellness retreats with her patients helped spark the idea for the brand. We also get into what it takes to scale fresh, certified organic, non-GMO, gluten-free, dairy-free, and refined sugar free meals, snacks, juices, and shakes while staying true to quality and purpose. Neka shares how Urban Remedy has grown into more than 400 Whole Foods Market locations and other major retailers, how she continues to innovate around what consumers want next, and why every ingredient in Urban Remedy products is chosen for its healing properties. If you're interested in learning what it takes to build a mission-driven food brand, scale fresh products without compromising standards, or create a company around a deeply held belief — check out the interview on my podcast. You can find it here or anywhere you listen to podcasts

Blaine Billingsley is a Member of Technical Design Staff at OpenAI whose path into the field ran through music composition, spare-change website work at college, and a decade across Gmail, Airbnb, YouTube and Slack. At OpenAI he was hired to work on Presence, then redirected to solve a more immediate problem: making ChatGPT genuinely useful as a daily tool for designers. Working with a single engineer, he built the ChatGPT product design plugin — a bridge between the raw power of Codex and the day-to-day workflow of product teams. In this conversation with Randy Silver, he talks about what design actually means when your interface is a text box, why volume beats perfection in an age of infinite iteration, and why the fundamentals of good product thinking are more durable than the tools used to apply them.Key takeaways— The designer's job at an AI company has shifted from pixels to outputs. Deciding what "good" looks like, building the criteria to evaluate it, and heuristically assessing results is now a core part of the role — one that didn't exist in the same form at Gmail or Slack.— LLMs don't replace structured creativity techniques; they scale them. The crazy eights exercise squeezes eight ideas from a room of people in eight minutes. A well-directed ChatGPT session can return 80 in the same window, alone, while you're at lunch.— Volume beats perfection. The best way to make a pot isn't to try to make the best pot — it's to make a thousand pots. That logic now applies directly to prototyping: generate at scale, stay unattached, and find the nugget in the noise.— Evals are closer to synthetic user research than quality assurance. The hardest part isn't building the rubric — it's correctly anticipating what people will actually try to do. Show it to one more person and your assumptions will immediately break.— The second 80% problem hasn't gone away. Getting to a working prototype is dramatically faster; getting that prototype to production is still gruelling — and becomes harder still when platform direction shifts mid-sprint.— Small teams with AI assistance need to protect the rituals that keep them aligned. When two people can each produce a week's worth of work in an afternoon, parallel drift becomes the real collaboration risk.— Role boundaries are dissolving, but specialisations still matter. The question is less "what is your title" and more "what does the band need right now, and can you play that part?"— Experience brings judgment; freshness brings juice. The best work often comes from junior designers unconstrained by years of accumulated assumptions — and both things need to be in the room.Chapters (00:00) Introduction(01:14) Blaine's background: from music composition to product design (02:32) What design means at OpenAI (04:21) The ChatGPT product design plugin (06:12) Deciding what to build: the early exploration (10:05) Structured creativity and LLM-powered ideation (13:37) Volume over perfection: the thousand pots approach (16:13) Designing as a two-person team (20:29) What is the job now? (23:33) Evals as synthetic user research (27:08) Testing at scale when you can't know your users (30:15) How they actually did the research (33:01) The second 80%: from prototype to production (35:06) Staying aligned without roadmaps (38:19) Demo: the product design plugin (44:52) When a prototype isn't ready to ship (48:26) Design sprints, reimagined (49:27) Advice for joining an AI-first product team (52:17) The jazz analogy: experience, freshness and your role in the band Featured LinksChatGPT for Work: https://openai.com/chatgpt Codex: https://openai.com/codex Figma: https://figma.com FigJam: https://www.figma.com/figjam Linear: https://linear.appOur HostsLily Smith enjoys working as a consultant product manager with early-stage and growing startups and as a mentor to other product managers. She's currently Chief Product Officer at BBC Maestro, and has spent 13 years in the tech industry working with startups in the SaaS and mobile space. She's worked on a diverse range of products – leading the product teams through discovery, prototyping, testing and delivery. Lily also founded ProductTank Bristol and runs ProductCamp in Bristol and Bath.Randy Silver is a Leadership & Product Coach and Consultant. He gets teams unstuck, helping you to supercharge your results. Randy's held interim CPO and Leadership roles at scale-ups and SMEs, advised start-ups, and been Head of Product at HSBC and Sainsbury's. He participated in Silicon Valley Product Group's Coaching the Coaches forum, and speaks frequently at conferences and events. You can join one of communities he runs for CPOs (CPO Circles), Product Managers (Product In the {A}ether) and Product Coaches. He's the author of What Do We Do Now? A Product Manager's Guide to Strategy in the Time of COVID-19. A recovering music journalist and editor, Randy also launched Amazon's music stores in the US & UK.

We're on summer break and replaying one of our favorite episodes. This episode originally aired on September 22, 2025.A wearable can collect endless data, but it only matters if people trust it enough to change their behavior.In this replay, Oura CEO Tom Hale joins Steve and Michael to explain how the company combines clinical-grade accuracy with a consumer-friendly product. They discuss why the ring's form factor makes overnight tracking so powerful, how Oura turns physiological signals into useful guidance, and why the company is being pulled faster than expected into traditional healthcare.We cover:Why sleep data can reveal changes in the body before symptoms appearHow Oura designed a health product that supports users without judging or nagging themWhy accuracy is the foundation for trust, predictions, and behavior changeHow Oura navigates the boundary between wellness products and regulated medical devicesThe company's expansion into Medicare Advantage, women's health, metabolic health, and clinical care—About our guest:Tom Hale is the Chief Executive Officer at ŌURA and a member of its board. As the CEO he sets the company's business strategy and vision to make health a daily practice for members all over the world. He has over 30 years of experience across the technology and consumer product industry.Before joining ŌURA, Hale was president of Momentive where he drove B2B strategy and led product growth. During his time there he was instrumental in taking the company public in 2018, leading the team in key acquisitions, and driving the evolution and rebranding of the company into a multiple SAAS business. Previously, he held leadership roles at HomeAway and Linden Lab as the Chief Operating Officer and Chief Product Officer, respectively, and held executive roles at Macromedia and Adobe.Hale has a Bachelor of Arts from Harvard University and sits on the boards of Cars.com, RocketReach, and NoiseAware.—If you're enjoying the show, we would so appreciate it if you left us a review!—

What does it take to go from practicing law to becoming the Chief Product Officer of a company disrupting the legal industry with AI? In this episode of the CPO Rising series hosted by Products That Count Resident CPO Renee Niemi, LegalOn Technologies CPO Vanessa Davis will be speaking on how she made the leap from attorney to product leader, and why putting the customer first drives every major decision she makes. She also gets into how LegalOn navigated a major stack overhaul to move fully to LLMs, what the entrance of tools like Claude into legal tech means for the industry, and why DAU over MAU is her north star metric.

Football franchises run on data. Jono Luk of Sumer Sports explains how AI is changing who wins — on the field and in the stands.Full Show Notes:Most sports AI coverage focuses on stats. Jono Luk, Chief Product Officer at Sumer Sports, is thinking about something harder: measuring what a player decided, not just what they did. Sumer's computer vision tracks all 22 players up to 60 times per second, generating probabilities for every moment of every play — not to describe what happened, but to evaluate whether the best decision was made.That depth of game intelligence turns out to be useful in two places. For coaches, GMs, and scouts, it surfaces skill that box scores miss entirely. For the business side of a franchise, that same real-time game data becomes the trigger for personalized fan experiences — the right offer, the right moment, whether someone is in the stadium or watching from a sports bar. Jono calls this the before, during, and after — and argues it's the same attract-retain-monetize cycle every enterprise runs, just with a different playbook.The episode also covers what Jono wishes organizations understood before they start any AI conversation: AI isn't synonymous with LLMs. Computer vision, specialized models, and multi-component pipelines built for specific data types are doing work that frontier models simply aren't designed for. That framing matters for any enterprise buyer, not just sports franchises.What We Cover:How Sumer Sports uses computer vision to evaluate player decisions, not just outcomesWhy specialized AI models outperform general-purpose frontier models for sports analyticsThe two sides of AI in a football franchise: football operations and fan engagementHow real-time game data triggers personalized in-venue and at-home fan experiencesWhat the NIL era means for AI-assisted recruiting at college and high school levelsWhy AI in the enterprise isn't just about LLMs — and how to think about the broader toolkitThe one question Jono wants every organization to ask before deploying AIGuest Bio:Jono Luk is Chief Product Officer at Sumer Sports, a football data analytics and AI company that uses computer vision to analyze every player, every game, in real time. Before Sumer, Jono held product and technology leadership roles at Cisco. He brings a cross-industry perspective on how AI fits into larger solutions — not as a replacement for human judgment, but as the infrastructure that surfaces better decisions faster.Sumer Sports: https://www.sumersports.comJono Luk on LinkedIn: https://www.linkedin.com/in/jonoluk/ (confirm URL before publishing)Resources Mentioned:Sumer Sports: https://www.sumersports.comLopez Research: https://www.lopezresearch.com/research/

Enterprise retailers index only 40-50% of their product pages. Joe Doran, Chief Product Officer at Botify, breaks down why AI crawlers lag Google by 20 years in crawl efficiency and how JavaScript-heavy PDPs leave bots seeing just 30% of page content. The conversation covers structured product feeds as the new on-page SEO, aligning catalog data with protocols like OpenAI's Agentic Commerce Protocol and Google's Universal Commerce Protocol, and moving beyond organic traffic in isolation toward citation rate, crawl volume, and multi-touch attribution models built for zero-click discovery.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Enterprise retailers index only 40-50% of their product pages. Joe Doran, Chief Product Officer at Botify, breaks down why heavy JavaScript rendering and fragmented product data leave nearly half of retail catalogs invisible to Google and AI crawlers alike. He details the crawl budget compounding effect that shrinks indexation, the confirmation-crawl behavior LLMs use to verify and cite pages, and why structured product feeds—not visible page content—now determine agentic commerce visibility. He also makes the case for rethinking attribution beyond session-based tracking to measure multi-touch contribution across AI search, paid media, and traditional organic channels.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Matt Muilenburg is the Chief Product Officer at Impel, a company building the AI platform used by thousands of dealerships to run sales, service, and fixed operations. He has spent thirty years working in dealer technology, starting at the Cobalt Group in the early internet era. He has focused on the impact of artificial intelligence on dealership operations over the last several years. Topics: 09:55 The Trade-In Lead Killing Profits. 18:40 Smallest Dealers Face Biggest Existential Risk. 21:40 First $100K Goes To Fixed Ops. 25:00 50% Of Dealers Use AI Unknowingly. 27:00 Employee ChatGPT Use Is A Legal Timebomb. 37:10 BDC Role Obsolete Within 12 Months. This episode is brought to you by: 1. Digital Dealer - Join us September 22–23 in Detroit and register today at DigitalDealer.com. Use code CDG25OFF at checkout and bring your team for a generous discount. Visit @ ⁠here⁠ for more info. 2. Uber for Business - The true cost of moving your service customers is bigger than it looks. Visit @ ⁠here⁠ to get started. 3. Impel - Meet the AI Operating System built for a new era of automotive retailing. Visit @ ⁠here⁠ for more info. Check out Car Dealership Guy's stuff: For dealers: CDG Circles ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://cdgcircles.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Industry job board ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://jobs.dealershipguy.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Dealership recruiting ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://www.cdgrecruiting.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Fix your dealership's social media ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://www.trynomad.co⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Request to be a podcast guest ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://www.cdgguest.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ For industry vendors: Advertise with Car Dealership Guy ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://www.cdgpartner.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Industry job board ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://jobs.dealershipguy.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Request to be a podcast guest ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://www.cdgguest.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Car Dealership Guy Socials: X ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠x.com/GuyDealership⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Instagram ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠instagram.com/cardealershipguy/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ TikTok ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠tiktok.com/@guydealership⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ LinkedIn ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠linkedin.com/company/cardealershipguy⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Threads ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠threads.net/@cardealershipguy⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Facebook ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠facebook.com/profile.php?id=100077402857683⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Everything else ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠dealershipguy.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Imagine redesigning your most important processes from a blank sheet of paper, with no legacy systems to hold you back. Alpa Lally, Chief Product Officer at Grant Thornton, shares how the company is transforming into a frontier firm by reimagining core processes instead of automating them. She unpacks how embedded analytics reshapes client conversations, why AI governance is what helps you move faster, and how to reinvent your career in the age of AI. Key Moments: From Structural Engineering to Product Leadership (01:36): Alpa explains how designing buildings taught her the vision, strategy, and foundation-up thinking she now applies to product. Becoming a Frontier Firm (06:27): Rethinking how work gets done for 13,000-plus professionals means recognizing that automating a broken process just does the wrong thing faster. Embedding ThoughtSpot Analytics (14:57): By putting insights in auditors' hands on day one, Grant Thornton shifts client conversations from data gathering to strategy. The AI Proof Gap: Governance Enables Speed (19:32): Alpa reframes governance as what lets you move faster, sharing that 78% of firms doubt they'd pass an AI governance audit. Is Product Management Dead? (24:33): The role is evolving, not dying, and AI raises the value of deciding which opportunities are actually worth pursuing. Key Quotes: “A frontier firm uses AI not just to improve how work gets done, but fundamentally rethinks how the work gets done. It's moving beyond productivity gains and creating entirely new ways to deliver value.” - Alpa Lally “The challenge is if you simply automate a broken process, you end up doing the wrong thing faster.” - Alpa Lally “What ThoughtSpot has done is [give us] our ability to embed them immediately into the flow [which] has opened up a whole level of different insights that we can offer, not to our practitioners only, but imagine an auditor showing up on day one to your client and having these insights already calculated, already delivered.” - Alpa Lally Mentions Grant Thornton's 2026 AI Impact Survey Report Wall Street is debating the AI buildout. Enterprises just answered: More than 80% say their GPUs run at half capacity or less Hers for the Taking by Tracey Newell Guest Bio Alpa Lally is the Chief Product Officer at Grant Thornton. Alpa is an experienced product management executive with several years in designing, developing, and launching consumer and business products for large to mid-sized to small organizations, fintechs, startups, and Fortune 500. She has led global cross-functional teams to drive high growth targets while staying laser-focused on solving customer and consumer problems. Alpa leverages data and analytics to drive successful business outcomes that deliver results and achieve corporate growth goals. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Leveraging AI Efficiency and Human Insight  Shep interviews Filip Jaskólski, Chief Product Officer at Text. He talks about how customer service, empowered by AI and human collaboration, can shift from being a cost center to a revenue generator for businesses.  This episode of Amazing Business Radio with Shep Hyken answers the following questions and more:    How can customer service move from a cost center to a revenue generator?    What is the ideal balance between AI automation and human agents in customer support?    How can companies use AI to boost upselling and product recommendations?    Why should businesses transition from reactive to proactive customer service?    What metrics actually matter when evaluating AI in customer support?   Top Takeaways:    Customer service has evolved beyond being a support center. When done strategically, it can be an important contributor to customer retention and revenue.      Every interaction with customers is an opportunity to gain valuable information about what they want or need. Aside from answering questions and solving problems, successful companies use these customer signals to improve their products and services.     By analyzing and interpreting not just the words that customers use but also the intent and context behind interactions, AI becomes an essential tool for providing personalized recommendations.     The potential for upselling and cross-selling exists in every customer conversation, not just in face-to-face interactions. Automated systems are now sophisticated enough to identify when recommendations are relevant and welcome, turning customer support channels into points of sale.     The goal is not to fully automate contact centers. Instead, successful businesses strive for a balance between AI and human strengths. For example, AI can sort through large numbers of inventory to suggest products that match the customer's needs. At the same time, human agents are capable of empathy and judgment that are essential in building a lasting connection with customers.     Revenue, satisfaction, and loyalty are the biggest indicators of success in using AI to enhance customer and employee experience. Often, companies get stuck measuring how many customers interact with AI, or how fast problems are resolved while missing out on real opportunities for growth.     Plus, Shep and Filip discuss why businesses should be proactive rather than reactive when interacting with customers. Tune in!  Quote:   "With the technology that we have today, AI can help us go deeper in our relationship with customers. We can analyze so much data and context to match what our customers need to what we can offer."      About:    Filip Jaskólski is the Chief Product Officer at Text. He drives product strategy and development with a focus on practical, scalable AI-powered customer experience solutions.  Shep Hyken is a customer service and experience expert, New York Times bestselling author, award-winning keynote speaker, and host of Amazing Business Radio.    Learn more about your ad choices. Visit megaphone.fm/adchoices

Today, Nicole is teaming up with U.S. Bank to unpack the state of small businesses and what entrepreneurs can do right now to get ahead.  Nicole sits down with Shruti Patel, U.S. Bank's Chief Product Officer for the Business Banking segment, to unpack the findings from the bank's fourth annual Small Business Survey and what they reveal about the state of entrepreneurship right now. Shruti breaks down why small business optimism dipped from 93% to 83% this year even as resilience holds strong, why only 3% of owners are currently considering a sale or exit, and what that signals about the massive wealth transfer coming as Boomer-aged owners hand off their businesses to the next generation over the next decade. Then the conversation turns to Gen Z founders specifically: their appetite for bold, calculated risk, and the surprising trend of delaying life milestones like marriage and family to build their businesses… a bet that, according to the data, is actually paying off in faster growth. Nicole and Shruti also get tactical: how business credit actually works (and why your personal credit score matters more than you'd think) and the real documentation lenders want to see. Plus: how small businesses are using AI to cut costs (even when the ROI math gets murky), where digital currency payments stand today, and why frictionless checkout is a bigger deal than most owners realize.    Learn more about U.S. Bank's Small Business Banking solutions at: usbank.com  Check-out the results of U.S. Bank's Small Business Survey: https://www.usbank.com/business-banking/business-resource-center/small-business-survey.html Here's what Nicole covers with Shruti: 00:00 Are You Ready for Some Money Rehab? 00:43 Meet Shruti Patel, U.S. Bank's Chief Product Officer 01:20 Inside U.S. Bank's 4th Annual Small Business Survey 02:16 Why Optimism Dropped from 93% to 83% 04:45 Why Only 3% of Owners Are Considering an Exit 05:18 The Great Wealth Transfer and Succession Planning for the Next Decade 06:31 Inside Gen Z's Bold, Calculated Approach to Risk 07:37 Delaying Marriage and Family to Build a Business 09:03 "You Can Have It All, Just Not All at Once" 11:07 How Gen Z Defines Success 12:10 The Death of the "Shark Tank" Fundraising Dream 13:45 Debt vs. Equity: Rethinking How to Finance Growth 14:17 What Banks Look for Before Approving a Loan 16:08 Do Businesses Have Their Own Credit Score? 17:38 Personal Guarantees and the Documentation You'll Need 19:06 The SBA Loan Process 19:38 How Small Businesses Are Actually Using AI to Save Money 21:16 The "Digital Target Checkout" Problem with AI Costs 22:39 Where Digital Currency and Crypto Payments Stand Today 24:15 Why Frictionless Checkout Is Everything 26:03 Inside U.S. Bank's Business Essentials Launch 29:32 U.S. Bank's Partnership with the NFL and the Financial Edge Program 33:45 Shruti Patel's Tip You Can Take Straight to the Bank All investing involves the risk of loss, including loss of principal. This podcast is for informational purposes only and does not constitute financial, investment, or legal advice. Always do your own research and consult a licensed financial advisor before making any financial decisions or investments.