Podcasts about Personalization

The Experience Strategy Podcast | theexperiencestrategist.substack.com Part three of a four-part mini-series unpacking the frameworks in Dave Norton's new book, Human Context: How Intelligent Companies Build Customers. Most companies build their entire models around habits and routines. But the number one behavior people exhibit today isn't a habit or a routine — it's mode acquisition. People move fluidly between modes all day, they're fluent in the language of them ("I'm in writing mode, don't talk to me"), and they expect the companies they interact with to understand where they are. Most companies don't. This episode explains what modes are, how they connect to situational markets, and why knowing someone's mode tells you more about how to serve them than any demographic ever could. What's in This Episode The definition that matters most — and it's one word. A mode is a mindset and a set of behaviors that a person gets into temporarily. That last word is what separates modes from habits (permanent patterns) and routines (permanent structures). Right now, the three hosts are in podcast mode. When they hit stop, they won't be. Joe takes a different tone between episodes. Aransas's voice changes. Dave gets Joe's "I'm in writing mode" texts. People are already living this way — the framework just names what's happening. The ballpark and the batter. To connect modes back to the last episode: if situational markets are the ballpark — the bounded context, the market you're going after — then modes are the batter. The same situation can contain many different modes. Two people can both be in the situation of choosing a college for their daughter. One is in full mommy mode — relational, emotionally loaded, cross-domain in its implications (financial, personal, professional, aspirational). Another is an adult returning to education for themselves, in a more self-directed, pragmatic mode. Same situational market. Completely different mode. Completely different support needed. Joe's extension makes it even richer: everyone on the field is in a different mode at every moment. The batter stepping up with a runner on third is in a different mode than when he's in the dugout. And if you know someone's in dugout mode — Dave's point is clear — sunflower seeds are your product. Modes cross demographics. That's the whole point. Aransas in mommy mode could be any age, any income, any geography. The mode — not the demographic — tells you what she needs. Joe names the full stack of jobs that mode carries with it: functional, emotional, social, and aspirational. Know the mode, and you know the context. Know the context, and you can personalize in a way that demographic data never allows. How modes, situations, and jobs connect. The three frameworks work together as a system. Jobs to be done describes what the customer needs broadly — the functional, emotional, social, and aspirational outcomes they're hiring for. Situational markets describe the bounded context: the when-statement, the market that's been identified and sized. Modes describe how — the specific mindset, energy, and intention the person brings to that moment. Dave's summary: situation tells you the market, mode tells you how they're experiencing their time within it. Know all three, and you have context that's genuinely actionable. Why modes replace personas — and why that matters. Personas imply a static, monolithic person. Modes are the opposite: dynamic, contextual, temporary. A person is not their persona. They are whoever they are in this moment, in this situation, in this mode. That concept changes what you build, what you say, and how you show up. The mode map in Human Context gives companies a practical tool: map your specific situations to the modes customers are likely to enter, and build for those combinations rather than for a type of person. Most companies are leaving this on the table. Dave has been developing the modes framework for over a decade. He remains genuinely surprised that more companies don't use it — especially now, when the language of modes is so embedded in how people describe themselves. The person who texts "I'm in writing mode" is handing you a direct signal about their context. Most companies have no system for receiving it.   Get the Book Human Context: How Intelligent Companies Build Customers by Dave Norton is available now on Amazon (Kindle and print) and on Dave's Substack. The book includes a mode map framework and industry-specific workbooks showing how to apply modes, situational markets, and the other frameworks to your category. Find the hosts by name or as The Experience Strategist at theexperiencestrategist.substack.com.

AI is changing how B2B buyers search, evaluate solutions, and decide which brands to trust. For marketers, that means traffic, leads, and traditional attribution metrics no longer tell the whole story.On StrategyCast, Lori Jones talks with Andrew Davis, SVP of Marketing and Sales at TextUs, about how AI is upending buyer behavior and forcing marketers to rethink their go-to-market strategies. Andrew explains why today's buyer journey happens across Google, AI platforms like ChatGPT and Claude, review sites, retargeting, and other touchpoints long before a prospect converts.And don't forget! You can crush your marketing strategy with just a few minutes a week by signing up for the StrategyCast Newsletter. You'll receive weekly bursts of marketing tips, clips, resources, and a whole lot more. Visit https://strategycast.com/ for more details.==Let's Break It Down==00:00 How AI Is Changing Buyer Behavior01:42 Andrew Davis' Path From Sales to Marketing04:21 Why Traditional Marketing Playbooks Stop Working06:11 AI Search, AEO, GEO, and Changing Demand08:00 The New Multi-Channel Buyer Journey10:39 Why Traffic Is Not the Same as Demand14:16 Lead Scoring and Multi-Channel Engagement16:11 Why Cost Per Lead Can Be Misleading17:48 Personalization and Human Connection in the AI Era22:08 How Modern GTM Strategies Are Changing24:28 Why Creative Testing Needs to Happen Faster27:37 The Marketing Skills That Matter in an AI-Driven World31:28 Human Intelligence as an AI Advantage32:37 Where to Connect With Andrew Davis33:23 Building Trust Across the Buyer Journey==Where You Can Find Us==Website: https://strategycast.com/Instagram: https://www.instagram.com/strategy_cast/Facebook: https://www.facebook.com/strategycast==Leave a Review==Hey there, StrategyCast fans!If you've found our tips and tricks on marketing strategies helpful in growing your business, we'd be thrilled if you could take a moment to leave us a review on Apple Podcasts. Your feedback not only supports us but also helps others discover how they can elevate their business game!

Nékter Juice Bar CTO Jon Asher joins Fast Casual Nation hosts Paul Barron and Cherryh Cansler to break down how AI is reshaping guest personalization, loyalty, and data strategy at the 200+ unit juice bar chain — plus why clean first-party data matters more than any single AI tool.#FastCasual #RestaurantTech #AIinRestaurants #NekterJuiceBar #LoyaltyMarketing #RestaurantIndustry #GuestExperienceBecome a supporter of this podcast: https://www.spreaker.com/podcast/fast-casual-nation--3598490/support.Get Your Podcast Now! Are you a hospitality or restaurant industry leader looking to amplify your voice and establish yourself as a thought leader? Look no further than SavorFM, the premier podcast platform designed exclusively for hospitality visionaries like you. Take the next step in your industry leadership journey – visit https://www.savor.fm/Capital & Advisory: Are you a fast-casual restaurant startup or a technology innovator in the food service industry? Don't miss out on the opportunity to tap into decades of expertise. Reach out to Savor Capital & Advisory now to explore how their seasoned professionals can propel your business forward. Discover if you're eligible to leverage our unparalleled knowledge in food service branding and technology and take your venture to new heights.Don't wait – amplify your voice or supercharge your startup's growth today with Savor's ecosystem of industry-leading platforms and advisory services. Visit https://www.savor.fm/capital-advisory

What if tweaking your hearing aid settings could actually improve your mood? In this video, Erin Picou, Au.D., Ph.D., Associate Professor and director of the Hearing and Affect Perception Interest Laboratory at Vanderbilt University Medical Center, shares groundbreaking research on how personalized hearing aid programming goes far beyond better sound—it transforms emotional wellbeing, confidence, and energy levels.

2026 State of Financial Marketing report is available for free at https://www.digitalbankingreport.com/trends/2026-state-of-financial-marketing/?YouTube More than half of the banks and credit unions in our 2026 State of Financial Marketing research have generative AI operational or better inside marketing. Not one of them describes its customer data as real-time and AI-ready. That gap runs in a straight line through the study. Generative AI raised production capacity, while thin data and almost no predictive decisioning keep the output from being relevant. 55% are not using predictive AI at all. 1% rate AI-driven content and creative as effective, the lowest score on the tactics chart, against the largest planned budget increase in the research. We funded the layer that produces marketing and held flat the layer that decides who should receive it, when it should arrive, and whether it worked. It also explains the distance between what this industry says about personalization and what it does. 83% sit at segment-based personalization or below and 1% call themselves hyper-personalized. Two-thirds of what we call personalization is choosing which audience receives a message, which is list selection under a newer name. Jim walks through what that looked like when he ran marketing at a bank, sorting a core tape by ZIP code and balance tier, and what has genuinely improved since. None of it is a reason to wait. Good solution providers build strong targeting on imperfect data every day. Imperfect data can't recognize what just happened to a customer and respond while it is still happening. Personalization and decisioning is also the least outsourced marketing function in the study at 13%, even though a lack of internal talent is the second-largest barrier, which means this industry outsources its strengths and protects its weaknesses. ABOUT: Jim Marous is Co-Publisher of The Financial Brand, Owner and Publisher of the Digital Banking Report, and host of the Banking Transformed podcast.

Philippe Hertzberg has never bought an advertisement aimed at a traveler.Hertzberg is the CEO of Secret Journeys, a company that designs private access experiences inside landmarks like Notre Dame and the Arc de Triomphe. Most tour businesses expand their bookable services to capture more revenue per client. Hertzberg does the opposite: Secret Journeys turns away hotel, ground transport, and flight bookings, even when clients ask for them, to stay a single, uncategorizable thing. Most tour businesses also try to reach travelers directly. Hertzberg doesn't advertise to travelers at all. He sells exclusively through travel advisors, and a single pitch to Virtuoso's CEO in 2022 put him in front of that network's 20,000 advisors.Three other decisions run the same direction. Hertzberg turns down press coverage that would put Secret Journeys in front of the traveling public, free exposure most businesses would take, because he wants the advisor, not his own company, to stay the one the client trusts. He casts storytellers the way Disney casts characters, and the trait he's actually hiring for is curiosity about the guest, not guiding credentials or destination expertise. Landmark access gets negotiated the same patient way: opening the Arc de Triomphe at night took two years of solving the administrator's actual objections one at a time, including agreeing to cover security staff's cab fare home. The episode also covers how a storyteller turned a five-year-old's obsession with bells into a private treasure hunt through the towers of Notre Dame, and which cities, Amsterdam, Seoul, and Prague among them, Hertzberg is looking to expand into next.Resources:Secret Journeys: secretjourneys.travelPhilippe Hertzberg on LinkedIn

When Scotty O gets to moderate panels at these conferences, he is lucky to meet some of the brightest and smartest in the industry. That is how he met David Burrows who has been in retail and on the cutting edge of ecommerce for decades. Founder at Arkearth, Hivessence, & Hiveshine. We experienced a Fire Alarm during recording and as usual, we did not edit it out! Enjoy the real honest conversation.   Always Off Brand is always a Laugh & Learn!   eTail episodes are brought to you by TALKOOT! Go to https://talkoot.com/ to find out how you can scale your content, copy, story telling. Faster Product Content Operations for the AI Era!     FEEDSPOT TOP 10 Retail Podcast! https://podcast.feedspot.com/retail_podcasts/?feedid=5770554&_src=f2_featured_email   GUEST David Burrows  LinkedIn: https://www.linkedin.com/in/dmburrows/ https://www.hivessence.com/ Huge Shout Out to everyone at eTail for the great support and giving us the place to record at their great events.    QUICKFIRE Info:   Website: https://www.quickfirenow.com/ Email the Show: info@quickfirenow.com  Talk to us on Social: Facebook: https://www.facebook.com/quickfireproductions Instagram: https://www.instagram.com/quickfire__/ TikTok: https://www.tiktok.com/@quickfiremarketing LinkedIn : https://www.linkedin.com/company/quickfire-productions-llc/about/ Sports podcast Scott has been doing since 2017, Scott & Tim Sports Show part of Somethin About Nothin:  https://podcasts.apple.com/us/podcast/somethin-about-nothin/id1306950451 HOSTS: Summer Jubelirer has been in digital commerce and marketing for over 17 years. After spending many years working for digital and ecommerce agencies working with multi-million dollar brands and running teams of Account Managers, she is now the Amazon Manager at OLLY PBC.   LinkedIn https://www.linkedin.com/in/summerjubelirer/   Scott Ohsman has been working with brands for over 30 years in retail, online and has launched over 200 brands on Amazon. Mr. Ohsman has been managing brands on Amazon for 19yrs. Owning his own sales and marketing agency in the Pacific NW, is now VP of Digital Commerce for Quickfire LLC. Producer and Co-Host for the top 5 retail podcast, Always Off Brand. He also produces the Brain Driven Brands Podcast featuring leading Consumer Behaviorist Sarah Levinger. Scott has been a featured speaker at national trade shows and has developed distribution strategies for many top brands. LinkedIn https://www.linkedin.com/in/scott-ohsman-861196a6/   Hayley Brucker has been working in retail and with Amazon for years. Hayley has extensive experience in digital advertising, both seller and vendor central on Amazon. Hayley lives in North Carolina.  LinkedIn -https://www.linkedin.com/in/hayley-brucker-1945bb229/   Huge thanks to Cytrus our show theme music "Office Party" available wherever you get your music. Check them out here: Facebook https://www.facebook.com/cytrusmusic Instagram https://www.instagram.com/cytrusmusic/ Twitter https://twitter.com/cytrusmusic SPOTIFY: https://open.spotify.com/artist/6VrNLN6Thj1iUMsiL4Yt5q?si=MeRsjqYfQiafl0f021kHwg APPLE MUSIC https://music.apple.com/us/artist/cytrus/1462321449   "Always Off Brand" is part of the Quickfire Podcast Network and produced by Quickfire LLC.  

Watch Us On YouTube! Take advantage of our ongoing benefit for annual subscribers of our Slack community. Annual subscribers receive a free Points Path Alerts subscription OR a 30% discount on Points Path Pro. JetBlue is finally adding domestic first class—but is a nicer seat really what the airline needs most? Ed and Richard are joined by Points Path founder Julian Kheel for a packed episode that starts with JetBlue's plans for three rows of domestic first class. The guys like plenty about the JetBlue onboard experience, but there's an elephant in the room: operational reliability. July data discussed on the show puts JetBlue at just 62% for on-time arrivals and a 91.7% completion factor. Richard and Julian argue that fixing the network and operation might be a higher priority than installing premium seats. There's another tradeoff. JetBlue can install first class without dramatically reducing the total number of seats because its cabins historically had generous legroom—but the new configuration significantly reduces Even More Space seating. That leads to a discussion about whether JetBlue is simultaneously premiumizing the front while "depremiuming" economy. Richard also has something else on his mind: domestic airfare. He's seeing some eye-watering prices for family trips, including roughly $2,400–$2,500 for four people on relatively short domestic trips. Julian says Points Path data used in a recent study is showing significant year-over-year increases in holiday pricing for both cash fares and miles, making locking something in early increasingly important. Then Julian weighs in on Google's new AI-powered points-and-miles search after Ed and Richard tested it last week. His verdict falls somewhere between theirs: there's potential, but the current product still struggles to return complete results. More fundamentally, Julian questions whether travelers actually want to book trips by chatting with an AI bot. The real prize, he argues, isn't simply showing every available fare—it's personalization that understands your points, credits and other assets and tells you which option is best for you. Air Canada has new routes coming, including a daytime Toronto–London flight, but its upcoming A321XLR configuration gets Ed's attention: just 14 lie-flat seats, no premium economy and an otherwise all-economy cabin at a time when airlines seem to be racing to add premium capacity. United, meanwhile, is adding a new app feature designed to help during delays. Travelers will be able to stand by for as many as three alternate flights and receive notifications if seats become available. Julian sees it as a useful, customer-friendly addition. Richard is…less convinced. Finally, Ed and Julian tackle a question close to home: Does the Washington, D.C. region really need a fourth commercial airport? Manassas Regional Airport has received permission to offer commercial service, potentially opening the door to carriers such as Avelo. Ed digs into the economics of Dulles, National and the broader DC market—and why making a fourth airport work may be harder than it sounds. Get hydrated like Ed in Vegas with Nuun If you enjoy the podcast, I hope you'll take a moment to leave us a rating. That helps us grow our audience! If you're looking for a way to support the show, we'd love to have you join us in our Travel Slack Community.  Join me and other travel experts for informative conversations about the travel world, the best ways to use your miles and points, Zoom happy hours and exciting giveaways. Monthly access Annual access Personal consultation plus annual access We have witty, funny, sarcastic discussions about travel, for members only. My fellow travel experts are available to answer your questions and we host video chats multiple times per month. Follow Us! Instagram: https://www.instagram.com/milestogopodcast/ TikTok: https://www.tiktok.com/@milestogopodcast Ed Pizza: https://www.instagram.com/pizzainmotion/ Richard Kerr: https://www.instagram.com/kerrpoints/ ✈️ What We Cover in This Episode ✈️JetBlue is finally getting domestic first class Three rows and 12 first-class seats Why JetBlue can add premium seats without a huge capacity reduction Whether premium cabins address JetBlue's actual problems ✈️ JetBlue's reliability problem 62% on-time arrivals in July A 91.7% completion factor Comparing JetBlue with other North American airlines Why Richard still chooses JetBlue despite the operational headaches ✈️ Domestic airfare is getting painful $2,400+ family trips When Europe can seemingly cost less than Orlando Using Delta companion certificates for other travelers Why locking in refundable/rebookable fares early can make sense ✈️ Is JetBlue "depremiuming" economy? Fewer Even More Space seats Adding premium capacity at the front What happens to the JetBlue economy experience ✈️ Julian weighs in on Google's AI award search Incomplete results Why chatbots may not be the future of travel booking Discovery versus actually executing a trip Why personalization may be the real breakthrough ✈️ Air Canada's unusual A321XLR strategy New international routes Daytime Toronto–London service Only 14 lie-flat seats No premium economy Why the configuration seems surprising in today's premium-heavy market ✈️ United adds more disruption tools Stand by for up to three flights after a delay Alternate airports may be included Julian likes it Richard really doesn't ✈️ Does DC need a fourth airport? Manassas Regional Airport gets commercial approval Potential low-cost-carrier service Dulles versus National airport economics Why supporting four airports is difficult Which airlines might realistically serve Manassas ⏱️ Episode 453 Timestamps 10:04 – JetBlue finally reveals its domestic first-class plans 13:18 – Does JetBlue need first class—or better reliability? 15:00 – Why domestic airfare has gotten so expensive 16:14 – The numbers behind JetBlue's operational struggles 22:08 – Is JetBlue "depremiuming" the rest of the cabin? 25:58 – Julian weighs in on Google's AI award search 31:08 – Personalization: the real future of points-and-miles search? 32:56 – Air Canada's surprising A321XLR configuration 36:37 – United's new three-flight standby feature sparks a debate 42:17 – Does Washington, D.C. really need a fourth airport?

Send us Fan MailPrinting on curved packaging sounds simple until you try doing it at industrial speed without missing nozzles, wasting materials, or slowing production to a crawl. We sit down with Florian Fässler, Head of R&D for Digital Technologies at Polytype, to unpack how direct-to-shape digital printing has evolved from a promising alternative into a robust manufacturing process that can handle real-world airflow, turbulence, and uptime demands.We get into the technical leaps that matter most, including greater throw distance, modern inkjet printheads, and waveform optimisation that improves drop speed while reducing satellites. From there, we explore why manufacturers and brands are increasingly choosing digital direct-to-shape for short runs, rapid changeovers, and simpler logistics, especially in B2C and web-to-print models where lead times can be hours, not weeks. Florian also explains how printing directly on the container cuts label carrier waste and supports recycling goals while keeping inventory lean.The conversation moves from decoration to capability: variable data printing enables unique QR codes and barcodes within the run, opening doors to connected packaging, traceability, and smarter customer engagement. We also look ahead at AI and automation, from AI-generated artwork to operator support tools, predictive maintenance, nozzle sensing, and even what happens when procurement becomes agent-to-agent ordering. If you care about industrial inkjet, sustainable packaging, mass customisation, and the future of manufacturing networks, this is a practical, grounded listen. Subscribe, share with a colleague, and leave a review with your biggest takeaway.Listen on:Apple PodcastGoogle PodcastSpotifyWhat is FuturePrint?FuturePrint is a digital and in person platform and community dedicated to future print technology. Over 20,000 people per month read our articles, listen to our podcasts, view our TV features, click on our e-newsletters and attend our in-person and virtual events. We hope to see you at one of our future in-person events:FuturePrint Packaging, Labels & DTS Summit, 29-30 September '26, Valencia, SpainFuturePrint Industrial Print Show, 11-12 May '27, Munich, Germany

SummaryIn this episode, Alan Zhao from warmly.ai discusses how AI is transforming customer experience and marketing automation. Discover how hyper-personalization, data integration, and responsible AI practices are shaping the future of sales and marketing. Key topicsAI-driven customer personalizationData integration and decision treesMarketing automation and outreachEthical considerations in AITools and platforms for AI marketing TakeawaysAI enables hyper-personalized marketing at scale.Understanding visitor intent improves conversion rates.Human-in-the-loop remains vital for trust and authenticity.AI tools can automate complex content creation.Ethical responsibility is crucial in AI development. Chapters00:00 Introduction to AI in Marketing02:50 Transforming Customer Experience with AI05:31 The Role of Personalization in Marketing08:40 Human Interaction in AI-Driven Marketing11:29 Keeping Up with Rapid Technological Changes14:17 Innovative Tools and Technologies in Marketing17:07 Ethics and Responsibility in AI19:51 Getting Started with AI in Marketing The AI for Sales Podcast is brought to you by BDR.ai, Nooks.ai, and ZoomInfo—the go-to-market intelligence platform that accelerates revenue growth.Skip the forms and website hunting—Chad will connect you directly with the right person at any of these companies.

How do you give sports fans deeper insight into a live match without covering the action with statistics they never asked for? Two years ago, I spoke with Patrick Mostboeck in episode 2788, How Sportradar Are Revolutionizing Sports with AI. Patrick returns to Tech Talks Daily as Senior Vice President of Fan Engagement at Sportradar for a timely conversation during the U.S. Open about how AI and real-time sports data are changing the way fans follow a match. We begin with the move from scores, schedules, and basic statistics to thousands of data points that can describe what is happening on the court or field. Patrick explains that the value comes from context. In tennis, ball position, shot type and player movement can reveal patterns around fatigue, court positioning and momentum that may be difficult to see from the television picture alone. AI can process those signals quickly enough to help broadcasters and digital services explain why a match may be changing. That creates an obvious temptation to show everything. Patrick is candid about the lesson Sportradar has learned from putting products in front of users: less is often more. A product team may want to display every feature it has built, while the fan simply wants to understand the action. The technology works best when the improvement feels natural and the viewer does not have to fight through a stream of graphics. We also consider the second screen. Many of us now watch sport with a phone or tablet nearby, checking other scores, following another match or looking for an explanation of a moment we have just seen. Patrick argues that media companies and rights holders can support those habits by offering different routes into the same event. A first time tennis viewer may need immediate context, while a fan who has watched the sport for 25 years may want deeper performance data. Personalization can serve both groups without taking away the shared experience of live sport. Patrick explains how Sportradar's 4Sight combines 3D data visualization, contextual data, and real-time insight inside live streams. The aim is to identify relevant moments and provide a clear narrative rather than add graphics for their own sake. He also describes official sports data as infrastructure that rights holders can actively develop and commercialize across media, advertising, coaching analytics and other services. For organizations wondering where to begin, Patrick offers a practical sequence. Start with the fans and identify the information they value before and during an event. Assess the quality and history of the data already available. Then speak with partners who understand how that information can support useful products and sustainable commercial models. We close by discussing prediction. Better data can help systems model possible outcomes for fans, media teams and coaches, but sport still retains the uncertainty that makes it worth watching. Will predictive insight deepen our appreciation of the action, or could too much information remove some of its magic? Listen to the conversation and share your thoughts with me.

In the travel world, getting someone to click "book" is only the start of the journey. The true test of brand loyalty — the moment where a consumer becomes a lifelong advocate — happens when they step through the front doors of their hotel. For a global leader managing 28 distinct brands, delivering a consistently exceptional experience for millions of travelers every night requires a delicate balance of deep data and authentic human emotion.In this episode of Campaign Chemistry, Dan Reynolds, SVP of global marketing at Hilton, reveals how the hospitality powerhouse crafts stays that resonate long after checkout. Reynolds walks through how Hilton leverages algorithmic insights to surprise and delight guests, turning routine travel into meaningful personal connections. He pulls back the curtain on their boldest cultural plays, from a two-decade-long partnership with McLaren and unique activations like the Waldorf Astoria Racquet Club to headline-grabbing campaigns with Paris Hilton and Lando Norris. Beyond virality, Reynolds addresses the hard business of marketing: bridging social media engagement with direct bookings, navigating brand consistency across human and digital touchpoints and drawing endless creative fuel from real customer stories. campaignlive.com Music - Take you Out by Lucid Tides, courtesy of Triple Scoop. What we know about advertising, you should know about advertising. Start your 1-month FREE trial to Campaign US. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Looking for daily inspiration?  Get a quote from the top leaders in the industry in your inbox every morning.   What's the one premier event that brings the global attractions industry together? IAAPA Expo 2026, happening in Orlando, Florida, November 16th - 20th. It's where more than forty-thousand professionals come to share the wonder, explore over a thousand innovative exhibitors, and discover future-focused solutions. From education to networking to ideas that drive real business impact, IAAPA Expo is where what's next takes shape.   Register now and save up to 30% at IAAPA.org/IAAPAExpo. Guest experience is often introduced during orientation, reinforced through a training session, and documented somewhere in an SOP or handbook. The challenge is what happens after that. If the standard is not consistently reinforced, coached, recognized, and refreshed, it can quickly become disconnected from daily operations. Building guest experience into an operating system creates a continuous cycle that keeps the standard active while allowing it to evolve as the organization improves. In this minisode, Matt and Josh talk about treating guest experience as an operating system that lives within the daily rhythm of the organization. Guest experience should live in the operation “Guest experience is not simply a standard, not simply a training initiative, and it certainly is not a one-time event.” A guest experience standard provides an important foundation, but the standard needs a system around it to remain relevant. That begins before or on an employee's first day and continues throughout their entire experience with the organization. Rather than treating guest experience as a standalone initiative or department, it becomes part of how employees are selected, trained, coached, recognized, and developed. The standard must translate to the job “They're both personalizing the experience, but they're being done in a very different way.” A consistent guest experience does not mean every employee delivers it identically. Personalization at admissions might include learning and using a guest's name, while a ride operator may have only seconds to notice a shirt, team logo, or other conversation starter. The same standard can look different across roles while remaining anchored to the same expectation. On-the-job training creates the bridge between understanding the standard and knowing how to demonstrate it within a specific position. Reinforcement keeps the standard alive “Are they seen as micro training sessions?” Guest experience cannot rely on everything being taught during orientation. Daily shift meetings, one-on-one conversations, and spot coaching create opportunities for continuous reinforcement. Instead of using every pre-shift meeting exclusively for operational updates, leaders can ask about recent wow moments, guest complaints, or feedback employees have heard. Those conversations turn everyday experiences into training content and continually reconnect the team to the standards they learned on day one. Recognition strengthens the system “You must prioritize recognition over reward.” When employees demonstrate the guest experience standard, recognizing the behavior helps reinforce what the organization wants repeated. Recognition does not need to be transactional or dependent on prizes and gift cards. Genuine appreciation can show employees that leaders notice how the standard is being delivered. Combined with coaching and reinforcement, recognition helps move guest experience beyond a training initiative and into the everyday culture of the organization. Your operating system needs updates “It literally is refreshing the operating system.” Standards should evolve as the organization improves. A handbook that accurately described exceptional service two years ago may no longer represent what the team is capable of delivering today. Periodically reviewing and raising the standard creates a cycle of continuous improvement. Day one leads to on-the-job training, reinforcement and recognition, followed by refreshing the standard and beginning the cycle again. Each pass through the cycle creates greater alignment and momentum. Consistency does not require scripting “The message was consistent, but the delivery was very personal.” A strong operating system creates consistency without eliminating personality. Team members across different departments can deliver the same underlying standard in ways that fit their roles and interactions. A parting pleasantry, for example, may sound different at a ride exit than at the park exit, but both reinforce the same expectation. Guests experience a cohesive standard even when every interaction feels natural and personal.   Guest experience already exists in every organization. The opportunity is to become more intentional about how it operates every day and how it continues to improve. How are you building guest experience into your daily operating rhythm? Find AttractionPros on social media or email attractionpros@gmail.com to share what is working in your organization. To connect with AttractionPros: AttractionPros.com AttractionPros@gmail.com AttractionPros on Facebook AttractionPros on LinkedIn AttractionPros on Instagram AttractionPros on Twitter (X)

Jasmine Jonte runs CRE8TION, a done-for-you program design agency that's built 160 programs and reached more than 100,000 students.This whole conversation revolves around one question: now that anyone can generate a course outline in ten minutes, what are people actually paying for?Her answer is that they were never paying for the information. The passive income promise sold to experts in 2020 was a marketing lie, and AI didn't break the model so much as make the crack impossible to ignore. She walks through where her clients use AI inside a program build, where they deliberately don't, and what the standard looks like now that buyers know what good feels like.What you'll learn:Why the barrier to entry keeps dropping while client expectations keep climbingThe $7,500 program that showed her experts know what they know but can't teach itWhat her clients are replacing workbooks and calculators withThe one thing she says AI can't be coded withHow to talk about AI use with clients who have friction around itThe closing line about lifetime value that reframes your whole delivery modelCHAPTERS01:05 Meet Jasmine Jonte02:05 From Teacher to Agency03:52 AI Raises the Bar06:58 New Client Expectations09:00 Beyond Information Dumps12:03 Personalization at Scale15:08 How Much AI to Use17:23 Positioning and Disclosure22:53 Case Studies in Action28:02 Make Results Easy29:28 Where to Connect>MEET JASMINEThanks for Listening!If you enjoyed this episode, please help us share it by:Following the show—this helps you stay updated and supports us!Leaving a positive review—this boosts our ranking and helps more entrepreneurs find the podcast.--------------------------Entrepreneur School is proud to be featured on the Feedspot list of 30 Best Canada CEO Podcasts! https://blog.feedspot.com/canadaceopodcasts/

Summary In this episode, Chad Burmeister interviews John Taylor, CEO of Act Three Agency, about the transformative impact of AI on podcasting, customer experience, and marketing. They explore how AI enhances discoverability, personalization, and ethical considerations in the evolving AI landscape. Key topics AI's impact on podcast discoverability and search Generative engine optimization (GEO) and metadata importance Converting niche audiences into customers Maintaining personal touch in AI-driven content Ethical considerations and responsible AI use Chapters 00:00 Introduction to AI in Podcasting 02:55 AI's Impact on Customer Experience 05:33 Challenges Faced by Podcasters 08:16 Conversion and Discoverability in Podcasting 11:09 Misconceptions About AI 13:59 Maintaining the Human Touch in AI 16:46 The Role of Soft Skills in the AI Era 19:28 Ethics and Responsibility in AI 22:23 Future Technologies and AI 25:09 Conclusion and Future Outlook The AI for Sales Podcast is brought to you by BDR.ai, Nooks.ai, and ZoomInfo—the go-to-market intelligence platform that accelerates revenue growth.Skip the forms and website hunting—Chad will connect you directly with the right person at any of these companies.

In this episode, we sit down with Brianna Keefe, founder and CEO of Toastique — a fresh, made-in-house cafe concept that started as a single 1,000 square foot store in Washington D.C. in 2018 and has grown to over 65 locations across 25 states, entirely through franchising and word of mouth. Brianna opened her first store at 24 with no formal marketing plan, no app, and no third party delivery — just a highly shareable product, a commitment to quality, and an instinct for community. She opens up about how grassroots marketing and in-person community building became the foundation of Toastique's entire growth strategy, what the pandemic taught her about the strength of the brand she had built, how she has had to evolve as a leader as the business scaled, and the customer service principles she swears by that any business in any industry can apply. Key Takeaways:// Word of mouth is still the most powerful marketing channel you have. Toastique spent nothing on marketing for its first year and a half. The product was shareable, the experience was memorable, and customers did the rest. Brianna's belief: if you focus on quality and experience from day one, that becomes embedded in the culture of the brand.// Grassroots marketing compounds over time. Before apps, third party delivery, or a formal strategy, Toastique built its presence by showing up in the community — catering office breakfasts, doing pop ups in residential buildings, and connecting with neighboring small businesses. That foundation still drives some of their strongest growth today.// Product presentation is a marketing decision. Toastique was built from the beginning around food that looks as good as it tastes because people eat with their eyes first. The visual shareability of the product meant customers were doing organic social marketing without being asked.// Be knowledgeable about what you sell, at every level of the team. Toastique requires every team member to pass an 80-question product knowledge quiz before working the register. If someone cannot answer a customer's question confidently, the experience breaks down — no matter how warm the greeting was.// Personalization at scale is still possible. Remembering names, orders, and personal details — and following up on them — is what turns a transaction into a relationship. In hospitality and in marketing, that memorability factor is what keeps people coming back.Connect with Brianna: LinkedIn____Join the MHH Collective! The MHH Collective is a community for marketers and business owners to connect, ask real questions, and grow their careers together. Join for access to live Q&As with industry experts, a private Slack community, and ongoing resources: https://www.marketinghappyhr.com/mhh-collectiveSay hi! DM us on Instagram and let us know what content you want to hear on the show - We can't wait to hear from you! Please also consider rating the show and leaving a review, as that helps us tremendously as we move forward in this Marketing Happy Hour journey and create more content for all of you. ⁠Join the MHH Collective: ⁠Join now⁠Get the latest marketing trends, open jobs and MHH updates, straight to your inbox: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Join our email list!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow MHH on Social: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TikTok⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

In this episode, host Greg sits down with Oban MacTavish, CEO and co-founder of Spade, an intelligence company transforming how financial institutions leverage their payments data. Oban explains how transaction data represents the highest throughput information banks have about their customers, yet remains largely untapped due to poor data quality and outdated payment infrastructure dating back to the 1960s. He discusses how Spade addresses this challenge by creating a comprehensive merchant graph covering 99.9% of businesses across the United States and Canada, enabling banks to understand exactly where their customers spend money in under 40 milliseconds.The conversation explores the delicate balance between personalization and privacy in banking. Oban argues that personalization doesn't have to feel creepy when done right—citing examples like banks no longer requiring travel notifications and suggesting that offering relevant products based on customer behavior can actually enhance trust rather than diminish it. He emphasizes that banks are uniquely positioned to leverage customer data effectively, as consumers already expect their financial institutions to understand their spending patterns and needs. The key is meeting customers where they are with relevant products at the right time, rather than making irrelevant offers that erode trust.Looking ahead, Oban shares his vision for the future of banking, predicting that financial services will increasingly run on verticalized AI models specifically designed for the industry's unique data challenges. He pushes back against the hype around AI agents replacing human customer service, arguing that the real opportunity lies in using AI to enhance customer experiences and drive revenue through better underwriting and personalization. Despite predictions of disruption, Oban maintains that traditional banks aren't going anywhere—instead, the winners will be those institutions that successfully compete on user experience and leverage their data assets to provide truly personalized service.More info:Spade: https://spade.com/ ; https://www.linkedin.com/company/spadedata/Oban MacTavish: https://www.linkedin.com/in/oban/Greg Palmer: https://www.linkedin.com/in/gregbpalmer/Finovate: https://www.finovate.com; https://www.linkedin.com/company/finovate-conference-series/FinovateFall: https://informaconnect.com/finovatefall/#Finovate #FinovateFall #fintech #financialinstitutions #creditunions #AI #modernization #technology #strategy #fintechstrategy #personalization #data #transactiondata #digitaladoption #podcast #fintechpodcast #financialservices #innovation #cx #digitraltransformation #fintech #finserv

The Customer Service Department Is Dead: What the Future Service-Centric Organization Looks Like Customer service cannot remain the department responsible for cleaning up problems created by the rest of the company. If an organization is serious about becoming service-centric, every department must understand how its decisions shape the customer experience—and one accountable leader must ensure the entire system works. In Episode 268 of the Customer Service Revolution Podcast, Denise Thompson and John R. DiJulius III examine what the future service-centric organization will look like as AI reshapes customer behavior, frontline roles, organizational design, and the economics of service. The future will not belong to the company with the fastest chatbot or the fewest employees. It will belong to the organization that uses technology to remove friction behind the scenes while making the experience more human in front of the customer. Customer Experience Must Be Enterprise-Wide—but Someone Still Has to Own It "Customer experience is everyone's responsibility" sounds inspiring, but it can become an excuse for having no accountability. John argues that successful organizations need a clear experience champion—someone who loses sleep over the experience and has the authority, KPIs, and executive access to challenge decisions that could hurt customers or employees. In a large enterprise, that may be a chief experience officer supported by a customer experience department. In a smaller organization, it may be a shared role assigned to an HR, training, operations, or other senior leader. The title matters less than the clarity of the mandate, the time committed to it, and the metrics tied to it. The role should also extend beyond the customer. A truly service-centric organization manages the entire experience ecosystem: customer experience, employee experience, and vendor experience. AI Should Remove Friction, Not Humanity AI is changing customer service, but using it only to reduce headcount can create expensive unintended consequences. Gartner predicts that by 2027, half of the companies that cut customer service staff because of AI will rehire people to perform similar functions under different titles. Gartner has also reported that only 20% of customer service leaders had reduced agent staffing because of AI. As AI handles routine questions, human employees inherit the escalations, emotional customers, sensitive conversations, and high-stakes decisions. That work can be more meaningful—but also far more demanding. Organizations must protect employees from empathy fatigue, make access to a human easier, and train people in the skills technology cannot replace: empathy, curiosity, listening, rapport building, judgment, and the ability to defuse an upset customer. Your Customer May Send an AI Agent Instead of Visiting Your Website The customer journey may no longer begin on a company's website, app, or contact center. Gartner found that customers were approximately three times more likely to use a third-party generative AI tool than a company-provided chatbot when trying to resolve a service issue. Among customers who already used generative AI, 58% had used it to complete a task—not merely find information—and that figure reached 74% in B2B settings. That creates a new strategic threat: the company can become invisible while an outside AI platform recommends brands, compares choices, completes purchases, and resolves problems. Technology is easy for competitors to copy. Human connection, trust, community, and a distinctive brand experience are harder to duplicate. Access to a Human Could Become the Next Competitive Advantage Pega research found that 77% of consumers believed they always or often achieved better outcomes when dealing only with a human, while two-thirds preferred human-led support. Nearly half said they did not trust businesses that used AI to handle customer service interactions completely. Despite that preference, many organizations continue to make people fight through layers of self-service before reaching an employee. John's answer is blunt: a customer should be able to reach a human when the customer wants to. Companies that preserve convenient human access—and equip those employees to deliver empathy, expertise, and judgment—may be able to turn humanity itself into a powerful brand differentiator. Personalization Without Integrity Becomes Exploitation More customer data creates more opportunities to personalize an experience, but not every technically possible use of data is ethical. The public controversy over Delta Air Lines' AI-supported pricing illustrated how quickly personalization can be perceived as surveillance pricing. Using customer knowledge to anticipate a need or make someone feel cared for is service. Using a customer's identity, vulnerability, income, or presumed willingness to pay to extract the highest possible price is exploitation. Customers should be allowed to choose and pay for clearly defined service levels; businesses should not quietly decide that a particular customer can be charged more. Integrity cannot become collateral damage in the race to personalize. The Best Model Is People-Led and Technology-Powered Walmart and Starbucks offer a more promising blueprint. Walmart has introduced AI tools designed to support approximately 1.5 million U.S. associates, including real-time translation and technology that reduced shift-planning time from 90 minutes to 30 minutes. Starbucks' Green Apron Service model combines staffing, workflow improvements, and technology to give employees more time for craft and customer connection. These organizations are not presenting technology as the experience. They are positioning it as the infrastructure that helps people deliver the experience. That is where AI creates real value: transcribing workshop notes, organizing information, handling repetitive tasks, accelerating internal processes, and giving employees more time to think, connect, and solve. Stop Measuring Speed at the Expense of Loyalty Average handle time, ticket volume, and cost per contact can reward speed while quietly damaging the relationship. Fast service that makes a customer feel dismissed is not a win. Neither is a warm interaction that fails to solve the problem. The future service-centric organization must measure both efficiency and experience. John recommends tracking earned sales growth—the percentage of business generated through repeat customers and referrals rather than purchased through advertising—along with the operational and experience measures that explain why loyalty is rising or falling. The most important question is not simply, "Was the issue resolved?" It is, "How did the customer feel after doing business with us?" What Leaders Should Build Now The future service-centric organization will: Assign one accountable experience champion with clear authority, priorities, KPIs, and executive access. Make every department responsible for understanding its internal or external customer and its effect on the end experience. Use AI for repetitive, administrative, and low-risk work while preserving human judgment for sensitive, ethical, financial, and health-related decisions. Train employees continuously in AI readiness and service aptitude skills. Give frontline employees the authority to solve problems without unnecessary permission-seeking. Protect easy access to a skilled human whenever a customer wants or needs one. Measure loyalty, repeat business, referrals, complaints, certainty, and customer outcomes—not speed alone. Refuse uses of customer data that exploit vulnerability or presumed ability to pay. Build strong customer service systems first, then layer AI on top of them. Customer service may stop being a department, but service must become the operating system of the entire company. Chapters 00:59 — Why the customer service department is dead 01:51 — Enterprise-wide ownership still needs one accountable champion 05:06 — Does every company need a chief experience officer? 07:34 — Breaking silos through cross-functional CX leadership 08:26 — Are companies using AI to improve service or cut headcount? 11:14 — The new role of the human service professional 13:30 — Preventing escalation overload and empathy fatigue 15:17 — When customers send third-party AI to handle your company 19:36 — Will access to a human become a premium service? 23:08 — Why community and brand experience are returning 26:11 — AI costs, disappearing entry-level roles, and the talent pipeline 30:14 — Walmart, Starbucks, and the people-led, tech-powered model 34:03 — Personalization, surveillance, and the integrity line 38:59 — Which traditional customer service metrics now work against CX? 42:23 — A practical blueprint for leadership, employees, technology, and measurement 48:05 — The first question every CEO should ask Key Takeaways Customer experience can be enterprise-wide without becoming leaderless; one person must still own the system and its results. AI creates the most value when it removes repetitive work and gives employees more time for judgment, empathy, and connection. Automating simple interactions can leave human agents with a relentless stream of emotionally difficult cases, increasing the risk of empathy fatigue. Third-party AI platforms may become the new front door to the customer journey, making a distinctive human brand experience even more important. Easy access to a knowledgeable human can become a powerful competitive advantage. Personalization crosses the line when customer data is used to exploit vulnerability or presumed willingness to pay. Metrics such as average handle time can produce unintended behavior when they are not balanced with loyalty, customer outcomes, repeat business, and referrals. A company needs clear service systems before it layers AI onto the customer experience. Quotes "Someone has to lose sleep at night over the experience the company is providing." — John R. DiJulius III "When answers are everywhere, questions become the scarce resource." — John R. DiJulius III "When the world gets more artificial, we need to become more human." — John R. DiJulius III "The more digital we become, the more human is the competitive advantage." — John R. DiJulius III "Integrity shouldn't be something that is outdated." — John R. DiJulius III "EX equals CX. Employee experience equals customer experience." — John R. DiJulius III "Customer service may stop being a department, but service must become the operating system of the entire company." — Denise Thompson Resources Mentioned in This Episode Gartner: Half of companies that cut customer service staff because of AI will rehire by 2027 Gartner: 85% of service leaders are expanding human-agent responsibilities Gartner: Customers are three times more likely to use third-party GenAI than company chatbots Pega: Consumers demand more from AI-powered customer service PwC: 2025 Customer Experience Survey Walmart: AI-powered tools for 1.5 million associates Starbucks: Green Apron Service and improved service performance Delta Air Lines: Response regarding AI-supported pricing Links: ROX Dashboard:  https://thedijuliusgroup.com/rox-dashboard/ The DiJulius Group Methdology: https://thedijuliusgroup.com/x-commandment-methodology/ Company Service Aptitude Test:  https://thedijuliusgroup.com/c-sat-forms/individual-c-sat/ Schedule a Complimentary Call with one of our advisors:  tdg.click/claudia Ask John!  Submit your questions for John, to be aired on future episode:  tdg.click/ask Customer Experience Executive Academy: https://thedijuliusgroup.com/project/cx-executive-academy/ Experience Revolution Membership:  https://thedijuliusgroup.com/membership/ Books:  https://thedijuliusgroup.com/shop/ Contacts:  Lindsey@thedijuliusgroup.com , Claudia@thedijuliusgroup.com If you want to learn how world-class organizations build cultures customers cannot live without, explore The Experience Revolution Membership. Inside the membership you'll gain access to livestream workshops, practical frameworks, and proven strategies used by organizations around the world. Learn more at https://thedijuliusgroup.com/membership/ Learn More If your organization is working to improve customer experience but struggling to connect it to measurable business outcomes, The DiJulius Group can help. Visit: https://thedijuliusgroup.com Listen to more episodes: https://thedijuliusgroup.com/the-customer-service-revolution-podcast/ Subscribe We talk about topics like this each week; be sure to subscribe wherever you listen to podcasts so you don't miss an episode.

Patron Points President Erik Ogren and Director of Marketing Heather Webb talk with CSP's Vice President of Content Strategy Abbey Lewis for a special episode of the "At Your Convenience" podcast about their company's involvement in the Outlook Report, sharing insights on customer loyalty in convenience retail.Inflation has changed consumer behavior, with 35-40% of convenience store purchases now being planned rather than spontaneous. "Customers are making deliberate choices on where to go and what to buy," Webb said, requiring retailers to engage through personalized communication at the moment of decision-making.Both Webb and Ogren highlighted the growing importance of retail media networks for monetizing customer data. Loyalty members show a four-times increase in visits, 20-34% larger basket sizes and three times more likelihood to cross-shop categories.

Anika sat down with George Khachatryan to explore the evolving landscape of AI-driven marketing, personalization, and the massive trust gap currently sitting between brands and consumers. The conversation revealed a counterintuitive truth: while 93% of marketing leaders believe AI helps them understand their customers, only 53% of consumers agree. George's unique journey—from earning a PhD in mathematics at Cornell and building an early ed-tech AI company to founding OfferFit and navigating its $325M acquisition by Braze—offered a practical look at how reinforcement learning and predictive data science are permanently replacing the manual grind of traditional A/B testing. In This Episode How a background in mathematics and early intelligent tutoring systems laid the groundwork for complex AI architectures. Stepping away from specialized tech to learn foundational company building through management consulting and operational transformations. Moving beyond rigid "Next Best Action" rules to autonomous reinforcement learning agents that experiment at the individual customer level. The strategic decision behind merging OfferFit with Braze in a $325M deal and why deep data science and engineering alignment matters. Why hidden bots, lack of transparency, and mismatched brand expectations are eroding consumer confidence. Blending predictive machine learning models (for timing and offers) with LLM agentic copy generation for maximum impact. Why students and early-career marketers must embrace AI literacy to stay competitive in a rapidly shifting job market. Timestamps 00:00 Introduction: The math, the $325M exit, and the AI trust gap 02:00 From Cornell mathematics and early ed-tech to management consulting 04:18 The limitations of traditional "Next Best Action" and the birth of reinforcement learning 09:22 Real-world personalization: How brands like Yum Brands optimize customer engagement 12:39 The acquisition journey: Why OfferFit chose to integrate with Braze 16:53 The 93% vs. 53% problem: Why consumers feel misunderstood by brands 20:41 Hybrid AI systems: Stitching together LLM copywriting and statistical decisioning 23:33 The personal cost of a "Sydney is just a bot" moment: The importance of transparency 28:32 The reality of enterprise caution vs. consumer expectations 29:56 Agentic commerce and the future of bot-to-bot interactions 34:39 Managing negotiation bots and complex consumer retention scenarios 37:25 Generational divides: Gen Z's dual relationship with AI adoption and career anxiety 40:59 Lessons for founders: Aligning philosophical visions before a merger 43:35 Final thoughts: Embracing the historic and fascinating shift in marketing technology Key Insights & Takeaways Insight 1: Personalization Requires True One-to-One Experimentation Traditional marketing relies on segmenting audiences and applying rigid, rule-based logic. True optimization requires reinforcement learning agents that operate at the individual customer level, autonomously testing variables like messaging, timing, and offers to discover what drives incremental engagement. Insight 2: The Danger of Hidden Bots and Broken Trust Consumers do not mind interacting with AI or automated tools, but they expect transparency. When a brand masks an AI agent as a human—and fails to take responsibility for its actions—it creates a deep sense of betrayal that permanently damages customer loyalty. Insight 3: The Power of Hybrid AI Infrastructure The most effective marketing systems do not rely on a single flavor of AI. Combining statistical reinforcement learning (to determine when and what to communicate) with LLM agentic text generation (to personalize how it is phrased) yields performance lifts of over 100%. Insight 4: Shared Vision is the Anchor of Any Successful Acquisition For founders navigating a potential exit, technical integration is only half the battle. Long-term success relies on frank, open discussions about philosophical alignment, shared visions, and mutual risk mitigation before signing a deal. Insight 5: Enterprise Caution vs. Consumer Speed While marketers are often bogged down by internal alignment and slow decision-making processes, consumers are interacting with cutting-edge AI tools daily. Brands that fail to bridge this expectation gap risk becoming obsolete. Resources & Links Mentioned Braze 2026 Global Customer Engagement Review OfferFit Yum Brands & Home Security (Client case studies discussed in the episode) About George Khachatryan George Khachatryan is a mathematician, entrepreneur, and executive leader serving as the Head of OfferFit by Braze. Holding a PhD in mathematics from Cornell University, George previously co-founded the ed-tech pioneer Reasoning Mind and worked as an associate partner at McKinsey. He co-founded OfferFit, an AI decisioning engine that utilizes reinforcement learning to automate marketing experimentation, culminating in its acquisition by Braze in 2025 for $325 million. Connect with George LinkedIn: https://www.linkedin.com/in/george-khachatryan/ Website: https://www.braze.com/ Like the show? Leave us a rating or review: https://lovethepodcast.com/67940257010b317cdaa9d857Follow the Show: https://followthepodcast.com/67940257010b317cdaa9d857Send a Message: https://podcastfeedback.com/67940257010b317cdaa9d857Check out our Website: https://www.yourbrandamplified.comSpeak to my Delphi Clone: https://www.delphi.ai/amplifywithanika Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Episode 310 opens with Steve Dennis reporting back from an invitation-only Amazon analyst day in Seattle, two days focused on Prime and grocery. Steve unpacks the breadth of the Prime flywheel, Amazon's push into sub-one-day delivery, the drone facility he toured just before the company announced an expansion to roughly 500 markets, and why Amazon's rise to the number two grocer in North America should have rivals looking over their shoulders. Then, the numbers. US retail sales grew about 5% excluding fuel. Walmart delivered a lackluster 2.6% US comp, its weakest in six years, offset by a 46% jump in global advertising and nearly $3 billion in tariff refunds the company says it will reinvest in price. Target posted a nearly 4% comp with traffic up 3.6%; real progress, though Steve cautions the invitation can be better than the party. In off-price, TJX comped 4% while Ross Stores turned in a second straight double-digit quarter. And Simon Property Group made the case that great physical retail is alive and well. The interview, recorded live at the CommerceNext Growth Show in New York, features Scott Friend, Partner at Bain Capital Ventures, and Indy Guha, General Partner at VMG Partners. Scott co-founded price optimization pioneer ProfitLogic before joining BCV twenty years ago; Indy co-leads VMG's commerce infrastructure fund after scaling Signifyd. Together they tackle a hard question: when AI makes everything easier to build, how do you tell a real company from a pitch formula? Their answer centers on founder clarity and earned domain expertise, because a couple of quarters' head start has never mattered more. The conversation ranges across whether personalization and merchandising optimization are now table stakes, the surveillance pricing debate, AI-driven homogeneity versus the promise of the "N of one" customer journey, and Indy's memorable "Claude-proof" test for anyone building in commerce. Both push back on agentic commerce hype, arguing agents will own low-interest replenishment missions while people keep the treasure hunt. Scott points to the revenue ramp of AI-native companies as evidence this cycle is real, not overhyped. Both land in the same place: brand, community, and authenticity are the last durable moats, and retail teams must become architects rather than assembly-line workers. Back in studio, on the radar: Steve tracks the bond market, with 30-year Treasuries at a 19-year high and the 10-year at 4.75%, squeezing discretionary income and retailer expansion plans alike. Michael watches Canadian icon Roots, newly sold to New York's Marquee Brands with Joe Mimran advising on merchandising, and asks whether the brand can reclaim its former glory. Registration is open for a special webinar featuring Steve in conversation with Placer AI's Head of Analytical Research RJ Hottovy. From changing shopping patterns to emerging market opportunities, shifting consumer demand continues to reshape the industry. So don't miss this data-driven session unpacking the most important trends defining today's marketplace and the strategies leading brands are using to win retail's future. It's all brought to you by Placer.AI and It all happens on Tuesday September 29 at 1pm ET..Register here today:https://www.placer.ai/discover-events/discover-shifting-consumer-demand About UsSteve Dennis is a strategic advisor and keynote speaker focused on growth and innovation, who has also been named one of the world's top retail influencers. He is the bestselling author of two books: Leaders Leap: Transforming Your Company at the Speed of Disruption and Remarkable Retail: How To Win & Keep Customers in the Age of Disruption. Steve regularly shares his insights in his role as a Forbes senior retail contributor and on social media.Michael LeBlanc is a senior retail advisor, keynote speaker and media entrepreneur. Michael has delivered keynotes, hosted fire-side discussions hosted senior retail executive on-stage in 1:1 interviews worldwide. Michael produces and hosts a network of leading retail trade podcasts, including The Remarkable Retail Podcast, The Voice of Retail, The Food Professor, The FEED powered by Loblaw and the Global eCommerce Leaders podcast. He has been recognized by the NRF as a global Top Retail Voice for 2025 and 2026 and continues to be a ReThink Retail Top Retail Expert for the fifth year in a row.

What happens when a global call center veteran steps into the automotive industry and starts questioning the way dealerships have always done things?  In this episode of the Millionaire Car Salesman Podcast, Sean V. Bradley and LA Williams sit down with Lee Harris, current Internet Director at Minnesota Truck Headquarters, a BPO veteran turned automotive innovator who is bringing a completely different perspective to dealership customer engagement. "Your most valuable asset that you have in your dealership, it's not the cars on the floor, it's not the cars in the showroom, it's the people." – Lee Harris With years of experience leading high-volume customer service, operations, and technology organizations, Lee is taking lessons from outside automotive and applying them to one of the industry's biggest opportunities: how dealerships communicate with, follow up with, and ultimately serve today's customer. The conversation dives into the evolution of the traditional BDC, the growing role of AI and automation, the importance of stronger processes and training, and why technology should make dealership teams MORE effective without removing the human connection.  "AI doubles in capacity and capability every two weeks." – Lee Harris If you're a Dealer Principal, GM, BDC leader, sales manager, or automotive professional trying to prepare for where customer engagement is headed next, you're going to want to hear this conversation! Key Takeaways: ✅ Lee Harris highlights the value of integrating advanced AI tools and CRM customization to enhance client services' effectiveness within car dealerships. ✅ The automotive sector often lags in adopting modern technology, with Harris noting the industry's typical five to seven-year lag behind bleeding-edge solutions. ✅ Personalization and the human element remain crucial in customer interactions, even when leveraging high-end AI tools to streamline processes. ✅ Fostering a team environment where personnel investment in training and morale is prioritized can drive substantial success, as evidenced by record-breaking sales figures at MTH. ✅ Harris advises dealership leaders to rethink traditional managerial roles by emphasizing leadership qualities that inspire and genuinely connect with employees.   About Lee Harris Lee Harris is a seasoned professional with nearly three decades of experience in the Business Process Outsourcing (BPO) industry. He began his career as an agent and ascended to senior executive roles at large organizations like Conduent, Xerox Services, and Sutherland Healthcare. Harris has been involved with operations in numerous countries, managing substantial revenues and diverse teams. Currently, he is the Director of Business Development at Minnesota Truck Headquarters (MTH) in St. Cloud, where his expertise in technology, customer experience, and process development is helping redefine automotive sales strategies.     AI Revolution in Automotive BDC: Transforming Client Services in Dealerships   Key Takeaways: Adapting New Technologies: CRM technologies are increasingly seen as outdated; AI tools are proving indispensable for operational efficiency in auto dealerships. Focus on Human Capital: Building a dedicated, well-trained team with a strong culture and synergy is vital for success. Engagement Optimization: Increasing customer engagement through technology, particularly AI, is paramount for maximizing showroom visits and sales success.   The Shift from Traditional BDC to AI Integration in Dealerships In the ever-evolving landscape of automotive sales, dealerships are faced with the need to innovate or risk being left behind. This conversation brings to light the transformational journey from traditional Customer Relationship Management (CRM) systems to Artificial Intelligence (AI) driven strategies. As Lee Harris from Minnesota Truck Headquarters shares, "AI doubles in capacity and capability every two weeks," underscoring the rapid advancement and adoption of technology that is necessary for modern dealerships to thrive. The podcast participants echo a pivotal revelation: the traditional CRM's limitations in dynamically adapting to ever-changing dealership needs. Sean V. Bradley emphasizes, "CRM is antiquated technology now," advocating for a shift towards tools like Podium's AI. This technology steps beyond static scripts, offering dynamic, personalized communication powered by an extensive knowledge base. This ability, Harris notes, allows dealerships to handle communications with precision, enhancing customer interaction and satisfaction. Through this integration, dealerships empower their sales teams to focus on high-impact interactions by letting AI handle routine, low-complexity tasks. Bradley states, "If we delegate all the tier one remedial activities to artificial intelligence, […] now my humans can focus on higher levels." This delegation not only optimizes human resource capabilities but also maximizes lead conversion, showcasing the multilateral benefits of AI over traditional CRM systems.   Emphasizing Human Capital and Leadership In the broader scheme of automotive business development, human capital remains the cornerstone of any successful dealership. Lee Harris passionately argues for investing in people, expressing, "Your people are the most precious thing that you have in your group, in your responsibility." This sentiment is a cornerstone for transformational leadership and modern business strategies within dealerships. The discussion probes into what sets excellent dealerships apart — their approach to nurturing and investing in a highly competent and motivated workforce. For Harris, leading a team goes beyond managing transactions; it's about cultivating a culture of excellence where team members understand their value and are equipped with the right tools and training. By stating, "Invest both professionally and personally into those individuals to be successful," Harris emphasizes the significance of a dedicated and well-supported team for achieving dealership objectives. Training and development play an integral role in this framework. Dealer Synergy's Bradley On Demand platform is applauded for its comprehensive training, ensuring that team members "don't even get to touch a phone until they are through the initial training," a practice that ingrains a regiment of quality assurance and preparedness foundational to operational success.   Revolutionizing Customer Engagement A recurring theme throughout the dialogue is the pivotal role of customer engagement strategies in dictating sales and dealership success. The integration of AI is poised to revolutionize how dealerships engage with prospective customers, significantly bridging gaps between inquiries and successful sales. Bradley notes the chronic issue of low engagement levels, stating that most dealership efforts result in "not talking to somebody." This reveals a critical area of opportunity — the need for effective engagement strategies. AI tools like Podium's Jerry 2.0 transform engagement dynamics by facilitating omnipresent communication, ensuring customer interactions are timely, relevant, and personalized. In integrating AI, dealerships can remarkably enhance appointment show rates, which Harris notes as being "73% appointment show ratio" — a staggering figure above industry averages. This indicates AI's profound impact on bridging communication gaps, ensuring prospects are guided efficiently through the sales funnel. The potential of AI in this capacity is magnified by its ability to analyze and learn from interactions, delivering nuanced conversations that are tailored to client needs and potentially increasing showroom traffic and sales. Harris concludes, adopting "convenience and a friction-free process" is essential for translating client inquiries into satisfied customers, highlighting AI's role in crafting seamless customer journeys. In the evolving landscape of automotive sales and services, the dealership's adaptability to AI-driven methodologies is not just a competitive advantage; it is becoming a standard of future-forward operations. The rich discussions from industry leaders cast a spotlight on the profound changes AI brings, demonstrating a roadmap for others to follow, where smart technology and human empathy work in tandem toward exceptional dealership success.     Resources + Our Proud Sponsors: ➼ Podium: The AI Platform Powering the Modern Dealership. From instant lead response to seamless test drive scheduling, Podium's AI Employee Jerry works 24/7 to turn every lead into a conversion, so your team can focus on closing. Trusted by thousands of dealerships nationwide and proudly featured on the Millionaire Car Salesman Podcast. Learn how Podium can help you sell more cars, book more service appointments, and grow your dealership. Discover how Podium's innovative AI technology can unlock unparalleled efficiency and drive your dealership's sales to new heights. Visit www.podium.com/mcs to learn more!   ➼ The Millionaire Car Salesman Facebook Group: Join the #1 Automotive Sales Mastermind Facebook Group with over 29,000 automotive professionals worldwide. The Millionaire Car Salesman Facebook Group is the go-to community for car salespeople, BDC agents, sales managers, general managers, and dealer principals looking to increase performance, income, and leadership skills. Inside the group, members collaborate daily on automotive sales strategies, lead handling, phone scripts, closing techniques, CRM best practices, dealership leadership, and accountability systems. Learn directly from top automotive trainers, industry mentors, and high-performing sales leaders who are actively winning in today's market. If you're serious about growing your automotive career, increasing car sales, and building long-term success, join The Millionaire Car Salesman Facebook Group today!   ➼ Dealer Synergy: Dealer Synergy is the automotive industry's #1 Sales Training, Consulting, and Accountability Firm, with over 20 years of proven dealership success nationwide. We specialize in helping car dealerships increase sales, improve processes, and build high-performing Sales, Internet, and BDC departments from the ground up. Our expertise includes automotive phone scripts, rebuttals, CRM action plans, lead handling strategies, BDC workflows, Internet sales processes, management training, and accountability systems. Dealer Synergy partners directly with dealership leadership to align people, process, and technology, ensuring consistent results and scalable growth. From independent dealers to large dealer groups and OEM partnerships, Dealer Synergy delivers measurable performance improvements, stronger teams, and sustainable profitability.   ➼ Bradley On Demand: Bradley On Demand is the automotive industry's most advanced interactive training, tracking, testing, and certification platform for car dealerships — built to develop top-performing teams across Sales, Internet Sales, BDC, CRM, Phone Skills, Leadership, and Management. In addition to LIVE virtual automotive training classes and a library of 9,000+ on-demand dealership training modules, Bradley On Demand now includes AI Phone Roleplaying and Coaching to help salespeople and BDC agents practice real dealership conversations before they ever get on the phone with customers. This AI-powered roleplay technology strengthens phone scripts, objection handling, appointment setting, lead follow-up, and closing skills, while providing measurable coaching feedback for continuous improvement. Bradley On Demand empowers dealerships to train faster, coach smarter, improve call performance, increase closing ratios, and sell more cars more profitably — all through structured, trackable, modern automotive training.

We have access to more health information than ever before.We know movement matters. We know sleep matters. We know our habits matter. We can find workouts, recipes, podcasts, articles, expert advice and health tips within seconds.So if information was all we needed to change… wouldn't we all be doing everything we already know we're supposed to be doing?In this episode of FIT CHICKS Chat, Amanda explores the gap between knowing what to do and actually doing it—and why lasting transformation requires so much more than simply giving people more information.We're diving into six pieces that can help turn information into real change:• Personalization—because the "best" plan still has to fit the person• Simplicity and clarity instead of information overload• Understanding the behaviors underneath our choices• Creating an environment that makes change easier• Support and accountability without shame• Building the mindset and self-belief required for lasting changeWhether you're working on your own health or you're a coach or aspiring coach who wants to better support others, this episode will challenge you to stop asking, "What else do I need to know?" and start asking, "What is actually preventing me from using what I already know?"And if you love the idea of helping women bridge that gap between information and transformation, our Holistic Weight Loss Coach Certification may be your next step.Learn more here:https://fitchicksacademy.com/hwlcMake sure to hit +FOLLOW so you never miss an episode of FIT CHICKS Chat!

"Send me a text"The finale. Six episodes studying the brands winning right now, all pointed at the only question that matters for your business. What's coming next, and how do you get in front of it. I make five real predictions. Generic education dies while owned education becomes a moat. Personalization jumps from the three-minute quiz to your actual bloodwork, and whoever scales that builds the next giant. Discovery moves to AI recommendation, which makes generic brands invisible and specific brands unmissable. The four forces stay exactly the same while the terrain transforms completely, so the winners build desire, hope, trust, and belief on brand new ground. And a counter-wave of radical human simplicity rises against all the tech, proving both edges win and only the middle dies. Every arrow points the same way. Get specific, get defensible, own something, and pick an edge before the next wave decides for you.Learn more about The Supplement Business Accelerator Group at https://creativethirst.com/groupIf you're interested in working with me and my team to improve your supplement business. You can learn more at my website https://creativethirst.comClick here to grab your copy of the Health Supplement Ad Swipe Guide.Discover what really works in funnel marketingNeed help increasing sales on your own? Click hereStuck at $1 - $5M in revenue? Click HereCase Study on how Creative Thirst added over $200,000 for one supplement brand

We've spent nearly two decades trying to make selling easier, CRMs, automation, sequences, intent data, and now AI. So why does it feel harder than ever to actually earn a buyer's trust? Jen Allen-Knuth, founder of DemandJen, joins Rachel Truair to explore whether sales technology was ever really built for the buyer, or whether it mostly optimized the seller's side of the interaction. Jen makes the case that “personalization” has become one of the emptiest words in sales, breaks down what actually makes a cold email work, and gives her honest read on whether the sales profession shrinks as AI takes over research and outreach. The question underneath it all: if every piece of sales technology disappeared tomorrow, what would still make one human worth talking to?Quotes"I think if we continue on as we have, there is going to be a much smaller number of people that are gonna sit in a sales profession.""Personalization has been one of the worst terms to ever come out of sales or marketing because it's not specific enough to mean anything.""In sales, the hard work works because it's hard. Most people choose easy."From the conversationWhy so much of sales technology has been built to optimize the seller's side of the interaction, not the buyer'sWhy “personalization” has become one of the emptiest words in sales and marketing, and what real relevance looks like insteadWhat separates a cold email that gets a reply from the hundreds that get ignoredWhether the sales profession shrinks as AI takes over research, writing, and outreach, and where a human still earns their seat at the tableWhy customer stories are sales' most underused asset, buried in an LMS while reps lean on self-congratulatory slidesAbout the guestJen is the founder of DemandJen, a sales training and consulting company focused on helping GTM teams break through the status quo and avoid losing pipeline to buyer risk aversion. As a keynote speaker and sales trainer, she specializes in equipping sales teams selling into enterprise and mid-market with the tools to overcome customer hesitation and close more deals. Jen brings in-depth strategies to help teams confront the fear of change and risk, and she's a go-to for sales kickoffs and workshops that drive success.LinkedIn: https://www.linkedin.com/in/demandjen1/

Sidd Motwani, co-founder and CEO of Malachyte, on real-time personalization that starts before the first click. Malachyte builds a user vector, a numerical representation of each shopper's intent and preference, with no third-party cookies, no purchase history, and no sign-in required. Sidd and his co-founder built the user vector platform at Spotify, where it powers most of the application across music, podcasts, and audiobooks. In this conversation: What a user vector is and why it works cold, with no data about the shopper Personalizing from the referrer, device, time of day, and location before a first click The Spotify story, from one team's technology to the backbone of the app A free pilot for Shopify and Salesforce Commerce brands, with Malachyte doing the heavy lifting His agentic commerce take, agents and humans will both come to the store, and the store itself has to serve them proactively Chapters00:00eTail Boston and the data and AI track01:19What Malachyte does02:04The Spotify user vector story02:52Free pilot and the roadmap05:02Agentic commerce and proactivity Sidd Motwani: LinkedIn Malachyte: malachyte.com Recorded live at eTail Boston, August 10 through 12, 2026. To learn more about our at-event interviews, go to talk-commerce.com/events

How Neera's Vibroacoustic Bed Helps You Fall Asleep Faster"If you sleep this way, you wouldn't want to sleep another way.”When Igor said this, I had to go and try out the Neera bed myself, and afterward I interviewed Igor about the innovative science and technology behind Neera. It is a device designed to improve sleep through vibrational frequencies and personalized algorithms. In our conversation we explore how this technology can transform sleep quality and overall well-being.Topics:* Science of vibrational frequencies and sleep* Personalized algorithms for sleep optimization* Acoustic and mechanical engineering in sleep devices* The role of frequencies in regulating nervous system and chakras* User experience and self-reporting in sleep tech* Future developments in vibrational sleep technologyTimestamps:* 0:33 Who Igor is and what Neera does* 1:19 Why he built it: devices measure, apparatuses act* 2:57 Why sleep is the highest-leverage longevity target* 4:05 “See how it feels” and the phrase that sold it* 5:30 Where standard sleep advice runs out* 6:32 The mechanism: frequencies through touch, not ears* 9:48 Do solfeggio frequencies and brainwaves connect?* 11:24 Making 2 Hz on a mattress without a giant speaker* 12:38 Composing a state, and AI programs on request* 15:02 Personalization: wearables, self-reporting, onboard sensors* 17:23 Nina's session, and the cat purr program* 20:12 Chakra frequencies and the 96% blind test* 21:54 Inside the mattress: actuators and waveguides* 24:57 Validating with EEG and the cost of clean sleep research* 27:05 Day programs vs night programs* 28:43 Who it works best for: athletes, NSDR, day reboots* 29:58 Sleep inertia and the 3am wake-up* 32:53 Catching micro-wakeups and returning you to sleep* 35:06 The first week, and napping vs the 20-minute program* 39:12 Hardest part: hardware or software?* 41:15 The one non-responder* 42:09 Launch & Founders ClubABOUT IGOR:Igor is the co-founder of Neera. They are building nervous system regulation hardware for high performers. Over 15+ years in deep tech, he was design director on YotaPhone, the first dual-screen smartphone, and co-founded Gero (disease prediction from wearable movement data) and Atmotube (air quality sensing, 70,000+ units shipped, used in research at Stanford and Harvard).CONNECT WITH NEERA:* Website: https://neeralab.com/* Neera LinkedIn: https://www.linkedin.com/company/neerasleep/* Igor's LinkedIn: https://www.linkedin.com/in/igorme/ABOUT NINA'S NOTES: Nina's Notes explores the intersection of longevity science, neuroscience, and human optimization. Hosted by Nina Patrick, PhD in pharmaceutical sciences and longevity researcher, each episode translates cutting-edge research into actionable insights for living longer, better.CONNECT WITH NINA'S NOTES* Newsletter:https://www.ninasnotes.xyz* LinkedIn:https://www.linkedin.com/in/ninapatrick/* Website:https://www.ninapatrick.xyz Get full access to Nina's Notes at www.ninasnotes.xyz/subscribe

As lifestyles evolve, so does home design. Homeowners want flexible spaces, more privacy, stronger connections to the outdoors and finishes that reflect their personal style. The result is a shift toward homes that aren’t just attractive but also work for the way people actually live.  Kelley Collins, design studio manager with Ashton Woods, recently joined Carol Morgan on Atlanta Real Estate Forum Radio to discuss how thoughtful design can balance function, personality and timeless style — and why the best homes don’t necessarily follow the latest trend.  Home Design Starts With How People Live  “We always joke that your lighting is like jewelry for your favorite outfit,” Collins said.  Lighting can transform a room, highlight architectural features and draw attention to artwork or other focal points. But good design goes beyond what catches the eye. It starts with understanding how people will use a space.  That has become particularly important as more people work, study, exercise and spend time at home. Rooms that once served a single purpose now may need to accommodate a home office, classroom, playroom, workout area or guest space.  Flex Rooms Give Homeowners More Options  Flex rooms offer a clear example of home design adapting to changing needs. A home office today could become a study space for a child tomorrow. A playroom could eventually become a hobby room, exercise area or guest room. Adaptability matters even more for multigenerational households. Rising living costs have contributed to more families living with parents or in-laws, making privacy and separation increasingly important. Doors, finished basements and multipurpose rooms can help families accommodate more people without making everyone feel like they’re living on top of each other.  For homebuyers, it’s worth looking beyond how a floor plan works today. Consider how a room could serve the household five or 10 years from now.  Open Floor Plans Meet the Need for Privacy  Open-concept living remains popular, but the way people use their homes has prompted a closer look at privacy. An open kitchen, dining and living area can make entertaining easier and create a strong sense of connection. But when several people work, study or relax at the same time, too much openness can become a challenge. Interior doors, pocket doors and strategically placed private rooms can provide some separation without giving up the benefits of an open layout.  Rather than choosing between open and closed floor plans, homeowners increasingly want a balance between shared spaces and places to retreat.  Personalization Should Go Beyond Trends  Personalization plays an important role in the design process, but it looks different for every homeowner. Some buyers want to customize nearly every selection. Others prefer a more restrained palette and use one or two features, such as a distinctive backsplash or lighting fixture, to make the home feel like their own.  The goal is to create a cohesive design that reflects the homeowner without relying too heavily on a short-lived trend.  “If they do have that bold design or that style that they want to incorporate, they really do it with intention,” Collins said.  That doesn’t mean homeowners need to avoid bold choices. Instead, they should consider how those choices fit into the rest of the home and whether they’ll still feel right years from now.  Timeless Design Can Still Evolve  Home design trends constantly change. Cabinet colors have moved from dark finishes to gray and white and are now shifting toward warmer tones. Light and medium wood tones and off-white finishes are gaining popularity as gray and stark white interiors become less dominant.  Trend cycles make timeless design valuable. Buyers want their homes to feel current, but they also want to feel comfortable with their choices years after construction ends. A neutral foundation provides flexibility, while lighting, furnishings, artwork and hardware can add personality and allow homeowners to update their spaces over time.  Design for Durability and Everyday Life  A beautiful home also needs to hold up to everyday life. Flooring and countertops offer good examples. Natural hardwood remains popular, while engineered luxury vinyl flooring attracts buyers who value durability. Quartz continues to appeal to homeowners who appreciate its consistency and low maintenance, even as designers continue to value the character of natural stone. Aesthetics are only part of the decision. Families with children, pets or frequent guests may prioritize different materials than homeowners looking for a low-maintenance second home or an entertainment-focused space.  The Kitchen Remains the Heart of the Home  For all the changes in home design, some priorities remain remarkably consistent.  In the kitchen, an island can provide food preparation space, seating, a gathering point for family and friends and a place for homework or casual conversation. Other features, such as spa-inspired showers, reflect the same desire to make everyday spaces more enjoyable. Ultimately, good design isn’t just about making a room look good. It should make the room work better, too.  Trust the Design Process  For buyers building a new home, the number of decisions can quickly become overwhelming. Flooring, cabinets, countertops, tile, lighting and fixtures all contribute to the final result. A design professional can help homeowners understand how individual selections work together and where to focus their investment. Instead of making every decision at once, buyers can work through selections step by step and build a cohesive design.  The Future of Home Design Will Follow Lifestyle  No one can predict exactly which colors, materials or architectural features will dominate home design five or 10 years from now. Trends will continue to change. What we can predict is that homes will continue to adapt to the people who live in them. Flexible rooms can accommodate changing needs. Private spaces can balance open gathering areas. Outdoor living can extend a home’s usable space. Personalization can make a house feel distinctly like its owners. The most enduring design principle may be the simplest: Start with how people live and design from there. The goal is to create a home that represents the homeowner so well that “10 years down the road they still love their home.” That may ultimately separate a home that simply follows a trend from one that continues to feel right long after the trend has passed.  To learn more about home design trends and how lifestyles influence the way homes are built, listen to the full episode of Atlanta Real Estate Forum Radio. For more information about Ashton Woods, visit https://www.ashtonwoods.com/.  About Ashton Woods  Ashton Woods is one of the nation's largest private home builders, creating thoughtfully designed homes and communities across the United States. With a focus on design, quality and personalization, the company builds homes that reflect how people live today while providing opportunities for homeowners to make their spaces their own.  Podcast Thanks       Thank you to Denim Marketing for sponsoring Atlanta Real Estate Forum Radio. Known as a trendsetter, Denim Marketing has been blogging since 2006 and podcasting since 2011. Contact them when you need quality, original content for social media, public relations, blogging, email marketing and promotions. A comfortable fit for companies of all shapes and sizes, Denim Marketing understands marketing strategies are not one-size-fits-all. The agency works with your company to create a perfectly tailored marketing strategy that will suit your needs and niche. Try Denim Marketing on for size by calling 770-383-3360 or by visiting www.DenimMarketing.com.        About Atlanta Real Estate Forum Radio       Atlanta Real Estate Forum Radio, presented by Denim Marketing, highlights the movers and shakers in the Atlanta real estate industry – the home builders, developers, Realtors and suppliers working to provide the American dream for Atlantans. For more information on how you can be featured as a guest, contact Denim Marketing at 770-383-3360 or fill out the Atlanta Real Estate Forum contact form. Subscribe to the Atlanta Real Estate Forum Radio podcast on iTunes, and if you like this week's show, be sure to rate it. Atlanta Real Estate Forum Radio was recently honored on FeedSpot's Top 100 Atlanta Podcasts, ranking 16th overall and number one out of all ranked real estate podcasts. The post Ashton Woods: Where Design Meets Real Life appeared first on Atlanta Real Estate Forum.

What separates organizations experimenting with AI from those successfully turning it into real business value? In this episode, Life Accelerated host, Olivier Lafontaine, speaks with Robi Krempus, Vice President and Head of AI for Global Wealth and Asset Management at Manulife Wealth and Asset Management, about how the organization is moving AI beyond prototypes and into production. Robi shares Manulife WAM's approach to applying AI across investment management, distribution, and operations, emphasizing the importance of business collaboration, governance, and designing solutions around real organizational needs. The conversation explores lessons from deploying AI-powered sales enablement tools, driving adoption, and measuring impact through data-driven outcomes. Robi highlights why organizations should focus on high-value use cases, balance complexity with business impact, and build the right foundations to scale AI responsibly across the enterprise. Key Takeaways: AI creates the most value when organizations move beyond experimentation and build solutions around real business needs through close collaboration with users. Successful AI adoption requires strong governance, clear business cases, and a path to production that turns prototypes into measurable outcomes. Scaling AI responsibly means prioritizing high-value, lower-complexity use cases first while building the foundations needed for long-term transformation.   Jump Into the Conversation: (00:00) Meet Robi Krempus (03:48) Leading AI for Manulife Wealth and Asset Management(05:20) Applying AI Across Investment, Distribution, and Operations(06:31) Why Data and Measurement Matter for AI Success(07:50) Moving Generative AI From Experimentation to Production(09:20) Building AI Governance and Organizational Readiness(12:59) Creating AI-Powered Sales Enablement Tools(15:16) Building Custom AI Solutions for Business Needs(16:33) Cross-Functional Teams Driving AI Implementation(17:51) Encouraging AI Adoption Across Sales Organizations(21:28) Personalization and Compliance in AI-Generated Content(23:08) Measuring AI Value Through Business Outcomes(24:38) Lessons Learned From Scaling AI Solutions(27:11) Choosing the Right AI Use Cases(29:23) The Future of AI in Wealth and Asset Management(33:11) Closing Thoughts on Enterprise AI Transformation   Resources: Connect with Robi Krempus: https://www.manulife.com/ca/en/personal/group-plans/resources/bio/robi-krempus Connect with Robi Krempus on LinkedIn: https://www.linkedin.com/in/robi-krempus-ba121135/  Learn more about Manulife Wealth & Asset Management: Manulife Wealth and Asset Management  Connect with Olivier Lafontaine: https://www.linkedin.com/in/olivierlafontaine/

AI isn't just transforming the way we work, but also the way we write the software that people use for work. In this episode, we talk to two engineering productivity leads at Dropbox: Uma Namasivayam, senior director of software engineering productivity, and Anuradha Agarwal, director of software engineering. Whether it's writing tests, fixing bugs, tackling tech debt, or accelerating migrations, they explain how Dropbox engineers are using agentic AI—including in-house tools like Nova—to build the future of Dropbox, and create more space to do impactful work. ~ ~ ~  Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck.  Our theme song was composed by Doug Stuart.  Working Smarter is hosted by Matthew Braga. Thanks for listening!

Episode 157: This week, Kyle Van Pelt talks with Libby Buckley, Director of Wealth Administration & Marketing at Parable Wealth Partners. Libby leads the firm's client experience and team culture, bridges connections between clients, partner businesses, and non-profits, and creates experiences that help people rethink their wealth's potential to create change.  Libby talks with Kyle about how radical hospitality translates into the wealth management space. She discusses how firms can preserve high-touch, authentic human relationships as AI adoption accelerates, how to design thoughtful and memorable client experiences, and how organizations can scale without losing sight of their core purpose.  In this episode: (00:00) - Intro (00:57) - Libby's money moment (05:32) - Libby's definition of radical hospitality in wealth management (08:05) - Client events that create meaningful connections  (09:56) - Why AI makes authenticity even more valuable (11:52) - Practical advice for building soft skills and radical hospitality habits  (16:12) - How culture drives Parable's organic growth  (18:31) - Scaling without losing authenticity  (21:08) - Libby's outlook on the future of the financial services industry (24:08) - Libby's Milemarker Minute Key Takeaways Use efficiency to create better relationships. AI can save time, but its greatest value is giving leaders more opportunities to invest in conversations, trust, and meaningful client experiences. People remember how you made them feel. Exceptional service solves problems, but genuine hospitality creates lasting relationships by helping people feel seen, understood, and valued. Culture is something you protect. As organizations scale, intentional hiring, regular team development, and shared purpose become essential for maintaining the culture that fuels long-term success. Personalization goes beyond using someone's name. Understanding people's preferences, interests, and communication styles creates experiences that feel thoughtful instead of transactional. Quotes "We think of money as the invitation, not the destination. So, wealth is not something to accumulate, but something to activate." ~ Libby Buckley "If you don't know who you are, who you want to serve, and how you're going to do that uniquely, quit. Authenticity is going to matter so much more moving forward." ~ Libby Buckley "How do you show up, and how do you want to show up for clients and your team, I think is going to be one of the biggest contenders moving forward." ~ Libby Buckley Links  Libby Buckley on LinkedIn Parable Wealth Partners Unreasonable Hospitality Paterson Center The Ideal Team Player The Art of Gathering Chief Joy Officer Connect with our hosts Milemarker.co Kyle on LinkedIn Jud on LinkedIn Subscribe and stay in touch Apple Podcasts Spotify YouTube Produce game-changing content with Turncast Turncast helps your company grow by producing top-quality content and fostering transformative conversations. We specialize in content generation, podcasting, digital strategy, and audience growth for fintech and financial services companies. Learn more at Turncast.com.

Vanitha is a marketing professor at the University of Pittsburgh, Director of their Center for Branding, and author of Hyper Digital Marketing: Six Pillars of Strategic Brand Marketing in an AI-Powered World. Her client roster includes Hershey, Kraft Heinz, and P&G — brands that don't tolerate bad advice.In this episode, she explains why the old "command and control" era of brand management is over, what generative engine optimization (GEO) means for your go-to-market strategy right now, and why the most strategic thing you can do for your brand today might be making your purpose machine-readable. If you're still building a brand for humans only, you're already behind.Key Takeaways4:41 — The death of command and control branding. Brand meaning is no longer dictated from the top down. It's co-created by influencers, social users, experts — and now AI agents. Governance has to evolve.6:10 — GEO & AEO replace SEO. Generative Engine Optimization and Answer Engine Optimization are the new disciplines. Brand managers must now optimize for AI agents, not just human search.6:52 — Agent-to-agent commerce is coming. A customer's AI agent will negotiate with a seller's AI agent. The "double agent problem" is not hypothetical — it's the near future of B2C and B2B commerce.8:46 — Phygital is a strategic imperative. Physical and digital experiences are merging. AI-powered dynamic shelves, Gucci's tech-integrated showrooms, and real-time personalization are the new baseline customer expectation.10:07 — AI as a brand governance layer. AI can monitor every touchpoint and enforce brand compliance at scale — something no human team can do. It can also catch PR crises before they escalate.13:55 — Brand intelligence: three AI capabilities every founder needs. Predictive analytics (lead generation), generative AI (content at scale), and ethical AI (aligning purpose with every touchpoint) — each with a different role in the customer journey.16:05 — The uncanny valley of personalization. Empathetic AI can read emotional state and adjust messaging — but cross the line and customers feel surveilled. Personalization has to be "just right" or it backfires.19:20 — Startups have a structural advantage over legacy brands. Legacy companies are paralyzed by hierarchies and permission layers. Founders building from scratch can design AI-native workflows from day one.21:37 — Future-proof move: invest in data quality now. A unified, 360-degree view of customer data is the foundation for every AI capability. Without it, your AI tools have nothing to work with.22:47 — Purpose + Platform: the two most critical pillars. Purpose must become machine-readable. Platform thinking turns a product into an ecosystem. These two shifts separate brands that AI agents surface from those they ignore.26:44 — Brand as API. Codify your values into machine-readable rules. Program your AI agents to optimize for what you actually stand for — or they'll optimize for something else entirely.29:54 — Start from the experience, not the tools. The biggest mistake founders make: buying AI tools and hoping they add up to something. Work backwards from the customer's pain point, then slot in the right AI capability.37:39 — Highest-leverage AI moves in the next 60–90 days. Lead generation, predictive analytics for lifetime value modeling, and personalized content at scale — these are the three areas most founders are underleveraging right now.Tweetable Quotes"Brand meaning is no longer dictated from the top down. It's assembled by algorithms, co-created by communities, and negotiated between machines before a human is ever involved." — Dr. Vanitha Swaminathan"Your next customer's AI is already looking. The question is whether it can find you." — Jeff Mains"Taking your brand purpose and converting it into machine-readable code — that's what it means to be visible in an AI-powered world." — Dr. Vanitha Swaminathan"Peloton could have just sold treadmills. Every brand needs to ask: are we a product, or are we a platform?" — Dr. Vanitha Swaminathan"The small entrepreneur has a huge advantage. They're building systems from scratch — legacy organizations are caught with hierarchies that AI can't penetrate." — Dr. Vanitha Swaminathan"Purpose isn't a brand value anymore. It's infrastructure." — Jeff Mains"Start from the experience, work back to the tools — not the other way around." — Dr. Vanitha Swaminathan"You have to put checks and balances in place just like companies built privacy policies after the first cybersecurity wave. That's where brand management is headed." — Dr. Vanitha SwaminathanSaaS Leadership Lessons1. Your brand needs to be legible to machines, not just humans. AI agents are the new gatekeepers between your product and your buyers. If your differentiation, purpose, and proof points aren't structured in a way machines can parse, you won't make the shortlist — even if you're the best solution. Audit your website and content through the lens of an AI agent, not just a human reader.2. Stop buying tools. Start redesigning processes. Most companies pour money into AI tools that live in isolation and never add up to a better customer experience. The highest-ROI move is mapping your customer journey, identifying the friction points, and then selecting AI capabilities to solve specific problems. Tools follow process — not the other way around.3. Your data is your competitive moat. AI is only as good as what you feed it. Founders who invest early in unified, high-quality customer data — breaking down internal silos and creating a 360-degree view — will compound that advantage over time. Your competitors buying tools without clean data are spinning their wheels.4. Codify your values or your AI will invent them. If you don't tell your AI agents what to optimize for, they'll optimize for something — and it might not align with your brand. Translate your purpose, values, and brand standards into machine-readable rules. Think of your brand as an API: clear inputs, predictable outputs, consistent behavior at every touchpoint.5. The human-AI mix is your new product design challenge. The question isn't whether to use AI in customer-facing functions — it's where the handoff happens. Too much AI and you feel sterile. Too little and you can't scale. The founders who win will design deliberate human-in-the-loop moments that create trust and preserve the brand experience where it matters most.6. Think platform, not product. Every SaaS company is already closer to a platform than a product — you have data, users, and network effects working for you. Lean into it. Build the ecosystem around your core offering. Nike isn't a shoe company; Peloton isn't a treadmill company. Ask what yours is really for, and build accordingly.Guest Resourcesvanitha@katz.pitt.eduhttps://business.pitt.edu/professors/vanitha-swaminathan/https://www.facebook.com/PittBusinessSchool/photos/vanitha-swaminathan-thomas-marshall-professor-of-marketing-and-director-of-the-c/10158297436008280/https://www.linkedin.com/in/vanitha-swaminathan-5924896https://www.instagram.com/vanitha_swaminathanEpisode SponsorThe Futureproof Series - https://www.youtube.com/playlist?list=PLfkXKUPZ5xuOqMPR7_gzGybncTtavyR1NThe Captain's KeysSmall Fish, Big Pond – https://smallfishbigpond.com/ Use the promo code ‘SaaSFuel'Champion Leadership Group – https://championleadership.com/https://jeffmains.com/books/SaaS Fuel ResourcesWebsite - https://championleadership.com/Jeff Mains on LinkedIn - https://www.linkedin.com/in/jeffkmains/Twitter - https://twitter.com/jeffkmainsFacebook - https://www.facebook.com/thesaasguy/Instagram - https://instagram.com/jeffkmains

How much of your business was designed by you, and how much of it came from watching what worked for somebody else? In this episode, I'm getting into the concept I've been circling all year, which is personalizing your business model before you buy another strategy.  Nearly every "proven system" on the market is somebody's personality and strengths turned into a process, and when you buy the process without checking whether the person behind it resembles you at all, you end up running your business on willpower. I'm walking through why two completely opposite launches both worked this year, where the income roller coaster comes from, and the three functions of your business that can be personalized to how you're wired. I'm also sharing the two questions I run every new strategy through before I spend money on it, including the four-hour webinar I sat through for a program I decided not to buy. If something in your business has felt off lately and you haven't been able to name what it is, this conversation will give you language for it and a way to decide what stays, what goes, and what you never should have bought in the first place. Timeline Highlights [01:19] – Coming back from the summer interview series and why I pulled myself off the content cycle for six weeks [03:20] – The concept I've been diving into all year, and the offer I built that made money without fitting me at all [05:32] – Two launches at opposite ends of the price spectrum, and what they prove about what's working right now [09:02] – Why the thing that's working isn't a specific model, and what it is [13:03] – The four-hour webinar I watched for a program I decided not to buy, and the discernment behind that call [19:01] – Every proven system is somebody's personality and strengths turned into a process [20:26] – Why the coach teaching daily video and the mentor who refuses sales calls are both teaching themselves [23:57] – Where the income roller coaster comes from, and why willpower is the mechanism [27:15] – The three core functions of your business that can all be personalized to you [38:22] – The two questions to run before you buy another strategy, course, or coaching program [45:49] – The free personalization panel on August 12 with Megan Yelaney, Heather Sager, and Linda Sidhu Top Quotes from the Episode "Every proven system you can buy is somebody's personality and strengths turned into a process. The real question is whether that process fits how you're built." "If you try to run a system that doesn't match you, it runs on willpower, and willpower always runs out before the revenue does." "Those income swings are a design problem, and no amount of discipline is going to fix a model that was built for somebody else." "Almost any business model you've ever heard of is working for somebody right now. What's left to figure out is which one is working for you." "The strategy has to fit your average day. Your best day is not the one you'll be living most of the time." "I had close to a 40K month in July while barely showing up online, because the business runs on assets that compound instead of a schedule that demands I perform." "Simplicity is what scales. Complexity is usually the thing draining your revenue while you're busy adding more to fix it." Links & Resources Take the "What's Your CEO Type?" Quiz Free personalization panel, August 12 at 12:30 PM ET, with Megan Yelaney, Heather Sager, and Linda Sidhu: https://go.lauraschoenfeld.com/personalization  If this episode resonated with you, follow the podcast, leave a review, and share it with someone who's ready to build a business that actually fits their life.

Send us Fan MailJohn Owen, CEO of Blaze Pizza, joins Zack Oates to discuss how restaurants can create memorable guest experiences through personalization, consistency, and strong execution. With more than three decades of leadership experience across brands like McDonald's, Subway, and Scooter's Coffee, John shares why understanding the difference between customization and personalization is critical for today's restaurants.Zack and John discuss:Why personalization matters more than ever in hospitality The difference between customizing a product and personalizing an experience How brands should approach innovation and market disruption Why customer feedback must guide restaurant decisions Building consistency across hundreds of locations What restaurants can learn from Chick-fil-A's guest experience strategyThanks, John!Links:https://www.instagram.com/blazepizza/?hl=enhttps://www.linkedin.com/in/john-o-73422325/https://www.linkedin.com/company/blazepizza/https://www.blazepizza.com/

In this conversation, Dr. Gladden and Annelie Smith explore the intersection of genetics and nutrition, emphasizing the importance of personalized approaches to health. They discuss the evolution of nutrigenomics, the role of AI in developing tailored health plans, and the complexities of hormonal balance as influenced by genetics. Annelie shares insights from her clinical experience, highlighting the need for a systems biology approach to understand the intricate relationships between genes, hormones, and overall health. The discussion also touches on future directions in genetic testing and the potential for more accessible and actionable insights for individuals. In this conversation, Dr. Gladden and Annelie Smith delve into the complexities of hormone replacement therapy, emphasizing the importance of understanding hormonal pathways and the role of genetics. They discuss how stress impacts hormonal balance and the significance of reprogramming the nervous system for better health outcomes. The conversation also highlights the relevance of nutrigenomics in personalized nutrition and the powerful benefits of sulforaphane. Finally, they explore the value of genetic testing for optimizing health and wellness.   For Audience Join the other 20,000+ high-performers getting weekly insights on biological reversal, exponential strategies, and Life Energy optimization→ https://start.gladdenlongevity.com/subscribe If you're ready to measure your 60+ biological ages and build a personalized reversal plan, apply for a discovery call here → https://start.gladdenlongevity.com/apply-now   Use code 'Podcast10' to get 10% OFF on any of our supplements at https://gladdenlongevityshop.com/!    Takeaways ·       Nutrigenomics provides insights into personalized nutrition. ·       Understanding genetics can enhance dietary recommendations. ·       AI is transforming the landscape of personalized medicine. ·       Systems biology offers a holistic view of health. ·       Patient engagement is key to successful health interventions. ·       Genetic testing can reveal vulnerabilities in health. ·       Hormonal balance is influenced by genetic factors. ·       Personalized health plans can improve patient outcomes. ·       The future of genetics holds promise for broader applications. ·       Access to genetic information can empower individuals. Hormone replacement therapy is complex and requires a systems approach. ·       Understanding genetic pathways is crucial for effective hormone management. ·       Stress significantly impacts hormonal balance and overall health. ·       Reprogramming the nervous system can alleviate stress and improve health. ·       Nutrigenomics plays a vital role in personalized nutrition. ·       Sulforaphane is a powerful compound with numerous health benefits. ·       Diet should be tailored to the individual, not a one-size-fits-all approach. ·       Genetic testing provides valuable insights for health optimization. ·       Managing stress involves rebuilding mental constructs that generate it. ·       Investing in genetic testing is a one-time opportunity with lasting benefits.    Chapters 00:00 Introduction to Nutrigenomics and Personalization 02:49 The Role of Genetics in Nutrition 06:01 Systems Biology Approach to Health 08:55 AI in Nutrigenomics and Personalized Medicine 11:51 Case Study: Hormonal Balance and Genetics 14:59 Future Directions in Genetics and Health 23:35 Understanding Hormone Replacement Therapy 26:16 The Complexity of Hormonal Pathways 28:26 The Role of Stress in Hormonal Balance 30:22 Reprogramming the Nervous System 32:37 Nutrigenomics and Personalized Nutrition 36:27 The Power of Sulforaphane 39:04 Exploring Genetic Testing for Health Optimization To learn more about Annelie Smith:Email: annelie@3X4.io   Website: www.3X4Genetics.com   Reach out to us at:    Website: https://gladdenlongevity.com/     Facebook: https://www.facebook.com/Gladdenlongevity/    Instagram: https://www.instagram.com/gladdenlongevity/?hl=en     LinkedIn: https://www.linkedin.com/company/gladdenlongevity    YouTube: https://www.youtube.com/channel/UC5_q8nexY4K5ilgFnKm7naw    

This year, I made four of the hardest decisions I've ever made in my subscription box business. Not because I didn't know what to do. I actually knew for quite a while. They were hard because each one required letting go of something I'd worked incredibly hard to build. I rebranded my subscription box. I migrated to an entirely new platform. I closed my warehouse. I handed fulfillment over to a third-party logistics company. Looking back now, I can tell you with complete confidence every one of those decisions made my business stronger. If you're building a subscription box business, here's what each change taught me and why sometimes profitability requires making the hard call. 1. I Let Go of the Thing That Made My Box Famous For years, my subscription was known as the Monogram Box. Personalization was what made it special. It was also what was keeping the business from growing. Every personalized item had to be completed by my team before it could ship. That meant every box depended on us physically touching every order. As much as subscribers loved it, personalization created a ceiling on how efficiently we could operate. Eventually I realized the very thing that had helped build the business had become the thing limiting its future. Changing the brand to StyleBox wasn't about cutting corners. It was about removing a bottleneck so the business could become more profitable and scalable. Ask yourself: Is there something in your subscription box you're holding onto because your subscribers truly value it, or because you're afraid to change it? Those aren't always the same thing. 2. I Finally Moved to the Platform I Recommend to Everyone Else Inside Launch Your Box, I recommend Shopify and PayWhirl because I've seen how much simpler they make running a subscription business. Yet my own business was still operating on a different system. At some point I had to ask myself why. Migrating active subscribers is intimidating. You're moving customer accounts, payment information, billing cycles. There's a lot that can go wrong. But staying where I was meant choosing ongoing complexity. Today, my business is running on a platform built to scale instead of one held together by plugins and workarounds. Sometimes the temporary discomfort of change is worth the long-term simplicity it creates. 3. I Closed My Warehouse For years, the warehouse represented success. It was tangible proof that I'd built a real business. But it also came with rent, utilities, payroll, equipment, inventory carrying costs, and all the overhead that comes with maintaining a physical space. When it came time to liquidate inventory and close the warehouse, I realized I wasn't just letting go of a building. I was letting go of an identity. The truth is, the warehouse had served its purpose. Holding onto it wasn't helping my business anymore. It was simply expensive. One of the hardest lessons in business is understanding sunk cost. The money has already been spent. The only question left is whether keeping something continues to serve your business today. 4. I Handed Fulfillment to a 3PL Removing personalization, migrating platforms, and closing the warehouse made it possible to move fulfillment to a third-party logistics company. Was I nervous? Absolutely. When you've packed thousands of boxes yourself, handing that responsibility to someone else feels incredibly personal. But I discovered control isn't the same thing as quality. The right fulfillment partner doesn't lower your standards. They help you maintain them while giving you back your time, your energy, and your capacity to grow. Today my business is leaner, more profitable, and far more sustainable because I stopped believing I had to do everything myself. At first glance, these seem like four completely different decisions. But they all came down to one question: Was I making decisions that protected my business or decisions that protected my comfort? Growth often requires letting go of something that worked in order to make room for something that works even better. What's the Hard Decision You're Avoiding? Maybe it's changing platforms. Maybe it's raising prices. Maybe it's removing an expensive product from your box. Maybe it's outsourcing something you've always done yourself. Sometimes the next level of profitability isn't about doing more. It's about finally making the decision you already know needs to be made. Join me in all the places:     Facebook Instagram Launch Your Box with Sarah Website  Are you ready for Launch Your Box? Our complete training program walks you step by step through how to start, launch, and grow your subscription box business. Join the waitlist today!

There are roughly 100x more people who use code than who can write code. As code that “just works” becomes easier to generate, this group may be the biggest prize of all — if you can get the agentic interface right.A key trend we have been tracking over at AINews is the absolute explosion in Codex usage this year, with MAU now up >10x from Jan 2026. Less than two weeks after their July 9th launch, OpenAI said ChatGPT Work and Codex had reached 10M users combined (as we cover in the pod, Codex now powers ChatGPT Work, so all ChatGPT Work users are now users of the Codex harness, even if they aren't traditional engineers) — showing the early innings of what happens when you graduate from coding agents to knowledge work agents:We've been calling out how coding agents are “breaking containment” to do everything else this year to power every other part of knowledge work - and it started with the org chart, with a major reorg last month that amounted to two of Codex's most prominent leaders, Greg and Tibo, taking responsibility over product and ChatGPT specifically, completing a “Superapp” consolidation cycle first discussed in March.With these updates Codex is no longer just a coding tool. In June, OpenAI said knowledge workers already accounting for roughly 20% of Codex's user base and growing more than 3x as quickly as developers. A product dedicated for knowledge workers was being pulled out of the Codex team.However, knowledge work has a different set of problems and environments than coding. For decades, knowledge work has been scattered across different primitives like documents for writing, spreadsheets for analysis, slide decks for communication, and specialized applications for everything else. ChatGPT Work now enables users to work across every primitive with agents. Instead of opening an application and manually operating its features, the user can describe an outcome and collaborates with an agent that can assemble the tools, context, and artifact needed to reach it.From building no-code products at Airtable to leading Productivity Engineering at OpenAI, Akshay Nathan has spent much of his career trying to make the power of software accessible to people who do not write code. In this episode, Akshay joins swyx and Vibhu to unpack the launch of ChatGPT Work, why Codex unexpectedly took off among non-developers inside OpenAI, and the company's broader plan to bring useful agents from software engineers to knowledge workers and eventually everyone.We go deep on the shared agent harness behind Codex and ChatGPT Work, why OpenAI brought the experiences together without making them identical, and how persistent computers, artifacts, Sites, plugins, memory, and sub-agents are changing what people can delegate to AI. Akshay explains why some teams are replacing decks and spreadsheets with interactive websites, how agents can gather context across code, Slack, documents, and local files, and what OpenAI learned from personal-agent products like OpenClaw.Side note: also don't miss Abhihek's sandbox track keynote at AIE, which now powers a lot of the sandboxing for ChatGPT Work… and yes was also broken by an unreleased OpenAI model in the recent HuggingFace incident.Akshay also reflects on how AI is transforming product development itself: why more people will become generalists with a specialty, why ideas and taste become the bottlenecks when almost anyone can build, why LLMs still struggle to generate genuinely grounded new ideas, and why teams must distinguish increased motion from actual progress.We discuss:* Why Codex unexpectedly took off among non-developers inside OpenAI* Why employees felt like using Codex gave them a new superpower* The product insight that led OpenAI to build ChatGPT Work* Why Codex and ChatGPT Work share the same underlying agent harness* How their UX, Git visibility, artifacts, and sandboxing defaults differ* Why OpenAI merged its agent experiences instead of building separate products* How AI is blurring the boundaries between engineering, design, strategy, and operations* Why OpenAI wants the default model configuration to work for most users* When power users should use deeper reasoning, Ultra, or multi-agent modes* Artifacts, agentic spreadsheets, and creating high-fidelity work products* Why interactive Sites may replace decks and spreadsheets* The challenge of designing a simple interface for an agent that can build almost anything* Why users should retry tasks that models could not handle three or six months ago* How AI can gather context for performance reviews without replacing human judgment* The OpenAI automation that turns internal Slack and document activity into memes* What reaching ten million ChatGPT Work and Codex users means for the product* How OpenClaw inspired persistent environments, scheduled tasks, and personal agents* Using ChatGPT for financial planning, budgeting, workouts, meals, and household management* The design tradeoffs behind sub-agents and how much of their work users should see* ChatGPT memory, Chronicle, and long-term context* Why AI may make more people generalists with deep specialties* Why ideas and taste become more important when almost anyone can build* Why LLMs still struggle with the instruction “bring me new ideas”* Measuring productivity through quality at-bats instead of commits, tokens, or pull requests* The critical difference between AI-generated motion and meaningful progressAkshay Nathan* LinkedIn: https://www.linkedin.com/in/akshaynathan/* X: https://x.com/akshaynathan_Timestamps00:00:00 Introduction and Bringing the Power of Code to Everyone00:01:33 Joining OpenAI and Preserving a Startup Culture00:02:40 What OpenAI Learned from Enterprise AI Adoption00:05:28 Why OpenAI Built ChatGPT Work00:07:17 Codex vs. ChatGPT Work and the Shared Agent Harness00:12:07 Why OpenAI Merged Its Agent Experiences00:16:24 Models, Reasoning Levels, and Choosing the Right Default00:20:26 Artifacts, Agentic Spreadsheets, and Model–Product Collaboration00:24:22 Why Sites Could Replace Decks and Spreadsheets00:30:08 Designing an Agent That Can Build Almost Anything00:34:28 From Developer Agents to Knowledge Work—and Everyone00:36:07 Power-User Advice and AI-Assisted Performance Reviews00:40:41 OpenAI's Internal AI Memes and the Ten-Million-User Launch00:44:39 OpenClaw, Personal Agents, and ChatGPT as an Operating System00:50:24 Sub-Agents, Ultra Mode, and How Much Control Users Need00:54:39 ChatGPT Memory, Personalization, and Chronicle01:00:19 How AI Is Reshaping Product Development and Tech Roles01:03:15 Ideas, Taste, and Why LLMs Struggle to Generate New Ideas01:04:42 Measuring Productivity, Quality At-Bats, and Motion vs. ProgressTranscriptIntroduction: Akshay Nathan, ChatGPT Work, and the No-Code ArcSwyx [00:00:00]: We're here in the studio with Akshay from OpenAI. Welcome.Akshay Nathan [00:00:07]: Thank you.Swyx [00:00:08]: And with our trusty co-host, Vibhu. So you recently launched ChatGPT Work. You lead Core Product Engineering. It's been a long journey, into all this. I find it very interesting that you started with no code or low code, with Walrus and Airtable. And to some extent, ChatGPT Work is like the super app of super apps of, well, here is the ultimate no code. You just write a prompt.Akshay Nathan [00:00:32]: Yeah. It's funny how things come, full circle. I think for a long time in my career, I started my career working consumer fintech, but then after that, like, there's this hypothesis that, the things that we were able to do with code, like, as engineers, like, if we could bring that to many more people in a more, accessible way, then that would be truly magical. We were working on a startup. It's funny, like, before LLMs, before vision LLMs, on how to do automated testing with AI. It was just kinda jank, back then, but doing what we can, and then worked at Airtable for a while on the same thesis that, like, if we can bring a database or the primitives behind a database to people, that'd be really useful to them. But once LLMs came onto the scene, it became clear that, this was the missing piece, like, the missing technology required to, like, bring the magic of code to everyone without them having to know what's going on underneath the hood. And so, like, I think this launch and a lot of the stuff that we've been up to is, like, the manifestation of that.From Walrus and Airtable to OpenAIVibhu [00:01:33]: How was stuff when you joined? So you joined OpenAI 2023. Now we've got, so much more stuff, so ChatGPT, Codex app, ChatGPT Work. Have things changed?Joining OpenAI and What Hasn't ChangedAkshay Nathan [00:01:44]: I think the more interesting thing is how things haven't changed. Like, one, I joined I remember when I joined, it was, like, five hundred people. One thing I was worried about was, like, I was looking for something, more early stage and, like, was it gonna feel startup enough? And I joined, and I was like, “This feels even more startup-y than I could ever imagine.” And, like, that really hasn't changed even till now. I think the, like, level of, like, bottoms-up ambition and, like, the ability of anyone to, like, do anything or have an idea and ship it is really cool. But on the, like, mission side, I think what was really compelling to me is this mission of, bringing frontier intelligence to everyone. Like, building AGI and then bringing it to everyone. And, I think acknowledging back then that, like, that vision is gonna, not be a linear progression. Like, we're probably gonna, like, try different products and have different things that succeed and don't. But the vision has stayed the same, and the mission has stayed the same, and we're starting to see the pieces, fall together, and that's really cool.Enterprise Lessons: No One-Size-Fits-All AISwyx [00:02:40]: You worked on Enterprise. What A lot of people never touch ChatGPT Enterprise. What is something that you learned from there that you're bringing into your work now?Akshay Nathan [00:02:52]: I think how there's no one-size-fits-all solution in Enterprise. I remember in the early days of ChatGPT Enterprise, like, when we talked to customers and, like, everyone. That was, like, when I think it was a year after ChatGPT was released, and everyone was so excited to bring, AI into their enterprise. And, there were all these teams being stood up. It was, like, the AI deployment team with, like, these enormous budgets. And if you asked anyone, like, what were they excited about? Like, what were they excited about solving? Like, at first, you'd get, like, kinda like the baseline answers of, like, “Yeah, we have all this context and data and all this stuff.” But then if you ask them, like, “What was, like, a discrete use case that, like, they want AI to enable in their workplace?” You get such a different, like, variance, like, explosion of, different types of answers. And it's interesting, like, you using, like, these models and these products, you have this box, and you can say anything to it, which is the magic. But it'on the flip side, it also means that, like, you don't know what to do with it. And in Enterprise, I think a big part of that is, like, meeting the users where they are, like, what use case were they trying to solve, and then teaching them how they can use AI to, like, gain leverage there.Swyx [00:03:56]: Do you meaningfully differentiate that from forward-deployed engineering?Akshay Nathan [00:04:01]: I think there is the go-to-market side of it and then there is the product side of it. I think you need someone on the product side. And I think, like, however good we get at FDE motion, like, I think at the end of the day, if we have a user who's, like, looking at their computer or looking at their phone, like, it's our job in the product to, like, be enabling them and showing them where to go. So we're really excited about that.Vibhu [00:04:24]: Do you think there's been changes, over the past three years of adoption? So there have been, step function changes. You have reasoning models and whatnot. Is there still the same problems of Enterprise has black box, don't know what to do with it, or have things changed?Adoption, Agents, and the Next 10x MarketAkshay Nathan [00:04:39]: We're seeing now that, like, there's this huge uptake, right? Everyone is extremely excited about it. It feels like, many people are, millions, hundreds of millions of people are using ChatGPT. They understand, like, how generally to work with AI. But then, like, every time, like, a new capability gets unlocked, so now, like, we're seeing with agents, like, there is probably a contingent of, like, early adopters still who, truly get it, who are like, “ we you can do anything. You just have to make sure the right context is there, it's connected to the right tools, and that you are supervising it, but, like, anything is possible.” But then there's, like, this, like, 10x or 100x bigger market where, like, they don't yet get that, or they don't yet see that. And so I think that's the next stage here. So to answer your question, like, I think the adoption is there and growing fast, but I think the opportunity is, like, far bigger than that. That's where we wanna play, especially with ChatGPT Work.ChatGPT Work, Codex, and the Super App MergeSwyx [00:05:27]: Yeah. well, let's, let's skip ahead to ChatGPT Work. only, like, a month ago or so, announced. what was the decision process that led into it? there was this, overall merging of the super app. Is that what we're officially calling it? you deprecated the browser as well. Just, summarize your last, like, couple months of working on this thing.Akshay Nathan [00:05:50]: Yeah. It feels like forever now, but it's only been a few months. I think maybe the one, impetus that, like- Is most salient is when we release Codex, or even internally had Codex, like, it was really surprising to us, I think we recently put out some stats on this, that there was this, like, real inflection of, like, adoption among non-developers at OpenAI. And, I, through this product development process, like, would go to, like, these UXR sessions to talk to people internally. And the thing that stuck out to me is, like, one, like, you go talk to, like, strategic finance or marketing or whatever, and they're all using Codex for, their use cases. That part's cool, but the thing that really stuck out to me is how proud people were that they were using Codex. Like, how, likeSwyx [00:06:34]: It's like, “I'm not supposed to be using it, but I am.”Akshay Nathan [00:06:36]: It was that. It was, like, that they were, early to this, like, new thing, but it was also this thing of, like, they felt like they had a superpower, right? And, what we recognized then is that, like, the power of Codex, the power of agents, like, we already had this massive distribution base of people who have, come to know and love ChatGPT. Like, how do we show that to them? Like, how do we bring it to them? Which is, like, a hard product problem, and it's, like, a tricky thing, right? There's many ways you can go about it. And so that's what we called the Merge and the Super App over time, and ultimately launched it in ChatGPT Work, is how do we do that? But it came from that initial realization that, like, the power was not only for developers, like, much earlier than probably even we thought. Like, it could be extended to everyone.Swyx [00:07:17]: How do you see the products differently? So, like, who is it for, right? So Codex started out even CLI, then app. Now there's a merge of ChatGPT Codex and ChatGPT Work, so is it the opening for the average user, for enterprise, for work? How do you position it?Akshay Nathan [00:07:36]: I think we want to get it to position it for if you're doing work-related things, for lack of a better word, right?Who ChatGPT Work Is ForAkshay Nathan [00:07:42]: I think productivity is what, like, the pillar that I support. Like, that's the name of the team. And the reason for that, the reason we call it productivity and not, like, enterprise or, like, work or something like that, is because there's also personal productivity, right? And, like, I think ChatGPT Work is I've seen people do things in their personal lives that you wouldn't classify as, like, work technically, but, like, these agents are, super capable for. Like, one recent example that someone posted about, on our Slack is, like, someone had, like, a missed package, like they didn't receive it, and then they got, like, the picture of it, from Amazon or whoever the courier was, and they, like, asked ChatGPT Work to, like, find out where that package is. And, like, the agent, is extremely tenacious and, like, took the image and, like, looked at a bunch of, like, listings around their neighborhood and figured out exactly the apartment complex in which the package was, like, gave them some information. And so, like, I think there's all these things that, like, you, work-related or productivity-related things, I think that's what we want the product to be. You asked about Codex. I think we think Codex is, a durable brand, but we have a principle that, like, the user we don't want a user to get stuck in a tab or an experience where they don't get the power of the product. And so, like, everything that you can do, in the Codex portion of the product on desktop, you can do in ChatGPT Work and vice versa. But we made some opinionated product decisions on, like, how much of the Git state, if you're in a Git repo, do we wanna expose to the end user? Or how much do we wanna make the experience of seeing the agents thinking, like, diff forward so that you get exposed to the diffs out of the box. And then, like, on the safety side, like, how do we wanna think about, like, sandboxing and making sure that we have the right defaults in one state versus the other? So, there's, like, some opinions that go behind that, but we do want We don't want the user to need to choose which experience they're in.Swyx [00:09:26]: That is a good goal for AGI, right? Like, people don't want, like, to hide to choose what version of AGI they want. They just want the AGI to decide for them. can I get an answer or, like It's not super clear to me. Is the Codex harness and the ChatGPT Work harness the same? Is it just UI affordances, or are there prompt level or even deeper differences?Shared Harness, Different UX: Codex vs. WorkAkshay Nathan [00:09:49]: So the harness is the same. The harness is shared. on In both of the products, we made improvements to the harness to make it good for knowledge work, especially as it relates to plug-ins or computer use or artifacts. You get that power regardless of which experience you're in. On the UX side, there's opinionated takes that we have when you're in Codex mode, what the UX should be how the UX should behave, and some stuff around the sandbox like I mentioned, but the underlying harness and capabilities should be the same.Swyx [00:10:16]: I'm just kinda curious. Maybe we can, -- Is there a query that we can run that would look different in the two modes?Akshay Nathan [00:10:23]: Yeah. I tried to create, like ask it to create, like, a retirement calculator spreadsheet or something, in both modes. And then in Codex mode, you might have to be in a repo for this, but you'll see, like, the diffs of, like, the sheet that it's creating and stuff like that, and the file edits. But in Work you won't be able to see that.Swyx [00:10:42]: I think that's, that's super clear. And then also the other thing I wanted to dive into was your, the productivity team. what else is there? first of all, what are the top-level teams other than productivity? Isn't productivity everything?Productivity Teams and Core ChatAkshay Nathan [00:10:55]: SoSwyx [00:10:55]: Science?Akshay Nathan [00:10:55]: We have a team focused on ChatGPT. Like, the core chat experience, for consumer, which is like, not, I think all productivity. Like, there'People are using ChatGPT every day for search to, figure out how to write messages to loved ones, to think about, how to, like, learn a new topic, et cetera. And so there's so much more inside to create images. And there's so much more in chat that, the hundreds of millions of users are using that warrants, like, a very dedicated effort. And there's teams focused on enterprise and infrastructure and API and stuff like that, so.Swyx [00:11:33]: I will bring it up.Retirement Calculator Demo and Git-First UXSwyx [00:11:34]: Yeah. So I have them both running. This is ChatGPT Work. There's a Codex version here. I picked “Five Little Ducks” song, so this will take a while.Akshay Nathan [00:11:43]: Huh.Swyx [00:11:43]: I think we'll just keep it in the background and, as they finish, we'll look into some of the differences.Akshay Nathan [00:11:48]: Yeah. But immediately, I think if you flip back to the Codex version you'll see that,Swyx [00:11:53]: That it assumesAkshay Nathan [00:11:54]: Like theSwyx [00:11:54]: It assumes Git. Yeah. Yeah.Akshay Nathan [00:11:56]: The, like, dynamic island assumes that you're in a Git repo. And you might miss some stuff because some of it is, like, in the actual chain of thought with those changes and how we display that, but yeah.Swyx [00:12:07]: Is there an unintuitive like, is there a thing that you wanted to ship and then you got feedback, and you were like, “No, let's not do it?” Like, what's the thinking behind that?Why Merge the ExperiencesAkshay Nathan [00:12:14]: In, ChatGPT Work?Akshay Nathan [00:12:17]: I think one direction we could have gone with this is, like, keeping the experiences, like, completely separate. So it's like, whySwyx [00:12:22]: Different apps.Akshay Nathan [00:12:23]: Exactly, like different apps or even in the same app, like different, completely different experiences. Like, why merge it all? Like, what is. Codex, people love. Like, why bring these products together? And I think the intuition here is that, like, all of our jobs are, like, changing dramatically with AI. Like, for, like, every few months, like, I feel like I wake up, and I'm, like, doing a completely different thing than I was doing a few months ago. And my hypothesis here is that, or I should say our hypothesis is that, like, part of what we're, we're building, this technology is giving people leverage. Like, the things, maybe it's the more mundane parts of your job or parts that, like, if you were able to automate, you'd be able to share more ideas faster or whatever, like, you're able to do now. And because of that, like, that might blur the lines between someone who's, like, only writing code or creating strategy docs or, planning events or, helping with marketing or doing podcasts or whatever, right? And so, like, these things are gonna get blurred over time. And so, like, trying to draw a hard boundary based on, like, the who you are is gonna be, is gonna be tough. And, like, we should enable users to choose, but we shouldn't box them in. And so a lot of the work that went in here, like, keeping the primitives the same, like for example, plugins are, like, unified across, this product and ChatGPT and the cloud, was because of that. It's this thesis that, like, eventually things are gonna come together and we don't wanna be Like, we wanna be prescriptive about when to be in either experience, but we don't want to box anyone in.Swyx [00:13:45]: I wonder if there's users who are very tuned to the old ChatGPT harness that is effectively now replaced by the Codex harness. I can't imagine what that was, but maybe they're more the more conversational side. Can you compare and contrast the two harnesses? ‘Cause only you've seen it.Akshay Nathan [00:14:02]: Yeah. I think ChatGPT, the existing harness, like, still exists today. Like, it exists in this app,Harness Engineering: ChatGPT vs. CodexSwyx [00:14:08]: The classic, right?Akshay Nathan [00:14:09]: TheVibhu [00:14:09]: You just start a new chat, and you don't go under Work, right?Akshay Nathan [00:14:13]: Yeah. If you startVibhu [00:14:13]: SoAkshay Nathan [00:14:14]: A new chat and go to chat, then you're, you're talking to ChatGPT with the instant model.Vibhu [00:14:16]: Oh, we can technically do another. But on instant.Swyx [00:14:21]: Yeah. So this one's not gonna code or it's gonna be in line. It's on a in line in a sandbox.Akshay Nathan [00:14:26]: It'llVibhu [00:14:27]: Oh, that's coolAkshay Nathan [00:14:27]: We try to push you to go to Work if you're creating a spreadsheet. Yeah, but this isSwyx [00:14:30]: And this is a router decision? Sorry. Is it a router decision?Akshay Nathan [00:14:34]: This is the decision that, the model is making, and then, like it sees that you're able to. or you're trying to do something that would be better served in Work mode. But I think your question was like, what are the advantages of, like, the chat, like ChatGPT chat harness?Swyx [00:14:48]: It's more broadly, like, I wanna, do an oral history of harness engineering. Right? the ChatGPT harness lasted us from, let's call it the ‘01 era, until now, and now it's being replaced by the Codex harness effectively. And they're, they're overlapping somewhat, but I'm curious what changed if there is.Akshay Nathan [00:15:10]: My perspective on this is, like, there's, there's, there's there's like a constant process of, like, divergence, convergence, divergence, convergence. And in chat, like, many of the use cases I was talking about before, like, search or learning, I think we're, we're really optimizing for latency and optimizing for personality and, like, different things that, over time, like the product The reason people love ChatGPT is because we've been optimizing for those things and working on them for so long. Codex, what we learned was that, like, if you give the agent access to this infinitely flexible environment as a computer, it can do really powerful things. And so when we think about, like, okay, well, for knowledge work, like, what is which mode should we choose? It was like it felt more natural to us to bring that to this, like, computer environment and, maybe abstract some of the details of this computer away from users who might not be used to that, but, like, give them that same power. But ultimately, I think that we want the power in all places, right? We wanna meet people where they are. So I'm sure there'll be work down the road in order to get things to be, equivalently capable in all scenarios. But it's just a question of, like, what we've been focusing on the product on historically and what we're focusing on now.Models, Defaults, and the Reasoning SliderVibhu [00:16:24]: I think alongside that, outside of just harness and when to use Codex, ChatGPT, or Work, there's also the new models you've released, right? any guidance there? So people love to min-max what to use, like only use Terra on high reasoning versus, for this, you wanna use Sol here, ignore all theseAkshay Nathan [00:16:44]: There's 32 options.Vibhu [00:16:46]: But, that being said, for people that are expanding, so, productivity trying stuff for work that don't have the breakdown of what all this is what's, what's the advice, right?Akshay Nathan [00:16:59]: Well, I think before the advice, like the first thing is, like, none of this would be possible without these models. Like, the, I think you asked earlier, like, what was, like, the inspiration for work and, like, early on, like I mentioned, like, what we were seeing with Codex, but that was also because the models were getting infinitely more capable. That's happening again. I think it's like another step function jump now. And to answer the question on advice, like we want this default to be the best possible. Like, we wanna be opinionated about the default, and so we've we've chosen a default that we think is gonna be the best for everyone. And, we have for power users options under the hood. We could One could argue that there might be too many right now, and we're, working on simplifying it. But you can extend, the reasoning level, and you can change between the different model classes if you need to, but the default should be the best for most use cases. So my advice to most people would be to stick to that. And then, if you reach a situation in which you think that you could, you wanna try, a different configuration, if you're not seeing either the efficiency on the cost side or the quality on the intelligence side, then you can change the defaults and see if you can get something better. But we think that the default should be good enough.Swyx [00:18:09]: I have, I'm just gonna run something by you since you have way more experience than me. I've recently been doing Sol Lite but with goal, with the idea that the goal augments the reasoning effort, but with more terminations and turns.Swyx [00:18:24]: Is that a good way to think about it as opposed to Sol Ultra or Sol, Extra High?Akshay Nathan [00:18:29]: Yeah. It's hard to say becauseSwyx [00:18:31]: Yeah. It's like an interaction effect.Akshay Nathan [00:18:33]: exactly. It's like there's a preference on, for you as an individual, like how do you like to collaborate with the models? Like how many of those like terminations, as you call them, do you want where, you can steer or make sure that it's doing the right thing?Akshay Nathan [00:18:46]: I think generally people should try whatever works for them. I think that like using Ultra or the like multi-agent setups are best for like when you have like tasks that are either incredibly complicated, like open explorations or very paralyzable. I think even for tasks using goal, I think is best for tasks that you'll be able to make consistent progress in a way that's verifiable over time. But I think for most tasks, they don't fall into either of those buckets. And so like at least when they're starting, and so that's why I think the best first step is like trying it with the default configuration and then seeing like where you wanna go from there.Swyx [00:19:29]: Right. You guys worked on a slider, which is super helpful for reducing the amount of panic.Vibhu [00:19:36]: It's nice on mobile at least. There's a nice slider there.Swyx [00:19:38]: It's nicer.Vibhu [00:19:39]: I haven't tried it.Swyx [00:19:40]: So you have the advanced view there, but if you click advanced view. Yeah.Vibhu [00:19:44]: Ooh, it's just a nice slider. Yeah.Swyx [00:19:46]: Very pretty, very colorful.Akshay Nathan [00:19:48]: Yeah. The idea was here was like reduce it to like one dimension even though there's multiple dimensions, right? Try to project it onto a single dimension for the user. Like, something from that represents like, speed and efficiency on one side and then like quality and thoroughness on the other side.Artifacts, Spreadsheets, and the Work LaunchSwyx [00:20:04]: I am just puzzled that it uses Sol so much, like the lowerVibhu [00:20:07]: NoSwyx [00:20:07]: Grounds I would've usedVibhu [00:20:08]: I think the slider, if I'm not mistaken, isSwyx [00:20:09]: Terra.Vibhu [00:20:10]: Oh, it is.Swyx [00:20:11]: Yeah. See? So they preset Terra to only be the light one. But like I think a lot of people would more people should use Terra. One, because Sol keeps running out of capacity.Vibhu [00:20:22]: I'm the reason. Here's ten minutes of ourSwyx [00:20:24]: There you goVibhu [00:20:25]: Retirement calculator.Swyx [00:20:26]: Oh, that's the Excel thing working for you.Vibhu [00:20:28]: This is,Swyx [00:20:28]: Oh my God. Look at thatVibhu [00:20:28]: This is work, and then Codex is still cooking, so we'll get back into it. I think it'll be interesting to see the thought process, the reasoning, and also, this is eight minutes on work. Codex is still cooking.Swyx [00:20:41]: Yeah. And by the way, so I've, do Gabriel Chua? He's part of the OpenAI Singapore team. He showed me this, and I was like pretty shocked that this looks like Excel. It edits Excel files. You never paid an Excel license, right? Like, but somehow this is like workable and it's agentic Excel.Akshay Nathan [00:21:01]: Yeah. one of the big like pushes that we made for this launch was like artifacts, right?Akshay Nathan [00:21:05]: Like both on the model side, like I think if you compare this with GPT-5.5 and GPT-5.4 before that, you'll see that there's been pretty dramatic improvements in the quality of these artifacts and then also on the product side.Vibhu [00:21:16]: The UX side is also crazy, like hosted sites and whatnot. No longer needing to host your own little webpage, like itSwyx [00:21:23]: Oh, I have a story about that. I can do, a separate thing. I'll need to take the visuals here, but we-we'll, we'll cut to that later. Was there co-training, because you were moving making this big move and you launched GPT-5.6 on the same day as ChatGPT Work? Was there influence between the model training teams and the harness teams, or did they did the launch dates just happen to line up the same day?Akshay Nathan [00:21:46]: I think the we collaborate heavily with the research teams, and I think that's like one of the most magical parts of the job, like the most fun parts of the job. But yeah, just using artifacts as an example. Like, a lot of what you're seeing, like underneath the hood, there's a lot of work that went into making sure that like, we had the right infra to be able to train the models to get better at this. And then on the product side, like had the right experience for users to be able to collaborate with the model on an artifact like this. In fact, like this whole viewer, like the intuition here is that like, it's not necessarily that you wouldn't need an Excel license. This is stage one, right? Like, this is probably not what you meant when you're like making a retirement calculator.Vibhu [00:22:24]: Yeah, you can iterate very easily. Yeah.Akshay Nathan [00:22:24]: You wanna iterate and like when you're seeing it, and if this thing is high fidelity to like what you would see in or what your coworkers would see if you were to send this to Sean, like that I think makes it so easier and makes you trust the product in terms of iteration.Vibhu [00:22:39]: When you say coworkers would see, do you see a multiplayer, multi-team collaboration with artifacts? Any things you guys think about that?Multiplayer Artifacts and CollaborationSwyx [00:22:46]: You can already share it, right?Akshay Nathan [00:22:48]: Yeah. It's inter It's something that, we're actively thinking about. one thing that, we've noticed internally without talking too much about the roadmap is that like there's many times when someone will ping me about something, and I will ask ChatGPT Work the question, and then I'll ping them back the answer.Akshay Nathan [00:23:04]: And then I'll be thinking likeVibhu [00:23:04]: Like the simplest would be, the three of us are just all on one hosted.Akshay Nathan [00:23:07]: Exactly. And I'll think about like was I required in this loop or and then maybe it was, rephrase like what they were asking or pulled from certain context or whatever. But like, when I gave them back the answer, that process was also lossy, right? Like I gave them just like my interpretation of what ChatGPT Work cooked up. But like underneath the hood, there's so much context like in the rollout and stuff that could be interesting.Vibhu [00:23:28]: Yeah, it'sSwyx [00:23:28]: So like the answer was preemptively respond to every inbound request?Akshay Nathan [00:23:33]: No, it was just like literally like this is what I do sometimes as my job.Swyx [00:23:36]: I know you copy-paste and then you're just a message forwarding serviceAkshay Nathan [00:23:39]: Yeah. Yeah, exactlySwyx [00:23:39]: From AI to AI.Vibhu [00:23:40]: But I think it's interesting, right? It helps people understand the capability of what you can ask and delegate that oftentimes people don't realize until they try or someone shows you, and then you're like, “Oh, okay. Okay, I see.”Swyx [00:23:52]: I think it's als there's also like a, light security issue, where like you're the permissions layer. Like yes, I could query everything that you query, and I could get an automated response, but maybe I'm not supposed to see it. And that there's no way I would know because I'm not supposed to know what I don't know.Akshay Nathan [00:24:07]: Especially as like, with ChatGPT Work, we're, we're asking you to connect your plug-ins and, it's pulling from your local files and stuff like that. Like the amount of context that the agent has access to is like- Deeply personal and like that's something I think we need to preserve, so that'll be definitely a challenge.Swyx [00:24:22]: There's Excel, there's PowerPoint, there's Docs, the, grand trio of work. What other formats of work do you think about? like you worked on Airtable. Is there a future where there's like OpenAI Airtable? Like what does that look like if you ever ended up doing it?Akshay Nathan [00:24:41]: It's a really good question. I think,Formats of Work: Sites as Knowledge ArtifactsAkshay Nathan [00:24:43]: one that you didn't bring up was Sites, and I think that wasSwyx [00:24:46]: SitesAkshay Nathan [00:24:46]: A core part of this launch. There's one side of Sites that I think people commonly talk about, especially on Twitter and stuff or X, of like, this like prototyping tool. And like we saw that happen with this launch even. The model slider that you guys were referencing earlier, like that was developed almost fully in a Site. Like, the collaboration between design and engineering and product on that was like on a site where we play with, the affordance and figure out how it feels and all of that. But the other aspect that I think is a little bit less talked about is like Sites as like an artifact for knowledge work. I was talking to someone the other day who's on like our corporate finance team, and like we were mentioning how like now when they have these reports that they're, they're working on as a team month to month, historically those things were in slide decks and in spreadsheets, and now they're just in Sites. And like Sites is the mechanism that they collaborate across the team. And the reason is ‘cause it's like, it's like somewhat higher bandwidth. Like, at these tools like PowerPoint and Excel are like infinitely flexible, but at some point you reach the boundary of like either as a human you may not know how to use some feature or something, or the product itself doesn't support it. But with a site you can do anything. You ask for anything and you can get that. once people see that magic, I think it's been really valuable.Swyx [00:26:02]: Yeah, let me show you my case study. this involves all the hot topics including ChatGPT Work, but also GPT-5.6 token billionaires and token maxing and Sites and auto research. I'm a fan of this game called Strata. It's, it's like a little board game that youSites, Auto Research, and Research DashboardsSwyx [00:26:17]: That you play with, physical blocks, that come on top of it like that. So over the weekend I took like thirty photos and just threw into ChatGPT. one point seven billion tokens later, out comes this site with a fully playable thingAkshay Nathan [00:26:32]: WowSwyx [00:26:32]: With 3D, block placement and everything. Because it requires physical blocks and I needed friends to train on it so they can get better, so I can play against them. But also, I could also, do things like train an AI on it and that's, thatAkshay Nathan [00:26:45]: That's your auto researchSwyx [00:26:46]: That gets into auto research. So, you want to train your own AIs, and then make sure they self-play against, each other. I need to set both AIs. So this is AI versus AI, and they're, they're gonna self-play. the AIs start out bad and then you want to define a loss function and get good. I wasn't gonna supervise all this. I was at, I was down in San Mateo, attending a conference. What I ended up doing was, auto researching and on this and creating benchmarks and that there was just way too many parameters for me to read. So I started asking it for a site, and it's created this lab, panel. Where is there a, is there a shortcut for a site that is created?Akshay Nathan [00:27:28]: You should be able to go in the sidebar to Sites, top of the sidebar. The left sidebar.Swyx [00:27:33]: This one? Oh, left?Akshay Nathan [00:27:35]: Yeah. Just scroll all the way to the top.Swyx [00:27:36]: Oh. Oh, it says Sites. Oh, there you go. Yeah.Akshay Nathan [00:27:39]: Ooh.Swyx [00:27:40]: So it create, it creates the sites. I don't, I don't think this is, it is exactly what I wanted, but let me show you what it popped up, right? Like I think as a research artifact, it is very important to communicate, exactly, what is being done. Outputs this thing which I eventually started publishing. So I moved it off of Sites because I wanted more, database and infrastructure than Sites afforded me. But this is like a research output that you can start to mess with and like try to think about like what hyperparameters are you tuning for training AIs. And like I was trying to make like scaling laws and everything and doing all sorts of like game optimization stuff. And the fact that you can just throw this up as a research artifact, like I no longer need to read ChatGPT output. I read Site output. But then there's also a huge sprawl. Like look at how long this thing is. There's so many numbers. It is pretty overwhelming, so then I have to start pruning it from there. But, it's an interesting transition from Markdown effectively that you're putting out to, you're putting out a whole functional site.Akshay Nathan [00:28:41]: I think Markdown just isn't that optimal for people to read, right? Might as well just write HTML website and I don't know. I think you can do a lot with customizing this, right? You have your skills that explain what you want. Like I noticed they're quite verbose. I don't need a lot of this information.Swyx [00:28:57]: It's very verbose.Akshay Nathan [00:28:58]: So and then the nice thing of having a site side by side is, you just iterate on what you want and what you don't, right?Swyx [00:29:05]: Yeah. I don't know if, any that triggers any stories for you of how it's run internally. Am I doing this right?Akshay Nathan [00:29:11]: Yeah. I think that this is like a workflow that we're seeing like all different types of teams use, where like the canonical artifact that was previously a deck or something is now becoming a site. And like with a site you, because it's just HTML, you can like. It's infinitely flexible. And so, if you want to give more prominence to a certain thing that like in a slide deck would, feel like it was buried, like you can do that. You can have it be like the hero image, right? And so I think that like, people are starting to see that. There's more work to be done to make these things like much more easier, easy to collaborate on. You mentioned that they're very, they're long and verbose, could be broken up. I'm sure that there's still something to do there.Swyx [00:29:53]: They're super long. Yeah.Akshay Nathan [00:29:54]: Yeah. But I think we're starting to see that like there is this aspect of this is a really interesting, format, for people to use, that's like much more flexible than what they ever had before.Swyx [00:30:07]: I think your job also comes becomes meta. You're not designing the products. You're designing a product to make products, and I'm curious how you manage that.Designing a Product That Makes ProductsAkshay Nathan [00:30:18]: I think one thing that we've been Like when we look at the UX, like that we've been thinking a lot about is how can we balance like simplicity with capability? Like if we're designing a product, like you said, that like is made to make up build other things, right? You can build so many different things. But we can't put that all in front of you because you'll get overwhelmed.Vibhu [00:30:41]: Yes.Akshay Nathan [00:30:41]: And so we had similar problem or similar challenges even Chat-with ChatGPT, but especially now, like when there's so much that can be done, I think the balance that we're constantly trying to strike is like, how can we give the user enough of a UI surface where, they can be expressive, they can tell the agent what they need, they can verify that it's using the right tools, it's pulling from the right sources, et cetera, but then it gets out of the way. And then how can we build the right system such that we can show them instead of telling them what can be done? Because so much of this is gonna be like, how do they discover the next use case and the next one after that if they really want to be super powered by the AI.Games, Private Evals, and Show-Don'TellVibhu [00:31:19]: Yeah. It's interesting. I feel like everyone also just has a different way to do it, right? I made a similar version of this same game. I didn't take any pictures of board or rule game. I threw in at goal eighteen minutes, fifty-three seconds later, a lot of tokens later, I've got a similar version. not with all the auto research and whatnot, butAkshay Nathan [00:31:39]: You gotta do all the latest trends.Vibhu [00:31:40]: And yeah, I did it with, did it with Codex, not Work, but it's interesting, right?Akshay Nathan [00:31:45]: Yeah. And this is GPT Image generating the pro avatars. Very good for game design. LikeVibhu [00:31:51]: AndAkshay Nathan [00:31:52]: A lot of game designers were like really into GPT Image for assets.Vibhu [00:31:54]: I will say like the broader takeaway probably is the reason that we do this is more so just to test the tools, right? Like, this was also a test for GPT-5.6 came out. I had done the game on GPT-5.5, right? The ability for me to no longer need it to. I had to feed it the rules. It's, it's a pretty niche game. It couldn't find how to do this on its own.Akshay Nathan [00:32:15]: Oh, yeah.Vibhu [00:32:15]: GPT-5.6Akshay Nathan [00:32:16]: It is out-of-distribution, which is why I was also very keen on testing the GPT-5.6 capability.Vibhu [00:32:21]: But, this is just as work comes out, as new things come out, these are just our side ways to test things, right?Akshay Nathan [00:32:27]: Yeah. It's some private eval. That is not this private.Vibhu [00:32:31]: But also valuable because now you can send this to your friends and I learned about this game through seeing this.Akshay Nathan [00:32:36]: It's a hard game. He's very good.Vibhu [00:32:39]: It's good to when no one is competing with you. But yes, it's a classic RL problem of like self-play, bootstrapping your game AI. yeah, you see how easily work becomes personal and personal becomes work because the thing I do for personal, it directly informs people I work with because I showed it to them. They were like, “Oh, you can do that with GPT?” Which like I imagine is the growth strategy.Akshay Nathan [00:33:02]: Yeah. The show not tell is a big piece that, I think we've we're not still not fully cracked of like, showing people all the things that they can do with the product versus like trying to teach that to them through like, articles or onboarding or whatever.Akshay Nathan [00:33:18]: So meeting them in the moment.Vibhu [00:33:19]: It's a career risk for me, because I used to be in developer relations, right? Where your job is to show, and then you're like, “What do you mean? You don't, you don't need.” your job is to tell. And then. But the product people are like, “Well, we don't need you if our product is intuitive enough.” SoAkshay Nathan [00:33:37]: Yeah. that's the magic of the models. So you can tailor the telling or the showing to like specifically what the user needs, like what they care about, what they've done in the past, exactly where they are on the adoption journey. So I think that's like gonna be a super big opportunity.Vibhu [00:33:50]: Seems easier and easier now to tailor custom showing, right? People have different use cases. As much as you said you don't wanna segment different people into different buckets, right? It's also not that hard to for people that are in different categories. But the question, is you said your team is more broadly on. What was the term you used? Productivity?From Developers to Knowledge Work to EveryoneAkshay Nathan [00:34:12]: Productivity.Vibhu [00:34:12]: Productivity. So howAkshay Nathan [00:34:12]: Which is now work.Vibhu [00:34:14]: Is it work? Is there another distribution that we're not hitting? Is there a group of people that will have something different than ChatGPT, Codex or Work? Is there more that the mass isn't targeting?Akshay Nathan [00:34:28]: I see it as like a sequencing, like. The vision is like bring useful agents to everyone. We started with like developers. Like developers historically are like early adopters that are willing to put up with more friction, set things up, et cetera. Like that's where, Codex started. I think the next opportunity is like what we call general knowledge work, all the other functions around developers. I think when you go from developers to this segment, like there's inherent challenges with like, this show not tell thing that we're talking about, making the product more understandable, bringing in new capabilities that matter more for this cohort than matter for developers, things like artifacts, things like computer use, et cetera. And then I think like the same learnings, like similarly how we took the learnings from developers and brought it to, general knowledge work, the next stage will be like taking the learnings from general knowledge work and bringing it to everyone no matter what they're doing in their lives. And we're already seeing that a little bit. Like this game example that you have is, something that's like on the border of like fun and personal life to, your professional life. I use ChatGPT Work full-time at home for everything, like for whatever I'm doing. I used it the other day to come up with a meal plan and like, save that on the like computer environment that it has and something that I can continue going back to. Like is everyone doing that yet? Probably not because the thing says work on it, but eventually, we wanna get people there.Vibhu [00:35:51]: ChatGPT life.Akshay Nathan [00:35:52]: Yeah, exactly. ChatGPT cooking. But I think there's a lot of, there's a lot of opportunity there, but I see it as like, we're, we're built we built a foundation in software engineering, and we're gonna take the same learnings that we take from software engineering to knowledge work to everyone.Vibhu [00:36:07]: Do you have any power user advice? I feel like, there's a group of people that will live it, use it for everything, stay on it twenty four-seven. And then there's a bit of a gap between that crew and people that, okay, I use it for work. I use it occasionally. Sometimes I type questions. any advice, any learnings, anything you recommend or just, takeaways that you've found that help bridge that gap?Power User Advice: Push the Frontier of ImaginationAkshay Nathan [00:36:30]: I think a couple things that I've seen is like, one, that it really helps to broaden your imagination of what's possible, and this has been a learning even for me. Like, the technology has progressed so fast that, something that, like, even three months ago, like, no way the models can do this. Like, now it's like, wow, it's like it can. Like,Swyx [00:36:52]: Give an exampleAkshay Nathan [00:36:52]: We're going through right now our, like, review cycle internally, and, people always talked about this as, like, a thing that the models are good at and like, there's a cliché of like: Okay, like, no one wants to be writing reviews and, like, we just use AI to do it. But in all seriousnessSwyx [00:37:09]: And it can evaluate it as well.Akshay Nathan [00:37:10]: Yeah, exactly. In all seriousness, before it was, like, just, like, slop and, like, I think it was helpful, but, not super productive. Now I've found that, like, the model can do a much better job than me, especially in this environment of, like, pulling context on, like, what people are up to, how they've like the things that they've done to make a difference, highlighting like, wins that they've had that, like, I might may not even have seen. It has access to, like, everything, right? Like the code, like, things that they've caught, reviews, Slack, everything. And so it's, like, incredibly powerful in that domain and, like, just like six months ago, the last time we did this cycle, like, I didn't even I tried using it, but it was not at all helpful. And this time it's been, like, incredibly helpful and, like, so I think continuing to push the frontier of imagination of what's possible, even if you tried something before, I think is maybe the my biggest piece of advice. The other, thing is, like, the more you put in, especially in this environment where, like, the model has access to everything on your computer or in ChatGPT Work, like you can create, artifacts over time and save them in your library and, like, the model will continue having access to those. Like, the more information you give it about whatever domain you're in, whether it's your life or your work, the more valuable it becomes, and it'll become valuable in, like, ways that might surprise you. Like, it might pull from context in a way that, may be proactive and that you might not even have thought about. But it needs to have access to those, to that those tools or that context first.Reviews, Agentic Search, and Context GatheringSwyx [00:38:27]: One thing I just wanna talk about the review stuff because I'm still that's a very sensitive thing and you're, you're a founder, you've managed people, you've hired people. As manager myself, I'm very reticent to put out any LLM-generated things especially when it comes to people, ‘cause it feels like you don't care.Swyx [00:38:46]: Presumably at OpenAI, people are more open to being eval rated by GPT. But are there any unofficial rules around this? Like, what's the etiquette?Akshay Nathan [00:38:57]: Oh, I think the etiquette is that, like, I would never write something via, like, well, solely via AI and, like, present it as, like, a review for someone. What I was talking about is more, like, gathering context. That's the place where it's incredibly helpful.Swyx [00:39:08]: So it's just search.Akshay Nathan [00:39:09]: Yeah, exactly.Swyx [00:39:09]: It's agentic search. Yeah.Akshay Nathan [00:39:10]: It's like agentic search, but, that you can tailor and steer much more capably than you could before, ‘cause, like, the thing is it's all there's a flywheel happening, right? Because of Codex, people are able to do, and because of ChatGPT, people are able to do so much more now than ever before. And if you're able to do so much more, it's easy to miss things as well. And so, like, I think we need to use these same tools to keep up with all the impact that people are having and understand, where we can be helpful.Swyx [00:39:39]: I think the thing, like, I run a small company, so easy to search, but at the scale of OpenAI with the amount of messages that you guys put in Slack, do you think that it misses things?Remembering What Humans MissAkshay Nathan [00:39:50]: Probably, but I think that I also miss things.Swyx [00:39:52]: Like, it doesn't matter, right?Vibhu [00:39:53]: I think sometimes it'sSwyx [00:39:53]: Like it's, as it needs to be human-levelAkshay Nathan [00:39:54]: It's all relative, right? Yeah.Vibhu [00:39:56]: Sometimes it's nice when it finds things you wouldn't, right? Like right now, my Codex system prompts, they're set up in such a way that every project I have has a secret- separate, notes MD, and it just writes learnings to there. And then the global one can pull from all these. So sometimes it'll be like: Oh, there's this project you did like four months ago. Here's a note that we had, and it randomly pulls it back into context that I would never do, I haven't thought about.Vibhu [00:40:20]: And I'm like, okay, this is quite superhuman, right? Like, stuff that would. And, it'll save like hours on chunking of stuff or find something that's already been done. I'm like, as much as it might miss stuff, I would too, but it's very useful when it finds stuff. And I have like a very, non-super engineered solution to this. It's just marked down files that get pulled whenever they want.Akshay Nathan [00:40:41]: Yeah. I have a funny anecdote about this. Like, recently gearing up to this launch, the team has been, really cooking on it for a couple months, and over that time, like there's so much conversation and chatter going on in Slack and Docs and elsewhere. And, one of the members of the team set up this, scheduled tasks, like automation to like look at everything that's going on and, like, come up with the best memes and then post it in one of our shared channels. And like, there are two cool things about this. Like, the first is, like, I think the models are, over time, like starting to become like funny.Swyx [00:41:13]: Funny. Nice.Akshay Nathan [00:41:13]: Whereas like, a year ago, like that was not at all the case. The second is, it was what you were saying, like they find things that in surprising ways that you may not have thought of and like create connections that you may not have thought of. And that really helps with like the meme generation because then you can see something that, genuinely surprises you and, is funny in that way. So yeah, that's like not like the most productive, use of this the technology, but it does it does uncover this, like this capability that's emerging, which is just like to find information that you otherwise would not know of.Launch Momentum and the 10 Million User MilestoneSwyx [00:41:43]: Talking about the launch, I think, I have pretty much said this is the most successful launch in a long time. I think even more successful personally than 5.0, and they're announcing ten million users. Does it feel different? You've been through a lot of launches.Akshay Nathan [00:41:58]: I think it feels like a culmination. Well, I think two things. One, it feels like a culmination, like I was mentioning earlier, like this like vision mission that we've been on for a long time. Like I said, we saw the magic of Codex internally, and then we're like extremely excited to bring this to many more people and to see it working, to like see us reach, the distribution goal, numbers that you mentioned, like I think that's like huge and super exciting. The flip side of that is like, there's so much more to do too. Like, that's also really exciting. Like, ChatGPT as a whole, like the this product that, everyone almost equates to AI and like loves, has hundreds of millions of users. And so like ten million is really cool, but like we need to get this to everyone. Like, we need everyone to feel this magic. And so that's the next step from here. But yeah, I think extremely pumped about how it's going so far and the opportunities.Swyx [00:42:46]: Awesome. I did want to also Because I've, I've, I've been tracking the number closely, it transitioned at some point from just Codex users to Codex plus ChatGPT Work, because they're same harness. The whole point is that you don't, you can't, count them separately. Do you have roughly a billion, ChatGPT users? Why did it just jump to one billion right away? Like, isn't that the default on ChatGPT or no?Codex, ChatGPT Work, and the Developer BrandAkshay Nathan [00:43:11]: We don't default you into ChatGPT Work if you're on ChatGPTSwyx [00:43:14]: If you're free. YeahAkshay Nathan [00:43:15]: It's also only available to paid users right now. And I think there's like a process of, educating users of what is the value of this product, having them try it, learning from their feedback, and making it better over time. But the goal is to, get as many of the people who love ChatGPT today to like feel the power of ChatGPT Work. But I think it'll be a journey.Swyx [00:43:36]: Yeah. And Codex will still be alive as a brand for the foreseeable future. And we'll just toggle between them as needed for UI stuff.Akshay Nathan [00:43:44]: Yeah, I think it's even stronger point than that. Like, I think we fully intend to like, treat developer. Like, developers have been, a core market for us for so long, and like there's, there's so much more that we can do to make Codex great specifically for, software development, and we'll continue to do that. This doesn't take away from that at all. If anything, it should increase the utility of something like Codex, because now you can move seamlessly between writing a diff to creating an artifact or, doing a search over your factor.Swyx [00:44:11]: I do wonder how much this terminology leaks to the non-technical user. Like, do they have to learn to say artifact if I want artifact? Or.Akshay Nathan [00:44:20]: It's funny, like we call it artifacts internally ‘cause that's what the teams call it.Swyx [00:44:23]: It's nice. Yeah.Akshay Nathan [00:44:23]: But like externally, like no one says that, no one calls it an artifact. But I think that people like often, like describe things, whatever they're used to, right? So if, ChatGPT Work is good at creating slides, they'll say ChatGPT Work is good at creating slides, and that's what we want.OpenClaw, Personal OS, and Persistent ComputersSwyx [00:44:38]: One big Another, it's July of twenty-six. One big thing that also happens in, for OpenAI was OpenClaw, and that's I think a lot of people's first time really maxing a agent for personal stuff, but also crossing over to work in essence same way. As far as I understand, OpenClaw is still independent, but did you go through your own OpenClaw moments? Were there any lessons you took from OpenClaw to Codex or back? Whatever.Akshay Nathan [00:45:06]: I think there's a lot of inspiration. I did go through my own OpenClaw moment. I,Swyx [00:45:10]: Yeah, tell the storyAkshay Nathan [00:45:10]: Me and my wife like set up an OpenClaw to like try to manage everything in our house. Not that there's like a ton, but it was like quite useful. We gave it a calendar. It started, creating events for us and stuff. At some point, the laptop that we were running on, it died and never got a chance to pick it back up. But there was a lot of inspiration there, like, in ChatGPT Work, in web and mobile, like you get access to this like persistent computer environment where, you can store files, and those files stay around between sessions. And the idea is to be able to enable use cases like this. one of the members of our team uses ChatGPT Work for what they used OpenClaw from before, and then feel like it has like completely transitioned, which is like, workout planning and like meal tracking. which again, it's like a work-related thing, right? It's like not work necessarily, but it's like in personal productivity space. But it has all the same primitives. So it has scheduled tasks. It has the ability to store files on a file system. It has the ability to like reference those things over time. And so you start to see the same types of use cases emerge, which has been really cool.Swyx [00:46:14]: Is there a point that ChatGPT Work completely replaces OpenClaw? they're independent, so.Akshay Nathan [00:46:20]: Yeah, I'm, I'm not close to it, so I can't speak to the OpenClaw roadmap, but I don't think so. I think that there's gonna be, there's always a need for like this like incredible, like open source technology that team has built. And I think that we can draw inspiration, in the product and, ChatGPT, I think many more people have like heard about and used ChatGPT than have used OpenClaw. And if we can take the magic from OpenClaw and bring it to them, I think that'll be a success. I think that like one thing on the ChatGPT Work side that we feel strongly about is that like the core experience is that you come to this product and you have a conversation, start a session, whatever you wanna call it, with this agent. And the magic of the product is that you can do anything in that moment. And we would like to create a product where you don't have to click a button or to go to a different place, whatever, and you can get whatever functionality exists in, your finances app or where or any other product like in this one place. And so that's the goal. It's like it we want an extensible system with plugins where you can connect to the tools that you need in order to be able to accomplish like a financial task, where you can, if you're doing like science work, like we have an ability to like extend the system in such that you can like write the tech and it performs well. There'll always be like products that we support that are best in class at those things, but we want as much of the magic as possible in that core experience.Swyx [00:47:45]: Yeah. Do you think that you can do everything you used to do with Wealthfront in ChatGPT Finance?Finance, Data Access, and Centralized ContextAkshay Nathan [00:47:50]: I tried it. like ChatGPT doesn't yet custody, cash and assets for me. So that part, no, not yet. But I, there was like a whole component of like retirement planning and, like financial planning and budgeting and stuff that, we were looking into when I was there. And like with the finances plugin, like that's all possible with ChatGPT today. So, I feel

AI makes it easier than ever to find and act on information—especially now that teams can connect to and search across all the apps they use for work. So how do you ensure that only the right people and the right tools can access your team's most sensitive content? In this episode, we talk with Jess Jimenez, the head of security at Dropbox, about what security looks like in the age of AI at Dropbox-scale—from building AI products securely to building trust with the people who use them. Jess talks about the importance of access control lists, defending against the latest AI threats, and how Dropbox Protect helps teams securely share content with both humans and AI so they can collaborate more safely. ~ ~ ~  Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck.  Our theme song was composed by Doug Stuart.  Working Smarter is hosted by Matthew Braga. Thanks for listening!

The global healthcare landscape is being redefined, creating new opportunities for healthcare leaders to improve outcomes and expand access. In this episode we sat down with Eugene Sayan, Founder and CEO of Softheon, to explore how AI is empowering consumers, and driving a new era of innovation across the industry. With more than three decades of experience in healthcare technology, Eugene shares his perspective on the forces transforming healthcare delivery, from patient engagement and personalized care to interoperability, affordability, and the growing role of AI agents. He discusses the shift to a proactive approach that leverages data, automation, and intelligent systems to improve outcomes while reducing costs. The conversation also examines the future of healthcare organizations, the importance of responsible AI adoption, and the opportunities healthcare leaders have to build more connected, sustainable, and patient-focused experiences.  Chapter Timestamps: 00:00 Preview Clip 00:57 Introduction 01:33 Eugene's Background and Journey to Softheon 04:17 Consumer Engagement, Analytics, and Healthcare Innovation 06:29 AI, Personalization, and the Future of Care 09:13 AI Agents, Automation, and the Importance of Human Oversight 12:45 Consumer Empowerment and Rising Healthcare Costs 17:33 Provider Sponsored Health Plans and Value Based Care 18:19 Enabling Healthcare at Home Through Technology 23:18 The Power of Digital Engagement and Automation 24:25 Global Healthcare Innovation and Expanding Access 29:15 Ethical AI, Governance, and the Path to AGI 33:21 Interoperability, Data Portability, and What's Next If you're a healthcare executive, provider, payer leader, or healthcare innovator, this conversation offers valuable insights into the opportunities and challenges shaping the future of care. Connect with Eugene on LinkedIn at https://www.linkedin.com/in/eugenesayan Find Eugene's work at https://softheon.com Subscribe and stay at the forefront of the digital healthcare revolution. Find out why we're the fastest growing digital health channel on YouTube!  The Digital Healthcare Experience is a hub to connect healthcare leaders and tech enthusiasts. Powered by Taylor Healthcare, this podcast is your gateway to the latest trends and breakthroughs in digital health. Learn more about The Digital Healthcare Experience here. Taylor Healthcare empowers healthcare organizations to thrive in the digital world. Our technology streamlines critical workflows such as procedural & surgical informed consent with patented mobile signature capture, ransomware downtime mitigation, patient engagement and more. For more information about Taylor Healthcare, please visit imedhealth.com   The Digital Healthcare Experience Podcast: Powered by Taylor Healthcare Produced by Naomi Schwimmer  Hosted by Chris Civitarese Edited by Eli Banks Music by Nicholas Bach  

Dr. Mohsen Ghasempour, Chief AI Officer at Kingfisher, unpacks why the most dangerous thing a company can do with customer data is use all of it. He explains how a global, multi-brand retailer can draw the line between personalization that feels helpful and personalization that feels like surveillance. He also discusses why AI success is ultimately an execution problem rather than a technology problem. Key Takeaways:  What the "comfort test" is and how Kingfisher uses it to decide whether a personalization decision has gone too far How global retailers are resolving the tension between centralized AI infrastructure and brand-level autonomy Why legal and compliance teams are now embedded in AI development from the start What it will look like when AI stops being a distraction and starts being invisible infrastructure Guest Bio: Dr. Mohsen Ghasempour is a distinguished expert in the field of artificial intelligence (AI) with a solid academic foundation, holding a PhD in Computer Science. Currently, Mohsen serves as the Chief AI Officer at Kingfisher, where his leadership contributes to the advancement of artificial intelligence and machine learning technologies within the organisation. With over 15 years of experience as an accomplished data scientist and visionary leader, Mohsen has consistently harnessed the power of data to drive strategic decision-making. Prior to his role at Kingfisher, he held pivotal positions in leading technology and retail organisations, including The Hut Group (THG) and Shop Direct. In these roles, he spearheaded cross-functional teams to implement cutting-edge Machine Learning and AI solutions, resulting in measurable and transformative outcomes. ---------------------------------------------------------------------------------------- About this Show: The Brave Technologist is here to shed light on the opportunities and challenges of emerging tech. To make it digestible, less scary, and more approachable for all! Join us as we embark on a mission to demystify artificial intelligence, challenge the status quo, and empower everyday people to embrace the digital revolution. Whether you're a tech enthusiast, a curious mind, or an industry professional, this podcast invites you to join the conversation and explore the future of AI together. The Brave Technologist Podcast is hosted by Luke Mulks, VP Business Operations at Brave Software—makers of the privacy-respecting Brave browser and Search engine, and now powering AI everywhere with the Brave Search API. Music by: Ari Dvorin Produced by: Sam Laliberte  

Personalization could transform the future of retirement planning. This week on The Modern Custome Podcast, Jessica Austin Barker, Chief Digital Officer and Client Experience Officer at TIAA, joins Blake Morgan to explore how AI could help people receive guidance that reflects their individual goals, circumstances, and changing paths to retirement. Jessica shares why personalization remains only half solved, how AI could reduce the effort required to explore financial scenarios, and what an AI companion could offer across a customer relationship that spans decades. Listen to learn how AI could make retirement planning more personal, accessible, and easier to understand. Blake Morgan was called "The Queen of CX" by Meta. She is a customer experience futurist and author of three books on customer experience. Follow Blake Morgan on LinkedIn For regular updates on customer experience, sign up for her weekly newsletter here. Learn more at www.blakemichellemorgan.com 

AdTechGod sits down with Andrew Swinand, CEO of Inspired Thinking Group (ITG) and former CEO of Publicis Groupe Creative U.S. and Leo Burnett. Andrew shares how AI-powered content automation is helping global brands produce personalized creative at scale, reduce production costs by 50%, cut campaign timelines from 8 weeks to 2 weeks, and drive stronger marketing performance. They discuss operational AI vs generative AI, the future of agencies, creative effectiveness, personalization, and why the next decade may bring a creative renaissance instead of creative replacement. Takeaways AI-powered content automation is enabling brands to create personalized content at an unprecedented scale. ITG helps global brands localize campaigns across languages, markets, and audiences using AI. Brands are reducing production costs by roughly 50% while significantly speeding up go-to-market timelines. Operational AI delivers more immediate ROI than purely generative AI use cases. Most companies already possess valuable creative assets but struggle to find and utilize them efficiently. Effective personalization is not about one-to-one marketing but identifying "meaningful breaks" within audiences. Creative quality remains critical despite AI advancements. The future agency model will focus more on strategy, insights, and creative concepts while automation handles production. AI will eliminate repetitive production work but increase demand for higher-quality creative thinking. Andrew predicts a creative renaissance driven by the abundance of AI-generated content. Chapters00:00 Introduction & Welcome01:01 Andrew Swinand's Career Journey04:36 From Publicis & Leo Burnett to ITG06:20 What Inspired Thinking Group (ITG) Does07:43 How AI Transforms Content Production09:10 Cutting Costs, Speeding Up Campaigns & Personalization at Scale11:00 Why More Creative Variations Drive Better Performance12:42 Operational AI vs Generative AI15:18 AI-Powered Asset Organization & Content Discovery17:03 The Right Way to Personalize Advertising20:00 Why Creative Matters More Than Ever21:28 The Future of Agencies in an AI World23:28 AI Slop, Content Overload & Marketing Challenges26:36 What Marketers Are Overhyping About AI27:03 Andrew's Vision for Advertising in 5 Years28:23 Final Thoughts & Wrap-Up Guests: AdTech God Learn more about your ad choices. Visit megaphone.fm/adchoices

Today's Poll Question at Smerconish.com: Which is more valuable to you: the benefits of artificial intelligence or your privacy? Michael explores a provocative new way of thinking about artificial intelligence after reading "The Problem with Personalization" by media scholar Joseph Turow. While most AI debates focus on privacy and surveillance, this conversation examines a deeper concern: whether hyper-personalization is creating entirely different realities for each of us, weakening the shared experiences that hold communities together. Is AI's greatest cost the information it collects—or the social fabric it quietly unravels? Cast your vote on today's poll and hear why this emerging issue deserves far more attention. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, we dive into how interactive visual experiences drive online sales and lower backend costs. Angelo Coletta, founder and CEO of Zakeke, shares how his plug-and-play platform helps brands stand out with 3D product customization, virtual try-ons, and brand-safe AI automation. He also reveals strategies for launching quickly without complex development cycles. Topics discussed in this episode:  How visual interaction layers improve customer loyalty.What customization tools do to lower backend operational costs.How automated club uniform ordering eliminates manual mistakes.What 3D visualization adds to enterprise sofa configuration.Why AI-driven image generation boosts catalog visual variety.How computer vision algorithms prevent costly manufacturing errors.Why brand safety guardrails prevent AI prompt hallucinations.What 3D catalogs do to reduce global sampling costs.How prompt-driven onboarding speeds up setup processes.Why flexible public APIs simplify complex stack integrations.Links & ResourcesWebsite: https://www.zakeke.com/LinkedIn: https://www.linkedin.com/company/zakeke/Instagram: https://www.instagram.com/zakeke.official/Facebook: https://www.facebook.com/zakekeofficial/YouTube: https://www.youtube.com/channel/UCZPd_oA-Hjq6CE4G1vSUM1QGet access to more free resources by visiting the show notes at https://tinyurl.com/3jxf4djhI'd love your feedback. Tap the the link to send me a text. ______________________________________________________LOVE THE SHOW? HERE ARE THE NEXT STEPS!Follow the podcast to get every bonus episode. Tap follow now and don't miss out!   Rate & Review: Help others discover the show by rating the show on Apple Podcasts at https://tinyurl.com/ecb-apple-podcasts   Join our Free Newsletter: https://newsletter.ecommercecoffeebreak.com/   Support The Show On Patreon: https://www.patreon.com/EcommerceCoffeeBreak   Partner with us: https://ecommercecoffeebreak.com/partner-with-us/

Michael sits down with media scholar Dr. Joseph Turow to discuss his new book, "The Problem with Personalization: How Advertisers Learned to Make and Break Us from Ancient Times to the AI Age." Their conversation explores how AI, advertisers, and tech platforms are reshaping not only our privacy, but our perception of the world. Turow explains how hyper-personalized media and marketing could erode the shared experiences that hold society together, creating increasingly isolated digital realities. It's a thought-provoking discussion about the hidden costs of convenience, surveillance, and the future of public discourse. Original air date 20 July 2026. The book was published on 11 June 2026. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Can you still trust an incoming phone call when AI can imitate a familiar voice, personalize the conversation and target information specifically to you? In this episode, I speak with Alex Quilici, CEO of YouMail, about how artificial intelligence is changing phone fraud and why the personal devices carried by employees are becoming part of the corporate attack surface. Alex explains how YouMail uses data from its consumer call-protection service to identify scam behavior, understand the type of fraud taking place and connect those patterns with the phone numbers involved. Advances in large language models have improved this analysis, but the same technology is also helping criminals build far more convincing campaigns. Generic robocalls are being replaced by personalized conversations designed to extract information, impersonate trusted people and manipulate victims. Fraudsters can use AI throughout the attack chain, from identifying targets and analyzing stolen data to generating dialogue and adapting an approach during the call. Alex argues that attackers have adopted these capabilities faster than many defenders expected because successful fraud produces an immediate financial return. The conversation also examines why voice biometrics can no longer be treated as sufficient proof of identity. As voice-cloning tools improve, companies may need to combine multiple forms of authentication and move sensitive communications into trusted applications. A call received through a banking app, for example, could give the customer greater confidence that the caller really represents their bank. For businesses, the risk extends beyond company-managed technology. Attackers can identify where someone works, learn about their role and contact them through a personal phone that may sit outside corporate monitoring. An employee's private number can therefore provide another route into the business through impersonation and social engineering. Alex also makes a persuasive case for collecting less personal data. Personalization can improve a service, but every additional piece of information becomes something an attacker might obtain during a breach. His advice is to identify the minimum information needed to deliver the intended experience rather than gathering data simply because it may prove useful later. Despite the seriousness of the threat, Alex offers evidence that coordinated action can produce results. He has seen brand-impersonation campaigns reduced from tens of millions of calls each month to around 100,000 through monitoring, disruption and cooperation between businesses and telecommunications providers. If AI is making fraudulent calls harder to recognize, should businesses stop treating the telephone network as a trusted communication channel by default? Listen to the episode and share your thoughts with me.

Healthcare in America is stuck in a "sick care" model—we wait until people are already ill, then scramble to treat them. Dr. Gloria Winters, VP of Health Innovation at the YMCA of the USA, has spent the last year building something different: a community health operating system that pulls together your wearables, your medical records, and AI-driven insights into one place, so you actually know what to do with your health data instead of just staring at numbers. In this episode, she breaks down her "house" framework for the $5.6 trillion healthcare industry, why falls cost the country more than almost anything else, how she's working directly with HHS and the MAHA movement on preventive health policy, and why personal agency—not just data—is the missing piece in helping people actually change their behavior. If you've ever felt like your Apple Watch tells you everything except what you should actually do next, this conversation is for you. Key Takeaways:

Are you leaving money on the table by ignoring AI personalization in your Amazon brand? Neil Twa dives into the missed opportunities most operators face by not using customer behavior signals. While ad spend continues to rise, conversion rates remain stagnant. Neil breaks down a real case from one of his portfolio brands in the home goods category, where traffic and conversion were decent, but repeat purchases lagged. Discover how AI personalization can transform your brand's performance by utilizing data you already have. Neil shares three actionable moves you can implement this week, regardless of your current level. Open your Brand Analytics Search Query Performance report, filter by top SKUs, and identify search terms driving impressions but not conversions. The High Voltage Business Builders Podcast is here to help sellers at every level maximize their potential. Ready to implement with us? Join the Voltage Business Builders cohort at voltagedm.com?utm_source=rss&utm_medium=show_notes&utm_campaign=ep326 See your Amazon numbers in one place and protect your margins with Caiman Data at voltagedm.com: https://voltagedm.com?utm_source=rss&utm_medium=show_notes&utm_campaign=ep326&learn_mcp=1

Welcome to Nerd Alert, a series of special episodes bridging the gap between marketing academia and practitioners. We're breaking down highly involved, complex research into plain language and takeaways any marketer can use.In this episode, Elena and Rob explore what triggers the personalization backfire effect and why the same ad can feel helpful one day and invasive the next. Topics covered:[01:20] "Triggering the Personalization Backfire Effect: The Moderating Role of Situational Privacy Concern"[02:45] How the study tested three levels of ad personalization[04:27] When more personal data actually hurts performance[06:10] Privacy sensitivity isn't a fixed personality trait[07:10] Contextual targeting vs. identity-based targetingTo learn more, visit marketingarchitects.com/podcast or subscribe to our newsletter at marketingarchitects.com/newsletter.Resources: Kim, H., & Han, S. (2025). Triggering the personalization backfire effect: The moderating role of situational privacy concern. Behavioral Sciences.Get more research-backed marketing strategies by subscribing to The Marketing Architects on Apple Podcasts, Spotify, or wherever you listen to podcasts.

AI is reshaping how websites build trust and drive conversions. Anda Gansca, Co-Founder and CEO of Knotch, builds AI-powered content intelligence that shows how digital content influences buyers across the path to purchase. We debate whether personalization, trust, or traffic matters most as AI reduces website visits, why LLM-driven personalization risks repeating the "creepy factor" of early automation, and why human judgment still determines whether personalization builds trust or breaks it.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.