Podcasts about Slack

We spend a lot of time asking how brands can be memorable. We spend almost none asking what happens when the memory is the product.Agility gets talked about as moving fast with new tools. It's really the ability to change repeatedly without losing what makes you recognizable — and that gets harder when what you sell is something a customer plans to keep for twenty years.Today, we're going to talk about:- Why designing for permanence is a strategic choice, not a nostalgic one- Getting specific about what AI is actually doing inside a creative product — and where the customer stays the author- What has to hold steady across a brand as volume, automation, and channels all multiplyTo help me discuss this topic, I'd like to welcome, Andrew Laffoon, CEO & Co-Founder at Mixbook.About Andrew LaffoonAndrew Laffoon is the CEO and co‑founder of Mixbook, a leading photo storytelling platform that helps people transform meaningful moments into beautifully crafted memories. Since founding the company in 2006, he has led Mixbook's growth into a creative technology platform that makes it easier for people to tell, preserve, and share their stories.Andrew brings nearly three decades of experience in software development, product design, and entrepreneurship. His career began in the earliest days of the web, when he founded a web consultancy while still in high school. Prior to Mixbook, he built deep, cross‑functional expertise across engineering, design, operations, and go‑to‑market leadership.In addition to his entrepreneurial work, Andrew has been deeply engaged in education and community leadership. He has served as a Lecturer at UC Berkeley's Sutardja Center for Entrepreneurship and Technology since 2012 and was a member of the UC Berkeley Industrial Engineering and Operations Research (IEOR) Advisory Board from 2015 to 2025. He is also the Founding Board Chair of the Bay Area Center for Faith, Work and Tech, helping explore the intersection of purpose, vocation, and innovation.Andrew Laffoon on LinkedIn---------- Resources ---------- MixbookThe Agile Brand podcast is brought to you by TEKsystems. The hardest part of martech right now is telling which tools are actually earning their keep. That's the question running through the MarTech Summit Boston agenda on October 27. We're attending MarTech Summit Boston on October 27 as a media partner. If you want to join, the code AGILE15 saves you 15%. We're proud to be a media partner for #MAICON26 - Oct. 13-15! Learn how AI can power your marketing and business and help you grow smarter. Use code AGILE150 to save! Need to evaluate martech, AI, or CX platforms and don't know where to start? The Agile Brand Guide List is now in beta. We're building the most useful, free-to-use, and up-to-date way to assess what truly matters when evaluating platforms. Reach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit!Chaser is the only Slack-native project management platform that helps teams turn messages into tracked tasks, automate follow-ups, and maintain team-wide visibility, without adopting another tool. Now integrated with Claude and other GenAI tools. Learn more at trychaser.com and use code AGILEBRAND for a 3-month free trial (normal trial is 14 days).Start building your own apps with Replit and get $20 off.Enjoyed the show? Tell us more and give us a rating so others can find the show.Connect with Greg on LinkedInDon't miss a thing: get the latest episodes, sign up for our newsletter, and check out Martechipedia, the wiki for marketing technology.The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. Hosted on Acast. See acast.com/privacy for more information.

Scream turns 30, and Bloody Good Horror takes a deep dive into the movie that reshaped not only the horror genre, but wider pop culture. We look at the lightning in a bottle created by the joining of fright master Wes Craven with the voice of 90s youth, Kevin Williamson, how it brilliantly skewers the "rules" of the horror film while flipping them on their head, and how the cinematography, production design and score take the whole endeavor way over the top. Plus, a look at the 90s cultural context that Scream stepped into, why it was the Obsession of its day, and how the sequels have largely failed to capture the magic that made the original so special. After the break, we've got a packed round of horror news, including our conversation with the newly announced SAW director, Zach Cregger launching strays at Shudder, Resident Evil RT reviews going crazy and more.

How can marketers use AI to improve the customer experience without filling every channel with increasingly similar content? Recorded at Braze Forge 2026 in Las Vegas, this episode of Tech Talks Daily features my conversation with Christy Poulos, VP of Product Marketing at Braze. We discuss the practical choices behind AI marketing, from deciding what a campaign should achieve to keeping creative work, compliance, and customer relationships under human direction. Christy describes Forge as an opportunity for marketers to talk about their craft and the problems they face every day. Technology forms part of that conversation, but her starting point is the work itself. Teams are being asked to adopt AI while also demonstrating a useful return. Her advice is to connect the tools they choose with specific goals for the brand, the team, and the wider business. Producing additional content offers little reassurance if nobody has agreed what success looks like. We discuss Agentic Standards and the less glamorous work of checking campaigns against rules. Drawing on her experience marketing a regulated product, Christy explains why automating repetitive checks could give teams greater confidence in their output. The marketer still sets the boundaries. Her argument is that campaigns should operate within those boundaries whether a human or an agent prepares them. The interview presents the intended value of these capabilities, rather than independent evidence that they remove compliance risk. Another part of the conversation concerns where marketers actually want to work. Operator Connect introduces ways to connect AI assistants and other working environments with Braze. Christy discusses campaign briefs created in Claude and the growing interest in collaboration through Slack. She also makes a clear case for retaining the traditional product interface, where teams can review a campaign in context, check standards, and launch it. Some businesses are interested in these connections, while others are still developing their AI skills or learning what the tools can do. The question of creative quality runs through the interview. Christy believes customers will recognize generic AI content and that this could weaken their relationship with a brand. Her view is that marketers who continue to bring their own creativity and work alongside AI will produce stronger results. We also discuss conversational agents and the possibility of customer interactions that allow people to respond and feel heard, rather than simply receive another broadcast message. For teams wondering where to begin, Christy recommends Content Optimizer and email content testing as a first step. She describes the possibility of testing many variants, then progressing to Decisioning Studio Go to consider send times and channels. These are her recommendations for adoption, not measured results from a customer case study. Later, she discusses how insights from decisioning products could help marketers contribute to product strategy and business planning. One of the most memorable examples arrives toward the end, when Christy describes a ride hailing platform in Venezuela using Braze to create an earthquake awareness system. The company is not named in the interview, but the story illustrates her broader point about customers finding applications that product teams had not anticipated. Where could AI make your marketing more useful to customers, and which decisions should remain with the people who understand them? I'd love you to share your thoughts.

Hamish and Hannah Acland, co-founders of Mons Royale, join Second Nature to tell the story of building a global merino wool brand from Wanaka, New Zealand. The brand started with an email titled "Anatomy of an Idea" that brought the two of them together. They talk through the founding insight that base layers were the one piece of ski gear nobody had bothered to make exciting, and how they set out to build a global brand from day one rather than a New Zealand one, despite a disastrous first trade show and years of razor-thin margins as distributors took their cut. Hamish and Hannah are candid about the harder second chapter of the business: losing their creative conviction under pressure from wholesalers, the challenge of scaling a founder-led vision into a real team, and the ongoing tension between growth and funding. They also get into how "action sports can better people and planet" became the brand's operating mission over the language of sustainability, why Mons Royale built an athlete program when visibility wasn't even possible for a base-layer brand, and what it's taught them about resilience, team-building, and staying global-minded from a town of a few thousand people at the bottom of the world. Second Nature is proudly supported by Popfly and Halo: Popfly for Brands: https://popf.ly/secondnaturebrands Popfly for Creators: https://popf.ly/secondnaturecreators Halo: https://www.poweredbyhalo.com Show Notes: Mons Royale: https://monsroyale.com/ Hamish Acland: https://www.linkedin.com/in/hamishacland/ Hannah Acland: https://www.linkedin.com/in/hannah-acland/ ISPO: https://www.ispo.com/ Mattie Sims on Second Nature: https://youtu.be/tJl441qcZLk Robin Goomes: https://www.youtube.com/@robin_riding_hood Future Ground Event: https://monsroyale.com/blogs/news/future-ground-full-video BPC - Brand, Product, Content: Keen Shoes: https://www.keenfootwear.com/ Belonging (Book): https://bookshop.org/a/128566/9781529410310 Insta360 X6: https://store.insta360.com/consumer?utm_term=SUPERRIDER Find Us: Join us on LinkedIn: https://www.linkedin.com/company/second-nature-media Meet us on Slack: https://www.launchpass.com/second-nature Follow us on Instagram: https://www.instagram.com/secondnature.media Subscribe to our newsletter: https://www.secondnature.media Subscribe to the YouTube channel: https://www.youtube.com/@secondnaturemedia

John Rockhold, VP Market Engagement at Spotlight, says AI answer engines treat a company's own content as a ceiling — the citations that move buyers come from sources it doesn't control. He and Greg Kihlström get into what replaces the old B2B influence playbook.Self-citation is a ceiling, not a strategy. Publishing more owned content doesn't raise AI visibility past a point; third-party validation does the lifting.Analysts shape the vocabulary, peer platforms get the citation. The two do different jobs, and budget allocated as if they were the same tends to underperform.Influence is owned by everybody and therefore nobody. Rockhold on what has to change week to week across analyst relations, comms, and customer marketing — not just who it reports to.By the time a buyer contacts you, the influencing already happened. What that does to a marketing organization still structured around lead generation and MQLs.About John RockholdB2B buying has become AI-mediated and trust-driven, long before buyers engage a vendor. I spend my time observing how influence is formed, synthesizing signals from analysts, buyer research, and market behavior, and helping organizations make sense of what actually shapes modern buying decisions.As VP of Market Engagement at Spotlight, I draw on a background that includes journalism, analyst relations, and years of close collaboration with industry analysts. I'm trusted by analysts because I respect their role, understand how their work evolves, and prioritize accuracy, context, and long-term relationships over short-term outcomes.Much of my work focuses on how influence, visibility, and trust are earned in the modern B2B buyer journey. I help B2B brands understand how experts, customers, vendors, partners, and employees all shape visibility and credibility. At Spotlight, we refer to this coordinated approach to earning and sustaining trust across analysts, customers, and AI systems as Influence Orchestration.John Rockhold on LinkedIn Resources This episode is brought to you by Spotlight. Spotlight is pioneering the future of influence orchestration in the B2B buyer journey. Trusted by over 165 teams globally, Spotlight is the world's leading analyst relations consultancy and industry platform.The hardest part of martech right now is telling which tools are actually earning their keep. That's the question running through the MarTech Summit Boston agenda on October 27. We're attending MarTech Summit Boston on October 27 as a media partner. If you want to join, the code AGILE15 saves you 15%. We're proud to be a media partner for #MAICON26 - Oct. 13-15! Learn how AI can power your marketing and business and help you grow smarter. Use code AGILE150 to save! Need to evaluate martech, AI, or CX platforms and don't know where to start? The Agile Brand Guide List is now in beta. We're building the most useful, free-to-use, and up-to-date way to assess what truly matters when evaluating platforms.Reach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit! Chaser is the only Slack-native project management platform that helps teams turn messages into tracked tasks, automate follow-ups, and maintain team-wide visibility, without adopting another tool. Now integrated with Claude and other GenAI tools. Learn more at trychaser.com and use code AGILEBRAND for a 3-month free trial (normal trial is 14 days).Start building your own apps with Replit and get $20 off. View the Spotlight Influence Orchestration report.Learn more about the Spotlight Future of Influence Awards.Enjoyed the show? Tell us more and give us a rating so others can find the show.Connect with Greg on LinkedIn.Don't miss a thing: get the latest episodes, sign up for our newsletter, and check out Martechipedia, the wiki for marketing technology. The Agile Brand is produced by Missing Link. From ideation to creation, they craft human connections through intelligent, engaging & informative content. Hosted on Acast. See acast.com/privacy for more information.

With two games down and two to go for the USMNT in this extended international window, Jason grabbed veteran soccer writer Doug McIntyre of Fox Sports to break down the wins over Peru and Chile and talk about what it all means (with Mexico looming on Saturday). * What do we make of the young talent so far? * Are there senior level players in that group right now? * How the Olympics in 2028 are impacting this window * How Poch has changed the vibes for this new cycle * Cavan Sullivan's potential and future at Man City * Positional depth questions * Dual national panic and whether there's any fix Support The Best Soccer Show on Patreon and join the best American soccer community on our Slack. You'll also get access to bonus content, like Jason playing FIFA 18 with his 5-year-old son Thiago. Learn more about your ad choices. Visit megaphone.fm/adchoices

You'll get a regular Write Big episode tomorrow!Hi!As you may know, after ten years of #amwriting, KJ, Jess and Sarina are moving on to other endeavors and have handed the reins of the podcast to me. I'm honored—and very excited—to carry it forward.For the past nine months, I've been trying things, listening to what resonates with you, and weighing my own energy and my options for what #amwriting could become.And I've landed on a new plan.The goal is to keep the spirit of what #amwriting has always done—help writers get their best work done—and to offer more ways to see your own work more clearly.This is one of the hardest things about being a writer. Is this working? What's not working? Is the problem on the page—or in the way I'm thinking about the book? Am I solving the right problem? What should I do next?There is endless writing advice out there. What I want #amwriting to give you is something different: the chance to listen to writers work through real problems, hear the thinking behind the solutions, and get better at seeing and solving problems in your own work.And this is work I know how to do. I've trained more than 400 book coaches and spent years developing frameworks for coaching writers through the decisions, problems, and stuck places that come up as they make books. That means I also have a deep bench of skilled Author Accelerator certified book coaches I can bring into #amwriting.I think that puts me in a unique position to make a different kind of writing podcast—one built around showing you what good coaching looks like in action and helping you become better at thinking through your own work.You'll continue to get free #amwriting episodes every week, including Write Big, my episodes about what it takes to do your best work and keep doing it; and Margin Notes, short episodes that take a close look at a particular question, problem, or moment in the writing life. That is where I will often have guests join me.And, I've started writing the Substack posts each week as mini lessons for those who want to read rather than listen. Before, they were generic summaries and no one wants to read that. But a big part of this new #amwriting is now going to happen for paid subscribers.Why I'm asking you to pay $8/monthBookLab and Hot Seat Coaching take real time, effort, and energy to produce. They involve reviewing work, preparing for coaching conversations, bringing in the right coaches and guests, recording, editing, and producing the episodes.I love doing this work. I want to do more of it. And I need the support of paid subscribers to make it sustainable.So I'm making BookLab and Hot Seat Coaching part of the paid #amwriting membership.If you want to get better at seeing your own work clearly, making stronger writing decisions, and knowing what to do when you get stuck, I'm asking you to support this work by becoming a paid subscriber. It's $8/month.For $8/month, here's what you get* All the regular weekly #amwriting episodes, including Write Big and Margin Notes.* BookLAB — We take apart real submissions—first pages, book jackets, query letters, and more—to see what's working, what's not, and why. The more you learn to see in someone else's work, the more you can see in your own. I plan to share a BookLAB episode each month.* Hot Seat Coaching — Listen as real writers work through real writing challenges with me and Author Accelerator certified book coaches. You'll hear not just what they decide to do, but the thinking that gets them there—so you can get better at working through your own challenges.* The complete #amwriting archive — Ten years of conversations about virtually every stage of the writing life, organized by topic so when you hit a problem, you can find the conversations that can help. (This will take us a little while to organize but we're already working on it!)If you want to do more than listen, you can come further into the work.Annual — $80/yearAnnual subscribers get everything in the $8/month membership for a more affordable price, plus:* Attend our monthly BookLABs live on Zoom. Join us each month as we work on writing in real time. Raise your hand to share your first pages, book jackets, query letters, and other work for possible coaching and feedback* BookLABs will happen on zoom. We'll email links out before each episode. Times of these sessions will vary but the next three will be: * Thursday, Oct. 15 at 9 am PT* Thursday, Nov. 19 at 9 am PT* Thursday, Dec. 17 at 9 am PT* Get private recordings as I do a last-pass read-through of my forthcoming book, Write Big: 7 Questions That Will Change Your Writing Forever. I'll read the book and decide what to change or tweak as I go, sharing the process with annual subscribers.For writers who want even more access and coaching:The #amwriting Writers' Room — $180/yearGet in the room where we do the work.Writers' Room members get everything in Annual, plus invitations to join me and Author Accelerator certified book coaches for more intimate coaching experiences throughout the year, including Blueprint challenges for starting and revising a book.We're kicking off the Writers' Room with something I'm especially excited about: the very first Write Big Coaching Sessions.This will be a five-week experience where we'll work through the seven questions at the heart of my forthcoming book, Write Big: 7 Questions That Will Change Your Writing Forever.* Before each call, you'll receive a private audio episode of me reading a chapter. * The live calls (Pacific Time) are:* October 19 — 8:00 a.m.* October 21 — 4:30 p.m.* October 26 — 8:00 a.m.* October 28 — 4:30 p.m.* November 2 — 8:00 a.m.* November 4 — 4:30 p.m.* November 9 — 8:00 a.m.* November 11 — 4:30 p.m.* Then we'll come together on Zoom to write, talk, and work with the questions. * We'll have a private Slack channel throughout the five weeks for questions and conversation, and a community manager who will help direct the conversation and connections. We'll also post recordings there, so it's okay if you need to miss some of the live calls.You'll be part of the very first cohort to experience the book this way. You'll help me choose the book jacket, and I'll include your name in the acknowledgments of the finished book.The idea is to use these seven questions to look closely at your own writing and writing life: what you want, what you know, what's getting in your way, and what you want to do next.So you can decide how far you want to come into the new #amwriting:* Keep listening for free.* Get better at seeing and solving writing problems for $8/month.* Bring your own work into the conversation for $80/year.* Get in the room and get coached for $180/year.I'm really excited about what we're building next—and I hope you'll come with me.Thanks for your support!Jennie This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit amwriting.substack.com/subscribe

Get a $230 gift card after making a $500 payment with Melio (affiliate) - https://milestomemories.com/go/melio Mark started his morning trapped in his own backyard by a skunk, and somehow that was not the worst news of the day. Bilt just announced it is cutting Hyatt transfers from 1:1 to 4:3 on January 1, the same change Chase made to the Sapphire Preferred, and it has us convinced we know who is really behind all of this. We get into why Hyatt might actually want it this way and what it says about where the program is headed. Plus Q4's 5% categories went all in on dining, Chase has new targeted spend offers worth checking, Audible is back at 99 cents a month with a bonus credit, and easy bank bonuses are back, including an E*Trade offer worth up to $800 with a 4.25% APY. Is Hyatt still worth chasing for you? Let us know in the comments. Episode Guide: 0:00 Welcome to MTM Travel 0:23 Mark Gets Trapped by a Skunk 3:58 Q4 5% Categories: Dining Everywhere 5:31 Chase's New Targeted Spend Offers 7:09 Audible Is Back to 99 Cents a Month 9:58 Melio: $230 Gift Card After a $500 Payment 10:36 Getting Back Into Bank Bonuses 12:54 E*Trade's Up to $800 Bonus & 4.25% APY 15:54 Ameriprise Platinum, Mercedes Swag & the Ani Mindset 18:20 Bilt to Hyatt Drops to 4:3 in January 20:58 Is Hyatt Becoming Marriott? 22:52 Why Hyatt Wants Co-Brand Card Spend 25:43 Final Thoughts Links 5X cats - https://milestomemories.com/5-categories-for-2026-4th-quarter/ Chase My Bonus - https://milestomemories.com/chase-my-bonus-quarterly-spending-offers/ Bank Bonuses - https://milestomemories.com/bank-account-bonuses-2/ Bilt 4:3 - https://milestomemories.com/bilt-to-hyatt-transfer-ratio/ E-trade offer - https://milestomemories.com/etrade-800-signup-bonus/

Kamara Turner is back for her third appearance on Marketing Happy Hour, and this time she is bringing insights from her newest chapter: Supervisor of U.S. Enterprise Communications at McDonald's, where she has been navigating the world of internal and corporate communications after years of brand and external PR experience at Walgreens, PepsiCo, Ulta Beauty, and The Coca-Cola Company. In this conversation, Kamara opens up about what it is like to communicate for one of the most personally meaningful brands in the world, how she thinks about the difference between building a community versus an engaged audience, her nuanced approach to using AI as an organizational tool without letting it replace her writing, and the career lesson that has stuck with her most: not all great ideas will see the light of day, and that is okay. She also shares a standout influencer campaign from her Pulse and Perspective newsletter and walks through how she keeps cross-functional stakeholders aligned when everything is moving fast. Key Takeaways:// When you work for a brand everyone already knows, your job shifts from introducing to nurturing. At McDonald's, Kamara is not building brand awareness from scratch — she is maintaining and deepening a relationship that people already have deeply personal feelings about. That requires a fundamentally different communications mindset.// Community means pouring back into the people who support you. An engaged audience watches and listens. A community leaves with something — an idea, a resource, a tangible value. If you want to build one intentionally, start by asking what you are going to give people, not just what you want them to do.// Data is your best tool for getting buy-in. When you can back an idea with consumer insights and hard numbers, you are no longer just pitching a concept — you are connecting it to the business. In a comms role where numbers can feel foreign, leaning into data is what separates ideas that get approved from ideas that stall.Connect with Kamara: LinkedIn | Pulse and PerspectiveKamara's Episodes: Mastering Your Brand Communications and PR Strategy | The Strategies You Need for Brand Communications and PR____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

On September 6, 1997, the day of Princess Diana's funeral, Jobert Abueva couldn't get out of bed. He was in a Hong Kong hotel room, paralyzed for the better part of 48 hours, unable to touch the club sandwich or hot tea he'd ordered, crying from exhaustion, loneliness, and homesickness. It was, he says, the lowest point of a career that from the outside looked like nothing but success.For most of his thirties, Jobert had been living the frenzied pace of a global marketing career, opening new markets for Herbal Essences across Europe, the Middle East, and Asia, jumping from country to country in a matter of months, taking calls with U.S. headquarters at all hours. He got the raises and the next plum assignment. He also got the lack of sleep, the overeating, the overdrinking, and the signals he kept ignoring, until his body simply stopped.In this conversation, Jobert tells Lori how a childhood memory of Janus, the two-faced Roman god of beginnings and endings, surfaced in that hotel room and became the seed of a framework he now calls the Janus Plan. It's a conversation about what happens when you finally stop outrunning burnout, why looking backward is what makes it possible to move forward, and why boundaries only stick the second time you build them on purpose.What You'll Take AwayWhy ignoring burnout signals for years eventually catches up with even the highest performersHow a childhood memory of the Roman god Janus reframed Jobert's understanding of endings and beginningsWhy 'ponder the past' before 'frame the future' makes goals more sustainable than New Year's resolutionsHow setting boundaries the second time around, including turning down future expat assignments and developing a team instead of doing everything himself, reshaped his second corporate careerWhy any personal threshold, not just January 1st, can be the start of a meaningful new chapterGuest BioJobert E. Abueva grew up between four Asian countries and went on to a three-decade global marketing and philanthropy career, including launching Herbal Essences into international markets. He is a TEDx speaker, a Lambda Literary Prize recipient, and the author of The Janus Plan: A No-Resolutions Path to Begin Your Year with Intention. He lives in New Hope, Pennsylvania.Chapters & Key Timestamps00:00 Opening and episode premise00:39 The nomadic childhood that shaped a global career07:09 Launching Herbal Essences across Europe, the Middle East, and Asia10:55 The signals he ignored: exhaustion, overwork, and a frenzied pace12:00 September 6, 1997: the Hong Kong hotel room he couldn't leave15:48 A childhood memory of Janus reframes everything20:15 Ponder the past, frame the future: leaving corporate to write24:13 Setting boundaries the second time around26:05 The Janus Plan: a no-resolutions path to a new year34:24 His hype song and the moment it found him36:17 Where to find Jobert and the invitation to 'be like Janus'Resources MentionedBook: The Janus Plan: A No-Resolutions Path to Begin Your Year with Intention by Jobert E. AbuevaJobert's 2023 boyhood memoir (referenced in conversation; title to be confirmed with Jobert's team before publication)Hype Song: "You Get What You Give" by New Radicals - https://www.youtube.com/watch?v=DL7-CKirWZE&list=RDDL7-CKirWZE&start_radio=1Connect With Jobert AbuevaWebsite: https://joberteabueva.com/LinkedIn: https://www.linkedin.com/in/jobertabueva/Instagram: https://www.instagram.com/joberteabueva/Facebook: https://www.facebook.com/joberteabueva/Book: The Janus Plan: A No-Resolutions Path to Begin Your Year with IntentionContinue With LoriWebsite: https://zenrabbit.comLinkedIn: https://www.linkedin.com/in/lorisaitz/Email: Lori@ZenRabbit.comInvitation From LoriZen RabbitThis episode is sponsored by Zen Rabbit. Trust is the foundation of all great workplaces, and in today's hybrid, fast-moving work culture, it's built through consistent, clear, human communication.Quarterly town halls, Slack messages, or team-building events are rarely enough to create the connection employees need. That's why forward-thinking companies are hiring Lori to create internal and private podcasts that bring leaders and employees together through authentic stories and real conversations.Think of it as the old-school company newsletter reinvented for the modern workplace.If your company wants to strengthen communication, connection, community, and culture, connect with Lori at Lori@ZenRabbit.com or on LinkedIn: https://www.linkedin.com/in/lorisaitz/About FINE is a 4-Letter WordFINE is a 4-Letter Word is the show for leaders who are tired of pretending everything is fine.We explore what it takes to lead with empathy, vulnerability, gratitude, and courage, especially during the seasons when life and leadership feel anything but fine.Listen for honest conversations about how human connection influences innovation, retention, leadership, and real impact. New episodes every week.Follow FINE is a 4-Letter WordFollow or subscribe so you never miss an episode.If this conversation gave you something useful to think about, leave a review. Reviews help more people discover the show and join the conversation.

What We Cover In This Episode: Why you should set the rules for any workflow before you turn it on, and what happens when you skip that step [1:29] The sub coverage problem most studios are currently solving in group texts and Slack, and what sub management does differently [3:00] How the controlled handoff flow works from request to approval to schedule update, and where admin control lives at every step [4:37] The three questions to answer before you flip the switch on sub management [7:55] How to decide whether your studio needs manual approval or auto-approval, and why there is no wrong answer [9:13] How to build your approved class lists so the right requests only go to the right instructors [9:58] What the sub board and request flow looks like from your staff's side in the On the Go app [13:00]   Quotes:  "Approved classes lets you define what instructor is actually approved to be a sub and to teach what specific types of classes." [Megan, 10:21] "The biggest thing I want you to take away from this episode is don't wait until you need a sub to decide how your sub process should work. We're giving you the controls to decide who can request, who can see those requests, where the admin approval happens, and ultimately who gets assigned." [Megan, 13:45] LINKS:  Get Nick's New Book, The Boutique Advantage: How Independent Studio Owners Win Through Identity, Experience, and Economics Book a Call with the fitDEGREE Team Learn More About All of Our Partners (Including LoopSpark & LezVU) and Get Exclusive Offers Visit the fitDEGREE Knowledge Base Send Megan Your Playlist or Discuss the Podcast Here!  fitDEGREE's Business Portal support@fitDEGREE.com https://www.instagram.com/fitdegree/ ​​https://www.instagram.com/fitspot_guru/  https://www.fitdegree.com/blog  https://www.youtube.com/channel/UChJ5rK6zWPXjbxtUQx3ys9Q https://www.tiktok.com/@megan_fitdegree  

In this episode of Run the Numbers, CJ sits down with Todd McElhatton, CFO of Zuora, for a deep cut on pricing, packaging, and value in the age of AI. They dig into how companies are figuring out whether to charge for AI at all, why token-based budgets are starting to sit alongside headcount budgets, and why AI may be increasing — not decreasing — the value of deep expertise.—SPONSORS:Brex is an intelligent finance platform that combines corporate cards, built-in expense management, and AI agents to eliminate manual finance work. By automating expense reviews and reconciliations, Brex gives CFOs more time for the high-impact work that drives growth. Join 35,000+ companies like Anthropic, Coinbase, and DoorDash at https://www.brex.com/metricsAbacum puts your actuals, forecasts, models, and business context in one place, so you can update the plan, run scenarios, and answer "why did this change?" without rebuilding the story from six spreadsheets and a Slack thread. Connect your source systems, keep models and assumptions aligned, and give leaders trusted answers while decisions are still being made. Go to abacum.ai/mostly-metrics.RightRev is a revenue recognition platform built for the AI economy, helping finance support usage-based pricing, credits, hybrid contracts, seats plus consumption, and whatever commercial model comes next. It gives product teams the freedom to keep innovating without outdated revenue systems slowing them down. Learn how RightRev can help at https://rightrev.com/cjFidelity Private Shares gives founders the structure and simplicity to focus on what actually matters - building your company. If your startup needs a little extra support (and let's be honest, who doesn't need a little help now and then), then you're in for a pleasant surprise with Fidelity. If you stay investor ready, you don't have to get investor ready. Check out www.fidelityprivateshares.comRillet is an AI-native ERP built for modern finance teams that want to replace NetSuite and close faster. With revenue recognition, close management, multi-entity support, and native Stripe and Salesforce integrations, Rillet helps scaling companies run their finance stack in one place. Hundreds of teams, including Windsurf and Mercor, use Rillet to make the zero-day close real. Book a demo at https://www.rillet.com/cjCloud Capital helps you say goodbye to on-demand rates for cloud. Committing more cuts the rate you pay for cloud infrastructure by 20–60%. Commit wrong and you pay for capacity you'll never use. Cloud Capital underwrites that risk, so you capture the savings of deeper commitments without locking in architecture or putting engineers on it. Go to www.cloudcapital.coEY works with high-growth tech companies to navigate the messy realities of scaling—from regulatory requirements to IPO readiness. By helping teams get it right early and often, EY lets founders stay focused on building while reducing risk as they grow. Learn more at https://www.ey.com/techstartups—LINKS: Mostly Talent: https://mostlymetrics.typeform.com/to/cLTxtAsNGuest: linkedin.com/in/todd-mcelhatton-2140761Company: www.zuora.comCJ: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—TIMESTAMPS:0:00 Intro1:15 Meet Todd2:24 Debating Price7:33 Is Software "Going Headless"?9:18 Is AI Increasing the Value of Experts9:58 Hiring Specialists vs. Generalists16:49 Rethinking the Budget Envelope26:56 Time to Value31:20 Forward-Deployed Engineers35:20 Parallels Between On-Prem-to-Cloud36:10 Rethinking Strategy37:07 Avoiding the Sunk Cost Trap38:58 The Art of Pivoting40:12 VMware41:31 Experimenting With AI42:33 What Private Boards Bring43:13 Short-Term Pain43:45 One-Way Doors vs. Two-Way Doors44:57Long-Ass Lightning Round45:04 Biggest Career Mistake45:36 Advice45:56 Finance Tech Stack46:43 The Craziest Thing Expense#RunTheNumbersPodcast #AIforCFOs #FinanceLeadership #Zuora #GoingPrivate

Justin Duke, who runs Buttondown, calls himself a "radical LLM centrist." About two-thirds of Buttondown's merged code comes from LLMs, but he still pushes back on the most extreme software factory takes. He and Matt talk about why most "factories" are only tuned for throughput and why so much agent work is snacking: low effort and low value. They also get into the rise of fake third-party services, and whether Kanban is a warning about borrowing manufacturing ideas without the principles behind them. Plus: a huge pile of regexes, CI that rejects PRs without screenshots, and why Buttondown's Storybook has quietly become its staging server.Mentioned in this episodeSnacks are cheaper and tastier than ever: Justin's post on how LLMs make low-effort, low-value work very tempting. You get the rush of 15 merged PRs and no effect on customers. It pairs well with his Be careful what you make easier.PlanetScale's self-improving database: Both teams feed PlanetScale's Insights and schema recommendations to agents that open PRs, some of which merge automatically. It's close to a free lunch, though Justin argues it's also where the factory metaphor breaks, since real factories don't improve themselves.Linear Customer Requests: Justin's favorite little-used Linear feature. You link issues to customers along with their revenue, so "who's asking for this, and does it change whether they churn?" gets answered before an agent starts on the backlog.Plain: Buttondown's support tool. Instead of sending every thread to an LLM classifier the way Plain would like, they use a "staggeringly terrifying" pile of regexes that's easy to improve over time. Matt's team went the same way, with LLMs writing the regex instead of being the classifier.StrongDM's Digital Twin Universe: This is the software factory's take on the manufacturing "digital twin." StrongDM had agents build clones of Okta, Jira and Slack from their public API docs so they could run thousands of test scenarios an hour.Miniflare vs. stripe-mock: What matters most in a fake service is keeping state. Cloudflare's local simulator remembers what you did. With Stripe's mock, if you create a customer and then list customers, you get an empty list.Litmus / Email on Acid: Testing email rendering still means somebody keeping a headless Windows XP box running. Now it's much cheaper to build that kind of internal tool yourself.Storybook + Buttondown's demo site: Buttondown's "storybook maximalist" setup has stories for every page, component and transactional email, all snapshot tested. The public demo site with realistic data covers everything else, so they barely use their old staging server.Rails forensics skill for CVE-2026-66066: After the Active Storage image-upload RCE, known as KindaRails2Shell, 37signals released agent skills that check whether you were vulnerable and whether you were actually exploited. A small team would never have done that kind of investigation before.The productivity paradox: Justin asks why GDP hasn't grown with technology. His test for LLMs is what they let you do that your people and budget couldn't do three years ago.Thank you to this season's sponsor Laravel Cloud. Laravel Cloud is expanding beyond PHP to host your Rails, Node, or Django apps. For early access to the best place to host your app, email haley@laravel.com and mention YAGNI

John Nunemaker runs Fireside, Flipper and Box Out. He used to think of himself as a craftsman, until last December, when he found out that what he really loves is shipping. Now he reads the data models and queries but not the JavaScript. He's also dropping plugins and rewrote 80% of Fireside's infrastructure in three days while driving a camper. He and Matt talk about when you're the brain and when you're the hands, why agent tools hand you too many open loops at once, temporary scoped API keys, and why testing and verification might finally stop being seen as lower-status work.Mentioned in this episodeCompound Engineering: Every's plan, build, review, compound loop. The last step turns anything you did into a process you can reuse next time. John used it for about a month before paring back his setup.gstack: Garry Tan's Claude Code setup. John dropped most of it but kept the browse tools for before-and-after screenshots. Those led to his most-used homemade skill, /prove, which asks the agent to prove its work actually works from start to finish.Caddy on-demand TLS: This replaced Fireside's tangle of Nginx, background jobs and Redis for custom-domain SSL. The app says which domains get a certificate, and Caddy handles the rest. Claude suggested it after John asked what tool does this.Railway's canvas, for agents: This is John's pitch for fixing agent overload. He wants every worktree in Conductor, Codex or Cursor to be a box on an infinite canvas that you can group, connect and move out of the way, instead of an endless list of open loops.Codex remote access: Scan a code with your phone, and your Mac, fully set up and sitting on your desk, takes commands from a camping chair. This is what got John "mainlining" Codex.Cloudflare Tunnel: John's way to check work from his phone. The agent installs cloudflared, adds the host to Rails, restarts the server and gives him a link.Toxiproxy: Shopify's proxy for simulating slow, failing or flaky connections. John used it on GitHub's availability team so that a notifications database outage wouldn't take down all of GitHub.StrongDM's Digital Twin Universe: The "fake Slack" idea. Agents build single-binary clones of third-party APIs, so you can test OAuth, webhooks, rate limits and outages from any worktree. John now wants to do this for X and Meta at Box Out.Wispr Flow: After years of hand and arm pain, John now talks to his agents all day. The only problem is a sore throat.Flipper: John's feature flag product. His closing prediction: when nobody reads the code, feature flags and APMs matter more, so APMs will have to get much cheaper.Thank you to this season's sponsor Laravel Cloud. Laravel Cloud is expanding beyond PHP to host your Rails, Node, or Django apps. For early access to the best place to host your app, email haley@laravel.com and mention YAGNI

O trabalho remoto e híbrido trouxe uma flexibilidade sem precedentes, mas também criou um novo desafio de carreira: como garantir que o teu empenho, os teus resultados e a tua liderança são reconhecidos quando não estás presencialmente com a equipa? O risco do "fora de vista, fora da ideia" ainda é real, mas ser visto não exige presença física constante.Neste episódio, a Ema Gonçalves, senior consultant de recrutamento de perfis especializados de HR, Tax & Legal da Randstad Portugal ensina como construir uma visibilidade digital forte e intencional. Vais aprender a comunicar o teu impacto, a manter uma rede de networking ativa à distância e a garantir a tua progressão de carreira sem abdicar da tua flexibilidade.Neste episódio, vais descobrir:Preconceito de proximidade: o que é o proximity bias e como evitar que afete as tuas oportunidades de promoção.Comunicação assíncrona com valor: como usar o e-mail, Teams ou Slack para destacar o teu progresso sem sobrecarregar a equipa.Presença em reuniões virtuais: técnicas para ter uma voz ativa e marcar posição em videochamadas ruidosas.Networking à distância: estratégias para criar relações de confiança na empresa sem os encontros casuais do escritório.Presença híbrida estratégica: como rentabilizar ao máximo os dias em que vais presencialmente ao escritório.Demonstração de ambição: como sinalizar que queres crescer e liderar novos projetos, mesmo a trabalhar a partir de casa.A tua reputação não é construída pelo tempo que passas numa cadeira, mas sim pela clareza da tua comunicação e pela consistência dos teus resultados.

John Rockhold, VP Market Engagement at Spotlight, says AI answer engines treat a company's own content as a ceiling — the citations that move buyers come from sources it doesn't control. He and Greg Kihlström get into what replaces the old B2B influence playbook.Self-citation is a ceiling, not a strategy. Publishing more owned content doesn't raise AI visibility past a point; third-party validation does the lifting.Analysts shape the vocabulary, peer platforms get the citation. The two do different jobs, and budget allocated as if they were the same tends to underperform.Influence is owned by everybody and therefore nobody. Rockhold on what has to change week to week across analyst relations, comms, and customer marketing — not just who it reports to.By the time a buyer contacts you, the influencing already happened. What that does to a marketing organization still structured around lead generation and MQLs.About John RockholdJohn Rockhold is VP of Market Engagement at Spotlight, an influence orchestration agency rooted in analyst relations. His background spans journalism, analyst relations, and years of close collaboration with industry analysts. His work focuses on how influence, visibility, and trust are earned in the modern B2B buyer journey, synthesizing signals from analysts, buyer research, and market behavior, and helping B2B brands understand how experts, customers, vendors, partners, and employees shape visibility and credibility. Spotlight calls this coordinated approach to earning trust across analysts, customers, and AI systems Influence Orchestration.John Rockhold on LinkedIn ResourcesThis episode is brought to you by Spotlight. Spotlight is pioneering the future of influence orchestration in the B2B buyer journey. Trusted by over 165 teams globally, Spotlight is the world's leading analyst relations consultancy and industry platform.The hardest part of martech right now is telling which tools are actually earning their keep. That's the question running through the MarTech Summit Boston agenda on October 27. We're attending MarTech Summit Boston on October 27 as a media partner. If you want to join, the code AGILE15 saves you 15%.We're proud to be a media partner for #MAICON26 - Oct. 13-15! Learn how AI can power your marketing and business and help you grow smarter. Use code AGILE150 to save!Need to evaluate martech, AI, or CX platforms and don't know where to start? The Agile Brand Guide List is now in beta. We're building the most useful, free-to-use, and up-to-date way to assess what truly matters when evaluating platforms.Reach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit!Chaser is the only Slack-native project management platform that helps teams turn messages into tracked tasks, automate follow-ups, and maintain team-wide visibility, without adopting another tool. Now integrated with Claude and other GenAI tools. Learn more at trychaser.com and use code AGILEBRAND for a 3-month free trial (normal trial is 14 days).Start building your own apps with Replit and get $20 off.View the Spotlight Influence Orchestration report.Learn more about the Spotlight Future of Influence Awards.Enjoyed the show? Tell us more and give us a rating so others can find the show.Connect with Greg on LinkedIn.Don't miss a thing: get the latest episodes, sign up for our newsletter, and check out Martechipedia, the wiki for marketing technology.The Agile Brand is produced by Missing Link. From ideation to creation, they craft human connections through intelligent, engaging & informative content. Hosted on Acast. See acast.com/privacy for more information.

På temat att klättra i rank så tittar Marcus på vilka högt ägda spelare man kanske vågar släppa och vilka lågt ägda spelare som kan vara intressanta att investera i.

Brands have spent millions building out customer experience platforms — so why does the experience so often fall apart at the exact moment it matters most?Agility isn't just about moving faster or scaling up. It's about staying recognizably yourself when the pressure is highest — so the experience still holds together when every system is under strain.Today we're going to talk about what happens when the experience you designed on paper collides with the reality of peak customer demand. Specifically, we'll cover:- The idea of "experience debt" — and why high-traffic moments are where the hidden fractures in a customer journey finally show up.- Turning digital intelligence into actual decisions, not just dashboards, so friction gets fixed at the root instead of patched at the surface.- Where AI should predict and flag a problem versus act on its own — and what has to change across teams to own the experience end to end.To help me discuss this topic, I'd like to welcome, Jonathan Moran, Senior Manager, Horizontal Solutions Marketing at SAS. About Jonathan MoranJonathan Moran is responsible for global marketing activities for SAS' marketing solutions. He has more than 20 years of marketing technology and customer analytics industry experience. Jonathan has designed, developed and implemented analytical software solutions that helped Fortune 500 customers solve unique analytics business issues.Jonathan Moran on LinkedIn: https://www.linkedin.com/in/jonathanmoran/---------- Resources ---------- SAS: The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://aglbrnd.co/r/2868abd8085a9703The hardest part of martech right now is telling which tools are actually earning their keep. That's the question running through the MarTech Summit Boston agenda on October 27. We're attending MarTech Summit Boston on October 27 as a media partner. If you want to join, the code AGILE15 saves you 15%. https://aglbrnd.co/r/c70c250b8d52dff3 We're proud to be a media partner for #MAICON26 - Oct. 13-15! Learn how AI can power your marketing and business and help you grow smarter. Use code AGILE150 to save! https://aglbrnd.co/r/7fe458ced0f04658Need to evaluate martech, AI, or CX platforms and don't know where to start? The Agile Brand Guide List is now in beta. We're building the most useful, free-to-use, and up-to-date way to assess what truly matters when evaluating platforms. See more here: https://aglbrnd.co/r/f76be3a33cc491bb Reach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit! Learn more: https://aglbrnd.co/r/491818c79fb1873fChaser is the only Slack-native project management platform that helps teams turn messages into tracked tasks, automate follow-ups, and maintain team-wide visibility, without adopting another tool. Now integrated with Claude and other GenAI tools. Learn more at trychaser.com and use code AGILEBRAND for a 3-month free trial (normal trial is 14 days).Start building your own apps with Replit and get $20 off. Learn more: https://aglbrnd.co/r/93531742a7625a20 Enjoyed the show? Tell us more and give us a rating so others can find the show: https://aglbrnd.co/r/faaed112fc9887f3 Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter, and check out Martechipedia, the wiki for marketing technology: https://aglbrnd.co/r/35ded3ccfb6716ba The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content: https://aglbrnd.co/r/f1782ab12211f765 Hosted on Acast. See acast.com/privacy for more information.

Trump got the big AI companies to sign a voluntary, "morally binding" safety accord. OpenAI's DevDay delivered Dots, always-on agents, plus GPT-6.1 Sol and a play to make ChatGPT the new app store. Amazon refreshed the Fire TV Stick 4K. Trump releases a voluntary AI accord with tech leaders, asking companies to partner with external auditors and set up internal controls to monitor AI alignment (Reuters) Trump convened tech CEOs at the White House, where they signed a one-page voluntary pact instead of formal regulation, which he called "morally binding," leaving the companies to police each other (New York Times) Amazon unveils a faster, slimmer $60 Fire TV Stick 4K, simplifies its Fire TV Stick lineup, and plans to roll out an upgraded Alexa+ living room hub in November (Bloomberg) OpenAI launches Dots, always-on agents powered by GPT-6 Astra with their own cloud computer, in ChatGPT for Pro, Business Premium, and Enterprise users (Bloomberg) OpenAI's Dots, its answer to Meta's Muse, work in the background across 4,000+ apps, learn your preferences over time, and connect to Slack and Microsoft Teams (The Verge) OpenAI releases GPT-6.1 Sol, saying it nearly matches Astra on agentic coding and professional work at one-fifth of Astra's standard prices, in Work and Codex (OpenAI) OpenAI unveils ChatGPT Spaces, shared team workspaces for files and AI output, plus a meeting-notes plugin, and brings ChatGPT to Slack and Microsoft Teams for Business and Enterprise users (Engadget) OpenAI's DevDay announcements, from in-chat app suggestions to "Sign in with ChatGPT," turn ChatGPT into the place software gets discovered and used, taking direct aim at the app store model (TechCrunch) Subscribe to the ad-free feed.

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. Ed and Richard are back together after a weekend in New York—and before they can get to travel, there are some important matters to resolve. Richard has strong opinions about restaurant eggs, Ed has an explanation for his highly unusual chicken-wing-eating technique, and Julian and Jillian apparently think a perfectly reasonable honeymoon itinerary involves going from the Maldives to Lapland to Iceland. Eventually, travel news breaks out. First up is a partnership Richard knows particularly well: Bilt Rewards has added Amtrak Guest Rewards as its 26th transfer partner. Richard says the deal took roughly 14 months from the first phone call to launch and marks Amtrak's first traditional transfer partnership since Chase ended its relationship in 2015. Transfers are 2 Bilt points to 1 Amtrak point, and Richard argues the economics can still work because of the relatively high value of Amtrak points—especially when cash fares get expensive. There's also a follow-up to last week's Citi Strata Elite discussion. Listeners point out a potentially powerful pairing with Citi Double Cash: earn effectively 2 ThankYou Points per dollar on everyday purchases if you pay the balance in full, combine those points with Citi Strata Elite, and then transfer them to American Airlines AAdvantage. For someone specifically trying to build an AAdvantage balance, Richard thinks the strategy deserves consideration. Then Ed and Richard discuss a new software issue affecting the Boeing 737 MAX. According to the information discussed on the episode, a newer software version can cause issues with certain autopilot functions around an aborted landing/go-around. Boeing has identified a workaround involving the earlier software version, but Ed questions why increasingly powerful simulation and AI tools couldn't be used more extensively to find edge cases before software reaches aircraft. The Aeroplan credit card has also received a refresh. One new benefit provides a 15% discount on Air Canada flight rewards—and importantly, Ed says Aeroplan confirmed that it can stack with elite Priority Rewards. At the highest elite level, that creates the possibility of combining a 50% Priority Reward with the additional 15% card discount. The card is also making its fourth-night-free hotel award benefit permanent and adding a fourth-day-free benefit on car-rental redemptions. Finally, there's a strange problem developing around the Airbus A321XLR. Premium-heavy configurations planned by American and United may need ballast in the rear of the aircraft to keep the plane properly balanced. That's particularly interesting because adding otherwise unnecessary weight requires more fuel and could eat into the very long-range capability that makes the XLR attractive for "long, thin" international routes. That raises another question: How long are you willing to fly on a single-aisle airplane? Richard thinks a New York-to-California transcon is already approaching his limit. Ed is more willing to judge the experience by the quality of the seat rather than the number of aisles. 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 ✈️ Bilt adds Amtrak as a transfer partner 2:1 transfers from Bilt Rewards to Amtrak Guest Rewards Why Richard thinks the math can still work A Rent Day transfer bonus The partnership took about 14 months to complete Amtrak's first traditional transfer partner since Chase ✈️ The world's easiest honeymoon to pack for Maldives Lapland Iceland Julian apparently has some flights to figure out ✈️ A better Citi strategy for earning American miles? Pairing Citi Double Cash with Citi Strata Elite Effectively earning 2 ThankYou Points per dollar on everyday spending when the balance is paid in full Combining the points Transferring to AAdvantage Why the strategy gets Richard's attention ✈️ Another Boeing 737 MAX software issue An autopilot-related software problem Why the timing during a go-around matters Boeing's workaround Could simulation and AI catch more problems before deployment? ✈️ Aeroplan refreshes its U.S. credit card 15% savings on Air Canada flight rewards Stacking the discount with Priority Rewards Fourth Night Free on hotel redemptions Fourth Day Free on car-rental redemptions Why Ed thinks Aeroplan keeps finding ways to appeal to U.S. travelers ✈️ Can you have too many premium seats? American and United's A321XLR configurations Why premium-heavy planes may require ballast Extra weight means extra fuel How ballast could affect the XLR's range The economics of long, thin routes ✈️ How long is too long on a single-aisle plane? Seven-hour transcons Potential eight- and nine-hour XLR flights Richard wants a widebody Ed cares more about the seat ⏱️ Episode 456 Timestamps 4:32 – Bilt adds Amtrak as its 26th transfer partner 7:46 – Follow-up, restaurant eggs and Richard's Cracker Barrel problem 13:07 – Julian's completely normal Maldives–Lapland–Iceland honeymoon 15:01 – Points Path discounts for M2G supporters 16:33 – Citi Double Cash + Strata Elite: a better way to earn American miles? 23:03 – Another Boeing 737 MAX software issue 25:37 – Aeroplan's refreshed credit card and stackable award discounts 29:00 – Fourth Night Free hotels and Fourth Day Free car rentals 31:46 – Why premium-heavy A321XLRs may need ballast 35:53 – Would you fly eight or nine hours on a single-aisle plane?

Joining us on this episode of Living Off Rentals is Maria Laoang, our Airbnb Manager who's been overseeing the day-to-day operations for my short-term rental business, Dune Dwellings, for the past two years. Maria is a virtual assistant (VA) from the Philippines who manages our team of 3 full-time customer service team members. Together, they run the day-to-day operations of our Airbnb business.  Listen as she shares how her background in customer service led her to Airbnb management, her responsibilities, and what it means to hire for ownership rather than tasks. She also gets into what onboarding and training VAs look like in practice, how something as simple as a daily Slack recap can keep a whole team on the same page, and just how many moving pieces a short-term rental operation actually juggles, from guest services and cleaning to maintenance, vendors, systems, processes, and more. If you're looking to scale up your Airbnb operations with a virtual team, this one's for you! Enjoy the show! Key Takeaways: [00:00] Introducing Maria Laoang and her role as virtual rental manager [04:21] Maria's background in customer service and training [07:30] Responsibilities as a virtual short-term rental manager [08:18] Improving systems, SOPs and processes [10:28] The difference between a team member and a manager [13:28] How Maria found the job opportunity [15:15] Why clearly defining the role matters when hiring [19:17] The right time to hire a virtual team member [21:19] Language and communication in the Philippines [26:41] Building the onboarding and training process [31:37] Using Slack as the day-to-day communication hub [34:16] Advice for rental property owners thinking about hiring virtually [35:25] Being ready to delegate and build systems [37:54] Rewarding your team as owners [39:52] Outro Show Links: Living Off Rentals YouTube Channel – youtube.com/c/LivingOffRentals  Living Off Rentals YouTube Podcast Channel - youtube.com/c/LivingOffRentalsPodcast  Living Off Rentals Facebook Group – facebook.com/groups/livingoffrentals  Living Off Rentals Website – https://www.livingoffrentals.com/  Living Off Rentals Instagram – instagram.com/livingoffrentals  Living Off Rentals TikTok – tiktok.com/@livingoffrentals  Want to start investing in short-term rentals? Book a call to see if my STR Blueprint program is a good fit for you: livingoffrentals.com/call   

Enjoy the What's Bruin Show Network!Multiple shows to entertain you on one feed:Support WBS at Patreon.com/WhatsBruinShow for just $2/month and get exclusive content and access to our SLACK channel.Twitter/X: @whatsbruinshow        Instagram: @whatsbruinshowCall the What's Bruin Network Hotline at 805-399-4WBS (Suck it Reign of Troy)We are also on YouTube HEREGet Your WBSN MERCH - Go to our MyLocker Site by Clicking HEREWhat's Bruin Show- A conversation about all things Bruin over drinks with Bruin Report Online's @mikeregaladoLA, @wbjake68 and friends!Subscribe to the What's Bruin Show at whatsbruin.substack.comEmail us at: whatsbruinshow@gmail.comTweet us at: @whatsbruinshowWest Coast Bias - LA Sports (mostly Lakers, Dodgers and NFL) with Jamaal and JakeSubscribe to West Coast Bias at wbwestcoastbias.substack.comEmail us at: WB.westcoastbias@gmail.comTweet us at: @WBwestcoastbiasThe BEAR Minimum - Jake and his Daughter Megan talk about student life and Cal Sports during her first year attending UC Berkeley.Subscribe to The BEAR Minimum at thebearminimum.substack.comEmail us at: wb.bearminimum@gmail.comTweet us at: @WB_BearMinimumPlease rate and review us on whatever platform you listen on.

Your newest hire has a Google Workspace account, a Slack login and a laptop. It never sleeps, and it never asks before it acts. So who owns its identity? Ron welcomes back Ashish Rajan, CISO at Techriot.io and researcher with AI Security Lab, who spent 17 years in identity, cloud security and security leadership. His take: vendors haven't solved AI identity, and the open questions are on your side, not the product's. Ashish got into identity after failing his OSCP three times: if he couldn't break in, he wouldn't let anyone else in. Now he reviews Ron's own setup, where Hacker Valley's AI agent, Jennifer Romani, has her own accounts just like an employee. Ashish explains how that call changes from a one-laptop small business to an enterprise where every developer's machine acts like five. They also cover the Gemini breach headlines, swarms of agents and AI Security Lab, which Ashish describes as what OWASP is for AppSec, but for AI security. The uncomfortable truth: defenders have the same models attackers do, but attackers don't wait for a pull request review. Ashish calls that a people problem, not a technology problem. He also shares the question he asks before handing anything to an AI agent: can this be reversed? Impactful Moments 00:00 - Introduction 02:30 - Busting a myth: AI identity isn't solved 05:30 - Three OSCP attempts and a pivot to IAM 07:00 - Why AI identity is more complex than ever 09:15 - Hot or not: giving an AI agent its own accounts 11:10 - One laptop, five machines in the enterprise 12:50 - AI gateways and developer observability 14:05 - Where Ashish would spend his AI security budget 18:20 - Why defenders don't hack themselves first 19:05 - The real problem is people 22:15 - Swarms of agents are coming 23:50 - What AI Security Lab is building 26:35 - Never share your credit card with AI 28:40 - Ron's callback: can it be reversed? Links Connect with Ashish Rajan on LinkedIn: https://www.linkedin.com/in/ashishrajan/ Listen to Ashish's first Hacker Valley Studio episode: https://www.podbean.com/pw/pbblog-bpaij-51b280 –  Check out our upcoming events: https://www.hackervalley.com/livestreams  Love Hacker Valley Studio? Pick up some swag: https://store.hackervalley.com  Become a sponsor of the show: https://hackervalley.com/work-with-us/ 

This week we're sharing one of our most favoritest episodes of Office Hours. Conrad and Gyi dig into marketing questions from lawyers just like you, and share tactical advice for growing your law firm.  By the way, did you know you can join the guys every week at 1pm ET for Office Hours and ask your marketing questions? Details below.  Conrad starts with some muckraking about Business of Law: EvenUp apparently paid to keep its competitors out of the event, and the event pulled their booths at the last minute. Our sponsor, Eve, got shoved out too, so we'll be over here drinking from our Eve water bottles in solidarity. EvenUp and National Trial Lawyers: you've got some explaining to do. Then the guys tackle a handful of listener questions. What actually goes wrong when you relaunch a website? Did leaving WordPress for Lovable wreck your rankings? How often should you rebuild? And should you post on your personal LinkedIn or your firm's page?  Plus, the Lunch Hour Legal Marketing Summit 3.0 is headed to Austin, May 4–6. Get ready, Texas, here we come! ----- The 2027 Lunch Hour Legal Marketing Summit is locked and loaded. Grab an early bird ticket and save some $$. Join Gyi and Conrad for Office Hours, Thursdays at 1 PM ET on LinkedIn, Facebook, and Youtube! Submit your questions in real time, send them in advance via our Slack channel or connect with us on LinkedIn. You can also submit questions via this handy dandy Riverside feature. Special thanks to our listeners who contributed questions to this week's episode: Kelly Roedema of RSH Legal; The Hometown Lawyer Joshua Hodges; and Mr. Mike Howard! A big thank you to our amazing sponsors: Eve, Lawmatics, CallRail, Juvo Leads, and ALPS Insurance!

#370: Will AI replace QA testers? Three years ago, manual testers were told to learn automation or find another job. Now the automation engineers are hearing the same thing about AI. Same speech, new audience. Here's the thing. Nobody can test everything. Somebody still has to decide what quality means for your product and which workflows can't break, and your team is shipping ten times the code it used to. The conveyor belt got faster. You still have two eyes. In this episode, we speak with Shubha Govil, Chief Product Officer at Sauce Labs, about why the testing roles stay but the work doesn't.   Shubha's contact information: LinkedIn: https://www.linkedin.com/in/shubhagovil/   YouTube channel: https://youtube.com/devopsparadox   Review the podcast on Apple Podcasts: https://www.devopsparadox.com/review-podcast/   Slack: https://www.devopsparadox.com/slack/   Connect with us at: https://www.devopsparadox.com/contact/

Send us Fan MailHe was about to quit.Then Microsoft called.Peter Swimm built a Slack bot called Howdy — and Microsoft acquired it.But what happened inside that acquisition is not the story most founders expect to hear.Because Peter came out the other side with a perspective on AI that most CEOs have never been told.He is not here to tell you AI will save your business.He is here to tell you why the way you are using it right now is probably making things worse.Automating a broken process does not fix the process. It just runs the problem faster.And most companies — right now — are integrating AI into exactly the wrong things.

Three months ago Dwarkesh, who has been posting incredible blogs and episodes about RL, posted a framing question for his video essay on RLVR which upset a lot of Computer Use folks:We are no strangers to learning in public and are no strangers to the stress of getting things wrong when you have a big platform. However, we were at Anthropic for the Computer Use launch, there for Claude Cowork with the first big podcast on it, organized the first Computer Use track at AIE presenting the state of the art, and were close to the OpenAI-Sky Software acquisition that now powers the complete domination of computer use that Codex enjoys today. This is why we're excited to bring you today's first guest, Ari Weinstein, cofounder of Sky and now leading all the amazing CUA progress that casuals might miss:Ari explains why Computer Use is now “180 degrees different” from where it was months ago, how agents are learning to debug and recover from failures, why combining screenshots with accessibility data, the DOM, Playwright, and generated code changes the speed equation, and why the next frontier is making agents literally superhuman at using software.OpenAI clones JevIn the second half, Nikunj Handa from OpenAI's API team breaks down the new developer stack: async tool calling, mid-turn steering, WebSockets, UltraFast inference, the Decisions API, prompt caching, pre-warming, compaction, and the Agents API. Given that we were the first Jev podcast, we particularly focus on the unusually fast sprint on the Decisions API:And why it is just a Luna wrapper for now but the team is motivated and egoless enough to clone what they consider to be good patterns.We discuss:* Why OpenAI thinks Computer Use has changed dramatically in just the last few months* Dots and what changes when every agent gets its own Linux computer* Why Computer Use can now complete some tasks faster than the average human* The path from human-level to “literally superhuman” computer use* Why modern agents are much better at debugging and recovering from failure* How screenshots, accessibility trees, the DOM, Playwright, and generated JavaScript work together* App Shots and why they give models much richer context than ordinary screenshots* Why Computer Use can close the loop between writing software and testing it* Trust, permissions, and safety when agents can make payments and operate websites* Async function calling and why models no longer need to stop reasoning while tools run* Mid-turn steering, WebSockets, and the architecture behind more responsive agents* UltraFast inference and how OpenAI is pushing frontier models toward much lower latency* The rapid internal story behind the Decisions API* Why Decisions API is more than structured outputs at low latency* GPT Live, fast tool calling, and real-time computer control* How OpenAI is already using Decisions API for support classification and internal workflows* Longer prompt caching, cache pre-warming, and cache-aware applications* Server-side compaction vs manual compaction for long-running agent threads* What should live inside an Agents API versus a developer's own harness* OpenAI as an “AI cloud” and the search for higher-level primitives beyond raw model APIsAri Weinstein* Product & Engineering, Computer Use at OpenAI* X: https://x.com/AriX* LinkedIn: https://www.linkedin.com/in/weinsteinari/Nikunj Handa* Product, API at OpenAI* X: https://x.com/nikunjhanda* LinkedIn: https://www.linkedin.com/in/nikunjhanda/Timestamps00:00:00 OpenAI DevDay: Dots, GPT-6.1, Agents API, and Decisions API00:02:52 Dots and Personal Cloud Computers00:04:59 Why Computer Use Is “180 Degrees Different”00:06:04 From Sky to Self-Debugging Computer Use Agents00:09:24 How Computer Use Sees and Operates Software00:12:09 From Faster Than Humans to Superhuman Computer Use00:16:03 Agents API: Trust, Permissions, and Safety00:17:31 Computer Use for Coding, Testing, and QA00:19:14 GPT-6 APIs, Async Tool Calling, and UltraFast Inference00:23:21 The Rapid Story Behind Decisions API00:25:32 What Decisions API Is and How It Works00:30:24 What OpenAI Is Building With the New APIs00:32:23 Prompt Caching, Pre-Warming, and API Performance00:35:20 Context Compaction for Long-Running Agents00:37:13 Memory, Higher-Level APIs, and the AI CloudTranscriptIntroduction: OpenAI DevDay and the New Agent StackVibhu [00:00:00]: Okay. We're very excited to be here. Today is OpenAI DevDay. Special podcastSwyx [00:00:08]: We're the first podcast after your livestream.Vibhu [00:00:10]: First podcast. We have Ari here, who leads the product and engineering team for Computer Use agents. Before we kick in and dive deep on Computer Use, you wanna give a quick recap? What was announced? What's the quick slew of announcements you guys had today?Ari Weinstein [00:00:24]: Yeah. yeah, it was a super exciting day. we just got out of the keynote. It was really sick. there were a bunch of Computer Use announcements that I think are worth thinking about. We have, Dots, which is the new, sort of personal assistant product, and, that has some really exciting Computer Use features. There's GPT-6.1 Sol, which is this amazing new model, that I think is particularly great for Computer Use ‘cause of, sort of the cost and speed, advantages. I think, I think we shared that it's, a fifth of the cost of Astra and a seventh of the cost if you're looking at Computer Use specifically, which is really amazing. sorry, there were so many things. I'm trying to sort through it.Swyx [00:01:02]: And the API.Ari Weinstein [00:01:03]: Agents API, which now has Computer Use in it, which is really cool, ‘cause now developers can build on the same Computer Use, that is part of Codex, and ChatGPT. and then there were some demos of our existing Computer Use features, like app shots, where you can take the context of something you're doing on your computer and bring it into Codex and ChatGPT really fast. And then, like, native Computer Use on your Mac, where Roman had it taking screenshots of his app, automatically, and he could do other things on his computer while Computer Use was using his applications. so yeah, really exciting keynote.Swyx [00:01:35]: And not to mention the Decisions API.Ari Weinstein [00:01:37]: Decisions API.Swyx [00:01:38]: Off the bat, are they all the same model? Like, this is. Or the same dataset distilled to different models?Swyx [00:01:44]: Like, basically, like, is Computer Use using Decisions API, or are they, like, kinda separate?Ari Weinstein [00:01:49]: So what's really cool about the Decisions API is it, you know, it has all these new capabilities. It does inference in parallel. it doesn't have reasoning. It's a smaller model, than the ones we use for Computer Use. and so those capabilities make it really fast.Dots and Delegating Work to a Cloud ComputerSwyx [00:02:07]: Yeah.Ari Weinstein [00:02:07]: They also make it a little bit less good at doing, like, long horizon, sort of sophisticated tasks. And so I think I would say it's still an open area of research for how we, like, bring those approaches together. But, yeah, I'm really excited to see what people build with the Decisions API.Vibhu [00:02:24]: One of the interesting things is Dots now have attached personal computers.Ari Weinstein [00:02:28]: Yeah.Vibhu [00:02:28]: So it seems like they're very much more persistent. You've been using them for a while. How should people push the bounds? Like, what should people aim for? What should they try? Personally, right now I use it for a lot of customer service. LikeAri Weinstein [00:02:41]: CoolVibhu [00:02:41]: “Oh, this was wrong. I don't wanna sign in. I don't wanna authenticate.” Find whatever and just get it fixed.Ari Weinstein [00:02:45]: Yeah.Vibhu [00:02:46]: How should we push further? What should people try?Ari Weinstein [00:02:50]: Dots Are a really cool product because each Dot has access to its own Linux virtual computer in the cloud, which is different from our other products. you know, traditionally, we've have access to a browser in the cloud, or it has access to your own computer, but now you get your own entire Linux computer in the cloud. And so it can run full desktop applications, and it can also use a web browser. And so, yeah, you know, I think the powerful thing about Computer Use and the reason why I think it's so, exciting is because it makes it so that the agent can do anything you as a, as a person can do, because all the software in the world was designed for humans, and now agents can use that same software, and you can delegate to the agent. So, yeah, like, anything that you would do on a computer, you can ask a Dot to do. Yeah, I think what particularly is useful is gonna really depend on who the end user is and what- what's valuable in their life. but yeah, I would just start by thinking about, like, one of the things that you spend time on and how could you delegate those to an agent.Swyx [00:03:47]: Yeah, a lot of flight booking and shopping and honestly even, like, playing a game or whatever, right?Ari Weinstein [00:03:52]: Totally.Swyx [00:03:52]: Yeah.Ari Weinstein [00:03:53]: Yeah, I don't know. For me, something I did recently, I've been working on. I've, subscribed to a meal prep service ‘cause I was trying to, like, eat healthy, you know? And I really like this meal prep service I found because it lets me customize the meals I order to, like, a high degree of granularity. So I can say, like, “I want this many grams of chicken and this many grams of rice.” but it was so complicated. It took me two hours to do an order, and I found that I could ask Computer Use to do it for me, and it did it in 15 minutes. so I actually saved two hours. it both did it eight times faster than I could, and it saved me two hours on GPT-6.1 Sol.Swyx [00:04:32]: Yeah.Ari Weinstein [00:04:32]: So those are the kinds of tasks that I feel like, are really powerful.Swyx [00:04:36]: As a creator, I can tell you automatically, immediately, my number one use case is automating YouTube.Ari Weinstein [00:04:40]: Nice.Swyx [00:04:40]: Because, YouTube doesn't expose a lot of things via API.Ari Weinstein [00:04:43]: Yeah.Swyx [00:04:43]: And you have to just put it in a VM and just, like, run it, for, like, let's say, let's say their AB testing feature or making community posts. None of this is available by API ‘cause they hate developers.Swyx [00:04:53]: Anyway, so,Ari Weinstein [00:04:55]: I've heard that from our developer experience team too. They use it with YouTube a lot. Yeah. It's really awesome.Swyx [00:04:59]: So I wanna draw for, you know. let's say, I wanna get a little bit spicy. One of our, the leading AI podcasts, our friends, is famous for saying that Computer Use hasn't advanced in the last two years.How Computer Use Has Changed in the Last YearAri Weinstein [00:05:12]: Yeah.Swyx [00:05:13]: Which is a very interesting statement, and I think you're one of the best people in the world to talk about this, like, how have things have progressed, right?Ari Weinstein [00:05:20]: Yeah. You know, they said that a few months ago, I think, and I hope they have a different perspective now because Computer Use is, like, 180 degrees different than it was.Swyx [00:05:26]: He's a, he's a tough guy to impress.Ari Weinstein [00:05:27]: Yeah, okay. well, we're working on it.Swyx [00:05:30]: But, you know, you worked on. You've, like, basically spent your whole career working on, like, some kind of computer automation, right?Ari Weinstein [00:05:34]: Yeah.Swyx [00:05:34]: Like shortcutsAri Weinstein [00:05:35]: YeahSwyx [00:05:35]: At Apple, and then Sky, and then, and then joining OpenAI. Can you draw, like, what your through line is for, like, what is driving you and what- you, what wasn't possible back then maybeAri Weinstein [00:05:47]: Yeah.Swyx [00:05:48]: And, like, what your sort of milestones were.Vibhu [00:05:49]: I guess to add on to that as a follow-up question, what's the major change from using Codex Computer Use from, like, last weekAri Weinstein [00:05:57]: YeahVibhu [00:05:57]: Through to today? Is it model? Is it dots? Is it harness? So all the history plus what really just changed in today's announcements?Ari Weinstein [00:06:04]: Yeah. On the through line, I guess I've always been excited about automation and helping people automate tasks because then you can, like, save time in your life and focus on things that are more important to you than, like, operating a computer very intricately. And so, yeah, that was why we worked on some of those products. I was at Apple before. we made a company called Sky. we ended up joining OpenAI, which is really exciting. and I think something that wasSwyx [00:06:27]: And almost like you have to hack around Apple until Apple was like, “Fine, like, we'll just hire you and you can just work on the inside,” right? Like.Ari Weinstein [00:06:35]: It was, it was a cool place to get to work. what was really interesting looking back at Sky is we were, we were working on Computer Use there as well, and the models were so much less capable. And now the models, just in the last one year, have become extraordinarily capable at Computer Use. I think the biggest delta that I see is before they could, like, reliably start tasks, but then they would run into problems, and now they're really good at debugging. They're really good at trying again, introspecting what is and isn't working. and I think we've also brought the Computer Use the Computer Use field itself has moved forward. I think we're using more techniques. now Computer Use, often writes code. So if you actually look at it in Codex and you expand the tool calls manually, you can see that it's not just doing one action at a time. It's actually writing JavaScript code that it executes, that the computer executes to perform sometimes many actions at once, which is a great, you know, speed up and great capability. We use more accessibility, sort of multimodal interfaces. So, the model may use screenshots, it may use accessibility, it may use Playwright. it can use a lot of different mechanisms, based on the task at hand. and then, yeah, the model acceleration has been, has been just amazing. So, yeah, what's different today? I think we're making computers better all the time, so I think just, like, one day's difference, is probably a little bit less consequential than, like, even the past month or the past two months. but, yeah, I think the Computer Use in Dot is really exciting as well as, the new model that we came out with.Measuring Computer Use and Improving the HarnessVibhu [00:08:03]: On the keynote, Tejal was mentioning 7x improvements in Computer Use speed, a lot better on a few benchmarks. How do you guys think about measuring it? Computer Use is one of those things where, as you say, you know, it's improvements over time.Ari Weinstein [00:08:20]: Yeah.Vibhu [00:08:20]: Is it harness? Is it model? Is it post-training?Ari Weinstein [00:08:22]: Right.Vibhu [00:08:22]: How do you guys look at it internally about measuring how good it is, and what were the changes with the new model?Ari Weinstein [00:08:29]: We actually have a bunch of different ways of measuring it, some of which are on different permutations and configurations of the harness. It's a bit of a complicated story because, you know, our production products have, you know, some more safety checks, and, you know, those are configured differently based on the needs of the, of the task at hand. So there's a lot of ways to measure it, but I think regardless of how we measure it, we find pretty consistent gains. and those gains are, sometimes in the harness and sometimes in the model. and yeah, I was really excited by this result that GPT-6.1 is even more cost-effective for Computer Use than its baseline cost improvement as compared to Astra. It's, like, really cool to see.Swyx [00:09:10]: Yeah. I mean, one of the visuals I really liked from the livestream was that, you're sort of improving the Pareto frontier of, your, curve, and there was a lot of talking about how you're improving it together with the harness.Ari Weinstein [00:09:24]: Yeah.Swyx [00:09:24]: Can you give some examples of aha moments that you had, whether it's on, like, model driving the harness driving the model, whatever?Ari Weinstein [00:09:32]: I don't mean to repeat myself, but I think, like, introducing more modalities has been really powerful.Swyx [00:09:36]: Okay.Ari Weinstein [00:09:36]: One more specific example of that is, in the past, I think we saw a lot of Computer Use, products had to spend a lot of time, like, scrolling, you know? So it would, like, take a screenshot. It would try to do something. It would be like, “Oh, I gotta, like, scroll down to the next page of results,” and then it would take a screenshot, and then it would try to do something. It would scroll down again. And so I think, with accessibility and other. and, direct access to the DOM and other things like that, now the language model can actually see, like, an entire page or an entire application. It can write code that can do multiple steps at once. And so I think those have been probably the biggest single aha moments. There's, like, a lot of tiny ones that are less exciting in comparison, but actually we do find also that a lot of speed improvements are driven by, like, a lot of little paper cuts that we gotta go in and introspect.App Shots, Accessibility, and Better Computer ContextSwyx [00:10:21]: Yeah. A lot of really hard engineering.Ari Weinstein [00:10:23]: Yeah.Swyx [00:10:23]: I mean, app shots in general, right? Like, I think people don't quite get the difference if. because there's, like, a nice visual in Codex when itAri Weinstein [00:10:30]: YeahSwyx [00:10:30]: When you take an app shot, but they don't maybe they get the difference that, you are able to actually drive each button and you have the, you have each text, in a very optimal representation.Ari Weinstein [00:10:40]: Yeah. Exactly. Yeah. It's kind of fun actually. If you wanna be, like, really nerdy about it, you can go into Codex, take an app shot by hitting the two command keys. So you grab the content from whatever app you're working with, bring it into the, Codex or ChatGPT chat. And then the. if you click on the attachment and you click on this, like, little tiny button in the top right, you can see the raw text and you see the raw accessibility representation. And yeah, we've put a lot of work into, puttingSwyx [00:11:04]: Just dumping everything out. Yeah.Ari Weinstein [00:11:05]: Dumping it out, but also making it token-efficient, doing it efficiently. There's, like, a bit of an art to it. And, you know, it turns out that the same technology that was invented for humans, you know, who maybe have accessibility needs, who wanna use a screen reader technology, that technology is really helpful for them to be able to use computers. It's also really helpful for LLMs to be able to use computers. So that's been, like, really fun to get to work on.Vibhu [00:11:27]: For context, I feel like a lot of people don't understand app shots. They don't even know it's a feature.Ari Weinstein [00:11:30]: Yeah.Vibhu [00:11:31]: It's when you double hit command, it pulls in what looks like a screenshotAri Weinstein [00:11:34]: RightVibhu [00:11:34]: And you're like, “Oh, why have I opened up just a screenshot and thrown it in?” No, it's actually pulling all the metadata, all the code, everything.Ari Weinstein [00:11:40]: Yeah, exactly. Yeah. So it's like, you know, if you take a screenshot of a webpage that has a link- The screenshot doesn't include where the link goes. It doesn't include, you know, maybe you take a screenshot of your calendar, the ca- event ti- titles are truncated, you know? But when you take an app shot, it gives, like, the language model, like, full context about everything and, that lets it, just sort of, like, do much more.Swyx [00:12:02]: Yeah. For those who wanna see more, Jason Liu, I invited him to do a full workshop on this, at AI Engineer.Ari Weinstein [00:12:07]: Amazing.Swyx [00:12:08]: Did a great job.Vibhu [00:12:09]: I have a broader vision questionToward Superhuman Computer UseAri Weinstein [00:12:11]: YeahVibhu [00:12:11]: On Computer Use agents. So your example of take a screenshot, scroll page, take a screenshot is where we were.Ari Weinstein [00:12:17]: Right.Vibhu [00:12:17]: Today, they can automate a lot. what are the bottlenecks? Is it models? Is it harnesses? What. Where do you see it going in, like, two years? Do you see it just running for hours? How do we get there? Any predictions on where Computer Use goes?Ari Weinstein [00:12:32]: Yeah. I mean, I think what's really crazy that I think, You know, the team's accomplished over the past couple of months is that now Computer Use is, like, faster at accomplishing tasks than, like, the average human probably in most cases. and I think that the next frontier is to have Computer Use be, like, literally superhuman in its performance where it actually is as fast or faster at using software than, like, expert Computer Users like us. and I think that'll be really consequential and exciting when that happens because I think we'll be able to all of a sudden build products, that, provide just much more real-time experiences. And I think it'll also. lowering the barrier to entry of, or the activation energy, I suppose, of using Computer Use I think will make us start to default to doing certain things in agents that we've become accustomed to doing manually. And I think that's exciting also ‘cause it'll save us a ton of time. and I think there's a, you know, there are a lot of different little paper cuts and bottlenecks that are sort of standing in the way of that. I think that there's, yeah, there's things on the model side, there's things on the inference side, there's things on the harness side, there's things in the, in the representation. You know, we find that as Computer Use gets faster, we're increasingly bottlenecked by just, like, the speed of doing an operation. Like, for example, you know, a non-trivial amount of time in our benchmarks of Computer Use tasks is actually, like, let's say you're automating a task on doordash.com. Like, a lot of the time is actually waiting for doordash.com itself to load, you know?Swyx [00:14:04]: Yeah, then you just write a wait and then you execute the wait.Ari Weinstein [00:14:07]: Yeah, totally. And you wanna get. Yeah, actually, it's actually really important that you get that de- like, you want as little delay as possible between when it finally finishes loading and when you go andSwyx [00:14:16]: YeahAri Weinstein [00:14:16]: Trigger the LLM to do the next action, which is actually- itself a statistical science.Swyx [00:14:20]: Like an event-driven way maybe to do that.Ari Weinstein [00:14:22]: When possible, you want it to be event-driven.Swyx [00:14:24]: JavaScript has some load events.Ari Weinstein [00:14:25]: And JavaScript has load events for. or the web browser has load events for web navigation, but there's other types of events that actually really can't be event-driven. So there's a lot of complexityVibhu [00:14:34]: The one that comes to mind is, like, chatting with customer service.Ari Weinstein [00:14:37]: Yeah.Vibhu [00:14:37]: Replies could take 30 seconds, could take three minutes.Ari Weinstein [00:14:39]: Oh, right.Swyx [00:14:41]: I have dealt with so many bots with Codex. it's great, but I also wonder if the other side knows that they're talking to a bot ‘cause I'm, like, answering in complete sentences. Like, I'm capitalized correctly.Ari Weinstein [00:14:50]: That's hilarious.Swyx [00:14:51]: Like, I'm giving full num- full reference numbers and everything. Like, it's too. it's clearly too good. I don't care. Like Like, I'm just, like, trying to get my support case.Vibhu [00:14:58]: I've prompted it to, like, you know, “Don't pretend you're a bot. Be very annoyed human.”Vibhu [00:15:02]: Short one-liners, likeSwyx [00:15:04]: YeahVibhu [00:15:04]: Push it, do all this. I also tell it, “While you're waiting for responses, like, use subagents to research better ways to figure out what we need.”Ari Weinstein [00:15:12]: Nice.Vibhu [00:15:12]: It's just, like, human little intervention.Ari Weinstein [00:15:14]: That's awesome. I also feel like half the time it's a bot on the other end, so now youVibhu [00:15:17]: YeahAri Weinstein [00:15:17]: Got the bots talking to each other.Swyx [00:15:18]: Yeah. I will also say, you know, like, you know, one milestone of Computer Use that we are, we're at now is, you know, three, four years ago, we were scared of hooking up LLMs to the, to the web and toAri Weinstein [00:15:31]: YeahSwyx [00:15:31]: To our, to our devices. And now I'm having it configure DNS for me.Ari Weinstein [00:15:35]: Wow.Swyx [00:15:36]: I'm having it pay my bills, and, like, really, like, tens of thousands of dollars of, like, stuff I'm just sending it over and yoloing with Computer Use and, like, you know, what's the, what's the worst thing that can happen?Swyx [00:15:48]: So that- that's all, that's all really good.Building Safely With Computer Use in the Agents APIAri Weinstein [00:15:50]: Yeah.Swyx [00:15:50]: I think now that you've. you know, obviously, you also have to dogfood your own products and all these things. Now that you've sort of released this in API, what are some pitfalls or tips that you wanna tell developers, because they're about to, I guess, encounter all this, firsthand?Ari Weinstein [00:16:03]: First of all, I'm just really excited that we brought Computer Use into the Agents API. I think this is, really great because obviously a lot of developers are building applications that wanna be able to work with third-party websites and services. And so Computer Use has this universality to it. It can work with anything. So now all of a sudden, developers can build using the same Computer Use implementation that we're building on. I think there's great work to be done if you wanna build your own Computer Use harness, but it's hard. And also, we train our models on our Computer Use harness, so there is, an advantage to using the one that's in distribution for the model. There actually might be a speed and cost and accuracy advantage. So I think it's really great for people to get to build on top of that. And, yeah, you know, I think kind of to the point that you were making, like, I think we're all sort of still in the process and maybe, like, some of us are ahead of many people in the world of, like, getting comfortable with this technology and trusting it. And so I think it's incumbent on us to, sort of build that trust over time by making sure we're building things that are reliable, by building, the right kinds of safety checks, by asking for the user's consent before doing something consequential like making a payment, by, asking, you know, maybe depending on the application, making sure you're only letting it access the websites or applications that it actually needs for the task. So that's, I think, something important to think about. but yeah, I'd really encourage people to try the new Agents API, build all kinds of cool stuff on it. We'd love to hear your feed- feedback if, you know, depending on how it goes.Vibhu [00:17:31]: Have you seen any changes in the way it affects dev workflows? So one of the things with dots is, you know, you're seeing it in Slack.Ari Weinstein [00:17:38]: Yeah.Vibhu [00:17:38]: You're seeing people use voice and build. the example Roman showed of change this app and send me screenshots along the way and all this.Computer Use for Testing and Closing the Software LoopAri Weinstein [00:17:46]: Yeah.Vibhu [00:17:46]: Is anything that you're seeing there in adoption about how people are using Computer Use for coding workflows? Any tips people should take from that?Ari Weinstein [00:17:55]: One of my favorite use cases for Computer Use actually, and one that we see a lot in the wild, is Computer Use letting the agent- actually test the software that the agent has built, which is far more consequential than it sounds. Because traditionally, you know, you'd build something in Codex and then the-- and the Codex builds it for you, and then you have to test it, and you are now like QA for the agent, right? So with Computer Use, you can complete the develop-- the software development life cycle, where, the agent can build software, it can test it. So I have a lot of fun, you know, building stuff, having the agent test it. By the time it comes to me, it's already working. I have, extra fun because sometimes I'm, like, developing Computer Use itself, and so now I have a Computer Use agent that's using my Computer Use agent that's using something else. so yeah, I really, I really think this is a super powerful class of use case.Swyx [00:18:44]: I have a visual play test skill that I've developed that, really catches a lot of design issues,Ari Weinstein [00:18:49]: NiceSwyx [00:18:50]: That, you know, normally when you just look at code, you wouldn't really pick it up. it's also really good for cloning apps, though. If you're using a shitty SaaS and you wanna kill the SaaS You just clone it screen by screen by screen. and Obviously, Computer Use can completely drive everything, take screenshots, note it down, and then clone everything with Codex.Ari Weinstein [00:19:06]: That's really cool.Swyx [00:19:06]: But yeah, thanks for all your progress. I think, that isAri Weinstein [00:19:08]: AbsolutelySwyx [00:19:09]: Our time.Nikunj Handa: What's New in the OpenAI APIAri Weinstein [00:19:10]: Yeah.Swyx [00:19:10]: This is not the last that we're gonna talk.Ari Weinstein [00:19:12]: Yeah, cool. This has been really fun. Thank you guys for having me.Swyx [00:19:14]: All right.Vibhu [00:19:14]: All right. Okay, we're a strict cutoff. We're just gonna dive right in.Nikunj Handa [00:19:17]: Let's do it, yeah.Vibhu [00:19:19]: Okay, so, Nikunj, we're very excited to have you. You shipped a lot on the API side, like we justNikunj Handa [00:19:25]: YeahVibhu [00:19:25]: Talked about with Ari. You can now build with Computer Use agents. Anything you wanna highlight, the API side of changes, and introduce yourself a little and what you do?Nikunj Handa [00:19:34]: Yeah, for sure. My name is Nikunj. I lead product for the API team. Been here for roughly three years. been working on launching models. I feel like that's just been, like, a thing, constant thing throughout my time, here at OpenAI. And, with every new model, we try to, like, basically work super closely with the post-training team, the research team, to figure out what's new in it. and then we, like, expose those capabilities in the API. so that's, like, the basic way of putting it. and if you just look at, everything that's new with GPT-6, the cool new capabilities that we launched were, firstly, async function calling. so what you see with, like a lot of the things that you're seeing in, like, Codex and Dots and everything is that tool calls take so long that you don't have to, like, pause the model's execution while, the tool is running. So you could just, like, kick off a tool call, keep running, keep reasoning, and then check back in. so we launched async tool calling. We launched, like, mid-turn steering, so now you can, like, inject messages while the model is reasoning, in the middle. so as your tool call finishes, you can put in that instructions.Async Tool Calls, Mid-Turn Steering, and WebSocketsSwyx [00:20:43]: And that's also partially a model alignment capability, right?Nikunj Handa [00:20:46]: Yeah.Swyx [00:20:46]: Like, they have to train in the ability to train.Nikunj Handa [00:20:48]: Exactly, yeah. AndVibhu [00:20:49]: I feel like we've had it in the app. You could always, as it's reasoning, you could steer.Nikunj Handa [00:20:54]: Yes.Vibhu [00:20:54]: It wasn't the best. It's gotten much better.Nikunj Handa [00:20:57]: Yeah.Vibhu [00:20:57]: Excited to see how it does this in versionNikunj Handa [00:20:58]: Yeah, and I like our mainVibhu [00:20:59]: And nowNikunj Handa [00:21:00]: Goal in, our main goal in the API is to, like, put things in the API once it's trained into the harness. And so we kinda wait for that moment until it's good enough. And a lot of that is, like, actually being powered by WebSockets, which we launched, a few, I wanna say months ago. And so WebSockets just opens this, like, whole bidirectional, like, communication thing with the model. This is not, the GPT Life thing. I'm just talking about GPT-6. and you can do all these, like, async tool calling, async reasoning, injecting messages. It's a really fun API to work on. I think, like, really enjoying.Swyx [00:21:33]: Yeah. This is why we are the engineering podcast, because we get to talk about WebSockets.UltraFast and the Inference StackNikunj Handa [00:21:36]: Yeah.Swyx [00:21:37]: This also pairs very well with UltraFast, right?Nikunj Handa [00:21:39]: Oh, yeah.Swyx [00:21:39]: Like, that is now, like, I think for the first time ever available in the API.Nikunj Handa [00:21:43]: Yes.Swyx [00:21:43]: Which is, which is basically the theoretical fastest speed you can ever get, Frontier of Intelligence.Nikunj Handa [00:21:49]: Yeah. It's been so exciting to work on that project. I think, before I go into the API, the most fun part of, UltraFast has been just watching the inference team cook with Astra. Like, they're just, like, constantly having these, like, Codex agents running, trying to, like, squeeze out more performance. And, I would say, like, at least for a couple of months, a lot of it was focused on efficiency and driving the cost down, which is how we, like, were able to cut the Luna price by, like, 80%. It was, like, a lot of that was driven by, like, all the inference improvements they landed. And then now they've, like, shifted gears towards, like, how can we make this run as fast as possible? And so UltraFast has just been, like, amazing to see on a mo- on a model like Astra. Like, to go that fast has been really cool. And yeah, WebSockets is like. actually it was like the first time we launched WebSockets, it was for GPT, 5.3 Codex Spark, which was. Can't believe we named a model that, but, you know, that's what we launched it for. And obviously, it helps so much because, like, you gotta have the tool calls. you had, like, really reduced the overhead, of going back and forth with tools. And so, WebSockets is awesome for that.Swyx [00:22:57]: Yeah. it's always cute to see, like, I have my reset usage limit, and then I have my Spark usage limit that I never use.Nikunj Handa [00:23:03]: Yeah.Swyx [00:23:04]: Like, it's there if I want it.Nikunj Handa [00:23:05]: I think it's gone finally.Swyx [00:23:06]: It's gone. It's gone, yeah.Nikunj Handa [00:23:07]: I know it's gone, so.Swyx [00:23:08]: Yeah. you're slowly killing off all the, you know, theNikunj Handa [00:23:11]: The old ones, yeah.Swyx [00:23:11]: Oldies.Vibhu [00:23:11]: This is a great week. I mean, it was the first time we had Frontier Intelligence at extreme speeds.Nikunj Handa [00:23:17]: Yeah.Vibhu [00:23:18]: People really liked it.Nikunj Handa [00:23:19]: Yeah.Vibhu [00:23:19]: SoSwyx [00:23:20]: YeahVibhu [00:23:20]: First time it comes back.Swyx [00:23:21]: Yeah. for, 5.3 Spark is explicitly attributed to Cerebras. You guys are not confirming or denying that, UltraFast is related to Ce- Cerebras, but people are. I'll just say that people do care and, are wondering about it. And you have your own silicon as well. elephant in the room, decision models.Decisions API: OpenAI's Fast Decision ModelNikunj Handa [00:23:38]: Oh, yeah.Swyx [00:23:38]: Decisions API. We were the first podcast to do a big Jev, deep dive with, Diogo, and I also, you know, featured him at AI Engineer. How quickly did you see Jev and go likeNikunj Handa [00:23:49]: Oh my gosh. Yeah.Nikunj Handa [00:23:50]: Yeah. Firstly, like, huge props to Diogo and, like, the Jev team for, like, really inspiring theSwyx [00:23:55]: YesNikunj Handa [00:23:55]: Like, whole segment in the market. Like, obviously Jev comes out, everyone's, like, losing their minds over it. Our users are, like, hitting us up. But also, like, our internal teams are like, “We need, like, a much faster classification system.” We can. I don't wanna, like, get ahead of some of the dots features that are gonna comeSwyx [00:24:16]: WhooNikunj Handa [00:24:16]: But you're gonna see, like, some cool, like, really snappy, fast things built on top of the decisions API. but, you know, like, yeah. Props to Jev for, like, inspiring this whole thing. obviously a bunch of people at OpenAI get nerd sniped by that, and they're like, “How can we, like, make this work? We're not gonna, like-”Swyx [00:24:33]: Okay.Nikunj Handa [00:24:33]: “. train a new model.” ButSwyx [00:24:34]: Like, four weeks ago, this was not on the dev radar, right?Nikunj Handa [00:24:37]: No, not at all. No.Swyx [00:24:37]: Okay.Nikunj Handa [00:24:37]: This is likeSwyx [00:24:38]: WowNikunj Handa [00:24:38]: Jev-inspired and, likeSwyx [00:24:40]: I think you are officially the first one to your lab to, like, clone and, adopt this.Nikunj Handa [00:24:44]: Yeah. Yeah. I feel like, OpenAI has such a strong, like, hacker culture and, like, people are just, like, they get excited about things. And so, guy from inference, this one awesome guy from, the infra team are like, “ this is amazing. We're gonna, like, hack on it.” They build a prototype, it, like, works, and now we- we are just, like, hill climbing on latency and trying to make this as fast as possible, and we wanna, like, launch it in the coming days. so as soon as we hit our, like, latency target, we'll try to get this out.Vibhu [00:25:13]: It's interesting. At the same time of hacker culture, you also, as Sam said, like 99%, one of the most reliable APIs withNikunj Handa [00:25:20]: Mm-hmmVibhu [00:25:20]: I think probably the most usage, which is your team directly. how should people see decisions API? I feel like a lot of people saw Jev, heard the buzz, haven't built with it. You're making it very mainstream.What Decision Models Are Good ForNikunj Handa [00:25:32]: Mm-hmm.Vibhu [00:25:33]: What should people see it as? How should they use it?Nikunj Handa [00:25:36]: Yeah. I think the main use cases we've seen is, like, really fast classification. all the Computer Use demos have been amazing and really cool. I think there will be limitations, of course, in terms of, you know, having Astra, like, write, like, a JavaScript-like script to control your computer, versus having Luna pick, like, one action at a time. I think, it's not gonna be at the same intelligence level, but, like, maybe there's some Computer Use tasks that this is good enough for. So excited to see that come through. the other cool prototype I've seen internally is people hooking it up with GPT Live. So GPT Live is like, you know, our bidirectional, like, real-time,Swyx [00:26:14]: VoicingNikunj Handa [00:26:14]: A- API. And, it's built on this, like, model of front-end models and back-end models. So GPT Live is this, likeSwyx [00:26:20]: Think or talkerNikunj Handa [00:26:21]: Super fast. Yeah, think or, talker thing. So GPT Live is the talker, super fast, really good at delegation, and you have something like Astra sitting at the ba- at the back. But tool calling has always felt, like, really slow in GPT Live. and so people have been, like, putting together these, like, tool calling demos of GPT Live controlling a computer, and it just feels like so much more snappy and natural. So I'm, like, kinda excited to see, like, what people do with Live and with Luna on decisions API. so that'll be pretty exciting. Yeah.Swyx [00:26:55]: So I wanna iron this out for people, especially from the product side, because a lot of people have been putting out Jev clones. There's been about 100 in the last two weeks.What Makes a Decision Model DifferentNikunj Handa [00:27:01]: Oh, really? That's amazing.Vibhu [00:27:03]: The first couple days.Swyx [00:27:04]: But like, it. Like, they can clone a Jev API, which is honestly structured outputsNikunj Handa [00:27:09]: YeahSwyx [00:27:09]: Which OpenAI was first to.Nikunj Handa [00:27:10]: Yeah.Swyx [00:27:11]: Right? So, like, I think let's iron out for people what is a decision model, as far asNikunj Handa [00:27:16]: YeahSwyx [00:27:17]: As far as, like, what is important? It is not just latency. It's not just structured output, right? Because I could just have Luna as it'- The decision model is priced the same as Luna, right?Nikunj Handa [00:27:26]: Mm-hmm.Swyx [00:27:27]: Have turned off reasoning and then have structured output. Do I have a Jev? you know, no, right? And that's theNikunj Handa [00:27:33]: YeahSwyx [00:27:33]: That's the realVibhu [00:27:34]: There's a confidence there.Swyx [00:27:35]: Yeah.Nikunj Handa [00:27:36]: Yeah, totally. I think, the way that. So we haven't trained, like, a new model for this.Swyx [00:27:40]: Yeah.Nikunj Handa [00:27:40]: We're, like, building this purely on top of the same Luna weights that we have.Swyx [00:27:44]: Oh.Nikunj Handa [00:27:44]: So yeah. This is, like, really just Luna. And, on top of that, what you're doing is you're constraining. So, like, structured output's a big part of it. you're really optimizing the inference stack to, like, get very fast on TTFD. And because you can have multiple questions, what you do is, like, you basically run those in parallel,Swyx [00:28:05]: As a batch.Nikunj Handa [00:28:06]: Yeah. You run those in the-- as a batch. you-- All sorts of, like, inference techniques people are working on to try to make it as fast as possible. But I'd say, like, at least our implementation of it at the start and this first version is, like, zero-shotting this on top of Luna, to see how it goes. And obviously, you wanna, like, put it out there. Like, this is OpenAI's, like, classic iterative deployment thing. Put it out there, see what people think, and then, like, we'll make more model improvements, as needed. so yeah. That's, the decisions API.Swyx [00:28:38]: Yeah. And, obviously as a benefit, you have vision. They don't have vision, right?Nikunj Handa [00:28:42]: That's true.Swyx [00:28:42]: Obviously, Jev's comes withNikunj Handa [00:28:43]: Yeah. Like, we get it for free with Luna. Yeah.Swyx [00:28:45]: Yeah. I do think that, like, you know, some of the innovations, it sounds like, it's still to come if it's still the same Luna weights, which is, like, the confidence stuff, like, the in calibration is something that we've talked about on the podcast with, benchmarking calibration. ‘Cause basically, the whole point is that RLHF kind of collapses you towards what you want to hear.Calibration, Architecture, and the Open Research QuestionsNikunj Handa [00:29:03]: Yeah.Swyx [00:29:03]: But, like, not actually, like, what the amount of confidence is.Nikunj Handa [00:29:06]: Yeah. Yeah, totally. I'm eager to see how it pans out. Maybe there's, like, gonna be. These are gonna be, like, the key areas where we may have to, like, hill climbSwyx [00:29:15]: YeahNikunj Handa [00:29:15]: With the, with the future model release. But, yeah.Swyx [00:29:18]: And then architecture-wise, the other thing that's in the debate, obviously, you-- Nobody knows because Jev doesn't talk about it, but the two speculations are, one, maybe diffusion model instead of autoregressive.Nikunj Handa [00:29:28]: Mm-hmm.Swyx [00:29:29]: But you are able to achieve the parallel, generation in your way. And then the other one is some mech interp type thingNikunj Handa [00:29:37]: Mm-hmmSwyx [00:29:37]: That you're, like, analyzing the activations and then just outputtingNikunj Handa [00:29:40]: That would be coolSwyx [00:29:41]: The weights.Nikunj Handa [00:29:42]: Yeah.Swyx [00:29:42]: Which, like, you guys have all done the research on this. People have speculated.Vibhu [00:29:45]: There have been demos onSwyx [00:29:46]: YeahVibhu [00:29:46]: Both of these as well. I think Gemini shared a Gemini diffusion, Gemma diffusion on a Jev-style output.Nikunj Handa [00:29:53]: Oh, sick.Vibhu [00:29:53]: And, interp people have also, you know, pulled out interp from a middle layer, but this is all speculation.Swyx [00:29:59]: It's just like, what are you trying to aim for, right? Because you can achieve the API. Everyone can achieve the API. It's actually pretty trivial. But, like, then there's the speed, then there's the accuracy, then there's the other calibration features.Nikunj Handa [00:30:11]: Mm-hmm.Swyx [00:30:11]: I don't know what else.Nikunj Handa [00:30:13]: Yeah. Yeah. No, totally. It's so cool that this, like, whole space has been kicked off now and people are gonna do so much cool stuff and everyone's gonna learn from each other. And, yeah, I'm excited about it.What Developers Should Build NextVibhu [00:30:24]: I feel like being on the platform team, a lot of your job is to empower builders.Nikunj Handa [00:30:27]: Mm-hmm.Vibhu [00:30:28]: What do you think people should build with decisions API and also Computer Use agents? Any stuff that you've- been building with internally that you think really opens up after the new change?Nikunj Handa [00:30:39]: Yeah. okay, let's think. decisions API, use cases internally have been pretty obvious. Like, the user ops team was, like, jumping on it. We were like, “We gotta classify all of our support tickets.” what else came up? obviously, there were, like, the really cool GPT Live demos. I'm sure, like, the Codex app team might, like, pick this up and try to do something cool with it. So, you know, like, this whole thing started, like, a week ago, so it's, like, very early andSwyx [00:31:06]: Oh, one week.Nikunj Handa [00:31:07]: We're excited. Yeah. Yeah, pretty much.Vibhu [00:31:08]: There was a big push in, evals, LLM as a judge having really low latency there.Nikunj Handa [00:31:13]: Right. Yeah. That'll be interesting to see. and then, with the Agents API, we have-- we're basically, like, having a bunch of first-party products, like, at OpenAI built fully on top of it. we've had the Codex security stuff that just went out that's fully built on top of, the Agents API. We have, sort of the-- we- we are having, like, a meetings type of thing launching today.Agents API and OpenAI's First-Party ProductsSwyx [00:31:40]: Mm-hmm.Nikunj Handa [00:31:40]: I think there was, like, a demo. do you remember, like, the plugin extensions when Sam was showing it? There was, like, a demo for, like, you're in a calendar, you can sort of, like, have your meeting notesSwyx [00:31:51]: Like, drop into a singleNikunj Handa [00:31:52]: Flow into like your spaceSwyx [00:31:52]: Like, Google Docs type thing.Nikunj Handa [00:31:53]: Yeah.Swyx [00:31:54]: Right?Nikunj Handa [00:31:54]: And so the-- all of that stuff is, like, fully built on top of, the Agents API. and yeah, I'm, like, just excited to see. Like, we're just getting this out, and let's see what people build on top of it.Vibhu [00:32:04]: I think you showed it off very well. The whole edit spaces, pages, collaborate, add in your dot. Like, that's a lot, soNikunj Handa [00:32:12]: YeahVibhu [00:32:12]: There's a lot of inspiration people can go to.Nikunj Handa [00:32:14]: Yeah. All possible with Astra, you know. Like, thing- things just move so fast now. LikeSwyx [00:32:19]: YeahNikunj Handa [00:32:19]: People go from idea to execution so quickly, it's amazing.Swyx [00:32:23]: Is there something that you want, people to focus on to give you feedback? Like, what-- like, you know, maybe you're just putting this out there and you want-- and there's, like, a fork in the road and you want developers to help you decide.Responses API Performance and Long-Lived CachingNikunj Handa [00:32:35]: So I think Agents API and decisions API, they are like, these are our newest products. Would love, like, any and all feedback on that to figure out where to take them. I think, over here, we're, like, very open on Responses API, which is sort of like our workhorse over here. like, really focused on performance right now, and the performance comes in, like, two main ways. first is just, like, latency. We've been, like, rewriting the whole Responses API stack to, like, make it as fast as possible from a TTFT perspective, DVD perspective. So there's like-- that, like, continues to be, like, a main area of focus for us. The second thing we've been trying to do is, like, really go deep on caching, particularly with these, like, personal agents that are, you know, like, basically, like, a single thread that just goes on and on forever. We've been, trying to, like, really up our game on caching. We provide now guarantees of, like, cache hits within, like, 30 minutes. We're actually, like, we-- for one of our users, we just launched, like, a much longer cache window. So we have, like, a 12-hour caching guarantee, that we offer so that you have, like, guaranteed cache hits forSwyx [00:33:40]: Is that a public API?Nikunj Handa [00:33:42]: Not yet. That's in preview.Nikunj Handa [00:33:43]: We're gonna, like, try to get that out to everyone as soon as possible. But, like, just pay a little bit more for the cache write, and we, like, guarantee, like, cache reads for, like, a much longer period. So even if, like, your instinct thread, for example, like, you just, like, do something on it and then come back to it, like, three to four hours later, you- you're still getting the caching performance out of it. And launchedVibhu [00:34:04]: And you cut the cost there quite a bit too, right, with the new model?Nikunj Handa [00:34:07]: Oh, yeah. That's right.Vibhu [00:34:08]: Like, 25% cheaper, soNikunj Handa [00:34:08]: Yeah, with, like, driving down cache reads, yeah.Cache Pre-Warming and Cost-Efficient Agent ThreadsVibhu [00:34:10]: For builders, they should implementNikunj Handa [00:34:13]: YeahVibhu [00:34:13]: Because it's significantly cheaper.Nikunj Handa [00:34:14]: Yeah. Yeah. Just, like, building your apps with, like, to be very cache aware and sort of, like, use our prompt diagnostics or cache diagnostics tool to figure out, like, where things are dropping off. And, so the caching part is, like, really important. yeah, I also wanted to talk about pre-warming. We have that in the API now. So, like, if you know that, “Hey, I'm gonna get a cache,” like-- sorry, “I'm gonna get this prompt. I just wanna, like, pre-warm the cache, pay, like, the cache write fee right now, and then, like, have it sort of ready to go for the next 30 minutes for whenever.”Swyx [00:34:49]: And it can spawn many instances of that thread.Nikunj Handa [00:34:51]: Exactly, yeah.Swyx [00:34:52]: Yeah.Nikunj Handa [00:34:52]: You can just keep going and haveSwyx [00:34:54]: Yeah, just keep messing with the prompt thereNikunj Handa [00:34:55]: Tons and tons of that. and so, yeah, like, I'm very excited about getting feedback on, like, the low-level performance things that we can keep making Responses API the most performant and reliable way to, like, build on top of an LLM. And then you basically have our, like, new products where I'm just looking for, like, any and all feedback.Swyx [00:35:15]: Yeah, just use it, right?Nikunj Handa [00:35:16]: So yeah, just useSwyx [00:35:16]: Tell us what toNikunj Handa [00:35:17]: Yeah. Define our roadmap for us, please. So yeah.Swyx [00:35:20]: I think for me, the caching thing, great, right? Like, obviously very needed. But at the end of the day, you're still bumping up against a million-token contextCompaction and Managing Million-Token ContextsNikunj Handa [00:35:28]: Mm-hmmSwyx [00:35:28]: And that's probably not gonna change for the foreseeable future.Nikunj Handa [00:35:31]: Mm-hmm.Swyx [00:35:31]: Like, you still need good compression.Nikunj Handa [00:35:33]: Yeah.Swyx [00:35:33]: What is the best practice there?Nikunj Handa [00:35:34]: Yeah. Yeah, totally. so firstly, OpenAI has its own, like, proprietary compression, compSwyx [00:35:40]: Which is inNikunj Handa [00:35:41]: Compaction.Vibhu [00:35:42]: Compaction.Swyx [00:35:42]: It's in the agents.Vibhu [00:35:43]: It's in the API.Nikunj Handa [00:35:43]: Yes.Vibhu [00:35:43]: Agents API.Nikunj Handa [00:35:44]: Yeah.Swyx [00:35:44]: You decide for us, right?Nikunj Handa [00:35:45]: Yeah, exactly. So in the Agents API, it comes built into the harness. and if you're in Responses API, there's, like, two ways of doing it. One is what we call server-side compaction, which is you basically tell Responses API that if you ever hit this threshold of tokens, just auto-compact it and, like, go back, or sorry, like, reduce the context, being used. And the second way is, like, /compact, which is, like, if you want full control. So you can, like, /compact at any timeSwyx [00:36:15]: I hear youNikunj Handa [00:36:15]: Have your own logic on when to, likeSwyx [00:36:17]: It's not AGI.Nikunj Handa [00:36:18]: It.Swyx [00:36:18]: It's not AGI.Nikunj Handa [00:36:19]: Yeah. Yeah.Swyx [00:36:20]: Yeah. But it, I meanNikunj Handa [00:36:20]: YeahSwyx [00:36:20]: It is the manual override.Nikunj Handa [00:36:21]: Yeah, it is the manual way. And like, I don't know, but a lot of the big coding agents like to do it manually. I mean, like, if you look at the Codex implementation of it in the Code- open source Codex harness, you can see that they use /compact and do it. and, there's also, like, new, by the way, new compaction techniques that we are working on. Some of them you will be able to see in the Codex harness. Like, it's already implemented in the Codex harness. And so, they're like some file-based, systems that we are, like, experimenting with. So yeah, lots of cool stuff going on around in compaction as well.Swyx [00:36:57]: Cool. we are running out of time.Nikunj Handa [00:36:59]: Okay.Swyx [00:36:59]: I think you've talked about, a lot about performance and talked a lot about, the new APIs that you're launching. Can you give us any other hints as to things that you're interested in as far as the future of the platform is concerned?Higher-Level Platform Primitives and the AI CloudNikunj Handa [00:37:13]: We're obviously like very low level. Like, I used to work at Stripe before this, and, at Stripe a lot of the game was like building these higher level primitives and products on top of like the core payments primitives. and, I'm always like curious about what the best way of doing that is in AI. And I think we've had a couple of attempts at that. We like had launched assistance API like way back in the day, and like wasn't really the right fit. We were sort of like going off with this like Agents API, and, it gives you the codex harness, but like where's like the, what's the right amount of flexibility to give in that? That's like an open question. Like how should we like have memory walls and like all of these like higher level like API objects to take away, also like to abstract away more, like storage concepts. Like this is like a whole, like, there's a whole space that I'm like very curious about figuring out how we design. I think a lot of things in AI are just have a low-level API primitive and see an example harness and go and have your coding agent implement that. But how much of that do we build into the API is like a constant question that I'm thinking about.Swyx [00:38:24]: Yeah.Nikunj Handa [00:38:24]: So I don't know if folks have thoughts on that. If anyone has ideas, it would be super interesting to hear.Swyx [00:38:30]: Yeah. The analogy I always bring back to, and we'll end there, is, you're building an AI cloud, right?Nikunj Handa [00:38:35]: Mm-hmm.Swyx [00:38:35]: Like, which is, something that, Sam said a year agoNikunj Handa [00:38:38]: Mm-hmmSwyx [00:38:38]: Where, and you're, it's almost like you're kind of doing the AWS invention and you have to do, okay, this is EC2Nikunj Handa [00:38:45]: YeahSwyx [00:38:45]: And this is S3, and this is like. But you're doing the AI-native versions of each of these.Vibhu [00:38:48]: There are a lot of analogies, so you're pre-warming caches for stuff that you know will beNikunj Handa [00:38:53]: Yeah.Vibhu [00:38:53]: And it's nice that it's all exposed to buildersClosingNikunj Handa [00:38:56]: Mm-hmmVibhu [00:38:56]: ‘cause it just opens up ways that you can build new things.Nikunj Handa [00:38:59]: Yeah, absolutely.Swyx [00:39:00]: Okay.Vibhu [00:39:00]: Awesome. WellSwyx [00:39:01]: That's everything.Nikunj Handa [00:39:01]: Thank you, guys.Vibhu [00:39:02]: Thank you.Nikunj Handa [00:39:02]: Yeah. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.latent.space/subscribe

Leonardo de Moura created Lean and co-created Z3. ---This episode is sponsored by Parallel.Parallel, where agents find answers: web search, extraction and deep research APIs built for AI agents.Start free with the Parallel MCP server and $5 of credits every month: https://parallel.ai/mlst?utm_source=creator&utm_medium=podcast&utm_content=MLST---Tim Scarfe talks with Leo about how Lean escaped its original audience, why dependent types and Mathlib made it useful to working mathematicians, and what happens when formal verification leaves the lab. De Moura explains the small trusted kernel and independent checkers, and gives his account of the recent Collatz incident, in which a purported proof was accepted by both Lean's official kernel and Nanoda, apparently by exploiting a different bug in each.---TIMESTAMPS:00:00:00 Cold open: the green checkmark can lie00:00:59 Cathedral or bazaar: who controls Lean's core?00:04:55 Why Lean's core stays small and protected00:08:07 The Slack purge, Brandolini's law and the Lean FRO00:11:12 The Collatz exploit: two kernels, two bugs00:16:44 More kernels, reward hacking and safety by transparency00:21:04 Sponsor: Parallel00:21:59 Kim Morrison, Claude and the zlib proof00:25:25 Can we specify complex systems?00:28:04 Specs change: proofs are cheaper to redo with AI00:31:27 From Lean 1 to Lean 400:34:57 Dependent types in plain terms00:37:25 Lean 4's extensibility and Mathlib's growth00:41:44 Mathlib as infrastructure: Formal Frontiers00:44:15 Creativity, abstraction and nut-sniping00:48:46 Breadcrumbs, not learning: what AI agents lack00:53:03 Competence without comprehension, and verified guardrails00:56:21 Is the human still the author?01:01:44 AlphaProof, LLMs and why certificates still matter01:06:38 What's next for Lean, and its legacy01:11:42 How to start learning Lean---REFERENCES:tool:[00:00:48] Leanhttps://lean-lang.org/[00:01:24] Mathlibhttps://github.com/leanprover-community/mathlib4[00:12:09] nanoda_libhttps://github.com/ammkrn/nanoda_lib[00:12:19] CollatzLeanhttps://github.com/xrchz/CollatzLean/blob/a79357462a33d2a6babd4cf6c8d8bcd25425d653/README.md[00:13:06] Lean issue 14576https://github.com/leanprover/lean4/issues/14576[00:13:21] Lean pull request 14577https://github.com/leanprover/lean4/pull/14577[00:13:45] nanoda_lib pull request 22https://github.com/ammkrn/nanoda_lib/pull/22[00:15:33] Lean comparatorhttps://github.com/leanprover/comparator[00:18:02] Lean4Leanhttps://github.com/digama0/lean4lean[00:19:50] ARC-AGI-3https://arcprize.org/arc-agi/3[00:21:59] lean-ziphttps://github.com/kim-em/lean-zip[00:29:45] CompCerthttps://compcert.org/[00:29:45] seL4https://www.sel4.org/[00:30:23] Z3https://github.com/Z3Prover/z3[00:38:10] Veilhttps://github.com/verse-lab/veil[00:38:10] Velvethttps://github.com/verse-lab/velvetorganization:[00:00:52] Lean FROhttps://lean-lang.org/fro/[00:42:39] Mathlib Initiativehttps://mathlib-initiative.org/about/person:[00:05:11] Ilya Sergeyhttps://ilyasergey.net/[00:10:31] Joachim Breitnerhttps://www.joachim-breitner.de/[00:32:58] Adam Chlipalahttps://adam.chlipala.net/[00:38:42] Kevin Buzzardhttps://www.ma.imperial.ac.uk/~buzzard/[01:10:16] Terence Taohttps://terrytao.wordpress.com/book:[00:08:19] The Proof in the Codehttps://us.macmillan.com/books/9780374620059/theproofinthecode/other:[00:10:05] Brandolini's lawhttps://en.wikipedia.org/wiki/Brandolini%27s_law[00:45:33] A new result on unit distanceshttps://openai.com/index/model-disproves-discrete-geometry-conjecture/[01:01:08] Fermat's Last Theorem formalisationhttps://imperialcollegelondon.github.io/FLT/paper:[00:34:36] The Lean 4 theorem prover and programming languagehttps://doi.org/10.1007/978-3-030-79876-5_37---RESCRIPT:https://app.rescript.info/share/7d3d4a0059443236a01f6c9acbf4db58https://app.rescript.info/api/public/sessions/b007264c0ce89047/pdf

My newsletter: https://simonowens.substack.com/   Startup CPG didn't begin as a media company. It started with Daniel Scharff inviting a few people from the consumer packaged goods industry to meet up at a bar in San Francisco. But those informal gatherings eventually grew into something much larger: a 40,000-member Slack community, dozens of in-person events, a podcast, webinars, newsletters, social channels, and an awards program for emerging brands. Along the way, Scharff realized he had effectively backed into building a media company — one whose audience consists of the founders, investors, retailers, and service providers powering the next generation of food, beverage, beauty, and wellness brands. In a recent interview, Scharff explained how the pandemic helped transform a local events company into a national community, why Startup CPG keeps most of its products free while generating the bulk of its revenue from sponsorships, and how its events are increasingly designed to connect emerging brands directly with the retailers and investors who can accelerate their growth.  

This Is WholeLife: Future - Ken WetmoreFuture looks ahead to what God may be calling WholeLife Church to become—and the courage it takes to move forward. Through John 21, we're reminded that following Jesus may require new approaches, unexpected changes, and a willingness to grow. The future isn't about having every answer; it's about faithfully taking the next step and continuing to follow Jesus.Let us know your thoughts by reaching out and joining the conversation with your questions and comments using the information below:

In this episode of Disguised Coverage, Anthony is joined by Taylor Kyles to break down the details that will decide the Buffalo Bills vs New England Patriots in week 3. Schemes, structures, players, matchups, tendencies, and more.0:00 | Opening thoughts5:21 | One thing to fix for the Patriots 11:00 | Difference in Drake Maye this year vs last year17:43 | Bills pass rush vs Patriots pass protection28:2332| Patriots coverage 31:45 | Dalton Kincaid vs whoever40:09 | James Cook vs the Patriots run defense54:56 | Drake Maye and the deep ball1:03:02 | One Pie Pizza1:05:17 | Closing thoughtsPresenting Sponsor - One Pie Pizza https://www.onepiepizza.com/ Elevated Catering of Buffalo https://elevatedcateringbuffalo.com/Tell them Cover 1 and Disguised Coverage sent you!!Follow on Twitter: https://twitter.com/Pro__AntFollow on Bluesky: https://bsky.app/profile/proant.bsky.socialCover 1 would love to hear your thoughts on this topic and the show in general. Comment below and let us what you think!One Pass Premium Membership - https://www.cover1.net/onepass/Don't miss out on our PREMIUM CONTENT-Access to detailed Premium Content.-Access to our video library.-Access to our private Slack channel.-Sneak peek at upcoming content.-Exclusive group film room sessions & much more.Thank you for watching this video, we can't do it without the support of our fans. If you have any ideas for content you'd like to see from us, comment below. -DOWNLOAD THE COVER 1 MOBILE APP!► Android: https://play.google.com/store/apps/details?id=com.coverapp► iOS: https://apps.apple.com/us/app/id1532587486► Subscribe to our YouTube channel - https://www.youtube.com/channel/UClL6eJS1s8xmRoYRQbYgxQQ?sub_confirmation=1► Subscribe to our Cover 1 Network channel - https://podcasts.apple.com/us/podcast/cover-1-sports/id1370162953 -Cover 1 provides a multi-faceted analysis of the NFL and NFL Draft including Podcasts, Video blogs, Commentary, Scouting Reports, Highlights, and Video Breakdowns. NFL footage displayed is not owned by Cover 1. -Follow Us HereTwitter: https://twitter.com/Cover1Instagram: https://www.instagram.com/@Cover_1_Facebook: https://www.facebook.com/Cover1NFL/Official Merchandise:https://teespring.com/en-GB/stores/cover-1The Cover1.net website and associated Social Media platforms are not endorsed by, directly affiliated with, maintained, authorized, or sponsored by the NFL or any of its clubs, specifically the Buffalo Bills. All products, marks, and company names are the registered trademarks of their original owners. The use of any trade name or trademark is for identification and reference purpose

Thanks Pressable for supporting the show! Get your special hosting deal at https://pressable.com/wpminuteBecome a WP Minute Supporter & Slack member at https://thewpminute.com/supportThis episode of The WP Minute brings together Alex Panagis, Brian Coords, Andy Peatling, and Mike McAlister to tackle a big question: How do we get AI agents to actually use WordPress?The conversation starts with a problem that could have major implications for WordPress: when people ask AI agents to build a website, WordPress isn't always the recommendation. The group digs into why that is, what agents actually need from WordPress, and whether the platform is moving quickly enough.They explore AI-generated websites, discoverability, public benchmarks, design systems, MCP, the WordPress Abilities API, WP-CLI, Gutenberg, and the growing tension between WordPress's flexibility and the simplicity agents are looking for.The bigger question isn't just whether AI can build a WordPress site. It's whether WordPress can become a platform that AI agents actually want to build with.TakeawaysAI agents aren't consistently recommending WordPress.WordPress needs to become easier for agents to discover and use.AI-generated sites are changing what people expect from website builders.Public benchmarks could show whether WordPress is improving.Design systems give agents reusable building blocks.MCP could change how agents interact with WordPress.WordPress needs stronger opinions about how agents should use the platform.The Abilities API could become an important foundation for agentic WordPress.WordPress's open-source architecture creates both opportunities and challenges.The future may involve agents working alongside WordPress rather than entirely inside Important LinksWooCommerce Developer Resources: https://developer.woo.com/Ollie: https://olliewp.com/Miles: https://buymiles.ai/WordPress.com: https://wordpress.com/WordPress.org: https://wordpress.org/WP-CLI: https://wp-cli.org/Subscribe to The WP Minute: https://thewpminute.com/subscribeThe WP Minute Slack: https://thewpminute.com/support ★ Support this podcast ★

Winston Marshall says politeness is killing Britain. In this interview, he walks through how the country got here — two London synagogues firebombed in a single month while the prime minister is "very reluctant" to say "Islamism," more immigration in 20 years than in the previous 2,000, grooming gangs he traces back to the 1950s — and why he believes a right-wing government coming in in 2029 would have just five years to deliver, because if it isn't done, "it's kind of over." His message to Americans: "If America falls, the Western project falls." There are big things happening at Blaze, and we'd love for you to join us. You can join now at https://Get.BlazeTV.com/Nick and use promo code “NICK” to get $20 off! ----- SPONSOR: Alliance Defending Freedom Gender ideology has reached almost every area of public life, including schools, sports, medical ethics, and religious freedom. Alliance Defending Freedom has created a free five-part video series in which experienced attorneys explain how this ideology is affecting the culture and how you can advocate for your beliefs and freedoms with facts fortified by grace. Get the free series sent to your inbox at https://JoinADF.com/Nick ----- SPONSOR: Perplexity AI Perplexity Computer orchestrates all the leading AI models and automatically chooses the right one for every step of a project, so you are not bouncing between five different tools to finish one job. Dictate the whole project, from market research and financial projections to full pitches and presentations, and Computer keeps going until it is finished. It connects to Gmail, Slack, and the work tools you already use. Start your free trial of Perplexity Computer today at https://PPLX.ai/MTA and experience the next phase of AI. #ad ----- GET YOUR MERCH HERE: https://shop.nickjfreitas.com/ BECOME A MEMBER OF THE IC: https://NickJFreitas.com Instagram: https://www.instagram.com/nickjfreitas/ Facebook: https://www.facebook.com/NickFreitasVA Twitter: https://twitter.com/NickJFreitas YouTube: https://www.youtube.com/@Nickjfreitas TikTok: https://www.tiktok.com/@nickjfreitas3.0 00:00 – From Mumford & Sons to "my calling to serve God is to serve Britain" 07:25 – "Politeness is killing the country," and a PM "very reluctant" to say "Islamism" 14:54 – Why Britain voted Churchill out right after winning the war 19:50 – America was settled, not built by "a nation of immigrants" 25:54 – More immigration in 20 years than the previous 2,000 30:08 – English patriotism is back, but no one agrees what Britishness is 38:10 – As Christianity fades in Britain, the vacuum is "being filled by Islam" 43:34 – Deport 1.2 million and end welfare for foreigners 49:28 – Boris Johnson "turned it up," and both major parties started collapsing 53:02 – How long does Britain have? 57:52 – Why proportional representation under Andy Burnham would end "the British project" 1:03:33 – The Manchester Arena guard who didn't act for fear of being called racist 1:08:07 – Why The 2029 Election Is Very Hard to Call 1:11:02 – "If America falls, the Western project falls" This is Episode 589 of Making the Argument, published September 29, 2026. Learn more about your ad choices. Visit megaphone.fm/adchoices

Most leaders who carry everything already know they're doing it. Alli Murphy did. Four years ago on this show, she named her own patterns, from perfectionism to finding it easier to advocate for her team than for herself. She had a coach. It still nearly broke her. Alli is back to talk about what finally changed. She describes becoming what she calls the Chief Everything Officer, the leader that every decision and fire drill runs through. Then came the weekend a friend joked to her husband on a chairlift that Alli must be a figment of his imagination, since nobody had ever met her. She explains why "just say no" advice falls flat for leaders who were rewarded for the opposite, and why she runs mini-experiments instead, such as a week with no Slack or email in the first hour of the day. She also shares the question her coach asked that she couldn't answer: "What's your definition of enough for a workday?" For HR leaders who are a one-person department, Alli gets practical. List everything you own and question what's only there out of habit. Decide what enough looks like. Use a shutdown ritual so tomorrow starts with a plan instead of an inbox. About our guest Alli Murphy is a leadership coach and speaker who helps women directors and above step out of the Chief Everything Officer role. Through her business, Work & Thrive HQ, she runs The Elevate Lab, a 90-day coaching program, and a free community called the Non-Negotiables Club. Before going out on her own, Alli was a managing director and podcast host at Engage for Good, where she spoke on 700-person stages, led a corporate mastermind, and partnered with brands like Subaru, Hasbro, and Disney. She's a former collegiate athlete, grew up in Mexico City, and lives in Bend, Oregon. She's currently writing a book. TIMESTAMPS 00:00 Intro 02:15 Why Alli walked away from her managing director title 05:00 Why the ambition gap is really a support gap 06:10 How an acquisition made her the Chief Everything Officer 07:20 The chairlift joke that pushed her to get help 11:15 What's your definition of enough for a workday? 15:00 Where the pattern started 18:45 Process integrity vs. outcome integrity 21:05 How you still help when you stop doing it yourself 23:05 Why knowing your patterns isn't enough 25:55 What an HR department of one can do 29:10 Coach the leader or change the company? 30:20 What kept her from leaving sooner 32:05 Where to start A QUICK GLIMPSE INTO OUR PODCAST Podcast: Transform Your Workplace, sponsored by Xenium HR Host: Brandon Laws In Brandon's own words: "The Transform Your Workplace podcast is your go-to source for the latest workplace trends, big ideas, and time-tested methods straight from the mouths of industry experts and respected thought-leaders." About Xenium HR Xenium HR is on a mission to transform workplaces by providing expert outsourced HR and payroll services for small and medium-sized businesses. With a people-first approach, Xenium helps organizations create thriving work environments where employees feel valued and supported. From navigating compliance to enhancing workplace culture, Xenium offers tailored solutions that empower growth and simplify HR. Whether managing employee relations, payroll processing, or implementing impactful training programs, Xenium is the trusted partner businesses rely on to elevate their workplace experience. Discover how Xenium can transform your workplace: Learn more Connect with Alli Murphy: Website LinkedIn Instagram Newsletter The Elevate Lab Connect with Brandon Laws: LinkedIn Instagram About Connect with Xenium HR: Website LinkedIn Facebook Twitter Instagram YouTube

RVs are homes that go 60 miles an hour. That changes everything about what goes inside them.Chris sits down with Sean Petterson, CEO of Supersede, a company combining recycling and manufacturing in an unexpected way - turning recycled plastic into structural building materials. Supersede started with boats, where wood has an obvious problem - boats get wet!From there, the company moved into RVs, where the materials face constant movement and thermal cycling, on a production line that can build an entire RV in a couple of hours.Sean also explains the thinking behind Supersede's manufacturing model, including why he'd rather build 10 smaller plants than one big one.In this episode, find out:How running production lines in mirrored pairs cuts the distance operators walk across the floorWhy an RV, built to go 60 miles an hour, is a harder test for a material than a house that never movesHow Supersede built its own ERP with zero software developers, piecing it together through Slack, Jira, and GitHub insteadHow a pre-sold capacity threshold - already dropping fast - decides when Supersede builds its next plantHow embedding machine vision and LiDAR on the line replaces a QA machine that would otherwise cost far moreWhy Sean thinks manufacturers who didn't start using AI a year ago are already a decade behindEnjoying the show? Please leave us a review here. Even one sentence helps. It's feedback from Manufacturing All-Stars like you that keeps us going!Tweetable Quotes:"If you hadn't gotten on the AI bus 12 months ago, you're a decade behind." - Sean Petterson, CEO of Supersede“A big contributor to those inefficiencies is, frankly, just legacy that gets embedded.” - Sean Petterson, CEO of Supersede“In manufacturing, things can move slow, and we just have the unique benefit of making sure that we're investing effectively, but very efficiently.” - Sean Petterson, CEO of SupersedeLinks & mentions:Supersede is a manufacturing company turning recycled plastic into structural building materials, starting with its Marine Board product for the marine and RV industries.Harmoni is a factory orchestration platform that connects what's happening on your shop floor with the systems you already use, from your machines and operators to your ERP, giving your team one real-time view of production.PTC's Industrial Newsletter - a quick hit of clarity on how design, manufacturing, and service data can work together for manufacturing leaders looking to modernize.Make sure to visit http://manufacturinghappyhour.com for detailed show notes and a full list of resources mentioned in this episode. Stay Innovative, Stay Thirsty.

In this episode of the Impostor Syndrome Files, we talk about the power of our thoughts and why they can feel so convincing in the moment. My guest this week is Kay Tear, a business psychologist, executive coach and author who helps people better understand how their minds work.Kay challenges the way we think about impostor syndrome, resilience and our reactions to change. We explore how our state of mind shapes our experience and why two people can face the same situation and walk away with completely different interpretations.We also discuss what happens when we become consumed by fearful thinking and how we can loosen its grip. Kay shares why noticing our thoughts, creating space for fresh thinking and taking one small action can help us move forward with greater clarity and confidence.About My GuestMost leadership training is boring — and it's aimed at the wrong problem entirely. It teaches skills to people who are already too overwhelmed to take them in, and calls that development.  So Kay Tear built Business Reimagined to work with organisations that want to liberate their people from overwhelm, burnout and disengagement. They want to create an exceptional employee experience with unique yet proven approaches that redefine development and wellbeing. A Business Psychologist for over 20 years and an executive coach, Kay helps leaders learn about the human operating system — not behaviour, not competencies, but the inner world actually running the show underneath. Her approach is ruthlessly simple by design, because overwhelmed leaders don't need more content, they need less noise. Kay is the author of Overcome Imposter Syndrome and Overcome Anxious Attachment.~Connect with Kay:LinkedIn: https://www.linkedin.com/in/kaytear/ Amazon: https://www.amazon.co.uk/stores/Ms-Kay-Tear/author/B0F67BGCQ7 Website: www.businessreimagined.co.uk~Connect with Kim and The Impostor Syndrome Files:Join the free Impostor Syndrome Challenge:https://www.kimmeninger.com/challengeLearn more about the Leading Humans discussion group:https://www.kimmeninger.com/leadinghumansgroupJoin the Slack channel to learn from, connect with and support other professionals: https://forms.gle/Ts4Vg4Nx4HDnTVUC6Join the Facebook group:https://www.facebook.com/groups/leadinghumansSchedule time to speak with Kim Meninger directly about your questions/challenges: https://bookme.name/ExecCareer/strategy-sessionConnect on LinkedIn:https://www.linkedin.com/in/kimmeninger/Website:https://www.kimmeninger.com

Nubank spent thirteen years building one of the most loved financial brands in Latin America, growing past 140 million customers across Brazil, Mexico, and Colombia. This month, that brand entered the US for the first time, launching Nu Global alongside a dedicated US product built around a Nu Account and a no-annual-fee credit card. Ethan Eismann is the executive tasked with making that experience work. As Nubank's first Chief Design Officer, reporting directly to founder and CEO David Vélez, Eismann oversees design strategy across the company's entire product ecosystem. He joined Nubank in mid-2025 after two decades leading design at Google, Adobe, Uber, Airbnb, and Slack.

Godni Amir is the Founder and Executive Director of A Free Bird, whose mission is "to empower children affected by cancer to discover their inner artist." Godni joins host Steve Boland to talk about building and sustaining a nonprofit powered almost entirely by volunteers. After being inspired by his voice teacher's experience with cancer, Godni launched A Free Bird 18 years ago with a single Craigslist post and a free first event at Bloomingdale's, and has since been honored six times by NYC Service for volunteer engagement. He shares how the organization now coordinates 20 to 60 volunteers and interns from around the world across eight departments, using tools like Slack, Salesforce, and Google Workspace (plus a custom community dashboard in progress) to protect volunteers' time so they can focus on relationships. Godni talks about recruiting for passion first, pairing newer volunteers with experienced ones, and holding to clear policies and procedures while treating volunteers like family. He stresses the ideas of offering job references, learning opportunities, and appreciation events long after their service ends.  Listen now by clicking the player above or subscribe to the podcast on your phone for automatic updates. Get more details on how to subscribe on our podcast page. Please consider leaving a review on Apple Podcasts or your platform of choice. Thanks!

We are excited to have Anthropic share their latest AI x Finance work at AI Engineer New York, coming up in 2 weeks!In case you've been under a rock, here's a non-exhaustive list of what Anthropic has been shipping since closing the largest fundraise of all time in May at $47B ARR:* June: Launched Claude Tag and Sonnet 5 and Fable 5* July: Opus 5, /checkup. crossed $65B ARR* Last month: Fable/Mythos 5.1, and EFS (upcoming pod)* IPO target $2T, end 2026 ARR estimated $100B* Cowork/chat merged before did* Claude Mods* Dario endorses the same Pacing the Frontier message cosigned by all labs* Last week: Opus 5.5, Plugins portal, Cloud Sessions/Claude Projects* Today: Sonnet 5.5!Today's episode should catch you up, with Thariq Shihipar, the explainer-king of Anthropic, who we last caught up on Fable launch day with The Field Guide to Fable:The Future of Mutable SoftwarePay special attention to Claude Mods (especially the cheatsheet):In general this is also the inverse of the other viral tweet from Thariq:Cloud Brain, Local HandsAnd give a try to Claude Projects:The “hands” terminology is not just an analogy for the local/cloud paradigm that is being built up at frontier coding agent companies like Cognition, but is ALSO particularly relevant to the safety systems discussions that we'll be discussing with Anthropic in an upcoming episode as they prepare to pace to frontier with responsible AI deployment.For those who want Thariq's writing tips we teased at the start of the pod, watch the full video here:From the rapid rise of Claude Code to a future where agents can rewrite their own harnesses, collaborate across teams, and operate across cloud and local environments, the way we build software is changing extraordinarily fast. In this episode, Anthropic's Thariq Shihipar joins swyx and Vibhu to unpack how power users are actually working with Claude Code today, why prompting remains a high-skill discipline, and where Anthropic thinks the agent harness is headed next.We go deep on Claude Code's evolving interface: Ask User Question and elicitation, artifacts as persistent generative interfaces, Claude Tag for multiplayer agent workflows, Projects, model effort, implementation notes, and the new Claude Mods system for customizing the harness itself. Thariq explains why Claude.md may eventually disappear, why the smartest model could also become the cheapest model for many tasks, and why mutable software could become a new paradigm for how applications are built and customized.The conversation then turns to agent security and Anthropic's “Pacing the Frontier” argument. Thariq walks through recent incidents where agents discovered unexpected ways to communicate, exploit infrastructure, reverse-engineer benchmark scorers, and chain vulnerabilities together. We discuss sandboxing, prompt injection, autonomous agents, interpretability, constitutional classifiers, probes, fallbacks, Auto Mode, and why securing increasingly capable agents may become one of the defining engineering problems of the next few years.We discuss:* Why agentic coding went from controversial to the default in less than a year* Why prompting is still one of the highest-leverage skills for working with Claude Code* How expert users build a mental model of Claude and what it can reliably one-shot* Why discovering your “unknown unknowns” matters more as agents become more capable* Artifacts as persistent, generative interfaces between humans and agents* How Claude could split into a cloud-based “brain,” local or remote “hands,” and dynamic interfaces* Claude Tag, Projects, and multiplayer agents and how collaborative agent workflows could evolve* Why spending more time on the initial prompt can dramatically reduce wasted agent work* When to use low, medium, high, or max effort for different engineering tasks* Why frontier models may eventually outperform smaller models on both intelligence and token efficiency* Why implementation notes can expose decisions the model considered but chose not to make* Why Claude.md may eventually disappear — and why starting without one can sometimes be better* Claude Mods: customizing the execution loop, UI, subagents, routing, and behavior of Claude Code* Model routers, forked agents, and supervisor agents that automatically improve agent workflows* Why Claude Mods may be an early preview of “mutable software”* The bitter lesson of harness engineering and why agent architectures go out of date so quickly* How Claude Tag is becoming an organizational harness for multiplayer work* Why giving agents access to company data creates an enormous new security surface* The Exploit-Bench incident where agents discovered ways to communicate and collaborate* Why agents hacked Hugging Face for scorer code rather than benchmark answers* How agents chained sandbox and infrastructure vulnerabilities in unexpected ways* Why increasingly capable agents make traditional security assumptions harder to maintain* The argument behind Anthropic's “Pacing the Frontier” proposal* Why software engineers are increasingly doing two jobs: engineering and keeping up with AI* Constitutional classifiers, probes, and fallbacks and what interpretability looks like in production* How Auto Mode checks whether an agent's actions actually match the user's permissions* Why Thariq can see serious AI risks while still having a relatively low p(doom)Thariq Shihipar* X: https://x.com/trq212* LinkedIn: https://www.linkedin.com/in/thariqshihiparTimestamps00:00:00 Introduction00:04:12 Ask User Question and the Future of Agent Interfaces00:08:29 Artifacts, Projects, and Multiplayer Agents00:15:37 Prompting as the Core Claude Code Skill00:21:52 Context, Effort, and Smarter Model Usage00:28:10 Is Claude.md Going Away?00:32:49 Claude Mods: Customizing the Claude Code Harness00:36:35 Model Routing and the Rise of Mutable Software00:44:40 The Bitter Lesson of Harness Engineering00:50:49 Claude Tag as an Organizational Harness00:55:59 Pacing the Frontier and Autonomous Agent Security00:58:22 Agents Hack Hugging Face for the Scorer01:05:34 What Happens When Agents Need More Compute?01:10:32 AI Coding Is Changing Faster Than Engineers Can Keep Up01:17:17 Probes, Fallbacks, Interpretability, and Auto Mode01:28:32 AI Risk, p(doom), and Closing ThoughtsTranscriptIntroduction: Life at Anthropic and the Pace of ChangeSwyx [00:00:00]: We're here in the studio with our friend Thariq from Anthropic, and I guess generally the Claude Code, I-- there's, there's so much, merging of boundaries and you've been so on top of everything since you joined Anthropic. You have been early to Claude Code itself, but then also, and you've told that story in other podcasts, and you've also been talking about seeing like an agent. Most recently you did the top AIE World Tour talk, Field Guide to Fable, which obviously you guys launched Fable, so that was-- that's cheating. And mostly you most recently also launching Claude Tag, and we're also gonna be talking about Pacing the Frontier. There's a lot going on in Anthropic. I guess top of the question is, what's it like being at Anthropic when there's so much going on?Thariq Shihipar [00:00:48]: I think that It is, like. I think you can get whiplash sometimes. I think, like, going. When I joined Anthropic, I joined because of Claude Code. Like Claude Code had just come out and I was like, “This is so good.” And Opus 4 to me was like just, I could not imagine, like, how good it was? And that was, like, a real moment for me. But I was, like, trying to convince, like, my startup friends to use agentic coding, and they're like, “Oh, no, like, our engineers don't think it's good enough,” or something. And I was like, “That's insane.” and now you, like, fast-forward, 12 months, less, and, like, it's just like, yeah, the default way that everyone codes, right? And I think that, like, just having to go from, like, selling it to, like, now, teaching people how to be. make the most use of it and be more efficient and things like that is just like a big, like big change. And, yeah, I think, like, it's just hard to stay on top of everything as a human? Like, I think things happen so fast and likeSwyx [00:01:51]: You just throw more agents at it.Thariq Shihipar [00:01:52]: Yeah, like that's like the agentic stuff scales much better than the, like, human stuff where it's like, oh, like, there are three things happening right now and, like, they're all emergencies and, like, how do you, like, respond to it? Yeah.Teaching People to Use Claude CodeVibhu [00:02:05]: What do you split your time on? You do a lot of technical writing, engineering work.Thariq Shihipar [00:02:10]: Yeah, so I think that, like, when I joined the Claude Code team, I wanted to teach people how to use Claude Code and I think that, like, that has been something that, like, I thought, like, maybe I would spend a little bit of time on it or, like, I'd, like, do. I was spending some time on the agent SDK first, and I wasn't exactly sure, like, how the bitter lesson would go, when it comes to, like, harnesses, right? Like, I think sometimes we were like, “Oh, like, what's after Claude Code?”? And so initially I was like, I just wanna teach people how to use Claude Code and make it easier to use Claude Code. And I think that has just, like, as the harnesses have gotten better and better, that's like the dominant problem now is, like, how do you use the agents, right? Like, it's like such a high skill expression thing. So I do that and then I do engineering work. I give talks, but I think, like, when I'm doing engineering work, my goal is to take that feedback that we get from users and also, like, then be able to talk about, like, hey, how to use Claude Code to do engineering. So there's like a good loop there. Yeah.Swyx [00:03:07]: Yeah. I'll-- For listeners, we'll attach, the talk that you did with Sarah for the Dev Writers, meetupThariq Shihipar [00:03:13]: Oh, yeahSwyx [00:03:13]: Which we talked a little bit about, well, first you do the work and then you talk about the work.Thariq Shihipar [00:03:16]: Right.Swyx [00:03:16]: Something like that.Thariq Shihipar [00:03:17]: Yeah.Swyx [00:03:17]: It's sow and reap orThariq Shihipar [00:03:19]: Yeah, reap and. Sow and reap.Swyx [00:03:21]: Something like that. Something like that. Yeah, so, and then just to preview a little bit, we are gonna talk about the evolution of the harness. It has come a long way from just being a CLI. We're gonna talk about, Claude Mods, which is starting to leak today, because you couldn't keep it secret.Thariq Shihipar [00:03:36]: Yeah. yeah.Swyx [00:03:39]: Yeah, there's, there's a lot, there. I think you started off with, like, adding ask user question tool, which people love and hate.Thariq Shihipar [00:03:48]: Yeah.Swyx [00:03:48]: Like, I thought it was, like, very innovative, and then now I have, like, my own version. You have your Interview Me version.Thariq Shihipar [00:03:55]: Yeah.Swyx [00:03:56]: And, yeah, everyone just has, like, their own stuff. And, like, it no longer matters ‘cause now you're supposed to, write prompts that create other prompts and loops and all these things.Ask User Question and Human-Agent InteractionThariq Shihipar [00:04:05]: Sure, yeah.Swyx [00:04:06]: So what's the state of the art, today? Like, what are people. what are you, like, telling people to do today?Thariq Shihipar [00:04:12]: Yeah, ask user question was the first time that the model was good at elicitation. I think this was, like, an emergent behavior that I, like, wanted to see if the models could do. I have, like a human-computer interaction background, so I, like, did that in undergrad and grad school. And so this was like. I think it's like human-agent interaction to me, like, trying to figure out, like, how can the agent communicate with you and extract, the requirements, right? I think that, like, one of the things about, like, that's difficult as Claude Code has gone broader and broader is that everyone has, like, their own way of using it, and it's very hard to, like, change the default behavior. So for example, like, if someone asks Claude Code to do something,Thariq Shihipar [00:04:59]: Sometimes they just want them to do the work, ‘cause they're, like, maybe a very good prompter, and sometimes they want. like, are not good at prompting? And you need. like, the agent needs to, like, clarify? And so that's, like, a good split. Like, and the ask you the question tool like, splits along that side where, like, are-- do you feel like you're good enough to instruct the agent as it is, or is the agent able to, like. does the agent need to, like, pull out more requirements and, like, collaborate with you more and really understand your preferences?Thariq Shihipar [00:05:27]: I, on the whole, believe that pretty much everyone is more on the latter than the former, that they, like, have more ambiguity and they know less than they want, than they, like, think they know about the problem. but, like, it's like a interface design problem to make that easy? And so, like, if you're designing a problem, like, or if you're going through a problem, like, things like what's the schema or, like, what's the call stack and things like that are really important. like, the details in the design are important. Ideally, you want to figure out some of these, like, hard problems ahead of time before starting implementation. And yeah, that's why they call, like, unknowns, right? And so I think that this will forever be, like, a skill in agentic coding is, like, figuring out your unknowns. So, like, because even if the model is, like, super intelligent- It, like, needs to know what you want? And, like, you have preferences. like, you need to like, pull the, pull that out. and so that's, like, I think how I'm, what I'm pushing. the question then is, like, how does the agent interact with you? And I think that has been HTML, has been, like, the big way of doing that. And we've recently added artifacts, right? And artifacts, I think we've done a bad job of, like, or, like, I've done a bad job of, like, explaining how to use them fully. We have a lot of property capabilities. They have a database associated with them? And so every artifact can store and write persistent data. They can, like, feed back into Claude? And so, like, one thing that, like, people are not doing yet that I'm trying to, like, encourage is, like, this idea of a dashboard artifact. So you have, like, Claude working on a project long-term. Maybe it's like a kanban or something. it can store that kanban data in its database. Multiple Claudes can access that data via, like, the artifact MCP, and, like, that artifact can, like, talk to those Claudes as well. And so, like, the. We're building the primitives for you to be able to have this, like, generative interface via artifacts that will, like, let you surface more of that rich detail from the agents. And I think that, like, almost everything with agents right now is, like, this problem of, like, you think what you want, but you don't really know what you want, and, like, the agents need a lot of detail, and collaborating with them in the loop is really important. And so artifacts are, like, the, like, way that we're trying to evolve there. But there's a lot of work to do because it's so much more complicated than, like, a multiple-choice question? there's a lot more, like, detail in terms of, like, diagrams and code snippets and schemas or, like, whatever it is for that problem. But, like, artifacts is, like, the mo-more AGI-pilled way of, like, doing ask user question. So yeah.Artifacts as the Interface to the HarnessSwyx [00:08:15]: I think one thing that's unclear to me about these, the artifact stuff is, like, what feedback should go in through the artifact and what feedback should go through a Claude, a chat? Because the more AGI-pilled one is to just feed everything to the Claude.Thariq Shihipar [00:08:29]: I think the more AGI-pilled one is to go through the artifact. Like, and I think that, like, we imagine in the limit, I think that artifacts will be your interface into the harness? You can, like, comment on this, like, live, like, document of your plan, of the work. you can see maybe, like, multiple agents and different agents are doing this, and that artifact is built for the current work that you're doing, right? And so, like, each one has, like, slightly different. I think we're still, like, getting there from, like, an infrastructure perspective. But yeah, I think, like, on-the-fly interface for your harness is probably where things are headed.Vibhu [00:09:03]: Is there a version of it that's an abstraction from CLI or chat and you. Because right now, a lot of it is, okay, you're interfacing with Claude Code, you're having HTML given back for a mockup. It's pretty rich. There's diagrams. Artifacts are ways to connect these together. Why not just do everything that way?Separating Brain, Hands, and Surface UIThariq Shihipar [00:09:22]: Then it becomes, like, separating out, like, where is the inference happening? Where is the intelligence happening? Where is the work happening? like, I think this is like, difference between, like, or, like, some of the distinction between local and cloud, right? And so, I think right now, if you use Claude Code, it's, like, local and, like, you can spin off remote control, for example, to get some cloud behavior, or you can spin off Claude Code in the cloud, right? We're moving towards a place where instead of Claudes, like, you message a local Claude, it starts a session locally and it executes, to more like you have a Claude that you message that's in the cloud that's running. it can run, like, local, or, like, cloud sessions. This is how Claude Tag works. But, like, over time, we'll add, like, local hands as well. And so, like, local hands will be the ability for that agent to access your computer if it's online, and be able to, like, work there. And so it can spin off many different subagents. It can, like, commu- those subagents can communicate with each other, and that's where the artifact comes in to display all of that work. So you can imagine, like, the. You're separating out these things. So there's, like, the surface UI display that's an artifact and hosted somewhere and has a database and everything. There is the inference intelligence, right, that's happening on the cloud, and you don't have to worry about shutting off your computer or whatever, right? and then there's the, like, hands. Like, and it can be local, it can be in, like, a remote sandbox or wherever you need your work to be done. That's like unpackaging, like, the Claude Code experience right now where, like, right now it all happens in one place, right? So.Multiplayer Agents, Claude Tag, and ProjectsVibhu [00:11:00]: How do you see, like, the multiplayer side of that? So say teams want to work in this way. Right now it's very individual, but how do you see the future of multiplayer? Like, right now, I guess there's Claude Tag, which is a version, but.Thariq Shihipar [00:11:12]: We're launching projects. And so projects is the, like, this abstraction that's like Claude Tag, but on our Claude products, right? So you can message it and, like, it will do the Claude Tag-like stuff, like spinning off subagents. So We think with multiplayer. Like, Claude Tag is, like, a little bit more native multiplayer because it's just, like, in your Slack and the permissions are all figured out and stuff like that. But I do think multiplayer is, like, an important part of the story and, like, that will need to get tied together more. Like, you can imagine how complicated it gets when you're like, oh, you have hands, but now you have other hands in other people's computers too, and, like, you need to, like, permission them or, like, you have, like, your MCP and someone else's MCP, and how do you figure out how to use them, right? It gets, like, quite complicated. And Claude Tag does a good job of, like, sanding down all of these issues, right? So that, like, when you have, yeah, Google Docs, how does it access Google Docs, right? Like, it accesses through the shared Claude MCP, or it can access through your local credentials as well if it doesn't have access. But yeah, I think Claude Tag is our multiplayer, product, and it's really useful for these, like, things that are inherently multiplayer. Like, okay, like on-call, for example, incidents are inherently multiplayer. You want to tag Claude, you want multiple people to log in, you want it to be able to find context. I think whenever I'm, like, working on something and I want, like, privacy or security or, like, I want other people to review it's really nice to, like. I'll have a channel per project and I'll, like, at legal, for example, be like, “Hey, like, I want to ship this. Can you, like.” Like, here's. Like Claude knows everything, just chat with it. And that way legal gets precise answers, on like what exactly is shipping into the code, and I don't need to be in the loop, right? So I think like multiplayer is getting like more and more like, yeah, everyone can participate with Claude. I think Claude Tag is like that product and like projects will start off single player and will like, expand.Swyx [00:13:14]: I think there's a question about like maybe dual questions about identity and the unit of isolation.Identity, Permissions, and IsolationThariq Shihipar [00:13:20]: Yeah.Swyx [00:13:20]: Claude Tag, you specifically chose to make it its own identityThariq Shihipar [00:13:26]: Yes.Swyx [00:13:26]: Which is like, a controversial choice. There's, there's other ways to do it.Thariq Shihipar [00:13:30]: Yeah.Swyx [00:13:30]: Claude Projects probably it sounds like, if it's anything like ChatGPT Projects, it is, the isolation is that artifacts, that cloud instance, everyone's collaborating on this. It'll. It sounds like, it should be like if you're, if you're collaborating with legal on a thing, like that channel should be a project, right? Like it's not yetThariq Shihipar [00:13:50]: Yes.Swyx [00:13:50]: But it. that's the natural next step.Thariq Shihipar [00:13:53]: Yeah, like I think in Claude Tag, it's effectively. Like Claude Tag, you have to do your own arrangement. And so Claude Tag, yeah, each channel is like you can name it as you want, and I nameSwyx [00:14:04]: Yeah.Thariq Shihipar [00:14:04]: Like each featureSwyx [00:14:06]: Yeah.Thariq Shihipar [00:14:07]: As a channel.Swyx [00:14:07]: And, but I think like there is some trans- like it's unclear when there is transference, because let's say it is. if you have a coworkerThariq Shihipar [00:14:14]: Yeah.Swyx [00:14:14]: Who is tagging on all these things, yes, there is transferThariq Shihipar [00:14:16]: Yeah.Swyx [00:14:16]: Because it's the same person. but with Claude, it's unclear if it's like necessarily like, well, no, you don't know any of. you don't know about the other stuff. You should only use this stuff.Thariq Shihipar [00:14:25]: It's like the tip of the iceberg meme, right, where you can like. This is what we spend so much time onSwyx [00:14:31]: Yeah.Thariq Shihipar [00:14:31]: Is like there is like infinite surface area of like, okay, you want Claudes to. Not infinite, but like there's like surface area, a lot of like, surface area to figure out of like permissions and visibility and like how can you let Claude operate as well as you can, as safely as you can? And obviously, this is very important to us because like security for our code base is very important. And so we've put a lot of time into this. Yeah, there's so many like edge cases you can figure out where it's like, oh, like, yeah, this Claude in this channel has different permissions, but it can message another channel, and can't it exfiltrate data that way? Or like can you like. What if it uses your MCP and then messages someone else? Like there's like so much, and we've like really put a lot of work into sanding it down.Swyx [00:15:14]: Yeah. Lots of work. okay. Fable?Fable and the Meta-Skill of PromptingVibhu [00:15:18]: Fable, you wrote two good articles. you've written many good articlesThariq Shihipar [00:15:22]: Yeah.Vibhu [00:15:22]: But on, Field Guide to Fable, Building Claude Code. I'm curious from what you've seen, is there any common patterns that you see in like top users at Anthropic externally? Like what are best practices for getting the most out of Claude Code?Thariq Shihipar [00:15:37]: The like meta skill I say is like prompting is like very important? And like that. Like I think this is like not trivial to say because I think a lot of people are like, “Oh, prompting doesn't matter. It's just like I can just say a sentence and Claude will do it.” And I think prompting is really this like, this. It's like public speaking, like, or writing or something, and for a specific audience, and that audience is Claude. And you need to like build a mental model of Claude and how it thinks and how it works, right? And so that's like the most important skill in working with Claude Code is like having this mental model, right, of Claude and like what it can do well, what it can one-shot, what it can't. And so many people when you see prompting, they're just like, they're short prompts, but they have such a good mental model of Claude and of like the code base and things like that like it's effortless? But it's like high skill ceiling. So like that work of like, spending a lot of time prompting and building mental models of how, and intuition for how the agents work is really important. And then I think like the next thing is like the unknown stuff we talked about earlier, where it's like being able to find out like your, what you don't know or what you haven't written down, learning about like different things. I think as Claude can do more and more things, the likelihood of you doing something out of distribution for you and like you have low domain knowledge on is very high? And the more you can like learn the vocabulary to be able to prompt Claude, it becomes really important. And so like I think the most important unknowns are the unknown unknowns, where you're like, I just like don't even know that this exists, right? Yeah, exactly. I think that's like a illustration of like the map and the territory, right, where you're like, “Okay, this is my prompt,” and the territory is like the actual like work that the agent needs to do, right? And if you are like very precise, you can give more precise things, right? So like for example, in design, I'm not very precise. I'm not a designer, so I say like, “Give me like eight different mock-ups.” But if I was a designer, maybe I'd be like, “Oh, hey, here are some reference sites.” Like, “I want this type of font and this type of like look to it, and here's like a few different components to like visualize. Here's a Figma MC board to bring in,” like. And so you can just be so much more precise with that language. And if you're not a designer, you just need to like try and learn the language or learn the unknown unknowns. And this is true of like everything, I think. Like the more, like you can work with Claude to learn like how things work, the better your prompting will be. I think another good example of this is like game design, like where a lot of people are like, “Oh, like I can vibe code a game now.” And they're like, “It's not fun.” And like it's just like the thing about game design is like every one of these choices has like a lot ofTaste, Domain Knowledge, and Learning the VocabularySwyx [00:18:25]: Variations.Thariq Shihipar [00:18:25]: A lot of like craft to them. So it's like, oh, okay, like when you're making a flying game, the feel of the plane and the like, way it responds to your controls has a lot of like. Like, a game designer would spend like days on that. Do? and likeSwyx [00:18:44]: To me, that's what taste is, right?Swyx [00:18:45]: Like it is like from the possible space of one thousand mathematically valid answersThariq Shihipar [00:18:49]: Yeah.Swyx [00:18:49]: Here's the one that is the humans will like.Thariq Shihipar [00:18:51]: Yes. Yeah.Thariq Shihipar [00:18:52]: I think with taste, I'm like torn on this word ‘cause I think you're right, but everyone has different definitions, and it sounds kind, sounds like low skill or like elitist almost, where you're like, oh, like there are certain people with taste?Swyx [00:19:06]: It's like taste is what I call taste.Thariq Shihipar [00:19:07]: Yeah, exactly.Swyx [00:19:08]: And it's like these guys don't have taste.Thariq Shihipar [00:19:09]: Yeah, exactly. Oh, like an engineer doesn't have taste. Like I, the like founder, have taste.Thariq Shihipar [00:19:14]: ? And I think that's not true. Like I think like the engineers have a lot of taste for these particular like problems? And I think everyone has taste for particular problems. I think like Jason Liu, like say like in order to, yeah, have taste, you have to eat?Thariq Shihipar [00:19:32]: And I really like that, where it's like, okay, you have to like do a lot of things. You have to like iterate and figure out what you want, what you like, and, like build that like domainSwyx [00:19:41]: YesThariq Shihipar [00:19:41]: Domain vocabulary. And then when you're prompting, you're like synthesizing all of that for a product.Swyx [00:19:46]: Isn't it annoying when someone else says it better than you?Swyx [00:19:48]: It's just like, f**k, I have to quote this guy forever.Vibhu [00:19:51]: Having to quote Jason Liu forever.Vibhu [00:19:53]: He's gonna love this.Thariq Shihipar [00:19:55]: So I get prompts, more than that.Vibhu [00:19:57]: And sometimes it's not even that. Sometimes it's just intuitive, right? Like you don't realize you even want something till a model puts it out, and you're like, “Oh, this just feels immediately better,” right?Voice Prompting and Information DensityThariq Shihipar [00:20:07]: Yeah, exactly.Swyx [00:20:09]: One thing I go back and forth on is I feel like the way I prompt half the time, let's say I use voice.Swyx [00:20:16]: Did I say voice? Other people have voice. that is the opposite. That is just like me rambling for like two minutes Pressing down the function key and then let go, and then like hopefully it figures it out. And oftentimes it does.Thariq Shihipar [00:20:26]: Yeah.Swyx [00:20:26]: But it's not as thoughtful as like a structured prompt with like Well-run communication as though it's a PRD or a memo. Is that in line with how people do this? There's like bimodal prompting where there's some prompts where you spend a lot of time upfront and other prompts you just dash it off?Thariq Shihipar [00:20:43]: I don't think the voice is necessarily low. Like I think it's like more like how much information is in the prompt. like the model can. Like you can and like add some sentencesSwyx [00:20:53]: RightThariq Shihipar [00:20:53]: And be like, “Oh, like I changed my mind,” like in the middle of the prompt, and it will be able to follow that perfectly? So I think the like actual format of the text is less important, but then like the ability to. Like how much information is in it, right? And I think for voice, a lot of times, going back to like human-agent interaction and like for a lot of people, it's just way easier to talk than to like type? and I. If that gets more information out of you, like that's better.Vibhu [00:21:21]: At some level, it feels like just giving the model as much contextThariq Shihipar [00:21:24]: YesVibhu [00:21:24]: Over prompting before you kick off is a best practice. I don't know. A lot of the times, like when I was first trying out Fable, I spend a solid 30 minutes like really crafting a long prompt. This, I think, is a response of models running for longer and longer, right? It's still a little difficult to nudge them as they're in like, in the loop, but I just like intuitively spend more time kicking off that first prompt and working with it a lot.Spend More Upfront, Iterate LessThariq Shihipar [00:21:52]: My personal opinion is that if I was a software engineer, if I was like, just running my own startup, for example, I think I would mostly fit, stick to a max 20x? like maybe verification and so code review are like separate things. But I think like what I see a lot of times is people hit rate limits when they're doing this like, oh, like it did a lot of work and you're like, “Oh, I don't like this.” Like, “Can you like undo this and redo it?” And then you're like iterating on this like thing that the model could have done if you had like spent more upfront time or given it better context? And instead it's like you're like, “Nope, don't like that design. Try this.” Or like, “You messed this up,” or something like that. And then that just eats up so much more of like, your usage. And so that's like, I think maybe like a key like tip both for like efficiency as well, right? And yeah, I think like context, and not just like context on like what the goal is good, right? Like are you building a prototype or is it like a production thing? Like where can you spend compute or when, where can you not spend compute? Like I think you have to give the model permission or like not permission to do things sometimes where, like it doesn't know intuitively how much you want to spend on this task, right? And you can use effort for this. So I did-- I'm working on a blog post about that where it's like, if you want. For like we see that effort scales with the complexity of the task. So for security, effort gets like way more results. Like high effort versus like low effort gets, like changes the evals a lot. But for software engineering, it doesn't change it a huge amount because effort is mostly spent on the verification and the like edge case testing and things like that. And so like being able to like give the model that guidance of like, “Hey, this problem is something that I think I want you to spend a lot of time verifying and edge case testing,”?Effort, Model Choice, and VerificationVibhu [00:23:43]: How about model in the mix? So, there's Opus and Fable with effort.Thariq Shihipar [00:23:47]: Yeah.Vibhu [00:23:48]: There's also Haiku in there.Thariq Shihipar [00:23:49]: Yeah. It's not quite true yet, but it's very close where I think the frontier models will be Pareto dominant over like almost everything. like maybe. And sometimes I think Opus might be Pareto dominant. Do? Like I think depending on like how things, like shake out if it's like a newer version of Opus. But I think that like increasingly it's just going to be like the smart model is going to be able to like do the simple task for less tokens than the like the other models because of verification. With verification, in the limit, your model doesn't need to verify, right? If it's a perfect model, it just does the work once and it's like, okay, like you, I did it? And increasingly with Fable, I'm like, I'm like, “Dude, you don't need to spin up Chromium and screenshot all of these things.” Like I see it. Like you did it, right? And so a lot of the. At higher effort, you spend more of those tokens verifying. But if you're working on simpler problems, and a lot of software engineering is like well, like in Fable, like low and medium stability, it can spend less tokens verifying. And as the models get smarter and smarter, they will just be able to like, “All right, done.”? Like, I can run the lint for sanity's sake, but, like, I, like, know it lints? Like, you don't even need to do that. And that will be so much more token efficient than, like, the smaller models. Yeah.Swyx [00:25:15]: Is there a good, practice on our side that we can use to see if we're using too much effort? Like, I freakingThariq Shihipar [00:25:23]: YeahSwyx [00:25:23]: Hate wasting time on that stuff.Thariq Shihipar [00:25:24]: Yeah. I know what you mean. I think, like, so in this blog post, my rough distribution is, like, code review and security should be, like, high or max and, like, software engineeringSwyx [00:25:37]: You said recommend mix settings per domain.Thariq Shihipar [00:25:37]: Yeah. I think, like, if you're doing, like, UI or something like that, like low and medium, I think is you're building, like, an API and you want to make sure, like, you cover enough edge cases? And so I think building, like I said, that mental model of, like, how things work across these distributions is, like, yeah, part of the job.Implementation Notes and Decision LogsVibhu [00:25:56]: This is more intuition-driven or eval? Because I'm guessing this would change as you go.Swyx [00:26:00]: He has evals.Thariq Shihipar [00:26:01]: Yeah. So what I did in the blog post is I go over all of the terminal bench evals. So there are, like, 70 problems and I'm show that, like, okay, like, in the security problems it does more. and then I also, like, look at some of the transcripts just in terms of, like, how-- what does it answer, what does it forget or something. And a lot of times, this is another prompting tip I have, is, like, asking it to make decision notes or implementation notes because, in every eval problem that it faces, it thinks about the correct solution, and decides not to do it. it's like, oh, like, here is the answer. What if I did this? And then it's like, oh, probably not? and then keeps going. And this is, like, the majority of the failures, at, like, a higher max level. It's very rare that the model just doesn't know how to do something. If you just have these implementation notes, then you can review and you can be like, “Oh, I want you to do this thing that you didn't do.” The models are getting better at surfacing that overall. Like, I see in the transcripts of Fable 5.1, like, when it does this output, it will call out its decision-making as well. but making this more explicit in the harness is better. And now we're, allowing ways of you modifying the harness so you can, like, add someVibhu [00:27:23]: Ooh.Thariq Shihipar [00:27:24]: Calculate with there. Yeah.Swyx [00:27:25]: Yeah. So I do wanna call out two things that you mentioned that I think exist outside of prompting. One is like, let's, let's call it the prompt that is so important that it shouldn't be in a prompt. It is in Claude.md or Agents.mdThariq Shihipar [00:27:38]: YeahSwyx [00:27:38]: Which is like goals, right? Like your situation, your goals, the things that you want, the thing. and then second of all is the decision log or the experiment log or whatever log of traces that you might want to survive the current session to do those things. Those are, like, externalities that there's no standard. There's no-- It's not like skills. It's not like MCP. There's no standard. It's, it's just like it's a markdown file. first of all, is that right? Is Claude.md going away? You have a documented dislike of, Agents.md, but you're gonna do it?Claude.md, Agents.md, and Model-Specific InstructionsThariq Shihipar [00:28:10]: Yeah. Okay. So Agents.md, yeah, like, we're, we're gonna do it. I think it's just, like, different models are very different from each other? But I realize that it's, like, such a pain to, like, maintain different ones? And yeah, like, as the models get better and better, the floor of how they accomplish the simpler task is better. And so I do think in the limit, Claude.md goes away, and maybe not even, like, that far. Like, I think, like, I think that right now it might be better to start a new project without a Claude.md.Swyx [00:28:44]: Yes.Thariq Shihipar [00:28:44]: I think that, like, maybe if you see very repeated failure modes, you add them to your Claude.md. The really tough thing is that this changes per model. And so, like, if you've added a bunch of failure modes or, like evenSwyx [00:28:57]: So you need Fable MD, you need Opus MD.Thariq Shihipar [00:28:59]: Or well, even Fable 5.1 versus Fable 5.Swyx [00:29:03]: Yeah.Thariq Shihipar [00:29:03]: Like, it is annoying. Like, I'm not like,Swyx [00:29:05]: YeahThariq Shihipar [00:29:05]: Like, we don't, like, do this on purpose? It's just, like, how the models work, right? And so, like, maybe, like, Fable 5 had this, like, failure mode that Fable 5.1 doesn't. And if you keep this context, this running log of a bunch of different failure modes, they will probably over constrain Claude? And so this is like. we just added evals plugins for skills.Swyx [00:29:28]: Yeah.Thariq Shihipar [00:29:29]: And so now you can eval if a skill is better. I think Daisy on our team did this. And so, yeah, this is like we're trying to work on this. We know it's, like, you still have to spend tokens on it and, like, it's not, it's not perfect, but it's, like, we're trying to help out with this problem.Swyx [00:29:44]: And so, and as far as prompting goes, the one tip I wanna offer is, something I have told people a lot is sufficiently advanced prompting is indistinguishable from sufficiently advanced executive communication. So I've referred to-- This is an executive comms workshop from Heavybit that is the best I've ever seen in my career. And they teach this thing called the SCQA model. Just Google it. It's a, it's a thing. Like, people have done prompting for decades. It's just called executive communication. It's like when one person has to communicate to thousands of people down the org chart, this is what you do. so situation, complication, question and answer, is how you write the memo. but obviously sometimes you don't have the answer, but you can at least list out the SC and Q, and then they have some examples in there. So just leaving breadcrumbs for people if they want to explore.Underrated Prompting Patterns and ELI5Vibhu [00:30:31]: Before we move on, I wanna ask you, any other underrated tips, ways people could get a lot of value from Claude Code that they're not using?Thariq Shihipar [00:30:41]: Yeah, I think a lot of them are in the, this unknowns, like, doc. Like, I give a bunch of example prompts, like, using it for brainstorming, using it to quiz you after. we added this, like, explain it like I'm five skill which is a very short prompt. And it doesn't even say explain it like I'm five. It's like the key word of this prompt is big pictures, few words. like, that's like the main thing. And it is shockingly good? Like, you, like, I think I tweeted about this and it's like /eli5, and, like, you can install it as a plug-in. But yeah, it's, like, way better at just cutting through the BS and being like, yeah, exactly right here. So the diagrams are, like, quite clear. I think one of the things that is true with artifacts is, like, they put too much text in and people are not reading the artifacts? And so, like, this simplifies it a lot more. And, yeah, this came out of, like, just people at Anthropic, like, going through very complicated incidents and being like, “What is happening?”? So, this one I think is great, yeah.Swyx [00:31:47]: My version of this is the, it's like test your understanding. Give you a few choices and then, like, if you get it wrong, you have a mismatch between what you think is happening versus what's happening.Thariq Shihipar [00:31:58]: Yeah. I think this is one of those things that everyone loves talking about, and then very few people really do. Like, I thinkSwyx [00:32:05]: Really helpful.Thariq Shihipar [00:32:07]: Yeah. But most people just don't want to get quizzed about something? Unfortunately, I think this is one of the, like, things that we need to, like.Swyx [00:32:16]: What's the opposite of ask you the question or ask you the question before the thing?Thariq Shihipar [00:32:19]: Yeah.Swyx [00:32:19]: This is after the thing.Thariq Shihipar [00:32:20]: Exactly. Yeah.Vibhu [00:32:21]: It's a good way to stay grounded of, like, do you even know what you're doing, right? The worst case is when people send you slop and they haven't understood what they're asking for or what the output is, and it's like, “Dude, I don't wanna read this. Do you even know what it is?” So, you make it a rule for yourself that before you send stuff, you should at least know what's implemented.Claude Mods: Customizing the HarnessThariq Shihipar [00:32:41]: Yes, but so you could make this a mod and you could build your own mod to, like, make sure you test it. So yeah, you can do that.Swyx [00:32:49]: All right. Let's get right into it. What is Claude Mod, and what is this diagram showing?Thariq Shihipar [00:32:54]: Yeah. Okay, so Claude Mods is you can customize the entire Claude Code harness, and we're going to. If you have requests, we will, like, let you, like, please let us know. We'll add more and more. This works for CLI, it works for desktop. maybe it will work for Claude Tag in the future. I don't know. Like, we're trying to make this very extensible. You can see this reference sheet. I don't want people to get overwhelmed by it? At a high level, you can customize both the execution of the harness, and the UI of the harness. And so, like, you say on that Tetris example from Boris, that's like customizing the UI, right? Like showing, like, Tetris in the game.Thariq Shihipar [00:33:35]: But, like, let's say that you wanted to do this thing where you had. you tested your assumptions or, like, tested your understanding after every project, right? What you would do is you would ask Claude to make this plug-in. It would spin a classifier after every prompt. And so, like, at the end of each turn, you would spin off a sub-agent or, like, a forked agent. A forked agent is, like, maintains the prompt cache, right? So it's like a, like one of those unintuitive things where you can fork and do, like, a little request, and it'll be very cheap because the entire prompt cache is, like, done. And so you can be like, “Has this task been completed?” likeSwyx [00:34:18]: This is how you do BTW and all those.Thariq Shihipar [00:34:20]: Yeah. The underlying forked agent, yes. But so you can, in the f-fork sub-agent, you can say, like, “Has this task been completed? If so, return true.” And then in your hook, or in your, like, plug-in mod, or sorry, like, in the sub-agent probably, you would say, like, “If true, give me a quiz.” give me questions and answers, and then, like, in a JSON format, and then you'd parse it, and then you display above the prompt input, this list of questions, right? And so this is something that's, like, slightly token-intensive because, like, you have to do it after every end of the assistant turn. But it's, like, a lightweight classification, and then you can, like, get this quiz, and then you'll see, like, Claude will always do it for you. You don't need to remember to do it. There are lots of these, like, tips that we've talked about, right, where it's like, oh, implementation notes. You can also add a tool for implementation notes now. And so, like, this tool that I'm adding is, like, register, like, I think assumption is what I'm calling it, but, like, maybe I'll change it around. And this is a mod. And so, like, you give it a register assumption tool, and then it will keep a list. It'll. Every time it does it'll keep a, like, add to the list, and then at the end it will display those assumptions? Another mod I'm working on is a model router. And so, like, internal, like, Claude model routing, right? So it's. This is, I want to say the reason we don't do model routing by default is, like, it's a hard problem? And likeForked Agents, Assumption Tracking, and Model RoutingSwyx [00:35:51]: You will get it wrong.Thariq Shihipar [00:35:52]: Yeah, you, like, yeah, you will, like, accidentally use, like, Fable for a hard problem or Sonnet forSwyx [00:35:57]: Yeah, if you have auto approve, but you don't have auto mode.Thariq Shihipar [00:36:01]: Well, you will have auto. Like, you don't have, like, auto routing or something.Vibhu [00:36:04]: You don't have auto mode for model picker.Thariq Shihipar [00:36:06]: Yeah, exactly. SoVibhu [00:36:07]: I'm getting the rough question of, like, how much do you open this up and how much do people have to think about this? Like, when you talk about prompt caching and building a router, it seems like you could easily build a mod that routes per query, and I'm just killing my plan very fast, right? I guess my question is more so, like, what is, like, a product talk like this look like, right? Who is it for? Is it for power users? Is it everyone should be able to go throughSwyx [00:36:33]: Oh, definitely power users, right?Thariq Shihipar [00:36:35]: Yeah, I think it is power users, but, like, the nature of Claude Code is that so many people are power users? Because it's easy to share things, like you can. Like, one person can make a good model router thing that doesn't break prompt cache all the time, and then you can, like, compose them. Another cool thing about the plug-ins is that they can hook into and compose with each other. And so I have, like, a mod that will, like, create a mode selector at the top, and any plug-ins can register to be a mode. And so, like, the auto router can be a mode, right? Or, like, you can have a mode that's, like, artifact mode, where it's like it primarily talks to you in artifacts. like, you can toggle between plan mode? And so, like, you can create more and more of these modes. But the ability to create modes is in it itself a mod? And so there's a lot of richness here, but we do want to make it fairly easy. We want to be-- make it so that you can just, like, install someone else's. You can ta-- you can chat with Claude and, we'll, like, make sure that it understands the nuances of things like prompt caching and stuff, so it can, like, warn you. This is, like, not extremely complicated behavior for Claude, I think, but we should have just a good skill on how to make mods. and yeah, we'll see how we go. But I do think that this is, like, a preview of, like, mutable software, and, like, how, like, generative software, just like you can customize safely. If enabled, you could customize any piece of software. And I think that more and more apps ideally do something like this?Power Users, Modes, and Mutable SoftwareSwyx [00:38:13]: And by the way, you, we have, you have another cool tweet about how, there's the infinite money button, which is like make your SaaS, consumable by agents. I think mutable software is interesting and, other people have also tried to do it. I think the hurdle comes when you can do everything, then people, users get, tend to get confused. So usually the stuff that works is just like one opinionated flow. This is in the side of less opinionation. It's just like, well, more power to power users. And I think probably unlocked by AI, where, like, you can just prompt for whatever the thing is.Thariq Shihipar [00:38:47]: Yeah, or there can be a skill that gives the opinions?Mods vs. Hooks vs. ArtifactsSwyx [00:38:50]: Yeah.Thariq Shihipar [00:38:50]: And then, yeah.Swyx [00:38:51]: So knowing a little bit about, like, TypeScript and build systems and all these things, the closest-- I'm very curious that the team who worked on this, if, I don't know how close you were to them, if they drew any inspiration from build systems like Babel, Webpack, all these, like, old school things. Because it sounds very similar, like the plug-in ecosystem of those things where they can compose with each other.Thariq Shihipar [00:39:11]: Yeah, I'm not deep in the technical details, but I do know it was a collaboration with someone on the Bun team and someone on the Claude Code team.Swyx [00:39:17]: Yeah, it's a build system mecca.Thariq Shihipar [00:39:19]: Yeah. Exactly. It's, it's very exciting. But yeah, like, agents can just do this very complicated like, extensibility into your software now. And so, yeah, like, another reason to, like. If you run a startup, like, you can just prompt Claude and be like, “Hey, like, could we make an extension system? Like, what would that look like?”?Swyx [00:39:37]: Yeah.Swyx [00:39:38]: And I just really wonder, like, you had hooks in the past and plug-ins, all these things. So what specifically will mods be able to do that those things could not do?Thariq Shihipar [00:39:47]: Internally, we were originally calling this function hooks. And so, like, that's, like, gives you a little bit of an idea where, like, hooks register a, like an event to happen and then, like, a script to call. And this inside of the, like, TypeScript runtime is running things. And so, like, you get some benefits of just, like, it has a bunch of things in the Scope with, like, for example, like how many turns is in this conversation, right? Like, how many tokens have been used? Like, et cetera. Like, what are the messages? Things like that. So it has a bunch of messages that can be used. And then it's just, like, a lot more hooks. So we have, like, or a lot of, lot more, like, things you can register on. And then you can do because of the. because it's all happening in process, you can, spawn sub-agents, with four contests and contexts and stuff. And, like, that will return. You can parse the results of those. You can use structured output to like, return them. and then you can modify the UI, which you can never do in hooks. So, yeah.Swyx [00:40:50]: Yeah. Yeah. So modify UI, this is why you showed the Tetris example. Does it also ex-extend to artifacts? I assume it does.Thariq Shihipar [00:40:57]: You-- Like, artifacts are like a different way of customizing it. like, you can definitely. One of the mods I'm working on is, like, this dashboard mod, which will, like, prompt Claude to maintain a dashboard, that's an artifact. But they're like, slightly orthogonal, or not orthogonal. They compose with each other in different ways. Like, mods are, like, a little bit more, like, in your Claude Code harness, changing the agent loop? And, like, the UI is, like, an added benefit. and then artifacts are just like you want to, see things at a high level, very inter- highly interactive. like, the affordances can be a lot bigger than, like a TUI or even in our desktop.Next Steps, Supervisors, and Persistent GuidanceVibhu [00:41:40]: I'm guessing you'll have a good blog post on the differences, because right now you can also, make a loop that outputs to an artifact that's an interactive dashboard, but you can also do it with a mod. There's just some thinking about making a hacking on a harness when we don't know much about the harness, right?Thariq Shihipar [00:42:00]: Well, something I'm excited about with mods is, like, there's so much things with Claude Code that you just have to remember? You're like, “Oh, like, let me do this, and then let me call the dashboard skill that does the loop,” and things like that. And, or like, “Let me test my assumptions afterwards.” And I think, like, if you do all of these things using these little classifiers and stuff, and you're like, “These are the things I care about. This is what I want to do,” you can, like. You don't have to remember as much. One more, like, mod I'm working on is a next steps mod thatSwyx [00:42:28]: I have-- I was gonna say, I have a next step skill. I always run next steps.Thariq Shihipar [00:42:32]: And does it have access to your skills? Like, this is one of those things where I'm like.Swyx [00:42:37]: I think so.Thariq Shihipar [00:42:38]: Okay. Yeah, probablyVibhu [00:42:39]: Do skills need specific access toThariq Shihipar [00:42:41]: Well, I think there'sSwyx [00:42:41]: Don't they always haveThariq Shihipar [00:42:42]: I think there's, like, specific prompting, I guess, to, like, know your skills. Like I think Claude forgets them sometimes throughout, like, the thing. But anyways, the idea of, like, yeah, next steps that also are like, “Oh, hey, this has happened. Use the explain skill to explain to you what happened because this seems, like, quite complex,”? Or, like, yeah, “Use your unknown skill. It looks like you are, like, asking the model to, like, iterate on these small changes. It seems like you could prompt better.” like, “What if you did this?” Right? So, I think, yeah, like spending more compute there. Yeah.Swyx [00:43:20]: And it should always come out as multiple choice. we have, I haveVibhu [00:43:23]: We have his skill.Swyx [00:43:24]: My next step skill is like this.Thariq Shihipar [00:43:26]: Okay, perfect. Yeah.Swyx [00:43:27]: You can steal it.Thariq Shihipar [00:43:28]: Yeah.Swyx [00:43:29]: Like, but like, for me, it's all-- I think models really always need to be reminded, what are you trying to do here?Thariq Shihipar [00:43:35]: Yeah.Swyx [00:43:35]: Look at the whole transcript and go like, oh, was this original goal? Did your solution solve it? Were you lazy? If you're lazy, maybe there's a reason. Maybe you needed approval from me. Maybe you needed, there's two things you wanna suggest. So it's, it's a little bit like the modification of the ask user question or interview me skill. so it's next steps.Thariq Shihipar [00:43:55]: Yeah, exactly. And again, the benefit of doing it with mods is you can do it as a fork sub-agent, and so it doesn't remain in the context afterwards. So you have this, like, idea of like, okay, the model is doing its execution and you have this almost like supervisor, like, that is like making sure that you can do like the next steps well. So yeah.Swyx [00:44:15]: Yes. I do have two panels and like I often try to have a supervisor thing, keep the high-level context and then the implementationThariq Shihipar [00:44:21]: YeahSwyx [00:44:22]: Detail in another agent.Vibhu [00:44:23]: I feel like a lot of this abstracts away as models change? The, like, half an hour ago you said bitter lesson of harness engineeringThe Bitter Lesson of Harness EngineeringThariq Shihipar [00:44:31]: YeahVibhu [00:44:31]: And we're on the other extreme right now, I feel.Swyx [00:44:33]: Well, so yeah, exactly. If everything's customizable, what is Claude Code, right?Thariq Shihipar [00:44:37]: Yeah.Swyx [00:44:37]: And which I talked to you about last night.Thariq Shihipar [00:44:40]: Yeah, I think that this is. I think the bitter lesson is unintuitive? In terms of like. Also, like we're misusing a little bit of the bitter lesson here where it's like, it's more about like scaling and compute and stuff. But like, I think there is something where it's just like. I think I use it as an approximation here to say that harnesses go out of date very quickly? And like how, but how they change is unintuitive? And so like the big obvious example is like from chat to like agents where you had to give them entirely new tools, right? But like, I think this new version of like, oh, it can modify its own harness, right? This is like, an own harness loop is like a way of using its capabilities, right? Or like it can build an artifact. And like, I think the way I think about it is like the models have more and more intelligence, and they're like so much more intelligent now than like the average software engineering task. Like, you look at the like terminal bench ones and they're like solve like the Jacobian conjecture. Not really, but like, it's like they're, they're quite complex. Like, I would not have been able to do this really as a software engineer.Swyx [00:45:42]: And you said TB4 or TB2?Thariq Shihipar [00:45:43]: TB3. TB3.Swyx [00:45:44]: TB3.Thariq Shihipar [00:45:44]: Yeah. They're quite complex, but the goal is still to deliver user value, right? And like you said, there's like this infinite space of things to do. And so the ways like you spend compute are to keep the user in the loop and make sure that like you're getting to the right decision in the end of the day and like the right output. And artifacts and mods are this way of like spending that intelligence. and I think that's like, yeah, the next step. And so, yeah, I think Claude Code is like, has the core things of agent loop which are, have gotten more complicated. It's like, it needs a sandbox to operate safely. It needs auto mode to like make sure like the permissionsVibhu [00:46:21]: Approvals.Thariq Shihipar [00:46:21]: Yeah, approvals. it needs computer use and MCPs and like all of these like ways of accessing your data, and it needs web search and web fetch. And like, so the-- as the models can do more and more, the core harness has to be like quite complex and very secure. But then like how you interact with it can change quite a lot.Vibhu [00:46:42]: What other harness engineering best practices have you, from the Claude Code team itself? I feel like, there was a phase of plan mode, which is not as used. We now have auto mode. at a point you cut the majority of the system prompt, you got rid of examples. What other best practices are there for harness engineering?Core Harness Primitives and Managed AgentsThariq Shihipar [00:47:02]: I think there is like a forking path where at some point, eventually, yes, the model will just be able to like vibe code the exact version of Claude Code, even describing all this complexity that I've talked about, right? Like auto mode and computer use and stuff. Eventually, the models will just be able to do that in one shot. But I think they can one shot simpler harnesses? And so like, I think some people. Sometimes you don't need this full, like if you don't need computer use or like all this like more complicated stuff. I think before we, you had to use things like the agent SDK, which was like Claude Code wrapped, in order to like. And I would, like suggest people do that because there was so much complexity into building a harness. And now as that's got more abstracted, we have like, Claude managed agents, which lets you have that complexity, but still like, right, like a very bare bones like harness that's scoped to your task. Yeah, I think there's like this barbell effect where like for like very complex, for like coding task and like these like complex things, you should use our harness. And then for like a lot of like simpler or like, more domain-specific things, you can build your own harness because Claude has gotten better at building harnesses, and we have these harness primitives like managed agents. So yeah.Swyx [00:48:18]: Yeah. Is there a general progression? Let's say chapter one was ultra code dynamic workflows, then chapter two was cloud mods. Where is this going?Swyx [00:48:29]: Where you're, you're, you can customize the thing on demand.Thariq Shihipar [00:48:36]: Yeah. I do think that like this evolution of projects and like artifacts and splitting out like brain and hands and, surfaces is like where things are going more. And like, I think it's like not all quite there. partially it's like a, it's just like more token expensive? And like, I think likeProjects, Local Hands, and Cloud-to-Local HandoffsSwyx [00:48:59]: Why would projects be more token expensive? I understand mods would be slightly more token expensive. No, not something I'm worried about.Thariq Shihipar [00:49:06]: Yeah.Swyx [00:49:06]: But whatThariq Shihipar [00:49:07]: You're asking Claude to do. It's like creating loops. Like you're asking Claude to do more work for you. And so like it's managing the sub-agents and reviewing it, versus where you would be doing that work normally. And so that's like gonna be a little bit more intensive, like. Outputting to an artifact is gonna be a little bit more token-intensive than, like, outputting normally. I don't think it's too much more, but like, it's like combining all of these together well, like I think we're, we're still working on like local hands and things like that, I think is like, yeah, where things are headed, yeah.Swyx [00:49:37]: Yeah. Claude and local is, handoff is very interesting. I was thinking about this as reverse cloud remote.Thariq Shihipar [00:49:44]: Yeah.Swyx [00:49:45]: Because it's like remote, it's you're handing off to cloud, but here the cloud is handing off to local, right?Thariq Shihipar [00:49:49]: Yeah, exactly. Yeah, remote control is also another way of doing it. And I do want to say this is like how I think about it and like what the things that I'm most excited about this, but like there are, just like lots of different ways to work with Claude. Like some people use remote control a lot, some people use Claude Code on the web a lot. Obviously, like at Anthropic, we use Claude Tag a lot, and like what's great about Claude Tag is we set up all this stuff for our own execution. And I do think if you're an enterprise, that's still the best way to go. but if you're like an individual, Projects is this way of like, getting some of that like niceness of Tag, which has like that like supervising agent and yeah, adding artifacts and stuff, but like without having that whole like admin setup. And so there will be many ways to use Claude, I think. I think it's probably not just one like single.Claude Tag as an Organizational HarnessSwyx [00:50:36]: You had the multiplayer thing here. Let's, let's just check in on Claude Tag. it's been about two-plus months. Lots of, public, adoption and trying it out.Thariq Shihipar [00:50:45]: Yeah.Swyx [00:50:45]: What's new? What's, what have you found since the launch?Thariq Shihipar [00:50:49]: Like, Claude Tag is how we useSwyx [00:50:51]: It's like 80% of your

Strategic initiatives rarely stall because teams aren't working hard enough. More often, the information leaders need to make timely decisions is scattered across Jira, Asana, Slack, spreadsheets, meetings, and everything in between. By the time a risk becomes visible at the executive level, the opportunity to address it early may already be gone.Galen Low sits down with Maria Delgado Oliveros, founder of glidiffy and former program management leader at Uber, Hexagon PPM, and Chime, to unpack what makes strategic initiatives different from ordinary projects—and why better visibility can transform the relationship between program managers and executive sponsors. They explore how PMs can spend less time chasing updates and more time understanding dependencies, surfacing risks, making trade-offs, and becoming trusted operational partners.Resources from this episode:Join the Digital Project Manager CommunitySubscribe to the newsletter to get our latest articles and podcastsCheck out this episode's sponsor: FingerprintConnect with Maria on LinkedInCheck out glidiffy

Every product team is shipping AI. But the dirty secret is that, for many companies, very few users are adopting. The feature launches, the people who try it love it, and adoption stalls anyway. Our guest today thinks that's because teams obsess over building AI and barely think about adoption. Charanya Kannan is VP and GM of Navan Anywhere, which puts Navan's AI travel and expense tools inside Slack, Teams, and Gemini, where people already work, instead of asking them to open another app. She joined Navan when the company was still called TripActions and doing under $50 million in revenue... now it's well on its way to a billion. Her take: if customers have to work harder to use your AI, it isn't actually better. In this episode, Charanya shares: How Navan Anywhere was built distribution-first, bringing booking and expenses into the tools people already use every day Why Navan's margins went up in the AI era, while the rest of SaaS braces for compression And why she believes PMs who mostly manage process and Jira tickets will fade away, while those who can actually drive user benefit and business outcomes will matter more than ever Links LinkedIn: https://www.linkedin.com/in/meetcharanya/ Navan: https://navan.com/ Chapters 00:00 Introduction 04:17 Why AI features don't always get adopted 06:30 Building Navan Anywhere distribution-first 10:13 When to use AI vs. deterministic systems 12:01 Conversational cognitive load and why good UI still matters 15:57 Evals, distilled models, and the AI reliability pyramid 20:14 Product owners vs. product managers in the AI era 26:10 How Navan is growing margins while SaaS faces AI compression 31:40 Conclusion Follow LaunchPod on YouTube We have a new YouTube page! Watch full episodes of our interviews with PM leaders and subscribe! What does LogRocket do? LogRocket's Galileo AI watches user sessions for you and surfaces the technical and usability issues holding back your web and mobile apps. Understand where your users are struggling by trying it for free at LogRocket.com.Special Guest: Charanya Kannan.

Bain estimates a $100 billion market for software that reduces cross-system labor, the manual work that links multiple applications. The opportunity spans integration platforms, workflow automation, robotic process automation, and AI assistants. Examples in the space include MuleSoft, Workato, Zapier, ServiceNow, UiPath, Automation Anywhere, Salesforce, Slack, and Atlassian. Adjacent data platforms like Snowflake and Databricks centralize analytics but do not execute operational actions, which remain in systems such as SAP, Oracle, Workday, NetSuite, HubSpot, and Zendesk. Buyers prioritize security, governance, auditability, and measurable ROI, with pricing models ranging from per seat to per workflow. Execution risks include brittle integrations and rate limits, pushing vendors to invest in observability, access control, and human-in-the-loop approvals.Learn more on this news by visiting us at: https://greyjournal.net/news/ Hosted on Acast. See acast.com/privacy for more information.

What happens when an organization's AI ambition moves faster than its frontline's ability to absorb it?Agility isn't just deploying new technology quickly. It's whether the people and processes closest to the customer can change alongside it without the experience coming apart at the seams.Today we're going to talk about the friction between enterprise AI deployment and frontline readiness — and why the last mile of service is where AI investment either proves out or quietly falls apart. We'll get into:- What actually breaks between a strategic AI decision and the moment a technician has to act on it- Why fragmented data access is so costly when the person standing in front of the customer can't see the whole picture- How to measure success in field service when closing tickets faster isn't the same thing as a better outcomeTo help me discuss this topic, I'd like to welcome Taksina Eammano, EVP and GM of Agentforce Field Service at Salesforce.About Taksina EammanoTaksina Eammano is the Executive Vice President & General Manager of Field Service at Salesforce. She is responsible for the overall strategy and vision, product and innovation narrative, and financial performance of Field Service.Taksina Eammano on LinkedIn---------- Resources ----------Salesforce: https://www.salesforce.comThe Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://aglbrnd.co/r/2868abd8085a9703The hardest part of martech right now is telling which tools are actually earning their keep. That's the question running through the MarTech Summit Boston agenda on October 27. We're attending MarTech Summit Boston on October 27 as a media partner. If you want to join, the code AGILE15 saves you 15%. https://aglbrnd.co/r/c70c250b8d52dff3We're proud to be a media partner for #MAICON26 - Oct. 13-15! Learn how AI can power your marketing and business and help you grow smarter. Use code AGILE150 to save! https://aglbrnd.co/r/7fe458ced0f04658Need to evaluate martech, AI, or CX platforms and don't know where to start? The Agile Brand Guide List is now in beta. We're building the most useful, free-to-use, and up-to-date way to assess what truly matters when evaluating platforms. See more here: https://aglbrnd.co/r/f76be3a33cc491bbReach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit! Learn more: https://aglbrnd.co/r/491818c79fb1873fChaser is the only Slack-native project management platform that helps teams turn messages into tracked tasks, automate follow-ups, and maintain team-wide visibility, without adopting another tool. Now integrated with Claude and other GenAI tools. Learn more at trychaser.com and use code AGILEBRAND for a 3-month free trial (normal trial is 14 days).Start building your own apps with Replit and get $20 off. Learn more: https://aglbrnd.co/r/93531742a7625a20Enjoyed the show? Tell us more and give us a rating so others can find the show: https://aglbrnd.co/r/faaed112fc9887f3Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter, and check out Martechipedia, the wiki for marketing technology: https://aglbrnd.co/r/35ded3ccfb6716baThe Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content: https://aglbrnd.co/r/f1782ab12211f765 Hosted on Acast. See acast.com/privacy for more information.

Get a $230 gift card after making a $500 payment with Melio (affiliate) - https://milestomemories.com/go/melio Mark is back from the Azores after four airlines in five days, and he has thoughts. First, though, Rakuten's increased card offers are some of the best we've ever seen, including a no annual fee Bank of America card worth up to 40,000 Bilt points plus a $250 bonus, and there's one catch for Membership Rewards members you need to know. Then the trip: Royal Air Maroc business class on Alaska miles (the seat is fine, the service is another story), a night in Lisbon that started with Uber chaos and ended at a rooftop sunset, and a TAP flight with seatmates Mark will never forget. The Azores themselves might be the best value trip in the Atlantic, with Hawaii-level scenery at mainland Europe prices, smoked pineapples, thermal springs, and an Amex FHR stay in Ponta Delgada. Plus how Mark dodged the Boston storms for free, whether he should have taken $700 to wait, and why short whirlwind trips are worth it for busy parents. Have you been to the Azores? Let us know in the comments. Episode Guide: 0:00 Welcome to MTM Travel 0:23 Mark's Back From the Azores 1:01 Rakuten's Huge Card Offers (Up to 40K Bilt Points) 3:08 Royal Air Maroc Business Class Review 5:01 Where the Service Fell Short 7:55 Casablanca, Bus Gates & a Surprisingly Good Lounge 11:30 Lisbon: Uber Chaos & a Rooftop Sunset 14:48 Pizza Hut's Double Stuffed Crust 15:44 Why Portugal Is So Underrated 18:48 TAP to the Azores & the Middle Seat Debate 22:12 The Azores: Hawaii Without the Price Tag 27:00 Where to Stay: The Octant via Amex FHR 29:30 Pineapples, Tea & Thermal Springs 32:09 Escaping the Boston Storms for Free 36:05 Is Whirlwind Travel Worth It? 39:01 Final Thoughts Links Rakuten offers - https://milestomemories.com/rakuten-offering-extra-bonus-for-bank-of-america-cards/

Using AI is one thing. Building an entire system around it is another.Matthew Bertram sits down with returning guest Richard Valentine and Hector Herrera for a deep technical conversation about how AI power users are moving beyond individual prompts and building their own AI architecture, specialized agent teams, memory systems, workflows, and internal infrastructure.They explore model drift, token management, specialized AI teams, scheduled learning, memory decay, human approval systems, and why AI shouldn't necessarily remember everything. The conversation also goes inside the challenge of transforming an organization from having a handful of AI power users to becoming truly AI-first.The discussion then turns to privacy, on-premise AI, security, credential management, deepfakes, impersonation, and the growing importance of controlling the infrastructure businesses increasingly depend on. Finally, they bring it back to marketing and SEO, exploring how AI systems can connect Search Console, analytics, trends, and other data sources to create feedback loops that continuously adapt marketing decisions to what audiences are actually doing.• rebrand updates and why we're building a broader SEO and AI community resource • why Claude can get “nitpicky” and how model behavior changes break workflows • token management, subagent sprawl, and rules for routing tasks to the right model • Hector's “teams” approach with doctrines, routing, scheduled learning, and change logs • memory decay, relevance scoring, and crystallization for keeping knowledge accurate over time • AI-first adoption inside organizations, consistency across tools, and reducing “islands” of usage • personas in Slack and email assistants, including permissioned execution and critical-system guardrails • on-prem and private setups for regulated industries, resilience, and avoiding vendor lock-in • security protocols like redaction, vaulting secrets, daily scrubs, and minimizing human error • deepfakes, propaganda, impersonation risk, and why EEAT signals matter more than ever please leave an honest review, uh, how we're doing.Guest Contact Information:Richard ValentineWebsite: richardvalentine.devLinkedIn: linkedin.com/richard-l-valentineHector HerreraWebsite: hexaisystems.comLinkedIn: linkedin.com/hector-herreraMore from EWR and Matthew:Leave us a review wherever you listen: Spotify, Apple Podcasts, or Amazon Podcast.Free SEO Consultation: https://www.ewrdigital.com/discovery-callWith over 5 million downloads, The Best SEO Podcast has been the go-to show for digital marketers, business owners, and entrepreneurs wanting real-world strategies to grow online.Now, host Matthew Bertram — creator of the LLM Visibility Stack™, and Lead Strategist at EWR Digital — takes the conversation beyond traditional SEO into the AI era of discoverability.Each week, Matthew dives into the tactics, frameworks, and insights that matter most in a world where search engines, large language models, and answer engines are reshaping how people find, trust, and choose businesses. From SEO and AI-driven marketing to executive-level growth strategy, you'll hear expert interviews, deep-dive discussions, and actionable strategies to help you stay ahead of the curve.Find more episodes here: youtube.com/@BestSEOPodcastbestseopodcast.combestseopodcast.buzzsprout.comFollow us on:Facebook: @bestseopodcastInstagram: @thebestseopodcastTiktok: @bestseopodcastLinkedIn: @bestseopodcastConnect With Matthew Bertram: Website: www.matthewbertram.comInstagram: @matt_bertram_liveLinkedIn: @mattbertramlivePowered by: ewrdigital.comSupport the show

I'll admit it. I came into this conversation ready to talk about "those damn kids." They give me the blank stare. They call me bro. My friend in staffing says they show up for one day of work and never come back. Phil Putnam walked me back from the ledge. (Mostly. The bro thing still bugs me.)Phil Putnam is a workforce behavior strategist and keynote speaker who spent 20+ years as a team member and executive at Apple and Adobe. Now he helps associations and companies like PCMA, Bloomberg, Slack, and Salesforce understand how different generations work and give. He's a Gen Xer with two Gen Z mentors, ages 26 and 22, and he is unapologetically pro-Gen Z.In this episode, we get into why safety is the North Star for this generation. They've never known life without school shootings, and many of them believe the planet won't outlast them. Phil maps what each generation wants from work: loyalty for boomers, excellence for Gen X, value exchange for millennials, safety for Gen Z. Most fundraising strategies are written by boomers and Xers, through a boomer and Xer lens.For EDs managing Gen Z staff, Phil explains why "bring me a first draft" can feel terrifying to someone raised on teaching to the test. His advice: never lower the job requirements when a Gen Z fundraiser says they hate the phone. Pair the requirement with safety instead. Try it, and I won't punish you for the draft. And if they still won't do the job, find them another role or let them go. Replacing an employee costs roughly 150% of their salary.Then we tackle loyalty. Phil's take: Gen Z is loyal, just not to employment as we know it. The oldest Gen Zer has been working for six years. Layoffs, COVID, AI, more layoffs. Top performers get an average raise of 3.7%. The math doesn't math.On the donor side, Gen Z is 27% of the workforce today and will be 31% by 2035. Forbes 30 Under 30 is almost entirely Gen Z. Phil's approach starts with values alignment: ask what they care about and what they're afraid of, then take their answers at face value. For retention, keep the first gift easy, put your Gen Z donors in the room with your boomers, and connect them to each other.My favorite moment is Phil's welcome email test. You pay an association hundreds of dollars, and the first email asks you to join a committee. It's like ordering dinner and getting handed an apron. His point lands hard for fundraisers: your donors are your customer, not your resource.If your donor strategy only speaks boomer, this conversation is for you.Important Links:Phil Putnam SpeaksEmail Phil: booking@philputnam.comMy Big Ask Gifts ProgramMy Book, Get That Money HoneyMy NewsletterJoin the Free Webinar

Kris and David are back to discuss the week that was September 22-28, 2008. Topics of discussion include:ROH New Horizons debuts on PPV featuring Bryan Danielson vs. Tyler Black, Nigel McGuinness defending the ROH Title against Claudio Castagnoli, appearances from Naomichi Marufuji and Go Shiozaki, and so much more.An update on Kevin Nash's contract status in TNA.Booker T's horrible Ugandan accent in TNA."The Love-In" starring “The Guru” Sonjay Dutt and SoCal Val.Who's going to portray Suicide in TNA with Frankie Kazarian getting hurt?The Great Muta winning the Triple Crown again in AJPW.HUSTLE going down the toilet at the box office.The total insanity of the TEAM VADER shows in Tokyo.INDYPENDENCE DAY in England.Homicide is crowned "The King of New York” on a very random show in Queens.Erick Stevens winning the Jeff Peterson Cup the same weekend that Drake Younger wins the Ted Petty Invitational.Vince McMahon wanting better ACTING~! from the WWE roster.The TV wrestling boom in Spain officially coming to an end.Raw General Manager Mike Adamle. That is all.Santo Marella's rivalry with “BAPTISTA.”Triple H slumming it on SmackDown, where he's programmed with the Great Khali and Vladimir Kozlov.Stephanie McMahon beefing with Kevin Dunn even as far back as 2008.Why isn't WWE connecting with adults?All that and more on a fun episode of BTS!Timestamps:0:00:00 ROH0:23:15 TNA1:12:32 Eurasia: AJPW, NJPW, NOAH, Apache Army, DDT, Dragongate, Fukumen Mania, Futen, HUSTLE, Kageki, Team Vader, VKF, Zero-One. JWP, WSW (Portugal), & Indypendence Day2:00:52 Classic Commercial Break2:05:21 Halftime/Anti-aggregator ranting2:53:09 Other North America: AAA, CMLL, IWRG, Juarez, BPW, ACE, Mark Madden, Jeff Peterson Memorial Cup, & IWAMS3:38:56 WWETo support the show and get access to exclusive rewards like special members-only monthly themed shows, go to our Patreon page at Patreon.com/BetweenTheSheets and become an ongoing Patron. Becoming a Between the Sheets Patron will also get you exclusive access to not only the monthly themed episode of Between the Sheets, but also access to our new mailbag segment, a Patron-only chat room on Slack, and anything else we do outside of the main shows!If you're looking for the best deal on a VPN service—short for Virtual Private Network, it helps you get around regional restrictions as well as browse the internet more securely—then Private Internet Access is what you've been looking for. Not only will using our link help support Between The Sheets, but you'll get a special discount, with prices as low as $1.98/month if you go with a 40 month subscription. With numerous great features and even a TV-specific Android app to make streaming easier, there is no better choice if you're looking to subscribe to My AEW and other region-locked services.For the best in both current and classic indie wrestling streaming, make sure to check out IndependentWrestling.tv and use coupon code BTSPOD for a free 5 day trial! (You can also go directly to TinyURL.com/IWTVsheets to sign up that way.) If you convert to a paid subscriber, we get a kickback for referring you, allowing you to support both the show and the indie scene.To subscribe, you can find us on iTunes, Google Play, and just about every other podcast app's directory, or you can also paste Feeds.FeedBurner.com/BTSheets into your favorite podcast app using whatever “add feed manually” option it has.Advertising Inquiries: https://redcircle.com/brands

Your next great marketing idea might already be sitting in a sales call, customer email, or Slack message. In this episode, we're breaking down why customer conversations are one of your most valuable sources of marketing intelligence, and how to actually use them. You'll learn why specific customer language creates stronger content, how growing companies accidentally fall into generic messaging, and why marketing needs a direct line to sales, customer service, and the broader customer experience. You'll also learn simple ways to build that feedback loop without adding another complicated process to your business. Because instead of guessing what your audience wants to hear, your marketing should reflect what they're already asking, thinking, and saying.   Listen in as Emma explains: Why some of the best content ideas come from customer conversations How a disconnected marketing team can lead to generic, ineffective messaging Why customer objections are valuable data for stronger marketing content     And much, much more!  

When every individual on your team can suddenly move ten times faster, what stops them from moving ten times faster in ten different directions?In this episode of Supra Insider, Marc Baselga and Ben Erez sit down with Andrew Somervell, co-founder of Hamster, an AI-native workspace for product teams. Andrew and his co-founder built Taskmaster, the open-source tool that shipped plan mode before the major coding tools had it, and the question that kept coming back from users was how to take it to work. He explains why that pointed at a team problem rather than a tooling problem, and why he doesn't believe PMs want to live in a CLI.They explore the artifacts Andrew thinks a team actually needs, why he killed the PRD and what he ended up building in its place, the three meetings his team runs every week, and Ben's repeated pressing on the harder question underneath all of it: what genuinely changes when AI becomes multiplayer rather than a set of people each working alone with it.All episodes of the podcast are also available on Spotify, Apple and YouTube.New to the pod? Subscribe below to get the next episode in your inbox