Podcasts about TAM

In this episode of the Ecomm Breakthrough Podcast, host Josh Hadley explores why businesses hit growth plateaus, identifying two key factors: execution and market size. Drawing from his experience scaling an ecommerce brand to eight figures, Josh emphasizes that even skilled operators are limited by their total addressable market (TAM). He advises entrepreneurs to evaluate their market's size and growth trajectory, warning against shrinking niches like keto snacks. Josh recommends pivoting to adjacent or larger markets when growth stalls, citing Simple Modern as a success story, and encourages choosing markets with strong tailwinds to maximize business potential.Bullet Points:Mindset shift regarding stalled business growthTwo primary reasons for growth plateaus: execution and market sizeImportance of selecting the right total addressable market (TAM)Insights from scaling an ecommerce brand from zero to eight figuresImpact of market size on business growth potentialExamples of markets experiencing growth and decline (e.g., keto snacks, med spas)Need for entrepreneurs to evaluate true market size and growth rateRecommendations for pivoting to adjacent or larger marketsImportance of understanding market nuances beyond broad industry dataStrategies for leveraging existing expertise to tap into new growth opportunitiesTimestamps:00:00:00 Introduction: Two Reasons for Stalled GrowthThe host introduces the two main reasons for stalled business growth: execution and the size of the total addressable market.00:01:00 The Importance of Market SizeYour business goals must match the size of the market you're in. The total addressable market is a key predictor of success.00:03:32 Good Operators in Bad MarketsEven the best operators with great teams and processes will be limited by the size of the market they serve.00:06:19 Understanding the True Total Addressable MarketEntrepreneurs should analyze specific, fast-growing niches within a larger market, not just the overall industry data, for maximum growth potential.00:08:37 Aligning Your Goals with Your MarketChoose a market size that matches your ambitions, whether you want a $100 million brand or a smaller lifestyle business.00:10:55 A Personal Example: Recipe CardsThe host shares his experience starting in the declining recipe card market, highlighting the importance of avoiding stagnant or shrinking markets.00:12:04 What to Do If You're in a Stagnant MarketInstead of exiting, analyze your market's growth rate. If operations are solid, the market itself may be limiting your growth.00:13:17 Pivoting to Adjacent CategoriesThe host uses Simple Modern as an example of a brand that expanded into adjacent categories to continue growing after its primary market plateaued.00:15:48 Final Advice and ConclusionTo achieve ambitious growth, focus on large, fast-growing markets, as even average operators can succeed with strong market tailwinds.Links & Mentions:Med Spa Space: "00:03:32"  Creatine and Electrolytes: "00:07:26"  Gummies: "00:08:37"  Poppi Soda: "00:08:37"  Grüns: "00:08:37"  Total Addressable Market (TAM): "00:09:38"  Simple Modern: "00:13:17"  ChatGPT: "00:15:48"Transcript:Josh Hadley 00:00:00  Today, I want to dive into a massive mindset shift that I have had when it comes to stalled growth in a business. Typically, it boils down to two major reasons. Number one is going to be execution, and number two is going to be the size of the market. Today I want to unpack why your brand might not be growing to the level that you want it to be, and how I've seen that happen in my own business. Welcome to the Ecomm Breakthrough Podcast. I'm Josh Hadley. I've scaled my own ecommerce brand from 0 to 8 figures, and I'm actively building towards nine figures in sales. This podcast is where I document that journey and share the systems, the strategies, and the lessons learned in real time so that you can learn what actually matters and scale your own business. My name is Josh Hadley. First and foremost, I am a man of faith. I am a husband to a beautiful wife and the father of four children. I've been playing in the e-commerce space for over a decade, doing over $20 million in annual revenue in multi-million on sales channels such as Amazon, TikTok, Shop and Shopify.Josh Hadley 00:01:00  And last but not least, I am also the host of the number one Business strategy podcast for eCommerce entrepreneurs, and that is E-com breakthrough. Today, I want to unpack something extremely important that honestly took me way too long to discover and actually understand. And it is this sometimes the goals and passions that you have, and the size of business that you want to create does not match the size of market that you are you are currently playing in. And the example is this. Let's say you want to have a $100 million brand before you can say, yeah, I'll be able to create $100 million brand. Even the best operator may not be able to create a $100 million brand. If they pick the wrong drumroll, please mark it. At the end of the day, the total addressable market is one of the number one things that will predict the success and the future growth in your brand More than anything else, I have seen this time and time again, and the lesson comes from this as I continue to go to ecommerce events and different mastermind groups, oftentimes I've been sitting next to an operator that, honestly speaking, I'm not overly impressed with.Josh Hadley 00:02:19  They kind of seem pretty lazy, and they don't really run a very good team, and they might be fairly unethical. Yet guess what I hear? Oh yeah, I'm running this million dollar brand. And guess what? The underlying reason as to why they're running a $100 million brand is they are riding the coattails of a massive trend and a massive opportunity that is growing over 20% annually year after year. The market is growing in a massively meaningful way, and so they only need 0.5% of the market. And honestly, they don't even need to be that good of an operator because like the market's just so hungry for what it is that they are offering. Alex Ramos talks a lot about that today. Right now, which is like the med spa space is just like a massive opportunity. It is growing year over year, month over month. It is a hot space. And honestly, there's a lot of like fairly poor operators that are succeeding massively well in the med spa space just because like it is such a hot and attractive and growing market right now.Josh Hadley 00:03:32  And so the lesson is this you might be one of the best operators that is out there, meaning you're a great leader, you have a great team behind you, you have the right processes, you have the right playbook. But guess what? If you're in the wrong market, you're only going to rise to the size of market that you can actually conquer and however big that market is. So let's take this as an example. Let's say there's a particular market for we'll talk about a specific supplement. Right now let's talk about, like, the Cato market. Okay. So in the Cato market, or let's call it the snack market, not necessarily supplements. Okay. Cato was on a tear, you know, five years ago or so. But Cato as a whole is actually seeing declines year over year now. So now is not...

Po strateških razpravah na blejskem forumu, ki se je sklenil včeraj, je pozornost usmerjena v Dublin. Tam so včeraj zasedali obrambni ministri Unije in sklenili, da je treba hitreje zapolniti vrzeli na področju evropske obrambe. Danes se bodo zbrali zunanji ministri in med drugim razpravljali o spremembah odločanja na področju zunanje politike. Druge teme: - Pri nas pridelamo vse manj jabolk, letos zaradi podnebnih sprememb ena najslabših sezon - Slovenski turizem dosega rekorde, vprašanje pa je, kako upravljati rast - Na beneškem filmskem festivalu tudi slovenska manjšinska koprodukcija in film s Slavojem Žižkom

Today, I'm joined by Lorne Lucree, founder & CEO of Wizard Wellness.   Aspirational allergy support, Wizard Wellness is applying skincare logic to nasal care with its drug- and steroid-free sinus microbiome system.   In this episode, we discuss why the allergy aisle is ripe for disruption.   We also cover: Missing solutions for a large TAM First clinical testing and vanity metrics in allergy aisle Beauty playbook: microbiome science meets friction reduction   Subscribe to the podcast → insider.fitt.co/podcast  Subscribe to our newsletter → insider.fitt.co/subscribe  Follow us on LinkedIn → linkedin.com/company/fittinsider    Website: www.wizardwellness.com Available at Amazon, Walmart, CVS, and Target Store Locator: https://wizardwellness.com/pages/where-to-buy  Instagram: https://www.instagram.com/wizardwellness  Tiktok: https://www.tiktok.com/@wizardwellness    -   The Fitt Insider Podcast is brought to you by EGYM. Visit EGYM.com to learn more about its smart fitness ecosystem for fitness and health facilities.   Fitt Talent: https://talent.fitt.co/  Consulting: https://consulting.fitt.co/  Investments: https://capital.fitt.co/    Chapters: (00:00) Introduction (01:18) Background and overview (03:15) Drug-free, steroid-free approach (04:30) Prestige beauty connection to allergies (05:45) Microbiome science evolution (07:30) Vanity metrics and clinical testing (09:15) TAM and market opportunity (12:27) Drug-free solutions gaining traction (15:00) Customer acquisition and messaging strategy (19:00) Cleanse, relieve, balance (20:15) Navigating the education path (23:15) Oral care and skincare parallels (27:30) Shelf positioning and brand blocking (29:15) Expansion and messaging (31:48) Where to find Wizard Wellness (32:23) Conclusion

Náray Tamás élete során többször is megmutatta, hogy nem félt hátat fordítani annak, amit mások a siker csúcsának tartanak. A magyar divatvilág egyik legismertebb alakjaként csinált fényes karriert, majd mindezt maga mögött hagyva nyolc éve Spanyolországban kezdett új életet, festőművészként és íróként. És közben sem veszítette el azt a szókimondó őszinteséget, amely miatt sokan tisztelik, mások hevesen bírálják. Vele készült ez a mostani podcast, amelynek ez az első része hagyományos, nem mellesleg élénk, humoros és sziporkázó beszélgetés, majd a szeptember 3-án este 8 órakor felkerülő második részében jön Náray Tamással is a közkedvelt IGEN vagy NEM című, félig komoly, félig vicces játék, amely ezúttal is tartogat meghökkentő válaszokat, váratlan vallomásokat és felszabadítóan humoros fordulatokat. TÉMÁK EBBŐL A PODCASTBÓL: ◼ A siker vajon szabadságot ad, vagy kompromisszumokat követel? ◼ Meddig érdemes alkalmazkodni a környezetünkhöz, és mikor kell nemet mondani? ◼ Felelősek vagyunk-e minden döntésünk következményéért? ◼ Lehetséges-e tévedések nélkül élni? ◼ Az ember előbb találja meg önmagát, és utána lesz szabad, vagy a szabadság vezet el az önismerethez? ◼ Az őszinteségnek mindig van helye az emberi kapcsolatokban?Hogyan támogathatja a munkánkat? - Legújabban már a Donably felületen is támogathat bennünket, itt ÁFA-mentesen segítheti munkavégzésünket: https://www.donably.com/friderikusz-podcast - De lehet a patronálónk a Patreon-on keresztül is, mert a támogatása mértékétől függően egyre több előnyhöz juthat: https://www.patreon.com/FriderikuszPodcast - Egyszerű banki átutalással is elismerheti munkavégzésünk minőségét. Ehhez a legfontosabb adatok az alábbiak: Név: TV Pictures Számlaszám: OTP Bank 11707062-21446081 Közlemény: Podcast-támogatás Ha külföldről utalna, nemzetközi számlaszámunk (IBAN - International Bank Account Number): HU68 1170 7062 2144 6081 0000 0000 BIC/SWIFT-kód: OTPVHUHB Akármilyen formában támogatja munkánkat, nagyon köszönjük!Kövessenek, kövessetek itt is:youtube: https://www.youtube.com/c/FriderikuszPodcastFacebook: https://www.facebook.com/FriderikuszPodcastInstagram: https://www.instagram.com/friderikuszpodcastSpotify: https://open.spotify.com/show/0TBImnF4bdNCvmhJwyOlRhAmazon Music: https://music.amazon.com/podcasts/a159b938-d63e-4927-9e9b-bea37bc378d3/friderikusz-podcastYoutube Music: https://music.youtube.com/playlist?list=PLu6L9HlV4-KuNOYy_rS97rP_Q-ncvF14rApple Podcasts: https://apple.co/3hm2vfiDeezer: https://www.deezer.com/hu/show/1000256535

Strap in and check your thrusters, we're looking back at the animated show Star Wars Resistance! Some of our stand out aspects include the visual style, Tam's journey into the First Order, the found family standing together on the Colossus, and more! If you haven't checked out this hidden gem of a show we hope we can inspire you to give it a chance! Hosted on Acast. See acast.com/privacy for more information.

What if America could add gigawatts of nuclear power without building new nuclear plants? Alva Energy is upgrading existing reactors to produce 20–30% more power, potentially adding 200–300 megawatts per plant in just 3–5 years.Company bio:Alva Energy is developing technology to increase the output of existing nuclear power plants by upgrading their nuclear steam systems and adding a second turbine generator. The company is already working exclusively with six operating reactors, and estimates projects could add roughly 200–300 MW for around $1B, less than one-fifth the cost of new nuclear construction.Speaker bio:James Krellenstein is the co-founder and CEO of Alva Energy. A physicist by training and the son of a nuclear engineer and energy economist, James combines nuclear technology, project finance, and first-principles thinking. Alva has raised a $32M Series A led by former Intel CEO Pat Gelsinger with Playground Global.Five lessons for entrepreneurs:Look for billion-dollar opportunities hiding in plain sight – Alva's core nuclear uprate approach had already been demonstrated in Sweden. The opportunity came from understanding why it hadn't scaled in the US—and redesigning around that bottleneck.Go to the source material – James traces part of Alva's technical insight to reading a 15,000-page nuclear engineering filing. Secondary summaries are convenient; sometimes the best opportunities are buried several layers deeper.Design the financing alongside the technology – Alva separates its venture-backed TopCo from individual project companies that can use project debt and equity. The goal is to make nuclear upgrades financeable like other infrastructure assets.Don't let venture capital's obsession with speed destroy execution – Demand grew faster than Alva expected, reaching engineering exclusivity with six reactors in under two years. James has deliberately tapped the brakes when necessary because nuclear engineering quality matters more than locking up TAM.Align incentives around getting projects built – Instead of relying on traditional time-and-materials contracts that can reward higher project costs, Alva uses fixed-price structures and invests alongside project investors. Everyone benefits from bringing projects online faster and cheaper.--1️⃣ Join our confidential CEO community.Private CEO group for VC/PE-backed climate tech founders navigating capital, strategy, and scale. Capped at 45 CEOs.→ entrepreneursforimpact.com2️⃣ Join 40,000 professionals who get our newsletter.Climate tech finance, strategy, leadership. 2-min read.→ entrepreneursforimpact.substack.com3️⃣ Leave a podcast review.If you got value, take 30 seconds and do the community a favor. It helps push more capital and talent toward scalable climate solutions.

A Tisza Szigetek tagjai csendben, önfeláldozással dolgoztak Magyar Péter sikeréért és a kormányváltásért, négy hónappal a választás után mégis látványosan háttérbe szorultak. Augusztus huszadikán rendezik a Tisza Szigetek országos találkozóját. Megnézzük, milyen viszony van a szigetek és a kormány között, és mire valók egyáltalán a Tisza Szigetek? A vendégünk Mikecz Dániel politológus, a Társadalomtudományi Kutatóközpont kutatója.—host, szerkesztő: Kuczogi Jakabszerkesztő: Tóth Szilárd Jánosélővágó: Gerendás Bálintvideótechnikus: Szántó Tamás grafikus: Szabó Dominik vágó: Kubik Bence kommunikáció: Gál Borbála gyártásvezető: Kátai Orsolya—Legyél rendszeres támogató! https://cause.lundadonate.org/partizan/adomanyPartizán webshop:https://shop.partizan.hu/—Írj nekünk!Ha van egy sztorid, tipped vagy ötleted:szerkesztoseg@partizan.huBizalmas információ esetén:partizanbudapest@protonmail.com(Ahhoz, hogy titkosított módon tudj írni, regisztrálj te is egy protonmail-es címet.)Támogatások, események, webshop, egyéb ügyek:info@partizan.hu—Csatlakozz a Partizán közösségéhez, értesülj elsőként eseményeinkről, akcióinkról!https://csapat.partizanmedia.hu/forms/maradjunk-kapcsolatban—Legyél önkéntes!Csatlakozz a Partizán önkéntes csapatához:https://csapat.partizanmedia.hu/forms/csatlakozz-te-is-a-partizan-onkenteseihez—Iratkozz fel a Szignálra: https://csapat.partizanmedia.hu/forms/iratkozz-fel-a-szignalra-a-partizan-kulpolitikai-hirlevelere/Iratkozz fel a Partizán Szerkesztőségi Hírlevelére!https://csapat.partizanmedia.hu/forms/iratkozz-fel-a-partizan-szerkesztoinek-hirlevelere

In this episode of The Circuit, hosts Ben Bajarin and Jay Goldberg break down the shifting dynamics across the semiconductor landscape, from analog chips to custom silicon and corporate balance sheets.Analog Devices (ADI) & The Data Center Wave: ADI reports a strong quarter, driven by a doubling of its data center revenue and expanding opportunities in 800-volt data center architectures. Ben and Jay discuss ADI's conservative focus on SAM (Serviceable Addressable Market) over TAM, high gross margins, and how analog content per gigawatt is becoming a key driver for power, safety, and sub-volt conversion.AI Sentiment vs. Market Reality: The hosts address the hype around AI "curing cancer," clarifying Moderna's recent bio-informatics announcement, and discuss the growing local friction surrounding massive data center construction projects.Custom ASICs & Marvell's Google Win: Analysis of Marvell's expanding relationship with Google for periphery XPU attach, optical interconnects, and CXL. They unpack why this is a massive win for Marvell's diversification and clear up misconceptions regarding Broadcom's market position.The Era of "Balance Sheet Competition": Semiconductor giants are using equity, warrants, and Special Purpose Vehicles (SPVs) to fund data center capacity. Ben and Jay debate the risks of chip companies taking on debt-like obligations to compete with NVIDIA.

When we first dicsussed the Summer of Simulative AI in 2024 we knew it would be a brief summer, but it has recently come back with a vengeance with SimGym in April and now Simile AI's $2B Series B, backed by GreenOaks and Index Ventures with prominent backers like Fei-Fei Li and Andrej Karpathy, running tens of millions of simulations for Fortune 100 clients like CVS and 85–99% accuracy vs human focus groups. Time to catch up on why this Second Summer of simulation is working!From creating Smallville, the landmark 2023 paper on Generative Agents that showed AI characters could remember, plan, socialize, and develop emergent behaviors, to now building foundation models of human behavior, Joon Sung Park is trying to answer a much bigger question: what if we could simulate the world before making decisions in it? In this episode, the Simile co-founder and CEO joins us to unpack the path from generative agents to digital twins, why today's frontier models still fail to capture how humans actually behave, and what it would take to eventually simulate all 8 billion people on Earth.We go deep on Simile's approach to modeling human behavior: long-form interviews, observational and transaction data, randomized controlled trials, population-level and individual-level models, and post-training on the causal mechanisms behind why people make decisions. Joon explains how his research created digital twins that reproduced human behavior and attitudes 85% as accurately as people reproduced their own responses, why models optimized to be rational can be bad simulations of irrational humans, and why understanding “social physics” may require changing model weights rather than simply prompting frontier LLMs.We also explore the much larger ambition behind simulation: testing products and policies before deploying them, finding counterintuitive paths toward desired outcomes, modeling emergent behavior across entire societies, and potentially tackling problems like climate change, democratic instability, and UBI. Joon reflects on scaling laws for simulation, the economics of data-center-scale simulated worlds, the connection to Thomas Schelling and psychohistory, why simulation is surprisingly similar to painting, and whether we might already be living in one.We discuss:* How Smallville and Generative Agents led to Simile* Why Joon's team asked: “What if we can just recreate the world that we live in?”* Why useful personal agents require deep models of their users* Memory architectures, Markdown files, and the limits of prompting* “Social physics” and behavioral foundation models* Why web data captures what people say more than what they actually do* Interviews, transactions, observational data, and randomized controlled trials* Why predicting the future matters less than understanding how to shape it* How Simile creates representative simulated populations* Simulation versus prediction and the connection to Foundation's psychohistory* How to evaluate simulations instead of simply stacking LLM hallucinations* Creating digital twins of 1,000 real people and reaching 85% behavioral accuracy* Why frontier models can struggle to reproduce real human behavior* Why good simulations need to reproduce human biases and mistakes* Post-training models on randomized controlled trials* Population-level versus individual-level simulation* Scaling laws for human simulation* The long-term ambition to simulate all 8 billion people on Earth* Whether simulations could help solve climate change or detect collapsing democracy* Thomas Schelling and the history of agent-based modeling* Why future simulations could require an entire data center* Multi-agent simulations and what happens when simulated people interact* Replacing expensive human panels with synthetic populations* Why market research is only the starting point for simulation* Why Joon sees simulation as surprisingly similar to painting* Using simulation to study questions like UBI* Whether we are already living in a simulation* Why AGI and simulation may be the twin technologies of advanced civilizationsJoon Sung Park* LinkedIn: https://www.linkedin.com/in/joonspark* X: https://x.com/joon_s_pk* Website: https://www.joonsungpark.com* Simile: https://www.simile.comTimestamps00:00:00 Introduction and Joon's Path from Art to AI00:01:46 Smallville, Generative Agents, and the Origins of Simulation00:05:03 “Let's Just Create a World” and the Future of Personal Agents00:09:53 Social Physics and Behavioral Foundation Models00:14:08 Prediction vs. Simulation: How Do You Shape the Future?00:16:59 How Simile Models Real People and Populations00:25:35 Evaluating Simulations, Digital Twins, and 85% Accuracy00:30:23 Post-Training Models to Reproduce Human Behavior00:40:04 Scaling Laws and Simulating 8 Billion People00:43:10 From Schelling to Society-Scale Agent Simulations00:46:13 The Cost and Economics of Simulating the World00:52:05 Real-World Use Cases, Synthetic Populations, and the Market00:57:27 The Future of Simulation, Painting, and UBI01:04:23 Are We Already Living in a Simulation?01:06:08 Building Simile and HiringTranscriptIntroduction: Joon Sung Park, Simile, and the Story So FarVibhu [00:00:00]: Today, we have Joon in the podcast. Excited to kick this one off. Very exciting company. I wanna kick off and ask you the question, talk us through the story of your life. How have you gotten here?Joon [00:00:13]: Yeah, for sure. I'm really excited to be here. A story of my life. So I was born in Korea, and I lived there for a good 11 years or so of my life, and then my family moved to Boston. So we moved when I was 11, and my parents were doctors, so they were going through their postdoctoral studies. My dad was a surgeon, so he was doing his sabbatical years at the Boston Children's Hospital. So I grew up there, not too close to tech. I was very much a music and artsy, painting kind of guy.Vibhu [00:00:49]: Painting.Joon [00:00:49]: Exactly. I got into painting a little bit later, in high school, but that's what I used to do. And then I grew up mostly in the East Coast after Korea. So I lived a good number of years in New Hampshire, and then I went to college in Pennsylvania. And I got into more of this tech scene, in college. So I was originally trained to be an artist. I thought that would be my professional career. So it wasn't a hobby. It was like, “Hey, let's make a living out of this.” And then gradually, I got really interested in this idea of, hey, the greatest artist often creates their own medium, and the best medium that we had available today was in computation. So I decided to go deeper into that, and one thing led to another, and we can go deeper into this, but I decided that research was something that I gradually got interested in, and here I am.Smallville, Generative Agents, and the 2023 Breakout PaperSwyx [00:01:46]: So there's a lot that you packed into the research components. You had one of the best papers of 2023, which was the generative agents paper, commonly known as the Smallville paper.Swyx [00:01:58]: Feel free to call back to anything else that you mentioned, but most people would have heard of you from this. Do you have any statistics on how many people have, like, read it? arXiv gives you something, right? Some stats.Joon [00:02:10]: Yeah, it's a good question. How many people have read it, I'm not sure.Joon [00:02:14]: I know we do keep track of citations, and they are going up quite fast.Swyx [00:02:23]: Yeah, Google Scholar has 7,200 citations.Vibhu [00:02:25]: I feel like it made a bigger hit than that, and it was a pretty instrumental paper. It got cited so many times.Swyx [00:02:34]: It is frequently the answer when people ask, “What is the best paper you've read recently?” It's this one.Vibhu [00:02:39]: I thought the memory component was pretty underrated. It was a very good early memory system, and one of the biggest papers.Foundation Models and the Search for Killer ApplicationsJoon [00:02:47]: Yeah, so maybe I can talk a little bit about how this particular paper came together. So when I got into research, it was back in 2020 when I started my PhD program at Stanford, and that was the year, when we were about to get GPT-3 to be available. So we already had GPT-2, and you could sense that there was this new class of models that was just becoming available in the market, and the team got very intrigued. And the general consensus was, “Well, is this model going to be useful for anything?” “It's really strange that these models are not trained to do any particular task.” But we decided to take a bet. So a large group of scholars at Stanford, and it was led by one of my co-founders, Percy Liang, and we came togetherSwyx [00:03:35]: Who coined foundation models.Joon [00:03:36]: Who coined the term foundation models. We wrote this paper, where that term came from called Opportunities and Risks of Foundation Models. And during that process, really the thing that I started to think deeply about was, here is a model that is fundamentally new in our ecosystem. The reason why this was new was it wasn't, again, trained to do anything in particular, but its premise was it could do anything and everything. It was like a stem cell, if you were to take a biology analogy. And I got really interested in this idea that, well, if we were to really think about what are the killer applications that this particular technology would enable, what would that be? Many of my colleagues were using this for simple classification, simple generations. Interesting that these models can do that, but from an interaction perspective, not that interesting. We've known how to do that for many decades. And what we came down to was these models are trained on this very broad data from the web, right? So these are human behavioral data. It's social media, Wikipedia, all these data. So if you poke at the right angle, then you could see human behavior that would just pop out that's quite realistic, and we've never seen that before.The Time Machine Game and Recreating the WorldJoon [00:04:45]: So that got us really interested. The exercise that we decided to do, with this particular group of colleagues, Michael Bernstein, Percy Liang, and myself, who ended up becoming my co-founder at Simile, we sat down and we played this game that we call the time machine game.Joon [00:05:03]: Imagine we were to get on a time machine and fast-forward 10 years and look back. What would have been the single application that will have mattered that would be the most interesting and inspiring? And when we thought, “Well, what if we can just recreate the world that we live in?” it's really hard to get more ambitious than that. Like, let's just create a world.Joon [00:05:24]: And that's where we started. And initially, we had this paper that was a precursor to the generative agents paper called Social Simulacra.Swyx [00:05:32]: Before you go further, were there other candidates for the most ambitious thing in the time machine exercise? What was number two or number three?Personal Agents, User Models, and Why Simulation Came FirstJoon [00:05:44]: There is a close second that we were considering, which ended up becoming more of these automation tools, especially the vision around really personalized agents that would do things for you.Swyx [00:05:59]: That's also happening.Joon [00:06:00]: It's also happening. But it was interesting for us, right, in that the reason why, we decided to go with the idea of simulation, one, I was a huge science fiction nerd, and this idea of creating simulation, I was personally really just fascinated. I loved the idea. It's really cool to see, like, a game town like this and just see these agents live in it. But at the same time, my bet was if you were to create a really amazing personal assistant out of this technology, what you need first is an amazing model of your users. So I told a model, “Hey, can you go buy late dinner for me?” And it orders Hawaiian pizza, and I do not like pineapples on my pizza. Then it totally failed. The way for it to not make that mistake is only by having a deep understanding of who I am. And I gave a very simple and dumb example here, but you can imagine how this core understanding of people is instrumental. This is how, if we have our family and closest friends, they have a good mental model of who we are. That's the basis of our social connection. So our bet also was this technology around simulation, creating accurate representation of people ought to precede the more complex agents that would automate the world that we live in. So that was the bet. But that was a very close second, and I'm still very much fascinated by it. I think there's a lot of interesting work that's going around. My hot take here, though, is I don't think we've seen a true personal assistant that's useful, in ways that meet the ambition of that particular line of work. I think there are early applications that are interesting, and if you talk to even ChatGPT nowadays or Claude, they know a lot about us. So a lot of the generation it's doing, I do think it's much more tailored, but I think the ambition is quite large in that field, and I don't think we quite have all the right ingredients just yet.Swyx [00:08:01]: So OpenClaw and these personal agents, what do you want to see from them that they don't currently have?Memory, Markdown, and the Limits of PromptingJoon [00:08:09]: I do think it's slowly getting there, but I do generally want them to have much deeper understanding of the person. Right now, you look at the models. OpenClaw, what it's leveraging is a Markdown file, and I think it's quite clever, right? So if you look at the generative agents paper, this was the same intuition that we had, where initially when we were creating the memory architecture for the generative agents, and, like, this is, like, back in 2022, so we didn't really quite have the idea of even agentive architecture or the term agent. But the intuition that we shared with some of the work that's coming out today was we initially thought, “Well, do we want to make the memory into, let's say, knowledge graph? Do we want to train a bespoke model?” All of these things. And what we decided to do was, “No. Just forget about all this.” These language models are quite good at modeling text and understanding and reasoning about text. So just put everything in a Markdown file or a text file. You're done. I thought that was quite interesting that we could do that, and there's a lot of strength in doing that. But also, there are limitations. It's the way you retrieve and make sense of data that's extremely large, it takes a lot of work. So I think that technology is getting better. I also do, however, think, there are certain things you just cannot shape just by prompting the model. So to some degree, you do need to touch the parameters of the model itself. So there is this work that I do think does need to happen, and it is happening. The question is, how far can we take it? How do we source data, and how do you also create an ecosystem where people are continuously feeding data to this model so it's learning about you?Vibhu [00:09:50]: What's the intuition between why you need to do it in the model?Social Physics and Behavior Foundation ModelsJoon [00:09:53]: My intuition behind the actual when do you train or even post-train a model versus just prompt a model is if the model has to learn the underlying physics of the world that it's operating in. So it has to learn new social physics. The places where it doesn't have to train are the places where it already has the physics. We trust the physics. It already has the base statistics, but it's just trying to react to an environment. Then I think you can just prompt your way into getting the actions out of it. I don't think the models that are out in the open have yet learned the complete mapping of social physics of humanity. This is one of the core theses of Simile, right? And one of the core reasons why that is the case is if you look at the data that the model was trained on, these models were trained on the web data, like, whatever was available on the web. And these are really interesting data sets, but they are fundamentally the self-exposed attitudinal data with some behavior data that's sprinkled around here and there. And it has yet to learn the really deep behavioral nature of people, not just what people say they do online, but what they do in real life. And this is one of what I would consider to be the dark knowledge of humanity that we haven't quite captured. And it's these data that would also need to get factored into the model creation.Vibhu [00:11:21]: You call it behavior foundation model.Vibhu [00:11:23]: There's a good one-liner here, but outside of that, what type of data do you need? What are you changing on the model level? How do you go about modeling, doing a behavior foundation model?The Three Data Buckets: Interviews, Behavior, and CausalityJoon [00:11:35]: We think about data in three buckets. So one bucket is interview data. It's quite interesting. Rich qualitative data is interesting. It's not behavioral, but we would literally ask people, “Hey, tell me the story of your life.”Vibhu [00:11:53]: It's just what we're doing here exactly.Joon [00:11:54]: The question that you all asked at the beginning of this interview literally is the question we also ask. And we ask our participants to go a little bit deeper, than how far I went. Maybe I can give more of my life story in lieu of this. But the reason why that data is interesting is by learning about this very long-tail information about people, you get a lot of texture around this model, like, this person as a model. So even understanding their childhood memory or even their trauma, their first love, these things, quite informative in ways that's really hard to predict. So that's one. Then there are two tranches of what I would consider to be the behavioral data. One kind of behavioral data is observational. So these might be like transaction data, or these might be data that you can get by scraping the web, right? So you can imagine why these data sets would be interesting, right, because they give you the base statistics of people's behavior.Joon [00:12:55]: But then there is the last category of data, that I personally think is perhaps the most important, which is the data that describes the causal mechanism, the whys of people. Some of this is covered by the interview data, the qualitative, because people talk about why they made certain decisions. But really, where you get to see the most behavioral aspect of this is in randomized controlled trials, like RCTs. Imagine you have the same setup, but you have a few different variables that you are trying to tweak. Can you get realistic human behavior out of it in ways where, imagine you had this particular option. Imagine you're even trying to choose whether you're going to drink coffee or not. The day you drink coffee versus the day you didn't drink coffee, does your behavior change? That's a data set that describes a causal mechanism. This is quite important in modeling people. The reason why this is important is oftentimes when people come to us, or not just to us, but the reason why people are interested in simulation isn't because they want to predict the future. If you're trying to win against the stock market, predicting the future is interesting.Prediction vs. Simulation: Shaping the FutureJoon [00:14:08]: But most people, most decision-makers, what they want to know is, how can we shape the future? It doesn't really help you to hear that your sales are going to tank in two quarters. They're just gonna say, “Wow, that sucks.” What they want to know is, well, what do we need to do now to avoid that future? That's the causal mechanism. And this is also very hard data to come by, right, because the world is our ground truth, but it happens once. So in a very controlled setup where everything is equal except for one variable, this kind of data set rarely happens. So this is a reason why this data set is both hard to come by and quite important if you're trying to model human behavior.Swyx [00:14:50]: So behavior, I think, is the hardest data set to acquire. What is out there? What is even possible? You're not going to know a lot of details about my life. I don't even have data for myself on my own health or habits, and I just don't log everything. So how can you have that data?Joon [00:15:14]: So we run a lot of randomized controlled trials.Swyx [00:15:17]: But you put people in the lab, they watch them sleep, or what?Joon [00:15:20]: We do care a lot about the consent process. People know that we invite them to be a member of this community to both share data and have themselves represented in different forms. But we bring a lot of people to the lab, or virtual lab, where we design experiments that would pose them real behavioral decisions. And often in these experimental setups, what makes the difference between what is attitudinal versus behavioral is whether the stake in your decision is real. That's ultimately what makes it behavioral. So in these setups, we are inspired by our colleagues in social sciences, psychology, and so forth. So when they run studies, the techniques they utilize is imagine there's an online store that you're inviting people to come by. Then whatever they purchase in this experiment, they actually get that item delivered. Like, these are the things that make the stakes real. So we run a lot of these experiments, and we also do partner with firms. Right now, we also have customers who are quite excited to at least give us a glimpse of the behaviors that their users exhibit so that we can get a little bit deeper understanding of how people behave in these different platforms.How Customers Use Simile: Populations, Queries, and ExperimentsVibhu [00:16:39]: I think on the customer side, they have a lot of data about their users, who has bought. They have the action data.Vibhu [00:16:47]: Can you walk us through an example of what someone comes to you for? What questions would they want solved? Do you customize a model for them? Do you have something off the shelf? What does that look like?Joon [00:16:59]: Today, when people leverage our models, it's often to better understand the population of their interest. So usually, the start of the relationship, we come together and hear about what population they want us to model, right? So it might be that if you're a CPG company that's selling to all of the US, then maybe it's fairly straightforward. You want to model the gen pop of the US. But at the same time, if there is a vertical or if there's a market that they're trying to go into, imagine, they want to better understand, let's say, people in their 20s and 30s living in California. That's a much more specific population. So we hear about this population, and we go recruit these people, with consent, and with incentives, and we collect some of their data and create a model of these people. Then what our product allows you to do is query them. So it can take as input a filter that is a description of the population that you want to talk to, just like the one I just mentioned, and an environment. The environment can literally be survey questions, behavioral experiments, It can be A/B testing. Oftentimes, the core use cases are things like concept testing, to start with. But also, people sometimes want to do focus groups or one of the fun use cases that we also serve is even modeling things like earnings calls for public companies.Joon [00:18:21]: So these are the use cases that we often start with.Swyx [00:18:23]: Concept testing, is that an established term? I've never heard of concept testing.Concept Testing, Gallup, and PoliticsJoon [00:18:27]: Yeah. So it has to do with they have, let's say, different messaging, different products, different ideas.Swyx [00:18:32]: It's like a marketing exercise.Swyx [00:18:33]: Okay, got it. Got it. Politics?Joon [00:18:36]: We do, have a strategic partnership with Gallup, and of course, Gallup is deep into policy space and so forth. Right now, we have not worked deeply with politics, like that area just yet, however.Swyx [00:18:49]: I'm curious if there is demand or if they really would have different needs that somehow fundamentally don't mix with your existing, users or people.Joon [00:19:00]: I think there's certainly demand.Joon [00:19:02]: But we are very much mindful of how this technology gets adopted and the societal impact that we'll end up having with this technology. And I do see politics as an area where a company has to be particularly thoughtful about the way they operate and make impact. So this is where we also want to make sure that we form enough of guardrail and perspective on how to leverage this technology before we go on to serve markets like the politics.Swyx [00:19:29]: I'll give people an example. one of my favorite shows is The West Wing. I don't know if people have watched.Swyx [00:19:34]: One of the key storylines is, like, the president has, multiple sclerosis, but they haven't. they need to figure out how to disclose it. So they run a poll with a fake governor and ask people to respond on the poll,Counterfactuals, Polling, and When Simulation Is UsefulSwyx [00:19:47]: They try to make decisions based on the results of that poll on, like, how well they'll be received, like where, how should we play this?Swyx [00:19:54]: And I'm like, well, I think those counterfactual things, I would use a simulation for this if I could trust it.Joon [00:20:01]: For sure.Joon [00:20:02]: In that show, how'd it go?Swyx [00:20:04]: In that show, it was, like a foregone conclusion. They were like, “We know it's bad. We just don't know how bad.” And then the poll came back. It was like, “It's really bad.” And then they just did it anyway.Joon [00:20:14]: Part of it is to show, right? So you're, you're looking at the ideaSwyx [00:20:17]: Maximizing drama.Joon [00:20:18]: How bad could it be? Oh, it's horrible.Swyx [00:20:20]: And to some extent, I think that is part of the trick of the, or the challenge or with being a customer of yours, which is that if I know it's. if I roughly know and can intuitSwyx [00:20:35]: What the effect is going to be, do I need you? What sensitivity of it, of effect do I need in order to make a decision, right? So for example, if I, my approval rating is 50%Swyx [00:20:48]: And I, they have this negative piece, news item comes out, and it drops to 30.Swyx [00:20:52]: If it drops to 20, if it drops to 40, do I care? No. It, I know it drops. It's negative. So when do I care about simulations?Joon [00:21:01]: You do something that's clearly bad, that's not popular, and people don't like you, like, yeah, it's likeSwyx [00:21:05]: You don't need a simulation.Joon [00:21:07]: Yeah. Well, so there are a couple of things. one is, there are use cases where, like every day, developers, designers, policymakers, marketers, every single day, they create assets. They create new products. And turns out, it's many of the decisions in hindsight is obvious. Yes, of course this is bad, but we still run those studies because understanding the magnitude and understanding how acute something is quite difficult, even if, we feel like, of course, like this makes sense. this is the reason why we make so many mistakes. Like, every time somebody goes online and say something that has huge backlash, you look at that and like, “What an idiot.” However, it's tough. That's one. There's also another aspect here, which is, again, this is the reason why simulation is different from prediction. In simulation, in the ideal case scenario. So what simulation is trying to show is it's trying to show each step of the way or each step that we need to take to get to a certain outcome, right? So in the most advanced simulations, sometimes the next step that we're suggesting might be quite counterintuitive. The analogy that I sometimes give, and I ground it in a more realistic example, but, I, as I mentioned, I'm a huge fan of science fiction, and I don't know how, many of the audience members have read, like, things like the Foundation series by Asimov.Simulation as a Path, Not Just a PredictionSwyx [00:22:37]: Oh, yeah. We've mentioned psychohistory a number of times.Joon [00:22:39]: Okay, fantastic. So I might be, talking to the right crew. If you read Foundation series, literally the first act is there's a group of scientists who have found out that, “Oh, our galactic empire is going to collapse, and we're going to have 30,000 years of unrest.” And they run psychohistory, the simulator that tries to teach them, “Okay, how can we keep this unrest to a 1,000 years?” And they plan this out, and the first step of that plan is to get the scientists who say, “Okay, this is coming,” exiled into this random place in this, galax- galaxy.Swyx [00:23:18]: Terminus.Joon [00:23:19]: Exactly. And that's so counterintuitive. Like, what a strange move that you literally sent the group of scientists who was raising voice around this potential collapse of galactic empire into nowhere. How is that the right first move? Well, it turns out in this particular simulation, that was the move.Joon [00:23:40]: It's these things, right? And the reason why these reasoning is possible is because you're showing the step function or each step that results in a particular outcome. So really what simulation allows you to do in its highest form is you give it not a problem or question, like what would people answer to the survey? That's not what we do. What we tell it is, “Here is a goal that we have. In the context of foundation, we want to keep the unrest to a 1,000 years. What is the path that we need to take now to get to that particular future?” And that's what simulation allows you to do. Now, translating that into real market, imagine you're a automobile company and you're about to release a, EV, and you're trying to understand, well, how do we market EV, to make sure that our stock price goes up? But what if the answer comes down that, well, you can market your EV in XYZ way, but that might change people's perception around the cars that's not EV and make your overall sales to go down. Not very intuitive, especially all you're trying to optimize is EV salesss, and that's the only thing that you're tracking, then that might result in a completely wrong solution, or at least different solution than what you would have expected, whether it's right or wrong.Joon [00:24:57]: That's the power of simulation.Swyx [00:24:58]: For listeners, we covered a similar topic with Mikhail Parakhin from Shopify, where they are working on SimGym. I don't know if he ever talked to you about it. it's very similar.Joon [00:25:07]: ISwyx [00:25:07]: The goal is increased conversion, but then the journey is very unusual.Joon [00:25:12]: Journey is unusual.Swyx [00:25:12]: Yeah. The-- He's trying to look for interventions on a shopping trajectory, which is similar to what you're saying. Like, it's not about the attitudinal, is your word for it.Swyx [00:25:24]: It's about behavior.Joon [00:25:25]: It's about behavior.Swyx [00:25:25]: And that's exactly the difference, right? It's, like, not about the near-term direction about-- but it's more about, like, how do you affect multiple turns of interactions.Vibhu [00:25:35]: You had a good quote at the start about this as well. It's not about people wanting to know the outcome. It's about how they can change it, change the way to get there, something like that. But I wanna take it back to how do we know this is grounded? LikeGrounding and Evaluating Digital TwinsVibhu [00:25:47]: How do you run evals? How do you test that simulations come through? if I was to do the same thing that you described with, say, your favorite LLM, Opus, GPT-5.6, have some agent to map out these thingsVibhu [00:26:02]: How different are the answers we would get if I give it the same goal, the same objective, make a decent system? You're saying that you need to change the model weight. You have your own solution to this. But how far off are we, and how do you check if it's grounded? you have some interesting stuff on your site that points to how you run real evals, but if you could take us through that side. I think that's one of the big concerns that people have. They're like, “LLMs hallucinate.”Vibhu [00:26:27]: “You're just hallucinating layer after layer,” right?Joon [00:26:30]: The way we do this, and this is the paper that we worked on after the generative agents paper that really became the, at least for Simile and also the field of simulation and synthetic panels, really became the foundation. Yeah, this is the paper. the paper is called Generative Agent Simulations of 1000 People. Here's what we've done. For this paper, we brought 1,000 people that's representatively sampled from the US to a virtual lab. And what we have done was we spent two hours collecting fairly wide-ranging data. In this particular study, we focused a lot on this interview data, that was, whose script was taken from this project called American Voices Project. And then we would also pair that with a lot of behavior data and so forth, whatever we can collect within two hours. And then we would send these people away for a couple of weeks. And during that time, I would use this data to create their digital twins. And I would bring the humans, participants back after 2 weeks and have them complete a battery of surveys, experiments, behavior studies. So we have the list here, which included things like behavioral economics games. We would run literally, like, Big Five personality test, General Social Survey. We would also go ahead and run the randomized controlled trials that were published on PNAS. And we would have their digital twins predict how the source individuals would have acted in these studies and surveys. And this is where we could replicate people's behaviors and attitudes 85 percent as accurately as people would replicate their own. So that was the first really paper that gave this validated results that we can model individuals in an accurate way. And what we ended up finding now, of course, in AI space, so this paper came out at the end of 2024. AI space, a year and a half, 2 years, that's a lifetime.85% Accuracy and Why Frontier Models Miss Human BehaviorSwyx [00:28:24]: Yeah. Just, for listeners who are not seeing the YouTube, I just wanna say, like, the headline figure is 85 percent accuracy, like, which is a big improvement over all the otherSwyx [00:28:34]: Methods that you showed.Joon [00:28:36]: But the part that was particularly striking to us, especially as we improved this technology even further, was the generative AI models like ChatGPT, Claude that's coming out, it does give you the right foundation. However, what they do not consider is the true attitudinal and behavioral aspect of people, especially in the population that you care about. So what these models are really good at today is they're trying to become the super rational, objective machines, right? So you go get their data from places like Mercor, Scale. You talk to professional programmers, scientists to create model that's amazing at reasoning. That's what they do. Simile doesn't care about any of this. The models that we're talking about here, what we're trying to create are models that are as dumb as I am, right? So if I make some mistakes, the model has to make the same mistake.Swyx [00:29:34]: Oh, that's very hard.Joon [00:29:35]: That's very hard.Swyx [00:29:36]: You're solving Murphy's paradox.Joon [00:29:37]: That's exactly. And this is a completely different data and training objective. This is also where we see quite a bit of discrepancy in the performance in human behavior prediction between the frontier models, Simile's model, and the models being created in this space, where in some cases, the model performance of frontier models go all the way down to 20, 30 percent, especially if you go into that more niche population on topics that our customers would care about. On more gen pop, it might be around 50 to 60 percent. So it's not very robust. Like, you wouldn't want to make your decision off of these and these findings. If you can bring that up to 85 percent, that is ultimately what people end up getting very excited about.Swyx [00:30:20]: Yeah. Do we wanna keep going on the paper, routes?Joon [00:30:23]: Yeah, for sure. So the last one, was an interesting one. So this, paper was the follow-up paper that we had, to the 1000 agents paper, where the idea was now can we augment the models even further and post-train a model based on a lot of randomized controlled trials? So this was an interesting one. The data is always the most interesting part of modeling in many ways. The data that we got here was there's this, there's this platform called Open Science Framework. So some, the audience might be familiar with this. And there has been, especially in the social sciences over the past 5 years or so, there has been this concern around replicability of studies. And so it was a bit of a crisis, the scientists acknowledged, where we rerun the study and we don't see the same finding.Post-Training on RCTs and Replication StudiesVibhu [00:31:12]: Oof.Joon [00:31:12]: It's tough. And the reason why it's there-- that was often the case was there's this survival bias where the papers that get published often need to maintain what we call the value of less than 0.05 in the experiments that we ran. That suggests that only-- there's only 5% chance that the results that we saw is false positive. But the tricky part was all the papers that were not published, and there's still a 5% chance that whatever we publish is totally just randomly generated. Like, there's a 5% chance that, hey, this effect is not real, but it just happened to be real because of the sampling bias. So because of that, what scientists started to do was they started to register their studies. So before running an experiment, they would go to this platform and say, “Here is the data. Here is the population that we're collecting, and here's the hypotheses.” And they would just say, “Here is our hypothesis.” Like, “This is what we believe.” And you cannot retroactively change those hypotheses. This is what gives us more scientific statistical confidence that whatever effect that you ended up seeing is true. So that ended up creating this really interesting platform where there's one platform that has now contains tens of thousands of real-world experiments and hypotheses. And a lot of these are really high-quality, like, professionally designed behavior studies and random- randomized controlled trials. So we got the data and the studies from this platform and used that to make a point. And this particular, model is not, something that we're serving commercially because this was a part of the open science. But this particular data set, helped us make a point that by collecting a lot of these randomized controlled trials, that are really well-designed, we can make significant improvement in model's capability to predict human behaviors. So that's what this paper was about.Vibhu [00:33:10]: Is this stuff done on a individual level? Like, do I need to tune the model per individual, per company? Is there foundation model changes and then some slight post-training? Anything you can share there?Population-Level vs. Individual-Level ModelsJoon [00:33:21]: So this particular model was trained. the data we had at the level of individuals, but this particular model was trained. We experimented with both. And this is what we end up doing at Simile too. We always train 2, distinct model. One is what we call the population-level model. The other is what we call the individual-level model. And both take very similar input, which is the description of a subpopulation or individual and a stimuli. In this particular work, we've done the same. Here, the results that we are reporting are much more geared towards individuals because we do think that is a harder task in many ways, but that's what we have done.Vibhu [00:34:02]: You seen anything on the questions that humans can solve that models can't solve? So likeHuman Biases, Mundane Choices, and What Models MissVibhu [00:34:09]: Currently, it's, I live 5 minutes walk away from a car wash. It's a 10-minute drive. Should I walk or drive?Joon [00:34:16]: Huh.Vibhu [00:34:16]: The model will say, “Oh, walk to the car wash.” And, you don't have your car.Vibhu [00:34:20]: Is anything like this a problem in simulation? You would assume, like, very simple for human to think about, but if the model is saying you should walk to the car wash, anything here?Joon [00:34:32]: It's less, what can we solve, but I think it's more about what biases or mistakes do people make that models miss. Like, imagine that you are, like the. When I was still at Stanford, I lived in Palo Alto. So it's about, I would say, 40-minute walk from the campus. You ask the model, “Okay, let's go home. What can I, what can I do?” It would likely call an Uber or, give me, the bus time. But for the longest time, I really liked walking back. And the reason why I wanted to do that was not for efficiency. It really helped me think. And I like to walk for, half an hour or 40 minutes or so a day, where I just get to, just think about ideas, research, just get lost in my thoughts. That's very human activity. Unless the model has seen that and understands the importance of that activity, it would miss these kinds of features. So that I think, is fundamentally what we're trying to model. Like, what is fundamentally human might not be the most efficient thing to do, might not be the right thing to do, but things that make us who we are.Swyx [00:35:43]: I'm curious if, there are some data sets that you really want that would materially help you. One version of this may be interesting, which is more valuable to you to acquire as a data set, all of LinkedIn, all of Twitter, all of Facebook?What Data Matters: Social Media, Transactions, and FacebookJoon [00:35:57]: It's a little bit hard to rank, in part because, there's, there's this product saying where no feedback is wrong because it teaches you something about your users. Doesn't matter what feedback.Joon [00:36:11]: I think it's a little bit like that.Swyx [00:36:12]: So just whatever is bigger.Vibhu [00:36:13]: What about a different domain? Say it was. What about all of Amazon data?Joon [00:36:17]: Oh, yeah.Vibhu [00:36:18]: Shopping data, right?Joon [00:36:18]: Shopping data. So Amazon data is interesting in that it's very much behavioral, although, like, what people do on social media, you could squint and say that is also behavioral. But the transaction data is always interesting. It is also most commonly available, however.Joon [00:36:33]: If we were to look at purely social media, like if you really, if I were, if I had to really pick, Facebook likely is interesting because I do think it is most a default version of people. Because you go to LinkedIn, it's very much professional environment. So people put up their, they have their guards up, right? And that still is interesting because that is true human attitude and behavior, but it is not your base state. you go to Twitter- Twitter, people have their own crazy personas, or depending on who you are. Like, my Twitter profile and, persona is very much, initially was I was very much an academic. “Hey, I'm here to share my studies.” Now, I share, things that's related to Simile. But Facebook is one of those more private space where people just connect with their friends. In that way, I do think it shows you a little bit more about who that person is. So if I had to pick, I'd likely pick, Facebook.Swyx [00:37:30]: Yeah. And you're interested in, like, the whole person and their background and philosophy. I, is it too clinical or too machine learning-oriented to just say this is just ways to inject variance and biases? The broad question, is, like, is this any better than a randomized, like, combinatorial explosion version? So we have a link to the TencentBillion Personas, Synthetic Demographics, and Bespoke DataSwyx [00:37:54]: Billion persona paper, where they did not do any of the groundwork that you are doing.Swyx [00:37:59]: They just did like a cross matrix of here's all the professions in the world, here's all the people, possible backgrounds in the world, do a dot product across all of them, and that's it. That's your prompt for a billion people.Swyx [00:38:12]: This will do something. I don't know if it'll do what you do, but it gets you some way, some percent of the way there.Joon [00:38:18]: So this was an interesting paper. Like, what I admired about this paper when it came out was the scale. And you do gradually want to be able to simulate really large societies and interactions. So the scale is definitely admirable. it is relying heavily on the known statistics that went into training the model. So to the extent that you believe that statistics is correct, this is not a bad way to go about this. But the thesis here, and this is something that we also have seen in the market, like if this works, then we have solved simulation.Joon [00:38:54]: It,Swyx [00:38:55]: Because I survey, like, okay, 5% of the US population is in construction.Swyx [00:39:01]: The other 5% is in medicine, whatever, right? And then you just keep going down the list, and then you do the other side. 5% has, like, the big 5 personalitySwyx [00:39:08]: Of, like, neurotic or whatever. That's it.Joon [00:39:11]: That's it. So if you believe that the underlying data set and the platform that we're leveraging has all the right statistics, then this will have solved it. you're at that point merely retrieving the knowledge that is already embedded in the model, in the model parameters. That's not, unfortunately, what we see, where there is such detailed and also niche knowledge about people that if you just take one example, it might feel very mundane, but it's quite rich when you put together, that you do need to do a lot of bespoke data collection to better understand people. And this is also, I think what makes this particular, job fun, which you want to deeply understand people, and the process of deeply understanding them requires a lot of attention to the details. And you do need to pay attention to and pay respect to the daily lives that people lead.Scaling Simulation: From Thousands to SocietiesVibhu [00:40:04]: I wanna talk about scaling simulation.Vibhu [00:40:07]: So what can't we simulate, what can we simulate, and how does scaling affect this? So how big are the models? What if we go from, 8B, like, couple 100 billionVibhu [00:40:18]: Like billion000 parameters, billion000? Do we get scaling? Any interesting emergence? Like, at a certain scale, at a certain amount of training, you uncover anything unusual and any learnings from that?Joon [00:40:31]: What we are seeing is at Simile, so we do post-train our own model. The thing that we're seeing is the early glimpse of scaling law in simulations. The more data about humans and more compute you ingest, you start to get predictive and predictable gains of the model performance in simulating it, simulating people.Vibhu [00:40:51]: Ooh. We need a scaling law curve.Joon [00:40:52]: It's scaling law. Whenever you find it's a beautiful thing. And we're starting to see the glimpse of it, which is quite exciting. But if you talk about the ambition of simulation as a whole, it's not merely about building a model. It's about building a model, then creating the agents that become the individuals in a much larger ecosystem. So they're creating this multi-agent simulation. Down the line, you want these multi-agent simulation to also live in a very rich environment, right? What we are really trying to get to at that point is, hey, can we create. All right, let's do a time machine game again, and 5 years, 10 years into the future, can we create a simulation of 8 billion people living on Earth? I think that's quite interesting. And that really is the vision. And once you get to that state, the questions that you can help answer for the society also start to change from my perspective. The answers are fundamentally about emergence of the emergent behavior of society and large groups of people.Joon [00:41:53]: So the questions that I get excited by, and maybe this is a stodgy- a bit. I have my, academic side of me.Joon [00:42:01]: And for me, it's questions like, can we help solve climate change? If you look at climate change as a problem space, this is what we, like social scientists would often call it the wicked problems, problem where you have many actors with competing incentives for trying to make a very complex decision and coordinating that coordination decision. Very difficult to really solve in real life, which is also the reason why we couldn't solve it. Can simulation help us solve that? Another one is, can we understand the signals for collapsing democracy, or can we understand or can we uncover the origin story of the monetary system? These are societal questions that we never really had a good way of answering. If we can create simulations of our society, you have to believe that these are the problems that we can solve. So that's really the ambition of this field. And, I also think, yes, I think there's a Nobel Prize to be won there, which wouldn't be surprising. And I think there's some amazing societal impact that we can have to help people make better decisions.Climate Change, Democracy, and Societal SimulationSwyx [00:43:04]: Nobel Prize in economics?Joon [00:43:06]: In economics.Swyx [00:43:06]: Oh, I see. I see. Rooting for you to write that paper.Joon [00:43:10]: One of these days. But, one of the scholars that I was deeply inspired by, When I was coming into the space of simulation, is this scholar, named Thomas Schelling.Schelling, Agent-Based Models, and the Nobel PrizeSwyx [00:43:23]: Schelling point?Joon [00:43:24]: So the canonical example of the work that he's done was he was one of the creators of agent-based modeling. So this was, like, in the 1970s and 80s. It's very early days, but this was truly one of the first exemplars of simulations. And one of the canonical model from that time, and of course many of these simulations are trying to tackle the societal problems that's most relevant for their era, it was called the model of segregation. So racial segregation was a big topic, that, we cared about. And what they've done was they created this grid world where they had red dots and blue dots. And these dots were, back in the day, like, they were the agents, and they had a simple rule that governed their behavior. If certain percentage of your neighbors are of different color and if that goes above certain threshold, then you move to a new location at random.Joon [00:44:21]: One of the striking finding of this paper or this agent-based model was for the longest time, people thought the segregation within society was caused by explicit and overt racism.Joon [00:44:34]: But if you look at this model, people's preference towards living with people of the same color, that preference can be very minute.Joon [00:44:42]: But the very small difference causes the society to segregate completely over time. This was very counterintuitive for a lot of people. And this particular work ended up informing housing policies. Mixed income housing, got really inspired by this work. And Thomas Schelling ends up winning the Nobel Prize for having laid the groundwork for very early versions of simulations. The opportunity that I do see here in the more scientific terms, is agent-based models for the longest, had impact in the 1980s, 90s, to some extent, early 2000s, but it has now gotten forgotten by the community a little bit. Because as you can imagine, red dots and blue dots is not really a rich description of people.Joon [00:45:31]: But with the emergence of things like generative AI and, in particular, generative agents, we do have an opportunity to create these agent-based models that are high fidelity enough to help us make really complex decisions. And that's the opportunity that I see. If that truly works, then yes, that is the work that will result in a Nobel Prize.Swyx [00:45:53]: Yeah. For what it's worth, and I grew up in Singapore. 80% of Singapore is in public housing, and public housing has, enforced racial quotas for exactly that reason, which is very interesting. okay, so we talk about scaling, we talk about all these, the agent possible applications.Cost, Reuse, and the Economics of SimulationSwyx [00:46:13]: I'm scared about the cost. if you even-- let's just keep it to the US, about 8 billion people.Swyx [00:46:21]: But, how much does it cost to model so many hundreds of millions of people?Joon [00:46:26]: Oftentimes today, we don't start at that scale, this stage of the, of industry and simulation as technology. But we can get our users extremely rich and meaningful insights even by modeling thousands, tens of thousands of people. And today what we do is every week we are collecting data on the scale of tens of thousands people's data, and we have panel partnerships that gets us to tens of millions of people globally. So that's what we do today.Swyx [00:46:55]: And just as a side note once you've collected one person for one studySwyx [00:46:59]: Can you reuse that same person for all the subsequent studies?Joon [00:47:03]: That's exactly right.Swyx [00:47:03]: Okay.Joon [00:47:04]: The beauty of this model and these agents is the fact that they are domain-agnostic.Joon [00:47:08]: That what you're really trying to understand is what is the fundamental nature of these people? What's their social physics? And there are a lot of, a lot of, people that does change over time. Like, even, like, even things like, how many times have you gone have you been to, like, CVS the past week? that will change. But there's so many traits about people that are also known to never change. Like, your risk tolerance doesn't really change over time. It's very consistent. So it's these things that we're trying to learn. But the scale we are operating is right now hundreds or, tens of thousands to hundreds of thousands. And in many of the core use cases that we are deployed in, and this is more than enough population, to cover those. Really, at that point, what you care about is less the number of people, but more do you have the right subpopulation of interest covered? And this is also the reason why people want a larger sample. It's not because they want, stronger statistical guarantees. It's more that can they filter down to any population of their interest. However, you can also imagine in 10 years, if we truly believe that the compute is going to scale, that we'll have much more availability for compute, and our ambition for simulation is also going to scale accordingly, there's definitely a reason for us to create an entire data center worth of simulations.Joon [00:48:35]: Or in my hunch here is I do think in the next some number of years, we will start creating simulations that will cost as much as training a foundation model. But perhaps it's going to be so valuable to the society that it would be a no-brainer. Right now, even today, like, we are training bunch of new foundation model just so we can say we trained one and we spent tens of millions. But if we can create a simulation at the level of society that would solve climate change, I would run that today. I would raise the money right now just to run that.Multi-Agent Simulation and Social InfluenceSwyx [00:49:10]: Amazing. the follow-up question is, does it also compound if you let the simulations talk to each other?Swyx [00:49:18]: Or do they already do that today? They don't, right, as far as I understand?Joon [00:49:22]: It depends on what simulation you're trying to run.Joon [00:49:24]: In the multi-agent simulation setup, the agents do talk to each other.Swyx [00:49:28]: Right, which is exactly Smallville, right?Joon [00:49:29]: That's right.Swyx [00:49:30]: But a lot of times, for example, in commerce, you're just by yourself, so there's no point talking. which is way cheaper.Vibhu [00:49:37]: But they use all these levels, right? Like, you decide what you will buy based on what other people around you buy and talk about, right?Swyx [00:49:43]: It depends.Vibhu [00:49:44]: It depends.Swyx [00:49:45]: Again, I'm, I'm coming at this from a cost point of view. I'm like, “Oh my God.” LikeVibhu [00:49:48]: I thinkSwyx [00:49:49]: If there is, like, some combinatorial thing of, like, thousands of people talking to thousands of people, then that one million X's might cost.Vibhu [00:49:56]: I have a very different view as the cost point aside. Like, running these studies in reality is a lot more expensive, right? Running any study like this is you gotta have people do it, you gotta sign people up. It's very expensive and sometimes, like, not feasible to run the study.Vibhu [00:50:14]: But the outcome or the decisions you make are very expensive on them, right? So spend X million on something that, the overall process costs 100 million might as well, right? There's, there's a lot of value to be had there. It's a small cost, but I'm excited on the cost side.Joon [00:50:33]: To some extent, and when you deploy technology, you often want to deploy in a way where you can replace existing budget or you can make things more efficient, and that is the best way to deploy. However, the way you capture the long-term value of the technology is making the argument that, no, it's the upside, that by making this better decision using simulation, you have saved yourself or made yourself hundreds of millions or even billions of dollars, and that's a case to be made.Vibhu [00:51:06]: Random tangent question. So if you're doing a lot of inference, a lot of model multi-agent stuff, are you at the point where it makes sense to, train a model that' very sparse? You're expecting to do multi-million dollar runs. Are you thinking about this in model architecture standpoint or inference efficiency, or, you're still at the research phase of it works, we're not super there yet?Joon [00:51:34]: Efficiency, we do think quite a bit about. this is technology that is deployed now in some of the largest enterprise companies in the world, and we do process significant number of queries, that are trying to, simulate the populations in the world. So efficiency is a consistent thing. we don't want to over-optimize too early, so I wouldn't say, like, this is the higher bid Right now, but this is definitely something that we think pretty carefully about.Swyx [00:52:05]: Yeah. Are there other case studies? So we, you talked about CVS, talked about Gallup, Deloitte, Wealthfront.Efficiency, Enterprise Use, and Real-World Case StudiesJoon [00:52:12]: Wealthfront is an interesting one, because one of the things they were trying to do, they were one of the first customers that wanted to do product testing that goes beyond just asking people what they think about, let's say, behavior experiments and so forth. So there, really what we had to do was reason about multimodal input, so images, but also you can also imagine, like, these agents traversing through Figma mockups or websites. So some of the things that our agents can also do is it can be given a domain, like, or, like, a website URL and go use it for a while. It's these things. And Wealthfront was one of the first, customers, that was very excited about this possibility.Vibhu [00:52:53]: What have people been asking? Like, is there any demand that we have not covered? Like, UI testing, right?Vibhu [00:52:59]: I wanna try a new. I wanna ship a new feature, test the UI, simulate how people will do it. Any interesting things that you're seeing demand for?Product Testing, Websites, and Synthetic PanelsJoon [00:53:08]: Today, a lot of the demand does come from like, the places where people have historically used human panels, we can now replace with agents, and these synthetic populations. And this is not replacing human panel. in many ways, the simulation that Simile is building is grounded. So the way that I think about this is we are trying to represent humanity at scale. And in that way, the use cases are what we would expect, but it's the scale of deployment that surprises me.Joon [00:53:44]: Turns out there are so many decisions that people make every day in these organizations, groups, and we want to be able to say, “We listen to people. We have consulted our users.” But in reality, that is rarely the case because getting to people and asking them many questions, it's difficult. It's both costly, time-consuming, but most importantly, people are just not available. If I had to answer 1000 survey questions for this one particular, vendor, even if I wanted to do that, like, I would never do it. And that's very much the case. What simulation can do is ensure that the voices of people are always represented in rooms where the decisions for them is made, right? So all the stakeholders of this particular product launch, ideally they're consulted. That's what this technology really is trying to enable.Market Size, TAM, and Human Decision-MakingSwyx [00:54:39]: In my mind, that means it skews towards more consumer focus, right? Like, anything with a wide enough customer base where you do benefit from the diversity that you represent. What are some rough statistics, just for people who are not familiar with this market in general, what's the market size that. I'm sure you have some, like, rough numbers. market size is, like, a vague questionSwyx [00:55:01]: But, like, how much do people spend?Joon [00:55:03]: So market research is a $100 billion industry.Joon [00:55:06]: But the thing about simulation is not a tool for market research. Simulation is a tool for human decision-making. So the question around what is a TAM here is quite tricky, right? Because it's easy to say, “Well, market research TAM is roughly 100 million or 100 billion.” so is it a TAM? And not really, right? Because in many ways, you're trying to inform all human decision-making. You're trying to inform every decision that are made about humans for humans. What is a TAM for that? It's really unclear. And I'll be honest. Like, I have a scientific background, I have a research background, so I didn't come into the field calculating, oh, what is the TAM for human decision-making? But I just had to assume, well, if we can inform every decision that is made about human for human, that has to be big.Swyx [00:55:58]: Some- something valuable.Joon [00:55:59]: Exactly.Swyx [00:55:59]: To some extent, you are a unicorn founder now, and you have to care as a CEO. But, like, I do think, like, yeah, when you go into these boardrooms with people that you're quoting millions of dollars of contracts for, like, you have to say, “Well, here's what you spend on humans-”Swyx [00:56:15]: “. And here's what we save you, and it's 85% similar.”Joon [00:56:19]: And certainly, the value case, is something that we care deeply about. Like, what is the value that we provide to the users and the decision-makers? But this is also where, like, as a founder, I think valuation only tells one very superficial aspect of the story, and I try not to think too much about valuation, in general, because that's not what also motivates a team or certainly doesn't. I'm, I-- Again, the interesting thing about researchers is we are happy living in academia, getting paid next to. we get paid okay. we don't get paid that much, as a researcher here in academia, but it's the impact and it's the, it's the value that we can provide to the individuals and the society that really drives us. And in that way, ultimately what drives us is the impact. Does the simulation we provide have a real impact in people's decision-making in ways that progresses our society forward? If the answer is yes, then yes. that has to be great business, and we see that in numbers, and we do care deeply about that upside story, but that's the heart of it.Where Simulation Goes NextVibhu [00:57:27]: Do you have any timeline predictions? So we talked about scaling laws of simulations.Vibhu [00:57:33]: You brought up, okay, maybe one day we can simulate how to solve climate change.Vibhu [00:57:38]: Where are we now?Vibhu [00:57:40]: If that's not the end state, what is an end state, and what does progress look like?Joon [00:57:45]: So what I sometimes tell people is simulation as industry, it feels a lot like where GPT-3.5, GPT-4 was, for the AGI saga, which is we have now technology that is powerful enough to do real damage on the verticals that we are tackling. At the same time, there's a lot of progress that is yet to come. And that's, I think, where this is. So the way I see it, I do think there will continue to be breakthroughs both in data, in algorithms, and there will be much more aggressive scaling that will also happen over the next few years. But I think that's roughly where we are.Swyx [00:58:27]: I think that was about the ro

CELÝ DÍL NAJDETE NA https://herohero.co/studion A V RÁMCI KLUBOVÉHO PŘEDPLATNÉHO DENÍKU N https://denikn.cz/podcast-studio-n/ Evropa řeší migraci, Turecko si buduje vlastní sféru vlivu a česká vláda mezitím otevírá otázku budoucnosti veřejnoprávních médií. Ve Studiu N jsme se zahraničním reportérem České televize Andreasem Papadopulosem mluvili o třech zdánlivě vzdálených tématech, jež spojuje jedno: proměna evropského prostoru a jeho vztahu k okolnímu světu. Papadopulos upozorňuje, že motivace lidí, kteří se vydávají na nebezpečnou cestu do Evropy, není možné redukovat na hledání pohodlnějšího života. „Ti lidé nejsou na cestě za lepším životem, ale za životem,“ říká. Podle něj je důležité rozumět tomu, před čím tito lidé utíkají, i když to podle něj neznamená, že Evropa by měla své hranice jednoduše otevřít. „Tam, odkud pocházejí, by ten život mohli ztratit. Byl by tragický. A to je žene. Neříkám, že je to správně a že by měli do Evropy přijít otevřenou branou, to vůbec ne. Myslím ale, že je důležité vnímat jejich motivaci. Nedá se umenšit tím, že jim řekneme, že je tady nechceme. Oni jdou s mnohem větší motivací a přes mnohem větší nástrahy a překážky, než je nějaký hraniční plot nebo španělští policisté s obuškem,“ popisuje zahraniční zpravodaj České televize. „Pro ně je ten pobyt na pláži v Ceutě jedním z nejlepších období, protože dostávají denně jídlo a mají jistotu, že se nezapletou do stejných problémů jako po cestě,“ říká Papadopulos. Z Ceuty se rozhovor přesouvá k Turecku a jeho stále ambicióznější zahraniční politice. „Turecko chce být mostem mezi západní civilizací a civilizací Středního východu,“ říká novinář. Podle něj Ankara usiluje o stále větší vliv v Africe, Libyi i na Blízkém východě a současně zůstává pro Severoatlantickou alianci velmi cenným partnerem. „Pro NATO je Turecko vytrčeným tykadlem směrem do tohoto prostoru,“ tvrdí. V některých oblastech podle něj dokonce může coby regionální mocnost převzít část role, kterou dosud hrály Spojené státy. Země za Erdoganovy vlády výrazně rozšiřuje své mocenské ambice, zároveň ale prochází hlubokou ekonomickou krizí. „Turecko je nemocné, ale má silného sultána,“ říká reportér, se kterým jsme se spojili do Istanbulu, odkud působí jako zahraniční zpravodaj veřejnoprávní televize. Jak funguje evropská migrační politika a proč se ji nedaří dlouhodobě nastavit? Co ukazuje příběh Ceuty? Jaké jsou Erdoganovy skutečné ambice? Kam se může posunout Turecko v novém geopolitickém uspořádání? Co může znamenat plánovaná proměna veřejnoprávních médií v Česku? A co by jejich ztráta znamenala pro schopnost české společnosti orientovat se ve světě, který je stále složitější? Podívejte se na celou epizodu. Celé díly Studia N najdete na platformě Herohero, na webu Deníku N jsou přístupné předplatitelům a předplatitelkám Klubu N. Bezplatné části zveřejňujeme v podcastových aplikacích Spotify, Apple Podcasts, Podbean či na YouTube. Sledovat nás můžete také na Instagramu.

CHAPTERS00:00 Intro00:26 Who Gabe is and what Subfrost does01:56 Finding traction in a bear market02:20 The China road trip and an unexpected user base04:32 Alkanes' share of Bitcoin block space, in Gabe's numbers05:30 How trustless can Bitcoin smart contracts really be?06:06 Progressive decentralization: nine signers, then doxxed, then permissionless08:59 Current TVL09:03 The L2 misconception and the UTXO model10:44 Spam, BIP-110, and where Gabe thinks censorship starts14:25 The TAM argument: ETFs, perps, and moving Bitcoin on chain18:07 Institutional Bitcoin: what it opens up and what it risks24:44 Will younger holders ever self-custody?28:25 Where did Bitcoin's volatility go?33:27 Why build on Bitcoin instead of another chain37:05 July 2: the attempted drain of frBTC41:13 The failsafe, the halted unwraps, and the cleanup43:50 The free audit, and the one they paid for44:53 Stablecoins, KYC, and the third route47:53 One year out: indexers, apps, and dxBTC51:44 Where to find Gabe

What if commercial businesses could cut clean energy project costs by up to 45%, all while someone else finds, buys, finances, and operates on-site systems on massive real estate portfolios?Company bio:VECKTA Energy is a technology platform that helps businesses design, procure, finance, and operate on-site energy systems, including solar, batteries, and generators. Its platform can analyze thousands of data points across large property portfolios, identify the best opportunities, and connect buyers with a network of 4,000+ suppliers, developers, equipment providers, and financiers.Speaker bio:Gareth Evans is the founder and CEO of VECKTA Energy. An environmental scientist by training, his career took him from oil and gas projects in Iraq to leading a global power consulting practice, where he saw firsthand both the vulnerability of traditional energy supply chains and the complexity of buying distributed energy systems.Five lessons for entrepreneurs:Turn complexity into your moat – Vecta sits between consultants, developers, financiers, equipment providers, and customers. Instead of avoiding a fragmented market, it built technology to coordinate it.Align your business model with customer outcomes – Customers pay a subscription, but Vecta also earns a success fee when projects actually get contracted. The company wins more when customers move from analysis to steel in the ground.Sell economics before sustainability – Gareth has watched customer priorities shift from sustainability toward cost, predictability, and increasingly reliability. Meet customers where their budgets and pain actually are.Follow customers into new markets – Rather than expanding internationally because the TAM looks attractive, Vecta follows existing customers into new geographies, pressure-tests the model, and then decides where to invest at scale.Earn your stripes before chasing the title – Gareth's advice to younger leaders: be patient, learn the craft, take difficult assignments, and build credibility. Responsibility is more valuable when you've developed the judgment to handle it.--1️⃣ Join our confidential CEO community.Private CEO group for VC/PE-backed climate tech founders navigating capital, strategy, and scale. Capped at 45 CEOs. → entrepreneursforimpact.com2️⃣ Join 40,000 professionals who get our newsletter.Climate tech finance, strategy, leadership. 2-min read. → entrepreneursforimpact.substack.com3️⃣ Leave a podcast review.If you got value, take 30 seconds and do the community a favor. It helps push more capital and talent toward scalable climate solutions.

Two years ago, Square tore up its general-manager model and rebuilt the entire company around functional excellence. In this episode of The Product Podcast, Carlos (CEO at Product School) sits down with Willem Avé, Global Head of Product at Square (part of Block), to unpack why they made that bet, what it costs, and how AI is now reshaping the org itself.Willem started at Block as a CTO whose company was acquired, grew up through engineering, and has seen every era of the company from the little white card reader to today's multiple product ecosystems. He explains why orgs should be built around customer outcomes (and how quality degrades the further you drift from that principle), why hardware demands a different kind of craft than software, and how Jack Dorsey's thinking pushed them toward the idea of running Block like a "mini AGI company," where AI encodes institutional knowledge instead of red tape and process. Then he opens up a live demo of "manager bot," an agent that lets a small-business owner delegate real tasks (like an inventory workflow for a bakery) without worrying about memory, connectors, or prompts. He closes with a genuine hot take on TAM and what AI agents mean for the size of the market Square can serve.What you'll learn:- Why Square replaced general managers with a fully functionalized org, and what "functional excellence" buys you- How to organize teams around customer outcomes, and why quality drops the further you drift- Why hardware craft (approachable, reliable, "it just works") differs from software craft- What it means to run a company like a "mini AGI," and how AI can encode knowledge instead of process- Why the era of the simple question-answer chatbot is ending, and what replaces it- A live look at "manager bot": delegating real business tasks to an agent- Why small-business owners want outcomes, not memory, connectors, or prompt-craft- Willem's hot take on TAM, and how agents expand who Square can serve- Why economic empowerment and democratizing advanced technology is the throughlineChapters:00:00 Trailer01:32 Inside Square and Block: how the teams are designed03:34 The four orgs: audiences, platform, growth, money04:46 Marrying hardware and software in one function05:56 Finding leaders who understand both worlds07:25 The DRI model and killing the silent veto09:16 Can everyone report to one person?11:12 Why flat orgs still need great managers12:41 Building for people who are not on X every day14:41 The loneliness of running a business17:24 Demo: Manager Bot doing real work20:19 Why AI should not create more work for sellers22:13 Hot take: TAM is almost infinite24:22 Killing the fragmented point solution stack26:06 WhatsApp, Instagram, and the comms problem27:54 Buzz and what nobody has solved yet28:34 ClosingConnect with Willem Avé:Global Head of Product, Square (Block)LinkedIn: https://www.linkedin.com/in/willem-ave/Host: Carlos, CEO at Product School:LinkedIn: https://www.linkedin.com/in/villaumbrosia/About Square: Square, part of Block, builds payments hardware and software plus a broader ecosystem of tools that help sellers and small businesses run and grow. Block also includes Cash App and other brands.About the Product Podcast: Product School's podcast brings you candid conversations with the founders and product leaders shaping tech.Social Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

Magyar Péter és a Tisza Párt legfontosabb kampányígéretei között szerepelt az elszámoltatás. Az Országgyűlés ennek megfelelően meg is szavazta a Nemzeti Vagyonvisszaszerzési és Vagyonvédelmi Hivatal felállítását, amelynek elnökét nyílt pályázat útján választják meg. Mára az is kiderült, hogy 96-an jelentkeztek a posztra. Köztük van Molnár Csaba, a Kulcsár-ügy kapcsán országosan megismert sztárnyomozó is. A feladata nem kisebb, mint 30 ezer milliárd forint visszaszerzése. A kihívás nehézségeiről és az új szuperhivatal működéséről egyedül a Partizánnak beszélt.30 ezer milliárd forint. Az elmúlt két évtizedben ennyi közvagyon vándorolt jogtalanul magánzsebekbe a Nemzeti Vagyonvisszaszerzési és Vagyonvédelmi Hivatal felállításáról szóló törvény szövege szerint.—host, szerkesztő: Kuczogi Jakab szerkesztő: Rádi Antónia élővágó: Gerendás Bálint videótechnikus: Szántó Tamás grafika: Sánta Dánielvágó: Hargitai Fannifotó: Nagy Tamás kommunikáció: Gál Borbála gyártásvezető: Kátai Orsolya—Legyél rendszeres támogató! https://cause.lundadonate.org/partizan/adomanyPartizán webshop:https://shop.partizan.hu/—Írj nekünk!Ha van egy sztorid, tipped vagy ötleted:szerkesztoseg@partizan.huBizalmas információ esetén:partizanbudapest@protonmail.com(Ahhoz, hogy titkosított módon tudj írni, regisztrálj te is egy protonmail-es címet.)Támogatások, események, webshop, egyéb ügyek:info@partizan.hu—Csatlakozz a Partizán közösségéhez, értesülj elsőként eseményeinkről, akcióinkról!https://csapat.partizanmedia.hu/forms/maradjunk-kapcsolatban—Legyél önkéntes!Csatlakozz a Partizán önkéntes csapatához:https://csapat.partizanmedia.hu/forms/csatlakozz-te-is-a-partizan-onkenteseihez—Iratkozz fel a Szignálra: https://csapat.partizanmedia.hu/forms/iratkozz-fel-a-szignalra-a-partizan-kulpolitikai-hirlevelere/Iratkozz fel a Partizán Szerkesztőségi Hírlevelére!https://csapat.partizanmedia.hu/forms/iratkozz-fel-a-partizan-szerkesztoinek-hirlevelere

Watch the show on television by downloading the SuperCrowd.tv Channel app to your Roku or Amazon Fire TV or e360tv channel app to your Roku, LG or Amazon Fire TV. You can also see it on YouTube.Devin: What is your superpower?Tom: Passion is what fuels the fire in my belly… It gets me excited, keeps me up late, and helps me go after these investments.Glenn: My superpower is bringing people together, adding value wherever I can… I try to help founders after I invest by sending resources or opportunities their way.Regulated crowdfunding has leveled the playing field for investors, allowing almost anyone to back startups with significant growth potential. During this episode, I had the pleasure of discussing strategies with two veteran Reg CF investors, Tom J Wright and Glenn Burney, who've honed distinct approaches to choosing impactful investment opportunities.Glenn emphasizes the importance of early-stage research and trusted tools like KingsCrowd, a platform that evaluates crowdfunding opportunities. “I usually start there, and if they're rated at least a four, I start digging deeper,” he explained. Glenn's diligence doesn't stop there; he carefully evaluates the founders. “The most important things I look for before I invest are the founders and the total addressable market. If I believe in the founder and the product or service, that's when I invest.”Tom echoed many of Glenn's insights but with his own seasoned approach, placing a special emphasis on market size. “I love a big TAM (total addressable market) because a startup can grow as big as the market allows,” he said. Using a memorable analogy, Tom compared startups to goldfish, explaining that their growth often depends on the size of their environment: “A goldfish will be small in a small tank, but if it's in a lake, it can grow to a foot long.”Beyond market size and founder qualities, Tom also values passion and disruptive potential. “Is the founder full-time? Are they going to do whatever it takes to make this thing successful?” He noted that revolutionary technology is often his green flag: “I love revolutionary tech because it can reset an entire market.”Valuation also plays a critical role in their decision-making. Glenn shared his preference for startups with valuations under $20 million, explaining his goal of achieving at least a 10x return: “If I feel like I can get at least a 10x return, then I feel like the valuation is good.” Tom approaches things similarly but allows for higher valuations when the opportunity feels right. “You want in early… Low valuation and a big TAM? That's a powerful combination.”Their stories also highlight the importance of intuition and alignment. “Does it resonate with me personally?” Tom asked, reflecting on how his values influence his choices. Glenn concluded by sharing his proudest success: investing in a startup that became a unicorn, providing him with a 21x return.The insights shared by Tom and Glenn prove that regulated crowdfunding isn't just about profit—it's about backing great people with big ideas while making a difference in the world. For investors, their advice is invaluable: do your research, trust your instincts, and focus on opportunities that combine potential impact with strong fundamentals.tl;dr:Tom and Glenn share strategies for evaluating and investing in Reg CF startups for impact.They highlight tools like KingsCrowd and key criteria such as TAM and founder commitment.Glenn recounts his story of helping a startup raise $125,000 via a meaningful introduction.Tom and Glenn discuss aligning investments with personal values and market trends for success.Both emphasize the power of passion and networking in transforming investments into impact.How to Develop Passion and Networking As a SuperpowerTom's superpower is his passion, which fuels his mission to make the world more just. As he explained, “Passion is what fuels the fire in my belly… It gets me excited, keeps me up late, and helps me go after these investments.” Glenn's superpower is networking and connection. He shared, “My superpower is bringing people together, adding value wherever I can… I try to help founders after I invest by sending resources or opportunities their way.”Glenn shared a story that exemplified his networking prowess. After investing in a startup, he connected them with an accelerator program that ultimately helped them raise $125,000. His introduction led the company to win the program's grand prize, underscoring how impactful his connections could be for early-stage companies.Tips for Developing the Superpower:Continuously seek inspiration by surrounding yourself with motivational materials, like books and quotes.Look for examples of courage and perseverance from history and everyday life to reignite passion.Focus on adding value to others before asking for help in networking situations.Leverage social media platforms like LinkedIn to build meaningful professional connections.Look for ways to champion others' success through introductions and referrals.By following Tom and Glenn's example and advice, you can make passion and networking your superpowers. With practice and effort, you could develop these skills to do more good in the world through impactful investments and purposeful connections.Remember, however, that research into success suggests that building on your own superpowers is more important than creating new ones or overcoming weaknesses. You do you!Guest ProfileTom J Wright (he/him):Angel Investor/Unicorn Hunter/Crowdfunding Course Creator, Angel Investor, Crowdfunding Course CreatorAbout Online Angel Investing/Crowdfunding Courses for Investors: Tom Wright is currently preparing several online angel investing/crowdfunding courses for investors who want to learn how to take advantage of the INCREDIBLE OPPORTUNITIES that now exist for every-day people, in start-up companies. These courses will be part of an amazing, informative and highly actionable group of ongoing courses available through Tom's Angel Investing Academy, available soon at Kajabi.comWebsite: Please look for his angel investing courses soon at KajabiOther URL: youtube.com/watch?v=yDjYw0mfRHcBiographical Information: Tom Wright is an accomplished angel investor and startup expert with a portfolio spanning 141 startup companies. An early investor in Cisco, Tom has built a reputation for identifying promising companies and supporting entrepreneurs at the earliest stages of growth.He was ranked #7 among startup investors worldwide on Wefunder, one of the world's leading equity crowdfunding platforms. His experience has also led him to become an angel investing expert and course creator, helping others understand startup investing and how to evaluate emerging opportunities.Tom's influence extends across the startup and investment community. At Wefunder, he is followed by Mr. Wonderful of Shark Tank, StartEngine, and more than 555 other angel investors, startup founders, and venture capital firms.With deep firsthand experience as both an investor and educator, Tom brings a practical perspective on startup investing, portfolio building, and finding high-potential companies before they become widely recognized.LinkedIn: linkedin.com/in/tom-wright-59a80324Glenn Burney (he/him):Accounting Manager, American UniversityAbout American University: ⁠American University is a student-centered research institution located in Washington, DC, with highly ranked schools and colleges, internationally renowned faculty, and a reputation for creating meaningful change in the world. Our students distinguish themselves for their service, leadership, and ability to rethink global and domestic challenges and opportunities.Biographical Information: Glenn Burney is an accounting professional and active angel investor based in Arlington, Virginia. He serves as an Accounting Manager at American University, where he leads a team responsible for financial reporting, reconciliations, endowment accounting, and other critical financial operations. Outside of his professional career, Glenn has built a diverse portfolio of early-stage investments across healthcare, biotechnology, artificial intelligence, energy, consumer products, and other emerging industries. He is especially passionate about identifying promising founders and companies before their potential is widely recognized. Glenn approaches angel investing with disciplined curiosity, combining detailed research, thoughtful founder engagement, and a willingness to support ambitious ideas that could create meaningful economic and social impact.LinkedIn: linkedin.com/in/glenn-k-burney-jr-68a55842/Personal Facebook Profile: facebook.com/glenn.kevin.3Support Our SponsorsOur generous sponsors make our work possible, serving impact investors, social entrepreneurs, community builders and diverse founders. Today's advertisers include PurposeBuilt100™ Winners and supercrowd.tv. Learn more about advertising with us here.Max-Impact Members(We're grateful for every one of these community champions who make this work possible.)Brian Christie, Brainsy | Cameron Neil, Lend For Good | Carol Fineagan, Independent Consultant | Eric Coury, Arthia AI | John Berlet, CORE Tax Deeds, LLC. | Justin Starbird, The Aebli Group | Ken Steele, Rotarian | Lory Moore, Lory Moore Law | Marcia Brinton, High Desert Gear | Mark Grimes, Networked Enterprise Development | Mike Babbit | Coledger Solutions | Mike Green, Envirosult | Nick Degnan, Unlimit Ventures | Paul Lovejoy, Stakeholder Enterprise | Pearl Wright, Global Changemaker | Scott Thorpe, Philanthropist | Sharon Samjitsingh, Health Care Originals | Add Your Name HereUpcoming SuperCrowd Event CalendarIf a location is not noted, the events below are virtual.Join the SuperCrowd Impact League! You can be recognized for making impact investments via Reg CF. See how your activity compares to your peers. It's free. Win valuable prizes. Start now!SuperCrowd Impact Member Networking Session: Impact (and, of course, Max-Impact) Members of the SuperCrowd are invited to a private networking session on September 8th at 8:00 PM ET/5:00 PM PT. Mark your calendar. We'll send private emails to Impact Members with registration details. Upgrade to Impact Membership today!SuperCrowdHour, August 19, 2026, at 12:00 PM Eastern. Devin Thorpe, CEO and Founder of The Super Crowd, Inc., will lead a session on “How to Make Money As an Impact Investor Starting with $10.” Drawing on his experience as a former investment banker, impact investor, and crowdfunding expert, Devin will demonstrate how anyone can begin building wealth while investing in companies that create positive social and environmental impact—even with as little as $10. In this session, he'll explore how impact crowdfunding has opened investment opportunities to everyday investors, explain how to identify promising mission-driven companies, and share practical strategies for building a diversified portfolio over time. Attendees will learn how to get started with limited capital, manage risk, evaluate investment opportunities, and avoid common mistakes new investors make. Whether you're completely new to investing or looking for an affordable way to expand your impact investing portfolio, this SuperCrowdHour will provide actionable insights to help you invest with purpose, build long-term wealth, and make a meaningful difference. Register now!SuperCrowd26 featuring PurposeBuilt100™: This August 25–27, founders, investors, and ecosystem leaders will gather for a three-day, broadcast-quality global experience focused on disciplined capital formation, regulated investment crowdfunding, and purpose-driven growth. We're bringing together leading voices in impact investing, compliance, digital marketing, and circular economy innovation to deliver practical frameworks, real-world case studies, and actionable strategies. The event culminates in the PurposeBuilt100™ Showcase, recognizing 100 of the fastest-growing purpose-driven companies in the U.S. Register now to secure your seat and get all the details. August 25–27, streaming worldwide.Visit Our Complete Community Event CalendarIf you would like to submit an event for us to share with the 10,000+ changemakers, investors and entrepreneurs who are members of the SuperCrowd, click here.Manage the volume of emails you receive from us by clicking here.We share educational information—not investment advice. Some links may generate compensation. See our full disclosure.We use AI to help us write compelling recaps of each episode. Get full access to Superpowers for Good at www.superpowers4good.com/subscribe

Copenhagen Fashion Week street style, Hilary Duff’s Y2K revival, and TikTok's viral "outfit villain theory" are having a serious moment. Tam and Chelsea Hui are breaking down all the biggest fashion headlines, from extreme maximalist layering on the Danish runways to the thin line between authentic personal style and cool-girl trend fatigue. Plus, the fashion world is in overdrive after the Met Gala announced its controversial John Galliano exhibition, raising the ultimate question of whether we can ever truly separate the art from the artist. And Hilary Duff is single-handedly resurrecting the iconic "jeans and a nice top" uniform on tour, complete with nostalgic vintage tees and glow-in-the-dark stars. BOUJIE TO BUDGET: Chelsea's Item: Budget: Dissh Fiora Black Cupro Fringe Top $149.99 Mid-Range: Maison Essentiele Lace Longline Cami $325 Boujie: Rag &Bone Billie Sequined Tassel Top $749 Tamara's Item: Budget: Feather & Noise Lola Cropped Jean in Black Spot, $89.95 Mid-Range: Sheike Amara Denim Barrel Jean, $150 Boujie: Alemais Boa Mid Rise Jean, $390 HELPFUL LINKS: Right now, every Mamamia subscriber is automatically entered to win a $5,000 Dreamworld holiday for four; flights, accommodation, express passes and more included. Subscribe here to enter. T&Cs apply. Become a Mamamia subscriber and get an all-access pass to everything we make, including exclusive podcasts and early listening, subscriber-only articles, monthly giveaways, discounts and our home workout app, MOVE. Subscribe here. Get access to Very Peri, Mamamia's exclusive perimenopause series, for just $59. 25 world-leading experts, over 20 on-demand sessions, available now. We’ve sorted through the noise so you don't have to. Go to veryperi.com.au today. You hot? Same. GET YOUR FASHION FIX: Watch us on YouTube here. Follow us on Instagram & TikTok: @nothingtowearpod Shop the Pod: Sign up to the Nothing To Wear Newsletter to see all the products mentioned plus more, delivered straight to your inbox after every episode. Feedback? We're listening! Email us at podcast@mamamia.com.au CREDITS: Co-Hosts: Tamara Holland & Chelsea Hui Producers: Talissa Bazaz, Ella Maitland & Zara Sengstock Audio Producer: Scott Stronach Just so you know—some of the product links in these notes are affiliate links, which means we might earn a small commission if you buy through them. It doesn’t cost you anything extra, and it helps support the show. Happy shopping! Mamamia acknowledges the traditional owners of the land on which we have recorded this podcast.Become a Mamamia subscriber: https://www.mamamia.com.au/subscribeSee omnystudio.com/listener for privacy information.

The most petty and ii informed podcast in the world! New Zealand comic Ray O'Leary tells us about his passion for a meal-deal, deaf actor Jamie Rea teaches Tam how to sign, Harthill born and Vegas residing mentalist Colin Cloud dazzles Ray and Tam with some live magic and the brilliant Gyles Brandreth explains why he has Dame Judi Dench's teddy bear in his bag and did Gyles really share a bath with Jimmy Edwards? Click and find out.

Don’t miss this massive channel shift! Subscribe to our Newsletter:https://theultimatepartner.com/ebook-subscribe/ Check Out UPX:https://theultimatepartner.com/experience/ In this episode of the Ultimate Partner Podcast, host Vince Menzione sits down with Alexandra Zagury, Corporate Vice President of Channels at Microsoft, to explore ecosystem shifts, partner-led growth, and AI transformation. https://youtu.be/9jrSGX5bM90 Key Takeaways Microsoft’s telemetry and propensity data offer unprecedented insights that many partners are currently failing to unlock. Partners must evolve past basic licensing models and build comprehensive managed service stacks across the entire customer lifecycle. Establishing an AI Center of Excellence on the Microsoft platform is critical for capturing future market share and technical intensity. The modern tech ecosystem demands a shift from product-led growth to true partner-led growth driven by multi-partner collaboration. Renewal engines targeting 110% to 125% retention require an always-on motion starting well in advance of contract expiration. Investing in sales readiness and precision velocity training ensures that end sellers can effectively articulate the value of the Microsoft platform. If you're ready to lead through change, elevate your business, and achieve extraordinary outcomes through the power of partnership—this is your community. At Ultimate Partner® we want leaders like you to join us in the Ultimate Partner Experience – where transformation begins. Key Tags Microsoft, telemetry, Hyperscalers, channel, small medium enterprise, telcos, hosters, SSPs, Cisco, CSP, agentic GTM, propensity data, SPX, PUPP, cloud descent, MSPs, managed XDR, Agent 365, skilling, co-sell, renewals, flywheel, AI Center of Excellence, enterprise Transcript Alexandra Zagury Audio Podcast [00:00:00] Alexandra Zagury: One of the things that I think is the best kept secret at Microsoft is the telemetry that we offer our partners. [00:00:08] Vince Menzione: You can feel it happening. The ecosystem is shifting beneath us, the way Hyperscalers are partnering, how AI is remaking the channel and what it means to win in 2026. Welcome to the Ultimate Partner Podcast. [00:00:22] Vince Menzione: I’m Vince Menzi, own your host, and each week I sit down with leaders at the intersection of technology. Partnerships and outcomes. The voices shaping how ecosystems actually work. We talk about what’s real, what’s changing, and what it takes to lead in this era where the partner channel isn’t just part of the strategy. [00:00:41] Vince Menzione: It is the strategy because being in the room changes everything. Let’s [00:00:46] Guest: start. [00:00:50] Vince Menzione: I am thrilled because I get to have a leader that is somewhat new in role and is the corporate vice president of channels for Microsoft. And so Alex is here to, is joining us for the first time at Ultimate Partner. I’m thrilled to have you. Thank, thank you so much. Thank you so much. Welcome, welcome. [00:01:14] Vince Menzione: Thank you. Thank you. You and I are gonna be in the center seat in the middle. Okay. Yeah. Yeah. We wanna. So I am thrilled. Um, you’re relatively new in your role at Microsoft. [00:01:24] Alexandra Zagury: Seven months. [00:01:25] Vince Menzione: Seven months, [00:01:26] Alexandra Zagury: yes. [00:01:26] Vince Menzione: Wow. That’s a, that’s a crazy. So take us through, ’cause for those who don’t know you, but a little bit of an introduction, your title, your role, CVP, and uh, your remit. [00:01:37] Vince Menzione: Let’s talk about that and what your organization is focused in, in your mission. Yeah. [00:01:41] Alexandra Zagury: So hi everybody. Really exciting to be here. Thanks for the invitation, Vince. I always love to be with partners and with the channel. So my, I came to Microsoft to lead a new role, which we call Global Channel Sales, and it was part of the strategy of Microsoft to really bet on the growth in small, medium enterprise. [00:02:04] Alexandra Zagury: With the channel partner led growth. So my remit is really to lead our managed partners, but also to lead the strategy when it comes to the channel. Very specifically looking at the telcos, the distributors, the hosters. The sis and, uh, the SSPs of course. And, and so my role can be summarized in one word growth, and that’s what we do every single day is map our ambition to your ambition and figure out how we actually conquer this age of ai. [00:02:40] Vince Menzione: It’s a pretty big role. It’s a pretty, you know, I forgot about hosts ’cause we don’t, we don’t talk about them as much these days in the cloud. [00:02:48] Alexandra Zagury: Still a lot [00:02:48] Vince Menzione: of opportunity. You’ve got, and you’ve got all the telcos as well, which are pretty significant organizations, right? Lumen Field, just around the corner. [00:02:56] Vince Menzione: Mm-hmm. Right up the. Right up, I said across the river, but it’s across the pond in Seattle. And, uh, what does that look like from an organization perspective in terms of dollars? Are you allowed to disclose numbers? [00:03:08] Alexandra Zagury: No, we [00:03:08] Vince Menzione: don’t talk numbers. Okay. And, but you have a long career in this type of environment, in this role. [00:03:15] Vince Menzione: 10 years at Cisco, right? [00:03:17] Alexandra Zagury: Mm-hmm. [00:03:17] Vince Menzione: Tell us a little bit more about your background, [00:03:18] Alexandra Zagury: please. Yeah, sure. Um, well I started out as a, a sales leader. Uh, actually I started out in banking, if you wanna go all the way back. Um, but I fell in love with the channel actually, when I was at Yahoo, believe it or not. Wow. [00:03:32] Alexandra Zagury: Because it was the first interact sales model that I had the privilege to operate in, and I really understood. Stood the power of going through a channel. And then I was at Blackberry where I, I, I also, um, well had various sales leadership roles, but our model was all through, was all through the channel. [00:03:51] Alexandra Zagury: Yes. Um, some startups and then help [00:03:54] Vince Menzione: in those days too, right? [00:03:55] Alexandra Zagury: Yeah. It was all sps and I learned from Jim Balze the channel fundamentals. So, um, and then ended up, of course, at Cisco the last. Nearly 11 years, which I think is also one of the greatest channel companies. Yes. And really has thrived in a partner, partner led growth, and in a partner led model. [00:04:12] Alexandra Zagury: And so when, when Microsoft called, I mean, this was just the opportunity of a lifetime. To lead the channel during an era where we’re all getting disrupted, we’re all having to blueprint new systems, new ways of working, where go to market is getting identified, and we’re all having to figure out how to become customer zero ourselves, but then also how to go to market. [00:04:36] Alexandra Zagury: With, with agents. And so this was the, the most exciting time that I could think of to join the Microsoft ecosystem and really take us to the next level. [00:04:44] Vince Menzione: Well, your background is perfect for this. I, I, Rodney Clark is a friend, has been a guest on the podcast and in, in the studio, and I think of Cisco is the quintessential channel company. [00:04:56] Vince Menzione: Like when I think about how channel got created and how it worked well, it was always Cisco that did it. So give us like your perspective now, like seven plus months and like how does this feel like you’ve You’ve got a big remit and, uh, various, uh, routes to market. We’ll call them, uh, channels to market. [00:05:14] Vince Menzione: So take us through a little bit of that, like Yeah, sure. [00:05:16] Alexandra Zagury: Describe [00:05:16] Vince Menzione: the transition, what it’s been like [00:05:18] Alexandra Zagury: for you. So one of the things we’re focused on is supporting the channel through the transformation, and we look at it in a couple of lenses. The first lens is really helping the channel become customer zero. [00:05:29] Alexandra Zagury: We really believe that the partners that invest in. Actually identifying their own processes and their own go go to market are the channels, are are the partners that it can actually win because if you are using it, you’re gonna be able to sell it. The second layer is all about technical intensity, and I’m very passionate about this because I see it from two lenses. [00:05:51] Alexandra Zagury: One is. I would like each and every of our partners to lead in building an AI Center of Excellence based on the Microsoft platform. It is a unique opportunity. I can give you lots of numbers, right? We’ve all heard about the trillions of agents that are gonna be here by 2030. We’ve all heard about the tam. [00:06:12] Alexandra Zagury: I mean, our TAM is going from 777. Million to over a billion, uh, to over a trillion. I, it’s, the numbers are just enormous, insane, right? Over half a billion of customers in our base that are using, that are, that are based already on the Microsoft platform. So all the goodness of our IU IQ platform can be unlocked with all the services that the partners can build. [00:06:36] Alexandra Zagury: So investing in that technical skilling and building those practices are gonna be, is gonna be essential. The third part. The third pillar is all about ag agentic, GTM. So once you’re actually using, uh, the Microsoft platform, you’re gonna have to reimagine all your business’s pro processes, your sales processes, and the more that you are integrated into how we do, how we do things. [00:07:00] Alexandra Zagury: One of the things that I think is the best kept secret at Microsoft is the telemetry that we offer our partners. Yeah. I mean, it’s unbelievable. I’ve never seen the quality of propensity data. And now I’m gonna give you the ABCs, which is please, A SPX, which is where we get all our copilot data, PUPP, which is our proposal upsell, uh, planner, right, cloud descent, where you can actually get your next action directly to your sellers. [00:07:27] Alexandra Zagury: There is just so much goodness that we give, which is part of our, our investment in partners. Which takes me to the fourth pillar, and that is all about value alignment and one of the things that I’m very focused and I bring with me from, from Cisco and the work that I did with MSPs is really thinking through what is that value exchange between us and the partner. [00:07:49] Alexandra Zagury: I believe that I’m in the business of earning your trust. Earning your preference. And, and, and we do that by really mapping that value alignment. So not just, one of the things that the whole industry has copied from Microsoft is really looking at our incentives across the customer lifecycle. Yes. So really mapping the value alignment across the customer lifecycle, not just at the point of the deal. [00:08:13] Alexandra Zagury: ’cause that was the whole purpose of CSP. That’s right. The investments we make in tele telemetry, the investments we make in our go-to-market assets and having those bi-directional feedback loops so that we can be continuously improving. So those are sort of the things that I’m thinking about every day. [00:08:29] Alexandra Zagury: There’s a couple of others as we lead and support you in this transformation. ’cause I think of my job as to supporting and driving growth with you so that we have that joint ambition. But also supporting the transformation that both of us are on this journey. [00:08:44] Vince Menzione: And Microsoft was the first with Jay McBain was with us yesterday, and we talked, we’ve talked about this before, but you were the first company to take and look, get rid of the old metal systems, right? [00:08:55] Vince Menzione: The bronze, silver, gold, mm-hmm. And move to basically a point system for partners so that they can come at it from a kind of a global perspective on how they drive success. What was, um, what did you learn about this partner community, your first months that you didn’t expect? [00:09:12] Alexandra Zagury: Can I say something controversial? [00:09:14] Vince Menzione: Absolutely. Okay. [00:09:14] Alexandra Zagury: I love, [00:09:14] Vince Menzione: we love controversial, [00:09:15] Alexandra Zagury: so I think one of the things that I was surprised was that I didn’t see all the partners really unlocking the value of CSP. Yeah. What do I mean by that? When Microsoft moved to the Point System, and I was on the other side, really, I was so jealous of CSP when I was running managed services. [00:09:34] Alexandra Zagury: Here’s an offer that is for partners, for Partner that gives you that initial. Guarantee in terms of the margin that helps you throughout the customer life cycle with all the incentives and, and programs that we have. And I didn’t see, I mean there are some partners, but I was surprised not seeing more partners really building their value stack and their services across the lifecycle. [00:09:59] Alexandra Zagury: And I think there’s such a great opportunity now to do that. That was one of the most surprising things I thought. Oh my gosh, there must be so many, so many services stack, so many people really unlocking, unlocking that, that value. That was a, that was a little bit surprising. [00:10:14] Vince Menzione: Why? Why do you suppose, why do you suppose that was happening? [00:10:17] Alexandra Zagury: I think some of the things that we were listening here, there’s some, sometimes complexity. There are things that we still have to. Get better on, and I’m one of the first ones to say that like our partner experience, we have, um, you know, a lot of focus right now on partner center and ensuring that we’re identifying it. [00:10:36] Alexandra Zagury: I don’t know if I can say it, but, you know, one of the things that we’re looking at is replicating internally. We have Agent J. That supports our sellers through the sales process. Nice. We’re looking at having something similar for our partners. Very cool. Getting some claps there. So, yeah, so, uh, I think, you know, that I, some, there are some lockers that we, we have to acknowledge a lot of them are operational and comes with being a 50-year-old company. [00:11:02] Vince Menzione: I, I’ll give you my perspective too. I wanna get your thoughts on this. ’cause I got to, I’ve gotten to know this MSP community, which is a, you mentioned managed services and that, um, I think that some of them, well, I think Microsoft is leaning in, in a much bigger way. Um, we had Jose on stage yesterday and just the, the energy around the room, there he is, he’s back here. [00:11:23] Vince Menzione: The energy in the room around the MSP community is palpable and it maybe it wasn’t there a few years ago. Maybe some people got off the bus, so to speak, like they weren’t really paying attention mm-hmm. To all the change and all the investments. That you men, you’re mentioning or being made to support this, would you, what would you say about that? [00:11:42] Alexandra Zagury: Yeah, I’d say that that that is correct, but I’d also say that what I learned, you know, leading MSP at Cisco was that. All the stars have to be aligned, right? And if one thing is not right, if you don’t have product market fit, if you, if you, if you don’t have a good way to, uh, consolidate your offer, if you don’t have that investment in practice development, like there’s a series of things that we need to get right. [00:12:07] Alexandra Zagury: And I think Jose and I spent a lot of time thinking through those things and we’re, we’re ready to, to welcome the community and specifically around security. I mean, that was the second thing that I was really surprised because I lost so many deals on the other side to Microsoft, and I was like, and then I come on this side and I’m like, there’s all this opportunity everywhere. [00:12:28] Alexandra Zagury: I look underneath this chair, this opportunity, and I’m like, why are people not going after it? There is the opportunity to build managed XDR solutions, the opportunity to reinvent the song. There’s, there’s just so much opportunity and I think people get so stuck in the. Just thinking of it from a licensing model and not thinking it from the, the full on end-to-end value that you can then unlock through the best licensing model on the planet. [00:12:55] Alexandra Zagury: And so, look, we’re here, we’re, we’re ready to talk to all of you and, and really figure this out ’cause we are gonna place really bet big bets next year on ensuring that we’re growing with the MSP community. [00:13:08] Vince Menzione: So what are you personally focused on in changing Microsoft to drive this. [00:13:13] Alexandra Zagury: Well, uh, I don’t know. [00:13:14] Alexandra Zagury: Changing is a, is a, is a big word. Well, I like evolution, change, [00:13:17] Vince Menzione: evolution, evolving. [00:13:18] Alexandra Zagury: You know, I [00:13:19] Vince Menzione: transition. [00:13:21] Alexandra Zagury: I think there is, there is a couple of things that I’ll say that one of the things that I, I’m really focused on right now, the first one is skilling. We’re at a time of such transformation. That investing in skilling, and if you look at our skilling model, it has four pillars. [00:13:37] Alexandra Zagury: The first pillar we’re best in class, in which is certification specializations, and making sure that our ecosystem is certified to go to market. The second one, which we call project ready. It’s sort of how we help you, uh, technically skill the folks that sit in your practices. And there’s more work to do there, and there’s more that you can learn about how we can actually help you. [00:13:59] Alexandra Zagury: And then the middle part I’m obsessed with right now, which is sales ready and tech sales ready. So it is ensuring, because AI is new for everybody. Yes. It’s a muscle, it is a proposition that you have to sell it’s value that you’re selling. I, I love what the gentleman from Lenovo was talking about. It’s, it’s that CSB always on motion. [00:14:21] Alexandra Zagury: Yes. And so really getting very crisp to the end seller at the, at the reseller. For example, at the end, seller at the partner about why Microsoft. Why now, how do I sell and how do I win? And giving them the assets, the competitive battle cards, the, the, the ability to end objection handling all these. Great, we have them. [00:14:45] Alexandra Zagury: I mean, the amount of content we have, but it’s about doing it at what I call precision velocity. [00:14:51] Vince Menzione: Precision [00:14:51] Alexandra Zagury: velocity, right? Which is this concept of how do we get very precise at a persona level. So that we get the velocity of impact. And so I’m, I’m very obsessed with that right now. And there’s two other things I’m very obsessed with, right? [00:15:04] Alexandra Zagury: The other one is this practice building, ensuring that we are together building these AI centers of excellence, um, especially for all our managed partners. This is something that I’ve put on, uh, every single PDM in our org is gonna, is gonna be talking about that. And then the third one is one that I find super interesting, which I think all of us. [00:15:25] Alexandra Zagury: Have a lot of work to do, which is partner to partner. [00:15:29] Vince Menzione: Yes. [00:15:29] Alexandra Zagury: If we look at a customer outcome, thank you. A customer outcome is built of many partners, right? There’s so many different touch points. I think some folks talk about seven partners in, in a customer outcome, and so how do we actually. Use agents, use agent solutions to suddenly unlock this opportunity because most of the time you’ll see an SSP with an si, maybe an ISV in the middle of a transaction to deliver on that customer outcome. [00:16:04] Alexandra Zagury: Yes. So what can we Microsoft do? And I’d love ideas, right? I haven’t cracked this. I don’t think the industry has completely cracked this. It’s more of a, a science than, than, well, more of an art than it is a science today. So that’s the third thing that I, I, I’d love to really improve and, and get better at. [00:16:20] Vince Menzione: I wish you got to see my slide earlier. ’cause I had the seven seats. I had this, I had the seven partners surrounding the customer. Customer is able to make their decisions now because with their cloud commitments [00:16:31] Alexandra Zagury: mm-hmm. [00:16:32] Vince Menzione: They’re in the, they’re in the seat where it used to be. I would rely on the partner to tell me what to do. [00:16:38] Vince Menzione: I, I’m cobbling together the best solution for my organization. Based on the trusted partners, to your point, those seven seats, and that’s partner to partner action. And Jay McBain was here yesterday and he took us through a great example. It’s AstraZeneca, that Microsoft won AWS, thought they were gonna win the deal, and then there were Microsoft partners in involved. [00:17:00] Vince Menzione: And the, the decision was made in December, but the deal didn’t happen until July. And that whole process was because all these different partners showed up. And influence the decision and the solution areas for that customer. [00:17:12] Alexandra Zagury: Yeah, that’s the best example of PLG partner led growth in action, which I think, again, that is the other thing that I’m super excited about is that actually p proving in the AI era that it’s about PLG as partner led growth, not the other PLGI. [00:17:31] Vince Menzione: I love that. I love that. Instead of product led growth, it’s partner led growth. So I understand there’s three layers that you’re very interested in that you want, you were gonna take us through today. Okay. Do you know about this, [00:17:44] Alexandra Zagury: the layers [00:17:45] Vince Menzione: of we have, uh, copilot chat. Oh, yes. 365 and, and agents. [00:17:49] Alexandra Zagury: Yeah. [00:17:50] Vince Menzione: From a product perspective, I thought maybe, [00:17:51] Alexandra Zagury: yeah, sure. [00:17:52] Alexandra Zagury: This is, I mean. This is the, uh, advantage of choosing the market Microsoft platform. Yeah, so as you look, look at it, there’s, there’s definitely different options, but when you look at Microsoft, what’s really, really interesting is that we have all the, all the layers. There’s no AI without data, and we’ve got that data foundation. [00:18:15] Alexandra Zagury: We also have the intelligence data foundation, right? Then we’ve got the, the layer of actually building those AI agents, and then the last layer that we have is actually the experience or the application layer. So when you look at our platform is a completely integrated platform with the different choices. [00:18:35] Alexandra Zagury: We are not behold, beholden to one LLM or another LLM. You’re actually able to bring your data and, and bring the LLM that you want to deliver on the, on the outcomes that you need. And I think that is very, very unique about our proposition. Yeah, I [00:18:50] Vince Menzione: agree. [00:18:50] Alexandra Zagury: But the other thing that is unique, it’s the most exciting product out there. [00:18:55] Alexandra Zagury: Agent 3, 6 5, our own oh oh seven. It really is a differentiated proposition that every single partner can build services around. Starting with your advisory services, tell me customer, what is it that you are thinking of? Then you actually move on to thinking about security because again, just like there’s no AI without data, you have to start with that data foundation. [00:19:24] Alexandra Zagury: There’s no AI without security and no security without ai. And so really thinking through how, uh, agent 3, 6, 5, I love it. I get these claps once a, I love, love really thinking about how Agent 3, 6 5 really unlocks, not only. A security budget, but an observability budget because you can do both. You are talking to both, uh, folks at the customer, right? [00:19:47] Alexandra Zagury: You can actually start talking about how you’re gonna actually govern all of these agents, manage all of these agents, but also there’s the observability layer, which is gonna tell you what actually can you do? How can you actually deliver on the outcomes that we all want from ai, which is productivity. [00:20:05] Alexandra Zagury: Experience and efficiency and all the other things. So I think this is the biggest opportunity this channel has ever seen, and every single partner is gonna have to make a choice on what platform they’re gonna lead with, and we believe it should be ours because it is completely integrated across these three layers with our very own oh oh seven. [00:20:30] Vince Menzione: I wanna get your perspective, but it feels like many of these partners in the MSP community are stuck at that CSP level. We were having this conversation about getting through that, coaching ’em through it. What would your be your perspective on that? [00:20:44] Alexandra Zagury: Um, I’d say, uh, use this moment to unlock that opportunity. [00:20:50] Alexandra Zagury: First off, invest in your skills. Get your, get your team skilled and, uh, on Microsoft, build your center of excellence. Map out your strategy where actually you’re gonna monetize and use all the different assets that we have. And if you are being really, um, I mean, most of them are serviced through a distributor. [00:21:12] Alexandra Zagury: Make your distributor accountable for supporting you in packaging the offers and giving you the, uh, information that you need in terms of skilling. And then in terms of co-selling, again, distributor has a lot of tools that can help you understand how to unlock the co unlock, the co-selling opportunity with Microsoft. [00:21:35] Alexandra Zagury: I think that’s another really big competitive advantage that Microsoft has. When, uh, Microsoft changed what it started by, by, by changing its strategy. I think clarity is kindness. We were very, very clear that where we want, we wanted partners, of course, to play an enterprise with a services stack, but we were very clear that we were betting on a partner led growth in small, medium enterprise, right? [00:22:03] Alexandra Zagury: And so we’ve built our whole operating system. Around that. And so I think it’s really about finding the information that you know you want, planning your strategy, getting skilled and go to market with us. Our co-sell Advantage is very, very unique. It is one of the only companies that has the sales teams completely aligned because CSP is our hero motion. [00:22:29] Vince Menzione: So being with a customer through the journey on CSP, but also renewals are a big component of growth. Talk to us about that. [00:22:36] Alexandra Zagury: Yeah. Renewals are, uh, a machine and an engine that is just absolutely beautiful. It’s your [00:22:42] Vince Menzione: flywheel. [00:22:43] Alexandra Zagury: It is your flywheel. Um, and it is the gift that keeps on giving. We, of course, have a very focused, um, and in fact, one of the things that I’ve done since. [00:22:52] Alexandra Zagury: Uh, since we’ve started, it started a very focused motion in terms of looking at our renewals. We have very specific targets. We, we like to see a renewal at 110% at the moment of renewal. And then we like to see a motion, t plus three, T plus six. That gets us to that a hundred and and 25%. But what we’ve also found out is that this needs to be an always on motion. [00:23:18] Alexandra Zagury: So one of the things that we’re doing is using this concept of precision velocity becoming very rigorous. ’cause we have all the data. Yeah. In terms of what is that next action, and really looking at starting that renewal process, we see that the partners that are able to reach the targets are the ones that start at T minus. [00:23:36] Alexandra Zagury: Six, maybe T minus three, you’re cutting it, but T minus six. And really building that constant motion, getting out in front Yeah. With the customer is really important. And then of course, we now even have these amazing go back motions, uh, with, with our partners where we actually, after the renewal, we go and. [00:23:56] Alexandra Zagury: The renewal was not at the target. We just constantly keep on going. Uh, going back with the, with the partners and we’ve unlocked a, a bevy of data. We, our operating model, we call it the pods, where the PDM sits at the center and orchestrates it with all the different roles that we have. And so we now have a very systematized moment, uh, motion of how to do the renewals. [00:24:18] Vince Menzione: So for the partners in the room, what’s one investment that they should make and what should every partner in the room do differently? Going into, uh, July 1st. [00:24:27] Alexandra Zagury: Well, I think the first thing, remember, CSP is our hero motion, so really for, uh, real, really focused on that. But the one investment, can I say two? [00:24:38] Vince Menzione: Please, please. [00:24:38] Alexandra Zagury: Your time. The, the first one is skilling, right? This is the time. [00:24:43] Vince Menzione: Yeah. [00:24:43] Alexandra Zagury: Technical intensity is super, super important, and really making those investments in skilling not only from a practice perspective, your your, your technical practice, uh, teams, but also from a sales readiness perspective. [00:24:59] Alexandra Zagury: This is a new muscle. It’s we’re all learning how to truly sell outcomes, and so getting your sales teams ready. Is is really important. And then the second one very tied to that is building your AI Center of Excellence based on the Microsoft platform. Because as we go into FY 27, you will see that the partners that prefer and grow with us are the ones that will see the investment come to them. [00:25:28] Vince Menzione: So I want to use the term front. I I, I’ve been avoiding the term frontier firm, but I think it is super critical. Everything I’ve heard today, like you need to be customer zero. You need to get in train, advance on it and go build against it. [00:25:41] Alexandra Zagury: Absolutely. Well, if you had, let me a third, I would’ve said customer zero. [00:25:46] Vince Menzione: You have it? Alright. We have less than a minute. Would you be okay if we ask for like maybe one question? Yeah, absolutely. We’ll do like one, maybe two. So good to have you by the way. Thank you, Vince. So nice to have you here. [00:26:04] Vince Menzione: I think we did such a good job. Oh, here we go. Here’s, here’s fun. A mic is coming your way. [00:26:20] Vince Menzione: Thank you. Here we go. Okay. [00:26:22] Guest: So we’ve been very keen on, um, skilling our people, and I still find it very hard to get all of the information out of Partner Center to get a complete global view. Are you and your team thinking about maybe having an MCP server access and having a real portal working with that data? [00:26:41] Alexandra Zagury: You just touched on one of our areas of improvement. Absolutely. In fact, um, thank you for, stay tuned for holding us accountable to that. That is definitely one of the things that we’re working on is how to integrate skilling hub into partner center. Right. As most of you will know, there are it Qs, and so that’s one of the things that we are definitely prioritizing, but thank you for holding me accountable to that one. [00:27:09] Vince Menzione: Awesome. [00:27:13] Vince Menzione: We have one more back here, David. I see. We wanna see how fast they can move that microphone across the room. Relay system here. The relay team. There we go. [00:27:25] Guest: That was excellent, Alexander. Thank you. And welcome. [00:27:28] Alexandra Zagury: Thank you. [00:27:29] Guest: Can you point to a specific example? ’cause I think it’s so critical what you highlighted just the skill piece and the customer outcomes piece. [00:27:35] Guest: Right. Can you point to a specific example of a story that you really love that highlights, uh, customers lighting it up with ROI. [00:27:44] Alexandra Zagury: Yeah, I think, you know, we’re, we’re, we’re a platform, so I just saw a win wire. Like at Microsoft, we get these win wires all the time about how an SSB actually won a, a deal against one of these big AI only companies. [00:28:00] Alexandra Zagury: And it was really about selling the full platform, right? Yeah. Because if, if you, if you put a full platform against an LLM proposition, I mean, the full platform really stacks up because it’s completely integrated. It’s not behemoth to one, you’re not making a bet on one company. And it really highlighted our mantra around trust and intelligence. [00:28:24] Alexandra Zagury: The customer was able to see, they, they were an M 365 customer, so all their iq, all their intelligence was already there. They knew that they, there were guardrails against it. They had a problem with shadow ai and by actually standardizing on copilot and going on that journey from copilot paid to agents, they sue the, they saw the full, uh, value proposition. [00:28:49] Alexandra Zagury: And so we won that deal and it was one of the. First E seven deals that we won, so it was great. [00:28:55] Vince Menzione: Fantastic. Great. Congratulations. [00:28:57] Alexandra Zagury: Thank you [00:28:58] Vince Menzione: Alex. I am so honored and thrilled that you got, you chose us to be your I I would say the first big Yeah, absolutely. Presentation in front of the partner community. [00:29:07] Vince Menzione: I’m so excited to have you. [00:29:08] Alexandra Zagury: Thank you [00:29:09] Vince Menzione: guys, and hopefully many more times ahead with us. [00:29:10] Alexandra Zagury: Absolutely. Invite me at anytime. [00:29:12] Vince Menzione: Okay. Well, thank you [00:29:13] Alexandra Zagury: so much. [00:29:14] Vince Menzione: Thank you. So great [00:29:15] Alexandra Zagury: to have you. Thank [00:29:16] Vince Menzione: you so much. Thanks for listening to The Ultimate Partner Podcast. If today’s conversation resonated, share it with a partner leader in your network. [00:29:26] Vince Menzione: Subscribe where you listen, and head over to the ultimate partner.com. For show notes related content and the resources for this episode. And if you haven’t already, now’s the time to register for the Ultimate Partner Live Event in Reston, Virginia, October 26th through October 28th. Until next time, keep showing up in the rooms that matter because being in the room changes everything.

Hrvaški gasilci se znova z vsemi silami borijo s požarom, ki je vnovič vzplametel na Dugem otoku in se zaradi močnega vetra hitro širi. Na zahtevnem, nedostopnem terenu znova pomagata kanader in air tractor. Pod nadzorom pa so štirje požari na območju Zadra in eden na otoku Iž ter največji v okolici Omiša. Tam zaradi vetra obstaja nevarnost vnovične razširitve ognjenih zubljev, ki so včeraj zahtevali najmanj eno smrtno žrtev. Ob tem se je nov požar razširil iz Bosne in zajel tudi hrvaški del Dinare. Na terenu so gasilci in kanaderji, oblasti so na pomoč vpoklicale tudi vojsko. V oddaji tudi o tem: - Na praznik Marijinega vnebovzetja verniki romajo v Marijina svetišča; na Brezjah se jih je zbralo 3 tisoč - Jedrska elektrarna Krško zvišala obratovalno moč na 90 odstotkov - Mineva 5 let odkar so talibani vnovič prevzeli oblast v Afganistanu

00:00 - 6 óra 31:07 - A magyar turisták is menekülnek a Horvátországban pusztító tűz elől - vonalban Judit, akinek már sikerült elmenekülnie 50:05 - Egyetlen ágy miatt kér segítséget a Bethesda Gyermekkórház - vonalban Dr. Tamásné Bese Nóra Bethesda kórház főigazgató helyettese 1:06:28 - Ma több információt dolgoz fel az agyunk naponta, mint 500 éve egy király egész életében - vonalban Szász Máté, neurobiológus 1:45:17 - Telefonon értük utol Balázst Hajsza közben

3 - Egyetlen ágy miatt kér segítséget a Bethesda Gyermekkórház - vonalban Dr. Tamásné Bese Nóra Bethesda kórház főigazgató helyettese by Balázsék

Leonie's recording from outside, and there's a reason. Operation De-SADify is underway after a week of crying at random, including weeping twice in one day about Cathy Freeman winning gold in 2000. Tam has found the Slavic shamanic teacher she's been hunting for years and is running a literary festival. We're both reading fabulous books that we want to tell you about. Also: the autistic Olympics. Census night, baby.WHO THIS IS FORIf you're a neurodivergent creative running a business while also holding kids, ageing parents and your own wobbly nervous system through the last month of winter, this one's for you. Especially if you can't tell whether you need a strategy or just more sunshine and a nap. Two women talking honestly about widening to hold it all.TOPICS COVEREDSeasonal affective disorder, micro-depresso and Operation De-SADifyA Laufey concert with a teenager, and discovering there's room for all of usHow healing primitive reflexes changed Leonie's capacity for big overwhelming citiesTam's Slavic shamanic training and coming home to your own lineageEmotion as a pathway to the divine, instead of sitting still and being decorousParenting your kids as they are, not as your ancestors assigned themSandwich generation life and the tragedy-comedy of caring responsibilitiesCensus night as competitive sportKEY INSIGHTSRandom crying is a useful depression indicator if you're not ordinarily a weepy soul. If you're welling up at nothing at the end of winter, up your light, your vitamin D and your outdoor hours.Nervous system work has profound effects.. Leonie went from wanting to hide in a bush in Sydney to happily sitting through an arena concert.The way you see your child can be an inherited story rather than a true one. Keep people around you who'll aren't afraid to tell you you're wrong. Leonie's husband told her she was misreading one of their kids, and he was right.Don't break under the pressure. Widen. That's what every grandmother before you did.Making money and keeping money are two different skills. A leaky container drains a great income.NOTABLE QUOTES"I don't want to be the mother that just gets all her feathers ruffled just because she's gotten some feedback." — Leonie"Instead of feeling like I'm going to break under that pressure, I just keep thinking that I need to widen so I can hold it all." — LeonieLINKS & RESOURCESUnicorn Biz & Life Academy, $99/year: https://www.leoniedawson.com/academyJoin Leonie's mailing list for the illustrated book notes: https://www.leoniedawson.comDandenong Ranges Litfest, programme launch 27 August, tickets 28 August: https://dandyrangeslitfest.net/Tam's Slavic shamanic teacher, Vlasta: https://www.tiktok.com/@thevlasta Iris Meyer, shamanic practitioner: https://brightshaman.com/BOOKS MENTIONED:Indistractable by Nir EyalThe Psychology of Money by Morgan HouselUnnatural Habits (Phryne Fisher) by Kerry GreenwoodIf this one resonated... make sure you hit subscribe pretty pls! A review takes 40 seconds and helps other gorgeous souls find us. And if you want the whole toolkit, the Academy is $99 a year for 100+ programs, monthly coaching, and the Make Your Money Back Challenge that pays for your membership before you've finished your cup of chai!ABOUT YOUR HOSTS!Leonie Dawson is a multi award-winning entrepreneur who has created over $16 million in revenue in part-time hours. She is the founder of the Unicorn Biz & Life Academy which helps 3,000 people build unique, joyful & abundant businesses.https://www.leoniedawson.comTamara Protassow is a non-fiction writing mentor + creativity coach. She's developed books with 55+ authors over 16 years, both for self-published authors as well as for Hay House UK. https://www.tamaraprotassow.com #WomenInBusiness #NeurodivergentEntrepreneur #AuDHD #CreativeBusiness #SpiritualBusiness #MidlifeWomen #SandwichGeneration #PersonalGrowth #SoulfulBusiness

Featuring: Ace, Ammosart, Ashgar, Tamrielo, and Thalen After a mostly understandable break, we return with a mostly normal show. Topics include Cozy Grove and its recently-released sequel, lots of the crew falling back into Gunfire Reborn, and Tam enjoing High on Life 2. We also talk a bit about recent ARPG releases, with both Grim Dawn and Hell Clock both having new expansions. After that, remaining topics include the mystery game The Incident at Galley House, a long-delayed game completion of Titanfall 2, Palworld's 1.0 release, and concluding with Meccha Chameleon.

Robotaxis are accelerating along the road to commercial viability. Auto and Shared Mobility Analysts Andrew Percoco and Tim Hsiao discuss what this rapid development means for global investors.Read more insights from Morgan Stanley.----- Transcript -----Andrew Percoco: Welcome to Thoughts on the Market. I'm Andrew Percoco, Head of North America Auto and Shared Mobility Research. Tim Hsiao: And I'm Tim Hsiao, Greater China Auto and Shared Mobility Analyst.Andrew Percoco: Today, why robotaxis may be approaching a commercial inflection point. It's Thursday, August 13th at 8am in New York.Tim Hsiao: And 8 pm in Hong Kong.Andrew Percoco: So Tim, for years, robotaxis were really confined to limited pilot rollouts across the globe. You've done a lot of work over the last few weeks. We put out a big collaborative report on the robotaxi market and how it could be a $1 trillion TAM by 2040.What makes this moment different than some of the other robotaxi hype cycles that we've seen in the past? Tim Hsiao: We observe four things have been converging. Firstly, end-to-end AI is improving much faster. Secondly, hardware and the training costs are falling. And thirdly, more well-capitalized players can fund deployment. And last but not least, regulation is becoming clearer.The leading operators are no longer just demonstrating the technology. They are running fully driverless services around the clock and generating commercial rides. So in our view, the questions has been shifting from can it work to who can expand operating areas, raise utilization and lower costs at a much faster pace.So that's a very different setup versus the 2018 and 2021 hype cycles. Andrew, U.S. autonomous miles could rise from 116 million in [20]25 to 16 billion by 2032. But still make up only about 0.5 percent of all miles driven. How can robotaxis become a meaningful business while remaining such a small part of the market?Andrew Percoco: I would say, you know, obviously the U.S. mobility and transportation market is a massive market. So even with the rapid growth that we expect in robotaxis, it's going to take a long time to make a material impact in the overall market share of mobility. But if you think about the profit pools in this business, 16 billion miles at $2 a mile can, you know, pretty quickly become a very significant TAM and market opportunity.And I think, you know, fundamentally, if you think about a robotaxi business, I would argue you're better utilizing an asset... Or if you think about the, you know, car park, the amount of vehicles that are, you know, in the fleet today or in the U.S. today, they're sitting idle 90 percent of the time, right?So you're talking about taking a smaller amount of volume and driving a higher utilization on that fleet and driving much improved economics. So yes, it's going to take time to displace the, you know, hundreds of millions of cars that you have on the road in the U.S. and displace the penetration of miles driven. But ultimately, you know, we think that the profit pool and the opportunity in robotaxis are much more attractive for the entire value chain, as it relates to robotaxis. And I'd say there's a few things that we're watching along the way to make sure that, to your point, you know, this is not another hype cycle. And that there's real commercial backbone to this business.I'd say the first is seeing the rollouts continue to improve, and the density of the rollouts improve across the select cities that we've seen in the U.S. right now. Robotaxis are only available in a handful of cities in the U.S., so we want to see that continue to expand into more cities. But also the density of the fleet increase in the cities where they're currently present.And at the same time the safety side is still something that gets a lot of questions in making sure that it is truly safer than a human driver, across technology platforms, right? There's various players in this market with different approaches to technology. So, I think seeing that the safety curve is starting to or continues to improve is going to be very important for the viability of this market going forward.Obviously U.S. is very different from China. What have you seen in China? China has shown some impressive growth and utilization in some of the operators that are on the road in China. So just curious as to your perspective in terms of what you're seeing on the ground there. Tim Hsiao: I think China shows that there's much in operations and skill challenges as technology challenges. The fleet in China is above 5,000 vehicles across I think more than 7500 square kilometers in key cities. And some operators average more than 20 orders per vehicle per day.So, total cost of ownership has fallen roughly 30 to 40 percent, while remote assistance ratios are moving from like one operator for like 20 to 40, even like 50 to 60 vehicles. And we think it will achieve like one for a 100. So that has produced real break-even happens, especially in some major cities like Guangzhou, Shenzhen, Wuhan – the tier one, tier two cities.So in our view, I think in China, wider operating domains, fleet density and utilization rate, as you just mentioned, reinforce one another. So make it some more like the real commercial case. Instead of just, like trials as we saw a couple years ago. If more value shifts towards the software, fleet operation, and the data, as well as the customer relations, how does that change the profit pool, across the auto industry, especially in the U.S.?Andrew Percoco: First off, I think the auto industry in general is becoming, you know, more software focused and aware. You know, it's being led by the robotaxi market where the autonomous driving software and technology is obviously the most important part about getting this technology to market.That is ultimately trickling down to personally owned cars where you're seeing more autonomous technology being deployed. Auto OEMs are able to charge subscription revenue for this software. So it expands, I'd say, the value proposition of buying a vehicle expands the profit pool for the OEMs.It changes in some ways the cyclicality, or can change the cyclicality of the industry if you've got more kind of recurring revenues, subscription like business model versus just a hardware focused OEM model, which has been kind of the predominant focus for the OEMs historically. I'd say the other angle, interesting angle here is, you know, as this business scales, there's gonna be a lot of vehicles on the road. There's gonna be a lot of fleets of vehicles on the road. Those need to be managed by somebody or some company, right? So if you think about, you know, the rental car industry, right? These companies have been in the business of managing fleets and renting out fleets for a very long time. They know how to do that very, very well.I think there's an interesting opportunity for that part of the value chain, to participate in aiding these robotaxi fleet operators, in scaling and bringing their business to market. Charging, maintenance, reconditioning, all the things that take a lot of time and a pretty large amount of physical infrastructure.That's an opportunity for the rental car industry to come in and leverage their existing know-how to help. And, you know, I think Tim, an important part of this commercialization process is driving down the cost structure of robotaxis. They are very sensor; heavy sensor heavy. They're very compute heavy. I think China is the clear leader on cost and supply chain. I think in China you're seeing robotaxis, you know, around $35,000 to $40,000, which is considerably lower than what we see in the U.S. today.So, how do you think that that will accelerate adoption in China, but I'd say more importantly overseas as some of these robotaxis businesses look to expand outside of China. Tim Hsiao: In our view, it could be a major accelerant because as we noticed that the depreciation is still one of the largest fixed costs for robotaxi. So, as we just mentioned, I think, $35000 to $45000 US dollars, the purpose-built robotaxi can lower the breakeven utilization threshold. And make it easier to finance fleets and open cities that could not support the $150,000 US dollar vehicle.And not only in China, because globally, I think the Chinese cost deflation can be paired with the local ride-hailing platforms in the overseas market that provide demand and regulatory access. But as we highlighted in our previous, the global reports once again, we don't think the cheap vehicle is sufficiently by their self.So in our views, on top of the competitive cost structure, registration, data localization, insurance, and local operating costs can still delay the margin curve, particularly in Europe, which we think there are still quite a lot of uncertainties. So Andrew, as we just, as we just discussed, the lower vehicle costs help, but the operating model still has to work, right? So with operating costs expected to fall and the margin potentially moving above 30 percent or even higher at scale, what are the key assumptions investors should focus on?Andrew Percoco: There's a handful of key assumptions you need to sensitize to get to that 30 percent or more margin structure in this business. I'd say the first is going to be utilization, right? You need to be running these assets at a high utilization to essentially amortize those fixed costs over a larger number of miles driven.Number two, insurance today is probably one of the largest buckets of cost when we think about this business. Insurance is, from our perspective, a big unlock for this industry as the safety, as we mentioned before, the safety data continues to improve. We think that will be a reason to, to expect that the insurance costs associated with autonomous driving technology and robotaxis will continue to decline.It's about 30 cents per mile on our estimate, so it's very significant in terms of the overall cost structure of robotaxis. Drivers or where there's the most sensitivity around the model. Obviously, there's charging costs, there's maintenance costs. Those are, I think, fairly known at this point. But the utilization and insurance, I think, are the two biggest drivers of really getting that margin profile to improve over time. Tim, I guess when you think about the next, call it 10 to 15 years, I think we will put out a trillion dollar market by 2040 from a TAM perspective.What do you think the biggest markets are that investors should be watching, in terms of getting us to that trillion dollar TAM? Obviously, U.S. and China are kinda leading now, but what are the next markets people should be watching?Tim Hsiao: In addition to the major market, as you just mentioned, the U.S. and China, in our views, I think we also need to focus on markets like Europe, the Middle East and Southeast Asia. I think their scale is underappreciated, as we highlighted in our previous report. Because if you think about that, Europe, the Middle East, and Southeast Asia in aggregate have roughly four million taxis together ride-hailing vehicles.So even with 25 percent conversion, they imply that about one million is the L4s vehicles. The Middle East offers supportive regulators, you can tell, simpler operating environments and higher fares. And if you think about the Southeast Asia, the ASEAN, I think the market has dense demand and strong local platforms.And of course, Euro markets definitely can't be ignored because Euro will move more slowly, because we think the regulations and the data rules would initially add cost. But the truth is, if you think about the European market, I think the taxis or ride-hailing fares are among the highest globally, even compared to the U.S. and rest of the world.So in our view, the material margin could be more attractive. And this market, on top of the U.S. and China, in our view, can support several regional winners. So, not only limited to a very, you know, the single one or two markets.Andrew Percoco: Yeah, it's great Tim. It sounds like, you know, the robotaxi race, if you want to put it that way, will be won by those who can really bring together technology, and a compelling cost structure while also following the proper regulations and making sure the safety is improving at a rate that's acceptable to regulators.So, Tim, thanks for taking the time to talk today. And thanks for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you listen, and share the podcast with a friend or colleague today.

What separates a good partner strategy from a truly transformational one? For Akshay Rao and Tom Henderson, it comes down to one thing: turning partner strategy into real field execution. In this episode of Hunters and Unicorns, Simon Kouttis and Ollie Kuehne sit down with the co-founders of a stealth startup and two of the most experienced leaders in partner and channel alliances, with experience at companies including Wiz, Zscaler, AppDynamics, and Skytap. They break down why companies struggle to capture their Partner Total Addressable Market (PTAM), why strategy often gets disconnected from execution, and how organizations can use partnerships to accelerate growth rather than simply generate sourced revenue. The conversation explores what a gold-standard partner strategy looks like, how to measure the true value of partner relationships, why focused partner ecosystems outperform “everything to everyone” approaches, and how field teams can turn individual deals into long-term partner momentum. In this episode: • The missing link between PTAM and field execution • Why partner strategy cannot live only on a PowerPoint deck • How to calculate the real value of a partner relationship • Why focused partner strategies outperform broad ecosystems • How deals can become “currency” for building partner momentum • The difference between sourcing revenue and accelerating TAM • How companies can unlock growth they couldn't achieve alone About Akshay Rao & Tom Henderson - Akshay Rao and Tom Henderson are veteran partner and channel executives who have worked together for more than 11 years across companies including Wiz, Zscaler, AppDynamics, and Skytap. They are now co-founders of a stealth startup focused on rethinking how companies build and execute transformational revenue through the channel ecosystem. Subscribe to Hunters and Unicorns for conversations with the leaders building, scaling, and transforming high-growth technology companies. #HuntersAndUnicorns #PartnerStrategy #ChannelSales #B2BSales #RevenueGrowth #GoToMarket #SalesLeadership #Partnerships #SaaS #techleadership Timestamps: 0:00 — Trailer 1:23 — Welcome & Introductions 3:06 — What Does Gold Standard Look Like? 5:20 — TAM & the Missing Link to Field Execution 8:18 — Opportunity Cost Across Company Sizes 9:28 — Strategy vs Execution — Where It Falls Apart 10:30 — How to Practically Identify Your Partner TAM 16:01 — Executive Sponsorship — The First Gate 20:40 — What Being Easy to Work With Actually Means 25:00 — Why Aren't More Reps Doing This? 31:50 — Multi-Party Attribution — The Real Problem 37:51 — How the Cisco Model Changed Partnering 42:27 — Can You Build Channel-First From Day One? 51:59 — Doomed at Every Size — The Core Frustration 1:00:12 — Why Would Anyone Work in Channel 1:02:20 — Why Tom Turned Down Jobs to Found Mobilize 1:05:30 — What Is Mobilize & How Does It Work 1:11:30 — Who Is Mobilize Built For & What's the Outcome 1:13:25 — Closing

In today's Cloud Wars Minute, I analyze the extraordinary RPO growth at Microsoft, Oracle, Google Cloud, and AWS and what it signals about AI demand. Highlights 00:03 — We've got another example here where, in the greatest growth market the world has ever known, we are working with some big numbers that put the law of big numbers to the test here. So, if you look at the four hyperscalers, and I go in order of the size of their backlog or RPO, you've got Microsoft, Oracle, Google Cloud, and AWS. 00:29 — So this is fully committed business. It's fully contracted and not yet recognized as revenue. So this is what's coming down the road, to look into the pipeline, in the future, these companies have — this isn't some guesstimate of what they hope they'll get. This is signed, contracted business. So this is one of the factors, probably the key factor, behind why you see these CapEx numbers approaching or exceeding $200 billion. 01:09 — Now that has led to a couple of these companies entering into the debt markets to try to fund this data center expansion and all that enormous CapEx outlay that they've got to go through. In turn, a couple of these companies for a quarter or two had negative cash flows, and that's got some people on Wall Street unable to comprehend it. The world's coming to an end. What are we going to do? 01:46 — I think the perspective is being switched here, right? Traditionally, the idea is bad. You don't want to have negative cash flow. Okay, that's pretty basic. I think we got that. The difference is there have never been a market with a size, a total addressable market , anything like this, growing at the rate this is. Look at these latest numbers for the four hyperscalers. 02:23 — Oracle, off a much smaller revenue base, has this huge future business coming in: $638 billion in RPO, growing at 363%. Google Cloud had a huge jump this past Q2, $514 billion in backlog, up 390%, and a resurgent AWS posted its biggest backlog number ever, $496 billion, and I believe that growth rate of 154% for its backlog is much higher than any they've reported over the last five or six quarters. 04:07 — So I think it's significant, but I also think it's being vastly overblown. I just want to say one more time: $2.3 trillion. Now, that's not like a TAM figure. Somebody's saying, "Oh, we think the market for new scooters is going to be $2.3 trillion." These are four companies, just four , not the whole tech industry, and these are their signed, contracted, committed figures for what they've got in their backlog or RPO. Visit Cloud Wars for more.

Episode One of an ADSN Original: 30 Minutes kicks off welcoming Harry Campbell, founder of Driverless Digest and one of the leading global experts on autonomous vehicles and mobility. He joins hosts James Borow and Daniel Druger to break down the state of the self-driving industry. Harry unpacks the Waymo vs. Tesla debate, explaining why Waymo has a massive safety and operational lead, but how Tesla's fleet scale could flip the script if they crack full autonomy. He walks through how LiDAR costs have plummeted upending Tesla's original camera-only thesis, and why Uber is facing an existential investor crisis as its Waymo partnership deteriorates and its stock underperforms.The conversation digs into regulation and the human cost of disruption, from taxi medallion collapses to the 110K Uber and Lyft drivers in New York City facing an uncertain future. Harry also breaks down the drone delivery boom in Texas, why near-zero delivery costs could create unlimited TAM, and what excites him most over the next 3-5 years as more AV companies enter the game. Whether you're a consumer, investor, or just someone who's been curious about getting into a Waymo, this is the episode to understand where autonomous vehicles actually stand today.Connect with Harry at:https://therideshareguy.com/https://www.thedriverlessdigest.com/Thank you to our sponsors:AdQuick – Making OOH advertising as easy to plan, buy, and measure as digital. adquick.comThrad.ai — Building the advertising infrastructure for AI. thrad.aibeehiiv — The all-in-one platform for newsletters, websites, and every tool you need to grow and earn. beehiiv.comThe Farm — Fraction commercial legal with an in-house approach to outside counsel. thefarmllp.comSTAY CONNECTEDJames on Twitter & LinkedIn – /jamesborowDaniel on LinkedIn, Instagram, TikTok – /danieldrugerSubscribe & leave a ⭐⭐⭐⭐⭐ review on Spotify & Apple Podcasts.

Grab the free Avatar Workbook, write your first draft down, then sharpen it with our Avatar Creator bot. And if everyone keeps telling you you're killing it, but your revenue hasn't moved in two months and you know there's more in you, book a discovery call and let's find out what's actually stalling it. Follow Geronimo Unfiltered: ⁠Spotify⁠ ⁠ Apple Podcasts⁠ ⁠ YouTube⁠ ⁠Instagram⁠ Ryan and I are taking over the pod to fix the biggest problem we see in studios: you think you know who you're for, and what you've actually got is a demographic. Every owner we meet swears they know their avatar. Then they say it out loud and it's "35 to 45 year old mums." That's a census field, not an avatar. And it's exactly why the ads feel like shouting into a crowded room of people who don't care, because if your avatar is everyone, it's no one. We ran this exercise as a live workshop this week and watched owners articulate who they're actually for, some for the first time ever. The messages were still coming in that night saying it finally clicked. So we're walking you through the same six steps we take every studio inside the academy through, in about the same 30 minutes we spend doing it with our clients. And here's the kicker: none of it has anything to do with what you do inside your gym. Pen and paper for this one, it's a writer downer. In this episode you'll hear: Why specific is not narrow, and how actively repelling the wrong people is what fills your studio with the right ones The six questions that uncover the fear your best members have never said out loud (the depth of your conversations determines the depth of your pockets) A live role play that starts at "I want more Pilates coaching" and ends at "I want to know I could protect my daughter," and why nobody buys your methodology The cheap-money trap: what uni student deals did to Doza's F45 (churn three times a year, and they crowded out the members he actually wanted) The one-line hook template that positions you as a category of one, plus the cover-your-logo test to check you've nailed it Loved this one? Binge this next: your message is only half the machine, so hear why ads flop even when the avatar is right in "⁠10x Your Leads in 2025: Why Your Ads Aren't Working (And What To Do Instead)⁠" And when you're ready to do this properly, this is the exact process we use to take owners from stuck at the same revenue two months running to their first 20k month, then 40, then beyond 100k, without burnout. ⁠Book your discovery call here⁠ CHAPTERS 00:00:00 You don't have an avatar, you have a demographic 00:04:59 Specific is not narrow (meet Stuck Sam) 00:07:53 Tony and Nat: the two avatars that built a million dollar gym 00:10:00 Step 1: Mine your best members (and the TAM check) 00:13:57 Step 2: Understand their pain, six questions deep 00:16:04 Sidebar: the uni student trap 00:19:53 Step 3: Give them a name 00:21:56 Step 4: From pain to promised land 00:24:41 Live role play: what she actually wants 00:27:10 Excuses and refusals (and how to weaponise them) 00:29:14 Step 5: Why here, not there 00:31:57 Step 6: Create the hook 00:33:26 The cover-your-logo test 00:36:12 Recap and your next move

Zeitgeist #33 s Tomášem Brolíkem o prvních 100 dnech vlády strany Tisza, nové hlavě státu a mezích moci ústavní většiny v Maďarsku. Moderuje Štěpán Sedláček.Maďarsku už přes tři měsíce vládné strana Tisza v čele s Peterem Magyarem, která má v maďarském parlamentu ústavní většinu. Premiér poměrně rychle mění pořádky, které v zemi 16 let budoval Viktor Orbán se svou stranou Fidesz. Mimo jiné zahájil přestavbu veřejnoprávních médií v nezávislé instituce a pomocí ústavních dodatků omezil funkční období politiků. U jednotlivých předsedů vlád na maximálně osm let ve funkci, což vylučuje návrát Orbána v roli premiéra. U poslanců pak jde o maximálně dvanáct let. Parlament také předčasně ukončil mandát prezidenta Tamáse Sulyoka a schválil vznik nového úřadu, který má prošetřit zneužívání veřejných prostředků a korupci. Na post hlavy státu Tisza posléze nominovala někdejšího předsedu nejvyššího soudu Andráse Baku.Viktor Orbán a jeho příznivci mnohé z těchto kroků vnímají jako útlak a tyranii. Sledujeme bourání a znovuzakládání maďarského státu, budování spravedlivější demokracie nebo jde především o střídání politických garnitur a boj o moc? Jaké první přešlapy udělal nový premiér? Rychlé politické změny v Maďarsku rozebírá v novém díle Zeitgeistu zástupce šéfredaktora týdeníku Respekt Tomáš Brolík se Štěpánem Sedláčkem.

Za dva měsíce vypuknou senátní a komunální volby. Andrej Babiš kandiduje v 25 ze 27 obvodů a má slušnou šanci se ve všech případech dostat do druhého kola. Jak tam uspěje?ANO pro tyto volby zvolilo strategii jít samo, bez dohod s vládními partnery z SPD a Motoristy, kteří nekandidují vůbec. Naopak sněmovní opozice zvolila cestu dohod. Příklad: ODS postaví 14 vlastních kandidátů, ve třech případech nominuje někoho společně s dalšími stranami a v deseti obvodech podpoří jiné opoziční kandidáty. Jaká strategie se ukáže účinnější?Andrej Babiš si může dovolit jít sám, protože sjednotil voličský tábor bývalé sociální demokracie a komunistů. Nejspíš spoléhá, že ho ve druhém kole podpoří vládní SPD, která postavila svého kandidáta v 21 obvodech. Uvidíme.Roztříštěná opozice zase musí kooperovat navzájem. Nakonec může rozhodnout faktor, který byl důležitý v nedávných sněmovních volbách. Stručně řečeno, zjeví se dlouholetí nevoliči, které něco zvedne ze židlí a přiměje jít k volbám?Podobné to bude v komunálních volbách. Podle některých politologů je český volič natolik zkušený, že už nevolí značku, ale vybírá si jednotlivé kandidáty. Existuje jedna výjimka v podobě hnutí ANO. Tam je tvrdé jádro hodně velké a prostě se volí Babiš, i když jsou na kandidátkách jednak úplně jiní, ale zároveň neznámí lidé. Je to tak – pro skalní voliče ANO je hlasování pro Babiše věcí až náboženské víry.Bude to fungovat i tentokrát? A připomínají Babišova nedělní videa černou magii?

OPEN HEAVENSMATALA LE LAGI MO LE ASO LUA 11 AOKUSO 2026(tusia e Pastor EA Adeboye) Manatu Autu: O mea e tuu iai e fausia mea e maua mai ai 1 (Inputs determine outputs 1) Tauloto Tusi Paia: 1 Korinito 9:24 “Tou te lē iloa ‘ea, o ē tausiniō i le ala tanu, e tausiniō uma i latou, ‘ae maua le taui e le to‘atasi? ‘Ia fa‘apea ‘ona ‘outou tausiniō, ‘ina ‘ia ‘outou maua.”Faitauga - Tusi Paia: Faataoto 31:1-9O le mamao e te fia ausia i lau faigamalaga i le olaga nei, o le tele foi lena o le manaomia ona e galueaina lelei lou tagata. Mo se faataitaiga, afai e te fia malaga i se mea mamao ao loo tumu lelei le pinisini o le taavale, e te ono tu i se pamu i le ala e toe utu ina ia e ausia le nofoaga mamao o loo e malaga iai. Peitai, afai e latalata le nofoaga o loo e malaga atu iai, e te lē manaomia le tu i se pamu e toe utu le taavale. O soo se tagata e naunau e mamao le tulaga e ausia i le olaga nei, e tatau ona galueaina punaoa mo ia, e aofia ai le ola faapaiaina, galue punouai, aoaoga, lelei fesootaiga ma tagata i lona olaga, alo ese mai amio lē lelei o le ai ai soo, matamata tifaga, faaalu vale taimi i luga o upega tafailagi, pati faasoloatoa ma mea faapena. E manaomia le pulea lelei o lau amio ma lou tagata pe afai e mamao le tulaga e te fia ausia. Ou te manatua ao ou laitiiti, e faanofo lava a'u e lou tina i totonu o le fale e fai meaaoga ao taaalo soka au uo i fafo. E masani ona ou faasea i lou tina peitai na faaauau ona ia faia seia oo ina matua ma avea ma masani ia te au le faia o meaaoga. E iai se taimi na ou alu i le fale o le tuagane a lou tinā, o fai se solo tele o faafiafiaga i le auala, na o uma ai tagata o le matou aiga sei vagana a'u. Na sau seisi ma fesili mai pe aisea ou te le alu ai i fafo e matamata i faafiafiaga, na ou tali atu, ‘o le tagata o le a matamata uma ai tagata i le lumanai e lē matamata i ni faafiafiaga'. I le tele o tausaga mulimuli ane, ina ua siitia a'u e le Atua, na ia faamanatu mai ia te a'u lea aso, ma faapea mai, ‘o le asō, o loo matamata uma mai le lalolagi ia te oe'. Le au pele e, faaalu au tupe ma punaoa e galueaina lou tagata i mea uma e manaomia i le mamao ma le maualuga o le olaga e te fia ausia. Ao agai isi tagata na ave i le tafeaga i Papelonia e aai i meaai matagofie i le maota o le tupu, na taulai le vaai a Tanielu ma ana uo ia vavaeseina i latou mo le Alii (Tanielu 1:3-12). Ou te talitonu e lē na o i latou tagata Iutaia na aoaoina i le maota o le tupu i lea taimi, peitai e na o i latou na faia mea tetele aua foi na faaalu tatau a punaoa e galueaina i latou. Atalii poo le afafine o le Atua, afai e tetele ni au miti o iai ma o loo e naunau ia tino mai, e tatau ona e totogiina le tau e galueaina lou tagata. E tatau foi ona e tuuesea ni avega mamafa e pei o le paiē, leai o se pulea o lou tagata, ma tulaga eleelea e pei o le agasala e taofia oe mai le ausia o faamoemoega a le Atua mo lou olaga. Ou te tatalo ia e ausia faamoemoega a le Atua mo lou olaga, i le suafa o Iesu. Tatalo, Tamā, faamolemole fesoasoani mai ia te au ina ia galueaina punaoa talafeagai mo lo'u olaga ina ia ou ausia faamoemoega ua e saunia mo au, i le suafa o Iesu, Amene. 

Türkçe biliyoruz, konuşuyoruz, yazıyoruz… ama her zaman doğru mu?

Argentina wanted a tank, some Germans wanted some money moved out of Switzerland, the TAM was born. A Marder hull, a 105mm gun, a lightish modular family of vehices it all looked good. And yet it failed to get to the fight the one time it mattered.

Peter Martin questions the lack of leaders on the pitch in the Scottish Premiership. Tam McManus believes Hibs fans are waiting for an excuse to call for David Gray's head at Hibs. Gordon Parks reckons Falkirk might have a battle to stay up this season. Predictions, arguments and Tam's hair dominate the show!

Is the tech industry moving too quickly, or are founders letting fear of AI labs stunt their ambitions? Sarah and Elad explore the current landscape of artificial intelligence, venture capital, and startup dynamics. They discuss the realities of building multi-trillion-dollar companies, shifting market sizes and outcome-based pricing models, and how founders are reacting to the rise of major AI labs. They also talk about what the framework for startup exits should look like, the potential for researcher burnouts in the next eighteen months as ASI looms on the horizon, bottlenecks for compute, and the impact of regulatory capture and shifting ecosystems from California to Texas. Apply for Embed - Conviction's Catalyst for AI-Native Startups Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Chapters: 00:00 – Cold Open Trailer 00:31 – Episode Introduction 01:44 – The Next Trillion-Dollar Company 03:12 – Tech Waves as Punctuated Equilibria  04:42 – TAM vs. Revenue Reality 07:14 – Market Size vs. Speed 10:32 – When Founders Should Sell 14:04 – Financing and Time Cost 17:57 – RSI and the Looming Promise of ASI 21:49 – Compute Power Laws 28:12 – Regulations and Disruption 33:06 – Beyond Transformers 34:26 – Tradeoffs - Safety vs. Progress 39:11 – Conclusion

OPEN HEAVENSMATALA LE LAGI MO LE ASO FARAILE 7 AOKUSO 2026(tusia e Pastor EA Adeboye) Manatu Autu: Tatalo mo lou pitonuu ma tuaoi (Prayers for your neighbourhood) Tauloto Tusi Paia: Roma 12:16 “Ia gatasitasi o ‘outou manatu; ‘aua le manatu i mea silisili, a ‘ia feoa‘i ma ē ‘ua fa‘amaulalo; ‘aua le fa‘afiapopoto.”Faitauga - Tusi Paia: Salamo 133:1-3TataloLe Alii e, ou te faafetai ia te oe mo lo matou pito nuu. Faafetai mo lau puipuiga ma le alofa mutimutivale ia te a'u ma ou tuaoi. Tamā, faamolemole puipui lo matou pitonuu i lou filemu. Faataga i matou ia matou nonofo filemu e aunoa ma le fefe poo faanoanoaga, i le suafa o Iesu. Lo matou Tamā, faamolemole ia iai galuega e faatupuina le tamaoaiga i lou pitonuu i le suafa o Iesu. Le Alii e,  faamolemole ia siomia lo matou pitonuu i  lou mamalu. Aua nei faatagaina ni faamai poo galuega amioleaga e faia i lo matou pitonuu, i le suafa o Iesu.Tamā, faamolemole, faamanuia i o matou tuaoi i lou filemu, olioli ma le soifua maloloina lelei. Ia tofo tagata uma o lou pitonuu i lou agalelei, i le suafa o Iesu. Tamā, faamanuia ma foai i o matou taitai le poto e faia ai faaiuga tonu e manuia ai lo matou pitonuu, i le suafa o Iesu. Le Alii e, ou te folafola atu, e leai se faalavelave faalenatura poo se faalavelave e faatupuina e tagata e tupu i lo matou nuu, i le suafa o Iesu. Faamolemole ia matou malu i lalo o ataata o ou apaau i taimi uma, i le suafa o Iesu.Le Alii e, faamolemole taitaiina mai tagata uma e lei faaolaina i lo matou pitonuu ina ia latou lafoai o latou ola ia te oe. Ia faataga i latou e maua lau faaolataga i le suafa o Iesu. Tamā, faamolemole auina atu le fesoasoani i e vaivai pe mativa i soo se itu i lo'u pitonuu. Ia latou tofo ma maua lau tausiga matautia, i le suafa o Iesu. Tamā faamolemole, faataga lou alofa e nofo tupu i lo matou pitonuu. Fesoasoani mai iai ia matou maua le loto gatasitasi ma ia alofa le tasi i leisi, i le suafa o Iesu. Tamā, faamolemole ia e talepe le malosi o le fili o loo taotaomia talavou i lo matou pitonuu. Ia nofotupu i o latou olaga lau amiotonu, i le suafa o Iesu. Tamā, ia e faamanuia i lo matou nuu, ia galue le mana o oe Agaga Paia i Ekalesia kerisiano uma i lo matou nuu e manumaloina agaga mo oe, i le suafa o Iesu e tatalo atu ai, Amene. 

In a world where 21,883 software companies are all chasing the same narrow pool of buyers, automation isn't a competitive edge — it's the noise. Neal Goyal, who has closed $41M in software revenue with 81% of it sourced from LinkedIn, makes a compelling case for slowing down to speed up. This episode breaks down why trust is the only moat that can't be replicated, how LinkedIn is actually a stage where your ideal buyers are sitting in the audience, and why the kindergarten rules you already know — give before you ask, show up for others first — are the most powerful GTM strategy available right now. If you're over-automating and under-relating, this one is a wake-up call.Key Takeaways[0:00] — The counterintuitive edge: doing things that don't scale is the most powerful thing you can do in a world where everyone has the same automation tools[6:09] — The ecommerce SaaS explosion: from 5,000 to 21,883 software companies chasing the same TAM — and why that kills trust by default[8:47] — You're not competing against direct mail competitors; you're competing for the finite bandwidth of a 3–5 person marketing team[13:33] — Why 100% inbound pipeline is a "cancer" — it feels great but attracts everyone, not the right ones[16:46] — 81% of $41M in closed revenue sourced from LinkedIn — what the first 8–9 months of posting with zero engagement actually looked like[18:48] — The theater analogy: your buyers are in the seats, but only 1 in 100 sellers ever gets on stage[21:15] — The lurker phenomenon: LinkedIn engagement is low because it's public and professional — and that's exactly why the relationship value is high[21:18] — Why your LinkedIn connect request is like asking for someone's phone number at a bar — and what to do instead[26:37] — The bank account model: you can't make a withdrawal from an account you never opened. Deposits (engagement, value) must come before asks (connection requests, pitches)[32:47] — Email as a trust eroder by default — and why "who sent it" matters infinitely more than any subject line[34:45] — "Relationships beat algorithms" — why building rapport on LinkedIn before hitting the inbox changes the open rate entirely[36:46] — How to get organizational buy-in for a long-game strategy: lead from the front, be the best BDR on your own team[40:38] — What to do when your target prospect isn't posting on LinkedIn: write about them, spotlight their work, and watch what happens[44:09] — The founder question almost nobody is asking: where is your moat beyond technology? Care at scale is the answerTweetable Quotes"Automation takes away the most valuable skills we learned in kindergarten — give to others before you ask for anything in return." — Neal Goyal"Trust doesn't scale. That's exactly why it works." — Jeff Mains"You're not competing against direct mail companies. You're competing for the limited bandwidth of a 3-person marketing team alongside 21,000 other software vendors." — Neal Goyal"Nobody remembers who liked their post. They remember who left a comment that showed you actually read it." — Jeff Mains"Every cold pitch you send is a withdrawal from an account you never opened." — Jeff Mains"Only 1 in 100 sellers posts on LinkedIn — but your buyers are there 7, 8, 9 times a day. That IS the stage." — Neal Goyal"If you post 3 times a week, you move to the top 1% of content creators on LinkedIn. That's how low the bar is — and how big the opportunity is." — Neal Goyal"Care is going to be the thing that stands out above everything we talk about with AI. If you can demonstrate it, you're going to win." — Neal GoyalSaaS Leadership Lessons1. Do the things that don't scale — on purpose. When everyone has access to the same AI tools, the same sequences, and the same targeting data, doing what everyone else is doing makes you invisible. Genuine human attention is rare enough that when a prospect receives it, it stops them cold. That's your competitive edge.2. Trust is the only moat automation can't replicate. With the software landscape growing 4–5x in a few years and churn becoming a top threat, the relationship you build before the sale is what keeps the customer after it. The companies that invest in their customers the way they invest in prospects will win the retention wars ahead.3. LinkedIn is a stage, not a social app — and almost no one is using it that way. Your buyers are on LinkedIn every day. Only 1 in 100 sellers posts. If you post three times a week, you're in the top 1% of creators on a billion-person platform. Stop thinking about it as a channel and start thinking about it as the most accessible stage you'll ever have.4. Deposits before withdrawals — always. The bank account model isn't a metaphor, it's a system. Comment authentically on your prospects' posts before sending a connection request. Connect before pitching. Build before asking. This sequence flips connect acceptance rates by 3–5x and transforms cold email into warm email.5. Lead from the front to change a team's culture. Philosophy alone doesn't move teams. Results do. When Neal steps into a new org, he operates like an IC first — showing, not just telling. When the team sees the long game producing pipeline, they buy in. You can't coach trust-building from the sidelines.6. You're not competing against your category — you're competing for attention. Whether you're at seed stage or Series C, the real battle is for a limited-bandwidth buyer with 3–5 people on their team and 21,000 vendors in their inbox. The question isn't "are we better than our direct competitors?" It's "are we worth their attention right now, and are we earning it?"Guest Resourceshttps://www.linkedin.com/in/nealgoyal/Episode SponsorThe Futureproof Series - https://www.youtube.com/playlist?list=PLfkXKUPZ5xuOqMPR7_gzGybncTtavyR1NThe Captain's KeysSmall Fish, Big Pond – https://smallfishbigpond.com/ Use the promo code ‘SaaSFuel'Champion Leadership Group – https://championleadership.com/https://jeffmains.com/books/SaaS Fuel ResourcesWebsite - https://championleadership.com/Jeff Mains on LinkedIn - https://www.linkedin.com/in/jeffkmains/Twitter - https://twitter.com/jeffkmainsFacebook - https://www.facebook.com/thesaasguy/Instagram - https://instagram.com/jeffkmains

The most petty and ill informed podcast in the world! Which expressions would you ban Stuart and Tam from saying this season? Sean McDonald reveals his Mastermind specialised chosen subject and we get live music from singer Cammy Barnes. All that plus Weekend's Football; Suits; Decent Proposals; Scottish Food XI and Terracing Teaser.

Tamara Steffens is managing director of Thomson Reuters Ventures, where she invests in early-stage companies building around legal, tax, accounting, and enterprise workflow. Corporate venture capital can look like a shortcut to customers, distribution, and credibility, but Steffens says founders need to understand what has to be true before strategic money can actually help. In this conversation, we get into what happens after Thomson Reuters Ventures joins your cap table, how founders can turn a corporate investor into real product or go-to-market leverage, and why inflated TAM slides can work against you. We also talk about what founders should do before and after the check clears, why some good businesses should avoid venture capital entirely, and why she says every founder should be thinking earlier about exit paths.   RUNTIME: 36:14 EPISODE BREAKDOWN (1:53)    An Overview of Thomson Reuters Ventures (3:57) CVC Expectations: When Strategic Capital Can Actually Help (7:09) Why Your TAM Needs to Match the Product You Actually Have (10:04) When Strategic Capital Becomes Product Leverage (13:13)  What Founders Should Do Before and After the Check Clears (22:18) How CVC Evaluates Founders When the Market Gets Frothy (29:05) Building the Relationship Before Series A (31:30) Why Exit Paths Matter Earlier Than You Think LINKS Tamara Steffens Thomson Reuters Ventures Thomson Reuters Fund/Build/Scale Founder Narrative Advisory SUBSCRIBE

ACIM Quote:I am not the victim of the world I see. (ACIM, W-31)Today's Guest:Rachel Meixner joins Tam and Matt to discuss forgiveness lessons in close relationships, including with an ex-husband, a church group, and her parents.You Can Find Rachel's Books Here: https://www.amazon.com/stores/Rachel-Meixner/author/B0H59K6CXVWant to Support Miracle Voices with a Donation?Visit, https://www.miralcevoices.org/donateThink your Forgiveness Story Could Inspire Others?Submit your forgiveness story here: https://www.miraclevoices.org/form

Wednesday - We talk; texting outside your relationship, voice text emojis, chicken wings, and more on Jim's soda addiction. Tam and Lucky the German Sheppard from Save A Life Pet Rescue are in for Animal House. Orlando Sentinel columnist Scott Maxwell on if it is okay to leave bagged dog poop in a neighbor's trash can. Plus, JCS News, JCS Trivia & You Heard it Here First.

Wednesday - We talk; texting outside your relationship, voice text emojis, chicken wings, and more on Jim's soda addiction. Tam and Lucky the German Sheppard from Save A Life Pet Rescue are in for Animal House. Orlando Sentinel columnist Scott Maxwell on if it is okay to leave bagged dog poop in a neighbor's trash can. Plus, JCS News, JCS Trivia & You Heard it Here First. See omnystudio.com/listener for privacy information.

The recent headlines about Dorit and PK spark a conversation about Housewives trying to prove how rich they are. Then, the Two T’s get into a debate about Brandi Glanville calling her sons boring. Plus, we dig into the comments after the RHOC scene between Tamra and Teddi… people are shocked seeing Tam like this!See omnystudio.com/listener for privacy information.

Gabriette and Matty Healy's wedding has officially set the tone for bridal fashion, and Tam and Lucinda are unpacking every single detail. From Gabriette's subversive Matières Fécales couture gowns to Mel C's secret Australian wedding in borrowed Victoria Beckham, the girls break down all the celebrity bridal news, plus the key 2026 wedding trends you’re about to see everywhere. Then, they'er unpacking what even is "Millennial Ache" and why is Gen Z suddenly obsessed with the early 2000s, offline era? They unpack Hailey Bieber’s sold-out Gap denim collab, Elle Ferguson’s collection, and why the ultimate millennial sneaker, the humble white plimsoll is making a massive comeback. Plus, Jonathan Saunders takes the helm at Kate Spade for a major brand revival. And stick around for Bougie to Budget, where Tam brings the cool utility cargo pants to replace your worn-out jeans, and Lucinda shares the sleek derby shoes you'll be wearing straight into spring. BOUJIE TO BUDGET: Tam's Pick: Cargo Pants Budget: Next Khaki Green Barrel Leg Cargo Trousers, $65. Midrange: BY DYLN Ella Pant in Hemp, $149. Boujie: Camila Coelho Gigi Pant in Olive Green, $378.59. Lucinda's Pick: Derby Shoes Budget: Zara Leather Derby Shoes in Brown, $105. Midrange: Charles & Keith Pippa Leather Derby Flats in Chalk, $149. Boujie: W Concept Heenn Folded Dirby Shoes In White, $250. GET YOUR FASHION FIX: Watch us on YouTube here. Follow us on Instagram & TikTok: @nothingtowearpod Shop the Pod: Sign up to the Nothing To Wear Newsletter to see all the products mentioned plus more, delivered straight to your inbox after every episode. Feedback? We're listening! Email us at podcast@mamamia.com.au CREDITS: Hosts: Lucinda Pikkat & Tamara Holland Producer: Talissa Bazaz, Ella Maitland & Zara Sengstock Audio Producer: Scott Stronach Video Producer: Michael Kean Just so you know—some of the product links in these notes are affiliate links, which means we might earn a small commission if you buy through them. It doesn’t cost you anything extra, and it helps support the show. Happy shopping! Mamamia acknowledges the traditional owners of the land on which we have recorded this podcast.Become a Mamamia subscriber: https://www.mamamia.com.au/subscribeSee omnystudio.com/listener for privacy information.

Leadership Series from a sailing boat with Dr Hynd and Prof Tamas David-Barrett BAL Leadership Series Leadership Series with Dr Hynd and Prof Tamas David-Barrett Episode 107 . We are delighted to announce the next session of our Leadership Series, featuring a distinguished guest: Prof. Tamás Dávid-Barrett (University of Oxford). . Prof. Dávid-Barrett will be presenting insights from his book Gender Species, which explores how gender norms emerge and evolve across cultures. His research provides a fresh, cross-disciplinary perspective on one of the most important conversations of our time: how gender shapes, and is shaped by, societies worldwide. . Bringing together expertise from economics, network science, anthropology, and biology, Prof. Dávid-Barrett is also the CEO and Chief Strategist of Future Human Systems Research (FHSR Global), a pioneering firm studying how artificial intelligence will reshape global economies and human systems. His career bridges both macroeconomic research and evolutionary science, spanning more than forty countries, and his academic journey includes appointments at Oxford, École des Ponts Business School (Paris), Universidad del Desarrollo (Chile), and the Kiel Institute for the World Economy (Germany). He is also a Fellow of the Royal Anthropological Institute. As a thought leader, Prof. Dávid-Barrett engages business leaders, investors, policy makers, and scientists on the long-arc forces transforming societies, economies, and cooperation in the age of AI. ✨ This session promises to be a thought-provoking exploration of gender, culture, and the future of human systems. get your copy of the book: https://www.amazon.com/Gendered-Speci...   meet Prof Tamas David-Barrett:   / tamasdb     #sailing #boat #genderequality #leadership #humanscience #economicgrowth #humanbehavior #oxford #trinitycollege

AGENDA: 00:00 – Apple SUES OpenAI: Did They Steal Apple's Biggest Secrets? 05:10 – Is OpenAI's $6BN Hardware Bet Already Dead? 12:50 – Zuckerberg Is Back: Meta Finally Takes On OpenAI 18:05 – The AI Spending Bubble Nobody Is Talking About 23:45 – Claude Is Coming for Designers, Product Managers & Figma 27:15 – Anthropic's $50BN Explosion: Have We Already Hit AI's TAM? 36:00 – The $26BN AI IPO Powering the Entire Industry 40:00 – Seed Investing Is Dead? Jason Calacanis Changes Strategy 57:00 – SaaS Is in Trouble: AI Is Accelerating Terminal Decay 01:15:00 – Why Greylock Said No to Billions of Extra Dollars  

BM's (IBM) worst day in 58 years—is it a buying opportunity? Plus, Fed Chair Warsh's testimony… The odds of a rate hike dropped significantly… Two AI buys… The perfect backdrop for big banks… And Wrap's (WRAP) growing TAM. In this episode: The Rule Symposium was great—with one catch [2:40] Key takeaways from Day 1 of Fed Chair Warsh's testimony [8:34] Why the odds of a rate hike dropped significantly [16:08] IBM just had its worst day in 58 years. Is it a buying opportunity? [20:39] These two power plays are buys on the AI pullback [26:27] The greatest environment ever for big banks [29:34] Wrap's total addressable market just grew by 3x [41:13] Everything included in our new all-in-one investing hub, Curzio Alpha [51:31] Today's episode is brought to you by Savvy, the smarter way to book a vacation rental. Travelers save an average of $400 versus Airbnb and VRBO. Your unforgettable family vacation is waiting—and thanks to Savvy, you'll get the rental you want, at the prices you deserve! Savvy.com: Stay smarter. https://www.savvy.com/wsu Did you like this episode? Get more Wall Street Unplugged FREE each week in your inbox. Sign up here: https://curzio.me/syn_wsu Find Wall Street Unplugged podcast… --Curzio Research App: https://curzio.me/syn_app --iTunes: https://curzio.me/syn_wsu_i --Stitcher: https://curzio.me/syn_wsu_s --Website: https://curzio.me/syn_wsu_cat Follow Frank… X: https://curzio.me/syn_twt Facebook: https://curzio.me/syn_fb LinkedIn: https://curzio.me/syn_li

(0:00) Bestie intros: Brad Gerstner fills in for Friedberg! (2:58) OpenAI vs Anthropic IPOs: Why it matters who goes first, what they learned from the SpaceX IPO, the unlimited TAM of intelligence (27:39) The open source decision, Meta's new model, Zuck's price war, AI duopoly (54:29) CCP considering putting export controls on Chinese models, is open source ending in China? (1:03:09) Trump Accounts launch, getting young Americans bought back into capitalism Apply for Summit 2026: https://allin.com/events Follow Brad: ttps://x.com/altcap Follow the besties: https://x.com/chamath https://x.com/Jason https://x.com/DavidSacks https://x.com/friedberg Follow on X: https://x.com/theallinpod Follow on Instagram: https://www.instagram.com/theallinpod Follow on TikTok: https://www.tiktok.com/@theallinpod Follow on LinkedIn: https://www.linkedin.com/company/allinpod Intro Music Credit: https://rb.gy/tppkzl https://x.com/yung_spielburg Intro Video Credit: https://x.com/TheZachEffect Referenced in the show: https://polymarket.com/event/ipos-before-2027 https://x.com/thejessezhang/status/2074154325933424861 https://x.com/praveenTweets/status/2074605343439810922 https://x.com/nikesharora/status/2074802778074124434 https://x.com/nikesharora/status/2074814752174522857 https://x.com/brian_armstrong/status/2070670644577280109 https://x.com/andyfang/status/2074252174226493584 https://x.com/nikesharora/status/2074630732019036574 https://x.com/finkd/status/2075218444056707458 https://x.com/alighodsi/status/2074996561306955958 https://blog.nicolasmeridjen.com/en/blog/2026-04-03-alibaba-qwen-closed-source-end-of-open-weight https://www.chinatalk.media/p/chinas-ai-companies-are-going-closed https://www.reuters.com/world/beijing-is-looking-curbing-overseas-access-chinas-top-ai-models-sources-say-2026-07-07 https://x.com/KurtSupeCPA/thread/2074817292550984010

Bozoma Saint John takes her new job as red carpet correspondent very seriously and takes the one and only Tamra Judge to task for things she has said about Boz over the past few months. In true Tam fashion, she fights back. After all, she ain't one of the longest running housewives for nothin'. Vicki Gunvalson slams the entire Housewives franchise as “broken”, says she never got closure from Brooks and reveals the new plan for her love tank. West cheats on Amanda and Amanda responds. Last, but not least, a few suggestions on how to fix the broken Valley.  @behindvelvetrope @davidyontef BONUS & AD FREE EPISODES Available at - www.patreon.com/behindthevelvetrope  BROUGHT TO YOU BY: QUINCE - quince.com/velvetrope (Get Free Shipping and 365 Day Returns to As You Indulge In Affordable Luxury)  MYFITNESSPAL - podcasts.myfitnesspal.com (Use Code VELVET, All Upper Case Letters, For 15% Off The Premium App That Will Change Everything For You Regarding Fitness & Nutrition)  ZENNI OPTICAL -  zenni.com/podcast (Use Code Podcast15 For 15% Off Your First Order Of The Most Affordable, Stylish Glasses and Sunglasses) ADVERTISING INQUIRIES - Please contact David@advertising-execs.com MERCH Available at - https://www.teepublic.com/stores/behind-the-velvet-rope?ref_id=13198 Learn more about your ad choices. Visit megaphone.fm/adchoices