Podcasts about HP

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The Pope's first encyclical about the importance of human dignity and the threat posed by A.I. is causing a stir. Some secular journalists are celebrating Leo's moral clarity, while Trump administration officials are saying the Pope should stay in his lane. Historian Yuval Noah Harari has his own warning about A.I. and explains how we are moving from an "attention economy" into an "intimacy economy." With the launch of Holy Post Media on Substack, Kaitlyn and Skye take you behind the paywall to sample everything offered by Holy Post Plus, including a daily devotional for people who hate devotionals. Also this week, a dog in Nebraska stands his ground.   Holy Post Plus: Ad-Free Version of this Episode: https://holypost.substack.com/p/723-pope-leo-ai-and-the-intimacy   Getting Schooled - Matchmaking 201: https://holypost.substack.com/p/getting-schooled-matchmaking-201   0:00 - Show Starts   1:49 - Theme Song   2:12 - Sponsor - Poncho - If you've been looking for the perfect shirt—something breathable, fits great, feels even better, and stands out in a good way—give Poncho a try. Get $10 off and free shipping your first order by using this link: https://www.ponchooutdoors.com/holypost   3:23 -  Sponsor - Sundays Dog Food - Get 40% off your first order of Sundays. Go to https://www.SundaysForDogs.com/HOLYPOST or use code HOLYPOST at checkout.   4:28 - With God Daily is Here!   8:27 - Dog Shoots Woman!   10:55 - The Pope's Encyclical on A.I.   24:50 - How A.I. Hacks Brains   34:21 - Sponsor - Feeding America - Feeding America, led by neighbors! Give now to end hunger at https://www.feedingamerica.org   34:55 - Sponsor - World Relief - Multiply your impact today! Start your monthly partnership with World Relief to walk alongside refugees and others on the move. Give today at http://worldrelief.org/holypost   36:00 - Sponsor - BetterHelp - This episode is sponsored by BetterHelp. Give online therapy a try at https://www.betterhelp.com/HOLYPOST and get 10% off your first month!   37:05 - Narcissism and A.I.   53:07 - Tour of HP+   56:28 - With God Daily   1:03:46 - My Hill to Die On   1:11:34 - Getting Schooled   1:18:37 - 66 Verses   1:26:25 - Advice-ish   1:33:58 - End Credits   Links Mentioned in News Segment: Dog Shoots Woman at 7-Eleven! https://www.theguardian.com/us-news/2026/may/26/dog-shotgun-nebraska-convenience-store   Slate on the Pope's A.I. Encyclical: https://slate.com/technology/2026/05/artificial-intelligence-pope-leo-encyclical.html   Other Resources:   Holy Post website: https://www.holypost.com/   Holy Post Plus: www.holypost.com/plus   Holy Post Patreon: https://www.patreon.com/holypost   Holy Post Merch Store: https://www.holypost.com/shop   The Holy Post is supported by our listeners. We may earn affiliate commissions through links listed here. As an Amazon Associate, we earn from qualifying purchases.  

New Wave Of Phishing Emails with SVG Files https://isc.sans.edu/diary/New%20Wave%20Of%20Phishing%20Emails%20with%20SVG%20Files/33040 Android 2026-06-01 security patch level vulnerability details https://source.android.com/docs/security/bulletin/2026/2026-06-01 Poly Voice Possible Remote Control of Certain Poly Devices CVE-2026-0826 https://support.hp.com/us-en/document/ish_15052661-15052687-16/hpsbpy04083 https://www.rapid7.com/blog/post/ve-cve-2026-0826-critical-unauthenticated-stack-buffer-overflow-hp-poly-vvx-trio-voip-phones-fixed/ Security Advisory Ivanti Neurons for ITSM (CVE-2026-9614) https://hub.ivanti.com/s/article/Security-Advisory-Ivanti-Neurons-for-ITSM-CVE-2026-9614?language=en_US My Upcoming Classes https://www.sans.org/profiles/dr-johannes-ullrich

Every playbook, every case study, every innovation workshop is built on the same question: how do you succeed? You map the path forward. You model the upside. Nobody teaches you to ask the harder question. How would you guarantee this fails? That's inversion thinking. Charlie Munger called it one of the most useful tools he had, and he used it for sixty years. Most innovators know the quote. Almost none of them actually use it. By the end of this episode, you'll know why that gap exists, what it costs, and the exact steps to close it. If you want to try this on a real decision right away, I've built a free tool for it. Link below. I'll come back to it later in the episode. What Is Inversion Thinking? Inversion thinking is the practice of reasoning backward from failure. Instead of starting with "what does success look like and how do I get there," you start with "what would guarantee this fails" and design those conditions out of the plan. You'll also hear it called thinking backwards, and when it's aimed at a project before launch, a pre-mortem. Munger's rule was three words: invert, always invert. Or, in his blunter version, "All I want to know is where I'm going to die, so I'll never go there." People hear this and think pessimism. It isn't. A pessimist names the failure and stops there. Inversion names the failure and uses it to redirect the plan, while the fix is still cheap. HP Invented the Category. Then Gave It Away. In 2005, HP built Halo. It was the best telepresence system in the world. You walked into a Halo room and the people on the other end looked like they were sitting across the table from you. Life-sized. Perfect audio. Nobody had built anything close. The team that made it was brilliant, and they believed one thing without question: quality wins. They built rooms that cost $500,000 each. They required customers to run those rooms on HP's proprietary network at a monthly cost that would make your eyes water. Every decision traced back to the same conviction. Make the experience extraordinary, and the market will come to you. Nobody in that room asked the one question that mattered. What if quality isn't what the market is buying? Because it wasn't. The market was buying access. Cisco, and then Zoom, came at the same opportunity from the opposite end. Good-enough quality, on any device, on any network, available to everyone. They understood what the Halo team never tested. In communications, reach beats quality. Every new user makes the service more valuable to everyone already on it, so the product that spreads to the most people wins, even when it looks worse. That network effect beat Halo so completely that Zoom became a verb. HP defined the category and then gave it away. In 2011, under quarterly pressure, HP sold Halo to Polycom for $89 million. In 2022, HP bought the business back, folded into Poly, for $3.3 billion. Thirty-seven times the price, to reacquire a category it had invented. The failure was visible the entire time. It lived inside one assumption nobody questioned: that quality was what the customer cared about most. An inversion exercise would have dragged it into the open. Ask "how do we guarantee Halo fails," and one honest answer was already the plan. Bet everything on quality. Price it for the few. Lock it to our own network. Leave the rest of the market wide open for a cheaper rival. No crystal ball required. Read the plan from the other side and the failure was sitting right there in it. The Three Moves Inversion runs in three moves. The first two are mechanical. The third is where the discipline lives, and where most people quit. Move One: Invert the Question Take the goal and flip it. Write your goal as one sentence. The way you'd say it to the board. "We will win the telepresence market with the best experience available." Turn it into a failure question. Same goal, opposite direction. "How would we guarantee we lose the telepresence market?" List every path to that failure. Don't rank them. Don't defend anything. Write down every way it could happen, including the ones that feel unlikely or embarrassing to say out loud. Price. Distribution. A competitor's move. A wrong read on the customer. Sort each one: recoverable, or not. A slow first year is recoverable. Letting a competitor own the network effect while you keep only the high end is not. The ones you can't undo are what matter here. Set the rest aside. Move Two: Find the Load-Bearing Assumption Behind every failure you can't recover from sits a single assumption holding the whole plan up. Find it. Take your most serious irreversible failure mode. The one from Move One that would actually end the project. Ask what would have to be true for that failure to never happen. For Halo: "Enough customers will pay a large premium for superior quality, and they'll do it fast enough to matter." That sentence is the load-bearing assumption. Ask whether you tested that assumption or inherited it. Did you confirm it with evidence, or did it ride along with the idea because it felt obviously true? The Halo team inherited theirs. Quality felt like an objective good, so nobody checked whether the market agreed. If you can't point to the evidence, you've found your real risk. A plan resting on an untested load-bearing assumption is a bet wearing the costume of a strategy, however solid the rest of it looks. Move Three: Decide What to Do With It Once the assumption is exposed, you have three honest choices. Kill it. If the assumption is false and the failure is irreversible, stop now, while stopping is still cheap. Change the plan so the failure mode disappears. The Halo team had room to do this. A software tier on any network, at lower quality, to build the user base and the network effect, with the premium rooms kept for the customers who'd pay for them. They'd have owned both ends. The plan allowed it. The conviction didn't. Proceed, with the bet named out loud. Sometimes you take the risk on purpose, eyes open, because the upside justifies it. That's legitimate. Taking the same risk by accident, because nobody said the word "assumption" in the room, is not. The one move you cannot make is to see the failure mode and proceed as though you hadn't. That isn't confidence. It's the most expensive form of hope there is. Why You Can't Do This Alone You know the three moves now. The hard part is running them on your own work. You can't fully see your own assumptions. You built the plan. You believe in it. The assumption holding it up feels so obvious that questioning it never occurs to you. The Halo team wasn't careless. They were the best in the world at what they did, and that was the problem. The more expert you are, the more your assumptions feel like facts, and the less it occurs to you to test them. Then there's the room. Even when someone can see the failure coming, the dynamics of a team work against saying it out loud. You earn standing by backing the plan, not by listing the ways it dies. Raise the failure scenario and you look like you lack conviction, or like you're not on board. So the failure half the room quietly senses stays unspoken until it's expensive. Culture rewards the loudest voice on the upside, not the person who turns out to be right about the risk. Two walls. You can't see your own assumptions, and the people who might see them are discouraged from speaking. AI has none of those problems. No ego in the plan, no career to protect, no boss to impress, no reason to soften the bad news to keep the room comfortable. Point it at your work, tell it to find the failure, and it will, without flinching and without politics. It won't make the call for you. It surfaces the failure modes you're too close to see, and then you do the judging. That's how you practice this skill on your own. You sit down with a real decision and a partner that has no reason to spare your feelings. So I built the AI Prompts for Inversion Thinking for exactly that. One prompt makes the AI write the post-mortem of your project before you've even started. Another has it play a competitor designing your defeat. Then one walks you to the single assumption your whole plan is betting on.  You bring the decision and the judgment. The prompts make sure nothing gets skipped just because it's uncomfortable to look at. Here's your work this week. Take one real decision you're sitting on, something with actual stakes, and run it through the pack. It's free at innovation.tools, or use the link in the description. The Long Game The people who use inversion well aren't more negative than their peers. They're more honest about which risks they can walk back and which ones they can't. That single distinction, made early and acted on, is the difference between a project that fails fast and cheap and one that fails slowly, expensively, in year ten. The failure that ends your project is usually the one plenty of people saw coming and nobody was willing to name. Say it now, while it still costs you nothing.

DAMIONCarnival Corporation's data breach exposed personal data of nearly 6 million customers: An April social engineering attack on an employee account compromised names, dates of birth, and government-issued ID numbers. WHO DO YOU BLAMESkills: Technology & Cybersecurity: Experience with information technology and cybersecurity matters is increasingly important to mitigate the risks our business faces, promote innovation and maintain a competitive edge in a rapidly evolving technological ageLeast represented 5/11CEO Josh WeinsteinNO: at Carnival since 2002, started as General CounselSir Johathon BandNO: First Sea Lord and Chief of Naval Staff, the most senior officer position in the British Navy (2006 to 2009, when he retired); Admiral and Commander-in-Chief Fleet (2002 to 2006); Served as a naval officer in increasing positions of authority (1967 to 2002)Jason CahillyNO: CEO Dragon Group LLC, provides capital and business management consulting and advisory services worldwide; The NBA: CFO & Chief Strategic Officer; Goldman Sachs: Partner; Global Co-Head of Media and Telecommunications; Head of Principal Investing for Technology, Media & TelecommunicationsNelda ConnorsNO: CEO/Chair Pine Grove Holdings, a privately held investment company; CEO Atkore International, manufacturer of electrical, safety and infrastructure solutions; VP Eaton Corporation, electrical and automotive supplierLaura WeilNO: Founder Village Lane Advisory LLC, specializes in providing executive and strategic consulting services to retailers COO New York & Company, women's apparel and accessories retailer; CEO Ashley Stewart, women's apparel retailer; CEO Urban Brands, apparel retailer; COO AnnTaylor Stores, women's apparel retailer; CFO American Eagle Outfitters, apparel retailerAudit Committee: Oversee management's risk assessment processes to identify principal and emerging risks, including financial, IT, cybersecurity and non-HESS operational risksLaura Weil*: NOJason Cahilly: NOJeffrey Gearhart: NOWalmart Corporate Secretary and lawyerStuart Subotnick: NOCEO at Metromedia Company, wireless/communications, until 2010; Carnival director since 1987 Health, Environmental, Safety and Security Committee: Oversee management's processes to identify principal and emerging health, environmental, safety, security and sustainability-related risks, including those related to ship operations and cybersecurity, RAAS health, environmental, safety, security audits, IAG and external investigations into significant ship incidents, and health, environmental, safety, security-related hotline complaints, and assess the steps management has taken to minimize such risks.Sir Johathon Band*: NONelda Connors: NOHelen Deeble: NOFormer CEO P&O Ferries Division Holdings, shipping and logistics businessKatie Lahey: NOExecutive Chair Korn Ferry Australasia, leadership and talent firmMicky Arison (75%): Exec Chair and former CEO and 7% stockholderThe CEO Pay Ratio1,063:124 retail CEOs made as much in a day as their typical employee earned in a year — and a big one didn't. WHO DO YOU BLAMEThe separation of CEO and Chair: Hamilton E. James Chair/Ron Vachris MMNot uniqueOnly 50% of the board is men. WTF?uniqueOne share = one voteNot uniqueState of HQ = WashingtonAlso StarbucksState of Inc = WashingtonAlso StarbucksPledge of allegiance to stakeholdersCostco generally has: Higher wages; Better benefits; Lower turnover; Higher sales per employee.Industry-leading employee compensation AND Self-imposed low-margin pricing philosophyWalmart only low-margin pricingOther comps:Todd Vasos of Dollar General, Shane O'Kelly of AutoZone, Gerald Morgan of Texas Roadhouse, Jack Sinclair of Sprouts Farmers Market, William Stengel of Genuine Parts Company, Michael Creedon of Dollar Tree, Ronald Sargent of Kroger, Lauren Hobart of Dick's Sporting Goods, Joshua Kobza of Restaurant Brands Inc., Kecia Steelman of Ulta Beauty, Scott Boatwright of Chipotle, Ted Decker of Home Depot, Bob Eddy of BJ's Wholesale Club, Corie Barry of Best Buy, James Conroy of Ross Stores, Chris Turner and David Gibbs of Yum Brands, Chris Kempczinski of McDonald's, Marvin Ellison of Lowe's, Brian Cornell of Target, Ernie Herrman of TJX Companies, Doug McMillon of Walmart, Brian Niccol of Starbucks, Hal Lawton of Tractor Supply Co, Laura Alber of Williams-SonomaFigma Gets an Activist Investor. Exhibit A on Why Companies Don't Want to Go Public. Figma's first year as a public company hasn't gone well. Findell Capital Management said it needs to take steps to shed its unwarranted reputation as an artificial-intelligence “loser.” WHO DO YOU BLAME?Figma founder and CEO Dylan Field: Owns 10% of shares but 72% of voting power: Class B shares worth 15 votes per shareDylan owns 158 Class A Shares (or 0.00003556% of 444,278,887)And Chair$5B net worth$865M total summary compensation in 2025; $91M in 2024Nominating Agreement:Figma must nominate Dylan Field to be a director and include him in the proxy statementThe company must use its resources to back him up and actively convince other shareholders to vote for him In response to a question about how he was going to change the world, Dylan said he was going to build better software for drones.Bro fest sausage party2 of 9 directors are womenTop 5 NEOs all dudesPeter ThielForced Dylan to drop out of Brown for a dumb fellowshipVC Blowhardiness on the BoardVC dude John Lilly (Greylock): Lead Independent Director2nd longest tenure (2014)Member of the Audit Committee; Member of the Nominating Committee (only Lilly and Rimer)VC dude Andrew Reed (Sequoia)Director at debt-maker Klarna Group (also way down since IPO): down roughly 54% from its initial $40.00 IPO price, and down nearly 68% from its all-time highMember of the Compensation Committee (which modeled Dylan's pay package after Elon Musk)VC dude Danny Rimer (Index Ventures)Director since 2014B.A. in History and Literature from HarvardMember of the Compensation Committee (which modeled Dylan's pay package after Elon Musk)Member of the Nominating Committee (only Lilly and Rimer)Luis von AhnDuolingo co-founder and CEO2025: shared an internal email outlining Duolingo's new "AI-first" strategy where Duolingo would “gradually stop using contractors to do work that AI can handle”Stated that "AI is a better teacher than humans" and that the future role of teachers would be reduced to providing "childcare."Blamed the controversy on a "lack of context" in his original statements"AI-First" memo goes viral: $389; today $118MATTDanone, Starbucks shine in methane-reduction rankingDanone is the only company in the group aligned with the Global Methane Pledge, an initiative backed by 150 countries that targets a 30 percent reduction in global levels of the gas by 2030. The French multinational also leads the pack in progress toward its target, having come close to hitting it five years ahead of schedule.WHO DO YOU CREDIT?Chair of the CSR committee Lise Kingo (9% influence), one of three directors tagged as merit directorsmaster's degree in Responsibility & Business from the University of Bathbachelor degrees in Religions and Ancient Greek Artbachelor's degree in Marketing and Economicscertificate as International Director from INSEADEx Novo Nordisk environmental affairs, internal audit, compliance, human resources, communication, branding and sustainabilityHelped create the UN SDGs and the UN Global CompactSomehow only bats 559 on carbon intensity (career) and 415 for scope 1/2 (career)Also, using deference metrics, the ONLY DIRECTOR tagged as fully independentEmployee rep member of the CSR committee Bettina Theissig (5% influence) and the employees of DanoneThe committee charter mandates employees get a say: At least two thirds of the CSR Committee must be independent, as defined by the AFEP-MEDEF Code. At least one Director representing employees must be a member of the Committee.In France (Danone's domicile), the European Investment Bank found that French employees were the most aware of environmental issues - 82% of French employees said they were highly concerned about environmental issues, highest in EuropeLead Independent Director and chair of the Nom/comp committee who put together the comp plan, Valerie Chapoulaud-Floquet15% influence, second to the 18% influence CEO (democracy!!), got 99.16% shareholder approval in April (even as CEO got 89.73% approval and pay got 93.19% approval)20% of short-term pay and 30% of long-term pay is based on hitting sustainability targetsWhen you pay a CEO to do a thing, they are more likely to do a thingEx-CEO Emmanuel FaberOusted in 2021 by the board of directors and activist investors, he transformed Danone into an “enterprise a mission” (a French version of a B corp)Investors voted 99% in favor of the move and a year later ousted Faber, the board resigned, and the new board and CEO are basically moving back towards being environmental leaders because it paid offShort term share price laggedHe said in 2024 that nature is “at the core” of Danone, It took the stock 3 years from Faber's ousting to return to Faber levels - and in the meantime, they were sued for plastics and emissionsIsn't this HIS win?Current CEO Antoine de Saint-AffriqueBecause CEOGM Board Director Jonathan McNeill Stepping DownCEO of DVx Ventures. Ex COO at Lyft Inc. and ex president, Global Sales, Delivery and Service at Tesla, current director at Lululemon, GM director since 2022, on the Governance and Corporate Responsibility committee and Risk and Cybersecurity committee.We know that half of boards on average think someone on the board should be replaced - did the GM board not like McNeill?WHO/WHAT WOULD WE BLAME FOR PUSHING MCNEILL OUT?Outsider dude bro DRLet's be honest, McNeill worked at much more… modern?... companies than GMThe board is OLD SCHOOL - ex Northrop Grumman, ex Visa, ex Lazard, ex HP, ex eBay, ex Novartis, ex Walmart, other directorships at Goldman, Huntsman, P&G… these are professional, insular boardsMeanwhile, he's investing as a VC in AI, other auto/mobility startups, comes from boards that are bro founder lead (Tesla, Lyft) He's invested in AI, crypto, heavy tech, intertwined with VCs all overNot deferential enoughBarra is connected to 94% - THE ENTIRE - boardMcNeill has the highest network power on the board at $9tn, higher than even Mary Barra (who is super connected), but is NOT a power player in the board community of GM - the dominant board communities for GM are massive blue chip US companies, where McNeill has deeper connections in smaller IT/tech focused companiesHe doesn't need the pay, he gets nothing for the connections really, he has connection to Barra but his network is different - was he too independent?Pissed he doesn't have enough influence McNeill has the LOWEST influence on the GM board at 4%He's relatively new, younger, working as a VC where you have a lot of power of capital allocation“I don't need this shit” effect?Too many womenMcNeill's dvX ventures portfolio team is 6 dudes and 1 womendvX entire operations staff is two woman - guess what they do“Chief of Staff” (ie, HR)Executive Assistant (yes, listed on the team)Board is 2 women, 3 men (McNeill not on board)This one seems unlikely I guess?Too busy, meh, move onOne of dvX portfolio companies is curbee, with GM Ventures' Kurt Baumgarten on the board (and the dvX co-founder is founder of Curbee)McNeill on at least 3 of his portfolio boards or advisory committees, plus LULU and GM…

The AI trade keeps powering markets higher, but investors are facing a growing concentration problem as more of the S&P 500 becomes tied to artificial intelligence, semiconductors, cloud infrastructure, and the companies funding the buildout.Mike Armstrong and Paul Lane break down why AI-related stocks now make up an increasingly large share of the market, how strong earnings growth is being driven by both real profits and rising private AI valuations, and why companies like Alphabet, Amazon, Meta, Nvidia, Dell, HP, and even unexpected names are becoming more interconnected through the AI boom. They also discuss whether Nvidia's push to bring AI chips into PCs can revive the personal computer market, why young workers may be struggling for reasons beyond AI, and how YouTube-driven movies and McDonald's new growth strategy show changing consumer behavior across entertainment and fast food.

出演者：藤原鞠菜 配信ペース：隔週火曜日 番組時間：平均40分 ——————————————————————— ＜各テーマ紹介＞配信されるテーマは回によって異なります。 「ふつおた」･･･何でもありのお便りコーナー。投稿は毎日募集中！！！！！ 「歴史秘話ウィステリア」･･･サークル曲の裏話など。 「まりにゃのこれな～んだ？」･･･音当てクイズ。 「まりにゃのオススメ」･･･オススメ商品をご紹介。 「はじおと」･･･「音楽」×「初めて」に関して語るコーナー。 （初めて買ったCD、初めて心を動かされた音楽、初めてカラオケで歌った曲等。） 「これかた」･･･テーマを決めて語る割とフリーダムなコーナー。 （テーマや語ってみた投稿募集中。） 「答えて、まりにゃ」･･･まりにゃへの質問募集中。 「トレンドなう」･･･収録時に開いたTwitterのリアルタイムトレンドについてコメント。 「まりにゃのTOP5」･･･思いついたら勝手にランキング。 「まりにゃのドキドキ質問箱」…twitter投稿になります。（ https://peing.net/marinya_）  「みんなの答え合わせ」…twitterで出題するアンケートの結果報告。みんなに聞きたいこと募集中。 ——————————————————————— ——————————————————————— ■CD新作・出演告知など■ ★Wisteria Magic通販サイト「うぃすましょっぷ」★ wismashop.booth.pm/ 新作も旧作も全て送料込み！ ★イオシスショップ様にて一部旧作を委託販売中！★ www.iosysshop.com/SHOP/list.php?Search=wisteria ★しがないレコーズのyoutube「しがない5分ショー」に出演してます。 藤原鞠菜は木曜日担当です。 https://www.youtube.com/channel/UCA_FmkoMu24R_6o3m3_Ulqg —–　　—–　　—–　　—–　　—–　　—–　　—–　　—– —–　　—–　　—–　　—–　　—–　　—–　　—–　　—– ・の〜すとらいく様の18禁PCゲーム 「女装百合畑/Trap Yuri Garden」にて、主題歌「優雅にヒロイン宣言」を担当させて頂きました。 ・TinklePosition様の18禁PCゲーム 「お兄ちゃん、朝までずっとギュッてして！夜までもっとエッチして！」 にて女未こはくちゃん(三女)のED曲担当させて頂きました。 ・TinklePosition様の18禁PCゲーム 「お兄ちゃん、朝までずっとギュッてして!」 にて女未こはくちゃん(三女)のED曲を担当させて頂きました。 —–　　—–　　—–　　—–　　—–　　—–　　—–　　—– —–　　—–　　—–　　—–　　—–　　—–　　—–　　—– ——————————————————————— この番組は音楽サークルWisteria Magicがお届けする番組です。 藤原鞠菜やサークルの過去または最新の活動内容につきましては 以下をチェックしてくださると嬉しいです♪ ・藤原鞠菜のTwitter（ twitter.com/marinya_ ） ・藤原鞠菜のHP「ふじわらんど」（ fujimari.com/ ） ・磯村カイのTwitter（ twitter.com/isomurakai ） ・磯村カイのHP「TONAKAI soundworks」（ https://soundworks.tonakaii.com/ ） 藤原鞠菜への贈り物の宛先 〒107-0052 東京都港区赤坂4-9-25 新東洋赤坂ビル10F レイズイン　アカデミー気付　藤原鞠菜宛 VOICEVOX:ずんだもん VOICEVOX:四国めたん

En el Radar Empresarial de hoy destaca Hewlett Packard Enterprise, que registra una fuerte subida del 28% en las operaciones posteriores al cierre bursátil tras presentar unos resultados que han sorprendido positivamente al mercado. La compañía alcanzó un beneficio por acción de 79 centavos, el más elevado desde 2018 y muy por encima de los 53 centavos que esperaban los analistas. Además, la facturación total superó los 10.000 millones de dólares, una cifra que también rebasó las previsiones del consenso y que confirma la fortaleza de su negocio en un entorno marcado por la creciente demanda tecnológica. Uno de los aspectos más relevantes de estas cuentas ha sido el extraordinario comportamiento de su división vinculada a la inteligencia artificial. Los ingresos asociados a esta área superaron los 7.000 millones de dólares, representando cerca del 70% de la facturación global de la empresa. Dentro de este segmento sobresale especialmente el negocio de servidores, que aportó más de 5.000 millones de dólares. A ello se suma una sólida cartera de pedidos relacionados con soluciones de IA, valorada en 6.300 millones de dólares. La confianza de la compañía en la evolución de su actividad también se refleja en la mejora de sus previsiones de beneficio por acción, que pasan a situarse entre 3,35 y 3,45 dólares, frente al rango anterior de entre 2,30 y 2,50 dólares. La estrecha relación de Hewlett Packard Enterprise con organismos públicos y grandes clientes institucionales sigue siendo una de las claves de su crecimiento. Entre sus contratos más relevantes figura el acuerdo firmado en 2021 con la Agencia de Seguridad Nacional de Estados Unidos (NSA), con una duración de diez años y un valor estimado de 2.000 millones de dólares. Mediante este convenio, la compañía proporciona infraestructura de computación de alto rendimiento a través de GreenLake, una plataforma estratégica que constituye uno de los pilares fundamentales de su oferta tecnológica para empresas. Otro contrato destacado es el suscrito el año pasado con el Departamento de Defensa estadounidense, valorado en más de 900 millones de dólares, para ofrecer servicios en la nube destinados a centros de datos de una de sus organizaciones. La actual configuración de la compañía se remonta a 2015, cuando HP se dividió oficialmente en dos empresas independientes. Mientras HP conservó los negocios de ordenadores personales e impresoras, Hewlett Packard Enterprise asumió las actividades relacionadas con servidores, software corporativo e infraestructuras tecnológicas. La entonces consejera delegada, Meg Whitman, defendió la operación argumentando que la estructura del grupo se había vuelto demasiado grande y compleja para seguir operando de forma eficiente.

Carl Quintanilla, Jim Cramer and David Faber discussed the AI trade: Nvidia enters the PC space by unveiling a new N1X processor. The announcement gave a boost to shares of Microsoft, Dell, HP and Arm — while putting pressure on the stocks of Intel, AMD and Qualcomm. SoftBank CEO Masayoshi Son spoke to CNBC in Paris about the company's plan to invest more than $80 billion in data centers in France. At Stargate's data center in Michigan, David previewed his exclusive interviews with OpenAI CEO Sam Altman, Oracle CEO Clay Magouyrk and Related Digital Chairman Jeff Blau: Also in focus: Barry Diller's $18 billion bid to acquire MGM Resorts, Berkshire Hathaway buys Taylor Morrison for $6.8 billion, U.S.-Iran tensions weigh on stocks.   Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In episode 363 of The Real Jason Duncan Podcast, Tom LeNoble discusses how he built careers at Facebook, Walmart, HP, and Verizon — the jobs most people spend their whole lives chasing. And then his body started breaking down. More than once. Life-threatening. And in those hospital rooms, stripped of every title he had built his identity on, he found out the truth his business cards had been hiding for years: his value was never in what he did. Tom LeNoble has held leadership roles at Facebook, Walmart.com, Palm, and MCI. He's now CEO of the Academy for Coaching Excellence and a leadership coach at Santa Clara University's Miller Center for Global Impact. He survived multiple life-threatening illnesses and has lived with metastatic cancer for over fourteen years. He is the #1 bestselling author of My Life in Business Suits, Hospital Gowns, and High Heels — a memoir that traces everything we talk about in this conversation. Today, Tom sits down with Jason to expose one of the most invisible and dangerous golden cages a high performer can build: the belief that your worth lives in your title, your role, and how well you perform. Lose the role, and you lose yourself. Until you finally find out that was never true. This episode dives into: The moment Tom first suspected the business suit wasn't doing what he thought it was doing Growing up in humble beginnings — and how that wired him to chase titles as proof of worth The lie culture, family, and industry handed him — and how long he believed it before the truth hit What it actually felt like to be on a fast track at some of the biggest companies in the world — and why it still felt like something was missing Surviving life-threatening illness more than once — and why the first time wasn't enough to crack the cage open What happened in the gap between diagnoses — and what belief was strong enough to pull him back into the performance even after his body sounded the alarm The moment everything he thought he knew turned out to be wrong Why the most dangerous cage isn't built from failure — it's built from real results and genuine achievement What it looks like to coach senior executives who are deep inside the same cage he almost died inside — and why most of them are certain they're not Why title-identity is the hardest cage to call out to a high performer The truth on the other side: your value was never in what you did — it's in who you are, what you share, and how you serve others What he knows now that he wishes someone had told him twenty years ago — and why nobody did What he wants the world to know If you've ever used a title, a company name, or a role to answer the question "who are you?" — this episode is the one that finally names what that costs.

Are you looking to save time, make money, and start winning with less risk? Then head to https://www.ovtlyr.com.Learn more about OVTLYR: https://youtu.be/TUCbD5KovlcEverybody's been talking about AI replacing software companies.Meanwhile, software stocks have been quietly ripping higher.And that's exactly what we're diving into today.A few weeks ago, names like ServiceNow looked completely broken. People were dumping software stocks left and right, convinced AI was about to make them irrelevant. Then something changed. The selling stopped. The buyers stepped in. And suddenly some of these stocks started exploding higher.In this video, we're looking at the software sector comeback, where the biggest opportunities may still be hiding, and why money is rotating back into tech right now. We also break down fresh OVTLYR buy and sell signals on stocks like ServiceNow, SAP, Atlassian, Palantir, Super Micro Computer, IonQ, NVIDIA, Micron, Palo Alto Networks, Fortinet, HP, Intel, and more.✅ Why software stocks are suddenly leading the market✅ The buy signals showing up across tech✅ Stocks that may be getting too crowded✅ Key resistance levels traders should watch✅ Where the best risk-to-reward setups may be formingThe biggest money isn't made chasing headlines.It's made by spotting trends before everybody else notices them.Subscribe to OVTLYR for disciplined trading strategies that actually make sense.

Patrick Moorhead and Daniel Newman cover Daniel's acquisition of Enterprise Technology Research, IBM's historic $15 billion single-day commitment spanning quantum and open-source security, Anthropic's Claude Opus 4.8, and the heaviest single earnings night of the season featuring Dell, Marvell, Salesforce, Synopsys, Snowflake, HP, and Micron crossing $1 trillion in market cap. The handpicked topics for this week are: Anthropic Releases Claude Opus 4.8: Six Weeks After 4.7 Anthropic dropped Opus 4.8 just six weeks after 4.7, claiming it surpasses GPT-5.5 and Gemini 3.1 Pro on agentic coding, knowledge work, and computer use. Benchmark improvements across the board: agentic coding up from 64.3% to 69.2%, knowledge work from 1753 to 1890, agentic computer use from 82.8% to 83.4%. Three new features ship alongside it: Dynamic Workflows for multi-subagent orchestration inside Claude Code, Effort Control for managing token spend, and mid-task system messages via the API. Fast mode is now 2.5x faster and 3x cheaper. Pat's honest take: what it says on paper is good, particularly on tool triggering and citation precision, but he has lost significant trust in the company and is watching closely. (The Decode)   IBM Commits $10 Billion to Quantum: The Largest Single Quantum Bet in History IBM announced a $10 billion commitment over five years targeting a large-scale fault-tolerant quantum computer by 2029, landing the same day as the $5 billion Project Lightwell announcement for a single-day IBM strategic commitment of $15 billion. Pat has been calling 2029 to 2031 as the realistic commercial quantum window and calls this the strongest single corporate financial signal yet that the timeline is real. Daniel's framing: IBM wants to be the NVIDIA of quantum, and with a $10 billion commitment, it's sending a flare to the entire industry that pure-play quantum companies cannot compete at this balance sheet level. (The Decode)   IBM and Red Hat Launch Project Lightwell: $5B to Secure Open-Source Software IBM and Red Hat committed $5 billion and a global force of 20,000 engineers to secure open-source software for enterprises through frontier agentic AI, anchored by 11 of the largest US and Canadian banks including Bank of America, Goldman Sachs, JPMorgan Chase, Mastercard, and Visa. Pat's read: this is the productization answer to Anthropic Mythos. Mythos found the vulnerabilities. Lightwell is the industrial-scale patching and validation layer enterprises can actually buy on a subscription. Daniel adds that IBM is flexing its engineering talent base as a premium strategic asset, a direct counter to the narrative that AI replaces engineers. (The Decode)   Anthropic Project Glasswing: 23,000 Vulnerabilities Found Across 1,000 OSS Projects Anthropic's Claude Mythos scanned more than 1,000 widely deployed open-source projects and surfaced approximately 23,000 candidate vulnerabilities, with 1,094 confirmed as critical severity. The Cyber Verification Program now gates the strongest cyber-capable Claude variant behind vetted defenders only. While the tool creates real value, the surface of attack will likely grow as fast as any tool built to defend it. (The Decode)   Anthropic in Talks to Run Claude on Microsoft Maia 200 CNBC and The Information reported Microsoft is in active negotiations to supply Anthropic with its custom Maia 200 inference chip, which would make Anthropic the only frontier lab simultaneously running production workloads on four distinct silicon stacks: NVIDIA, AWS Trainium, Google TPU, and Microsoft Maia. Pat's context: Maia 200 delivers 30% better tokens per dollar than the latest Azure fleet per Satya Nadella, and this deal would be Maia's first major external deployment. Daniel's read: what can be built will be sold right now, and Anthropic chasing every available compute source is simply the structural reality of growing at 80x when you planned for 10x. (The Decode)   The Flip: Is AI CapEx Too Expensive to Earn Its Return? Pat takes the affirmative. With $725 billion in hyperscaler CapEx tracking for 2026, likely $1 trillion next year, memory has become the choke point making it even more expensive, and open-source models have closed enough of the quality gap for most enterprise tasks that the premium of frontier APIs is increasingly hard to justify. A recent Signal65 white paper shows on-prem payback at 18 months. Daniel's counter: Dell just booked $24 billion in AI orders in a single quarter. Agentforce crossed $1 billion ARR at 169% growth. NVIDIA guided to $91 billion. Only 20% of enterprises are using AI and only 2% of consumers. Both hosts admitted off the flip their notes looked nearly identical. (The Flip)   Micron Crosses $1 Trillion Market Cap Micron became the 12th US company ever to cross $1 trillion in market cap, surging 19% on May 26th as UBS raised its price target to $1,625, implying a $1.8 trillion market cap. Samsung's Q1 memory ASP jumped 146% year over year. DRAM spot prices spiked 55 to 60% quarter over quarter. Daniel has been pounding this call since sub-$100 and calls it a cycle elongated beyond anything seen in the 27 prior memory cycles, driven by HBM capacity reallocation away from consumer DRAM creating structural shortage. (Bulls and Bears)   Dell Technologies Q1 FY27: The Biggest Enterprise AI Infrastructure Print of 2026 Record $43.8 billion revenue, up 88% year over year, crushing the $35.7 billion consensus by $8 billion. AI-optimized servers at $16.1 billion, up 757% year over year. $24.4 billion in AI orders booked in a single quarter. FY27 AI server revenue guide raised from $50 billion to $60 billion. Non-GAAP EPS of $4.86 beat the $2.96 consensus by 64%. Stock up 18% after hours. Pat's framing: Dell was very clear about what they were going to do. Rack engineering, sales, and service. The basics. And they executed the basics at an extraordinary level while building a special relationship with NVIDIA who views Dell as a market maker for both enterprise and NeoCloud. Daniel's add: play nice and win. Michael Dell navigated the political landscape brilliantly and pulled the entire Dell brand along with him. (Bulls and Bears)   Marvell Technology Q1 FY27: Record Revenue, Data Center at 76% of Mix Record $2.418 billion revenue, up 28% year over year. Data center at $1.833 billion, up 27% year over year, now 76% of total revenue. Q2 guide of $2.7 billion at midpoint accelerates growth to 35% year over year. Operating cash flow a record $638.8 million. Daniel went on TV and said it's "written in the stars," arguing the market had misunderstood this one for too long by conflating its custom AI ASIC story with the full breadth of its connectivity and networking portfolio. Pat's closing: the shorts are eating it now and the custom AI ASIC versus merchant GPU debate is finally settling into the right answer, which is both in lockstep. (Bulls and Bears)   Salesforce Q1 FY27: Agentforce Crosses $1 Billion ARR Revenue $11.13 billion, up 13% year over year. Non-GAAP EPS of $3.88 crushed the $3.12 consensus by 24%. Agentforce ARR crossed $1 billion, up 169% year over year, with 28.6 trillion tokens processed, up 152% quarter over quarter. 50% of Agentforce bookings came from existing customers expanding. Daniel flagged the $25 billion accelerated buyback funded by new debt as an interesting signal worth watching. Pat's bottom line: it's not perfect, but certainly no "SaaSpocalypse" in those numbers. (Bulls and Bears)   Synopsys Q2 FY26: First Full Quarter With Ansys Integrated Revenue $2.276 billion, up 42% year over year, beating consensus. Non-GAAP EPS of $3.35 beat $3.15. FY26 guide raised to $9.665 billion midpoint. Daniel's framing: every chip runs through Synopsys tools, and the Ansys addition makes it the full-stack co-design platform Jensen Huang keeps talking about. Synopsys is not just the pick and shovel of current AI silicon. It is the pick and shovel of quantum, robotics, and space as well. (Bulls and Bears)   Snowflake Q1 FY27: Strongest Sequential Dollar Growth in Company History Product revenue $1.33 billion, up 34% year over year, the strongest sequential dollar growth in Snowflake history. Net revenue retention 126%. FY27 product revenue guide raised to $5.84 billion. Natoma acquisition announced for secure agentic enterprise connectivity. New $6 billion multi-year AWS commitment. Daniel's closing: proprietary unique data is the real moat of the agentic era, and that data has to live somewhere. It is going to go to platforms like Snowflake. (Bulls and Bears)   HP Inc. Q2 FY26: Eight Straight Quarters of Growth With AI PCs at 44% of Shipments Revenue $14.4 billion, up 9% year over year, the company marks its eighth consecutive quarter of top-line growth. Non-GAAP EPS of $0.86 beat the prior guide. Personal Systems at $10.2 billion, up 13%, with 30% operating profit growth. AI PCs jumped from 35% to 44% of shipments quarter over quarter, with HP guiding to 60 to 70% next fiscal year. FY26 EPS guide raised. Pat's note: they still need a permanent CEO, which would help investors sleep better at night. Daniel's add: the real explosive moment for device companies comes when AI moves to the edge and enterprises shift from expensive frontier model consumption to on-device inference. (Bulls and Bears)   Everpure Q1 FY27: Record Revenue, Rebrand Complete Record revenue of $1.1 billion, up 35% year over year. Product revenue $577 million, up 55%. Subscription ARR at $2 billion. FY27 guide raised to $4.41 to $4.51 billion. Pure Storage officially completed its rebrand to Everpure. Daniel's emerging thesis: the agentic era has focused enormous attention on memory and compute, but after the inference runs, the data has to sit somewhere. Storage has not seen its full inflection yet and Everpure is well positioned when that wave arrives. (Bulls and Bears)   The Decode Anthropic Releases Claude Opus 4.8 May 28  https://techcrunch.com/2026/05/28/anthropic-releases-opus-4-8-with-new-dynamic-workflow-tool/ IBM Commits $10B Over Five Years to Quantum Computing the Same Day as $5B Project Lightwell, Bringing IBM's One-Day AI https://www.barrons.com/articles/ibm-stock-quantum-computing-aafbb1eb IBM + Red Hat Announce Project Lightwell  https://newsroom.ibm.com/2026-05-28-ibm-and-red-hat-commit-5-billion-to-redefine-the-future-of-open-source-in-the-ai-era Anthropic Project Glasswing / Claude Mythos Finds 23,000 Potential Vulnerabilities Across 1,000+ Open-Source Projects https://www.securityweek.com/anthropic-mythos-detected-23000-potential-vulnerabilities-across-1000-oss-projects/ Anthropic Negotiating to Run Claude on Microsoft's Maia 200 AI Chips  https://www.cnbc.com/2026/05/21/anthropic-microsoft-maia-200-ai-chip.html OpenAI + Anthropic Walk Back the AI Jobs Apocalypse Ahead of IPOs https://finance.yahoo.com/sectors/technology/articles/ai-chiefs-walk-back-job-193605798.html https://x.com/RiskCentre/status/2059397756016611668 The Flip Is AI Capex Becoming Too Expensive to Earn Its Return — and Will the Result Be a Forced Shift to Open-Source and Smaller Use-Case-Specific Models, or a Continued $725B+ Hyperscaler Buildout That Vindicates the Capex on Productivity Gains? FOR:  The shift is to open-source + smaller use-case-specific models with better token economics, not away from AI https://x.com/danielnewmanUV/status/2059822712122400975 DeepSeek 75% permanent price cut + Anthropic Claude Code restriction reversal https://www.buildfastwithai.com/blogs/ai-news-today-may-26-2026 $190B Microsoft capex + $725B+ aggregate hyperscaler capex with no analog ROI yet  https://www.buildfastwithai.com/blogs/ai-news-today-may-26-2026   AGAINST:  Salesforce Agentforce ARR crossed $1B this quarter on 28.6T tokens processed  https://www.stocktitan.net/sec-filings/CRM/8-k-salesforce-inc-reports-material-event-3b8ead2852bb.html Lenovo +105% AI revenue, +84% Q4; Dell $43B AI backlog: the AI infrastructure flywheel is converting capex to revenue today https://investor.marvell.com/news-events/press-releases/detail/1023/marvell-technology-inc-reports-first-quarter-of-fiscal-year-2027-financial-results NVIDIA $91B Q2 guide + $1T Blackwell+Vera Rubin CY25-CY27 reaffirmed  https://www.cnbc.com/2026/05/20/were-raising-our-price-target-on-nvidia-after-another-knockout-quarter-and-guide-.html DeepSeek + Chinese price war is a Chinese export-controls story, not a US economic ceiling story https://www.cnbc.com/2026/05/21/anthropic-microsoft-maia-200-ai-chip.html   Bulls & Bears Micron (NASDAQ: MU) Crosses $1 TRILLION Market Cap for the First Time https://www.cnbc.com/2026/05/26/micron-stock-trillion-market-cap.html Dell Technologies Q1 FY27 ACTUALS  https://www.cnbc.com/2026/05/28/dell-q1-earnings-report-2027.html Marvell Technology Q1 FY27 ACTUALS https://investor.marvell.com/news-events/press-releases/detail/1023/marvell-technology-inc-reports-first-quarter-of-fiscal-year-2027-financial-results Salesforce CRM Q1 FY27 ACTUALS  https://investor.salesforce.com/financials/quarterly-results/ Synopsys SNPS Q2 FY26 ACTUALS https://investor.synopsys.com/events-and-presentations/events/event-details/2026/Q2-Fiscal-Year-2026-Earnings/default.aspx Snowflake SNOW Q1 FY27 ACTUALS  https://www.businesswire.com/news/home/20260527027931/en/Snowflake-Reports-Financial-Results-for-the-First-Quarter-of-Fiscal-2027 HP Inc. HPQ Q2 FY26 ACTUALS https://finance.yahoo.com/markets/stocks/articles/hp-q2-earnings-call-highlights-230459161.html Everpure (NYSE: P, formerly Pure Storage) Q1 FY27 ACTUALS  https://investor.salesforce.com/financials/quarterly-results/ Synopsys SNPS Q2 FY26 ACTUALS https://investor.synopsys.com/events-and-presentations/events/event-details/2026/Q2-Fiscal-Year-2026-Earnings/default.aspx Snowflake SNOW Q1 FY27 ACTUALS  https://www.businesswire.com/news/home/20260527027931/en/Snowflake-Reports-Financial-Results-for-the-First-Quarter-of-Fiscal-2027 HP Inc. HPQ Q2 FY26 ACTUALS  https://finance.yahoo.com/markets/stocks/articles/hp-q2-earnings-call-highlights-230459161.html Everpure (NYSE: P, formerly Pure Storage) Q1 FY27 ACTUALS https://www.prnewswire.com/news-releases/everpure-announces-first-quarter-fiscal-2027-financial-results-302783502.html

  Welcome to the Firearms Insider Gun & Gear Review Podcast episode 627. This episode is brought to you by Walker Defense, XS Sights, and Hi-Point. In this show we have a Premier LPVO review. We talk about the BullWark, Ripley, Magpuls LCP max, and an inexpensive RMSc red dot.    As you may know, we showcase guns, gear, and anything else you might be interested in. We do our best to evaluate products from an unbiased and honest perspective.   I'm Chad Wallace, host of the most dedicated firearms podcast around With me tonight are: Tony, Rusty, and Dave   Sponsor #1: Walker Defense Research   Walker Defense provides shooters with the finest, most innovative, quality, tactical accessories and firearm components around. From their NILE grip panels to their NERO muzzle brakes, no details are ever left behind. Only top quality materials are used in the manufacturing process. Together, all of this gives you some of the best firearm performance around. 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This is NOT legal advice, nor should it be considered as such. Viewer discretion is advised.   Main Topic is sponsored by: Hi-Point     Hi-Point firearms has been crafting American made firearms for over 30 years. If you are looking for your first firearm, or just want something fun for the range, Hi-Point has you covered with models including handguns, pistol caliber carbines, and AR15's. They even have a new suppressor line. Hi-Point firearms can be found at extremely affordable prices, making them available for anyone that wants to protect themselves and/or their families. Every Hi-Point also comes with a lifetime warranty and most of their products are 50 state legal. 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The answer is inside this episode of the No Outlet Podcast! The best part is that...it is a TRUE Story.! It has it all and could be a James Bond movie for sure. So take a listen, and hopefully you find the topic as interesting as we did !#spies, #HP, #autonomy, #search, #thetown, #consequence, #revolution, #crime, #whitecollar, #fraud, #value, #marketing, #2010s, #stickywicket

Melissa Levy (Advertising & Experiential Marketing Executive)Current Role: President of Sparks (a leading global brand experience and live events agency) Former Role: President and Chief Client Officer at Digitas North America Bio: Melissa Levy is a powerhouse executive in the advertising, digital, and experiential marketing industries. She began her career in finance and transitioned into e-commerce marketing during the dot-com era before finding her true calling in the agency world. Levy spent 15 years at the Publicis-owned digital agency Digitas, rising through the ranks to become the President and Chief Client Officer. During her tenure, she oversaw a team of hundreds across multiple U.S. offices, managing high-stakes accounts for Fortune 10 giants and major consumer brands like Microsoft, HP, and PayPal. In early 2026, she made a high-profile move to become the President of Sparks (a subsidiary of Freeman), where she now steers the agency's creative, strategy, and live-event production operations. A fierce advocate for diversity and leadership development, Levy is a founding member of the Boston chapter of Chief (a network for executive women) and serves on the board of directors for the AdClub. Her work has earned top industry accolades, including Cannes Lions, Effies, and the Ad Club's Women We Admire award.

Jason Zigelbaum is the solo founder behind Zigpoll—the zero-party data platform trusted by Sony, HP, Kraft Heinz, and Hallmark.  Zigpoll collected over 100 million survey responses and counting. Third-party cookies are going away. Ad platforms are losing signal. Brands that don't collect first-party data are flying blind. Zigpoll fixes that.  Zigpoll makes it dead simple to launch contextual surveys that ask the right questions, at the right time, in the right channel so brands can stop guessing and start knowing.  How brands use Zigpoll:  - Discover how customers found you with post-purchase surveys - Improve products with real customer feedback  - Boost sales with on-site CRO surveys - Recover lost sales with abandoned cart & exit intent surveys  - Segment audiences by demographics and psychographics for higher-ROI campaigns  What makes it easy:  - No code. Installs on Shopify in seconds  - Surveys in any language with built-in translation  - Conditional logic and follow-up questions that dig deeper  - Triggers for post-purchase, abandoned cart, fulfillment, exit intent  - Deliver via SMS, email, or on-site  - Pipes data directly into Klaviyo, ActiveCampaign, Gorgias & more In This Conversation We Discuss:  [00:00] Intro [02:31] Starting with what you already know  [04:35] Uncovering your business blind spots  [07:38] Lowering mental friction for your users  [09:06] Eliminating the guesswork from strategies  [11:07] Callouts [11:07] Catching errors with your users' feedback  [13:35] Segmenting buyers to understand habits  [17:24] Using AI as a powerful force multiplier [22:21] Testing concepts without real users  Resources: Subscribe to Honest Ecommerce on Youtube Survey & feedback platform.zigpoll.com/ Follow Jason Zigelbaum LinkedIn linkedin.com/in/jason-zigelbaum If you're enjoying the show, we'd love it if you left Honest Ecommerce a review on Apple Podcasts. It makes a huge impact on the success of the podcast, and we love reading every one of your reviews!

出演者： miko、quim 配信ペース： 隔週 番組時間：89分10秒 ♯本番組はリモート収録です。 ♯収録時環境の影響により、全体的に聴き取り辛くなっております。 　申し訳ございません。 隔週に1回お届け。mikoラジ、第398回です。 労働は害悪でおなじみの我さん。 今週もハードでデスで笑いが悪い意味で止まらない模様。 しがないさんも驚きの隈……。 チーム我等の明日はどうなる?! 最後までごゆるりとお楽しみくださいませ。 ♯途中で色々とノイズ等入りますが、収録時のものです。 　ご安心ください、お手持ちの機器は正常です。 大変な絵 https://x.com/radio_4649/status/2059720447147843593?s=20 ・おとらってRECORD 公式サイト n-remix.com/otolatte/ ↑『おとらって10thライブ KUWANA』に参加予定の方は、 　「来場予約はこちらから」からご予約を！ 開催日／2026.8.23(日) 　第一部　OP11:30　ST12:00 　第二部　OP14:40　ST15:00 //////////////////// VOICEVOX:ずんだもん VOICEVOX:四国めたん //////////////////// -------------------- ●お便り募集中！ mikoラジでは以下の内容でお便りを募集中です！ ・ふつおた 　／普通のお便り、お待ちしています！ ・mikoは大変な絵を描いていきました 　／miko画伯に描いて欲しいお題をお待ちしています！ ・メシヲコエテ 　／料理人・mikoに教えて欲しいレシピをお待ちしています！ bit.ly/2GAWjyv 投稿フォームからラジオに投稿が出来ます！ コーナー名を選び、メッセージ・ラジオネーム・お所を入力して、 どんどん送ってください！　お待ちしています！！ ------------ 本ラジオのメインパーソナリティーである「チーム我等(miko/quim)」、 それぞれ以下個人サークルにて活動中です。 ・miko：miko ・quim：SHIGANAI RECORDS（ shiganai.com/ ） 活動詳細については、上記HPの他 各人のブログ/twitter等にて随時告知しておりますので、チェックしてみてください！ ・みころぐ。(mikoのブログ)（ ameblo.jp/miko-nyu/ ） ・@ mikonyu(mikoのtwitter)（ twitter.com/mikonyu ） ・@ quim(quimのtwitter)（ twitter.com/quim ） --- その他の活動については、以下のとおりです！ -- チーム我等がメインクルーとして活動していた「アルバトロシクス（ albatrosicks.com/ ）」、 これまでリリースしたCDは、イオシスショップ（ iosys.booth.pm/ ）にて頒布しております。ご興味ある方は是非！ ---------- ☆2026年5月IOSYSはいてない.comパワープレイ楽曲 M1. One Era feat. DD"ナカタ"Metal Produced by RoughSketch Vocal by DD"ナカタ"Metal 音楽ジャンル：Hardcore 収録アルバム：NBCD-052 20 Years Of RoughSketch: Golden Best & Remixes 2026 2026・4・26 Release https://notebookrecords.net/discographyportal.php?cdno=NBCD-052 積み重ねた『ジャパニーズ・ハードコア』を貴方に クリエイター「RoughSketch」の活動20周年を記念した2枚組アルバム。 書き下ろし新曲を含めたベストアルバムに加え、ディスク2には活動の中で出会った日本全国各地のトラックメイカーによるRemixが集結！ CD特典コンテンツとして2026年3月8日に行われた6時間ライブセットの音源をフルでダウンロード可能！

Investors parse a critical wave of software earnings and shifting market leadership. Adam Crisafulli of Vital Knowledge breaks down the market's latest theme and explains what strong software results could mean for the broader rally. Our Leslie Picker reports on Jamie Dimon's latest comments around succession planning and what they signal for Wall Street leadership. Salesforce, Snowflake, HP, Marvell and Synopsys all report earnings giving investors a fresh read on enterprise spending, AI demand and infrastructure growth. Brent Thill of Jefferies reacts to the software results and explains where the sector goes next. Plus, the sharp drop in Zscaler and what it says about cybersecurity stocks and investor expectations with Evercore's Peter Levine. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Ploopy is back with a bean-powered pointing device, Germany invests in KDE, Firefox gain 6 million new users, and taking a look at the DIY router from Banana Pi.The video version of the show is available to Patrons, along with the Extended Chaos podcast featuring over an extra hour of LWDW content every week.Patreon: ⁠⁠⁠⁠⁠⁠⁠⁠https://www.patreon.com/lwdw⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Discord: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://discord.gg/uQVckr5gEZ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Timestamps:00:00 Intro05:52 Steam Deck restock and new price 09:36 HP joins LVFS14:09 3D Movie Maker On Linux19:04 USB4 stream protocol 22:35 Rockchip-powered Flipper One TopicsMore LVFS Support :-Dhttps://itsfoss.com/news/hp-supports-lvfs/3D Movie Maker On Linuxhttps://benstoneonline.com/posts/porting-3d-movie-maker-to-linux/USB4STREAM (Mir_ppc)https://itsfoss.com/news/linux-usb4stream-protocol/Flippy Rocks https://www.collabora.com/news-and-blog/news-and-events/collabora-flipper-opening-up-the-rk3576.html

Timestamps: 0:00 Corsair's New Memory Supplier 1:14 HP's Broken BIOS Updates 2:09 California Age Verification Law Backlash 4:24 QUICK BITS INTRO 4:37 China's Underwater Data Center 5:12 TSMC Employee Bonuses 5:44 Rippable GameCube, Wii, and Xbox Games 6:12 Drone Speed Record 6:44 The Pope Weighs in on AI NEW SOURCES: https://lmg.gg/gZoBL Learn more about your ad choices. Visit megaphone.fm/adchoices

Book 7, Chapter 7: The Will of Albus Dumbledore

In this episode of Leader Generation, Tessa Burg talks with Tariq Hassan about what it really takes to modernize a business for the AI era. Drawing from leadership roles at agencies, Hewlett-Packard (HP), Petco and McDonald's, Tariq shares lessons from leading transformation at some of the world's biggest brands. They explore why success with AI is not chasing the newest tools. Instead, it starts with understanding the problem you're trying to solve, organizing your business around customer needs and using data in ways that build trust—not just transactions.  Leader Generation is hosted by Tessa Burg and brought to you by Mod Op. About Guest: Tariq is a transformational, global business leader whose career sits at the intersection of culture, sports, commerce, and technology. With more than 25 years of experience spanning Fortune 50 companies to fast growth startups across a wide range of categories. He's recognized for modernizing organizations through digital transformation and harnessing culture to drive relevance required to grow in a digital economy. Tariq has served as U.S. Chief Marketing and Customer Experience Office at McDonald's and Petco and has held global leadership roles at Bank of America and HP. Today, Tariq is Founder and CEO of Light21, an advisory firm helping startups and Fortune-scale companies modernize marketing through AI and data platforms to create digitally enabled customer ecosystems. He also serves as a Google CMO-in-Residence while advising emerging technology and sports ventures. He can be reached on LinkedIn.  About Tessa Burg: Tessa is the Chief Technology Officer at Mod Op and Host of the Leader Generation podcast. She has led both technology and marketing teams for 15+ years. Tessa initiated and now leads Mod Op's AI/ML Pilot Team, AI Council and Innovation Pipeline. She started her career in IT and development before following her love for data and strategy into digital marketing. Tessa has held roles on both the consulting and client sides of the business for domestic and international brands, including American Greetings, Amazon, Nestlé, Anlene, Moen and many more. Tessa can be reached on LinkedIn or at Tessa.Burg@ModOp.com.

Lyt med når vi i denne sæsonafslutning endevender filmen "Harry Potter & Halvblodsprinsen". Vi går i dybden med alt fra skuespillerne til filmteknik og produktion. Som altid drysser vi også ud af viden "behind the scenes", og giver et par fun facts undervejs. Som altid er dette en episode fuld af grin, nørderi og drys af HP-magi.

Take the 2026 AI Engineering Survey and get >$2k in credits and AIE WF tickets!On the product side, everyone is getting Computer - Perplexity, Manus, Cursor, and so on. Meanwhile on the research side, agentic evals like TerminalBench and GDPVal are also assuming computer (Harbor). On both ends, the consolidating LLM OS stack has become a standard toolkit, and Daytona is one of a small set of AI Infra companies that are booming because of it.“The end of localhost” has been Ivan Burazin's obsession for more than a decade.Something that is all too familiar…Long before agents became the default way people talked about software development, Ivan was already chasing the idea that development should not depend on a fragile local machine. CodeAnywhere, one of the first browser-based IDEs, was an early attempt at that future: move the development environment into the cloud, make setup reproducible, and free developers from the endless “works on my machine” tax.The thesis was directionally right, but the market wasn't ready yet.However, agents changed that. They do not care about a laptop, desk setup, or favorite editor. They need a computer they can access through an API: something stateful enough to keep working, fast enough to spin up instantly, flexible enough to resize, isolated enough to be safe, and composable enough to run the messy real-world workflows that real software engineering actually requires.Daytona isn't just selling “sandboxes” in the narrow code-execution sense. It is the latest version of Ivan's original localhost thesis.In this episode, Daytona's CEO joins swyx to explain why AI agents need more than code execution boxes: they need composable computers, stateful sandboxes, instant startup, dynamic resources, and infrastructure that can survive workloads going from zero to 100,000 CPUs.We go deep on the new agent compute market: Daytona's hard pivot from human dev environments to AI sandboxes, the New Year's Eve MVP that customers begged for, why Daytona runs on bare metal with its own scheduler, how one customer runs almost 850,000 sandboxes a day, and why RL/eval workloads went from 0% to roughly 50% of usage in just months. Ivan also explains why agents need Windows and macOS machines, why CLI may matter more than MCP, why Kubernetes is painful for this workload, and why the future AI cloud may look more like Stripe than AWS.We discuss:* How Daytona grew out of CodeAnywhere, Shift, and the “end of localhost” thesis* Why Daytona pivoted from human dev environments to AI sandboxes* Why agents need composable computers instead of disposable code execution boxes* The New Year's Eve MVP that customers chased API keys for* Why Daytona chose bare metal, stateful snapshots, and its own scheduler* How Daytona spins up one sandbox in ~60ms and 50,000 sandboxes in ~75 seconds* Why Daytona's biggest customer runs ~850,000 sandboxes a day* How RL/eval workloads create zero-to-100,000 CPU spikes* Why RL workloads went from 0% to roughly 50% of Daytona usage* Why customers compare Daytona against EKS/GKS and say they're “never going back”* Why every AI agent may need a computer, including Windows and macOS environments* The Apple licensing constraints that make macOS sandboxes hard* Why CLI gives agents more power than MCP* How open source helps agents integrate Daytona* Why agent-generated PRs may break today's CI/CD assumptions* Why AI SaaS companies reselling tokens may face a cold shower* Why the AI cloud may look more like Stripe than AWSIvan Burazin* LinkedIn: https://www.linkedin.com/in/ivanburazin* X: https://x.com/ivanburazinDaytona* Website: https://www.daytona.io* X: https://x.com/daytonaioTimestamps* 00:00:00 Hook* 00:01:12 Introduction* 00:03:15 CodeAnywhere, Shift, and the end of localhost* 00:05:58 What Daytona is: composable computers for AI agents* 00:08:07 The pivot from dev environments to AI sandboxes* 00:10:17 The New Year's Eve MVP and customers begging for API keys* 00:12:56 Bare metal, stateful sandboxes, and Daytona's scheduler* 00:17:28 60ms startup, 50,000 sandboxes, and 850K daily runs* 00:21:53 Spiky RL/eval workloads and the new agent infra problem* 00:28:12 RL workloads, Kubernetes pain, and dynamic resizing* 00:33:31 Why every AI agent needs a computer* 00:38:48 macOS sandboxes and Apple's licensing problem* 00:44:28 Why CLI may matter more than MCP* 00:48:11 Open source, GitHub stars, and agent integration* 00:53:11 Git, CI/CD, and agent collaboration bottlenecks* 00:58:15 Founder life and building a 25-person infra company* 01:02:44 AI SaaS, token resale, and API-first business models* 01:06:10 GPU sandboxes, data centers, and compute growth* 01:09:48 Why the AI cloud may look more like Stripe than AWS* 01:11:26 Closing thoughtsTranscriptIntroduction: Daytona, CodeAnywhere, and the End of LocalhostSwyx [00:00:02]: Okay, we're in the studio with Ivan Burazin, CEO of Daytona. Welcome.Ivan [00:00:07]: Thanks for having me, man.Swyx [00:00:08]: Ivan, you and I go back.Ivan [00:00:10]: Way back.Swyx [00:00:11]: How I don't even know how, you found, did you reach out or, for Shift.Ivan [00:00:17]: I reached out to you. The reason was you - we were just - we were thinking about I was one of the co-founders of CodeAnywhere, the first browser-based IDE, and so we were thinking a long time of, localhost should die. And you had this article.Swyx [00:00:29]: End of localhost.Ivan [00:00:30]: Then I reached out to you because of that, and then we talked, and I was actually at a different job and learning about I was the head of, developer experience, and you were quite well-versed in that, and I actually reached out to you, among other people, how do we go about that? What are the key things and whatnot at this point in time? And you were nice enough to take the call, and I remember I was late on your call with you.Swyx [00:00:51]: I don't remember.Ivan [00:00:52]: I remember because I was with my then I'm thinking of a girlfriend or wife at that point in time, I'm not sure. It's the same person, so that's great, and I was late ‘cause we were, in, Italy on, vacation, and then I was late for something. I felt so bad, and you were so nice to be, good about.Swyx [00:01:10]: The reason I'm nice is because I'm also late to other people, so it's like, who's, who's without sin here, yeah, so I have to, for those who don't know, InfoBip Shift, there's this whole thing that, you did in the past, and, and that was basically one of the inspirations for me starting AI Engineer, which is like, I have to thank you for giving me that push to be like, “Oh, you can, you can build and sell conferences?”Ivan [00:01:34]: I remember you asked you asked me at the beginning to give me advisory shares, and I was so focused on what we were doing, I said no, and I should've took the advisory shares. So I'm sorry, dude. But anyway.Swyx [00:01:43]: We're not, we're not venture backed.Ivan [00:01:44]: No, it doesn't matter.Swyx [00:01:45]: It's Yeah, anyway, so I think what's impressive about you is that CodeAnywhere is the thing that you've been trying to build, and, you kind of put it on hold and then came back after InfoBip. Just give us the story, do you - the story and the origin story, going into Daytona.From CodeAnywhere and Shift to DaytonaIvan [00:02:05]: Sure. Like, really way back, me and my co-founder have been together. I say this, I've said this multiple times, it's like we were married and divorced and married. Some people actually ask me is my co-founder my partner. they thought it literally. It's not literally, but we have done multiple companies together, and to your point, we had this shift where we went from the CodeAnywhere to the conference called Shift, and then back to, Daytona. We originally started stacking servers, doing like virtualization in the early 2000s and, routers and doing basically all these things, at a foundational level, and that was a services company which we sold to focus on what my co-founder actually invented, which was the very first browser-based IDE, right, I say the first. Before us was actually Heroku. They did it for a very short time until they became Heroku. But outside of them, we were the only one, and it was called.Swyx [00:02:55]: There was Cloud9.Ivan [00:02:57]: Cloud9 came out slightly after us. There was Replit, which came out when we stopped doing it, Replit came out, and they have been successful since then, which is great. There was Nitrous.io. There was quite a few that existed at the time, but it was like too early. But the interesting part is that we, at that point in time, because there was no VS Code, there was no Kubernetes, and Docker had just started when we Or I'm not sure if it was even public at that point in time. And so we had to build everything to the whole stack ourselves and that was the key learning that we brought into and that we've been using in Daytona today. So it was super early. There's about 3 million people used CodeAnywhere. It was slightly, it was angel-backed more than venture-backed. We ended up paying everyone back because it didn't have that sort of scale. But, three years ago, we started something similar with Daytona, which is not what we are today, but it was automating dev environments for human engineers, the basically the underlying stack of CodeAnywhere. And then we did a hard pivot last January to sandboxes. And so here we are.Swyx [00:04:01]: Historic pivot, yeah, and, it's one of those things where, I had independently invested in CodeAnywhere, but also in E2B, and then both of you pivoted into the same thing, and I'm like, “F**k.”Ivan [00:04:12]: You invested, you invested in Daytona. You invested in Daytona. But you were the first If we had not got your check, we wouldn't have done it.Swyx [00:04:18]: No way.Ivan [00:04:19]: No, it was like, “We have to get him on board first,” and you were that kicker that we, that got us off the ground.Swyx [00:04:23]: No, because you were putting me on your pitch deck, man. I was like, “Man, this is like a good trip if I don't invest.”Ivan [00:04:29]: That's because it was your quote. It's like we.Swyx [00:04:30]: Yeah. It's the end of localhost.Ivan [00:04:31]: Did a bunch of research about end of localhost and who was interested in that,.Swyx [00:04:34]: No, that's like, I put, I wrote that blog post, and every single company in that field reached out to me, and then every VC who was receiving those pitches then also had to call me and, talk it, talk through it with me.Ivan [00:04:47]: It's finally happening though.Swyx [00:04:48]: It was really super interesting.Ivan [00:04:48]: It's finally happening.Swyx [00:04:49]: It's finally happening.Ivan [00:04:49]: Yeah, it's finally.Swyx [00:04:49]: It's finally happening, with maybe sort of non-human users. Yeah, so what is Daytona today? Let's get like a quick description. I'm wearing the shirt.What Daytona Is Today: Composable Computers for AI AgentsIvan [00:04:58]: You're wearing the shirt. Yes,.Swyx [00:04:59]: It says, I think your branding is very good. Like, it's very consistent. It runs AI code. Like, it cannot be simpler.Ivan [00:05:05]: Exactly, but we're gonna probably have to change that.Swyx [00:05:07]: Oh, s**t.Ivan [00:05:07]: It's also a subset of what we do. Unfortunately, we really love this, Run AI Code is super simple. People interpret it different ways. I think we've given out 5,000, 6,000 of these shirts. People wear them with pride because it doesn't really market about us.Swyx [00:05:21]: Yeah, Daytona's on the back.Ivan [00:05:22]: It markets the back. It markets to the person itself, so I think we did a really good job on that one. But it is also a subset of what we do, because people, when they think about Run AI Code, they just think about these small, let's call it isolates, code execution boxes that, you send some code, you get an output. Whereas what Daytona is today is essentially composable computers for AI agents. It is, the market calls them sandboxes which can be misleading.Swyx [00:05:44]: All these things. All these things on.Ivan [00:05:45]: Yeah, exactly, ‘cause it can be misleading ‘cause people usually think about sandboxes as a demo or a test environment versus a production-grade environment. But what Daytona does, if you think of the laptop that you have in front of you or the computer that's over there, or, my wife is an architect, so she has like a Windows with a 3D graphics card inside to do 3D rendering. Like, as humans, we have different computers or different compositions of computers. And our belief is strongly that agents today and going forward will need all these different compositions of computers to do different types of tasks. And so we offer that basically through an API.Swyx [00:06:19]: Yeah, to give people - I'm trying to sort of front-load all the aha moments or the wow moments so that people can, stay engaged and click like and subscribe. the market is exploding, right? Like, you have been reporting 74% month-on-month growth, and it also, it's just been growing for a while. Like, it's been going like this. And every single - It's not just you guys. It's every single.Ivan [00:06:41]: Everyone, yeah.Swyx [00:06:42]: Sort of, compute provider. I don't know if you agree with me saying compute provider or not.Ivan [00:06:48]: It's fine.Swyx [00:06:48]: Yeah. So like organically PLG-driven growth, but also enterprise is doing super well, I think I wanna rewind to January of last year when you did the pivot. Like, so you obviously called this market early, and you were positioned for it, and you are now one of the market leaders. But what was the insight that made you do the pivot?The Pivot: From Human Dev Environments to Agent SandboxesIvan [00:07:06]: The insight that made us do this pivot is the quarter before that, so end of 2024, when we had - Basically, we did a demo with - I don't I think we discussed this as well, Devin was not public. You actually gave me access to Devin at that time. So Devin.Swyx [00:07:25]: I did?Ivan [00:07:26]: Yeah, you gave me access.Swyx [00:07:26]: I don't think I was supposed.Ivan [00:07:27]: Yeah, exactly.Swyx [00:07:28]: Yeah, I.Ivan [00:07:28]: So it doesn't matter. You.Swyx [00:07:29]: Yeah. I gave like three friends access.Ivan [00:07:31]: Yeah, or it was a call and you showed it to me. It doesn't matter. but OpenDevin was available, which is now called OpenHands. And so we're like, “Oh, this seems to be a thing. This is not public. Let's take our for human automation of dev environments and take, OpenDevin and launch that as a SaaS.” And we did that. Not very many people signed up and used it, but a lot of people reached out that were building agents, and they were like, “Hey, my agent needs a compute sandbox runtime,” whatever you wanna call it. I forgot what it was called at that point. And then we were like, “Oh, amazing. This is a new market. Here is our infrastructure. Here's our product, and go.” And what we found really fast, soon, was that people did not like what we had built. It didn't work. And I remember talking to people at the beginning when we're doing this, the sandbox we're building for agents. People were like, “Oh, why is it different? It's the same thing. We have like EC2, we have VMs, we have all these things.” But we saw that everyone we gave it to, it was like 20, 30 people, they all said, “No.” Like, “This is not what we need. This sort of breaks.” And basically, me and my co-founder not knowing a lot about - ‘cause we're infra people. We're not AI people. So I basically took it upon myself to like watch every single podcast that exists, including all of, all of these and all that, and sort of get up to date, read all the blogs, like get, understand what's going on.Swyx [00:08:45]: Do you wanna shout out who else was useful, just in case people are also looking.Ivan [00:08:49]: Generally we -, I looked at There's a few of podcast, different segments and different types. So there's you guys, No Priors, Bill Gurley's was great while.Swyx [00:09:04]: VG2, yeah.Ivan [00:09:05]: Yeah, while it was around. So there's a few. 20VC is interesting from a different dynamic, and some are different dynamic. But there was, also Red Points.Swyx [00:09:14]: We're not really about the compute market.Ivan [00:09:15]: It was also already - Sorry?Swyx [00:09:16]: You're, you want - You're looking at the agent infra market.Ivan [00:09:19]: I was looking at the agent market and the AI market in general and sort of understanding who are the players, what the perception, and how that goes. And like obviously you complement this with like going to conferences, going to events, going to meetups, reading white papers, like doing all the things that you have to do to understand what's happening. And so when we figured, when we sort of had an idea of what we had to build, literally over the New Year's Eve, literally on New Year's Eve, I half vibe coded the first MVP, first minimal viable product of what Daytona is today. And I went to sleep at like 3:00 AM or something like that. I was doing - I just put my like baby daughter and wife to sleep and, Happy New Year's, and go back to just, doing this. And I sent it to my co-founder, my CTO, and he saw it in the morning. He's like, “This is absolute garbage.” “Do not show this to anybody at all, but the idea is good.” And so he took two weeks, and he rebuilt it.Swyx [00:10:09]: Did it like look like that? Listen, I - It was rough idea.Ivan [00:10:12]: Oh, not even, not even close. Like it was it was way worse. But it was like a very - It was a simplistic view of what it should be. Like, it worked, but it was not ideal. And so he went, we went down the whole, which is his job as CTO, to go, and he came back with this version. We then called all the people that had said like, “This is garbage,” a quarter ago. And we set up these calls, and we gave it to - We just demoed it to everyone. And all the calls went long, every single one. They were 15-minute calls, and they all went to like 25, 30 minutes or whatnot. And everyone said, “We need, we want access.” There was no login, just an API key, ‘cause it was just a beta or an alpha. And they said, “Oh, we want access.” And we're like, “Sure, yeah. Okay, thank you very much.” But after like the next day, if we'd not send it, every single one, like every call that we did, everyone came back, “Where is my API key?” Like everyone wanted it. We're like, “S**t.” Like this is it. Like I've never felt So one, the understanding to your point was like most people thought it was the same infrastructure for humans and agents. We understood a quarter ago it's not. We just didn't know what was the right primitive. And then when we came, and we can talk about what that is, and we gave it to these people, I've never seen, I've never experienced - I've done multiple companies in my life. I've never experienced this, that people literally call you if you do not give them access. Like they want access right now. And so it's like, okay, they don't want this. the thing that they want doesn't seem to exist, or they have not found it, and they really want what we want. And then when we understood that we're onto something, and then when you think about the size of the market, like the market for human engineers and enterprise is a very large market, so think GitLab or whatnot. But the market for every single agent that will exist ever in the future is just like, what is that market? How big is that? And we're like, “We are all in on this.” And so that is where we made sort of the cut between the old product and the new one.Bare Metal, Stateful Sandboxes, and the Lambda + EC2 ModelSwyx [00:12:02]: Yeah. But it wasn't composable at the time?Ivan [00:12:05]: It was very - It was basically just a Linux box that you could change, that you could define number of CPUs, disk, and RAM. Like that is what you could do, but you couldn't have multiple operating systems, you couldn't resize it on the fly, you couldn't add a GPU, you couldn't do like all the things. It was just the, just the first sort of variation of that, yeah.Swyx [00:12:22]: Was it bare metal from the start?Ivan [00:12:24]: It was bare metal from the start. And so the interesting thing that we thought about right away, so our.Swyx [00:12:29]: Which, give people the background, what is the normal path?Ivan [00:12:32]: Yeah, so, basically most providers run this on top of VMs. And also.Swyx [00:12:37]: Firecracker.Ivan [00:12:38]: Yeah, they run on Firecracker and VM. And so we also fire - We can get - We have multiple isolation layers and we can do that. But the common way to do it is that they, one, that the state of the machine, or the hard disk is not part of the sandbox itself. And the other thing is they're not meant to last forever. So most of them are preemptible, like they can There's a time that they can live. And so our thought was when we were going into this is, agents will be like humans in the sense of you don't want your laptop to be shut down until you're done with work. Like, and you want to close the lid and open the lid, it's the same state. So you - Agents would want that, like the pause and come back. They want those two things. But also agents really want speed, right? Can they get it? So when we thought about it's like we need something insanely fast, how to make it fast, how to make it long-running, and stateful. And so those two things, it's like combining a Lambda and an EC2, right? Those two things together. And so we didn't have an idea how others did it, ‘cause we didn't know too that there was a market around this. It was more like, okay, this is what we need, what they need. And we looked at Kubernetes, it wasn't wasn't good enough for that. We looked at Nomad, it didn't enable that. And so our history in rewriting our own scheduler at CodeAnywhere is basically what my CTO came up with. Like, he's like, “Oh, the learnings from there,” and he brought it. And the funny thing is, our third co-founder, when he saw it, he's like, “Dude, what is this? This is like 2008.” Like, we went back in time, and he's like, “Exactly.” And so the reason why Daytona is like super fast, and you see this on benchmarks, is we essentially, we run on bare metal. We have our own scheduler, we use the underlying, disk, CPU, and RAM of the underlying machine, which means your IOPS are insanely fast because there's no, there's no network between an EBS or something like that. But also the snapshot, the point in time, the templates, are also preloaded on the bare metal machines. So when you fire off a sandbox from a template or a snapshot, you're essentially directed to the bare metal machine where that snapshot is based on that NVMe drive, and then it literally just turns on that machine, and it's local. There's no network latency, anything on there. And so that is sort of the specificities that we, when we're thinking from first principles, what a computer would look like for an agent, that is what we came up with, and that's what we created.Benchmarks, 60ms Startup, and 50,000 SandboxesSwyx [00:15:02]: Yeah. I should maybe, I don't know if you endorse this, but there's someone that does compute SDK, you guys do very well on there, with like the TTI, right? I. is this a, is this a is this a relevant benchmark for you guys? I don't know.Ivan [00:15:16]: I don't know, and it changes every day. So today RKL is.Swyx [00:15:18]: I don't know what RKL is. Never heard of it.Ivan [00:15:20]: Yeah. RK, yeah, so it is there.Swyx [00:15:22]: You are, at least a third of the next tier of performance, and then, there's a lot of other better-known names that are very slow to start.Ivan [00:15:31]: Yeah. We've been the number one by far for a long time, and now there's different, there's different definitions also of sandboxes, different isolation patterns, different other things. So RKL runs it literally on the S3, the data, so it's very different, and they spin up a sandbox, spin up a container for that, so it's a different type of thing. So the definition of a sandbox is something that we can all, we all need to get along with. But yeah, we're insanely fast on getting these things, up and running. And so you can see even there that it's a zero point 0.10 to 0.11, so.Swyx [00:16:03]: Close enough. Yeah. what else do you need, right?Ivan [00:16:05]: Yeah. So the benchmarks itself, so, in this, in I don't think the benchmarks equate to market ownership or revenue or anything like that. and I've seen this with multiple benchmarks, not just in sandboxes, but in general benchmarks around.Swyx [00:16:20]: It's table stakes. It's just like.Ivan [00:16:21]: Exactly. But it doesn't hurt.Swyx [00:16:22]: Just roughly check.Ivan [00:16:22]: Like you definitely have to be up there and you have to be competing so that people know that, oh, this is definitely one of the top. Because this is only one dimension of what customers look for. There's other things like how many can you spin up consecutively? There's a feature set, there's support, there's like all different things that people look at, but you definitely have to be there, on the benchmarks.Swyx [00:16:40]: How many people do people spin up consecutively?Ivan [00:16:43]: So we have.Swyx [00:16:43]: Or concurrently, is the Concurrency, right?Ivan [00:16:45]: There's three metrics that we look at. And so one is like time to spin up one, and so our time to spin up one is 60 milliseconds with network latency. So request, spin up, reply, 60, the whole thing, 60 milliseconds. That is one. But if you wanna spin up 50,000 at once, we are now at about 75 seconds. So it takes about 75 seconds to spin up concurrently 50,000. Some others, there's public data around this, like take 2,000 seconds, which is 30 minutes. Like there's different variations of that. And then there is the so it is speed of one, speed of like multiple, and then how many can you consistently have up and running. And so we basically have right now no limit to how much we can add because we basically own our own metal. But the biggest customer of ours does like about 850,000 every single day is sort of where they're, where they're just shy of a million every single day that they're running, we do have a request for half a million concurrent, which is literally half a million CPUs somewhere running. So that's an interesting.Swyx [00:17:44]: They pay by like vCPU seconds.Ivan [00:17:47]: By seconds, yeah.Swyx [00:17:47]: Or whatever. Yeah. Okay, and so and then, and the other thing is, the sleeping and the resuming, ‘cause it's all the stateful resumption of all these things, how, what kind of workload are people putting through this, right? Like how is it Do we measure by gigabytes in memory, gigabytes in storage? I don't In like network attached storage. I, what are the costly ones of, out of all these features?Workload Economics: CPU, RAM, Network, and StorageIvan [00:18:15]: The most expensive thing are CPU.Swyx [00:18:18]: Okay. Yeah, of course.Ivan [00:18:18]: The second one, yeah Then it's RAM, then it's disk. We actually don't charge.Swyx [00:18:22]: Which is snapshotting, right?Ivan [00:18:23]: No, it's actually the, snapshotting's part of it, but basically the size of your hard disk, of your machine. So do you have 10 gigabytes, do you have 20, do you have 50, do you have whatever? And then the transference of that. Right now, currently we don't charge for, network at all at Polychron.Swyx [00:18:37]: Oh, you gotta, yeah, you gotta fix.Ivan [00:18:38]: Yeah. It is very much a it's a larger and larger part of our bill, so we're working around, that part there. Obviously, that is the least, expensive, so the hard disk is the least expensive, so it's basically CPU, RAM, for us network, ‘cause we don't charge the customer, and then hard disk, is how it's split up. But there's also different types of workloads, so we basically split it up into two types of workloads in Daytona. One is what we call background agents or long-running agents. and the other is, basically RLs and evals, which I put sort of together. And so they have very different patterns of usage, and if you look at the usage of a background And I'll just name names of companies, not specifically.Background Agents vs. RL/Evals: Two Usage ShapesSwyx [00:19:21]: Yeah, open, all hands.Ivan [00:19:23]: Yeah. So like a background agent's a Cognition, a Lovable, a like all these things are Harvey. These are all long-running, background agents. And so if you look at their usage patterns, their usage patterns are similar to human, which is like follow the sun. Basically, the usage patterns of that is like noon is probably the highest, and the midnight is the lowest, and then weekends are lower. weekday is higher.Swyx [00:19:42]: Yeah, that's a fun question. How global is it? Is it very US-centric or?Ivan [00:19:46]: The US is a large part, but we have currently, we have Asia, Europe, and the US regions.Swyx [00:19:52]: So it's quite global.Ivan [00:19:53]: Yeah, it's quite global. We have it all over. It's interesting that our I talked to you a bit about this. Our number one city by user.Swyx [00:20:01]: Hmm.Ivan [00:20:02]: Is Singapore.Swyx [00:20:04]: Oh, wow. Amazing.Ivan [00:20:05]: Which is an interesting one, right? Not by revenue, just by just like by individual head count.Swyx [00:20:09]: Really?Ivan [00:20:09]: Just like an interesting thing.Swyx [00:20:10]: Singapore is, Singapore is weirdly high in the adoption charts of AI for the population. It's like an, seven, eight million population. And it's like keeps showing up.Ivan [00:20:20]: No, it's quite interesting. We were quite shocked, and I was like, “Oh, this is interesting.” And also one that's up there.Swyx [00:20:24]: There's a reason I'm doing AI using Singapore. it's because I'm from there.Ivan [00:20:27]: We're there. We're gonna, we're gonna be there as well. and it's interesting that Japan is in the top or like Tokyo's in the top, which is in all the tech cycles it has never been. It has never been, so it's quite interesting that they're.Swyx [00:20:39]: I think the Japanese just love AI. Yeah. It's that, and then it's Brazil. That's it.Ivan [00:20:44]: Brazil has always been in.Swyx [00:20:45]: I think.Ivan [00:20:46]: Even when I look, if you look at like GitHub's data and ask historically with CodeAnywhere, it was always like US, Western Europe, and then you'd have like India, Brazil, China, like that would be there. But like Singapore was not in, specifically Japan was never in sort of that top, that top.Swyx [00:21:01]: Yeah. Weird pockets.Ivan [00:21:01]: Weird. Yeah, so it's very global.Swyx [00:21:02]: Okay, so actually that, but that's helps you to distribute your load through, all time?Ivan [00:21:08]: The interesting thing is like we have those kind of loads, but if you look at the researcher loads, they're quite different. So what they are is like if you give them concurrency of 10,000 or 50,000 or 100,000 CPUs at ARMb, when they fire off a run, it's just 100%. And then it just runs, and then it stops. So it's very, the usage pattern is squares basically, right? And it's also not follow the sun, because people will fire it off at midnight before they go to sleep but then wake up and so it's very unpredictable, so you don't know where that is. So the shapes of the usage are quite different than we have had before. And also what's interesting is when it's sort of a follow the sun, even if you have a high growth company, you can sort of predict your usage patterns and have enough capacity for that, because it's sort of, it grows in a, in a way you can project. When you have companies doing sort of like evals and RL, they're super spiky. So they're gonna come in, it's like, “We're gonna use nothing, then can we have 100,000?” Right? And then go back down. And then 100,000, go back down. So it's very different, right? And.Swyx [00:22:09]: Do you want to lock them into commits so.Ivan [00:22:11]: Yeah, we do.Swyx [00:22:12]: Yeah, okay.Ivan [00:22:12]: We so we have to lock them into some sort of commits to have that capacity, because we have to have, basically we have to have the capacity for peak. Right? And so right now, Daytona's mean utilization is 15%, 1-5.Swyx [00:22:25]: Oh my God.Ivan [00:22:26]: So it's very low.Swyx [00:22:27]: Because it's very spiky.Ivan [00:22:27]: It's very spiky, but we get up to 90%. so we have these things. And so what we're, what we're looking at right now as a company is similar to Cloudflare where you can like geo move things around, but that works really well for basically the background agent where it's follow the sun. But this, it's not. Like it's a very different shape. Obviously with scale you figure these things out, but that's an interesting new problem that we have, as a compute provider in the agent space. And when we were doing the conference recently, and so we talked to like Nikita from Neon and.Swyx [00:22:57]: I should bring it up.Ivan [00:22:58]: Parag from Parallel and whatnot, everyone has the same problem. Whereas the usage is super spiky, and this is something that has not happened before, that you have these types of like it was always, it the amplitudes were not this high, right? So it's quite interesting use case and problem solve.Compute Conference and Spiky Agent InfrastructureSwyx [00:23:12]: Yeah, I don't know if we're gonna bring this up again, but let's just talk about the conference, you had like 1,000 something people at the Warriors game, at the Sorry, where is it? What's.Ivan [00:23:22]: Chase Center.Swyx [00:23:23]: Chase Center.Ivan [00:23:23]: Chase Center.Swyx [00:23:24]: I went. It was, it was very impressive. Obviously, you can, how to throw a conference, what did you learn? you put, you pulled together all these impressive names.Ivan [00:23:33]: What I.Swyx [00:23:34]: What were you looking for?Ivan [00:23:35]: My thesis behind the Compute Conference was let's bring together people that are building infrastructure for AI agents. Because when I think of what we're building, it is the agent is the primary user, what are the ergonomics and usage patterns of agents, and so we can do that. And what I found, this was a theory, it wasn't proven, is that we all have these problems, as I touched onto. And I was, as I was talking on stage, it was like we all have the same underlying infra problems, which is this spiky workloads, unpredictable workloads that we've never had before, in human, compute or human infrastructure. And it's, again, it's the same when I was talking to Parag or when I was talking.Swyx [00:24:20]: Lynn. Nikita.Ivan [00:24:21]: Lynn, Nikita. Lynn especially, I was talking to her the other day as well. Like the It is a very interesting type of problem to solve because I can touch on Cloudflare because there's a lot of like talk about that recently as to how they solve that, which is they have a bunch of geos, and basically, as users work in different places, and depending on your tier, they can move you around the geos. And so that how, that's how they get the higher utilization. But you can sort of predict these, and it's If it's something in You'll rarely get a spike that is 10 orders of magnitude. Like you'll get a like let's say one of your customers has some like an exponential curve. What is that to I'm using Cloudflare as an example. 10%, 20%, whatever it is. I don't, I don't have this data, I'm just assessing. It's surely not 10x, right? It's surely not something there. And so how do you go out and solve this problem? And we're all solving this in different ways. So we have.Swyx [00:25:11]: She also has the same thing.Ivan [00:25:12]: Yeah, I know specifically that like Neon had that issue as well. Like how are we solving these spiky loads and things like that ‘cause we talked about it. And so the interesting thing for me to actually internalize was, yes, everyone that's building for agents first is going through this, and we're all solving similar problems, which is quite.Swyx [00:25:28]: Let me let me double-click on this. Okay. So for example, Neon, I happen to know that they're very sort of S3 oriented, right? so they're just like fully bet on S3. And you get to benefit from S3's distribution and infrastructure. So I would imagine that Neon doesn't have to care, whereas Lynn maybe has to care a bit more because obviously she's doing GPU inference. And, for listeners, we did an episode with her, one and a half years ago. And you have to care. But like, right?Ivan [00:25:54]: Parag cares for sure, and Nikita.Swyx [00:25:58]: And Parag is C of, Parallel.Ivan [00:25:59]: Parallel, yeah.Swyx [00:26:00]: Former CTO of Twitter.Ivan [00:26:01]: Twitter, yeah.Swyx [00:26:02]: They are the search.Ivan [00:26:03]: Yeah, they're search, yeah.Swyx [00:26:03]: I You and I know but the listeners don't know.Ivan [00:26:08]: Yeah, we can put it down in the screen, and so ‘cause we, when we were talking.Swyx [00:26:11]: I'll put it up on the, on the screen.Ivan [00:26:12]: Yeah, right.Swyx [00:26:12]: People can look it up if they need.Ivan [00:26:14]: Look it up. And, yes, but they still have CPU and RAM, allocation that you have to have up and running. And so CPU and RAM, you have to allocate that and have that ready. And so there's basically two ways to do it. One is you either over-provision and you can handle the bursts, or two, you basically have, I don't know if this is a term, just-in-time compute, which is like as your load becomes, as your usage comes in, you can fire off requests for VMs or bare metals at other cloud providers and then get them up and running.Swyx [00:26:43]: This is if you go above 100%, right?Ivan [00:26:45]: Yeah, this is.Swyx [00:26:46]: Like your overflow.Ivan [00:26:46]: If your overflow, like spillage or whatever you do.Swyx [00:26:48]: You probably lose money on it, but it doesn't matter, right?Ivan [00:26:50]: It, not Well, you might, you might not That is a more cost-effective way to do it but it's a slower way to do it. Because basically what you have to do is you have to like queue your requests, spin up these just-in-time compute, get it all ready, provision it, and then get your workload there. And so if the time isn't important that much, that's fine, and you can do that. But if your customer, and especially for, let's say, the RL training runs, the reason why a lot of people come to us is because GPUs are more expensive than CPUs, right? So you want your GPU running at, what, 100% the entire time. And so when you're running runs on CPUs, when the when the CPU cycle is like down and spinning up the next one, you want that to be instantaneous so that your GPU doesn't go down, right? And if you then have to like go out and provision machines, you're essentially telling the GPU that it has to wait, and that's incurring our cost. So there's things that you have to try to solve for there.RL Workloads, Declarative Images, and Kubernetes ReplacementSwyx [00:27:43]: Yeah, let's talk about the different workload, right? You said that, what was it? A few months ago, you had zero RL workload and now it's 50%.Ivan [00:27:52]: It will be this one, 50%, yeah.Swyx [00:27:54]: Let's talk about how different it is, right? Like I imagine, for example, a lot less dynamic code generation of like arbitrary code. Like here, it's probably all the same code. You're just doing parallel runs or something, I don't know.Ivan [00:28:05]: Yeah. So you'll have multiple Depends on the like for each run, you'll have a snapshot. And they, for the most part, they actually do use our declarative image builder, which is like, “Oh, we, the agent wants these dependencies, these env vars.”Swyx [00:28:17]: These ones, yeah.Ivan [00:28:18]: Yeah, the declarative image builder, it.Swyx [00:28:20]: Which is a very modal like thing that they.Ivan [00:28:22]: Yeah. And so we build it on the fly and then we propagate that snapshot, and you can spin up as many sandboxes as you want against that snapshot. And then if you have to do changes, the model can, or like it could be also be automated. It's like, “Oh, now for the next run, we need to install these things or remove these things or whatever to get, a task done,” and then it goes off and runs that. So yes, that is something that it seems that they prefer. The number one reason I found, or should I say, let's take a step back. What we are competing against in that environment is essentially managed Kubernetes. So EKS, GKE, whatever. That is what the vast majority run on. And anyone that has tried Daytona versus GKE, EKS is like, “I'm never going back.” That has always been. There's a few reasons. One is the ergonomics. So if you have, if you're using Kubernetes to spin that up, you have to essentially manage the interface interactions with that. Daytona, although as a compute provider, it's more akin to a Twilio and Stripe from a consumption perspective than it is an AWS. Like you have an API, an SDK, it's quite like easy and seamless to get these things up and running, that's one. The other is the speed to which we spin up, which we mentioned earlier, which is much faster, and the scale to which we can go to. We haven't got into features, but an interesting feature is that it's very hard to OOM, or out of memory, our sandboxes, because we can dynamically on the fly.Swyx [00:29:48]: Resize.Ivan [00:29:49]: Resize, which is like impossible on almost any other thing. There are some technologies that enable you to do that, but it's like a very hard thing. And so we actually saw this when, the Terminal Revenge team is, brought us actually. So thank you, Alex and the team, that brought us into this whole space.Swyx [00:30:05]: It's just very rare that, a framework would just say, “Guys, just use Daytona.”Ivan [00:30:11]: Yeah, I think it says it somewhere. Yeah.Swyx [00:30:13]: Yeah. I was like, “What is this?”Ivan [00:30:15]: There's all, there's multiple there, but they also mention a few other places. and so Daytona specifically-We have, the, just jumping on themes here We, I don't know where it says Data Center.Swyx [00:30:27]: I, there.Ivan [00:30:27]: Doesn't matter.Swyx [00:30:28]: There's a very strong recommendation, which is, very unusual. Which is, it's.Ivan [00:30:33]: We do not pay them for this, just.Swyx [00:30:34]: I know, yeah. They just like you.Ivan [00:30:35]: Yeah, they like us. yeah, and also a thing, so, Data Center has multiple isolation sets underneath. The customer doesn't have to know what they are. But basically we have Docker, which is a container, that's hardened with Sysbox. So it's Docker's, isolation that is a security equivalent to a VM, but it's still a container. And that is the default, and they, especially in these training workloads, really like that as an interface to be able to use just a basic Docker container, and we enable Docker and Docker. Which for these RL runs, if you need to do a Docker compose or Kubernetes, you can spin up a K3S inside of these things, which unlocks a huge amount of workloads that you can do that you cannot do on other providers. So just on that part is much more interesting. And so we went that, through that. We showed them that we could do that, and they enjoyed that quite a bit. They being the general venture people.Swyx [00:31:28]: Those people, yeah.Ivan [00:31:29]: And Harbor people.Swyx [00:31:29]: Harbor people, do are they, are they a company yet?Ivan [00:31:33]: As far, I do not know.Customer Pull, Slack Connect, and the Computer Use BetSwyx [00:31:35]: Okay. All right. Yeah. It's like super obvious that like, there's a lot of excitement and success around these things, okay, so yeah, tell us more, right? Like, this is an exploding workload, Harbor adopted you, which helped speed things along. But what are you learning as this new workload comes online?Ivan [00:31:53]: There's a couple things that we learned, which we chat about in the beginning. We, and this has led our story, as we mentioned, we like talked to a lot of customers along the way, and we add more features and more tool sets as we talk to customers. And it's interesting that And I think it's that the ecosystem is so small and/or the models get smarter, where when we see one user come with a request, we know it goes on a roadmap if like three to five customers come with the same request in that week. It's like very bizarre. It happens so many times, which is.Swyx [00:32:27]: Because they're all friends.Ivan [00:32:28]: Sorry?Swyx [00:32:28]: They all, they're all friends. They're all in the same group chat.Ivan [00:32:30]: Yeah, probably, yeah. ‘Cause and they're like, “Oh, can you do this?” And I'm like, “Okay, this is interesting. We'll put it on a feature request.” And then the next one's like, “Oh, can you do this?” “Okay.” It's all the same, right? It's always the same. And so what we try to do, and I personally try to do, I try to be on as many call, quote-unquote “sales calls” I can. I'm in every Slack channel. We literally have about 1,000 Slack Connect channels, something like that. It's an interesting, there's so many interesting things you find out when you have all the Slack channels. You can also see where people, transfer between companies. You see leave Slack channel, enter Slack channel. It's an interesting thing. Also, just I digress, I feel that Slack Connect is literally LinkedIn what it should be. You have a list.Swyx [00:33:08]: LinkedIn charges you to, use your own connections, but Slack doesn't, right? Slack is like, do it for free. It's more lock-in. It's great.Ivan [00:33:15]: Yeah. It's amazing. Yeah. It's one of the reasons.Swyx [00:33:17]: You're gonna pay Slack for life.Ivan [00:33:18]: Exactly. You're there for life. So that's interesting. And so one of the things, the newer things we were talking about earlier is we made a big bet and put a lot of investment on computer use. that is not seen publicly the light of day. We haven't GA'd that yet, but we have.Swyx [00:33:32]: Is there a thing I can pull up?Ivan [00:33:33]: There is computer use there. It's right up a bit.Swyx [00:33:36]: Oh, yeah. Okay.Ivan [00:33:38]: What we have, what we talked about and what we've seen publicly is there's this theme now about, the human emulator where And Elon from XAI has talked about this publicly, and if you think about the models today, they're actually quite sophisticated and they can do a lot of work, but they still don't have access to all the tools. Like, I'm a strong believer that the most efficient way for an agent to work is essentially headless or through, terminal or whatnot. But if we, if we look at knowledge work in general, there's about 100 million knowledge workers in the US, about a billion in the world, and knowledge workers, and the salaries of them aggregate to 10 trillion in the US 50 trillion worldwide.Swyx [00:34:24]: Wow.Ivan [00:34:25]: Something like that. And if we look at, the five most important sectors of that, so like healthcare and government and financial services and whatnot, that's about 56% of that. So let's say it's about half of that. So in the US it's about 25 trillion, and most of them, most of that work is actually still locked into legacy apps inside of Windows, which is not going anywhere for a very long time. Like, people just won't invest in that. How much of it? our assumption is the following: if, in the RPA market, which is similar market, well, not the same 25% of, these white collar, workers', work is automated. If an agent is more sophisticated, can go through more runs, figure stuff out, let's say it's, 40%, right? And so if you take 40% of that, you get to essentially, $10 trillion a year.Swyx [00:35:17]: That's a TAM.Ivan [00:35:18]: That is a that is a TAM. So that's the TAM of the models, right? That's not our, essentially ours. But you get to that size, and to be able to do that, you essentially have to give agents these computers with the legacy. So computer use, either Mac or Windows or Linux. Linux we also obviously have and others have. But Windows specifically is something very new, and the only option right now is an EC2 with, Windows or on Azure. Both of them take anywhere from three to five minutes to spin up. We've created an actual sandbox, so it's a second instead of milliseconds, but you have, point in time snapshots, you have, forking, you have all the things that you have from a sandbox, but essentially enables you to hopefully unlock all this value. And so that's been our big push and bet, but we've sort of, kept our ear to the ground. What is sort of the next things in the market?RPA Returns: Why Agents Still Need ComputersSwyx [00:36:06]: Yeah, knowledge work, and building, and sort of RPA, the next wave of RPA. I got very excited about RPA kind of during COVID times. The UI path was IPO-ing. And it was, a very hot Isn't it, Eastern European?Ivan [00:36:20]: It is, Romanian.Swyx [00:36:21]: Romanian?Yeah, it might be the only Romanian, big unicorn okay, yeah. This I don't I don't, I don't have like a I think there's, I think there's a stage being set for the resurgence of RPA, ‘cause everyone understands that, yeah, no one wants to deal with these shitty apps and no one's gonna rewrite them. Like, you just have to do, a remote operation and programmatic operation of them.Ivan [00:36:45]: If you wanna unlock it, my own setup was basically the following. So I was doing a board deck recently, last month, whatever, and I'm like, “Okay, let's just, let's just do automated.” So, all our data's in, ClickHouse and PostHog and QuickBooks, where everyone else's is, and I'm basically, connected that all to, my Cloud code, like go off and go Cloud code whatever. Go off and, here's the integrations, go do that. It pulled out the first report, which was great. It connected to Brex and all these things, pulled it, which was great, and then I say, “Okay, now pull out this, and this,” and I kept getting, really well McKinsey-style design reports, but the data said partial data. all the missing data, partial data. Like, it can't access all the things, and I got so frustrated, and so I got, I got, my Mac Mini virtual sandbox with OpenClaw. I gave it its own account in our company, and then I went to all these services and created a read-only account, so literally like an intern in your company. And so I would say, “Now go and do this report,” and it would get the same, or like, “I can't via the MCP or the API or whatever. I can't get all the information.” I'm like, “Go log in.” And it will log into the website, then go in, export the data. It'll export the data and do the thing end to end. So even for things that have today APIs, not all of it is exposed, and I to get value, I get immense value right now, but it has to be a computer usage, unfortunately, and so I spend a bunch of tokens just on that, but I get the job done. And so if even a startup like ours, and using all the hottest tools, still needs a computer agent what hope does, Goldman have to have a headless, right?Swyx [00:38:22]: Yeah, what a - Why isn't Microsoft doing this?Ivan [00:38:27]: I'm pretty sure, Satya had a post yesterday.Swyx [00:38:29]: Oh, okay. I see.Ivan [00:38:29]: Which was like, “Every agent needs a computer.”Swyx [00:38:31]: I see, I see.Ivan [00:38:32]: So they have launched something recently.Swyx [00:38:34]: Yeah, they have Microsoft Power Automate, I'm sure, I'm sure, they're gonna have their version.macOS Sandboxes, Apple Constraints, and the Windows OpportunityIvan [00:38:39]: Version of that, yeah.Swyx [00:38:39]: You're gonna try to do yours, and it - I always know there's always demand for Mac, but I know it's, tricky to host, macOS sandboxes.Ivan [00:38:49]: We will have macOS sandboxes fairly soon. The problem with macOS, OS sandboxes is, I'm deep in this, I don't know how much interesting is.Swyx [00:38:55]: No, it's.Ivan [00:38:56]: MacOS has this problem.Swyx [00:38:57]: It's a licensing thing, right?Ivan [00:38:58]: Licensing thing. So one, you're allowed to run only two parallel VMs per machine, so that's one. Two, you can only license to a different user every 24 hours. So if you come in and theoretically, if I wanna charge you per second and I charge you one second, I have to have it idle for the rest of the day. I can't have anyone else doing that. So the pricing will be different in the sense that I will have to - we would have to charge for 24 hours, and that's not even, that's not even the most difficult thing. But the, thing above that is, from a security perspective, they enable you to do memory snapshot, pause, resume, but only on the same physical drive, physical machine. And so what you can do in, Windows world or Linux world is that I can move in the background, your snapshot from one to the other and manage load, right? Here, if you wanna do that, you essentially have to have your.Swyx [00:39:49]: Yeah, snapshots. Yeah.Ivan [00:39:50]: Your.Swyx [00:39:51]: It's like.Ivan [00:39:51]: Physical machine.Swyx [00:39:52]: You can't break it up.Ivan [00:39:53]: You can't, you can't move things around that, and all of that is, that part is, from a security standpoint, if it is written. Like, I understand the security aspect of that, but it disables you from doing these agentic, like really scalable agentic workloads.Swyx [00:40:08]: You need to do a vibe-coded, clean room implementation on macOS that you can then - That's like Clean OS or something. I don't know.Ivan [00:40:17]: So. We have.Swyx [00:40:18]: ‘cause like Linux was originally like a clean room rewrite of Unix.Ivan [00:40:21]: Okay. Yeah.Swyx [00:40:21]: Or something like that, right? Like same thing to macOS. Someone needs to do it.Ivan [00:40:25]: Someone will do that, and someone will have some long-running agents for a few days to figure this stuff out. But yeah. So definitely we - we're really close to offering something ‘cause people do want it, but the pricing will be different, and the feature set will be sort of stringent.Swyx [00:40:38]: Yeah, nobody's gonna use this. like, the labs, the labs will because they want to automate macOS.Ivan [00:40:42]: They have to do RL. They have to do RL again. But even if you The - So the point is with the RL part, if you, if you do RL on macOS, then the next iteration of the model comes out, it will be able to use these tools significantly. Then you actually need to run those, that somewhere. So you're gonna have to have that, later on. And from, if anyone at Apple is listening, I very much feel that they are shooting themselves in the foot of the scale of the revenue of compute or licensing they could get if they would just enable a concurrency model similar to what you can get on a Windows and a, and Linux.Swyx [00:41:17]: Yeah. Yeah. And I'm sure they've heard this before. They just don't care. Yeah, it's And maybe they will change their mind with the new CEO.Ivan [00:41:24]: Yeah. We'll see.Swyx [00:41:25]: We'll see.Ivan [00:41:25]: High hopes.Swyx [00:41:26]: High hopes.Ivan [00:41:26]: High hopes.Swyx [00:41:27]: Okay. But I, it's very clear the market opportunity is huge in Windows, and you can go for a long time on just Windows, but your customers are gonna want both. and I think, it is interesting to me that, this is the sort of God application of agents, right? Like, I don't It was - How big was OpenClaw for you guys? Like, was it, was there, a significant bump.OpenClaw, Agent Labs, and the B2B2C Sandbox MarketIvan [00:41:54]: Not for us because we.Swyx [00:41:54]: Because you already.Ivan [00:41:55]: We're kind of positioned differently. Whereas although it's completely PLG and we have individual developers that use it, most of the users that use Daytona are sort of a B2B2C. Sort of it's either B2B or B2B2C. So, in the researcher world, it's B2B, so you're selling to, labs and neo labs and things like that. But on the long-running agents, it's mostly, from a scale revenue perspective, it's mostly B2B2C, where you have a app layer agent that uses you at a big scale.Swyx [00:42:26]: Like a Manus. Yeah.Ivan [00:42:28]: Like a Manus Lovable type of thing.Swyx [00:42:31]: Yeah. I think that's the question of, well how, um-Uh, yeah, B2B to C is basically to me what I've been calling an agent lab, which is kind of like you're not in a model lab, but you're making a very good wrapper that is a platform that other people can sign up so they don't have to code those things. Yeah, it sound, it sounds like a much better market than the direct OpenClaw market.Ivan [00:42:56]: I've like - We I've done multiple things. So the CodeAnywhere's part of our career path R in the calendar, was very much an end user developer product. And so that is great. It You can get a lot of developer love, and I feel that we do as a company have a bunch of developer love. But it's a different type, where it's people building these things. Again, it's more akin to a Twilio because you don't really run - As a person, you wouldn't run Twilio. I don't know how many people remember. It was like ask your developer billboard and whatnot. And people really love Twilio, but they only used it inside of like, “Oh, I'm building this app or service for thing.” And so we're very much directly to that. And you also know that I used to work for a competitor for Twilio, so it's kind of ingrained, in my DNA.Swyx [00:43:35]: People don't know InfoBip is that big.Ivan [00:43:38]: Yeah, it's.Swyx [00:43:39]: Because.Ivan [00:43:40]: It's a billion euro.Swyx [00:43:40]: They're all American. They're like, “Whatever's in Europe doesn't matter to me.” But like it's the, it's the same size or bigger? Same size?Ivan [00:43:46]: It's about half the size.Swyx [00:43:47]: Half the size?Ivan [00:43:48]: Yeah, about half the size.Swyx [00:43:48]: It's like, yeah.Ivan [00:43:48]: Still huge. Multiple billions a year. Yes.Swyx [00:43:51]: That's crazy.Ivan [00:43:51]: Exactly, and so that - These are like really interesting and large revenue-generating, very sticky businesses. Whereas when you're selling to the - When your focus is the end developer, it is a very hard sell because they're very price sensitive, very price conscious, very around that. And there's very It's very hard to scale. Your cap is the number of people that are willing to spin up - First of all, wanna spin that up, and then spin up multiple of these. Whereas if you're in the enterprise one, like we know everyone's talking about like how many tokens they're spending, I'm spending. Like a lot of companies today are like, “If this is our company, spend as much as you can.” Like basically that is where we're going. And so if you think about that paradigm, where you're selling to companies that say, “Spend as much as you can to generate, productivity,” versus, “Oh, I'm a single person. I have this much budget, and I'm doing this thing because it's fun or it's helping me out or whatever.” Like it is a different, it's a different go-to-market, I think, strategy.MCP, CLIs, and Sandboxes as the Agent RuntimeSwyx [00:44:50]: Yeah, there's a lot of discussion. I'm just kind of going through like the mental list of things that are in your favor, which is, for example, MCP versus CLI. Like obviously you want CLI. It's been very good for you. I feel like it's maybe a drop in the bucket or maybe it's huge. I'm just checking whether it's like these are big trends.Ivan [00:45:10]: Those things you - work well in our favor, to your point just because every.Swyx [00:45:13]: They're kind of drop in the bucket, right?Ivan [00:45:15]: I think it's like sort of all the things come together. And so there's so many things that impact that. To your point, like OpenClaw wasn't huge for us, but like having the agent SDK, from Anthropic, so or Cloud Claude Code was very interesting. The reason why it was interesting is that a lot of, let's call them app I don't know what to call them, app layer agent companies, essentially they are like, “Oh, I can create this new app, this new agent. All I need, I just use Claude Code, and I throw it into a sandbox, and then I have my interface to the human to that.” And so that enabled so many more companies to actually offer this, and then they would pull on sandbox. So that was, that was interesting. And to your point, like MCP, versus the CLI, the MCP is an interface against an API, whereas the CLI is like you can actually go do things. Like this is it. The difference between integrations and actually running scripts or data or analysis against a thing. So being able to use a CLI very well enables the agent to do more things, and it's because that people will invoke a sandbox, they'll run it in the CLI, and but it'll do anal-analysis on that data and then give you an actual result versus just, pulling data from an API source.Swyx [00:46:29]: Yeah, it's a layer of indirection basically, it's the same thing as agentic search versus RAG, which where you're.Ivan [00:46:34]: Exactly, yeah.Swyx [00:46:34]: Just like you just win whenever people put more agents into their workflow. And so like it doesn't really matter, but I'm just kinda teasing out like what else have people heard about that like it's sort of, “Oh yeah, this is another sandbox use case. Oh yeah, that's another one.” Am I, am I missing any big ones?Ivan [00:46:51]: The thing, the thing that people, which is the computer use stuff, which I think is probably the most interesting one, is, and to your point, we've talked to so many people over the last year. It's like, “Oh, like why do you need a sandbox? Why do you need this? Why this?” And to your point, it's like, “Oh, I need sandbox for this. I need sandbox for that. I need sandbox-” It's like, “Oh, I need it for every single thing.” And so basically what I, what I - and it sounds like a broken record, it's like you use a laptop every single day, right? And you are n of one. It's just you. But now imagine how And by the way, the laptop, the computer PC market, the PC market is about equal to the cloud market in total. So it's about 150, 180 billion a year. Something like that. It's about roughly the three cloud hyperscalers is about equal to like Apple, HP, Lenovo, whatever, It's a little bit less, but it's sort of like that. And now imagine And that's just like, so how big is the addressable market? What, how many people are there in the world now? What's the last data?Swyx [00:47:45]: Let's call it eight billion.Ivan [00:47:46]: Eight billion. And so let's say you can have two computer, like you have one personal and one business, whatever. Like so it's double that, right? and so that's 16 billion, right? How many agents are gonna be running in two years, in 10 years, in 100 years? Like And for every single task, they will need one of these. And so how big is that? That market is essentially quote unquote “infinite”. You will get to the point, and Dylan Patel was at the conference talking about, from SemiAnalysis, that talks usually about GPUs, was also talking about how CPUs will now be a bottleneck because it will be the constraint. You won't be able to grow, or we won't be able to have enough of these because there won't be enough CPUs to basically do.Swyx [00:48:23]: Yeah. Well, I actually had a really good podcast with Doug Oliphant, who, which was his president at SemiAnalysis, where they've basically been like, yeah, it's been a GPU shortage first, but then it's cascaded down to memory and now to CPUs.Ivan [00:48:35]: CPU, yeah.Swyx [00:48:35]: It-What's next? So networking. So, networking actually has been in shortage for a while if you're looking at, just GPU networking. But, yeah, it's really crazy the amount of computer use that's going on, yeah, cool. I, other questions are, just the one very big part is the open sourceness which you didn't have to do, your competitors don't do, like it's not, a lot of people are worried about keeping their projects open source because some competitor can just slot fork it. I don't know if there's any reflections on just being an open source company.Open Source, Trust, and Enterprise ProcurementIvan [00:49:15]: Yeah. There's a bunch. So we the original product that we did was open source.Swyx [00:49:19]: Yeah. CodeAnywhere.Ivan [00:49:20]: So doing that was actually very good for us. There's basically a saying of, What's the saying? Like, companies that are, that are doing really well, measure themselves against, free cashflow, that are kinda okay, it's EBITDA, then, it's, it goes all the way down.Swyx [00:49:36]: The worst is like GitHub stars.Ivan [00:49:37]: GitHub stars. GitHub stars are the worst, yeah. So you go all the way down to GitHub stars. And so our original one was GitHub stars. That's what we talked about, we're at the point we're talking about revenue, so we're we've gone up the stack on that. And so we started.Swyx [00:49:47]: No, profit.Ivan [00:49:48]: Yeah. We haven't, we're, we'll get there. We'll get there. But basically at that point we did stars and GitHub and it was useful, and the original variation that we did, it we split the core into its own repo and it was Apache 2.0, so very, permissive. And then we basically would bundl

El director de atlCapital analiza los títulos de ACS, ASML, AENA, HP, Siemens, Intel o Grifols, entre otros

AI is already replacing jobs. Most people are completely unprepared.In this episode, Gaurav Arora sits down with Prashant Puri — Founder and CEO of AdLift, one of India's leading digital marketing and AI agencies — for the most important career conversation of 2026.Prashant has run SEO, digital marketing, and AI strategy for PayPal, HP, Myntra, and some of the world's biggest brands. He built AdLift from 5 people to 200 and exited for ₹50 crore. He is also the creator of Tesseract, an AI-powered marketing intelligence platform that is changing how brands think about search in the AI era.In this episode he names the AI tools beyond ChatGPT that are already replacing jobs, explains why knowing only ChatGPT in 2026 is not enough, and gives a step by step breakdown of what to learn right now to stay ahead.He also explains why Google is losing — 60% of searches now end without a single click — what the zero click era means for your career and business, why India has 180 million AI users but not a single homegrown AI company, and why most learn AI and earn lakhs courses are Ponzi schemes.What You Will Learn:- Which jobs AI will replace first in 2026- The best AI tools to learn beyond ChatGPT — Runway, Kimi, Claude, N8N, MidJourney and more-  How to use AI agents to automate your work and run tasks 24/7- Why Google is dying and what is replacing it- How to start learning AI from scratch as a complete beginner- Why India is the biggest AI user in the world but hasn't monetized it- The difference between someone AI replaces and someone AI makes unstoppable- How Prashant Puri built a ₹50 crore company from a 2 out of 5 performance reviewChapters:00:00 Will AI Take Your Job00:20 Meet Prashant Puri01:35 AI Tools Beyond ChatGPT02:40 Ocean Of AI Use Cases03:47 Marketing Creatives And Automation06:33 AI For Learning And Email08:44 Jobs And The New Marketer10:31 Why Degrees Still Matter12:29 Making Money With AI16:17 Avoiding AI Course Scams19:00 First Steps For Beginners20:13 Brand Visibility And SEO Basics21:45 AdLift PayPal Pitch Story24:04 Can AI Identify Problems25:19 Stop Being Lazy With AI25:33 Google vs LLM Search Shift26:59 GEO and Consideration Funnel28:58 From Searching to Asking29:39 Zero Click Era Explained30:56 Expertise Beats Fake AI33:12 Start Small and Compound34:32 AI as an Equalizer37:56 Tracking LLM Visibility Tool41:57 Tech Convenience vs Connection43:55 India Monetization and Ads45:54 Building Indian AI Models48:07 One Truth About AI FutureAbout Prashant Puri: Prashant Puri is the Founder and CEO of AdLift, one of India's leading digital marketing and AI agencies. With over 15 years of experience in SEO, paid media, and AI-driven marketing, he has worked with global brands including PayPal, HP, and Myntra. He is also the creator of Tesseract, an AI-powered marketing intelligence platform built for the zero click era.About Gaurav Arora: Gaurav Arora is one of India's most respected podcast hosts, known for deep and honest conversations with leading voices in business, entrepreneurship, technology, and personal growth.

Richa Pande is a highly accomplished B2B marketing executive specializing in Account-Based Marketing (ABM), customer journey design, and precision targeting. She is currently a driving force behind HP's global commercial and industrial print marketing strategies. Key Highlights of Her Career & Expertise:The "Science" of ABM: Richa is a leading voice in the marketing community regarding the foundational structure of ABM. She advocates that true marketing success isn't about letting sales "fend for themselves," but rather doing the heavy analytical lifting beforehand—filtering firmographics, building rich persona insights, and mapping out tight customer journeys. Customer-Centric Execution: A major pillar of her philosophy is creating "peer-to-peer" environments. She leverages marketing to connect high-value clients with one another and with industry experts, prioritizing relationship-building and direct feedback over traditional, aggressive sales pitches. MarTech & AI Integration: Richa frequently speaks at industry events (like Martechify) on the future of B2B marketing. She focuses heavily on how modern enterprise brands can leverage artificial intelligence, marketing mix modeling, and zero-party data to align marketing and sales teams under unified revenue goals.

In this episode, Tessa Burg talks with Fabio Ranieri, Head of AI Content Transformation at HP, about what it really takes to create content at scale without losing relevance. Fabio explains why better content doesn't come from simply making more of it. But rather it comes from better inputs, better audience understanding, and better systems that help marketers create content that fits the product, the customer, and the moment.  Fabio makes a strong case for why AI should free marketers up to focus on bigger ideas, sharper insights, and stronger customer experiences. It's a smart, grounded conversation for anyone trying to move past the hype and use AI in a more meaningful way. Leader Generation is hosted by Tessa Burg and brought to you by Mod Op. About Fabio Ranieri: Fabio is a growth and innovation leader with 18 years of global experience in product marketing, partner marketing, category management, and go-to-market strategy across B2B, B2C, e-commerce, SaaS, Telco, and consumer product sectors. Known for turning ambiguity into opportunity, he specializes in launching and scaling new experiences and products, driving digital transformation, and orchestrating high-impact GTM strategies across highly complex organizations. He's led end-to-end initiatives that delivered real business outcomes—from redesigning HP's global e-commerce channel experience, launching and leading new product lines and categories, to introducing Intuit QuickBooks' new mid-market offering. Always action-oriented, analytical, and creative, Fabio bridges the gap between product, marketing, and sales to maximize impact. He can be reached on LinkedIn.  About Tessa Burg: Tessa is the Chief Technology Officer at Mod Op and Host of the Leader Generation podcast. She has led both technology and marketing teams for 15+ years. Tessa initiated and now leads Mod Op's AI/ML Pilot Team, AI Council and Innovation Pipeline. She started her career in IT and development before following her love for data and strategy into digital marketing. Tessa has held roles on both the consulting and client sides of the business for domestic and international brands, including American Greetings, Amazon, Nestlé, Anlene, Moen and many more. Tessa can be reached on LinkedIn or at Tessa.Burg@ModOp.com.

出演者：藤原鞠菜 配信ペース：隔週火曜日 番組時間：平均40分 ——————————————————————— ＜各テーマ紹介＞配信されるテーマは回によって異なります。 「ふつおた」･･･何でもありのお便りコーナー。投稿は毎日募集中！！！！！ 「歴史秘話ウィステリア」･･･サークル曲の裏話など。 「まりにゃのこれな～んだ？」･･･音当てクイズ。 「まりにゃのオススメ」･･･オススメ商品をご紹介。 「はじおと」･･･「音楽」×「初めて」に関して語るコーナー。 （初めて買ったCD、初めて心を動かされた音楽、初めてカラオケで歌った曲等。） 「これかた」･･･テーマを決めて語る割とフリーダムなコーナー。 （テーマや語ってみた投稿募集中。） 「答えて、まりにゃ」･･･まりにゃへの質問募集中。 「トレンドなう」･･･収録時に開いたTwitterのリアルタイムトレンドについてコメント。 「まりにゃのTOP5」･･･思いついたら勝手にランキング。 「まりにゃのドキドキ質問箱」…twitter投稿になります。（ https://peing.net/marinya_）  「みんなの答え合わせ」…twitterで出題するアンケートの結果報告。みんなに聞きたいこと募集中。 ——————————————————————— ——————————————————————— ■CD新作・出演告知など■ ★Wisteria Magic通販サイト「うぃすましょっぷ」★ wismashop.booth.pm/ 新作も旧作も全て送料込み！ ★イオシスショップ様にて一部旧作を委託販売中！★ www.iosysshop.com/SHOP/list.php?Search=wisteria ★しがないレコーズのyoutube「しがない5分ショー」に出演してます。 藤原鞠菜は木曜日担当です。 https://www.youtube.com/channel/UCA_FmkoMu24R_6o3m3_Ulqg —–　　—–　　—–　　—–　　—–　　—–　　—–　　—– —–　　—–　　—–　　—–　　—–　　—–　　—–　　—– ・の〜すとらいく様の18禁PCゲーム 「女装百合畑/Trap Yuri Garden」にて、主題歌「優雅にヒロイン宣言」を担当させて頂きました。 ・TinklePosition様の18禁PCゲーム 「お兄ちゃん、朝までずっとギュッてして！夜までもっとエッチして！」 にて女未こはくちゃん(三女)のED曲担当させて頂きました。 ・TinklePosition様の18禁PCゲーム 「お兄ちゃん、朝までずっとギュッてして!」 にて女未こはくちゃん(三女)のED曲を担当させて頂きました。 —–　　—–　　—–　　—–　　—–　　—–　　—–　　—– —–　　—–　　—–　　—–　　—–　　—–　　—–　　—– ——————————————————————— この番組は音楽サークルWisteria Magicがお届けする番組です。 藤原鞠菜やサークルの過去または最新の活動内容につきましては 以下をチェックしてくださると嬉しいです♪ ・藤原鞠菜のTwitter（ twitter.com/marinya_ ） ・藤原鞠菜のHP「ふじわらんど」（ fujimari.com/ ） ・磯村カイのTwitter（ twitter.com/isomurakai ） ・磯村カイのHP「TONAKAI soundworks」（ https://soundworks.tonakaii.com/ ） 藤原鞠菜への贈り物の宛先 〒107-0052 東京都港区赤坂4-9-25 新東洋赤坂ビル10F レイズイン　アカデミー気付　藤原鞠菜宛 VOICEVOX:ずんだもん VOICEVOX:四国めたん

Andri Sadlak is a serial entrepreneur and Founding Head of Product & Strategy at Azoma, building AI-first commerce software for the age of agentic shopping. He's been an Amazon seller since 2017, exited his own brand, and co-founded ProductPinion. Today he's part of the team behind Amazon growth and AI visibility strategies for 8 and 9-figure brands like Mars, L'Oréal, and HP. He's one of the sharpest voices on Agentic Commerce, taking the world stage to break down how brands need to show up in the age of AI shopping assistants like Amazon Rufus, Walmart Sparky, and LLM search.Highlight Bullets> Here's a glimpse of what you would learn…. The evolution of e-commerce from traditional search engines to AI-powered answer and action engines.The rise of AI shopping assistants and their impact on consumer purchasing behavior.The integration of AI technologies by major companies like Amazon and OpenAI to enhance shopping experiences.The concept of generative commerce and how AI can autonomously complete purchases for consumers.The rapid adoption of AI tools and their influence on product research and decision-making.The importance of optimizing for AI algorithms in e-commerce, particularly on platforms like Amazon.The role of multi-modal understanding in AI, allowing it to interpret both text and images for better product recommendations.Strategies for sellers to optimize their listings for AI-driven systems, including managing Q&A sections and enhancing product images.The significance of external citations and media presence in building trust and credibility for AI recommendations.The future of e-commerce and the necessity for brands to adapt to AI-driven changes to maintain competitiveness.In this episode of the Ecomm Breakthrough Podcast, host Josh Hadley interviews AI-driven e-commerce expert Andri Sadlak. They explore how AI is revolutionizing online shopping, focusing on Amazon's shift from traditional search to AI-powered answer and action engines like Rufus. Andri shares actionable strategies for brands to optimize product listings for AI, discusses the importance of image and Q&A optimization, and highlights the growing role of external citations. The episode offers practical tips for sellers to thrive in the new era of agent commerce, emphasizing the urgency of adapting to AI-driven changes in e-commerce.Here are the 3 action items that Josh identified from this episode:Optimize for BOTH Amazon algorithms Don't rely on just traditional keyword SEO—start optimizing for both Rufus/Cosmo (AI-driven discovery) and legacy search to stay competitive.Fix your existing listings first (quick wins) Update product images, backend fields, alt text, and listing details—these are fully within your control and can drive immediate impact.Focus on one high-impact priority: Cosmo optimization Ensure your product answers key customer questions clearly (front + backend). Nail the fundamentals first—everything else builds on this.Resources mentioned in this episode:Josh Hadley on LinkedIneComm Breakthrough ConsultingeComm Breakthrough PodcastEmail Josh Hadley: Josh@eCommBreakthrough.comTools and Technologies"Rufus": "00:02:02""ChatGPT": "00:06:01""Gemini": "00:09:33""Perplexity": "00:09:33""ProductPinion": "00:02:02""Cosmo": "00:21:04""Claude": "00:28:05""Amazon Rekognition": "00:36:30""AWS (Amazon Web Services)": "00:36:30""Azoma": "00:54:36"Studies and Reports"Accenture Study on AI Trust": "00:13:13""Bain and Company Research on AI Usage": "00:16:05""Amazon's Cosmo Paper": "00:30:32"Skills and Features"Skills for Claude": "00:28:41""A+ Content": "00:39:55"Websites"Amazon Seller Central": "00:38:14""Affiliates Media": "00:44:19""ecommbreakthrough.com": "00:54:58"Books"Building a StoryBrand": "00:54:11"Key Concepts"Listings 10, 20, and 30": "00:22:34""Optical Character Recognition (OCR)": "00:39:04"Episode SponsorThis episode is brought to you by eComm Breakthrough Consulting where I help seven-figure e-commerce owners grow to eight figures. I started my business in 2015 and grew it to an eight-figure brand in seven years.I made mistakes along the way that made the path to eight figures longer. At times I doubted whether our business could even survive and become a real brand. I wish I would have had a guide to help me grow faster and avoid the stumbling blocks.If you've hit a plateau and want to know the next steps to take your business to the next level, then email me at josh@ecommbreakthrough.com and in your subject line say “strategy audit” for the chance to win a $10,000 comprehensive business strategy audit at no cost!Transcript Area:Andri Sadlak 00:00:00  The shift that we're talking about is search engines are becoming answer engines plus action engines. So it's already answer engines. We're already deep in it. Most of the people at least. And action engines is what a lot of people predict is going to happen next because we're going to save our time. We're going to go for convenience and trust AI. We already do, right? The good news you're watching this. So now you know that you need to pay attention. And I'm going to share with you exactly what I need to do.MC 00:00:29  Welcome to the Econ Breakthrough Podcast. Are you ready to unlock the full potential and growth in your business? You've already crossed seven figures in sales, but the challenge is knowing how to take your business to the next lev...

News and Updates: AI Compute Tax Debate: Economists and policymakers are debating taxing AI processing power to offset job displacement and fund social services, though critics argue it's too blunt a tool. AI Dividend Proposal: NY congressional candidate Alex Bores unveiled an "AI Dividend" plan funding direct payments to Americans through a token tax on AI consumption and equity stakes in frontier AI firms. Screenless Fitness Trackers Surge: Screenless wearables like Oura Ring and Whoop are booming, with U.S. fitness tracker purchases up 88% and smart ring sales up 195% between 2024 and 2025. Canvas Hacker Payout: Instructure, maker of the Canvas education platform, reached an undisclosed "agreement" with the ShinyHunters hacking gang after a breach exposed data from 275 million users across 9,000 institutions. FCC Router Ban vs. Supply Chain: AT&T warned the FCC that a global DRAM and NAND flash shortage, driven by AI deployments, is complicating compliance with its ban on foreign-made Wi-Fi routers. Google Unveils Googlebook: Google announced a new laptop line called Googlebooks running a fused Android/ChromeOS platform, featuring Gemini AI integration and a "Magic Pointer," with hardware partners including Acer, Dell, HP, and Lenovo.

Success rarely follows a straight path. What does it take to transition from sweeping floors and driving forklifts to leading global technology strategies at one of the world's largest tech companies?In this episode, guest Ed SooHoo joins the show to share his incredible professional journey, framing his career through what he calls the "Three Collars". Ed opens up about his extensive background as a blue-collar, card-carrying Teamster—working as a rail switchman, forklift driver, and machinist—and how those practical, "back of house" experiences laid the ultimate foundation for his future.We dive into his shift into white-collar corporate spaces at tech giants like Oracle and HP, his ventures into the "no-collar" entrepreneurial world running billiard clubs and microbreweries, and his current role as the Chief Technology Officer for Global Accounts at Lenovo. Ed reveals why his massive success isn't actually rooted in being a tech genius, but rather in being an "accidentalist" driven by relentless curiosity and mastering the art of asking questions instead of just pretending to have all the answers.Marketing with Russ...aka #RussSelfie, Episode 615Featuring Ed Soo Hoo

ClevelandMoto Podcast 551 Show Notes: Special Guest Myles Gauthier from MotoSmith Garage and Mike Stewart (Fireman Mike) from Virginia.  Last week we were all aboot Mexico and this week we're all aboot Canada. https://youtube.com/live/wrLU7oezjs8Harley is bringing back the 883 Sportster? For under 10K? Pardon me, but isn't the nightster already $9999 and technically VASTLY superior? https://www.cycleworld.com/motorcycle-news/harley-davidson-to-revive-883-sportster/Give yer balls a tug boys...this isn't what we want. KTM SuperDuke 1390 (aka The Beast) 190 HP in a street fighter? https://www.ktm.com/en-int/models/naked-bike/2026-ktm-1390-superdukerr.htmlThat's some solid ad copy right there. BRING BACK THE SV650, but make it taller, and more touring oriented, but don't exactly make a V-strom. And don't make it a parallel twin like you did with the V-strom. https://www.advrider.com/suzuki-announces-sv-7gx-crossover/DGR is this weekend. Are you ready?Support the showRemember folks...Ride Fast and Take Chances! check out our Youtube channel at https://www.youtube.com/c/ClevelandMoto

出演者： miko、quim 配信ペース： 隔週 番組時間：100分55秒 ♯本番組はリモート収録です。 ♯収録時環境の影響により、全体的に聴き取り辛くなっております。 　申し訳ございません。 隔週に1回お届け。mikoラジ、第397回です。 GW、終わっちゃいましたね……次の祝日は7月です。 病み上がりのしがないさん、労働は害悪な我さんのそれぞれのGWとか、GW明けとか。 ふたつの初めての○○○○があったり、いつも通りと特別と。 最後までごゆるりとお楽しみくださいませ。 ♯途中で色々とノイズ等入りますが、収録時のものです。 　ご安心ください、お手持ちの機器は正常です。 ・おとらってRECORD 公式サイト n-remix.com/otolatte/ ↑『おとらって10thライブ KUWANA』に参加予定の方は、 　「来場予約はこちらから」からご予約を！ 開催日／2026.8.23(日) 　第一部　OP11:30　ST12:00 　第二部　OP14:40　ST15:00 //////////////////// VOICEVOX:ずんだもん VOICEVOX:四国めたん //////////////////// -------------------- ●お便り募集中！ mikoラジでは以下の内容でお便りを募集中です！ ・ふつおた 　／普通のお便り、お待ちしています！ ・mikoは大変な絵を描いていきました 　／miko画伯に描いて欲しいお題をお待ちしています！ ・メシヲコエテ 　／料理人・mikoに教えて欲しいレシピをお待ちしています！ bit.ly/2GAWjyv 投稿フォームからラジオに投稿が出来ます！ コーナー名を選び、メッセージ・ラジオネーム・お所を入力して、 どんどん送ってください！　お待ちしています！！ ------------ 本ラジオのメインパーソナリティーである「チーム我等(miko/quim)」、 それぞれ以下個人サークルにて活動中です。 ・miko：miko ・quim：SHIGANAI RECORDS（ shiganai.com/ ） 活動詳細については、上記HPの他 各人のブログ/twitter等にて随時告知しておりますので、チェックしてみてください！ ・みころぐ。(mikoのブログ)（ ameblo.jp/miko-nyu/ ） ・@ mikonyu(mikoのtwitter)（ twitter.com/mikonyu ） ・@ quim(quimのtwitter)（ twitter.com/quim ） --- その他の活動については、以下のとおりです！ -- チーム我等がメインクルーとして活動していた「アルバトロシクス（ albatrosicks.com/ ）」、 これまでリリースしたCDは、イオシスショップ（ iosys.booth.pm/ ）にて頒布しております。ご興味ある方は是非！ ---------- ☆2026年5月IOSYSはいてない.comパワープレイ楽曲 M1. One Era feat. DD"ナカタ"Metal Produced by RoughSketch Vocal by DD"ナカタ"Metal 音楽ジャンル：Hardcore 収録アルバム：NBCD-052 20 Years Of RoughSketch: Golden Best & Remixes 2026 2026・4・26 Release https://notebookrecords.net/discographyportal.php?cdno=NBCD-052 積み重ねた『ジャパニーズ・ハードコア』を貴方に クリエイター「RoughSketch」の活動20周年を記念した2枚組アルバム。 書き下ろし新曲を含めたベストアルバムに加え、ディスク2には活動の中で出会った日本全国各地のトラックメイカーによるRemixが集結！ CD特典コンテンツとして2026年3月8日に行われた6時間ライブセットの音源をフルでダウンロード可能！

On this week's episode of The MacRumors Show, we discuss Google's latest wave of announcements for Android and Gemini, the newly announced Fitbit Air, and Apple Watch Series 12 rumors.The centerpiece of Google's announcements this week was Gemini Intelligence, Google's new umbrella platform for AI across phones, watches, cars, and laptops. Its headline capability is cross-app automation: users can photograph an event flyer and ask Gemini to find tickets on Expedia, or pull up a grocery list and have it build a cart in a shopping app. A companion feature called Create My Widget lets users describe a home screen widget in natural language and have Gemini generate it, drawing from Gmail and Calendar to build a personalized dashboard.Google also unveiled the Googlebook, a new laptop category designed from the ground up around Gemini with partners including Acer, Asus, Dell, HP, and Lenovo arriving this fall. Gemini in Chrome for Android gained an agentic browsing layer rolling out end of June, and Android Auto received AI-generated contextual replies and DoorDash voice ordering. A Meta partnership brings Ultra HDR, native stabilization, and night mode to Instagram on Android flagship devices.In January, Apple and Google announced a partnership under which Gemini would power the next generation of Apple Foundation Models, including a more personalized Siri expected this year. Apple's equivalent cross-app ‌Siri‌ actions were announced at WWDC 2024 but have not yet shipped; Gemini Intelligence is rolling out this summer using the same underlying technology.Google also unveiled the Fitbit Air this week, a screenless fitness tracker priced at $99 that ships on May 26. The device weighs just 12 grams with the band and tracks heart rate, AFib, HRV, SpO2, and sleep stages in a pill-shaped pebble with no display, no buttons, and no notifications. Battery life lasts for seven days, with a five-minute fast charge delivering a full day of use. A Stephen Curry Special Edition is priced at $129, with core tracking free and Google Health Premium adding an AI Coach for $9.99 per month after a three-month trial.The launch accompanies a broader rebrand. The Fitbit app becomes Google Health on May 19, with Google Fit folded in, Apple Health data supported on iOS, and APIs for Garmin, Whoop, and Oura. Bloomberg's Mark Gurman reported earlier this year that Apple has scaled back a comparable Health+ coaching service, with the feature now unlikely to launch. The Apple Watch SE starts at $249 and requires daily charging, and the Fitbit Air's $99 price with no mandatory subscription addresses a segment Apple does not cover.We also discuss the Apple Watch Series 12, which is shaping up to be an incremental upgrade. Bloomberg's Mark Gurmansaid in March that he does not expect any major design changes, and a significant redesign is now not expected until 2028.The leaker known as Instant Digital said this week that Touch ID, which appeared in leaked Apple code last year, has been deprioritized in favor of battery life improvements. DigiTimes previously reported an eight-sensor array on the back of at least one 2026 model, though blood pressure monitoring is said to be further out. A new chip is expected, with leaked code indicating a meaningful upgrade from the S10 used across the last three series, and watchOS 27 will be previewed at WWDC on June 8. Start your business with Shopify and get everything you need to sell online and in person. Start today at https://www.shopify.com/mac

Kim Wolfe is one of the few non-lawyer executives running operations at the top of corporate legal. With a Wharton MBA and a quantitative background, she leads legal administration at State Street. David Cowen sits down with Kim to unpack what executive-level legal ops looks like inside one of the world's most regulated industries, and the career advice that changed everything. Key Topics Covered: The non-lawyer operator archetype: How business operators in legal leadership are reshaping the function Banking's slower AI path: Why regulation means Kim is two steps behind Intel and HP, and okay with that Lawyer-to-lawyer training: Why pairing power users with hesitant adopters moves the needle Who owns training: Why 67 percent of legal ops says it belongs to them The career lesson: As long as I see you here, I cannot give you more The 5:30 AM discipline: Why two hours of solo thinking is Kim's most important investment Simulation training: Why flight-simulator-style learning may fix inconsistent mentorship

Google unveiled Googlebook, merging ChromeOS and Android into a unified laptop OS shipping this fall. WhatsApp launches Incognito Chat for private AI conversations. Anthropic's revenue run-rate is on track to hit $50B by end of June, and Anduril raised $5B at a $61B valuation. Google unveils Googlebook, its new laptop lineup featuring a unified OS merging ChromeOS and Android, with devices from Dell, HP, and others coming this fall (ZDNet) Google also unveiled Gemini Intelligence, bundling existing and new Gemini features, including task automation across apps and letting users vibe code Android widgets (The Verge) WhatsApp launches Incognito Chat, an AI chat mode built on Private Processing that Meta says lets users talk to AI without Meta being able to access the chats (Wired) Investor docs: Anthropic's revenue run-rate is on track to hit $50B by the end of June; Ramp says more of its customers now use Anthropic than OpenAI, a first (WSJ) Anduril raised a $5B Series H led by Thrive and a16z at a $61B valuation, up from $30.5B in June 2025, taking its total funding to $6.82B, and could IPO in 2027 (NYT) Richard Socher's Recursive Superintelligence raised $650M+ from GV, Greycroft, Nvidia, AMD, and others at a $4B valuation to pursue "recursive self-improvement" (NYT) Learn more about your ad choices. Visit megaphone.fm/adchoices

Most product decisions get made by analogy. Someone says, "This is how we've always done it," or "This is what the market expects," or "This is what the competition is doing." The room nods. The decision gets made. And buried somewhere in the middle of all of it is an assumption nobody checked. First-principles thinking is the discipline of identifying assumptions before the market finds them for you. By the end of this episode, you'll have the tools to strip any problem down to what's actually true and build answers that hold, even when the boardroom is watching, and the clock is running. What Is First Principles Thinking? First principles thinking is the practice of breaking a problem down to its fundamental truths, then building your solution up from what actually holds. Not from industry convention. Not from what worked last time. From what's actually true about the problem in front of you. The alternative is reasoning by analogy: doing what worked before, doing what competitors do, doing what the category expects. Analogy is faster and usually right. It fails badly when the thing that used to be true stops being true and nobody notices. Why Assumptions Go Unchecked In 2005, HP's CEO, Mark Hurd, stopped me in the hallway at Building 20 in Palo Alto and drilled me on HP's R&D funding. The metric he focused on was R&D as a percentage of revenue. He wanted HP's ratio to look more like Acer's. I pushed back. I argued we should be comparing ourselves to Apple, not Acer. Mark didn't hesitate. "We are not Apple, and we never will be." What stopped me in that moment wasn't the disagreement. It was the certainty. Nobody in the room questioned whether R&D as a percentage of revenue actually measured what we thought it measured. That metric had been in use for decades. Every competitor used it. Every analyst tracked it. It felt like bedrock. It wasn't. It was an inherited constraint that had calcified into a rule. R&D as a percentage of revenue tells you about accounting categories. It tells you nothing about what that spending produces, whether the right problems are being attacked, or whether innovation output is growing or shrinking. The assumption underneath the metric had never been tested. Nobody had ever asked whether comparing R&D ratios across companies with entirely different business models actually tells you anything meaningful. The cost of that unchecked assumption didn't show up in the next quarter. It showed up over the following decade. HP's innovation pipeline quietly drained, and the Fast Company "Most Innovative" recognition we'd earned three years running disappeared with it. One inherited metric, accepted as fact by an entire room of experienced people, making a generational decision. That's what derivative thinking actually costs. Not a bad quarter. A decade. The people in that room weren't careless. They were experienced. Experience is exactly what makes inherited assumptions feel like facts. The metric felt like a fact. It was a choice nobody remembered making. That's exactly what a first principles question would have caught. Nobody asked it. The Three Core Skills The three skills run in sequence, and each one depends on the one before it. The first, Strip the Assumptions, finds the inherited assumptions baked into how the problem was framed. From there, Test What Remains and Build Up takes what survived and builds your solution from what's actually true. Finally, When to Use First Principles tells you when the process is worth running in the first place. Skip ahead, and the later skills don't hold. Run them in order, and they compound.  Strip the Assumptions Before you can reason from first principles, you have to know what you're actually working with. Most problems arrive already carrying assumptions in how they're framed. Your first job is to find them. Steps to strip assumptions: Write the problem exactly as it was given to you. Don't improve the framing yet. Use their words. Underline every word that implies a constraint. "Must," "can't," "always," "never," "the only way to." Each one is a candidate. Ask, for each constraint: is this physically true, or is it inherited? A physical truth holds regardless of what you decide. An inherited constraint is someone's prior decision that calcified into a rule. Set the inherited constraints aside and restate what remains. This is the real problem. It's usually smaller and easier to solve than what you started with. Treat what survives as your design constraints. These are your real boundaries. Take this list into your brainstorming, and test every idea against what's on it, not against the assumptions you crossed out. This step takes 20 minutes when you do it honestly. Most teams skip it entirely, then spend months optimizing a solution to the wrong problem. Test What Remains and Build Up Not every constraint is an assumption. Some things are actually true: physics, unit economics, human behavior at scale. The goal isn't to pretend those constraints don't exist. It's to be precise about which reality you're dealing with. Steps to test what remains and build up: Take each surviving constraint and push on it. Ask: Is this true because it's physically impossible to change, or because changing it would be expensive, unfamiliar, or uncomfortable? Expensive and unfamiliar are not the same as impossible. Separate the hard limits from the soft ones. Hard limits are what's actually true: things that hold regardless of how the problem is reframed. Soft limits are negotiable. Label them clearly. Most teams never make this distinction and treat every constraint as if it were granite. State your hard limits in plain language.  Write it down. One sentence per hard limit. These are the actual boundaries your solution has to honor. Reason forward from what remains. Don't start from where the industry is and work backward to justify it. Now ask: what solution do the hard limits support?  That last step is where unexpected solutions come from. When you reason backward from convention, you arrive at a modified version of the existing answer. The shape is familiar because you started with it. When you reason forward from hard limits, you land somewhere the category didn't expect, because you weren't anchored to the shape of the existing answer. Solutions built this way often feel strange at first. People will question them. That discomfort is usually a signal you've found something real rather than something inherited. That's what reasoning from what's actually true produces, rather than reasoning from what everyone assumed. When to Use First Principles Before running the process, ask these four questions. One yes is enough. Has the environment this decision was built for changed significantly? Does every solution on the table feel like a variation of the same thing? Is the current approach inherited rather than chosen? Would a bad assumption here cost you more than an afternoon to find and fix? If all four are no, past experience is the right tool. Use it.  The 20-minute assumption-strip is cheap. The cost of skipping it isn't. The Assumption Reversal Exercise For this exercise, you will need a partner. Have them watch this video first. They need to know what an inherited assumption looks like before they can spot yours. Once you're both ready, grab the free First Principles Thinking Checklist at innovation.tools or find the link in the description. It gives you both a shared reference point before you start.  Here is how it works: Each person brings one real problem. Something current, with actual stakes. Not a thought experiment. The problem should be one you've been turning over in your mind without arriving at a satisfying answer. Work on your partner's problem, not your own. You are trying to find the assumptions baked into how they've framed it. They are doing the same for yours. The reason this works is that you can see their inherited constraints more clearly than they can. You're not inside their problem the way they are. Each person lists every assumption they can find in the other's problem. Write them down. Don't argue yet. Don't evaluate. Just surface as many as possible. Quantity matters here. The obvious assumptions are easy. Push past them. Take each assumption and reverse it. If the assumption is "this requires a significant budget," the reversal is "what becomes possible if it requires no budget?" If the assumption is "the customer won't accept a different format," the reversal is "what would we build if they would?" Don't ask whether the reversal is realistic. Ask what it opens up. Discuss what the reversals revealed. Not every reversed assumption leads somewhere useful. But one of them usually exposes a constraint that was never as fixed as it felt. That's the one worth following. The point of the reversal is simple. Some assumptions hold when you push on them, and some don't. You can't tell which is which until you try. The Long Game Every time you run this process and find something that didn't hold, you get faster at spotting them. The judgment about when to use it gets sharper. That's what improvement looks like in practice: not a dramatic flash of insight, but a practiced ability to find the assumption in the room before it finds you. The assumption that costs you most isn't the one you haven't thought of yet. It's the one you stopped questioning years ago.  Find your partner. Run the Assumption Reversal this week. That's where this starts becoming a skill. Subscribe for the next episode. It builds on this.

Jason Howell and Jeff Jarvis break down Google's Android Show, including Googlebook, the new Android-based laptop category with OEM partners like Dell, HP, and Lenovo, Gemini Intelligence as Android's new identity, and the AI Pointer feature co-developed with DeepMind.Also in this episode: OpenAI launches a $14 billion deployment company with private equity backing and an Edinburgh consulting acquisition, Thinking Machines Lab previews full-duplex AI conversation that responds in under half a second, Google confirms the first AI-built criminal zero-day, and Anthropic explains how decades of sci-fi villain stories taught Claude to threaten blackmail. Find every episode at aiinside.show. Note: Time codes subject to change depending on dynamic ad insertion by the distributor. 0:00 - Start 0:07:03 - Introducing Googlebook, designed for Gemini Intelligence 0:08:47 - Googlebook Is Google's New AI-Powered Laptop Platform Built on Android 0:09:09 - Reimagining the mouse pointer for the AI era 0:23:54 - A smarter, more proactive Android with Gemini Intelligence 0:28:49 - OpenAI launches AI consulting arm valued at $14 billion - OpenAI can't have incompetent AI consultants ruining the market, so bought its own 0:34:27 - Interaction Models: A Scalable Approach to Human-AI Collaboration 0:45:09 - Google says criminals used AI-built zero-day in planned mass hack spree 0:48:20 - OpenAI announces Daybreak initiative around Codex Security 0:48:33 - Anthropic says Claude's blackmail behavior came from fictional evil AI stories online 0:51:53 - Elon Musk's Grok Is Losing Ground in AI Race 0:53:46 - Threads tests a Meta AI integration that works similarly to Grok 100:54 - Digg tries again, this time as an AI news aggregator 1:05:37 - Princeton Mandates Exam Proctors After Fears of ‘Widespread' AI-Fueled Cheating Hosts: Jason Howell and Jeff Jarvis  Download and subscribe to AI Inside in audio and video: https://aiinside.show/  Support the podcast on Patreon for special perks: https://www.patreon.com/aiinsideshow. You'll get ad-free episodes, members-only Discord, T-shirts and stickers you love, and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Learn more about your ad choices. Visit megaphone.fm/adchoices

This edition of Circular Snapshots covers a lot of ground. Mexico passed landmark circular economy legislation in January — and it deserves far more attention than it got. We also look at Circle Economy's latest report, which puts a €25.4 trillion price tag on the value destroyed every year by our linear economy, and the EU Circular Economy Act as it heads toward autumn adoption. Plus a quick run through of four shorter stories: HP mining its own e-waste to build new laptops, the UK Packaging Pact launching with 100 founding organisations, a new fashion industry initiative to scale textile-to-textile fibre recycling, and fresh data on what's really driving the secondhand boom. Show notes:  Circularity Gap Report 2026 (Circle Economy): https://dashboard.circularity-gap.world/report/2026/cgr-2026-overview EU Circular Economy Act: https://www.ellenmacarthurfoundation.org/eu-circular-economy-act Mexico Enacts General Law for the Circular Economy: https://mexicobusiness.news/sustainability/news/mexico-enacts-general-law-circular-economy HP mining its own e-waste: https://www.fastcompany.com/91501080/hp-is-mining-its-own-e-waste-to-build-its-latest-laptops UK Packaging Pact launches: https://www.wrap.ngo/media-centre/press-releases/uk-packaging-pact-launches-unlock-progress-transforming-packaging Circular Fibre Collective launch: https://www.thefashionpact.org/industry-leaders-launch-the-circular-fibre-collective-to-scale-t2t-recycled-materials-by-2030/ ThredUp 2026 Resale Report: https://finance.yahoo.com/economy/articles/thredup-spots-worrisome-trend-consumer-150700654.html

(0:00) Intro (1:34) About the podcast sponsor: The American College of Governance Counsel (2:21) Start of interview  (3:20) Marie's origin story (5:19) Career Path in Law and Governance. Her time at HP and Agilent Technologies. (7:50) Transition to eBay  (9:57) Shareholder Activism and eBay's Story *CNBC clip with Ryan Cohen (14:42) Governance Roles and Board Memberships (16:50) Her teaching positions on the role of the General Counsel  (18:57) Chair and Director Succession (23:37) On separating Chair and CEO roles (25:44) Governance in Private Companies (30:40) The Impact of AI on Governance. She thinks of it in three buckets: 1) Customer/revenue opportunity; 2) from an enterprise wide standpoint; and 3) AI risks (34:36) Questions board members should ask management regarding AI opportunities and challenges (38:09) Energy Sector and AI *Marie serves on the board of Portland General Electric (43:10) Geopolitical Challenges in Business *reference to Meta-Manus China breakup (45:24) Building Trust in the Boardroom (48:30) Books that have greatly influenced her life: The Book of Alchemy, by Suleika Jaouad (2025) Phoenix in a Jade Bowl, by Bonnie Bongwan Cho Oh (her mother) (2013) Atomic Habits, by James Clear (2018) (50:32) Her mentors (52:38) Quotes that she thinks of often or lives her life by. (54:00) An unusual habit or an absurd thing that she loves. (56:00) The living person she most admires: Lisa Su. Marie Oh Huber has over 30 years of experience of strategic business, legal, regulatory and public policy experience in large global public technology companies, including eBay, Agilent Technologies, and HP. She currently serves on the board of Portland General Electric You can follow Evan on social media at:X: @evanepsteinLinkedIn: https://www.linkedin.com/in/epsteinevan/ Substack: https://evanepstein.substack.com/__To support this podcast you can join as a subscriber of the Boardroom Governance Newsletter at https://evanepstein.substack.com/__Music/Soundtrack (found via Free Music Archive): Seeing The Future by Dexter Britain is licensed under a Attribution-Noncommercial-Share Alike 3.0 United States License

This week, Dave speaks with John Santaferraro. John is the CEO and Head Research Analyst at Ferraro Consulting LLC. With 30 years of experience in AI, analytics, and data management, he brings a wealth of experiences as an industry analyst, marketing executive at HP and ParAccel, and strategic marketing consultant for companies like Google Cloud, SAP, HP, ThoughtSpot, Informatica, and dozens of startups. He is the host of The Digital Analyst podcast with over a million views in 32 episodes. John shares how AI is transforming retail, ecommerce, and digital strategy — from the shift from traditional data stacks to AI stacks, to the rise of agentic AI and AI-powered search.The conversation also explores how leaders can use AI as a strategic thought partner, why AI search is changing discovery and SEO, and what retailers need to rethink as commerce becomes increasingly AI-driven.Connect with John on LinkedInFollow Beyond the Shelf on LinkedInLearn More about It'sRapidGet the It'sRapid Creative Automation PlaybookTake It'sRapid's Creative Workflow Automation with AI surveyEmail us at sales@itsrapid.io to find out how to get your free AI Image AuditTheme music: "Happy" by Mixaud - https://mixaund.bandcamp.comProducer: Jake Musiker

Ossama El Samadoni leads GBM, one of the most respected technology organisations in the region, with over 300 employees, triple-digit million dirham revenue, and clients across the Middle East, Africa, Turkey and Russia. The disappointment that derailed his dream is exactly what built him. But this isn't a story about career pivots. It's a conversation that should make every business leader in this city sit up straight. Ossama has spent decades at the intersection of global technology and human vulnerability working with Dell, Oracle, HP, and IBM before taking the helm at GBM. He's seen cyber attacks quadruple during regional conflict. He's watched AI agents invent their own secret language when they detected they were being supervised. He's tracked state actors who wiped entire company systems without issuing a single delete command. And he's deeply worried that most leaders still don't understand what's already here. This is a rare conversation Ossama's first podcast and he gives everything. No corporate script. No polished PR lines. Just a trench fighter who trusts primary information over secondary noise, believes technology should serve human welfare not just profit, and will tell you plainly: it's not if you'll be attacked, it's when. Whether you're a founder, a CEO, or just someone trying to understand what AI is actually doing to our world this one will stay with you.   Timestamps:  0:00 – "A podcast virgin" Osama's first ever appearance 0:09 – Employees feeding company data into ChatGPT: the risk nobody talks about 2:11 – How generative AI actually works and why bias is already baked in  5:38 – The moment two AI agents invented their own secret language to hide from their supervisor  13:34 – Cyber-attacks quadrupled during regional conflict and why every company is a target 19:21 – How a demo system became a state actor's entry point  22:21 – The KPMG case: an entire system wiped with zero delete commands 25:56 – Password hygiene, the 14-day rule, and why you must never open junk mail in Outlook  28:39 – How to spot AI snake oil salesmen and the two questions that cut through the noise 30:13 – Deepfakes are already here and why trust will return to the room  47:10 – Made in Egypt, polished in UAE and why Dubai is harder than it looks  57:32 – If he started again at 21: invest in human welfare, not hype 59:35 – Leading from the trenches and the multiplier effect of great leadership  1:04:50 – Quickfire: rogue AI, the one question every CEO should ask, and more    Follow Spencer Lodge on Social Media: https://www.instagram.com/madeindubaipodcast/?hl=en https://www.facebook.com/profile.php?id=61586194260076 https://www.instagram.com/spencer.lodge/?hl=en https://www.tiktok.com/@spencer.lodge https://www.linkedin.com/in/spencerlodge/ https://www.youtube.com/c/SpencerLodgeTV https://www.facebook.com/spencerlodgeofficial/   Follow Ossama El Samadoni on Social Media:  https://www.linkedin.com/in/ossamae/ https://www.linkedin.com/company/gbm/ https://www.instagram.com/gbmmiddleeast/

Get the Winning AEO Playbook: https://clickhubspot.com/oksd Ep. 424 “I can't go a single second without someone asking me what the heck answer engine optimization is.” Kipp and Kieran have Beeri Amiel (Product at HubSpot and founder of XFunnel) and Aja Frost (Sr. Director of Global Growth and Paid at HubSpot) dive into the launch and demo of HubSpot's brand new AEO tool, built to track your visibility in answer engines and help you win the next evolution of search. Learn more on building your AEO strategy, measuring share of voice and sentiment, and using actionable insights to drive results your boss will love. Mentions Aja Frost https://www.linkedin.com/in/ajafrost/ Beeri Amiel https://www.linkedin.com/in/beeri-amiel/ HubSpot AEO Portal https://clickhubspot.com/aeo Dell https://www.dell.com/en-us HP https://www.hp.com/us-en/home.html Lenovo https://www.lenovo.com/ Get our guide to build your own Custom GPT: https://clickhubspot.com/customgpt Resource [Free] Steal our favorite AI Prompts featured on the show! Grab them here: https://clickhubspot.com/aip We're on Social Media! Follow us for everyday marketing wisdom straight to your feed YouTube: ​​https://www.youtube.com/channel/UCGtXqPiNV8YC0GMUzY-EUFg  Twitter: https://twitter.com/matgpod  TikTok: https://www.tiktok.com/@matgpod  Thank you for tuning into Marketing Against The Grain! Don't forget to hit subscribe and follow us on Apple Podcasts (so you never miss an episode)! https://podcasts.apple.com/us/podcast/marketing-against-the-grain/id1616700934   If you love this show, please leave us a 5-Star Review https://link.chtbl.com/h9_sjBKH and share your favorite episodes with friends. We really appreciate your support. Host Links: Kipp Bodnar, https://twitter.com/kippbodnar   Kieran Flanagan, https://twitter.com/searchbrat ‘Marketing Against The Grain' is a HubSpot Original Podcast // Brought to you by Hubspot Media // Produced by Darren Clarke.

Welcome back to Impact Theory with Tom Bilyeu. In today's episode, Tom Bilyeu and Drew dive deep into the wild landscape of current events, from the volatile swings in oil prices and energy crises to the behind-the-scenes machinations shaping global politics and markets. They tackle the real-world impact of economic shocks on everyday Americans, debate whether we're witnessing tactical negotiation or political theater in the ongoing U.S.-Iran conflict, and break down complex topics like bond yields, AI breakthroughs, and the rise of GLP1 drugs. You'll hear candid, sometimes skeptical takes on how world leaders are spinning narratives to sway both markets and minds, the strategic consequences of technological innovation, and how shifting economic realities are directly affecting businesses and jobs. The conversation goes philosophical, exploring the interplay between optimism, determinism, and the ever-present challenge of enacting real change—whether in your mindset, your business, or the world at large. Stay tuned as Tom Bilyeu and Drew blend big-picture analysis with actionable, real-world insights—cutting through the noise to get to the real impact beneath the headlines. 00:00 Intro 02:01 Gas Prices Surge, Energy Crisis Coming? 10:34 End of Operation Epic Fury 22:21 Bond Yield Spikes / Fed's Response 33:11 Affordability Crisis Messaging For Politicans 01:01:20 Coinbase Layoff 14% 01:07:00 MIT Give AI a HUMAN Body 01:10:20 A prompt of a screenshot of a screenshot of a screenshot 01:12:44 New AI Company SubQ Making Waves 01:21:22 South Korea's First Robot Monk 01:23:42 13% of Americans Take GLP-1 01:27:44 $1 Billion Ballroom 01:31:11 Chinese EV 01:35:59 Crowd funding Spirit Airlines 01:40:50 HP's New Printing Subscription Plan Blinkist: Start your free trial at https://blinkist.com/impact AT&T Business: Switch to AT&T Business at business.att.com Quince: Free shipping and 365-day returns at https://quince.com/impactpodMonetary Metals: Future-proof your wealth at https://monetarymetals.com/impactTruemed: Check your eligibility and start saving at https://truemed.com/impactShopify: Sign up for your one-dollar-per-month trial period at https://shopify.com/impactKetone IQ: Visit https://ketone.com/IMPACT for 30% OFF your subscription order What's up, everybody? It's Tom Bilyeu here: If you want my help... STARTING a business: join me here at ZERO TO FOUNDER:  https://tombilyeu.com/zero-to-founder?utm_campaign=Podcast%20Offer&utm_source=podca[%E2%80%A6]d%20end%20of%20show&utm_content=podcast%20ad%20end%20of%20show SCALING a business: see if you qualify here.:  https://tombilyeu.com/call Get my battle-tested strategies and insights delivered weekly to your inbox: sign up here.: https://tombilyeu.com/ ********************************************************************** If you're serious about leveling up your life, I urge you to check out my new podcast, Tom Bilyeu's Mindset Playbook —a goldmine of my most impactful episodes on mindset, business, and health. Trust me, your future self will thank you. ********************************************************************** FOLLOW TOM: Instagram: https://www.instagram.com/tombilyeu/ Tik Tok: https://www.tiktok.com/@tombilyeu?lang=en Twitter: https://twitter.com/tombilyeu YouTube: https://www.youtube.com/@TomBilyeu Learn more about your ad choices. Visit megaphone.fm/adchoicesSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Welcome back to Impact Theory with Tom Bilyeu. In today's episode, Tom Bilyeu and Drew dive deep into the wild landscape of current events, from the volatile swings in oil prices and energy crises to the behind-the-scenes machinations shaping global politics and markets. They tackle the real-world impact of economic shocks on everyday Americans, debate whether we're witnessing tactical negotiation or political theater in the ongoing U.S.-Iran conflict, and break down complex topics like bond yields, AI breakthroughs, and the rise of GLP1 drugs. You'll hear candid, sometimes skeptical takes on how world leaders are spinning narratives to sway both markets and minds, the strategic consequences of technological innovation, and how shifting economic realities are directly affecting businesses and jobs. The conversation goes philosophical, exploring the interplay between optimism, determinism, and the ever-present challenge of enacting real change—whether in your mindset, your business, or the world at large. Stay tuned as Tom Bilyeu and Drew blend big-picture analysis with actionable, real-world insights—cutting through the noise to get to the real impact beneath the headlines. 00:00 Intro 02:01 Gas Prices Surge, Energy Crisis Coming? 10:34 End of Operation Epic Fury 22:21 Bond Yield Spikes / Fed's Response 33:11 Affordability Crisis Messaging For Politicans 01:01:20 Coinbase Layoff 14% 01:07:00 MIT Give AI a HUMAN Body 01:10:20 A prompt of a screenshot of a screenshot of a screenshot 01:12:44 New AI Company SubQ Making Waves 01:21:22 South Korea's First Robot Monk 01:23:42 13% of Americans Take GLP-1 01:27:44 $1 Billion Ballroom 01:31:11 Chinese EV 01:35:59 Crowd funding Spirit Airlines 01:40:50 HP's New Printing Subscription Plan Blinkist: Start your free trial at https://blinkist.com/impact AT&T Business: Switch to AT&T Business at business.att.com Quince: Free shipping and 365-day returns at https://quince.com/impactpodMonetary Metals: Future-proof your wealth at https://monetarymetals.com/impactTruemed: Check your eligibility and start saving at https://truemed.com/impactShopify: Sign up for your one-dollar-per-month trial period at https://shopify.com/impactKetone IQ: Visit https://ketone.com/IMPACT for 30% OFF your subscription order What's up, everybody? It's Tom Bilyeu here: If you want my help... STARTING a business: join me here at ZERO TO FOUNDER:  https://tombilyeu.com/zero-to-founder?utm_campaign=Podcast%20Offer&utm_source=podca[%E2%80%A6]d%20end%20of%20show&utm_content=podcast%20ad%20end%20of%20show SCALING a business: see if you qualify here.:  https://tombilyeu.com/call Get my battle-tested strategies and insights delivered weekly to your inbox: sign up here.: https://tombilyeu.com/ ********************************************************************** If you're serious about leveling up your life, I urge you to check out my new podcast, Tom Bilyeu's Mindset Playbook —a goldmine of my most impactful episodes on mindset, business, and health. Trust me, your future self will thank you. ********************************************************************** FOLLOW TOM: Instagram: https://www.instagram.com/tombilyeu/ Tik Tok: https://www.tiktok.com/@tombilyeu?lang=en Twitter: https://twitter.com/tombilyeu YouTube: https://www.youtube.com/@TomBilyeu Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode, Madelyn O'Farrell chats with Jay Allardyce, Chief Product Officer at Octave (part of Hexagon), about how integrated data, design, and operations can transform industrial supply chains. Jay traces his path through HP, GE, Uptake, Google Cloud, and private equity–backed software to Octave, where he oversees tools that span the lifecycle of major infrastructure from design and build to operate and protect, including public safety and 911 systems. Using Octave's partnership with the Visa Cash App Racing Bulls Formula 1 team, he explains F1 as a “traveling city” and a live example of an integrated, feedback-rich supply chain and digital thread, in contrast to the value lost at each handoff in most industries. He argues that reliability and cost efficiency start at design and depend on context-rich digital twins and continuous feedback loops, not just more data. Jay also highlights the importance of thoughtful AI adoption, praising safety-focused approaches like Anthropic's and stressing that future, software-defined supply chains will be anticipatory networks enabled as much by better human questions and mindset shifts as by new technology. Don't miss this great conversation. Highlights from their conversation include: Jay's Career Journey Across HP, GE, Uptake, and Google (0:49) What Octave Is: Design, Build, Operate, Protect Software Portfolio (3:23) Octave's Partnership With Formula 1 and Visa Cash App Racing Bulls (5:45) Treating F1 as a “Traveling City” and Supply Chain Showcase (6:20) Digital Thread, Digital Twins, and Supply Chain Feedback Loops (8:40) Cost of Broken Digital Threads and 1x–10x Value Loss at Handoffs (9:55) Reliability as System Context, Not Just Single-Part Failure (11:46) Step Back From the Data: First Principles and 360-Degree Asset View (13:30) How To Ground AI Initiatives Before Spinning Up Infrastructure (16:30) Society's Need to Retrain How We Ask Questions of AI (18:50) Future Vision: Anticipatory, Software-Defined, Networked Supply Chains (20:08) Dynamo Ventures is a venture firm backing founders upgrading the physical economy. As intelligence moves into critical infrastructure and technology collides with physics, industry is entering a new era of transformation - the industrial renaissance. Born from the dirt and grit of supply chains and shaped by operations, not spreadsheets, Dynamo focuses on the complex realities of building in the real world. We invest in companies transforming infrastructure, manufacturing, logistics, transportation, and the systems that power global commerce. Dynamo works closely with founders who combine ambition with a bias to action, bringing a builder mindset to venture capital through deep operational insight, systematic pressure-testing and hands-on partnership. Our purpose is simple: to back the relentless shaping the industrial renaissance. Learn more at www.dynamo.vc Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

 When it comes to thriving, listening to our inner compass is crucial. Living out our purpose alongside others can only really happen when we use the tool of discernment. But that can often feel kind of daunting. It's hard to know where to begin.  Bonnie Wan has developed a three-step process for tuning into our true desires – and then putting them into action.  Bonnie Wan is a strategist, bestselling author and creator of The Life Brief: A Playbook for No-Regrets Living. She took the idea of a brief from her marketing campaigns, and repurposed it for our creative and spiritual lives. Bonnie shares her challenging experience writing her own life brief – and the surprising path it led her down.  Bonnie walks us through how to apply the life brief to a big decision, which begins with allowing our human messiness to come to the surface. And more often than not, living out our purpose is relational.  Bonnie has over 30 years of experience guiding major companies. At advertising agency Goodby Silverstein & Partners, Bonnie has led strategy for BMW, Comcast/Xfinity, Frito-Lay, HP, Kraft-Heinz, and PepsiCo. She also led award-winning campaigns fighting racial injustice, child sex trafficking, cyberbullying, college campus rape, and gender inequality.  With & For is a podcast of the Thrive Center, an applied research center that exists to catalyze a movement of human thriving, with and for others through spiritual health.  Learn more at thethrivecenter.org. Follow us on Instagram @thrivecenter Follow us on LinkedIn @thethrivecenter Dr. Pamela Ebstyne King hosts With & For, and is the Executive Director of the Thrive Center and the Peter L. Benson Professor of Applied Developmental Science at the School of Psychology & Marriage and Family Therapy at Fuller Seminary. Follow her @drpamking. About With & For Host: Pam King Senior Director and Producer: Jill Westbrook Operations Manager: Lauren Kim Social Media & Graphic Designer: Wren Juergensen Senior Producer: Clare Wiley Executive Producer: Jakob Lewis Produced by Great Feeling Studios Special thanks to the team at Fuller Studio and Fuller Seminary's School of Psychology & Marriage and Family Therapy. The podcast was made possible through the support from the John Templeton Foundation. The opinions expressed in this publication are those of the host and guests, and do not necessarily reflect the views of the John Templeton Foundation.

Success Audit as discussed on the show: https://podcast.saahilmehta.com/businessSaahil is dedicated to helping ambitious leaders and entrepreneurs scale their success without sacrificing their health, relationships, or inner peace. His approach to conscious leadership encourages individuals to redefine what achievement means, shifting from constant striving to intentional, fulfilling progress.Over the years, Saahil has coached and spoken at organisations such as HP, Dell, Bank of America, P&G, 24x7.ai, Petrochem, Summit Capital, Tata Group, Thomas Cook, TiE, EO, and YPO. As a member of Dr Marshall Goldsmith's 100 Coaches, he contributes to a global leadership movement focused on clarity, purpose, and sustainable growth.Saahil supports founders, CXOs, and next-generation entrepreneurs to navigate moments of transition, pressure, and uncertainty. His work helps leaders move from overwhelm to direction, enabling them to perform at their best without burning out or compromising what matters most.His philosophy is drawn from lived experience. As a mountaineer, Saahil has climbed some of the world's iconic peaks, including Kala Patthar (5,644m), Mount Elbrus (5,642m), Mount Kilimanjaro (5,895m), and Chopicalqui (6,354m). The mountains taught him a principle that guides his coaching today: the journey should strengthen you, not exhaust you. Connect with Saahil Mehta:Website: https://www.saahilmehta.com Success Audit: https://podcast.saahilmehta.com/business LinkedIn: https://www.linkedin.com/in/saahilmehta Facebook: https://www.facebook.com/saahilmehtaofficial YouTube: https://www.youtube.com/channel/UCxy4r8jsNSdrm3JcEdzCUIQ TurnKey Podcast Productions Important Links:Guest to Gold Video Series: www.TurnkeyPodcast.com/gold The Ultimate Podcast Launch Formula- www.TurnkeyPodcast.com/UPLFplusFREE workshop on how to "Be A Great Guest."Free E-Book 5 Ways to Make Money Podcasting at www.Turnkeypodcast.com/gift Ready to earn 6-figures with your podcast? See if you've got what it takes at TurnkeyPodcast.com/quizSales Training for Podcasters: https://podcasts.apple.com/us/podcast/sales-training-for-podcasters/id1540644376Nice Guys on Business: http://www.niceguysonbusiness.com/subscribe/The Turnkey Podcast: https://podcasts.apple.com/us/podcast/turnkey-podcast/id1485077152