Podcasts about Vector

Crew breaks down a packed week in mobile and games. AppLovin's stock craters despite the SEC closing its inquiry with no action, Unity sells Supersonic to Tripledot for a shockingly low $40 million, and Take-Two's GTA VI presales are on fire even as its mobile business slows. Topics Covered:• AppLovin's Q2 earnings and stock drop despite growth• Unity's Vector model closing the gap with AppLovin• Unity selling Supersonic to Tripledot for $40M• Take-Two's Q2 earnings, Zynga portfolio trends and GTA VI presales• GTA VI's Netflix trailer exclusive• Blizzard's leaked internal email and its quiet turnaround• Ubisoft Barcelona's layoffs and the birth of Puzzle Mage• Royal Smash and the rise of cannon physics puzzlesCHAPTERS:02:06 Spider-Man numbers debate03:23 Why Spider-Man wins03:53 Odyssey movie review05:28 Seattle roundtable recap07:34 Audience Qs and Roblox08:55 Corrections and Royal Match12:08 AppLovin earnings breakdown18:52 Unity Vector and D2827:14 Unity sells Supersonic34:21 Unity Supersonic Bargain35:09 Take Two Bookings Breakdown36:19 Zynga Portfolio Reality Check39:07 Old Games vs New Hits46:36 GTA VI Preorders and Netflix49:41 Blizzard Comeback Email53:31 Ubisoft Barcelona Fallout56:05 Royal Smash New Subgenre01:00:45 Farm Team and Monetization01:08:51 Wrap Up and Banter

Send us Fan MailWe catch up as the full crew reunites, starting with summer ramp misery and the real-world limits heat puts on flying decisions. Then we dig into the Synaptic A220 release, why it sparked so much drama, and what it teaches about aircraft nuance, developer QA, and how airlines and engines shape what we see in the sky. • summer heat, humidity, and density altitude affecting real flying motivation and safety margins • first impressions of the Synaptic Airbus A220 in Microsoft Flight Simulator, including performance and handling feel • why streamer-first rollouts can confuse users when a complex aircraft is both new and buggy • learning the A220's procedures, automation quirks, and ILS behavior instead of relying on habits from Boeing or Airbus staples • why stable releases come from strong QA programs and broad beta testing across hardware and add-ons • marketplace-first strategy, piracy concerns, patch cadence, and how perception fuels Discord meltdowns • real-world A220 route presence, fleet replacement questions, and the “in-between” role versus regional and A320-family aircraft • Pratt & Whitney PW1500G geared turbofan contamination issue and the ripple effects of engine shortages • GSX jetway and ground equipment realism frustrations and what still breaks immersion • Vector 787 alpha notes and why airline economics keep pivoting toward fuel efficiency • Alaska Airlines-style milk runs as a perfect sim use case for scenery and procedures • Black Square Commander 114 impressions and why cockpit variety matters • Leonardo Mad Dog nostalgia, mechanical design advantages, and the quirks that still trip us up Keep a lookout at flighttepexpo.com as well as visit our our website and our socials for updates. if anybody's interested, they can join CTP Aviation on JetcardWebsite: www.closedtrafficpodcast.comFacebook: @ClosedtrafficpodcastFollow us on Patreon: https://patreon.com/closedtraffic

Domark and Vektor Grafix's 1988 Amiga port of Star Wars converts Atari's legendary vector arcade coin-op into fluid raster graphics with digitised sound samples and mouse-controlled precision.

Domark and Vektor Grafix's 1988 Amiga port of Star Wars converts Atari's legendary vector arcade coin-op into fluid raster graphics with digitised sound samples and mouse-controlled precision.

One way or another.Learn more at https://critrole.com/unend-season3/ SEASON 3 DESCRIPTION:Yet again, the Ship's crew of cosmic explorers have discovered something they never set out to find. Their desperate attempt to get back on course has only pulled them deeper into the maze of reality, where new threats and revelations await them behind every door. Even if they somehow manage to make it back home… who will they be by the time they get there?UNEND SERIES DESCRIPTIONSeveral decades after the events of MIDST and Moonward, a supernatural ship and a remarkable crew set forth on an expedition to explore the highest heights, deepest depths, and furthest reaches of the known cosmos. But their journey is fraught with peril as they discover truths and realities far stranger than any of them could ever have imagined.JOIN THE FOLD or BECOME A BEACON MEMBERIf you want to receive UNEND episodes two weeks early and uninterrupted by ads AND gain access to lore expanding bonus content, join Beacon at https://beacon.tv or become a Fold Member at https://midst.co PRODUCTIONUNEND is created, written, produced and narrated by Third Person UNEND Theme Song by XenSenior Producer: Maxwell JamesLead Animator: Max SchapiroLore Keeper: Jared DeiroPost Production Coordinator: Bryn HubbardART CREDITS:UNEND Series Key Art by Julie Dillon || @juliedillonartUNEND Season 3 Art by Nate Gonzalez || @natemoonlife with Character Art by Lyadrielle || @LyadrielleUNEND Logo by Aaron MonroyUNEND is a Metapigeon production in partnership with and distributed by Critical Role Productions#UNEND #Season3 #MidstCosmos #CriticalRole Learn more about your ad choices. Visit megaphone.fm/adchoices

Strong public health systems depend on collaboration like partnerships across agencies or coordinating responses to emerging health threats. In this episode, ASTHO Senior Analyst for State Health Policy, Beth Giambrone, discusses a recent ASTHO Health Policy Update that examines how states are approaching vector-borne disease policy through surveillance, reporting requirements, education, and cross-agency coordination.  Then, ASTHO Senior Analyst for Medicaid and Health Systems Partnerships, Orobosa Idehen, introduces a new Medicaid Oversight Governance Map designed to help state health agencies better understand their governance structures, strengthen relationships with Medicaid partners, and identify opportunities to improve population health. Together, these conversations highlight how thoughtful governance, collaboration, and strategic policy making can help public health agencies make better use of limited resources while responding to evolving public health challenges.Medicaid Oversight Governance Map | ASTHOImproving Public Health Communication for Effective STI Programs | ASTHO

#376 | Eight marketers. Two minutes each. One live bracket to crown the best-performing paid ad play. We brought back the Blitz Exit Five Live session format - this time for the Paid Ads Playoff: a head-to-head paid ads showdown, where marketers pitch their single best ad from 2026 in real time to our live voting audience. The plays cover a lot of ground: scroll-stopping creative for an unfamiliar category, testing TV as a full-funnel channel, measuring out-of-home, a 9-minute LinkedIn video that beat every short clip, incentivized demo offers, ChatGPT ads, fighting Google's AI Overviews in paid search, and the most creative ad creative you've ever seen. Presenters include Alexander Goodwin (Fingerprint), Stefanie Wlotzki (SurveyMonkey), Jake Newby (Lendio), Anthony Blatner (Speedwork), Dylan Wingrove (Pacvue), Kenna  Rooney (EasyLlama), and Shlomo Genchin (Unbored.com), co-hosted by Jess Cook of Vector.Timestamps (00:00) - - Welcome to the Paid Ads Playoff format (05:32) - - Making an unfamiliar B2B category scroll-stopping on paid social (08:04) - - Testing TV as an always-on demand channel (10:23) - - Measuring out-of-home ads with control markets (13:03) - - Why a 9-minute LinkedIn video beat every short clip (15:48) - - Q&A: targeting, TV attribution, and matching creative to the platform (25:49) - - Incentivized demos and gift-card offers that convert (28:32) - - Testing ChatGPT ads and shifting budget out of Google (32:40) - - Fighting back against Google's AI Overviews in paid search (34:50) - - The soap opera ad and turning boring software into a story (48:13) - - Tracking signals and structuring content for a long-form ad (55:05) - - The analogy framework behind the year's best-performing ad Join 50,0000 people who get Dave's Newsletter here: https://www.exitfive.com/newsletterLearn more about Exit Five's private marketing community: https://www.exitfive.com/***Brought to you by:Zoom Webinars & Events – The virtual event platform built to help B2B marketers run webinars that actually drive pipeline, with branded registration pages, live engagement features, and built-in tools to repurpose sessions into clips and content. Learn more at zoom.com/exitfive.Customer.io - An AI powered customer engagement platform that help marketers turn first-party data into engaging customer experiences across email, SMS, and push. Learn more at customer.io/exitfive.Vector - A contact-level ads platform that lets you build audiences from actual people on your site, clicking your ads, and checking out your competitors. Learn how to build an ABM program that scales at vector.co/exitfive.Join us in Stowe, Vermont for Drive 2026 - three days away from your desk to learn what's working in B2B marketing from the people who are actually doing it. Grab your ticket at exitfive.com/drive.Walker Sands - An integrated B2B marketing and growth services agency that helps marketing leaders turn strategy into measurable business impact through their Outcome-based Marketing model. Learn more at walkersands.com/exitfive.***Thanks to my friends at hatch.fm for producing this episode and handling all of the Exit Five podcast production.They give you unlimited podcast editing and strategy for your B2B podcast.Get unlimited podcast editing and on-demand strategy for one low monthly cost. Just upload your episode, and they take care of the rest.Visit hatch.fm to learn more

It was 2005 and my first season coaching. Fresno State was playing USC and that night I learned that the phrase ‘Anybody, Anytime, Anywhere' was real.And today, with Fresno State entering the new look Pac-12, that phrase is at the heart of my conversation with head coach Matt Entz.Welcome to today's episode of THE DAWN, a collaboration between Y-Option and the Pac-12.Matt Entz first fell for Fresno State on a Saturday night in the Midwest, a young assistant watching the late ESPN game, checkerboard end zones on the screen, Pat Hill pacing the sideline. He'd GA'd for Coach Hill's old line coach, so he had a rooting interest built in, and it stuck. Now he leads this proud program and seventeen months into the job, he calls it Midwest California, blue collar mentality echoing the small Iowa town he grew up in. It didn't take long to see the same thing in his own roster, blue collar young men who grew up dreaming about playing for the Bulldogs.That dream now comes with a new league, the re-imagined Pac 12, and Coach Entz can feel the excitement building as September closes in. There's pride in it and pressure too, elevating a program and an athletic department that's now in Pac-12.Y-Option: College Football with Yogi Roth is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.THE DAWN debuted July 1 across the Pac-12's YouTube and Pac-12 Insider, the league's 24/7 FAST channel. The series culminates with a finale featuring never-before-seen behind-the-scenes content from the building of this new league. It drops in August, right before the season kicks off. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.y-option.com/subscribe

Deze Einde van de Week Live is ook te bekijken op https://youtu.be/wtGaIWPub4s Deze talkshow wordt mede mogelijk gemaakt door MSI. Alle meningen in deze video zijn onze eigen. MSI heeft inhoudelijk geen inspraak op de content en zien de video net als jullie hier voor het eerst op de site. Klaar om het weekend te betreden? Wij wel. Hopelijk komt het zonnetje ook even om de hoek kijken. En anders duiken we gewoon lekker in de back catalogue. Wij gaan er in ieder geval voor. En dat laten we je voelen in een nieuwe editie van Einde van de Week Live. Huey, JJ en Koos zitten klaar om jou helemaal bij te praten over alles wat er de laatste dagen gebeurd is. Een onderwerp dat aan bod komt, is de nieuwe story trailer en het nieuwe gezicht van Wolverine. Die leverden wat gefronste wenkbrauwen op. En dan vooral het gezicht van Wolverine. Gebeurde dat ook bij de drie heren? Koos mocht alvast aan de slag met de naval content van het vierde seizoen van Battlefield 6. Hoe beviel de speelsessie? Dit alles en meer zie en hoor je voorbijkomen in de Einde van de Week Live van vrijdag 24 juli 2026. Het smoelwerk van Wolverine zorgt voor gefronste wenkbrauwen Andere onderwerpen die langskomen zijn onder andere de mod scène van Starfield die ‘seemless’ vliegen mogelijk maakte, Miyamoto over de vele remakes en remasters van Nintendo en Amazon over wie de volgende 007-game mag gaan maken. Check de scherpe prijs van de krachtige Vector 16HX gaming laptop van MSI MSI zet deze week de Vector 16 HX AI. Deze krachtige gaming laptop heeft onder de motorkap een AMD Ryzen 8940HX processor, een NVIDIA GeForce RTX 5080 videokaart, 16GB RAM intern geheugen, een 1TB SSD, een 16” 240Hz QHD+ Display, een 24-zone RGB toetsenbord. Deze laptop gericht op hardcore gamers is hier scherp geprijsd verkrijgbaar bij MeGekko. Check de puike Arctis Nova headsets van SteelSeries SteelSeries is al een aantal jaar de vaste leverancier van onze headsets. Een parthership waar we meer dan tevreden mee zijn omdat hun gear top notch is en lekker over de oortjes valt. Hun Artic Nova lijn (metname de Arctis Nova Pro Omni) biedt alles wat een gamer zich kan wensen. Een optimaal geluid, een fijne mic, talloze instellingen via de Arctis companion-app, veel draagcomfort en als ze draadloos zijn, een lange batterijduur. Hier vindt alle info en prijzen van deze headsets. Vandaag hebben we een keer leuke verrassing op het hoofd. De Arctis Nova 5 Wireless South Park Edition headset. Wat ons betreft een leuke cadeau voor de liefhebbers van een van onze favo tekenfilm series. Info en orijs kun je hier vinden.Wil je adverteren bij de podcast Gamekings óf misschien bij een andere podcast van ILVY Network? Mail dan naar management@ilvy.com en/of kijk even op de website : https://ilvy.com/podcastSee omnystudio.com/listener for privacy information.

Tune in for the latest edition of the Search Pod, as our host Elliott is joined by Dylan Hoyle, founder of Vector.Elliott & Dylan discuss moving over to the US at the worst time, scaling a startup from a small office, endless opportunity in tech recruitment and much more

People will notice how you behave in certain situations, which is why we're slandering Nancy Reagan, rifling through our dad's office, accessing the secret bookshelf, learning how to be a swashbuckler, raiding the emergency supplies, freshening up to reboot the day, yup'n it up, having a Vector-off, playing hide-and-seek, seeking a pervert hole, wondering if we have electricity, consuming pickled turnips, dressing up the set, knitting on the bed upstairs, realizing this kid is granny, eating berries so we can know something, leaving papers all over the place, and drinking alone at the tavern. My dad always takes the good stuff. 00:00:00 Where Did You Come From 00:02:07 Intro 00:03:24 Exploring Dad's/Dyne's Office 00:13:50 Outside on Sky Pirate Isle 00:32:07 Pirate Isle Houses 00:47:28 Mom's House 00:50:08 Dusk 00:56:42 Real net 01:01:31 Outro Patreon: patreon.com/retroam Bluesky: @retrogradeamnesia.bsky.social YouTube: www.youtube.com/@RetrogradeAmnesia E-Mail: podcast@retrogradeamnesia.com Website: www.retrogradeamnesia.com  

「【新宿3丁目】「参謀BAR新宿」にて「VECTOR BREWING」の飲み比べ付きクラフトビール交流会が7月21日に開催！」　新宿三丁目にある「参謀BAR新宿」では、人気ブルワリー「VECTOR BREWING」の飲み比べ付きクラフトビール交流会を2026年7月21日(火)に開催。詳細をご紹介します。7月21日(火)に開催される飲み比べ付きクラフトビール交流会『【参謀BAR Night】クラフトビールを片手に、ゆるく語ろう』は、経営者コミュニティ「参謀」を運営する株式会社経営参謀により、「飲みながら、クラフトビールというビジネスを知る」がテーマのテイスティングと交流を組み合わせたイベント。

In this episode of Tank Talks, host Matt Cohen sits down with Paul Ziadé, CEO and co-founder of North Vector Dynamics, a Calgary-based company building full-spectrum precision missile systems for Canada and its allies. A former tenured professor at the University of Calgary turned defence entrepreneur, Paul brings a deeply personal and historically literate perspective to the Canadian defence landscape. He shares his family's story of displacement from Lebanon and Armenia, and how that legacy of resilience informs his mission to build a sovereign missile capability for Canada.Paul offers a frank assessment of Canada's defence complacency, arguing that the culture of risk-aversion is “upstream of everything.” He explains why the obsession with “dual-use” investing is holding the country back, why pure-play defence innovation is critical, and how startups like his can deliver capability faster than the traditional 10-year procurement cycle. He also breaks down the massive opportunity presented by the Golden Dome NORAD modernization and why Canada must participate not just as a buyer, but as an active builder.Whether you're a defence founder navigating the Canadian ecosystem, an investor trying to understand the shift in risk capital, or a policy wonk watching the Arctic heat up, Paul Ziade delivers the kind of straight talk that cuts through the noise.From Civil War to Canadian Soil (00:01:20)* Paul's upbringing as the child of Lebanese-Armenian immigrants who fled civil war and genocide.* How his parents' appreciation for Canada's peace and rule of law instilled a deep sense of responsibility.* The household rule: “Laziness was never an option” , competitive soccer, piano, student government, and French schooling.The Kennedy Space Center Spark (00:04:00)* How a grade 10 family trip to the Kennedy Space Center “lit the fuse” for his obsession with rocketry.* Touching the Saturn V and realizing what human ingenuity could achieve.* Why he needed a strong goal to anchor his focus and drive.Academia to Entrepreneurship (00:05:38)* Why he left a tenured professorship after 10 years at the University of Calgary.* The mindset shift: moving from committee-driven, overthinking academic life to the velocity and action-mentality of startups.* How academia trained him to be a better communicator, but startup life gave him instant feedback on every decision.The North Vector Vision (00:08:53)* The mission: precision missile systems on every continent protecting allies and Canada.* Full-spectrum air defence , from low-and-slow drones to hypersonic threats.* Assembling the “Avengers” team from his university labs, including co-founders Craig (aerospace research chair) and Colin (former TA).The Supply Chain Blind Spot (00:10:36)* Canada's massive gap in energetics , from solid rocket motors to warheads, and upstream chemical synthesis (RDX, HMX, C4 propellants).* Why “vertically integrated” doesn't always mean what people think.* The need for government signals to encourage private companies to take the risk and spool up.Defence Investing: Then vs. Now (00:14:48)* In 2022, no one wanted to look at North Vector , squeamishness around defence was rampant.* The gap between the narrative and reality on the ground in Canada.* Why most Canadian investors are still obsessed with “dual-use” investing, which Paul argues is historically misguided.The Dual-Use Delusion (00:29:31)* The problem with forcing every defence tech to have a civilian application.* Historical examples: GPS (missile guidance), duct tape (waterproof ammunition sealing).* The parallel to basic science , pure math and quantum mechanics funded with no immediate application, yet yielding enormous real-world benefits.Canada vs. The U.S. (00:18:43)* Honest admission: it's easier to build defence tech south of the border.* Why North Vector chose to stay in Canada despite the friction.* Canada as a “frontier market” , a massive opportunity for those willing to build.* The debt of gratitude to the country that gave his family refuge.ACDC & The 70% Target (00:21:20)* Paul co-chairs the Alliance of Canadian Defence Companies (ACDC) , now nearly 200 members.* The goal: champion Canadian-owned, Canadian-controlled companies and advocate for fast contracts.* Holding the government accountable to the Defence Industrial Strategy (DIS) without displacing primes.In-Q-Tel & The Culture Shift (00:23:16)* What a Canadian version of In-Q-Tel would need to get right.* The critical need: give delegated authorities permission to take risks and accept failure as part of the process.* Moving money out the door faster to small, scrappy startups that could win big.The Golden Dome Opportunity (00:27:13)* Canada's lack of commitment to NORAD modernization and the Golden Dome.* The upside: a $500B–$1.2T opportunity.* Paul's proposed win-win: “Give Trump the $61B win, but ensure $40B goes to Canadian firms.”* How Canada can participate as an active builder, not just a buyer.About Paul ZiadéPaul Ziadé is the CEO and co-founder of North Vector Dynamics, a Calgary-based company building full-spectrum precision missile systems for Canada and its allies. A former tenured professor at the University of Calgary, Paul holds deep expertise in high-speed propulsion and aerodynamics, having spent over a decade in academia before pivoting to the startup world. He is also the co-chair of the Alliance of Canadian Defence Companies (ACDC) , advocating for Canadian-owned, Canadian-controlled defence firms. A first-generation Canadian with roots in Lebanon and Armenia, Paul brings a historically literate perspective to national security and the urgent need for Canada to build sovereign defence capability.Connect with Paul Ziadé on LinkedIn: https://www.linkedin.com/in/paul-ziade/Visit North Vector Dynamics' website: https://www.northvectordynamics.com/Learn more about ACDC: https://www.alliancecanada.com/Connect with Matt Cohen on LinkedIn: https://ca.linkedin.com/in/matt-cohen1Visit the Ripple Ventures website: https://www.rippleventures.com/ This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit tanktalks.substack.com

Unity just made direct-to-consumer payments free for every developer on its IAP SDK. No take rate, no fees. So what's the catch?I sat down with Steve Ganem, VP of Product at Unity, to unpack the real strategy — and it turns out the story isn't about payments at all. It's about data.Steve brings a rare vantage point: 19 years in games (EA, Activision's Tony Hawk franchise, 11 years running his own studio through the free-to-play transition), then a decade at Google Analytics. In this conversation we cover why "free" is a rational move rather than a giveaway, why going D2C without Unity could actually cost developers ad signal, the conversion tradeoff most coverage skips (web checkout is harder than Face ID), and how this connects to Unity's advertising business and its AI platform, Vector.Whether you're a developer weighing D2C, a PM modeling the conversion math, or an investor watching Unity's turnaround, this one goes well past the announcement.

Send us Fan MailThe COVID-19 pandemic proved vaccine platforms can move at unprecedented speed. It also revealed how dangerously narrow the world's response really was, built almost entirely on a single technology.Dr. Dan Barouch and Kris Brown, Co-Founders of Vector Sciences, join host David E. Williams to discuss why durable pandemic preparedness depends on having multiple vaccine platforms rather than just one, how their Rheovax platform uses mucosal immunity delivered through the nose to block transmission rather than just prevent severe disease, and why public trust in vaccines depends on being honest about what each technology can and cannot actually do.

Watch the Engineering Director Promotion Plan (free): https://youtu.be/ZrRe3O8KHSQ Fear doesn't go away. You just learn to turn the volume up on what matters more. Zach sits down with former F-16 fighter pilot Lt. Col. Waldo Waldman to talk about flying 65 combat missions while battling claustrophobia, why courage isn't the absence of fear, and how engineering leaders build the kind of resilience that actually holds up under pressure. Waldo shares the "why before you fly," the trap of being all thrust and no vector, and why nobody great is doing it solo. You'll learn: Why "envisioning the victory" and knowing who you're flying for pulls you through fear faster than willpower How to tell the difference between real growth and just staying busy in your comfort zone Why courage is love in action — and how that reframes the hard calls you make as a leader The wingman principle: who you need in your cockpit before the missiles start flying

#367 | Dave sits down with Jess Cook, VP of Marketing at Vector, to talk about how she spent $12K on seven micro-influencers with zero UTM tracking and generated $1.1M in pipeline. Jess also breaks down why she started a brand podcast as an awareness play, how a B2C copywriting background at major CPG brands shaped the way she thinks about brand and standing out in B2B, and what it actually takes to make the jump from content leader to VP of Marketing.Timestamps(00:00) - - Intro (07:00) - - Why influencer marketing made sense as a first channel (12:15) - - Tracking pipeline without UTMs: using keyword alerts (13:06) - - The results: 45 demos, 80%+ ICP, $1.1M in pipeline (15:45) - - Why loose briefs outperform tightly controlled campaigns (20:23) - - How to scale an influencer program when you're a team of two (23:01) - - How to make your podcast an awareness magnet (31:49) - - How to know if your podcast is working when you can't track it (37:01) - - LinkedIn: 37K followers in 3 years and how the content strategy works (44:58) - - Why brand and mascots aren't optional anymore in B2B Join 50,0000 people who get Dave's Newsletter here: https://www.exitfive.com/newsletterLearn more about Exit Five's private marketing community: https://www.exitfive.com/***Brought to you by:Webflow - A website platform built for the agentic web, helping modern marketing teams build fully custom sites—no developer needed—that perform in AI search. Learn more at webflow.com/for/exitfive.Markup AI - A content quality platform that scans your content against brand voice, preferred terms, messaging standards, and AI-search readiness before it goes live, right inside Google Docs. Learn more at markup.ai.Optimizely - A no-code AI platform where autonomous agents execute marketing work across webpages, email, SEO, and campaigns. Learn how to deploy agents on your marketing team at Agents in the Mix. Learn more at optimizely.com/exitfive. Walker Sands - An integrated B2B marketing and growth services agency that helps marketing leaders turn strategy into measurable business impact through their Outcome-based Marketing model. Learn more at walkersands.com/exitfive.Knak - A no-code, campaign creation platform that lets you go from idea to on-brand email and landing pages in minutes, using AI where it actually matters. Learn more at knak.com/exitfive, or check out the MCP server by clicking this link.***Thanks to my friends at hatch.fm for producing this episode and handling all of the Exit Five podcast production.They give you unlimited podcast editing and strategy for your B2B podcast.Get unlimited podcast editing and on-demand strategy for one low monthly cost. Just upload your episode, and they take care of the rest.Visit hatch.fm to learn more

We're excited to have Databricks join us at AIEWF, among hundreds of the top companies in the AI Engineer ecosystem. LS subscribers can use their discount to get past the late bird pricing and access over $50k in sponsor offers! Everyone is still talking about Satya's Frontier Ecosystems post, but few have actually built a (now $175 billion) frontier ecosystem and cloud like our guests today.From open-sourcing the layer above coding agents to rethinking databases for the agent era, Databricks cofounders Matei Zaharia and Reynold Xin are pushing the company beyond the lakehouse into a full data-and-AI operating system. In this episode, Matei and Reynold join swyx at the 2026 Data + AI Summit to unpack Omnigent, LTAP, Lakebase, agent security, open formats, Mosaic, and why databases may matter more than ever once AI agents start doing real work.We go deep on Omnigent: Databricks' open-source meta-harness for combining, controlling, and sharing agents across Claude Code, Codex, Cursor, Pi, custom agents, and internal tools. Matei explains why coding agents and enterprise agents run into the same problems: portability, collaboration, session history, security, spend controls, and the need for a common API above every harness.Then Reynold walks through Databricks' database dream: why CDC is brittle enough to joke that it means “continuous data corruption,” why HTAP has been the holy grail of database engineering, and why Databricks thinks LTAP gets most of the benefits by unifying the storage layer instead of collapsing every query engine. We also cover Databricks' infrastructure scale, the culture behind rapid prototyping, the difference between tech and enterprise customers, Databricks vs Snowflake, whether vector databases should have ever existed, the Mosaic model strategy, Genie, AI Runtime, RL fine-tuning, and the thesis that traditional software gets rewritten once the data is in the right place and agents sit on top.Databricks began as a company for the big data era. The origination of Spark from the Berkeley AMPLab which eventually turned into the product Lakehouse convinced enterprises that they didn't need a separate data lake, warehouse, ML platform, and governance layer. They just needed one open foundation where all of their data could live and be reasoned over.Since then a lot has changed, but data has only become more important. Data is no longer something you keep track of and analyze ad hoc, it's the necessary context agents need in order to act. So the framing has shifted from “where do we put all of our data?” to “how do we expose the right slice of state, history, permissions, and business logic to an AI system at the exact moment it's doing work?”If frontier model performance becomes commoditized, the durable advantage then becomes the company-specific context around them: proprietary data, governed access, operational state, transaction logs, workflows, and feedback loops. Which makes Databricks positioned perfectly.Now coming fresh off the Data + AI Summit 2026, the company is moving just as fast to keep up, announcing Genie One, Omnigent, LTAP, and many more, indicating a central mission in its newer work: Databricks is trying to become the operating system for enterprise agents.Models are getting good enough, but agents are only useful if they have the right context, permissions, memory, state, cost controls, and access to live business data. Fundamentally it appears that significantly better model performance in production is a systems problem, one that data guys like us are remarkably well prepared to solve!We discuss:* Why Databricks built Omnigent as a meta-harness above existing AI agents* Why coding agents and custom enterprise agents need the same infrastructure* The common API for agent sessions, files, streams, tool calls, and cancellation* Why persistent sessions, cloud sandboxes, sharing, search, and collaboration matter* Why Databricks open-sourced Omnigent instead of keeping it proprietary* Databricks' internal agent usage, cloud sandboxes, and coding workflows* The scale of Databricks: 50–60 million virtual machines a day and exabytes before breakfast* Why agent security needs contextual and stateful policies* How an agent could read confidential docs, install a compromised npm package, and leak data* Why spend control matters when an agent can burn $500 reading logs* Startup opportunities around coding-agent analytics, quality, skills, and spend* LTAP, Lakebase, and why Databricks wants to rethink the database stack* OLTP vs OLAP, CDC, and why data pipelines break at 3 a.m.* Why HTAP has historically been the holy grail of database engineering* Why Databricks thinks LTAP is “HTAP done right”* How writing transactional data into column-oriented formats changes analytics* Why agents need live operational context from databases, not just telemetry* How Databricks prototypes strategic systems without endless process* Enterprise vs tech customers, governance, procurement, and DIY culture* The “second system syndrome” risk of rewriting a database engine* Building a database engine from a decade of traces and quadrillions of data points* Why vector databases should never have been a separate category* Why open formats and AI changed the race with Snowflake* The Mosaic story, DBRX, Genie, document parsing models, and specialized model training* Why model customization and RL fine-tuning may become mainstream* Why “get the data there, slap some agent on top” may rewrite traditional softwareMatei Zaharia* LinkedIn: https://www.linkedin.com/in/mateizaharia* X: https://x.com/matei_zahariaReynold Xin* LinkedIn: https://www.linkedin.com/in/rxin* X: https://x.com/rxinDatabricks* Website: https://www.databricks.com* X: https://x.com/databricksTimestamps00:00:00 Introduction00:02:22 Omnigent and the Agent Infrastructure Layer00:08:39 Agent Clouds, Common APIs, and Open Source00:16:52 Databricks Scale and Internal AI Workflows00:18:03 Agent Security, Governance, and Spend Controls00:27:34 LTAP and the Database Dream00:30:30 CDC, HTAP, and Why Data Pipelines Break00:34:05 Lakebase, Parquet, and Live Data for Agents00:36:47 Databricks' Culture of Fast Prototyping00:43:40 The Dream Engine and Rewriting the Database Stack00:51:02 Vector Databases, Query Engines, and LTAP00:52:36 Databricks vs Snowflake00:57:48 Mosaic, DBRX, Genie, and Specialized Models01:03:11 Context, AI Runtime, and RL Fine-Tuning01:06:15 Why Data + Agents May Rewrite Software01:07:09 Closing ThoughtsTranscriptIntroduction: Databricks, Data + AI Summit, and Founder DynamicsSwyx [00:00:00]: Matei and Reynold from Databricks, welcome to Latent Space.Reynold Xin [00:00:06]: Hey, thanks for having us.Swyx [00:00:07]: Yeah.Matei Zaharia [00:00:08]: Yeah, thanks so much.Swyx [00:00:09]: thanks for taking time out. You have your Databricks, Data AI Summit going on. You were just telling me how the first summit that you guys ran was just 50 peopleReynold Xin [00:00:17]: Yeah, it wasSwyx [00:00:17]: in BerkeleyReynold Xin [00:00:18]: little meetup at Berkeley, I thinkMatei Zaharia [00:00:19]: YeahReynold Xin [00:00:19]: put togetherMatei Zaharia [00:00:20]: We were doing these tutorials and, yeah, just teach people Spark.Swyx [00:00:23]: Yeah. obviously now it's like, I think like the headline number's like 100,000 people around the world, 30,000 in person.Swyx [00:00:30]: it's a crazyMatei Zaharia [00:00:31]: AmazingSwyx [00:00:31]: community. Well, I just saw the keynote.Swyx [00:00:35]: Ali's just. Did was it obvious or that back when that Ali would be, like, such a great, like, CEO? LikeReynold Xin [00:00:42]: OhSwyx [00:00:42]: such a great presenter?Reynold Xin [00:00:43]: What do you think?Matei Zaharia [00:00:44]: I think among our group of founders it was clear that, I think he'd be the best at this.Swyx [00:00:50]: Yeah.Matei Zaharia [00:00:50]: And yeah, it turned out great. And he's, he's ramped up on so many topics growing a company. He would just go in and, like, study it and, be talk to all the experts. Like, even if he can't hire the person, learn enough about, like, finance and sales and whatever it was, and, and go from there. Yeah.Swyx [00:01:09]: Yeah.Reynold Xin [00:01:10]: he's obviously very high IQ and a very high EQ, but it wasn't. Like, Ali today is quite different from Ali from, like 10 years ago. I think there's a lot of work that he put in to, get to this point.Swyx [00:01:20]: Yeah. no, to me the most appealing thing about him is that he's funny. And like, it, it's, it'Matei Zaharia [00:01:26]: It's true, yeahSwyx [00:01:26]: it's hard to make jokes about, data warehousesReynold Xin [00:01:30]: About serious topicsSwyx [00:01:31]: securityMatei Zaharia [00:01:32]: YeahSwyx [00:01:32]: what have you.Matei Zaharia [00:01:33]: Oh, yeah. That's for sure.Swyx [00:01:34]: Yeah. So you guys launched a whole bunch of things. I'll, I'll just name check briefly, the stuff because we're not gonna cover everything. Omnigentt, your baby. LTAP, your baby, your dream engine.Swyx [00:01:47]: we're also gonna cover Genie, cover CustomerLake, you acquired PantherMatei Zaharia [00:01:52]: YeahSwyx [00:01:52]: Open Sharing, and there's Unity AI Gateway. A lot of these, I think, like, are things that you would expect a Databricks to do. It's, it's like part of the roadmap. Everyone in your category has similar things. But I think, probably the two of you are leading the two most unique and differentiated initiativesOmnigent and the Agent Infrastructure LayerSwyx [00:02:09]: on, in the landscape. Maybe we'll start with, Omnigentt we'll, we'll, we'll, we'll go into it. I do think that a lot of people are exploring this meta harness concept.Matei Zaharia [00:02:21]: Yeah, totally.Swyx [00:02:21]: What led you to it?Matei Zaharia [00:02:22]: Yeah. There were a couple of, like, converging lines, which I think is a good sign that you need something new. So on the one hand, there's all the coding agent info internally. We have really great, dev infra team. they built something called Isaac, that's like a wrapper on Claude Code and Codex, and, lets you use them either on the web in, like, sandboxes or, just on your dev machine or on your laptop or whatever. And then, they were adding all kinds of stuff there. And we saw all the more advanced engineers like, were building their own workflows with tons of agents, and they were building their own UIs and stuff on top or even on top of that. And then the other one was, like, us building agents. We ship this, like, data science agent called Genie on the research team, which I lead. We also build a lot of internal ones for various things, and then we have all the customer ones. And all of them running into this thing of like, “Oh, I need to switch model and harness and so on,” every few months. Plus the agent is, like, completely useless if you can't share sessions with someone and have history and have search and all this, like, layer on top of it for collaboration. I thought a bit about it from both contexts and, at first people thought it was weird. They're like, “Why are you doing coding agents and custom agents in the same thing?” But I said it's, it's the same problems and, you just wanna build the stuff that lets you deliver the agent, maybe control it if you care about security, and, make it portable across things. And then we prototyped some things as experiments. We saw, yeah, we can make it work, and then we built that for real.Swyx [00:04:06]: I'm wondering if this let's call it architectureMatei Zaharia [00:04:11]: YeahSwyx [00:04:11]: maps to anything in your careers in the past. like I always think about how a lot of things just tie back to operating systems.Swyx [00:04:18]: A lot of operatingMatei Zaharia [00:04:19]: YeahSwyx [00:04:20]: systems tie back to databases,Matei Zaharia [00:04:21]: SoSwyx [00:04:21]: or the other way aroundMatei Zaharia [00:04:22]: so the thing, I do think it ties a lot to, like, network protocols, internet protocol. we alsoSwyx [00:04:29]: Communication between entities.Matei Zaharia [00:04:30]: Yeah. We did stuff with, like, data sharing also, which is probably, most viewers probably won't know unless they'Swyx [00:04:36]: Yeah, open protocol is the term.Matei Zaharia [00:04:37]: Yeah.Swyx [00:04:38]: Open sharing. Open sharing.Matei Zaharia [00:04:38]: Open sharing.Swyx [00:04:39]: Yes.Matei Zaharia [00:04:39]: Yeah. So it's like you have a company, you maintain some table, like let's say like a Walmart or something. They have like the, inventory and what's been sold in each store. And then you also have suppliers, and they would love to produce more things and ship them, like, exactly the moment you need them. So they would love, like, real-time access to your table. So instead of like sending emails around or Excel sheets or phone calls, why can't you share like a view of that table in real time with them? Then they query, they, join it with their data, and they decide what to send. So it's one of these things where you, like you might ask like today since we can vibe code anything so fast, why do we even need to design like protocols or APIs or software? Why can't you just vibe code things on demand? But for this type of interoperability where multiple parties that are moving at different speeds are building stuff and you still want some layer on top to coordinate, you do wanna design it and build it. So it reminds me of that, like agents talking to each other and, users talking to agents and tools.Agent Clouds, Cloud Sandboxes, and Keeping Sessions AliveSwyx [00:05:42]: Reynold, any other comments alternative viewpoints?Reynold Xin [00:05:46]: I think, by the way, we had a debate on exactly which set of benefits would, matter a lot, and I think around the time we decided to do this thing I was telling Matei, “Hey,” it just happened to be there's a particular week that I was coding nonstopSwyx [00:06:00]: from the moment I woke up to, like, the moment I went to bed, I was, like, looking at my Claude sessions, my Codex sessions. And one of the things that was particularly annoying was having to keep my laptop open.Swyx [00:06:12]: I was driving to a doctor's appointment, and I remember because I wanted to make sure the whole thing continues working.Matei Zaharia [00:06:18]: But by the way, it's so comforting to hear you say that because I'm like, “I don't know if I'm a clown and I'm doing this or like.”Swyx [00:06:25]: Yeah. Like honestly, I was driving and I was tethering my laptop to my phone.Matei Zaharia [00:06:29]: huh.Swyx [00:06:29]: Keeping it on the side. Whenever I hit a red light, I started looking at what's going on my laptop.Matei Zaharia [00:06:35]: Yeah.Swyx [00:06:35]: And I just felt that was ridiculous.Matei Zaharia [00:06:37]: Yeah.Swyx [00:06:37]: It felt like we went back to the dark agesMatei Zaharia [00:06:39]: YeahSwyx [00:06:40]: programming. the productivity you gain from all this coding age is amazing, but, yeah.Matei Zaharia [00:06:45]: Have you heard of cloud?Swyx [00:06:47]: Yeah.Swyx [00:06:48]: It was crazy to me.Matei Zaharia [00:06:49]: Oh, the thing you were working on was the sandboxes or was this before that?Swyx [00:06:52]: It was a sandbox.Matei Zaharia [00:06:53]: Okay.Swyx [00:06:54]: I was workMatei Zaharia [00:06:54]: So you were inSwyx [00:06:55]: So I was approaching from a very different angle. I wanted to, “Hey, we're gonna have cloud sandboxes that doesn't shut down. You can get one very quickly,” but not just for running agentic sessions.Matei Zaharia [00:07:06]: Yeah.Swyx [00:07:06]: It's also for running development. So I was personally building that week, and through building that, I ran into all these issues, and then I wroteMatei Zaharia [00:07:15]: YeahSwyx [00:07:15]: a document for Matei, it's like, “Here's my wish list of what the actual environment should do.” And I think he ended up almost implementingMatei Zaharia [00:07:22]: YeahSwyx [00:07:22]: every single one of them.Matei Zaharia [00:07:23]: Yeah, I remember Reynolds saying, ‘cause my first prototype of this had just chats with your agent and he said, “I have to be able to open a shell, like my own shell and like list files and like tail them and stuff.” SoSwyx [00:07:36]: So SSH into a mainframe.Matei Zaharia [00:07:37]: Yeah. it has that now.Swyx [00:07:39]: Tailing my log.Matei Zaharia [00:07:40]: Yeah.Matei Zaharia [00:07:41]: Yeah.Swyx [00:07:41]: And also another thing I think I asked was, I had. I still use cursor for the sole purpose of rendering markdown files.Matei Zaharia [00:07:48]: huh. Yes.Swyx [00:07:49]: So I said, “If you just give me a way to see my markdown files and renderMatei Zaharia [00:07:53]: YeahSwyx [00:07:53]: them properly, I don't need a separate tool anymore.”Matei Zaharia [00:07:55]: Yeah.Swyx [00:07:56]: And I think you also built that in.Matei Zaharia [00:07:57]: Yeah, we, yeah, we did that, yeah. Yeah, we had a lot of engineers building, their own vibe coding setup. But then the other thing they all said is like, “Hey, I built something that's amazing for me, but, like, no one else on the team can use it ‘cause I don't have a server to collaborate.” And this is why we tried to set up, Omnigent, so you can have a server and have the security, set up in there. So, like log in with Google or whatever and, like securely share stuff. which. And that's where we've seen a lot of other agents like hit things. Like people think they prototyped an awesome agent, but it's not allowed to connect to like some really important data or whatever because of the security team.Omnigent Architecture, Open Source, and Common APIsSwyx [00:08:38]: Yeah.Matei Zaharia [00:08:38]: So yeah.Swyx [00:08:39]: Yeah. At this point, so for those watching along on YouTube, we're gonna putting up a image of the structure here, and we can talk a little bit of the architecture. I think I just want to have people understand, ‘cause like when we're talking about software, it can be very abstract and like here is what we're talking about. You've worked out in open source this entire platform and there's a runner component and server component with a uniform API that you've, you've figured out. any other element and obviously you can plug in all this, persistence layers and compute layers. This is a whole cloud. It's an agent cloud.Matei Zaharia [00:09:12]: Yeah. It's, it's got these components to work with it. The, a lot of the action happens like on the machine where you deploy your agent too. So whatever you've got on there, you can run. But yeah, it's, I think it's the minimal thing you want to have hosted, like collaborative agents and to have that server. And one of the reasons we open sourced it is, anyone building agents, this gives them an app they can start with and customize, which we were seeing in Databricks too. Like someone would make a nice, agent app and then other teams would ask, “Oh, can I just use yours for my agent?”Swyx [00:09:45]: Yeah, I think we had like five or six different agentic frameworksMatei Zaharia [00:09:48]: YeahSwyx [00:09:48]: built by every different team. They do all do more or less the same thing. Yeah, you need to. people wanna take something that works in Forkit, and you might as well have something open source. Yeah, which also was another question, which is interesting for Databricks. Like what do you choose to open source? What do you choose to make it proprietary? It's in. this goes back to Spark, right?Matei Zaharia [00:10:05]: Yeah.Matei Zaharia [00:10:06]: One, so one of the reasons to open source something is if you think it's a layer that will there'll be some network effect, it'll benefit from many, people collaborating, on it. So, for example, with Spark, I don't know if when Spark came out, we also focused a lot on letting you have libraries on top. So like there used to be differentSwyx [00:10:28]: EcosystemMatei Zaharia [00:10:28]: distributed computing engines for like machine learning and graph computation. We said they should all be libraries that you can compose. And we made it super easy to add connectors to data sources too. And then we benefit because, we don't have the time to write like connectors to like, 1,000 like different databases and file formats, but we can just use the ones people make, and of course they benefit from joining, this thing. So that's like one of these as it. Another way to think about it is like imagine, we our thing wasn't open. We had some agent hosting thing, but it's not open and then there is an open one. if you're. Which one's gonna win in the long run? So like here, because there is this benefit from like people writing integrations, it'll be, it'll be that. And then there are other things that like you just can't, even deliver as open source that are things the company does. Like for example, how do you make sure you're like streaming, jobs or your Lakebase database doesn't like, lose all your data at night? Well, that requires an operational team that's gonna sit there. There's no way it has to be a service. So like we wanna make sure as a company we're really good at those infra services and then we're as open as we can in terms of like what you build on top.Swyx [00:11:42]: speaking from a benefits, I think we are already seeing pull requestsMatei Zaharia [00:11:45]: YeahSwyx [00:11:45]: of all kinds of ecosystem integration, even though it was only released on Saturday.Matei Zaharia [00:11:50]: Yeah, Saturday. Yeah. So someoneSwyx [00:11:51]: Let's see, let's see what's going on. Yeah, you can look at the merge ones. I asked Sam Nigon this morning aboutMatei Zaharia [00:11:59]: 400 merge already?Matei Zaharia [00:12:00]: Yeah. I think Recent quite, I would guess around half are not from our team. but for example, someone added support for running it on Kubernetesrnetes. people added, many cloud sandboxes, so this can launch a cloud sandbox and run your agent in there, which is great for sharing too, ‘cause it's not, like, on your laptop and someone's, like, running scary code on there. so yeah, many startups have put those in, and, we expect to see more of them. We also have more agent harnesses already. Cursor, CLI, and Antigravity also.The Modern Data Stack and the Emerging AI StackMatei Zaharia [00:12:34]: Yeah. That's all, beautiful. And I, I feel like the last time this happens, there was the rise of the modern data stack.Matei Zaharia [00:12:42]: I don't know if it's that useful. I'm, I'm curious in your postmortem.Matei Zaharia [00:12:46]: I think most peopleSwyx [00:12:47]: AgreeMatei Zaharia [00:12:47]: will agree that it is finally dead. but maybe this arises to a new modern AI stack that, like, does the same thing.Matei Zaharia [00:12:52]: I don't know.Reynold Xin [00:12:54]: I think the modern data stack was a pretty useful thing, probably even up until this day. I think what, maybe for the audience who don't understand the history, I think the modern data stack is effectively decomposed into you need a layer to ingest the data in, you need a layer to transform your data, and then all of this are run, and then you need a layer to maybe visualize your data. And all of this runs on some data warehouse, or later on, as we're doing data warehouse or lakehouse.Reynold Xin [00:13:21]: I think that concepts are all very powerful and very useful. They enable a lot of workloads. What people eventually run into is a question of unification and consolidation is, hey, do you really need to chop all this into different pieces and work with so many different vendors and platforms in order to get, like, a very simple visualization done, right? So I think, like, over time, everybody started realizing that customers are pushing us. We started, we can realize that, so we started building more and more capabilities and trying to consolidate. And at the end of the day now, customers don't have to worry about having me hook up five different systems in orderMatei Zaharia [00:13:55]: YeahReynold Xin [00:13:55]: produce a chart. But the. I think, honestly, something like this is probably happening, in how many different frameworks do you want to hook up together in order to produce, like do a very simple agent.Matei Zaharia [00:14:06]: Just to be clear, I would say the core of this is this common API on top of all the harnesses. So the API is like, you've got an agent session, and you can send in a message or, like, a file. That's what you can send in, and then you get out, these streams as it's streaming text or as it's doing tool calls. And, or the other thing you can send in is you can, like, tell it to cancel a turn. So that's the API. Now, the thing we did is we could get you that on top of, like, cloud code running in a terminal, Codex, Py, OpenAI SDK, all that stuff. We map them all to that same interface. So that is something that you'd have to maintain yourself if you built your own, like, agent orchestrator, and then whenever cloud changes its API, you gotta, tweak your thing or it's gonna lose some messages. So that's the thing that's valuable to maintain. Then on top of that, like, we built a few apps. I think we built a pretty cool UI and stuff, but that's, And we built a security and control piece, which I'm excited about. But it's that common interface, so we don't. We. That doesn't try to be a stack. And in fact, you could plug in your own UI on top of this, server. That, and that's one of the use cases we care a lot about, ‘cause we want to use this in our own products.Compute, Sandboxes, and Databricks ScaleSwyx [00:15:20]: Yeah. It should be everywhere.Matei Zaharia [00:15:22]: Yeah.Swyx [00:15:22]: I think one of those things that is really interesting to me is, like, well, first of all, I'll, I'll endeavor to do everything and not call it the modern AI stack because like it needs a different name.Matei Zaharia [00:15:32]: Yeah.Swyx [00:15:32]: But like, yes, like, so one of the first people that told me about compute, sandboxing was Nikita from Neon.Swyx [00:15:39]: Because a lot of people think about Neon as like, well, it's serverless Postgres with, like, the separation of compute and storage and, instant branching and all those things. But every database company is also a compute company.Matei Zaharia [00:15:51]: Yeah. Yeah.Swyx [00:15:52]: And so he was showing to me his whole, his sandboxing solution. I don't think he have ever launched it.Matei Zaharia [00:15:57]: So our sandbox solution, the reason we could build it so quickly was because we realized if you just take the actual Lakebase architectureSwyx [00:16:05]: YeahMatei Zaharia [00:16:05]: and remove the database from it, by the coming from NeonSwyx [00:16:08]: Exactly, rightMatei Zaharia [00:16:09]: you have this sandboxSwyx [00:16:09]: Every database company has it already, yeah.Matei Zaharia [00:16:11]: Now, there are some differences. For example, in the one to support this particular workflow, it's important to have local persistence,Swyx [00:16:19]: YeahMatei Zaharia [00:16:19]: because you want your state to persist. Your libraries, you don't have to install your library every time, right?Matei Zaharia [00:16:24]: whereas the Neon architecture, because of the separation of storage from compute, you don't need persistent local disk.Swyx [00:16:30]: Yeah.Matei Zaharia [00:16:30]: So there's some differences.Swyx [00:16:32]: Yeah.Matei Zaharia [00:16:32]: But the, at the end of the day, yeah, it's, Yeah, so this is when you run, like, a coding sandbox. Like, if I use it, yeah, we have the dev env internally at Databricks. There's, like, many, like, tens of gigabytes of data just for, like, all the source code and, like, artifacts and stuff that I built, and I want that to come back next time, so.Matei Zaharia [00:16:51]: Yeah.Matei Zaharia [00:16:51]: But yeah.Matei Zaharia [00:16:52]: Before the show, we was talking about some statistics that might be surprising at the adoption.Matei Zaharia [00:16:56]: It could be internal, it could be external, whatever comes to mind, just to impress people the scale this is happening.Swyx [00:17:02]: So we, on the analytics side, I think we launchedReynold Xin [00:17:06]: Maybe 50 or 60 million virtual machines a day across all three clouds, so we're one of the biggest compute orchestrators out there.Reynold Xin [00:17:13]: Stuff for sure for CPU compute.Swyx [00:17:14]: Yeah.Matei Zaharia [00:17:14]: Yeah.Reynold Xin [00:17:15]: the. And all of this process, I think exabytes of data, I joked about depending on which time zone you are, typically before you have breakfast, Databricks would have processed exabytes of data already on that day. and on Neon, it's pretty interesting, too. It's launching, I think, 13 million databasesSwyx [00:17:34]: YeahReynold Xin [00:17:34]: a day now.Swyx [00:17:35]: Yeah, to me that was, like, aReynold Xin [00:17:36]: And that's just likeSwyx [00:17:37]: Like, what do you mean?Matei Zaharia [00:17:38]: Yeah. And that's the point.Reynold Xin [00:17:40]: And a lot of those were thanks to agent- agents and branching experimentationSwyx [00:17:44]: YeahReynold Xin [00:17:44]: because we made it so easy and so quickly, and thanks a lot to Nikita's team, to launch databases. It's, the. So it's changing the way people use databases.Swyx [00:17:54]: Yeah. Okay, we're gonna go into more database talk in a bit, but I wanna make sure we close up anything on Omnigentt. you mentioned, you were excited about the securityOmnigent Security, Contextual Policies, and Spend ControlsSwyx [00:18:03]: control side.Matei Zaharia [00:18:04]: Yeah.Swyx [00:18:04]: a lot of companies are figuring that out right now, as well as the spend side.Matei Zaharia [00:18:08]: Yep.Swyx [00:18:09]: what have you found there?Matei Zaharia [00:18:11]: Yeah, so I spent quite a bit of time talking to internal users, developers, security team, managers, and also lots of customers, and there's a few things. Like, first of all, one thing, that immediately was. became obvious is for security, there's this tension between, like, usability and security. And, the way people do. Like, a lot of coding agents today have very basic things like you can tell me which tool patterns I'll allow or disallow or whatever. It's like yes or no. But that puts you in a very tough spot. So just as an example, like, should my agent be able to read, some confidential documents, or let's say, should it be able to install new packages from npm, which, maybe it's compromised. Yes or no? Like, maybe I wanna allow it. Should my agent be able to publish stuff to the company website? Well, if I'm using it to code on the website, yes. But should it be able to do both, so it can, like grab a confidential document and be prompt injected and leak it? Probably not. So the thing we decided we need is stateful or what we call contextual policies where you keep track of the state of that session. It's not like is it allowed to push to the marketing site or not, but, like, hey, if it did a risky thing, like it installed, a old package from npm, or it read, like, 1,000 confidential docs, then no. Then don't, don't do it. Otherwise, maybe it's okay. That's one example of, like, moving that trade-off so it's both more secure and more useful by having a more powerful engine, essentially. This requires tracking sessions. The other piece that was interesting there is, like, there are these very level events it's doing, and you want some libraries on top that parse them. Like, for example, we have a, MCP server on Google Drive internally. It's got 60 API calls. like, how do I know which of those, like, will share a document with stuff on the internet and which ones won't? It's, it's annoying. So we designed in Omnigentt the policy layer so that it's functions and you can have libraries. Like, someone can make something that maps the level events to high-level ones, and then you write a policy about the high-level things that came out. so and thatSwyx [00:20:25]: This is related to the Panther,Matei Zaharia [00:20:27]: Yeah, Panther is. will help with that. PantherSwyx [00:20:30]: YeahMatei Zaharia [00:20:30]: a similar idea on the event processing side, and it's Python-based versus a weird custom language. this is more, as in realSwyx [00:20:39]: I didn't even know we were good yeah.Matei Zaharia [00:20:41]: Those things are happening, yeah.Swyx [00:20:42]: Yeah.Matei Zaharia [00:20:42]: So yeah, but these are the cool things. I think the contextual or stateful part, and then the way it can be libraries, and that was another reason to make it open source because others will write libraries and, like, we and our customers can use them. And the final thing, because it's stateful, one of the states we track is how much you spent in that session. So I can. I've had, like, I ask an agent to debug something, and it spent $500 because it decided to read a lot of log files and burn a lot of tokens. but I can literally say, “Okay, launch a agent to do this and cap it to spending $5.” Like, ask me for permission if it needs more. And because we're counting that within that session, it'll pop up and tell me, “Okay, you spent five, $5. Do you wanna go on?”Reynold Xin [00:21:27]: So important context here. Matei spent the last five years, a lot of his time was architecting Unity Catalog at DatabricksMatei Zaharia [00:21:34]: YeahReynold Xin [00:21:34]: which is the governance layer for data.Matei Zaharia [00:21:35]: That's right, yeah.Reynold Xin [00:21:36]: And he's combining expertise at that layer together with all the AI governance he knows.Matei Zaharia [00:21:41]: Yeah.Swyx [00:21:41]: DoMatei Zaharia [00:21:41]: But I also spent a lot of time being annoyed by coding agents and getting prompts.Matei Zaharia [00:21:46]: And also as theReynold Xin [00:21:48]: All the aboveMatei Zaharia [00:21:48]: I don't want to end up on the front page as, like, I installed some weird npm package and leakedSwyx [00:21:53]: YeahMatei Zaharia [00:21:53]: all the code, so I'm especially paranoid. But also I have very little time, so I don't want to sit there approving, like, do you want to run a 20-line, bash script, yes or no? so that's why I spend a lot of time figuring out, like, how can I make it as safe as possible and not annoying?Swyx [00:22:10]: Yeah. Is safety and mmm, let's call it security a bigger concern than token maxing or token budgets? which one is, likeMatei Zaharia [00:22:19]: Oh, yeah, they're both there. I don't know. I guess it depends on the type of company you are. So I think, some companies, like, the budget is, limited and, they really care about thatSwyx [00:22:34]: you can be Uber and still be concerned?Matei Zaharia [00:22:36]: Yeah. Oh, yeah, totally. Yeah. If you haveReynold Xin [00:22:38]: for us, securityMatei Zaharia [00:22:39]: YeahReynold Xin [00:22:40]: super paramount.Matei Zaharia [00:22:40]: For us, security is absolutely critical as a, cloud provider. It's, it's the most important thing, and, token maxing, we're not so worried about it yet, but I've seen the Like, for example, I talked to some consulting companies. They have, like, 100,000 employees who are all coding for customers. If those each spend, like, an extra $1,000 a month, that's, that's not fun.Swyx [00:23:04]: YeahMatei Zaharia [00:23:04]: we have, like, only a few thousand engineers.Swyx [00:23:06]: What's the policy in Databricks? Is it just unlimited or what'Matei Zaharia [00:23:08]: It's, it's unlimited, but we do. we use our own product to, like, analyze the traces and stuff, and we have a team that'looking to optimize and to see if anyone's doing something weird. And, we had some really cool insights just from analyzing current traces, like whichSwyx [00:23:24]: YeahMatei Zaharia [00:23:25]: models are better at, say, Rust versus like TypeScript or whatever. So yeah, at least in our code base.Swyx [00:23:31]: Yeah. Amazing. Obviously, I have to ask the token question, obviously.Matei Zaharia [00:23:34]: Yeah.Swyx [00:23:34]: I think it'sReynold Xin [00:23:34]: YeahSwyx [00:23:34]: it's a key thing. But yes, security and control above that, and figuring out a sane layer there you can have some autonomy, but, not too much.Matei Zaharia [00:23:43]: Yeah. Yeah, and we wanna make it super easy. As a engineer, you should set a thing. So in Omnigentt, you can ask your agent, “Set a policy on yourself to do this.” So it can likeSwyx [00:23:52]: But if there's something I should be showingMatei Zaharia [00:23:53]: YeahSwyx [00:23:53]: I don't, I don't see it on the GitHub, but,Matei Zaharia [00:23:55]: Oh, yeahSwyx [00:23:56]: there's justMatei Zaharia [00:23:56]: Well, in the docs there's something.Swyx [00:23:57]: Yeah, this is it.Matei Zaharia [00:23:58]: You can look at it later.Swyx [00:23:59]: Okay. Yeah.Matei Zaharia [00:23:59]: Just look in the docsSwyx [00:24:00]: YeahMatei Zaharia [00:24:00]: contextual policies if you wanna see.Swyx [00:24:04]: I just like to point peopleMatei Zaharia [00:24:05]: look at the built-in policies.Swyx [00:24:06]: Yeah.Reynold Xin [00:24:06]: Yeah.Swyx [00:24:06]: If you want to, follow up on this is exactly where to look, right?Reynold Xin [00:24:10]: Yeah.Matei Zaharia [00:24:10]: Yeah. yeah, and the story of these is, like, I just wrote, like, I wrote a doc with like 10 ideas for things before as you were working on them. Well, that was, like, my wish list of things people asked, and I told the team, like, “Hey, can you do like at least five of these for the launch?” And then they just got back with all of them, so.Swyx [00:24:29]: Oh, wow.Matei Zaharia [00:24:29]: so you can come up with more, but them- some of them are just meant to be examples. really you can intercept, like, any event the agent is making, and you can then either block or force it to ask the user or, like, allow, and you can update state to keepSwyx [00:24:45]: YeahMatei Zaharia [00:24:45]: track stuff.Swyx [00:24:46]: Yeah, ‘cause ultimately you're, I think of you as, like, a systems designer.Swyx [00:24:50]: You let people plug in, right? That's the wholeMatei Zaharia [00:24:51]: YeahSwyx [00:24:52]: modus operandi of what you do.Matei Zaharia [00:24:53]: Yeah.Swyx [00:24:54]: It's likeMatei Zaharia [00:24:54]: And we care a lot about also composab- like, can someone else write a library that others use, whichSwyx [00:24:59]: YeahMatei Zaharia [00:24:59]: this is meant to.Reynold Xin [00:25:00]: There's also a batteries included philosophy hereMatei Zaharia [00:25:03]: YesReynold Xin [00:25:03]: probably very similar to how you did Spark, which is you could just start using.Swyx [00:25:06]: Yeah.Matei Zaharia [00:25:06]: Yeah, that's right. It has to be good out of the box at certain things, and then you can build your own things on top that, like, we don't wanna do. But in Spark, if you just wanna like, I don't know, like read a table or do, like, a aggregation, it should be awesome at that out of the box.Building on Omnigent: Contributions, Startups, and AnalyticsSwyx [00:25:23]: Yeah. People wanna catch up on Omnigentt, they should watch your keynote.Swyx [00:25:26]: they should go through the GitHub and the docs. If they wanted to contribute, or they want to build on this ecosystem what would you call out as the most high-leverage places get involved?Matei Zaharia [00:25:36]: Yeah, do get involved in the Discord and in GitHub. Our team is there, is monitoring, and, some of the things people ask for we just built ourselves. Some of them, we're, we're collaborating with them to build it. and also tell us, likeSwyx [00:25:49]: Yeah, they're gonna be veryMatei Zaharia [00:25:49]: how you would like to use it because I think especially for developers, like, everyone wants it to work their own way, and a really good developer tool, like you have to hear the feedback on all the ways and figure out the abstractions and how to let people customize. So we'd love to hear, like, if you think, “Hey, I, I don't want it to work this way,” tell us. We really just wanna get that compatibility layer across agents and then let you do stuff on top.Swyx [00:26:14]: Yeah. is there any, in terms of like the startup side, I'm, I'm a founder.Swyx [00:26:18]: I wantMatei Zaharia [00:26:18]: YeahSwyx [00:26:18]: I see an opportunity, I wanna get in front of you. What's your request for, like, a startup that, like, I wish someoneMatei Zaharia [00:26:23]: Oh, like you wanna integrate with us?Swyx [00:26:24]: someone was working on this.Matei Zaharia [00:26:26]: Oh, for a startup?Swyx [00:26:27]: Yeah.Swyx [00:26:28]: Like, your, you got your own startup. It's doing well.Matei Zaharia [00:26:30]: Yeah.Swyx [00:26:30]: But like, if you weren't working on your own startup, what is, like, obvious that you should You advise many startups too, obviously.Matei Zaharia [00:26:37]: I do think, just as a company with a lot of engineers, like anything that helps me make sense of how people are usingSwyx [00:26:46]: SpendMatei Zaharia [00:26:46]: coding agents and,Swyx [00:26:48]: Yeah. AnalyticsMatei Zaharia [00:26:48]: spend, but also quality or like you should write, you should add this skill, or you should write this thing, or your agents are really horrible at tasks involving this service, so I go spend time. That would be nice. yeah.Swyx [00:27:00]: Yeah. The closest I've found is, this team, GitAI.Matei Zaharia [00:27:03]: Oh, cool. Yeah.Swyx [00:27:04]: They started with, like, we will just do, code and human attribution, but they're building the analytics layer on top of that.Matei Zaharia [00:27:12]: Yeah.Swyx [00:27:12]: I do think, like, there are a bunch of, like, artificial analysis is obviously,Matei Zaharia [00:27:18]: Yeah, they have their benchmarksSwyx [00:27:18]: doing super wellMatei Zaharia [00:27:19]: YeahSwyx [00:27:19]: with their stuff. so there's, there will be people. I think this is like the domain of consultants first, but then peopleMatei Zaharia [00:27:26]: YeahSwyx [00:27:26]: will build software that, let's say, it's kinda like the management planeMatei Zaharia [00:27:29]: YeahSwyx [00:27:30]: for coding agents.Matei Zaharia [00:27:30]: Yeah, I think there'll be a lot of insights there. You have it in other areas.Swyx [00:27:34]: Okay. Well, and then the other, big thing is your dream engine.LTAP: Lake Transactional/Analytical ProcessingSwyx [00:27:39]: maybe you wanna tell the story of, LTAP.Reynold Xin [00:27:45]: So, and background with. I'm, I'm gonna make people listen to our Ankur Goyal episode where we talked about SingleStore, HTAPMatei Zaharia [00:27:52]: YeahReynold Xin [00:27:52]: and all that history.Matei Zaharia [00:27:52]: Yeah. The LTAP idea is pretty simple. so if people have heard of the, Ankur's, talk about HTAP, it's effectively the world of databases. Sorry, there's like maybe a lot of context needs to be injected here. The world of databasesSwyx [00:28:06]: I am happy to be the database podcast that I'm forcing people to, like, learn your databases, guys.Swyx [00:28:11]: You cannot vibe code with just markdown files.Reynold Xin [00:28:13]: Yeah.Swyx [00:28:13]: Like,Reynold Xin [00:28:14]: It's one of the most important fundamental systems technologies out there. But the world of database effectively split into roughly two halves. There's what we call OLTP databases, which are transactional, and think of your Postgres, your MySQL, your Oracle databases, and the other side is what we call analytics, and sometime might refer to term OLAP. And the difference is on OLTP, you typically have maybe run some transaction on some event that looks up at one specific row. We update that row, right? It's a very oriented data structure. And on analytics, you're trying to reason on the data. You're trying to compute, “Hey, what's my revenue per store? What's my. How's my website doing every day?” And then you, eventually want to probably end up running anal- machine learning on it to predict, “Hey, how will my maybe sales be going in the future?” they are so very different architecture, and everybody start with OLTP databases. Every app, when you become serious enough, that needs more than markdown files, you need to have a database. You want to lose your data, you want to have some transactional consistency. But once you want to reason on the data, if you only have like- A hundred rows, it's probably okay to run it on your Postgres or your own, your MySQL database. But once you have more data and want to run more complicated analysis, the very analysis might crush your Postgres database. So you start doing, getting data out of the OLTP databaseSwyx [00:29:35]: Replication.Reynold Xin [00:29:36]: Replicate them into the analytic systems and just startSwyx [00:29:39]: Yeah, which for people, Elasticsearch is, like, aReynold Xin [00:29:42]: Yeah. So some of them get into Elasticsearch for, like, blocked analysis. A lot of our customers obviously get into Databricks to run more sophisticated things.Swyx [00:29:51]: Yeah.Reynold Xin [00:29:51]: And there's this term called CDC, whichMatei Zaharia [00:29:54]: Change data captureReynold Xin [00:29:55]: change data capture. and what it does, it reads the binlog of the database, and if you don't understand what binlog is, it's fine. The, but it's a little delta of the data, and it reconstructs based on the delta, the state of the database, on the analytics side. But CDC is, like, a very painful thing. It's how standard in the industry, everybody uses it, but, it ends up being. I think many data engineers ends up being waken up at, like, 3:00 a.m, because there's some pipeline thing.Swyx [00:30:22]: my explanation is, like, Airbyte is like a, became a $5 billion company just doing CDC.Reynold Xin [00:30:27]: Yeah, exactly.Reynold Xin [00:30:28]: CDC is, like, a veryMatei Zaharia [00:30:30]: It's hard.Reynold Xin [00:30:30]: It's one of the most boring but one of the most fundamental operations, like, powering modern society.Matei Zaharia [00:30:37]: huh.Reynold Xin [00:30:37]: But it's so brittle that, we joke that it's, should be called continuous data corruption, because you might change your schema on your OLTP database, and then the CDC pipeline fails to handleSwyx [00:30:48]: YeahReynold Xin [00:30:48]: the schema change.Swyx [00:30:49]: Yeah.Reynold Xin [00:30:49]: And then everything goes out.Swyx [00:30:51]: And there's all sorts of tricks that you can do, like, you add in, like, some versioning or whatever, but yeah.Reynold Xin [00:30:55]: Yeah, but it's a very, in general, very complicated. Like, I think at my keynote, I asked the audience put up their hand if they love their CDC pipeline. Only, like, maybe two people put it up. So if single store, like, about maybe a decade ago, I think the industry had this idea, hey, what if I built a single database that can handle both workloads? Now I don't.Swyx [00:31:12]: Which, like, by the way, every database person ever has ever always dreamed about this.Reynold Xin [00:31:15]: Yes. Yes.Reynold Xin [00:31:16]: This is the holy grail of database engineering is why not build a single system that can do both of this? But it ends up just being a lot of compromises. one, I think one of the first issue is that, hey, each. they say Postgres has a massive ecosystem, right? You want to be using the tools that's built for Postgres. And Spark, for example, had a massive ecosystem. There's a lot of libraries you want to use. If you were to create now a new thing, you don't have a ecosystem. You tend to create a new, smaller proprietary API, and you're lacking both, and it's also very difficult to make it performance-wise to be, comparable on either side. So it ends up being sucking on both. And our whole idea of LTAP, it's obviously a wordplay on the term HTAP, is that we think this is HTAP done right. HTAP wants to build a single engine for both. We think you can get 99% of what you need by unifying the storage, and just have a single storage layer. And once you have the single storage layer, if your Postgres databases are writing data in a column-oriented format, everything analytics can just go read that data directly without any delay, right? There's no pipeline in between, so all the data will immediately be available for reasoning analytics. I think I was telling some customers earlier, hey, when we talked about this is gonna be super useful for agents, I at first didn't really believe in it myself, even though we wrote that positioning.Lakebase, Agents, and Live Operational DataMatei Zaharia [00:32:39]: Yeah.Reynold Xin [00:32:40]: But then last night I was having dinner with a Australian customer, and they told me, “Oh, hey, one of the big issue we have is we have all these logs from our services, and we see SLA dips and want to investigate. But then there's no way for those agents to even understand what's going on in the actual databases themselves. All we see is just, like, product telemetry of the database and the services.” It would make those agents 10 times more powerful if understand, for example, who's placing those orders, what is happening, what exactly are they doing. So now I'm sold on our own message.Swyx [00:33:13]: Yeah.Reynold Xin [00:33:14]: I think it's really. It gets you the almost all of the benefits of the HTAP holy grail, which is, hey, make the data available immediately for reasoning analyticsSwyx [00:33:26]: Yeah, I think,Reynold Xin [00:33:27]: without compromiseSwyx [00:33:28]: in the way that humans are generally intelligent and want to have the ability and access to query anythingReynold Xin [00:33:34]: YeahSwyx [00:33:35]: while they do the work, they also need history and need context.Swyx [00:33:38]: And, like, where else does they get context? That's it's an analytical workload.Reynold Xin [00:33:41]: Exactly.Matei Zaharia [00:33:42]: Yeah. Yeah. And I remember when we had incidents with our databases and engineers said, “Well, I can't just run a giant query on it to see what's going on because that's gonna bring down the database and hoard it even more.” Like, that's the stuff that this gets rid of, because you spin up a whole separate fleet of machines that's doing the analytics. You're not overloading, like, the main databaseReynold Xin [00:34:02]: RightMatei Zaharia [00:34:02]: that's still trying to serve stuff.Reynold Xin [00:34:04]: Yeah.Matei Zaharia [00:34:04]: Yeah.Why LTAP Works Now: Parquet, Postgres, and LakebaseSwyx [00:34:05]: So this has been a dream for a while. what had to get done in order to get to today? Like,Reynold Xin [00:34:11]: Yeah.Swyx [00:34:11]: I feel like, you have announced variants of this several times, but it wasn't as clear as LTAP.Reynold Xin [00:34:18]: Yeah.Swyx [00:34:18]: I think LTAP is like Like, okay, we've got it, guys.Matei Zaharia [00:34:21]: This thing, yeah.Reynold Xin [00:34:21]: I was talking to somebody at Meta, and then he was asking me, “Hey, what's the catch? Why is it possible now?” And I think the reality is we took a lot of time to work on the Lakebase architecture. obviously a lot of it came from the Neon team, which is a separation of storage from compute. And it turned out it was just a tiny little step away going from that to this LTAP idea, which is, hey, we just. in the Neon architecture and in Lakebase architecture, we're writing data in oriented format to the open data lake, but in there we're writing in Postgres pages. Ali and I were spending a lot of time debating, hey, can we just change that to write in column-oriented format? And we're just debating, and one day, one of our engineers who's, like, super smart came in, he's like, “Hey, I just prototyped it. It works.”Swyx [00:35:07]: Wait, it's, prototype what?Reynold Xin [00:35:09]: Prototype, instead of storing the data in the data lake in the oriented formatSwyx [00:35:15]: ColumnReynold Xin [00:35:15]: like Postgres pagesSwyx [00:35:15]: YeahReynold Xin [00:35:16]: write them in Parquet.Swyx [00:35:17]: Yeah.Reynold Xin [00:35:18]: and he just made the observation that, hey, our storage fleet has a lot of extra idle CPUs And we could use those CPUs to do the transcoding from row to column, where row is good for OLTP, but column is good for analytics. so let's do that transcoding at that time. And as a matter of fact, once you transcode the data compresses better. So from those services writing to, for example, S3 or other data lake, like object stores, you can write them faster ‘cause now they are now smaller.Matei Zaharia [00:35:49]: Yeah.Reynold Xin [00:35:49]: So there's no overhead, it's no compromise in performanceMatei Zaharia [00:35:52]: Some CPU overhead.Swyx [00:35:54]: Yeah, because,Matei Zaharia [00:35:55]: YeahSwyx [00:35:55]: we had extra CPUs anyway.Matei Zaharia [00:35:56]: We had that fleet anyway, yeah.Swyx [00:35:57]: so the debate ended. it's one of the classics of, tech, issue of a lot of debate, but then somebody went ahead and just tried to prototype it and it worked.Matei Zaharia [00:36:06]: But, like, something this strategicSwyx [00:36:07]: That's rightMatei Zaharia [00:36:07]: and important to the company, I expect there to be, like, a kickoff thing, like a design doc. Nothing like that.Swyx [00:36:13]: Nothing like that.Swyx [00:36:14]: He just. We were debating in many meetingsMatei Zaharia [00:36:17]: Yeah.Swyx [00:36:17]: and then we're just debating whether it's possible or not from first principle.Matei Zaharia [00:36:20]: YeahSwyx [00:36:20]: and then, somebody just did it.Matei Zaharia [00:36:23]: Yeah, if you set yourself up so people do that'll be great. And that happened a bit with Omnigentt too. I think if I just had a doc on, like, we can make these together, everyone would, would think, “Oh, what about this? What about this?” But then you. if you try it out, it helps. And then if you have real users and they bash it and, like, it's still working, or in this case, if you have the workload, what the workload looks like, you can just test the same pattern then.Databricks' Culture of Fast PrototypingSwyx [00:36:47]: Yeah.Matei Zaharia [00:36:47]: Yeah.Swyx [00:36:47]: Tech aside, which is very cool, this is, like, the most important thing, the culture of innovation, and you don't have to ask my permission, you don't have like, do a whole form- formal process, just do it?Matei Zaharia [00:36:59]: Well, especially these days, I think withSwyx [00:37:01]: YeahMatei Zaharia [00:37:01]: AI, it's easier to buildSwyx [00:37:02]: But so, likeMatei Zaharia [00:37:03]: a prototypeSwyx [00:37:03]: I think you are very I made a lot of suite of, like, large companies and, like, I think that at scale, things slow down, and I'm sure you felt it already, but somehow you have this core of people that, like, are exempt. How? I think we hire and we work with really good people, and that's a very important part of it, and empowering them, but also spending a lot of time, maybe us in the trenches matter a lot also.Matei Zaharia [00:37:28]: Yeah, I think, I think first, people can adapt to being in the larger company, so that helps. And we wanna make sure they know that they can try stuff and settle debates and have a lot of examples of how it was done before, or launch a thing in beta or whatever. and then the other thing I do think as a company, like despite the size, we don't launch that many, like, products. We try to keep it pretty coherent. That's, that was the whole, like, theory of the company, was like instead of having, like, 20 Amazon services you need to set up, like a analytics and machine learning stack, you just have one, and it's, like, the same API, the same semantics across all of them, the same copy of the data. So that requires, like, unification. And then we added one more thing at a time. Like, we added storage with Delta Lake. We didn't used to do any storage. Then we added SQL, we added, machine learning platform stuff. So, but yeah, don't, don't do too many, but do those things well and, that also helps, it helps keep it manageable.Reynold Xin [00:38:33]: Yeah. The other thing we encourage a lot is instead of building, boil the ocean for everything, let's figure out how do we do it incrementally, how do we do it very quickly. Like, many of our productsMatei Zaharia [00:38:43]: YeahReynold Xin [00:38:43]: they're built in the span of weeks, and then we go to, hey. Like, usually my first question to whoever team is building is who's the target customer? Who are you working with? Are you on a first-name basis with them? Are you texting with them? I think having that very tight loop,Matei Zaharia [00:38:59]: Can you bring up another launch that comes to mind when, in this thing? I just want to give examples.Reynold Xin [00:39:04]: Omnigentt itself happened that way.Reynold Xin [00:39:05]: Yeah.Matei Zaharia [00:39:06]: Who's the customer? That's a good oneReynold Xin [00:39:34]: storage layer we did. we had, our largest customer at the time said like, “Okay, I need some. I want something in the cloud ‘cause, I. if the rest of our network is compromised, like this thing needs to be separate to store and query the events.” And then, talked to us, he said, “Okay, this is the rate of events per second. This is, like, the freshness I want. Can you do it?” So that was, like, way larger than any workload we had, and we had our, engineer, working on that, Michael Armbrust, and he worked just to make this work. And once it worked for them, it worked for everyone else. Yeah. This was early in the company, probably like four years in or something.Matei Zaharia [00:40:24]: 20- 2018?Swyx [00:40:26]: Yeah, ‘17, ‘18.Matei Zaharia [00:40:28]: Few companiesSwyx [00:40:28]: Do you have other examples?Matei Zaharia [00:40:30]: there'Swyx [00:40:31]: Maybe you have othersMatei Zaharia [00:40:31]: yeah, Clean Room, which is how you share data in a way without sharingSwyx [00:40:35]: YeahMatei Zaharia [00:40:35]: underlying data, but you allow specific operations. Those were done effectively initially just for two customers. I think the industry has a sense of, hey, maybe if you overfit to, like, one or two customers, it's gonna be really bad for you. But I think the, downside of overfitting is much smaller than the upside itself. And if you try to be too ambitious and boil the ocean, it's a much bigger problem.Swyx [00:40:58]: Yeah. Yeah.Matei Zaharia [00:40:58]: ‘Cause you might end up having no customer.Swyx [00:41:00]: Yeah, that's more, that's the more likely outcome.Matei Zaharia [00:41:02]: Yeah.Tech Companies vs. EnterprisesSwyx [00:41:03]: than you can pivot from there. I do think there is such a thing as a bad customer that sometimes you should fire. Yeah.Matei Zaharia [00:41:08]: They could exist sometimes if you drive. well, one of the challenge I think we probably see, and maybe many AI, so newer generation companies are seeing is, so tech companies are very different from tech companies or traditional enterprises.Swyx [00:41:22]: Yeah.Matei Zaharia [00:41:22]: And, if you optimize everything just for tech companies, you might have various challengesSwyx [00:41:27]: OhMatei Zaharia [00:41:27]: scaling them outside of tech companies.Swyx [00:41:28]: Okay, what likeMatei Zaharia [00:41:30]: YeahSwyx [00:41:30]: what like top three differences that you always think about?Reynold Xin [00:41:33]: Governance is a big oneMatei Zaharia [00:41:34]: I think, yeah, a big one is like, yeah, security, data privacy, governance, all that stuff. So usually if you're building some kinda like B2B or developer tool, like your biggest market is gonna be enterprises, but it's just very different. A company that's existed for like, it's had some form of IT for like 30 years, they have so many legacy systems or they operate in a regulated space. whereas a startup or, even like a, like sorta more recent tech company, all the. everything is new and pristine. So yeah, it's just different, and if you've never worked with enterprises or been in one, you just won't know about it.Reynold Xin [00:42:13]: Yeah.Matei Zaharia [00:42:13]: Yeah.Reynold Xin [00:42:13]: And the procurement process is probably quite different. There's far more stakeholders.Matei Zaharia [00:42:17]: Yeah, that is one. Yeah.Matei Zaharia [00:42:18]: Another piece that's interesting is I think some tech companies, people, will say, “Oh, I can build that myself,” right? I'll just build that myself.Matei Zaharia [00:42:27]: So then you go,Reynold Xin [00:42:28]: I don't think people say that about Databricks, butMatei Zaharia [00:42:31]: yeah, it dependsReynold Xin [00:42:32]: They do.Matei Zaharia [00:42:32]: They do?Matei Zaharia [00:42:32]: Yeah, the. Yeah, and it depends on the teams and things. So, but, on the other hand, like many of the enterprises say, “I don't, I never wanna be in the business of building that.” Like, I don't want my, whatever, I'm a retailer or something, I never wannaReynold Xin [00:42:45]: Yeah, sell clothes,Matei Zaharia [00:42:46]: be down because like some weird like nerd like couldn't get streaming pipelines working.Matei Zaharia [00:42:51]: That is not what I'm doing.Reynold Xin [00:42:53]: Yeah.Reynold Xin [00:42:53]: Yeah. This makes them great customers, to be honest, right?Matei Zaharia [00:42:55]: Yeah. But you have to understand that it's hard without having worked there and stuff, like you may not appreciate.Reynold Xin [00:43:01]: Look, I think they're all great. don't get me wrong, they have different challenges. But the, many of the tech companies, for sure there's a lot, far more DIY.Matei Zaharia [00:43:10]: On the flip side, you have people who are. they're very much experts in their domain, like they're building airplanes, they're, designing medicines, whatever, and they just want to bridge the technology, where like they don't wanna learn, databases or whatever. As cool as we think it is, even as interesting as the average software engineer might think it is to read a little bit, like they just never wanna know. They just say, “I have a, giant like, matrix or whatever with my, clinical data, like how do I, how do I like cluster it or whatever?” So yeah.The Dream Engine and Rewriting the Database StackReynold Xin [00:43:40]: Yeah. That's true. Okay, so and then I wanted to build out the dream engine, vision. where does this all lead? So one of the thing we, realized maybe a couple years back is that every single database engine out there, especially on the analytics side, are a decade old. pretty much everything that have reasonable traction are about a decade old. And they all started targeting some very specific narrow use cases, and then over time it's become more and more successful. They have grown in their ambition, and then they try to support more and more use cases. But the fastest way to support those use cases tend to be hacked around the abstractions that were initially created, that were not for those use cases.Matei Zaharia [00:44:23]: Yeah.Reynold Xin [00:44:23]: And then, but you can support them more or less okay. And before it, after 10 years of organic evolution that way, it becomes a gigantic pile of s**t.Reynold Xin [00:44:31]: the. And, but that includes Databricks. And very few company or very few systems, I think, have the gut to say, let's go start from scratch. Let's go back to the drawing board and design, knowing everything we know today after a decade of workloads and probably billions in revenue, let's attempt to rewrite it from scratch and make sure it will work and it can support all of these use cases. So we started doing that, but it's a very ambitious project. by the way, you can search on Wikipedia, there's this thing called second system syndrome.Matei Zaharia [00:45:08]: Yeah, I know that. Yes.Reynold Xin [00:45:09]: Or second system effect.Matei Zaharia [00:45:11]: Every developer must know what a second syndrome is.Reynold Xin [00:45:12]: It's you built your first thing and it works out great, and the second one's bound to fail because you become too ambitious.Reynold Xin [00:45:19]: And then you ask so many requirements.Matei Zaharia [00:45:20]: Or like you think everythingReynold Xin [00:45:21]: YeahMatei Zaharia [00:45:21]: and then you're likeReynold Xin [00:45:22]: You justMatei Zaharia [00:45:22]: you're, “I'm gonna design the perfect system this time.”Reynold Xin [00:45:24]: Yeah. And it turned out it's not perfect, and then it start failing and you're too ambitious, never launch, and you get killed. The, and the engineering team that started this, they were brilliant. I think we hired some of the best database engineers, on the planet into Databricks, and they were brilliant. Thank God it's not their second system. Many of them have built more than two in the past.Matei Zaharia [00:45:44]: Ah, nice.Reynold Xin [00:45:45]: But they were still worried about this, hey, building a database engine from scratch, I think the conventional wisdom is gonna take like five years to mature. This would be a very long-term project. It could fail. I think one of the engineers jokingly said, “Hey, maybe we just call it Reynolds Stream Engine.” If we name after a founder, maybe we then may get canceled or killed. But I think they built something pretty remarkable. they went back to. They changed the way the database engines were built from a paradigm point of view. Usually when y

Host: Darryl S. Chutka, M.D.  Guest: Stacey Rizza, M.D.  Although vector-borne illnesses can be acquired by travel to distant parts of the world, some can be acquired here in the U.S. As a result, these infections become pertinent to primary care clinicians as they can produce serious complications. When should we suspect a vector-borne illness in a patient? How do we distinguish it from other viral syndromes? What are some of the serious complications that can occur? In today's podcast, we'll be discussing three vector-borne illnesses including Zika virus, West Nile virus, and Dengue Fever. My guest is an infectious disease specialist, Dr. Stacey Rizza from the Mayo Clinic as we discuss “Vector-Borne Illnesses”.  Connect with us! Mayo Clinic Talks Podcast Season 6 | Mayo Clinic School of Continuous Professional Development 

https://youtu.be/xkCGHOYkdC0 Grant McKinstrie, CEO of Digital Position, is passionate about helping eCommerce brands grow by combining customer insights, data-driven marketing, and emerging technology. With more than two decades of experience in digital marketing, Grant has built a team that helps brands increase revenue through SEO, paid media, conversion optimization, and customer-focused growth strategies. We explore Grant’s DP Growth System: Ask AI where consumers congregate, Immerse yourself in their communities, Create content they crave, Engage them on Reddit and Quora, Have influencers create videos, and Turn craved content into ads. Grant explains why understanding customer conversations is more valuable than relying on assumptions, how online communities reveal unmet needs and buying signals, and how businesses can transform those insights into content, influencer partnerships, and advertising campaigns that drive measurable growth. He also shares how AI is changing marketing, the challenges of scaling an agency, and why innovation remains one of the most important drivers of long-term business success. — Build Yourself a Growth System with Grant McKinstrie  Good day. Steve Preda here with the Management Blueprint Podcast, and today my guest is Grant McKinstrie, the CEO of Digital Position, a full-stack agency that builds a growth system for e-commerce brands. Grant, welcome to the show.  Thank you so much for having me. Good to be here.  Well, it’s great to have you here. And I’d like to start by asking you: What is your personal ‘Why’, and what are you doing to manifest it at Digital Position?  Well, specifically when we think about the eCommerce space, there’s so much crap being sold out there. And also, in terms of what AI has done to the industry, it has allowed a lot of people to start a lot of different businesses, sell a lot of stuff, do a lot of dropshipping, and all these different things. It’s about trying to find the gems. It’s about finding the good people to work with and the businesses that are worth growing at the end of the day. There’s so much good stuff out there that gets pushed down because either they haven’t worked with a good agency or they just don’t know how to market themselves well enough.  And I think the drive behind trying to find those people who are genuinely nice to work with and brands that are absolutely worth promoting and bringing out into the world is awesome and very rewarding. Being able to do that is incredibly fulfilling. That’s not to say that we’re perfect in every way, shape, or form. And it’s not like every single business we work with is perfect either. We do what we can. But all in all, I want to be able to help market products, people, and businesses that are absolutely worth getting out into the world and getting more people to know about.  Yeah. That’s so interesting that you say that because I had a client in this space where you are, and they were a little conflicted because some of the brands they represented, they were not really proud of. And I think it really impacted their culture in turn. They felt that they were not operating with integrity with all of their clients, and that created internal friction. And it kind of held them back to some degree. So that’s fascinating that you talk about this. And I also noted on your website that your average client tenure is over four years, which I think bears testament to this. Yeah. In a large majority of cases, I mean, we’ve had certain clients for six years and, in some cases, even eight years. So when you have tenures like that, they certainly last a long time. And sometimes it just doesn’t work, and we’re also very willing to openly admit that. I don’t want anyone to think, “Oh, if we sign up with you, it’s four years, and then we’re just constantly paying you for, I don’t know, whatever reason it might be.” But genuinely, we’re here to see how we can legitimately grow the business and actually bring you profit dollars that you weren’t seeing otherwise.  Because so many businesses that we come across are just not able to allocate their marketing spend efficiently. And they’re just… I don’t know. Not to get too much into the nitty-gritty of things, but in a general sense, 95% of the businesses we talk to are essentially burning money. And in most cases, they’re being worked through an agency churn-and-burn system. And it hurts to see. Literally, I had a pitch two hours ago before this call where every single platform they were on was just burning money. They were trying to remarket to people who already knew about the brand and spending money on people who already knew about them and were already going to purchase from them.  And the agency was trying to tell them, “Hey, all of our metrics are great.” But the business is suffering because of it. It happens all the time. It generally results in tough conversations for us because agencies have such a bad reputation. And we’re always trying to pick up the pieces and revitalize that relationship. Which has its highs and lows in many ways. But we’re out here doing the best we can. Okay, so that’s a great segue because this podcast is all about frameworks—how to do something that maybe other entrepreneurs are trying to do, don’t know how to do, but you figured out. So do you have some kind of framework? Maybe it’s about getting an eCommerce company up and running on advertising and advertising profitably. Maybe it’s some other area in your business that is easy to explain in three to five steps. Does anything come to mind?  The biggest thing that we have realized lately is what we have deemed community engagement. One, because of AI, you can scrape information so easily across the internet, and you can get fed so much crap that AI is just going to automatically generate for you. But what really matters at the end of the day is: who is your audience, where the heck do they hang out, and what are they talking about?  So we are constantly looking to inject ourselves into Reddit threads, Facebook threads, YouTube comments, Quora—wherever those people possibly are. Get into the subreddits. Get into those Facebook communities. Get into the comments of influencers or whoever is relevant within that space, and talk to them. See what they’re talking about within those threads. Engage with them. Have a conversation so that you can understand what actually makes this person tick. What do they truly care about? What do they call things? What are they talking about on a daily basis?  So that when you start creating content that resonates with those people, you know exactly how to connect with them. Because, as I mentioned earlier, so many people are creating commoditized products and content because of AI, because it’s making it that much easier to do. Nobody is truly trying to connect with the consumer at the end of the day. And therefore, you’re going to have so many people who become numb to anything being thrown in their face unless they actually feel like they’re being spoken to.  So the biggest thing is to get to know the person on the other side of the screen. Go to where they hang out. Go to where they’re engaging. And listen to them. I think a lot of people forget that and want to go straight into data, metrics, spreadsheets, and all this stuff. When there is a human-to-human interaction happening within marketing every single day. And that is what you need to continue to focus on. Okay, so maybe that’s the beginning of the framework. So get to know the person—or the customer—or both.  Yeah. And it sounds really simple. It’s funny, when you put it that way, it’s just: listen to the person you’re trying to sell to. But it’s incredible how infrequently that actually happens. Because a lot of people will talk about, “My product is the best. My product is so good because it does this cool little thing that nobody else does.” But who really cares unless it’s actually solving a problem that somebody has? And unless they’re able to understand exactly how it’s going to make them feel in that moment when that problem is solved or how it connects to their core persona or whatever it might be. It’s a very simple framework. But it is the most important thing that a lot of people tend to neglect.  No, I love it. I love it. So what does the actual framework look like? I understand you go to Reddit, you go to Quora, and you listen. But what is the process? How do you even know which part of Reddit you should go to, what you should listen to, and who the customers are? Give me the rundown. What do you do when a new customer walks through the door and you want to figure out how to make them successful?  Yeah, of course. So I think Reddit is just the easiest example. I think it’s what a lot of people are familiar with, but it also provides value because it’s related to all the LLMs and what they like to cite as sources as well. Funny enough, one of the best ways to start is if you have a brand, a service, or something that you’re looking to build. Feed that into AI—Claude, ChatGPT, whatever works for you—and have it help you understand: “Hey, what subreddits should I be participating in?” If I want to sell vegetable seeds, for example—and that’s an example from a client we’ve worked with—or if I want to get more into gardening, where should I go?  It will point you to gardening, DIY gardening, seasonal gardening, and all these different places that have communities of people who are very specific when it comes to anything you want to know about gardening. Then you jump in there and see people talking about: “When should I start planting my tomatoes?” Or: “When should I do any transplanting?” Or: “How do I need to handle my watering schedule?” And then you have layers and layers of threads, topics, and information that you can gather from. People are giving it to you for free and telling you exactly how they handle those things.  And that turns into content. That turns into ways for you to engage with those people. It turns into ads because if you’re able to understand what their pain point is, then you can make an ad out of that. At the same time, you can pull a lot of that information using AI. But the biggest impact still comes from truly engaging with those people. So you said that when you figure out what those communities are talking about in their Quora or Reddit communities, then you can engage with them. You can create content, you can create ads, and you can engage. And I’m just wondering, are there other forms of engaging with customers other than through content and ads? Good question. So yeah, that’s the main part. You can directly comment within those Reddit threads, or you can start creating your own content within those Reddit communities. If you start to see a trend of multiple people asking, “How do I start planting my tomato seeds?” Or, “Where do I even start with this?” Then you can create an entire guide on your website. Build a blog post around it. Or you can get together with an influencer who’s able to make a video around it and show the entire process through a visual element as well. So you’re not just doing written content, but video too. And then you can even run ads around that.  Because one of the biggest things, for example, with this brand that I’m kind of alluding to, is that every single ad and every single piece of content they were putting out beforehand was very disconnected from the true gardener at the end of the day, or the true DIY gardener. Because everything they showed was a picture of this beautiful, perfect pepper or tomato that nobody ever experiences unless you’re operating a commercialized system with all of the technology they have access to. But somebody in their backyard is not going to have a perfectly round tomato or a perfectly formed pepper. And therefore, no one knows how to get there. So you have to show them the step-by-step process.  What soil do you need to buy? What seeds should you buy? And then you become part of that system because: “Oh, I need to buy seeds. Okay, I’m going to go to this company and buy seeds from them.” And they also helped me throughout this entire process by becoming the subject matter expert on what to do with tomato seeds. It becomes this kind of system that you naturally inject yourself into as you create content that connects with that person. Because the biggest thing was recognizing that all of the content they were putting out beforehand made people think: “Well, my food is never going to look like that if I plant it in my backyard.” Yeah. “But how can I get there so that I feel a lot less stressed about even starting?” And you’re providing this entire guide for me to follow so that I can become a better DIY gardener.  Yeah. I love it. It’s a great approach to basically figure out where to go, talk to the people, and then communicate with them and create helpful guides for them. And the influencer video—that’s also very clever. So that’s how you help drive growth for your clients. But how do you drive growth in your own business?  Yeah, good question. Funny enough, man, it is so much harder to do it for yourself when you are so focused on other people. Reflecting inward is always tough. But what we have recognized lately is that you have to have a good freaking offer. Because so many agencies in this space say the same stuff. I sat on Instagram for two hours one day and rifled through every single ad from marketing agencies in the space.  And everybody says the same thing: “You’re doing your ads wrong.” Or: “You have no idea what’s happening with your attribution.” Or: “Google Ads is making you lose money.” Or: “Meta Ads sucks.” And all these different things. And everyone is saying: “You should let us do a free audit for you.” Or: “Come talk to us and we’ll help show you what’s wrong.” It’s like, okay, there’s a pretty big gap there. I have to spend all this time talking to you just to figure out whether you’re a legitimate business and whether you’re actually going to solve my problem. And you’re not really offering anything other than: “Hey, let’s sit down and talk about it.” When everybody else is doing the exact same thing. So the offer across the industry is generally weak.  There are a few agencies that have well-built offers. What we personally figured out through A/B testing is that we don’t even try to lead with the marketing conversation. Because in some cases, businesses find it difficult to admit: “Hey, our marketing sucks.” Or: “Marketing is our problem.” But a lot of people can identify whether their website sucks. They can look at it and say it’s old or that it’s not converting well. It’s generally easier for people to make that connection than the marketing connection.  So we’ve built an offer around A/B testing. For just about any eCommerce business doing over $1 million in annual revenue, we’d love to do a free A/B test for them. We will build a landing page of their choosing. It could be their homepage. It could be a product page. It could be whatever. We will create a mock-up ourselves and come to the call with it. We’ll show them our version alongside theirs. They can decide whether it seems better or not. And if they want to move forward, we’ll implement it on their site for free. Then we’ll run an A/B test until we reach statistical significance and can determine whether our page or their page performs better.  Either way, there’s no cost to them. We just want to show that we’re capable of providing value. We want to demonstrate that we can create something better than what they currently have. If it works out, awesome. Let’s continue the conversation. If not, no harm, no foul. We weren’t able to improve it for them, and it doesn’t make sense to continue the conversation.  Yeah. That is impressive. So you’re actually building a competing site, and you show them that you could do a better job than they are, essentially. Yeah, exactly. Yeah. And it’s… I don’t know. There’s somebody that I interact with who always says, “There are no sacred cows. There’s no ego in all of this.” It’s just, “We genuinely want to show that we can provide value in any way, shape, or form here.” It has garnered a lot of interest because it’s low friction. It’s, “Hey, at the very least, when we come to the call, we are going to show you something, and hopefully you like it.” And 100% of the time we’ve done this, everybody has loved it.  So it’s been a great source of driving more leads, more conversations, and more at-bats for the business. Simply by having an offer that people want to see value from, as opposed to: “Hey, we’re going to do an audit. There’s going to be a long turnaround time. Then we have to figure out the next steps. Then there’s going to be this big price tag,” or whatever it is. Whereas we’re just going to do something for you for free. If it works, great. If not, you didn’t lose any sleep over it.  Yeah. Love it. That’s pretty cool. And I think what’s really cool about it is that you do it without disrupting their existing business. Exactly. So they don’t feel like, “Okay, maybe it’s at no cost to me. Maybe it’s a marketing thing.” But at the same time, if you’re interfering with my customers, that’s actually a negative. Because it can create damage. That’s my reservation about people who offer to drive business for me. Yeah. But then they want to use my LinkedIn profile, and they can spoil my reputation online. And I’m never going to allow it. Because it interferes with my business. So I love that you found a way around that. That’s pretty cool.  Absolutely. Yeah, and we’re hoping that it just continues to grow. Fortunately, AI has allowed us to move a lot faster with this because I think that historically would have been a major holdup. Mocking up a page is not a very easy task. But because we’re able to understand the business and generate something relatively quickly through our experience and understanding of how a page should be structured, it works out really well. Yeah. Love it. So switching gears here, let me ask you this: What is something that you’re actively trying to figure out in your business?  Ooh, boy. Scale. I think the ability to scale something like this is where I’m trying to figure out what is going to break next. Historically, we’ve struggled to figure out things like: “Oh, we need a really good offer to drive cold outbound leads.” We have historically been a referral-only business. And while that’s worked, it certainly isn’t as sustainable long term as building a proper, predictable cold outbound system.  Now that we have something that is starting to work, and we’re seeing more leads come in, the question becomes: How do we scale this without the business breaking if we suddenly see a significant increase in leads? Because realistically, in the past, it’s been rare that we’ve had so many leads in the pipeline that we didn’t know how to handle them. But we’ve also recognized that the type of service we provide is elevated. We consider ourselves a boutique service. We know we’re not the cheapest in the market. But what we do know is that we can absolutely drive additional profit dollars to your business. Because we’re looking at the full marketing picture.  We’re not just focusing on PPC. We’re not just focusing on SEO. We’re not just focusing on organic social. We’re looking at how all of those things work together. And then we’re looking at the business as a whole and trying to drive an actual P&L impact. Not just say: “Oh, ROAS in Google Ads is good, so everything must be great.” No. That’s not always the case. As I mentioned earlier, that can happen while you’re still burning money because you’re simply retargeting people who already know about your business.  So the goal is understanding that we provide an elevated service and finding the right talent to help deliver it. So that as we continue to scale, we’re able to maintain the level of service that we know we’re capable of providing. And making sure that the people leading those client conversations are able to deliver on that promise every single time as well. Hopefully that answers the question, for the most part.  So if you have the deals coming through, the cold outreach is working, and your offer is working, is it just a question of finding the talent, or are there other things that could break?  Yeah. I think it’s hiring and talent for sure. And then the other piece is continuing to maintain the operational speed behind it as well. Because expectations in the industry are changing dramatically. We went from bi-monthly reporting to weekly reporting, and now people want to know how things are moving every single day. AI has sped things up to the point where people’s expectations are changing at a rate that we need to keep up with. And that is certainly one of the more difficult things to navigate.  Especially when there are 30 to 1,000 new AI tools coming out every single day. Then you need to figure out: “What’s the best one that I’m going to be able to utilize long term, instead of just dumping it and moving to a new one next week?” So yeah, the operational piece has been very interesting over the past couple of years. It went from everybody using ChatGPT, to all of these different AI transcription tools. We moved into Notion. Now we’re using Vector, which is popping off right now. Claude has obviously made a lot of strides as well. And it’s about figuring out how we continue to pivot across all of these different tools. And I’m barely scratching the surface with those examples.  We also have to make sure that the entire team is able to adapt to these changes over time. Because for so long, you could stick with a single tech stack and a handful of tools for years, and not much would change. But now, because of AI, things are adapting, changing, and improving incredibly quickly. And the expectations of the client are moving just as fast. So you need to be able to keep up with that. I’ve always wondered about this thing that Steve Jobs said: The two primary functions of a business are marketing and innovation. And you are doing one of the two primary parts of the business. You could even argue that marketing is innovation as well. So the two things converge. How is it possible for an agency to innovate for multiple clients on a continual basis?  Yeah. That just comes down to trusting the team and having the right people in the right place. And that’s why I think hiring is one of the biggest things that we need to focus on. Because AI has raised the floor for so many people. But it has also really shined a light on the people who are able to work alongside it efficiently, speed up their processes, and use their experience to make decisions really fast. It is more powerful than ever to have a creative mindset and the experience of seeing how things impact multiple different clients. And to understand how you can shift strategy at any point in time. It also requires having that childlike curiosity mindset.  Being willing not to accept everything as fact. Being willing to pivot at any point in time. It’s truly about making sure that the people around you are willing to adapt and accept that they are not going to be right all the time. But they’re willing to keep trying, keep learning, and keep figuring out what the next step is. And not fall into complacency. Because if you do, AI has probably already rocked your world at this point. So the biggest thing is having people around you, a support system, procedures, and training that allow that to happen naturally. And trusting that they will be able to follow that and see the vision—or at least try.  That’s fascinating. If there’s a company trying to figure out what to do, how to make sense of all these different platforms, SEO moving to GEO, AI, Reddit, Quora, rising advertising costs, TikTok, and all these other platforms coming online—and their head is spinning—what do you recommend they do? How do they select an agency? Of course, they should go to you. But how should they select an agency? What criteria should they use to select someone, whether that’s you or somebody else?  Yeah. I mean, really, it just comes down to being growth-minded. And maybe I’m not fully understanding the question, but if you have any passion or drive to grow what you’re doing, you need to surround yourself with people who are constantly looking to push the envelope. Whether that be an agency or an in-house team. And in some cases, it might not make sense for you to have an agency. That really depends on your brand guidelines and how closely you hold them to your chest. Because sometimes bringing in an outside agency can be very difficult.  It takes time to get them up to speed. If you’re looking to develop your own internal style of content because you have a lot of protection around the brand, then building that internally is going to make a heck of a lot more sense. Because they’re constantly going to be able to talk in your language. As opposed to an agency that wants to be an arm of your business, but at the end of the day, it’s difficult for that to always be the case. We try to live and breathe that as much as we can, but we also understand there are limitations. So I would say if you are a brand with extremely tight brand guidelines, then you need to train internally and make sure that is built into the culture and into the marketing team.  Otherwise, everything you put out from that point forward is going to be disjointed from what the brand actually means or is trying to stand for. Therefore, you need to have that in-house and you need more control over it. Otherwise, if you understand that other people have great ideas, and you want to leverage that, and you appreciate that they’re looking at hundreds, if not thousands, of brands and seeing how they succeed in the market, then an agency can be a beautiful way to go. And it’s generally more cost-effective in most cases. You’re going to have an agency with maybe three to five people—sometimes even more—overseeing your account.  And in many cases, that’s for the same cost as a single internal employee. So being able to leverage the minds of five different people with five different viewpoints of the world, and five different pairs of eyes looking at your website, versus just one… In my opinion, you’re going to win every time. Assuming you have the right team behind you. Yeah. That makes a lot of sense. So essentially, you’re outsourcing your marketing function to an expert team. This is all they do. And they’re held to a high standard because they work with a lot of companies in a fast-moving environment. It’s similar to having an internal attorney versus using a law firm with high-flying attorneys who operate at the cutting edge. You can never really replicate that cutting-edge environment, which helps nurture those people on the other side. Yeah. Love it. So if you’re listening to this and you want to take your marketing to the next level, and you want an expert team at your service to figure out how to grow your brand across multiple channels—content, advertising, customer engagement, and all that stuff—then reach out to Grant. But where can they find you, Grant?  You can reach out to us through digitalposition.com. Feel free to connect with me on LinkedIn. I’m happy to chat with anybody. I’m more than happy to share anything I’ve learned along the way, whether you’re another agency, a brand, or whatever it might be. I firmly hold the belief that there is a massive sea of people out there to reach. And I’m happy to share any learnings that I’ve had. Because, boy, there’s so much to digest in this world, and I’m happy to share whatever I know. But yeah, digitalposition.com for anyone who would possibly want to work with us or chat. Otherwise, I’m on LinkedIn and happy to connect there as well.  Well, Grant McKinstrie, CEO of Digital Position, a full-stack agency that builds growth systems for eCommerce brands. Thanks for coming and sharing your experience and your view of the world. And if you enjoyed listening, make sure you follow us on YouTube and Apple Podcasts because every week I come with an exciting entrepreneur who is sharing the best of what they know. So thanks for coming, Grant, and thanks for listening.  Thank you so much for having me. Important Links: Grant’s LinkedIn Grant’s website

Break/Fix Podcast's mission is to preserve automotive living history and welcomes returning co-host Don Weberg from Garage Style Magazine alongside guest Wallace “Wally” Wyss, a longtime automotive writer turned fine artist. Wally recounts how early exposure to GM design chief Bill Mitchell and a British magazine feature on the Iso Grifo shifted him from poetry and art studies into advertising and then automotive journalism, including stints at Car Life and MotorTrend with vivid Sunset Strip stories. He explains how a chance ride in a 427 Cobra led to meeting Carroll Shelby, and launching a best-selling Cobra book and deep Shelby insights about Shelby's deal-driven approach. Wyss describes becoming a “barn find” hunter and author, then “accidentally” transitioning into painting exotic and classic cars after selling a Shelby portrait, outlining his process, commissions, design critiques, and ongoing radio show, while reflecting on creativity, reinvention, and concerns about AI's impact on writing. ===== (Oo---x---oO) ===== 00:00 Meet Wallace Wyss 01:51 Early Influences Detroit and How Cars Spark Writing Path 05:15 MotorTrend Hustle Stories 07:39 First Cobra Book Breakthrough 12:02 Becoming "The Barn Find" Guy 19:08 Car Design Critiques & Most Beautiful Cars List 22:00 Vector and Jerry Weigert Tales 22:56 Roger Penske Corvette Story 24:53 Pitstop: "The Man In White" Origin Story 27:48 Accidental Art Career 33:55 Wally's Painting Process 36:28 Witnessing Car History 38:49 Advice And AI Fears; Shout Outs and Wrap Up! ==================== The Motoring Podcast Network : Years of racing, wrenching and Motorsports experience brings together a top notch collection of knowledge, stories and information. #everyonehasastory #gtmbreakfix - motoringpodcast.net More Information: Visit Our Website Become a VIP at: Patreon Online Magazine: Gran Touring Follow us on Social: Instagram

DESPICABLE ME IS WAY SWEETER THAN EXPECTED?! Despicable Me Movie Reaction — First Time Watching! Support us on Patreon: Despicable Me Reaction (Full Length Watch Along):   / thereelrejects   Check out the DC Studios: Showcase Podcast HERE https://app.magellan.ai/listen_links/... John & Roxy react to Despicable Me for the first time as our classic animated movie reaction journey continues with the Illumination movie that launched Gru, the Minions, and one of the biggest animated franchises ever! With the new Minions & Monsters movie arriving later this year, it felt like the perfect time to finally dive into the film that started it all. This Despicable Me movie reaction follows Gru's plan to steal the moon, his rivalry with Vector, Dr. Nefario's wild inventions, the Bank of Evil, cookie robots, shrink rays, and the chaotic first appearance of the Minions. In this Illumination Despicable Me reaction and Despicable Me full movie review, John & Roxy break down Steve Carell's hilarious performance as Gru, Jason Segel as Vector, Kristen Wiig, Miranda Cosgrove, Julie Andrews, Russell Brand, and the surprisingly emotional story of Margo, Edith, and Agnes changing Gru's heart. From “It's so fluffy!” to the unicorn book, Super Silly Fun Land, the moon heist, and the Despicable Me ending breakdown where Gru finally becomes a real dad, this movie ended up being way more charming, funny, and heartfelt than expected. It also serves as a great reminder of why audiences fell in love with Gru and the Minions before all the sequels, spin-offs, and upcoming adventures expanded the franchise. Follow Roxy Striar YouTube:https://www.youtube.com/@TheWhirlGirls Instagram: https://www.instagram.com/roxystriar/?hl=en Twitter:  https://twitter.com/roxystriar Intense Suspense by Audionautix is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/... Support The Channel By Getting Some REEL REJECTS Apparel! https://www.rejectnationshop.com/ Follow Us On Socials:  Instagram: https://www.instagram.com/reelrejects/  Tik-Tok: https://www.tiktok.com/@reelrejects?lang=en Twitter: https://x.com/reelrejects Facebook: https://www.facebook.com/TheReelRejects/ Music Used In Ad:  Hat the Jazz by Twin Musicom is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/by/4.0/ Happy Alley by Kevin MacLeod is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/... POWERED BY @GFUEL Visit https://gfuel.ly/3wD5Ygo and use code REJECTNATION for 20% off select tubs!! Head Editor: https://www.instagram.com/praperhq/?hl=en Co-Editor: Greg Alba Co-Editor: John Humphrey Music In Video: Airport Lounge - Disco Ultralounge by Kevin MacLeod is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/by/4.0/ Ask Us A QUESTION On CAMEO: https://www.cameo.com/thereelrejects Follow TheReelRejects On FACEBOOK, TWITTER, & INSTAGRAM:  FB:  https://www.facebook.com/TheReelRejects/ INSTAGRAM:  https://www.instagram.com/reelrejects/ TWITTER:  https://twitter.com/thereelrejects Follow GREG ON INSTAGRAM & TWITTER: INSTAGRAM:  https://www.instagram.com/thegregalba/ TWITTER:  https://twitter.com/thegregalba Learn more about your ad choices. Visit megaphone.fm/adchoices

Play NowNew Age of the Primes and Generations reveals are all over the start of the 403rd Seibertron.com Twincast / Podcast. Joyride, Tailgate, Unicron and many more get looked at first, then the talk moves on to the clear plastic Weaponizers just released at overseas retail. Powerlix Red Alert with no fewer than eight Mini-Cons leads into a look at one of the SDCC exclusives for the year, with a Jem and the Holograms collaborative release featuring Blaster and the Kiss Players cassettes. A pair of listener questions get the crew diving in to more character re-imaginings and the top "Top 5" articles from the site archives before the episode closes out with the recurring Bragging Rights segment.

The plot thickens! As a follow up to our big episode on the Chaotix Casefiles, we're stealing a quick peek at the Chaotix 30th Anniversary Special from IDW! Our favorite detectives take a look back at one of their earliest cases, as a malevolent masked miscreant menaces the Mythsonian Museum! Just who is the phantom thief Enigma? And is there perhaps an even deeper mystery behind the mystery? It's a riveting story that begs to be told... whether Amy Rose wants it to be or not. (0:00:00) Intro/Main topic: Chaotix 30th Anniversary Special (0:12:50) Recap (0:21:22) Vector flashback (0:32:50) Espio flashback  (0:44:02) Charmy flashback (0:56:09) Enigma flashback (1:06:55) Final thoughts (1:17:48) Outro Amie Waters on Linktree Special appearance by Redasatomato as Megani

Today on The Gist, examining the upcoming criminal verdict for the Golden Gate Bridge climate protesters, breaking down the debate over jail time for high-impact civil disobedience. Then, Sadie Dingfelder returns for another installment of "Is It Bullsh*t?" to investigate the historical and scientific reputation of raccoons and rabies. Then, in the spiel, comparing the foreign policy legacies of Ronald Reagan and Donald Trump and analyzing whether current U.S. intervention strategies serve as a deliberate long game or merely export short-term geopolitical misery abroad. Produced by Corey Wara Video and Social Media by Geoff Craig Do you have questions or comments, or just want to say hello? Email us at ⁠⁠⁠⁠thegist@mikepesca.com For full Pesca content and updates, check out our website at https://www.mikepesca.com/⁠ For ad-free content or to become a Pesca Plus subscriber, check out ⁠⁠⁠⁠https://subscribe.mikepesca.com/ For Mike's daily takes on Substack, subscribe to The Gist List https://mikepesca.substack.com/ Follow us on Social Media:⁠⁠⁠⁠ YouTube https://www.youtube.com/channel/UC4_bh0wHgk2YfpKf4rg40_g⁠⁠⁠⁠ Instagram https://www.instagram.com/pescagist/ X https://x.com/pescami TikTok https://www.tiktok.com/@pescagist To advertise on the show, contact ⁠⁠⁠⁠sales@amplitudemediapartners.com Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In our thrilling three hundred and twenty-first episode (THREE, TWO, ONE, SPACE SPINNER 2000! We’re back!) Alex and Conrad continue their journey through the Galaxy's Greatest Comic with Progs 972-975 of 2000AD, covering December 1995 and January 1006. This time we're starting our coverage of 1996 by jumping into The Pit, finishing up PARAsites, check in on Luke Kirby, and start new adventures with Flesh and the debuting Kid Cyborg! Thrills Covered: Judge Dredd (9:09) The Pit Luke Kirby (23:42) Vector 13 (28:16) paraSITES (1:01:36) Kid Cyborg (01:10:32) Flesh (01:21:22) Darkness Visible (01:39:03) Contact the show at spacespinner2000@gmail.com Delight your friends and confuse your family with Space Spinner 2000 merch: https://tinyurl.com/spacespinnermerch Song: Jesus to a Child by George Michael 39.22

Tooth and nail, we've brought it. No stealth, no sting, but all style. This week, we're going full meta and podcasting about a podcast as we break down every episode of The Chaotix Casefiles! Vector, Espio, and Charmy have gotten caught up in the biggest case of their career, one full of old faces, new surprises, and a culprit reveal that genuinely made us go "...wait, really?!" So give us your listen, cause you wouldn't want to miss when THIAG is on the case! (0:00:00) Intro/Main topic: The Chaotix Casefiles (0:13:30) Prologue: Chaotix Are on the Case! (0:30:14) Episode 1: The Case of the Two-Faced Thief (0:47:22) Episode 2: The Case of the High-Stakes Heist (1:02:37) Episode 3: The Case of Malicious Museum Misdirection (1:18:31) Episode 4: Assault on G.U.N. Base X (1:30:35) Episode 5: The Case of the Catastrophic Copter Crash (1:48:57) Episode 6: The Case of the Solitary Sage Siege (1:55:48) Episode 7: The Case of the Red Specter (Part 1) (2:10:14) Episode 8: The Case of the Red Specter (Part 2) (2:27:44) Final thoughts (2:39:24) Outro Guest edited by Melanie Amie Waters on Linktree The Chaotix Casefiles (complete playlist) "Chaotix Are On the Case" "Chaotix Are On the Case" (Original Demo) Episode 7 fan animatic

Hosts Brad Causey and Spencer Alessi break down the 2026 Verizon Data Breach Investigations Report, focusing on the findings that actually matter for IT and security teams.The biggest surprise: vulnerability exploitation has overtaken stolen credentials as the top initial access vector, accounting for 31% of attacks, while credential abuse dropped to just 13%. This completely flips the script on years of "identity is the new perimeter" thinking.Topics covered include:Vulnerability explosion and remediation crisis: Why there are too many vulnerabilities and not enough time for patching, with only 26% of CISA KEV vulnerabilities fully remediated (down from 38%)The patching time paradox: Median remediation time increased from 32 days to 43 days despite organizations initially getting faster at patching from 2022-2024Web application sprawl: How the push to cloud and SaaS has created massive attack surfaces organizations don't own and can't patchThe top 4 initial access vectors: Vulnerability exploitation, phishing, credential abuse, and pretextingRansomware economics shifting: 48% of breaches involved ransomware, but 69% of victims didn't pay and median payments dropped to $139,875Mobile phishing success: Mobile-centric phishing had 40% higher success rates than email phishing as users get better at spotting email threatsSocial engineering evolution: The human element appeared in 62% of breaches, with pretexting requiring different countermeasures than traditional phishingShadow AI explosion: 45% of employees are regular AI users on corporate devices (up from 15%), with 67% using non-corporate accountsAI data exfiltration: Shadow AI is now the third most common non-malicious insider risk, with source code being the top data type leakedMCP and IDE extension risks: Real-world examples including PocketOS having their entire production database deleted by Claude connected to a railway CLI MCPBrad and Spencer emphasize that while the threat landscape is shifting dramatically, the fundamentals still matter. Organizations need to get comfortable with not being able to patch everything and focus on what matters most.Blog: https://offsec.blog/Youtube: https://www.youtube.com/@cyberthreatpovTwitter: https://x.com/cyberthreatpovFollow Spencer on social ⬇Spencer's Links: https://spenceralessi.comWork with Us: https://securit360.com | Find vulnerabilities that matter, learn about how we do internal pentesting here.

One of the major obstacles to understanding quantum mechanics is the difficulty we have in simply accepting what the theory itself is telling us. The problem is that we know what the everyday world looks like -- stuff, arranged in space, evolving through time. So we can't resist the temptation to impose that picture on the quantum description, even if it's not actually there. In this solo episode I talk about what it means to take quantum mechanics at face value, and the difficult work involved in understanding how the everyday world of our experience fits into the picture. Blog post with transcript: https://www.preposterousuniverse.com/podcast/2026/05/25/355-solo-looking-quantum-mechanics-in-the-eyeball/ Support Mindscape on Patreon. Here is the survey on physicists' opinions about unsettled big-picture questions: Afshordi, Halper, Rini, and Schirber, "Big Mysteries Survey: Physicists' Views on Cosmology, Black Holes, Quantum Mechanics, and Quantum Gravity." And here is a short technical overview on the ideas described in this episode: Carroll, "Reality as a Vector in Hilbert Space." If you want further papers, look at the papers cited in this one.

(Presented by TLPBLACK: A cybersecurity intelligence platform focused on sharing curated, high-sensitivity threat insights and research with trusted security professionals.) Three Buddy Problem x Ekoparty Miami: Jordan Wiens, co-founder of Vector 35 and creator of Binary Ninja, talks about a decade spent building a decompiler in a market everyone told him not to enter. He walks through why accessibility drove the whole project, how Binja's intermediate-language system stacks up against IDA, Ghidra, and Radare, and why language-specific decompilation for Rust, C++, and Go is the next real frontier. Plus, thoughts on AI disruption and why "the model can do it" misses the point that the model is just driving the tool, what verifiability really means, whether AI tilts the field toward offense or defense, and questions around subsidized tokens, the collapse of the CTF talent pipeline, and what happens to a craft when the shortcut is always one prompt away. Cast: Juan Andres Guerrero-Saade, Ryan Naraine and Jordan Wiens. Timestamps: 0:00 Introductory banter 1:22 Vector 35 and the origin of Binary Ninja 2:32 From CTFs and SCIFs to building a decompiler 3:27 Before Ghidra: when an IDA license was out of reach 9:47 Language-specific decompilation: Rust, C++, and Go 12:47 Running a 17-person bootstrapped shop with no org chart 13:50 DARPA money, In-Q-Tel, and staying independent 15:23 AI as disruptor: the model drives the tool 18:06 Verifiability and the Fast16 reversing story 25:10 How AI actually gets used inside the company 28:52 Frontier models and guardrails 33:30 Will AI favor offense or defense? 40:51 Shrinking CTF talent pipelines

Some of the most useful new Illustrator features are easy to miss if you aren't actively exploring the latest updates and beta tools. In this episode, Theresa Jackson talks with illustrator and toy designer Thaddeus Coates and digital artist Luke Choice about the new Illustrator features they're genuinely excited to use. Thaddeus shares how Illustrator fits into his character design and toy-making process, including using Turntable to communicate ideas to manufacturers. Luke dives into the practical side of Illustrator updates, from snapping improvements and smoother performance to AI-assisted vector workflows inside Illustrator Beta. Whether you spend your days designing logos, illustrating characters, building client work, or experimenting with new ideas, there's probably a feature in this episode you haven't tried yet. Episode Highlights Prototyping with Turntable: Hear how Thaddeus Coates uses Turntable to prototype toy ideas and communicate designs to manufacturers faster. Live Preview Tools: Learn why Illustrator's Live Preview drawing tools feel more natural and responsive for illustrators working on iPad and desktop. Workflow Efficiency: Hear Luke Choice explain how small workflow improvements, including font browsing and snapping updates can save serious production time. Sketch to Vector: Explore how Sketch to Vector in Illustrator Beta is changing the way artists turn rough sketches and low-resolution artwork into editable vectors. Real-World Application: Hear both guests share examples of using Illustrator's newest features for experimentation, iteration, and client work. Resources CreativePro Week 2026: Nashville, June 29–July 3, 2026. https://creativeproweek.com/ CreativePro Events: https://creativepro.com/events/ Event Savings: Save $100 on any CreativePro event in 2026 with the discount code PODCAST: https://creativepro.com/events/ Membership Discount: Get $15 off one year of CreativePro membership with the discount code PODCAST: https://creativepro.com/become-a-member/ Adobe Help: What's New in Illustrator on the Desktop: https://helpx.adobe.com/illustrator/desktop/new-features/whats-new.html Thaddeus Coates: https://www.hippypotter.com/ Luke Choice: https://www.velvetspectrum.com/

In this episode of Head, Heart and Boots, Brandon and I sat down with J. Brad Britton for one of the most meaningful conversations we've had on the podcast. J. Brad spent decades leading inside the Cutco and Vector organizations, but this episode centers on something far deeper - his relationship with his son Sam and how that journey completely changed the way he thinks about leadership, communication, and human potential. What stuck with us most was hearing J. Brad talk about realizing Sam understood far more than anyone had assumed for years. It forced him to rethink not only his parenting, but the way we all judge people based on surface behavior instead of curiosity and empathy. We also dug into leadership lessons from Cutco, coaching young salespeople, and why presence and encouragement matter so much when developing people. This episode is thoughtful, emotional, and packed with perspective that applies far beyond business. Hope you enjoy Chris Why You Should Listen: [00:05:42] The moment J. Brad realized his son understood far more than anyone had believed for years [00:14:18] How raising a child with apraxia reshaped his perspective on leadership, patience, and communication [00:24:07] Why curiosity and empathy matter more than assumptions when working with people [00:36:12] Leadership lessons from decades inside the Cutco and Vector organizations developing young salespeople [00:49:03] A powerful conversation about fatherhood, encouragement, and learning to truly see the people in front of you Did you know... Only 30% of businesses listed for sale actually find a buyer? Even more striking, just 10% of those sell for the price their owners anticipated or higher, meaning only 3% of all business owners achieve their desired sale price. By focusing on understanding and enhancing your enterprise value, you can significantly boost your chances of joining that successful 3%. Business Health & Value Assessment Start Assessment Know Your Enterprise Value. See Your Potential Gaps. Complete this assessment in less than 15 minutes and receive a free assessment for your business that includes: A Lite Valuation Of Your Business Your Value Multiplier Per Your Industry Health Assessment Per Our PYB Methodology Business Value & Growth Roadmap Tailored For You Value Acceleration Strategies Spotlight on Floodlight: Your Secret Weapon for Sales & Scaling This isn't a paid plug. It's real talk from the front lines. If you've ever thought, “How do I get a VP-level sales leader or even a sales team without hiring full-time?” Floodlight has the answer. Fractional Sales Leadership They act as your outsourced VP of Sales, taking full responsibility for training, managing, and growing your sales team. No six-figure hire needed. Clients often close 20 to 50 percent more deals within six months, thanks to data-driven coaching, CRM setup, scripts, and performance reviews.More at floodlightgrp.com/sales Commercial Sales MasterCourse A self-paced, video-driven B2B sales course designed specifically for restoration teams. Perfect for building commercial revenue and getting free from TPA handcuffs. Covers mindset, prospecting, pipeline building, LinkedIn lead generation, and includes a $250 discount with code SALESBOOST.Details at floodlightgrp.com/courses Tailored Consulting & Coaching Floodlight's Propel Your Business methodology offers a full-circle roadmap: financials, sales, marketing, leadership, recruiting, productivity. All built for contractors. These aren't “life coaches.” They're former restoration owners who've lived the chaos and know how to scale out of it.Explore more at floodlightgrp.com Live Training, Tools & Strategic Partnerships Floodlight also delivers live onsite and virtual training, keynote speaking, and leadership tracks covering operations, project management, and strategic growth. Bonus: They've vetted tools like Xcelerate, Liftify, and Sureti. Floodlight clients get access to exclusive discounts on tech that actually moves the needle.See all partnerships at floodlightgrp.com/partners Why it matters for you as a listener You don't need to figure this stuff out alone. If you're serious about sales growth, operational clarity, exit readiness, or leadership development, Floodlight is already helping folks like you scale smarter. And you get it from industry insiders. People who've sat in your chair, survived the fires, and built systems that actually work.

Vector search has risen to become a foundational tool in modern search and retrieval systems, including the RAG pipelines that power many AI applications. However, the demands on retrieval systems are growing more sophisticated, which is revealing the limits of relying on a single vector similarity score. Vespa is a popular open source search and The post Vespa AI and Surpassing the Limits of Vector Search appeared first on Software Engineering Daily.

Vector search has risen to become a foundational tool in modern search and retrieval systems, including the RAG pipelines that power many AI applications. However, the demands on retrieval systems are growing more sophisticated, which is revealing the limits of relying on a single vector similarity score. Vespa is a popular open source search and data serving engine. Central to Vespa’s architecture is tensor-based retrieval, which is an approach that represents data as tensors rather than simple vectors. Tensor-based retrieval enables richer mathematical operations and more flexible ranking functions that can surmount the limitations of a single vector similarity score. Radu Gheorghe is a software engineer at Vespa with a background spanning nearly 12 years of consulting and training on Elasticsearch and Solr. In this episode, Radu joins Sean Falconer to discuss why vector similarity alone falls short in production, how tensor-based retrieval generalizes to support richer ranking functions, the trade-offs in chunking and multi-stage re-ranking architectures, and where AI search is headed next. Full Disclosure: This episode is sponsored by Vespa. Sean’s been an academic, startup founder, and Googler. He has published works covering a wide range of topics from AI to quantum computing. Currently, Sean is an AI Entrepreneur in Residence at Confluent where he works on AI strategy and thought leadership. You can connect with Sean on LinkedIn. Please click here to see the transcript of this episode. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post Vespa AI and Surpassing the Limits of Vector Search appeared first on Software Engineering Daily.

Vector search has risen to become a foundational tool in modern search and retrieval systems, including the RAG pipelines that power many AI applications. However, the demands on retrieval systems are growing more sophisticated, which is revealing the limits of relying on a single vector similarity score. Vespa is a popular open source search and data serving engine. Central to Vespa’s architecture is tensor-based retrieval, which is an approach that represents data as tensors rather than simple vectors. Tensor-based retrieval enables richer mathematical operations and more flexible ranking functions that can surmount the limitations of a single vector similarity score. Radu Gheorghe is a software engineer at Vespa with a background spanning nearly 12 years of consulting and training on Elasticsearch and Solr. In this episode, Radu joins Sean Falconer to discuss why vector similarity alone falls short in production, how tensor-based retrieval generalizes to support richer ranking functions, the trade-offs in chunking and multi-stage re-ranking architectures, and where AI search is headed next. Full Disclosure: This episode is sponsored by Vespa. Sean’s been an academic, startup founder, and Googler. He has published works covering a wide range of topics from AI to quantum computing. Currently, Sean is an AI Entrepreneur in Residence at Confluent where he works on AI strategy and thought leadership. You can connect with Sean on LinkedIn. Please click here to see the transcript of this episode. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post Vespa AI and Surpassing the Limits of Vector Search appeared first on Software Engineering Daily.

Vector search has risen to become a foundational tool in modern search and retrieval systems, including the RAG pipelines that power many AI applications. However, the demands on retrieval systems are growing more sophisticated, which is revealing the limits of relying on a single vector similarity score. Vespa is a popular open source search and data serving engine. Central to Vespa’s architecture is tensor-based retrieval, which is an approach that represents data as tensors rather than simple vectors. Tensor-based retrieval enables richer mathematical operations and more flexible ranking functions that can surmount the limitations of a single vector similarity score. Radu Gheorghe is a software engineer at Vespa with a background spanning nearly 12 years of consulting and training on Elasticsearch and Solr. In this episode, Radu joins Sean Falconer to discuss why vector similarity alone falls short in production, how tensor-based retrieval generalizes to support richer ranking functions, the trade-offs in chunking and multi-stage re-ranking architectures, and where AI search is headed next. Full Disclosure: This episode is sponsored by Vespa. Sean’s been an academic, startup founder, and Googler. He has published works covering a wide range of topics from AI to quantum computing. Currently, Sean is an AI Entrepreneur in Residence at Confluent where he works on AI strategy and thought leadership. You can connect with Sean on LinkedIn. Please click here to see the transcript of this episode. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post Vespa AI and Surpassing the Limits of Vector Search appeared first on Software Engineering Daily.

Jeff Haas Talks Malek: Reigning Devil, Indie Hustle, and Building Worlds Without Limits Jeff Haas is the kind of creator who doesn't just make comics—he builds ecosystems. From Sanctus at Arcana Publishing to the genre-bending Nightmare Patrol, Haas has consistently delivered stories driven by atmosphere, character, and ambition. Now, with Malek: Reigning Devil Volumes 1–3 live on Kickstarter, he's doubling down on a myth-heavy, creator-owned vision that reflects years of growth, risk-taking, and indie resilience. In his conversation with Al Mega on the Comic Crusaders Podcast, Haas dives deep into the evolution of Malek, the creative challenges behind expanding the series, and what crowdfunding really demands from modern creators. He also opens up about balancing creation with advocacy—using his platform and publicist experience to uplift fellow indie voices. This episode is equal parts inspiration, strategy, and celebration proof that indie comics aren't just surviving, they're thriving. YT: CCP Ep 655 Support Malek: Reigning Devil 3 at https://www.kickstarter.com/projects/theendofallterminus/malek-reigning-devil-3 Thank You for Watching / Listening! We appreciate your support! Episode 655 in an unlimited series! Host: Al Mega, Follow on X | Instagram | Facebook: @TheRealAlMega / @ComicCrusaders Make sure to Like/Share/Subscribe if you haven't yet: / comiccrusadersworld Twitch: / comiccrusaders Visit the official Comic Crusaders Comic Book Shop: comiccrusaders.shop Visit the OFFICIAL Comic Crusaders Swag Shop at: comiccrusaders.us Main Site: https://www.comiccrusaders.com/​​​​ Want to create amazing live streams like ours? Then look no further than StreamYard! The BEST and EASIEST to use Streaming Solution on Earth! Check it out at: : https://streamyard.com/pal/d/6492786798886912

An airhacks.fm conversation with Ian Rogers (@Ian Rogers) about: ZX Spectrum 128K with rubber keys and a burning side grill, Basic programming competitions, REM commands as ASCII art, PC versus Amiga and Archimedes era in the UK, fractal landscape generators for Wing Commander 4 cut scenes, Ocean Software in Manchester and the Head Over Heels game, Manchester Baby and Williams tube as the first stored-program computer, Steve Furber and ARM origins at the University of Manchester, Cosworth and Pi Research Formula One telemetry, transputers and embedded PowerPC data loggers, dynamic binary translation with the Dynamite simulator, ICL 2900 emulation for the Israeli tax system, MIPS to Itanium binary translation for SGI machines, Transitive Corporation and the PowerPC to x86 product that became Apple Rosetta, the Steve Jobs era at Apple, Spark to Power binary translation and the IBM acquisition of Transitive, JDBC versus ODBC API design observations, java.util.Vector and java.util.Hashtable synchronization decisions, StringBuilder array copying overhead from removing synchronization, DARPA HPCS languages Fortress, Chapel, X10, just-in-time parallelization from Java bytecode, LCC compiler from Princeton and the iBerg backend, JikesRVM as a metacircular Java VM written in Java, GNU Classpath and Sable VM by Etienne Gagnon, Apache Harmony port of JikesRVM to Windows, Maxwell and Maxine VMS as GraalVM precursors, Bernd Mathiske and the Sun acquisition by Oracle, GNU Classpath impact of the openJDK GPL release at FOSDEM 2006, Mark Wielaard and Rémi Forax FOSDEM stories, trace compilation and de-optimization parallels with JIT, Azul Systems Vega hardware and concurrent garbage collection, C4 collector design influencing ZGC and Shenandoah, Gil Tene's telephone exchange mentality for JVM responsiveness, page unmapping and signal handler memory pressure problems in HotSpot, Cliff Click and Modular, Google Android Runtime (ART) replacing Dalvik, transactional memory for class initializers in ART, ELF files and OAT format for ahead-of-time compilation, WhatsApp bytecode obfuscation breaking the ART verifier, lock balance verification for speculative lock optimizations, D8 and R8 Android compilers, Goit internal Google bytecode optimizer, Jeremy Manson and Google's OpenJDK variant, Linux kernel performance work and perf tooling, JikesRVM stack trace format making exception-heavy DaCapo benchmarks faster than HotSpot, Energy Efficiency across Programming Languages study comparing Java and Go, Ian Rogers on twitter: @Ian Rogers

If you want more workflows and tactics to build a business with AI, check out this free workshop: https://www.ideabrowser.com/workshop I sit down with Andrew Wilkinson and we go deep on how he's restructured his work, his health, and his family office around AI agents. Andrew walks me through Deep Personality (an app he vibe-coded after running psychological screens on himself and his girlfriend), the autonomous SaaS business he runs through agent harnesses like Harbor, and the vector-database setup that lets him query Tiny and his personal holding company like an oracle. We cover where software is headed, why he's pouring capital into TSMC and data center stocks, and the daily AI workflows he's built around health, email triage, and a personalized morning podcast. Listeners walk away with concrete prompting tactics, agent architectures, and a frank read on where the moats are moving. Timestamps: 00:00 – Intro 01:50 – The OpenClaw Unlock 04:53 – Demo: Deep Personality App 10:38 – Harbor: An Agent Harness For Real Companies 12:30 – Autonomous Companies: Hype Vs. Reality 17:30 – Credibility As The Missing Layer For Vibe-Coded Products 20:14 – Centralizing Data Pipelines 21:35 – Vector Databases 23:22 – Transitioning Companies to Agentic Companies 25:22 – Where Andrew Would Build Today 27:10 – The New Interface 28:21 – Why build now 30:59 – Replacing Adapar: A Networth Wealth Platform 33:29 – Services As The New Software 35:46 – G-Brain Explained and Andrew's OpenClaws 45:31 – Closing Thoughts Key Points Andrew runs a SaaS business called Deep Personality almost entirely through agents, generating roughly $20K of revenue while debugging eats half his time. Harbor (github.com/geekforbrains/Harbor) gives agents a GUI-style harness — dev, marketing, and support agents that can autonomously merge PRs and adjust ad budgets across PostHog, Meta, and Reddit. Andrew's family office swapped headcount for a $40K/month Claude bill; his CFO, who had zero coding background, vibe-coded a replacement for Adapar (priced at $50K–$100K/year) in about two weeks. Vector databases trained on Tiny and Andrew's holding company let him query 132 minority investments, P&Ls, and headcount data conversationally. For builders today, Andrew suggests aiming for a $1M–$2M product, then parking gains in TSMC and data center exposure given how fast software moats are eroding. His best prompting tip: ask the model to interview you with multiple-choice questions before generating any output. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND ANDREW ON SOCIAL X/Twitter: https://x.com/awilkinson Deep Personality: https://deeppersonality.app Tiny: https://www.tiny.com

For episode 250, we're chatting with Tomás (Tommy) Gutierrez, head brewer at Vector Brewing in Lake Highlands (east Dallas). Tommy enjoys brewing, cooking, and making music, and we get into just about all of that, including his top five guitarists. We also discuss the origin of some of the brewery's collaboration beers and recent beer dinners. More on the beats side, catch our conversation about Momo Boyd, Angine de Poitrine, and MorMor. Enjoy!

Final Fantasy VI - Episode 3This Week: Get to Vector. Next Week: Finish the banquet.  What's a video game book club? Exactly what you think! Some clubs read books, we play video games. Join us! Discord: https://discord.gg/hfnusHE Email: squelchcast@gmail.com Listen: www.squelchcast.com Support: www.patreon.com/Squelch or www.twitch.tv/dan0play 

Canva's mission is to empower the world to design, and by most measures, it's working. Millions of people create content in Canva every day, which means design is no longer something that belongs exclusively to designers. Now, with the acquisition of Affinity, Canva is making a move into professional territory. So what does that actually mean for those of us who make a living in this space? In this episode, Theresa Jackson sits down with Steve Caplin to dig into Affinity by Canva: what it is, how it works, and why the conversation around it goes well beyond the software itself. They give an honest take on where Affinity genuinely impresses and where it still comes up short for professional work, covering the same questions a lot of designers are already wrestling with about their role in a changing industry. If you've felt friction between your design team and the non-designers who use Canva, or if you've found yourself wondering how your job is evolving, this one's worth your time. Episode Highlights Switching between Vector, Pixel, and Layout within a single document is a departure from everything most designers are used to, and Theresa and Steve get into why that matters Theresa calls Affinity Canva's "olive branch" to professional designers, and unpacks why that framing deserves a second look Affinity's live filters and real-time previews create a noticeably different editing experience, and the episode explores what that unlocks "Free" as a pricing strategy has real implications for who gets to call themselves a designer The episode covers what Affinity still lacks, particularly around publishing workflows, automation, and accessibility, and why those gaps keep professionals anchored to InDesign and Adobe The tension between design teams and non-designers using Canva is real, growing, and worth talking about openly Designers are once again being asked to justify their value, and this conversation doesn't shy away from that The bigger question isn't which tool to use; it's what's shifting in the design industry and how to position yourself within that shift Resources CreativePro Week 2026, Nashville, June 29–July 3, 2026: https://creativeproweek.com/ CreativePro Events: https://creativepro.com/events/ Save $100 on any CreativePro event in 2026 with the discount code PODCAST: https://creativepro.com/events/ Get $15 off one year of CreativePro membership with the discount code PODCAST: https://creativepro.com/become-a-member/ Steve Caplin: https://stevecaplin.com/ Theresa Jackson's Self Portrait with Photoshop Displacement Map Filter: https://mir-s3-cdn-cf.behance.net/project_modules/max_3840_webp/00bfb313226357.56271a3df0ccf.jpg Canva Create Keynote: https://www.youtube.com/live/9HkO8masPT0 Affinity Download: https://www.affinity.studio/download Affinity for Photoshop Users by Steve Caplin: https://creativepro.com/affinity-photoshop-users/ YouTube: Displace Filter in Affinity: https://youtu.be/_9ZFMs1GkPg

This is the audio version of the Naavik Digest newsletter published on April 26th, 2026. This week, we dive into Unity's ongoing turnaround, the promise of Vector (its ad platform), and what comes next as AI evolves game development.You can read the newsletter (with even more sections and visual detail) here: https://www.naavik.co/digest/unitys-ad-driven-turnaroundLet us know what you think by sending us a note at podcast@naavik.co.Watch our episodes: YouTube ChannelFor more episodes and details: Podcast WebsiteFree newsletter: Naavik DigestFollow us: Twitter | LinkedIn | WebsiteSound design by Gavin Mc Cabe.

SaaStr 851: The Agents, Episode 002. Managing 20+ AI Agents: Lazy Agents, Stealth Churn & the Death of 60% Solutions In Episode 2 of The Agents, Amelia Lerutte, Chief AI Officer at SaaStr, and Jason Lemkin, Founder and CEO of SaaStr, share the trials, tribulations, victories, and minor defeats of managing 20+ AI agents in production. With three humans and 20+ AI agents now driving more revenue and output than SaaStr did with 20+ FTEs in 2020, this weekly series goes deep on what's actually working, breaking, and changing in the agentic era. This week's episode covers: 00:00 Welcome to The Agents Episode 2 01:00 Lazy Agents: How an AI agent silently deleted Amelia's session from the SaaStr Annual top 10 06:30 When agents blame the API: agentic accountability and the need for daily QA 09:00 The 60% Solution Problem: Why HubSpot's new AEO tool failed and got vibe coded better in 10 minutes 14:00 Figma Make vs. Replit, Lovable, and v0: Why no one will pay for "good enough" AI products 17:30 Classic Figma is now Grandpa Software: Production breakdowns and why Illustrator's agent is winning 21:00 Stealth Churn in Canva, ChatGPT, and beyond: The hidden metric every leader needs to watch 27:00 Why Claude Cowork created lock-in and killed ChatGPT usage for Amelia 30:00 Forward Deployed Engineers vs. Self-Serve: Why FDE light is the answer for SMB AI deployments 36:00 Vector breaks the agent freeze: How a 15-minute CEO-led deployment won SaaStr's business 40:00 The Agent API Test: Which APIs work best with AI agents (Salesforce wins, Marketo fails) 46:00 Resend, 11 Labs, and OpenRouter: The new gold standard for agent-friendly APIs 50:00 The Marketo collapse: When your marketing automation platform can't honor unsubscribes 55:00 Building an AI VP of Finance: Why collections is the next agent frontier at SaaStr 1:00:00 SaaStr Annual 2026 is three weeks away: May 12-14 in the SF Bay Area Topics covered: AI agents, agent management, lazy agents, stealth churn, vibe coding, Replit, Lovable, v0, Figma Make, HubSpot AEO, Claude Cowork, forward deployed engineers, FDE, self-serve AI, Vector, Salesforce, Marketo, Resend, 11 Labs, agent APIs, AI VP of Finance, collections automation, SaaStr Annual 2026 SaaStr Annual 2026 | May 12-14 | Come learn how to build, deploy, and manage AI agents from the leaders at Salesforce, Replit, Vercel, Cloudflare, and more. Register at saastr.ai Subscribe for weekly episodes of The Agents and the SaaStr Podcast. #AIAgents #SaaS #SaaStr #AgenticAI #VibeCoding

Final Fantasy VI - Episode 2This Week: Play until Locke gets out of bed.Next Week: Get to Vector.  What's a video game book club? Exactly what you think! Some clubs read books, we play video games. Join us! Discord: https://discord.gg/hfnusHE Email: squelchcast@gmail.com Listen: www.squelchcast.com Support: www.patreon.com/Squelch or www.twitch.tv/dan0play 

The mobile gaming ecosystem is shifting fast this month. We break down the shocking deplatforming of Freecash, a $500M+ rewarded ad network, and what it signals for the future of user acquisition. Then we dive into Unity's major strategic pivot: shutting down ironSource and going all-in on Vector. Is Vector actually working, or just great marketing?Topics Covered:● Freecash ban: what happened and why it matters● The future of rewarded ad networks● Unity shutting down ironSource● Vector performance, growth, and real-world results● The ongoing battle with AppLovin

⬥EPISODE NOTES⬥ What if the device quietly recording your daily commute could be turned against you in the time it takes to order a burger? That is not a hypothetical -- it is a demonstrated reality. Alina Tan, Security Architect and Co-Founder of HE&T Security Labs, and George Chen, Security Architect for a large global company, have spent years dissecting the attack surface of connected vehicle peripherals. Their research -- presented at SecTor and Black Hat Asia 2025 -- introduces a novel attack technique they call "DriveThru Hacking": an automated method for compromising dashcams through Wi-Fi within a standard drive-through window. The attack is unsettling in its simplicity. Most dashcams ship with default or easily guessable credentials, and many manufacturers do not even allow users to change them. Within a six-minute exposure window, Alina and George's tool -- DriveThru Hacker -- can discover, connect to, and exfiltrate video, audio, and GPS data from a target dashcam, then use an LLM to stitch together a timeline of the owner's home, workplace, daily routes, and private conversations. The result is a shockingly detailed picture of someone's life, assembled entirely from a device most people never think to secure. The research goes further than individual privacy. George walks through how 4G/5G-connected dashcams dramatically expand the attack surface beyond physical proximity -- opening doors to remote credential stuffing, API privilege escalation, and web-based attacks on cloud-connected accounts. More alarming still, Alina and George demonstrate how compromised dashcams can be converted into a mobile botnet -- a network of roaming, internet-connected nodes whose reach is not bounded by geography. Unlike static IoT devices, these infected cameras move through cities, near sensitive installations, and into places that are deliberately obscured from public maps. The conversation also digs into the broader ecosystem: the infotainment network and CAN bus segmentation (or lack thereof), over-the-air firmware update security, the challenge of detection and response when dashcams have no audit logs whatsoever, and what responsible disclosure looked like when contacting over a dozen manufacturers -- most of whom had no dedicated security inbox and some of whom had no contact information at all. Alina and George close with practical hardening recommendations for both consumers and manufacturers, and a look at what intrusion prevention for embedded devices might look like as this research continues. The connected car conversation has long focused on the vehicle itself. This episode makes the case that the accessories attached to it deserve equal scrutiny -- and that the window to act, like the drive-through line, is shorter than most realize. ⬥GUESTS⬥ Alina Tan, Security Architect and Co-Founder at HE&T Security Labs | Website: https://www.heatsecuritylabs.com/ George Chen, Security Architect for a large global company | On LinkedIn: https://www.linkedin.com/in/geoc/ ⬥HOST⬥ Sean Martin, Co-Founder at ITSPmagazine, Studio C60, and Host of Redefining CyberSecurity Podcast & Music Evolves Podcast | Website: https://www.seanmartin.com/ ⬥RESOURCES⬥ HE&T Security Labs | https://www.heatsecuritylabs.com/ DriveThru Hacking Session (Black Hat Asia 2025) | https://blackhat.com/asia-25/sponsored-sessions/schedule/index.html#drivethru-hacking-45214 The Future of Cybersecurity Newsletter | https://www.linkedin.com/newsletters/7108625890296614912/ More Redefining CyberSecurity Podcast episodes | https://www.seanmartin.com/redefining-cybersecurity-podcast Redefining CyberSecurity Podcast on YouTube | https://www.youtube.com/playlist?list=PLnYu0psdcllS9aVGdiakVss9u7xgYDKYq ⬥ADDITIONAL INFORMATION⬥ Redefining CyberSecurity Podcast | https://www.seanmartin.com/redefining-cybersecurity-podcast Redefining CyberSecurity on YouTube | https://www.youtube.com/playlist?list=PLnYu0psdcllS9aVGdiakVss9u7xgYDKYq The Future of Cybersecurity Newsletter | https://itspm.ag/future-of-cybersecurity Connect with Sean Martin | https://www.seanmartin.com/ ⬥KEYWORDS⬥ alina tan, george chen, he&t security labs, sean martin, dashcam security, connected vehicle cybersecurity, iot security, vehicle privacy, drivethru hacking, wi-fi hacking, mobile botnet, automotive cybersecurity, firmware security, over-the-air updates, credential stuffing, redefining cybersecurity, cybersecurity podcast, redefining cybersecurity podcast Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Could we one day bypass heart blockages without ever opening the chest? In this episode of The Heart of Innovation, Kym McNicholas and Dr. James Joye, who invented PTAB (minimally invasive leg bypass device) sit down with Dr. Chris Bruce, the lead author of a groundbreaking NIH and Emory study that has achieved a world first: a fully percutaneous (catheter-based) coronary bypass. Known as the VECTOR procedure, this technique was recently used to save a patient whose anatomy made a traditional heart valve replacement life-threatening. By building an "extra-anatomic" bypass from the aorta to the coronary artery—all through a small puncture in the leg—Dr. Bruce and his team have opened a new frontier in cardiac care. We discuss how they "poked a hole" through the heart to save a life and whether this technology could eventually replace traditional bypass surgery for common blockages. #heartvalve #coronarybypass #heartbypass #heartsurgery #globalpadassociation #heartdisease

Send a textAndy Yakulis—West Point graduate, former Army pilot, and Special Operations officer turned defense tech entrepreneur—joins Joe to talk about leadership, transition, and the rapidly changing nature of modern warfare.Recruited to West Point just days before September 11th, Andy entered the Army knowing he would serve during a generation defined by war. After flying Kiowa Warrior helicopters and spending nearly a decade in Special Operations, he became increasingly frustrated with the gap between the technology soldiers used in combat and what existed in the civilian world.Together, they discuss Andy's decision to leave the Army at 18 years to start Vector, a company focused on unmanned systems, as well as the challenges of military transition, the realities of leadership in the private sector, and how paying attention to what captures your curiosity might reveal the work you're meant to pursue.Watch the full interview on YouTube!Joe and Andy also discuss:Why physical fitness and sleep still shape Andy's decision-making as a CEOThe value of civilian education for military leadersThe “Saturday morning coffee test” for discovering what you're passionate aboutWhy veterans shouldn't feel pressure to find the perfect post-military job immediatelyThe challenge of leading teams in the private sectorWhy the future of warfare may shift from one operator controlling one drone to one operator orchestrating manyWhether you're transitioning out of the military, exploring entrepreneurship, or curious how technology is changing warfare, this episode offers insights on leadership, innovation, and pursuing work you feel called to do.A Special Thanks to Our Sponsors!Veteran-founded Adyton. Step into the next generation of equipment management with Log-E by Adyton. Whether you are doing monthly inventories or preparing for deployment, Log-E is your pocket property book, giving real-time visibility into equipment status and mission readiness. Learn more about how Log-E can revolutionize your property tracking process here!Dunedain Systems is a veteran-founded defense technology company building Warmind, an AI platform that accelerates military planning, operations, and document generation. Warmind connects to your unit's data and learns how your warfighting function operates, delivering outputs tailored to your SOPs and operational context rather than generic AI responses. Whether your team is building OPORDs, running intel workflows, or generating CONOPs, Warmind handles the heavy lift so your staff can focus on decisions, not paperwork. Built by combat veterans who lived the problem firsthand, Warmind is already in use across SOCOM and the broader DoD. The beta is free for anyone with a .mil or .edu email at dunedainsystems.com.Meet ROGER Bank—a modern, digital bank built for military members, by military members. With early payday, no fees, high-yield accounts, and real support, it's banking that gets you. Funds are FDIC insured through Citizens Bank of Edmond, so you can bank with confidence and peace of mind. Logistics Systems Incorporated (LSI) is a Service-Disabled Veteran-Owned Small Business supporting DoD and federal civilian agencies with enterprise IT operations, global logistics support, cybersecurity, data, and mission support services. Founded by a veteran Army leader, LSI is known for operating inside

Who will win the AI race in 2026?