Podcasts about Vector

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.

Wow I hope Noah's audio isn't completely effed up for most of the episode, good thing he talks the most and hosts the whole show. God dammit anyways here's one about sommelier levels, Family Guy endings, blue collar mind palaces, Fairly Odd Parents reboot, Elroy Jetson, Google ai keynote, Fletcher Hanks ai, the MK of podcasting, Eric Clapton junior, Michael sequel, making data centre golf course graveyards, turf balls, baitmaxxing or maxbaiting, Gymskin, pint law, new giant octopus, Tony the Tiger's Vector, cereals tier list, delayed gratification, and cereal games. Back to basics.

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.

TheMAGIC5 swim goggles are, hands down, the best goggles I've ever used. That was true 4 years ago and that is still true today after using their latest version. APOLOGIES! I just discovered that my last 2 audio files were not recorded with my good microphone (those darn Windows settings!). I promise, better audio next week.Join the community at www.patreon.com/thelonelytriathleteTRANSCRIPTWelcome to the Lonely Triathlete where I share with you the thoughts, opinions, experiences and tips n tricks of a podium placing age-group triathlete. Should I say "aging" triathlete? Aren't we all aging, really? 'Nuff said.Before I get started, just a quick reminder that Patreon members get bonus content at the end of this episode AND if you head over to Patreon.com, you'll see that I am posting a couple of written blog posts per week so check that out and be sure to leave some comments.OKYou know what piece of triathlon equipment gets talked about the least?Not aero helmets.Not carbon shoes.Not race wheels.Swimming goggles.And honestly, that's ridiculous when you think about it.Because if your goggles don't fit properly, your swim can go sideways fast. I remember being absolutely paranoid before my 2008 Ironman Canada that my goggles would leak, whcih is why I bought a pair of visor-style Aquaspheres.But a leaking goggle during a race isn't just annoying — it completely breaks your rhythm. Suddenly you're stopping, adjusting, sighting poorly, getting frustrated, maybe even panicking a little in open water.And during training?A bad pair of goggles can turn an enjoyable swim into an irritating grind.Too tight?You get the raccoon-eye pressure marks.Too loose?Water leaks in every flip turn.Wrong shape?They dig into your eye sockets and give you headaches.For a piece of equipment that literally sits on your face for hours every month, comfort matters a lot more than most athletes realize.Now here's the funny thing.Most swimmers and triathletes are buying goggles in roughly the $25–$60 range.That's kind of the mainstream market:Speedo VanquishersArena gogglesTYRAqua SphereThese are all good goggles. Totally functional. Those Aquasphere I used for Ironman were fantastic. I felt like I was wearing a motorcycle helmet they were so big but they did their job.But most of them are still basically “best guess” sizing. They have:Different nose bridges.Different strap tensions.Maybe one fits your face better than another.BUTYou're still adapting YOURSELF to the goggles.Not the other way around.And honestly, a lot of swimmers just accept leaking as normal.Like:“Oh yeah, this pair only leaks on hard push-offs.”Or:“They're good once you adjust them three times.”We've normalized mediocre fit.What's funny is that swim goggles have actually evolved a lot over the last 30–35 years.If you started swimming in the late 80s or early 90s, you probably remember the old-school goggles that basically felt like torture devices strapped to your face.The classic design back then was:hard plastic lensesFOAM padding around the eyesbasic rubber strapsand almost zero ergonomic shapingAnd those foam gaskets?They absorbed water over time, degraded quickly, and eventually became DISGUSTING little sponges attached to your face.The fit philosophy back then was basically:“Just tighten them harder.”Which of course created those legendary deep red eye rings that lasted half the day. People at work always new when I started my day with a swim workout.Then through the 1990s and early 2000s, companies started introducing softer SILICONE seals instead of foam padding.And honestly, that was a huge leap forward.Silicone:lasted longersealed betterfelt softer against the skinand didn't absorb water.That era also brought interchangeable nose bridges, which suddenly allowed swimmers to customize fit a little more instead of relying on a one-size-fits-all design.Then came the rise of racing-oriented LOW-profile goggles.Brands like Speedo, Arena, and TYR started focusing heavily on HYDROdynamics:smaller lens profilesreduced dragsleeker shapesmirrored lenseswider peripheral visionOpen-water swimming also changed the market.Triathletes needed goggles that worked in:bright sunlightchoppy waterlong-distance comfort situationsSo companies began introducing:larger lenses (hello Aquasphere)curved panoramic visionsofter “air gasket” technologybetter anti-fog coatingsUV protectionAnd that air-gasket concept was another major step.Instead of hard pressure points around the eye socket, companies started using cushioned seals filled with air or softer silicone structures that distributed pressure more evenly.The result:less squeezing…less leakage…and way more comfort during long swims.And NOW we've entered the NEWEST phase of goggle evolution:custom-fit goggles.Instead of trying to create one shape that works “well enough” for millions of people, companies like THEMAGIC5 are using face scanning and manufacturing technology to create individualized fits.Which honestly makes sense when you think about it.Human faces are wildly different.Eye socket depth.Nose bridge width.Cheekbone structure.And yet for decades the industry basically said:“Here are three nose bridges. Good luck.”So when you look at the history of swim goggles, it's actually a story of comfort slowly catching up with performance.Because the ideal goggle isn't really the fastest one.It's the one you completely forget you're wearing.Now, get ready, I'm about to brag about the best pair of swimming goggles I have ever owned. The Magic5.I received my first and original pair of Magic5 goggles about 4 years ago as a birthday, and they were great. They were actually PERFECT. Comfortable (which was a new experience for me) and leak free, which is a rareity. After a while I almost stopped thinking about them entirely — which is probably the highest compliment you can give a pair of goggles.But after 4 years they've been showing some wear and tear. They are still leak-free but the anti-fog coating has pretty much disappeared. I've been getting around this by spitting into the goggles and rinsing them out before putting them on but that act has been getting old and just as I was deciding to go ahead and order a new pair, TheMagic5 reached out to me and offered to essentially give me a pair of their latest model, the VECTOR, with no strings attached. All I had to do was pay for the shipping. Talk about perfect timing and a no brainer. So, I just got a chance recently to test them out at my local lake. This new pair is...just...great. They've made some upgrades, which I'll mention, but honestly, how do you improve upon perfection? Some of the improvements the company highlights include:Refined gasket geometry for improved facial pressure distribution- Sure, enough, I feel little to no pressure on my face, just as beforeUpdated scanning and fit algorithms using a much larger facial data set, which leads to improved comfort around the eye sockets during long swims- Again, the result is little to no pressure around my eyesEnhanced peripheral vision depending on the model- I already experienced great peripheral vision, apparently it's even better nowUpgraded anti-fog performance- We shall see, so far so goodImproved strap design and overall adjustability- Never had a problem beforeMore durable lens coatings- We shall seeExpanded lens options for indoor, outdoor, mirrored, and open-water conditions- True, and I went with the all-rounder "gold" version - it's supposed to be good for indoor/outdoor use. If you swim in predominently sunny conditions I would definately go with the specialied version for that conditionTheir newer “Vector” design specifically focuses on reducing pressure points while maintaining a secure seal- Like I said, can't feel them on my face, never couldSo, the biggest compliment I can give the new pair is this:They still disappear while I'm swimming.No leaking.No fiddling.No overtightening.No mid-set adjustments.Just swim.And here's a bonus, let's say you do experience some fit issues? You can contact Support and they will do another scan and send you another pair. I've never had to do that but it's nice to know that is an option.Now to be fair, not every swimmer loves them.Some swimmers swear they're the best goggles they've ever owned.Others say the fit process can be hit-or-miss depending on the face scan or the model.And like basically every swim goggle ever made, anti-fog performance eventually fades over time.But the consistent theme from people who do love them is comfort and leak prevention.Isn't it weird that this is one of those areas where triathletes sometimes get weirdly cheap?We'll spend thousands chasing marginal aero gains……but tolerate goggles that leak every third lap.If you swim multiple times per week, comfort matters.Focus matters.Rhythm matters.And when your goggles disappear from your awareness entirely?That's probably the sign they're doing their job perfectly.At the end of the day, triathlon performance isn't only about the big flashy upgrades.Sometimes it's about removing friction.Physical friction.Mental friction.Emotional friction.And well-fitting goggles remove all three.Because when your goggles work perfectly, your attention stays where it belongs:on your stroke…your pacing…your breathing…and the simple rhythm of swimming.And honestly, after using leak-free goggles for years now, I don't think I could ever go back.Check the show notes to see if I managed to secure an affiliate link so you can get a discount off your pair of TheMagic5 goggles.That's it from me, until next time.PeaceOk, Patrons, time to dive into Reddit and see what the latest questions or issues are:

TheMAGIC5 swim goggles are, hands down, the best goggles I've ever used. That was true 4 years ago and that is still true today after using their latest version.APOLOGIES! I just discovered that my last 2 audio files were not recorded with my good microphone (those darn Windows settings!). I promise, better audio next week.Join the community at www.patreon.com/thelonelytriathleteTRANSCRIPTWelcome to the Lonely Triathlete where I share with you the thoughts, opinions, experiences and tips n tricks of a podium placing age-group triathlete. Should I say "aging" triathlete? Aren't we all aging, really? 'Nuff said.Before I get started, just a quick reminder that Patreon members get bonus content at the end of this episode AND if you head over to Patreon.com, you'll see that I am posting a couple of written blog posts per week so check that out and be sure to leave some comments.OKYou know what piece of triathlon equipment gets talked about the least?Not aero helmets.Not carbon shoes.Not race wheels.Swimming goggles.And honestly, that's ridiculous when you think about it.Because if your goggles don't fit properly, your swim can go sideways fast. I remember being absolutely paranoid before my 2008 Ironman Canada that my goggles would leak, whcih is why I bought a pair of visor-style Aquaspheres.But a leaking goggle during a race isn't just annoying — it completely breaks your rhythm. Suddenly you're stopping, adjusting, sighting poorly, getting frustrated, maybe even panicking a little in open water.And during training?A bad pair of goggles can turn an enjoyable swim into an irritating grind.Too tight?You get the raccoon-eye pressure marks.Too loose?Water leaks in every flip turn.Wrong shape?They dig into your eye sockets and give you headaches.For a piece of equipment that literally sits on your face for hours every month, comfort matters a lot more than most athletes realize.Now here's the funny thing.Most swimmers and triathletes are buying goggles in roughly the $25–$60 range.That's kind of the mainstream market:Speedo VanquishersArena gogglesTYRAqua SphereThese are all good goggles. Totally functional. Those Aquasphere I used for Ironman were fantastic. I felt like I was wearing a motorcycle helmet they were so big but they did their job.But most of them are still basically “best guess” sizing. They have:Different nose bridges.Different strap tensions.Maybe one fits your face better than another.BUTYou're still adapting YOURSELF to the goggles.Not the other way around.And honestly, a lot of swimmers just accept leaking as normal.Like:“Oh yeah, this pair only leaks on hard push-offs.”Or:“They're good once you adjust them three times.”We've normalized mediocre fit.What's funny is that swim goggles have actually evolved a lot over the last 30–35 years.If you started swimming in the late 80s or early 90s, you probably remember the old-school goggles that basically felt like torture devices strapped to your face.The classic design back then was:hard plastic lensesFOAM padding around the eyesbasic rubber strapsand almost zero ergonomic shapingAnd those foam gaskets?They absorbed water over time, degraded quickly, and eventually became DISGUSTING little sponges attached to your face.The fit philosophy back then was basically:“Just tighten them harder.”Which of course created those legendary deep red eye rings that lasted half the day. People at work always new when I started my day with a swim workout.Then through the 1990s and early 2000s, companies started introducing softer SILICONE seals instead of foam padding.And honestly, that was a huge leap forward.Silicone:lasted longersealed betterfelt softer against the skinand didn't absorb water.That era also brought interchangeable nose bridges, which suddenly allowed swimmers to customize fit a little more instead of relying on a one-size-fits-all design.Then came the rise of racing-oriented LOW-profile goggles.Brands like Speedo, Arena, and TYR started focusing heavily on HYDROdynamics:smaller lens profilesreduced dragsleeker shapesmirrored lenseswider peripheral visionOpen-water swimming also changed the market.Triathletes needed goggles that worked in:bright sunlightchoppy waterlong-distance comfort situationsSo companies began introducing:larger lenses (hello Aquasphere)curved panoramic visionsofter “air gasket” technologybetter anti-fog coatingsUV protectionAnd that air-gasket concept was another major step.Instead of hard pressure points around the eye socket, companies started using cushioned seals filled with air or softer silicone structures that distributed pressure more evenly.The result:less squeezing…less leakage…and way more comfort during long swims.And NOW we've entered the NEWEST phase of goggle evolution:custom-fit goggles.Instead of trying to create one shape that works “well enough” for millions of people, companies like THEMAGIC5 are using face scanning and manufacturing technology to create individualized fits.Which honestly makes sense when you think about it.Human faces are wildly different.Eye socket depth.Nose bridge width.Cheekbone structure.And yet for decades the industry basically said:“Here are three nose bridges. Good luck.”So when you look at the history of swim goggles, it's actually a story of comfort slowly catching up with performance.Because the ideal goggle isn't really the fastest one.It's the one you completely forget you're wearing.Now, get ready, I'm about to brag about the best pair of swimming goggles I have ever owned. The Magic5.I received my first and original pair of Magic5 goggles about 4 years ago as a birthday, and they were great. They were actually PERFECT. Comfortable (which was a new experience for me) and leak free, which is a rareity. After a while I almost stopped thinking about them entirely — which is probably the highest compliment you can give a pair of goggles.But after 4 years they've been showing some wear and tear. They are still leak-free but the anti-fog coating has pretty much disappeared. I've been getting around this by spitting into the goggles and rinsing them out before putting them on but that act has been getting old and just as I was deciding to go ahead and order a new pair, TheMagic5 reached out to me and offered to essentially give me a pair of their latest model, the VECTOR, with no strings attached. All I had to do was pay for the shipping. Talk about perfect timing and a no brainer. So, I just got a chance recently to test them out at my local lake. This new pair is...just...great. They've made some upgrades, which I'll mention, but honestly, how do you improve upon perfection? Some of the improvements the company highlights include:Refined gasket geometry for improved facial pressure distribution- Sure, enough, I feel little to no pressure on my face, just as beforeUpdated scanning and fit algorithms using a much larger facial data set, which leads to improved comfort around the eye sockets during long swims- Again, the result is little to no pressure around my eyesEnhanced peripheral vision depending on the model- I already experienced great peripheral vision, apparently it's even better nowUpgraded anti-fog performance- We shall see, so far so goodImproved strap design and overall adjustability- Never had a problem beforeMore durable lens coatings- We shall seeExpanded lens options for indoor, outdoor, mirrored, and open-water conditions- True, and I went with the all-rounder "gold" version - it's supposed to be good for indoor/outdoor use. If you swim in predominently sunny conditions I would definately go with the specialied version for that conditionTheir newer “Vector” design specifically focuses on reducing pressure points while maintaining a secure seal- Like I said, can't feel them on my face, never couldSo, the biggest compliment I can give the new pair is this:They still disappear while I'm swimming.No leaking.No fiddling.No overtightening.No mid-set adjustments.Just swim.And here's a bonus, let's say you do experience some fit issues? You can contact Support and they will do another scan and send you another pair. I've never had to do that but it's nice to know that is an option.Now to be fair, not every swimmer loves them.Some swimmers swear they're the best goggles they've ever owned.Others say the fit process can be hit-or-miss depending on the face scan or the model.And like basically every swim goggle ever made, anti-fog performance eventually fades over time.But the consistent theme from people who do love them is comfort and leak prevention.Isn't it weird that this is one of those areas where triathletes sometimes get weirdly cheap?We'll spend thousands chasing marginal aero gains……but tolerate goggles that leak every third lap.If you swim multiple times per week, comfort matters.Focus matters.Rhythm matters.And when your goggles disappear from your awareness entirely?That's probably the sign they're doing their job perfectly.At the end of the day, triathlon performance isn't only about the big flashy upgrades.Sometimes it's about removing friction.Physical friction.Mental friction.Emotional friction.And well-fitting goggles remove all three.Because when your goggles work perfectly, your attention stays where it belongs:on your stroke…your pacing…your breathing…and the simple rhythm of swimming.And honestly, after using leak-free goggles for years now, I don't think I could ever go back.Check the show notes to see if I managed to secure an affiliate link so you can get a discount off your pair of TheMagic5 goggles.That's it from me, until next time.PeaceOk, Patrons, time to dive into Reddit and see what the latest questions or issues are:

Does he really only like Vector? Zantok and Jonno emanate energy to match Team Chaotix in this sixth episode of AJOLWTTA. Tune in for Zant Rants about Daylight Savings Time and podcast recording mishaps, a look forward on festival season in the city of Twoson, Arizonia, reflections on body dysmorphia, Pokémon price gouging, and so much more.

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 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

Peter Levine speaks with Ash Ashutosh, CEO of Pinecone, about the launch of Nexus and the shift from vector databases to knowledge engines. As agents become the primary users of software, they discuss why traditional retrieval systems break down and how AI systems need to evolve to support machine-to-machine interactions. The conversation explores how agents currently spend most of their time retrieving and reasoning over data, why that approach is inefficient, and how moving reasoning closer to the data can dramatically improve performance, accuracy, and cost. Ash also explains how Pinecone is rethinking the stack for agentic applications, introducing new abstractions, query languages, and developer workflows.   Resources: Follow Ash Ashutosh on X: https://x.com/ashashutosh Follow Peter Levine on LinkedIn: https://www.linkedin.com/in/peter-levine-681386172/   Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts. Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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!

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.Contrair tot vorige week vrijdag en al die vrijdagen ervoor, zitten er op deze vrijdag twee heren klaar achter de kenmerkende desk van Gamekings. We hebben het over JJ en Koos. Reden: alle andere hosts hadden andere verplichtingen. Niet getreurd, de twee kunnen dit prima aan. Gezamenlijk luiden ze het weekend in met een nieuwe editie van Einde van de Week Live. De twee bespreken in deze episode de eerste previews van 007 First Light, de speeltijd van Crimson Desert en de afloop van PlayStation DRM-gate. Dit en vele andere gespreksonderwerpen komen voorbij in deze Einde van de Week Live van vrijdag 1 mei 2026.Meerderheid spelers Crimson Desert nog niet over helft gameAndere onderwerpen die in deze video voorbijkomen, zijn de trailers van Blood of the Dawnwalker en de nieuwe Alien Isolation, een apart event in Rainbow Six, is Injustice 3 in ontwikkeling en Star Wars is aangekomen in Fortnite.Krijg top-game Pragmata bij de aanschaf van de Vector 16 HX AI gaming laptop van MSIMSI zet deze week de Vector 16 HX AI in het zonnetje. Een gaming laptop met aan boord de Intel Core Ultra 9 275HX-processor en een GeForce RTX 5080 GPU. Hierdoor heb je ondersteuning voor de nieuwste AI-technologie van NVIDIA. Verder is er 1 TB opslagcapaciteit, een 16” QHD+ IPS-scherm met 240Hz refresh rate (wat ideaal is voor competitieve gaming), 2x Thunderbolt 5-poorten en een 24-zone RGB gaming keyboard. Deze hardware is hier te verkrijgen, inclusief de top-game Pragmata.

6,5 millions d'abonnés cumulés sur les réseaux dont 6,4 millions sur TikTok : Tristan Mattioli est l'un des créateurs de contenu français les plus suivis de sa génération. Né du personnage Vector pendant le Covid, il a depuis fait évoluer son identité digitale et lancé son propre lieu, le Studio Mattioli à Paris.Dans cet épisode, on parle de la transition Vector → Tristan, du choix radical de quitter une agence pour gérer sa carrière seul, du brief que les marques ne savent plus lâcher, du rôle stratégique du Festival de Cannes, et du futur de l'influence à l'ère de l'IA et de la co-création.Une masterclass pour les CMO, marques et agences qui veulent comprendre comment travailler avec les créateurs aujourd'hui — et préparer leurs collaborations de demain.Épisode disponible en vidéo sur YouTube — retrouvez les interviews complètes en format vidéo pour une expérience encore plus immersive. → YouTubeVous appréciez le podcast ? Laissez une note 5 étoiles sur Apple Podcasts ou Spotify — c'est gratuit, ça prend 10 secondes, et c'est le meilleur moyen d'aider d'autres professionnels du marketing à le découvrir.→ YouTube - Apple Podcasts - Spotify - Deezer - Toutes plateformes (Smartlink) ·Newsletter Marketing & Influence — recevez en avant-première les prochains invités, les tendances clés et les insights exclusifs du secteur. Inscription sur marketinginfluence.fr→ Inscrivez-vous iciSuivez ADMS.PARIS I Globe Groupe sur LinkedIn et connectez-vous directement à Cyril Attias (LinkedIn) pour échanger sur le marketing, l'influence et les stratégies de marque.Un podcast produit par ADMS.PARIS I Globe Groupe et soutenu par Les Gens d'Internet, premier média français dédié au social media et à l'influence.Abonnez-vous à notre compte Instagram Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

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

Hosts Lois Houston and Nikita Abraham are joined by Brent Dayley, Senior Principal APEX and Apps Dev Instructor, to explore the latest vector AI supporting features in Oracle Exadata and GoldenGate 23ai. The conversation begins with an overview of Exadata's capabilities and then shifts to how GoldenGate is powering distributed AI, real-time data streaming, and analytics with advanced microservices architecture. Brent highlights recent GoldenGate enhancements, including distributed vector support, robust monitoring, OCI IAM integration, and support for next-generation AI workloads via real-time vector hubs.   Oracle AI Vector Search Deep Dive: https://mylearn.oracle.com/ou/course/oracle-ai-vector-search-deep-dive/144706/ Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, and the OU Studio Team for helping us create this episode.   Please note, this episode was recorded before Oracle AI Database 26ai replaced Oracle Database 23ai. However, all concepts and features discussed remain fully relevant to the latest release.   -------------------------------------------------------   Episode Transcript:   00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Lois: Hello and welcome to another episode of the Oracle University Podcast! I'm Lois Houston, Director of Communications and Adoption Programs with Customer Success Services, and with me is Nikita Abraham, Team Lead of Editorial Services with Oracle University.  Nikita: Hi everyone! Thanks for joining us! In our previous episode of this series, we took a deep dive into Oracle AI Vector Search and Retrieval Augmented Generation, or RAG, showing how unstructured data can be transformed into embeddings to power smarter, more context-aware AI with Oracle Database 23ai. Lois: That's right, Niki. We also explored how the OCI Generative AI service can be used with both Python and PL/SQL, and how AI Vector Search enables relevant information retrieval for large language model prompts. 01:21 Nikita: Today, we're focusing on the latest supporting features for Oracle AI Vector Search. Joining us once again is Brent Dayley, Senior Principal APEX and Apps Dev Instructor. Welcome back, Brent! To kick things off, could you outline what's new in Exadata with the 24ai release, particularly for AI storage? Brent: So Exadata has ushered in a new era of AI capabilities with 24ai release. Key features of Exadata system software 24ai include AI Smart Scan, Exadata RDMA Memory, known as XRMEM, Exadata Smart Flash Cache, and on-storage processing.  In-Memory Columnar Speed JSON Queries, Transparent Cross-Tier Scans, and caching enhancements, including Columnar Smart Scan at Memory Speed, Exadata Cache Observability, and Automatic KEEP Object Load into Exadata Flash Cache.  Now, Exadata system software 24ai is a significant release. It ushers in a new era of AI capabilities for Oracle Database users.  Now there have been some infrastructure improvements, including the ability to increase the number of virtual machines on X10M and Secure Boot for KVM Virtual Machines.  We have also improved and enhanced high availability and network resilience, including improved RoCE Network Resilience and enhanced RoCE Network Discovery. There have been some enhancements for monitoring and management, including AWR and SQL Monitor Enhancements and JSON API for Management Server.  Additionally, security enhancement. SNMP Security. Now, Exadata system software 24ai is supported on Exadata database machines and storage expansion racks from X6 and newer.  03:40 Lois: Those are some fantastic advancements for Exadata users. Now, let's pivot to distributed AI. Brent, can you walk us through how GoldenGate enables distributed AI? Brent: Let's take a look at some common GoldenGate use cases as a refresher. The first use case is multi-active, high availability, and cross-region deployments, spanning on-premises and cloud environments.  Another use case includes data offloading and data hub creation in order to support multiple downstream applications. Real-time data stores for Downstream Marts and Analytics. Micro and mini services architecture and an audit history of transactions.  Other use cases include migrations and upgrades of databases, including OCI-hosted databases. Another use case would be creating analytic data feeds for various applications, including SaaS and on-premises apps. And finally, stream analytics using application and transaction events captured by GoldenGate Stream Analytics.  05:03 Nikita: We know GoldenGate has long been a staple for enterprise data integration. So Brent, what makes GoldenGate the best choice today, and how has its architecture evolved? Brent: It offers DIY Stream Analytics. GoldenGate does remain the top choice for Enterprise Standard, real-time data streaming. It supports Oracle and third-party databases, vector sources, messaging systems, and NoSQL databases.  OCI offers a fully managed pipeline builder for Stream Analytics. This pipeline leverages various OCI services, such as OCI Streaming for real-time event ingestion, OCI Dataflow for stream processing, OCI Big Data for data storage and processing, and OCI Stream Analytics for real-time event processing and analysis.  GoldenGate microservices, available since 2017 in Oracle GoldenGate 12.3, is used in over 4,000 deployments in OCI. Benefits of GoldenGate microservices include the ability to employ the same trusted Extract and Replicat processes as the classic architecture.  Provides flexible and secure remote administration through a user-friendly web interface or CLI. Deployable on-premises in OCI as a service and in third-party cloud environments. Simplified patching and upgrading process.  Now the GoldenGate architecture evolution. First, classic architecture that was deprecated in version 19c and desupported in 23ai. Microservices Architecture introduced in version 12.3 and is the recommended architecture. A migration utility is available to upgrade from classic to microservices architecture.  07:12 Are you ready to create and manage AI Agents in Fusion Applications? Check out the Oracle AI Agent Studio for Fusion Applications courses! Start with the Foundations course to build, customize, and deploy AI Agents, and then advance to the Developer Professional certification. Explore hands-on labs and real-world case studies. Visit mylearn.oracle.com for all the details.  07:39 Nikita: Welcome back! It sounds like the latest GoldenGate updates offer new features and integrations. Could you share more about these enhancements? Brent: There are many new features and enhancements in GoldenGate, along with microservices, including a redesigned GUI for enhanced usability. Integration with StatsD and Telegraf for monitoring and metrics. OCI IAM integration for secure access control.  JSON Relational Duality for flexible data handling. Next-generation AI with distributed vector support. PDB Extract Capture for efficient data extraction from Oracle Pluggable Databases. DDL notification on Target Tables for schema evolution management.  Support for non-Oracle and Big Data technologies. Online DDL and EBR enhancement for improved performance. Data Streams Pub-Sub for asynchronous data dissemination. Async API support for standardized event communication. High-availability clusters for increased resilience. Trail Files Management for efficient data storage. And support for new features in 23ai database.  It also includes integrated diagnostics for improved troubleshooting of IE and IR processes. And 30 or more OS and database certifications for wider platform support. @Dbfunction Mapping for custom data transformations. And lastly, GoldenGate free recipes for pre-built solutions and best practices.  New in GoldenGate, distributed AI processing with vector replication.  09:37 Lois: And what type of use cases does this enable? Brent: Migrating vectors into Oracle Vector Database. Replicating and consolidating vector changes. Implementing multi-cloud, multi-active Oracle vector databases. Streaming text and vector changes to search engines.  Key considerations include that embedding models must be consistent across all vector stores for effective similarity searches.  10:09 Lois: Now, many organizations wonder if they can use generative AI with their own business data. Brent, how do enterprises typically approach this? Brent: Organizations are using generative AI typically like this.  Building LLMs from scratch. Training models on proprietary data for specific tasks. Fine-tuning LLMs, adapting pre-trained models to a specific domain using private data. And prompt engineering with retrieval augmented generation or RAG. Augmenting prompts with relevant information retrieved from a knowledge base to improve the accuracy and relevance of LLM responses.  Now it's possible to create a real-time vector hub for GenAI. This hub can ingest real-time data from various sources, including Oracle and third-party relational databases, vector databases, third-party messaging systems, and NoSQL databases, business updates, documents, events, and alerts.  11:11 Nikita: And how does the vector hub work?  Brent: DML and DDL changes, vector changes, and prompt or chat history are used to enrich prompts. And embedding model generates embeddings from the text data.  Similarity search is performed on these embeddings to retrieve relevant information from the vector hub. The retrieved information is used to augment the prompt, leading to more accurate and trustworthy answers from the LLM. Now, the benefits of real-time data and generative AI include the ability to ensure answers are based on fresh business data. And helps reduce hallucinations in generative AI responses.  Actionable AI and machine learning from streaming pipelines allows data from ERP and SaaS applications, databases, event messaging systems, and NoSQL databases to be ingested into streaming pipelines. This data can then be used for AI and machine learning model training, similarity searches, machine learning tasks, external AI, and machine learning integrations, alerts, and data product creation.  12:25 Lois: So if you had to summarize, Brent, why does GoldenGate 23ai stand out for artificial intelligence workloads? Brent: Well, first up, it improves data quality for AI model training and fine-tuning. And secondly, it enhances retrieval augmented generation by providing real-time access to relevant business data, leading to more accurate and trustworthy generative AI responses.  Nikita: Thank you, Brent, for sharing your insights and detailing these exciting new features across Oracle's AI stack. If you'd like to dive deeper into these topics, don't forget to visit mylearn.oracle.com and look for Oracle AI Vector Search Deep Dive course. Until next time, this is Nikita Abraham… Lois: And Lois Houston, signing off! 13:16 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.  

⬥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.

Organic LinkedIn is still the highest ROI channel in B2B marketing, and Jess Cook, VP of Marketing at Vector, has the numbers to prove it. With roughly $40,000 in total ad spend for the year, Vector made organic LinkedIn its single biggest lead source. In this episode of Beyond Social, Jess joins hosts Chris Cunningham and Reggie Azevedo to break down the B2B LinkedIn strategy behind those results.Jess covers how she built her own LinkedIn audience by committing to posting every weekday for a year, how she helps Vector's founders and team show up consistently on social media without sounding generic, and why borrowing B2C creative thinking is the biggest competitive advantage in B2B content marketing today.The conversation also digs into AI and content creation, specifically how social media managers can use tools like Claude to scale without losing their authentic voice, and why human storytelling will always be the thing that cuts through.If you manage social media for a B2B brand, agency, or enterprise team, this one's worth your full attention.Try Vista Social for FREE todayBook a Demo Follow us on InstagramFollow us on LinkedInFollow us on Youtube

⬥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.

What if lifesaving heart surgery no longer meant cracked bones, months of pain, and a long road back? Dr. Adam Brockman dives into one of the most exciting frontiers in modern medicine—the VECTOR procedure—a groundbreaking, minimally invasive approach reinventing how we treat blocked arteries. This episode reveals how advanced imaging and catheter-based tools may soon replace open-heart bypass for many, offering faster recovery and less trauma. But Dr. Brockman doesn't stop there—he connects it all to the bigger picture of longevity, exploring how habits, nitric oxide, and natural vascular support can keep your arteries clear long before intervention is needed. Tune in to “The Dr. Bob MartinShow” for a deep look at the past, present, and future of heart health—and discover how smartermedicine meets self-care for a longer, stronger life.Special Guest: Dr. Nathan Bryan, leading Nitric Oxide Expert (N1O1.com)

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

A Leadership training course organised for leaders at different levels in the ministry

Silicon Bites Ep311 | 2026-04-02 | Who is the real paper tiger? Ukraine schools NATO on drones while Trump torches the alliance. Several stories around NATO's future have converged this week – but here are two of the most important. Ukraine fired its NATO trainers. A mystified alliance is running out of time to learn why, suggests Hans Petter Midttun in an article published by Euromaidan Press. Ukraine's General Staff has decided to scale back overseas training for its troops and—despite the constant threat of Russian missile and drone strikes — move it to Ukraine. According to Militarnyi, General Staff's Deputy Chief for Doctrine and Training Yevhen Mezhevikin cited logistical concerns and a lack of relevant combat experience among Western instructors. "They are disconnected from our realities, from the current combat operations," he said.----------SUPPORT THE CHANNEL:https://www.buymeacoffee.com/siliconcurtainhttps://www.patreon.com/siliconcurtainhttps://www.gofundme.com/f/scaling-up-campaign-to-fight-authoritarian-disinformation----------SOURCES:Euromaidan Press — "Ukraine fired its NATO trainers. The alliance is running out of time to learn why." (March 31, 2026) — Primary analysis by Hans Petter Midttun; Russia's 80,000-strong Unmanned Systems Forces; 8,900 FPV drones per day; 2030 projection of 210,000Euromaidan Press — "'We are f—': 10 Ukrainians with drones wipe out two NATO battalions in war game" (February 13, 2026) — Delta system; 2.2-second detection; Hedgehog 2025 exercise detailsWall Street Journal — "NATO exercise reveals alliance can't survive Ukraine-style drone warfare" — Jillian Kay Melchior (February 12, 2026) — Primary source reporting; firsthand accounts from Hedgehog exercise participantsUnited24 Media — "NATO Drills Reveal Drone Warfare Could Eliminate Two Battalions in a Day" (February 13, 2026) — Delta system; Petraeus LinkedIn comments; Estonian Defence League coordinationUnited24 Media — "How 10 Ukrainian Drone Operators Crushed a NATO Offensive in Estonia" (February 15, 2026) — 412th Nemesis Brigade and 427th Rarog Brigade details; Vector reconnaissance systemDefence News — "Role reversal: Ukraine moves training home and exports the lessons abroad" (March 27, 2026) — Germany as first NATO member to invite Ukrainian trainers; Lt. Gen. Freuding quote; DELTA in REPMUS 2025; down from 18 to 3 EU training nations; Vandier quote on Russia adapting19FortyFive — "A NATO Wargame in Estonia Let Ukrainian Drone Experts Play the Bad Guy and the Results Were Brutal" (February 17, 2026) — Petraeus on lessons only being learned through systemic reform; combined arms contextDroneXL — "NATO's Hedgehog exercise exposed a brutal truth" (February 13, 2026) — Cross-reference on exercise details; US troops absent from Hedgehog 2025----------SILICON CURTAIN LIVE EVENTS - FUNDRAISER CAMPAIGN Events in 2025 - Advocacy for a Ukrainian victory with Silicon Curtainhttps://buymeacoffee.com/siliconcurtain/extrasOur events of the first half of the year in Lviv, Kyiv and Odesa were a huge success. Now we need to maintain this momentum, and change the tide towards a Ukrainian victory. The Silicon Curtain Roadshow is an ambitious campaign to run a minimum of 12 events in 2025, and potentially many more. Any support you can provide for the fundraising campaign would be gratefully appreciated. https://buymeacoffee.com/siliconcurtain/extrasWe need to scale up our support for Ukraine, and these events are designed to have a major impact. Your support in making it happen is greatly appreciated. All events will be recorded professionally and published for free on the Silicon Curtain channel. Where possible, we will also live-stream events.https://buymeacoffee.com/siliconcurtain/extras----------

Originally recorded as Matt Cohen's guest appearance on the Make It Click podcast hosted by Willson Cross.Matt Cohen joins Willson Cross on the Make It Click podcast for a sharp, no-fluff conversation on what actually makes early-stage startups click. As the founder and managing partner of Ripple Ventures, Matt breaks down how he went from Bay Street and Wall Street trading desks to becoming one of Canada's most active early-stage investors, backing founders at the inception stage, sometimes before incorporation, bank accounts, or even customers exist.Matt shares the real frameworks he uses to evaluate founders before product-market fit: team quality, problem validation, recruiting ability, and fundraising muscle. The conversation dives into how Ripple Ventures helps companies graduate from pre-seed to Series A, why Matt loves pivots (or “evolutions”), how Canadian founders differ from U.S. founders in ambition and risk tolerance, and why AI, deep tech, space tech, and defence are reshaping venture capital in Canada. If you're a founder thinking about taking the leap, or an investor trying to understand the next wave of Canadian innovation, this episode is packed with practical, brutally honest insight.Matt Cohen's Unconventional Path Into VC (02:07)From trading on Bay Street and Wall Street during the financial crisis to angel investing after the Turnstile exit, and eventually launching Ripple Ventures. How early wins in angel investing attracted Toronto family offices and became the foundation for Fund I.How Ripple Ventures Was Born Before the Fund Existed (06:04)Why Matt created the Ripple Ventures brand before raising institutional capital, how reputation compounded deal flow, and the early angel investments that became proof points for LPs.The Ripple Ventures Framework: The 4 Things Matt Looks For (16:46)The four-part founder filter: team, problem, recruiting, and raising capital. Why most inception-stage companies don't need customers yet, and what really matters before the first pilot.The Ideal Founding Team Structure in 2026 (20:56)Why two to three founders is the sweet spot, what breaks when there are four or five, and how AI-native companies are changing the ideal division of roles between technical, research, and business founders.Why Matt Loves Pivots (and Hates the Word Pivot) (24:48)A fascinating story of a database company evolving into consumer healthcare, plus the decision framework Matt uses to pressure-test major product or market changes.Why Canada's Founder Quality Is Rising Fast (34:18)Matt's most bullish view yet on Canadian founders, the Build Canada momentum, Shopify and AI spinouts, and why technical founders from Vector, Mila, and DeepMind alumni networks are creating a new wave.The Biggest Difference Between Canadian and U.S. Founders (41:34)A brutally honest comparison around ambition, downside protection, and why U.S. founders often optimize for upside while Canadian capital historically optimized for risk management.The Brutal Truth Every Founder Needs to Hear (48:25)Matt's best founder advice: don't believe your own BS, prepare for everything to go wrong, and understand the life cost of building a venture-scale company before you start.Ripple Ventures' New Startup Studio Thesis (55:20)Matt reveals how Ripple Ventures is evolving from fund + fellowship into a studio model, using AI agents and internal problem discovery to build products before bringing in founding teams.Listen to the Make It Click podcast: https://www.youtube.com/@hireborderlessConnect with Willson Cross on LinkedIn: https://www.linkedin.com/in/willsoncross/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

Skeptical overview of multiple topics related to UFOs!www.ufologyiscurropt.com - Luis Cayetano Support the show by signing up on Patreonhttps://patreon.com/strangerecon?utm_medium=unknown&utm_source=join_link&utm_campaign=creatorshare_creator&utm_content=copyLink

plume_rise_1.fds from the FDS Validation Guide (by NIST)&HEAD CHID='plume_rise_1',  TITLE='Test plume rise height in stable atmosphere' /&MESH IJK=50,52,50, XB=-50.,50.,-52.,52.,0.,100., MULT_ID='mesh1' /&MULT ID='mesh1', DZ=100., K_UPPER=1 /&MESH IJK=50,52,50, XB= 50.,250.,-104.,104.,0.,200., MULT_ID='mesh2' /&MULT ID='mesh2', DZ=200., K_UPPER=1 /&MESH IJK=50,50,50, XB=250.,650.,-200.,200.,0.,400., MULT_ID='mesh3' /&MULT ID='mesh3', DX=400., DZ=400., I_UPPER=3, K_UPPER=1 /&TIME T_END=900. /&MISC TMPA=20.36 /&WIND SPEED=5., LAPSE_RATE=-0.0048 /&SPEC ID='SULFUR DIOXIDE' /&VENT MB='XMIN', SURF_ID='OPEN' /&VENT MB='XMAX', SURF_ID='OPEN' /&VENT MB='YMIN', SURF_ID='OPEN' /&VENT MB='YMAX', SURF_ID='OPEN' /&VENT MB='ZMAX', SURF_ID='OPEN' /&PART ID='TRACERS', MASSLESS=.TRUE., SAMPLING_FACTOR=1 /&SURF ID='TOP', TMP_FRONT=200., MASS_FLUX(1)=0.01563, SPEC_ID(1)='SULFUR DIOXIDE', MASS_FLUX(2)=18.85, SPEC_ID(2)='AIR', COLOR='BLACK', PART_ID='TRACERS' /&OBST XB=-2.0,2.0,-2.0,2.0, 0,75, SURF_IDS='TOP','INERT','INERT' /&SLCF PBY=0, QUANTITY='VELOCITY', VECTOR=.TRUE. /&SLCF PBY=0, QUANTITY='TEMPERATURE' /&SLCF PBY=0, QUANTITY='DENSITY' /&SLCF PBY=0, QUANTITY='MASS FRACTION', SPEC_ID='SULFUR DIOXIDE' /&DEVC ID='z_CL', QUANTITY='MASS FRACTION', SPEC_ID='SULFUR DIOXIDE', XB=1800,1850,-200,200,0,800, SPATIAL_STATISTIC='MAXLOC Z' /&TAIL /Thank you NIST for providing an endless source of ASMR scripts on your github here: https://github.com/firemodels/fds/tree/master/ValidationI recommend everyone to go through this rich resource.----The Fire Science Show is produced by the Fire Science Media in collaboration with OFR Consultants. Thank you to the podcast sponsor for their continuous support towards our mission.

Is AI your biggest security threat—or your next unfair advantage?In this episode of Secure(It), host Philip de Souza sits down with Craig Nelson, founder of GrowthIQ.ai, to unpack how AI is reshaping cyber defense, data governance, and mission critical operations for security minded organizations.

#341 | In this Exit Five Live session, Cindy Dubon (Director of Growth Marketing, Goldcast), Kelly Arndt (Sr. Demand Gen Manager, Vector), Jeremy Chung (Founder and CEO, Ads by Jer), Tess Pfeifle (Associate Director of Marketing, AirVet), and Richard Meyer (Director of GTM and Growth, GoHappy) each break down a real ad campaign — the channel, the creative, the targeting, the spend, and the results. From influencer-led LinkedIn thought leader ads and CTV surround sound campaigns, to direct mail sequences, conference plays without a booth, and multi-channel signal-based targeting, these are campaigns you can actually steal from. Co-hosted by Jess Cook, VP Marketing at Vector.Ad campaigns linked here. Timestamps(00:00) - Intro and why real examples beat LinkedIn theory (06:15) - Session format and how to participate (08:07) - Cindy Dubon: $8K influencer campaign that generated $700K in pipeline (16:05) - Kelly Arndt: B2B surround sound with CTV, YouTube, and LinkedIn (24:56) - Jeremy Chung: Direct mail plus retargeting to book VC meetings (32:36) - Tess Pfeifle: Conference play with no booth and 2,000% ROI (39:31) - Richard Meyer: How GoHappy stopped overspending on LinkedIn (48:06) - Rapid fire Q&A with all five marketers 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: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.Consensus - An AI-powered interactive demo platform that lets you put personalized, self-serve demos on your site to turn anonymous researchers into high-intent leads. Learn more at goconsensus.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.Convertr - The enterprise lead data management platform that sits between your lead sources and your CRM, automatically validating, enriching, and standardizing every lead before it touches your systems. Check them out at convertr.io/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

This week, Aebhric O'Kelly is joined by Rhod Jordan and Bill Vasios as they discuss how to create an ICU in the jungle. They discuss setting up and managing a remote ICU in jungle environments, focusing on site selection, equipment, logistics, and medical considerations for field medics and responders.Chapters00:00 Introduction and Content Overview00:41 Premise and Scenario Setup for Jungle ICU01:33 Site Selection Criteria in Jungle Environments02:19 Environmental Challenges: Rain, Creepy Crawlies, and Hypothermia03:08 Privacy, Lighting, and Visibility in Remote Settings03:53 Creating a Functional Jungle Clinic Layout04:34 Lighting and Visibility Strategies at Night05:31 Accessibility and Zone Planning in Field Clinics06:09 Assessing Capacity: Multiple Patients and Beds07:01 Monitoring Equipment: Minimum and Advanced Options08:04 Power, Water, and Communication Logistics08:42 Prolonged Casualty Care and Exfil Planning09:59 Medical Supplies: Drugs, Medications, and Sterility10:42 Camp Craft and Bushcraft Skills for Remote Medics11:35 Wildcrafted Plants and Improvised Medicine12:12 Communication Strategies in Dense Canopy Environments13:08 Team Coordination and Role Assignments14:08 Dealing with Critical Patients and Exfil Decisions14:57 Infection Control and Hygiene in the Field15:54 Personal and Team Safety Measures16:39 Additional Non-Medical Gear for Remote Operations17:16 Lighting Solutions and Bug Management at Night18:08 Medications and Drugs for Jungle Medicine18:45 Over-the-Counter and Emergency Medications19:34 Special Considerations for Malaria and Vector-borne Diseases20:04 Infection Control and Hygiene Protocols20:56 Water Purification and Boiling Techniques21:35 Field Sterilisation and Maintaining Sterility22:25 Managing Glove Supplies and Hand Hygiene23:00 Dermatology and Common Skin Conditions23:38 Malaria Prophylaxis and Treatment Strategies24:32 Infection Control and Personal Hygiene25:14 Power and Charging Solutions in Remote Areas26:04 Water Supply and Filtration Methods26:45 Field Sterilisation and Water Boiling Techniques27:21 Camp Craft and Bushcraft Skills for Field Survival27:56 Wildcrafting and Medicinal Plants in the Jungle28:47 Communication Equipment and Strategies in Dense Canopy29:41 Team Coordination and Medical Decision-Making30:17 Water Safety and Potable Water Management31:05 Team Safety and Preventing Illness in the Field32:04 Bushcraft Skills for Remote Medical Operations32:58 Survival Skills and Improvised Medicine33:48 Communication Tools and Emergency Signalling34:28 Exfil Planning and Evacuation Protocols35:14 Prolonged Casualty Care and Equipment Needs36:01 Medical Kits and Supplies for Extended Operations36:51 Decision-Making in Critical Situations37:23 Non-Medical Essentials: Woobies, Tools, and Comfort Items38:10 Maintaining Morale and Team Cohesion38:42 Summary and Final Tips for Jungle ICU Setup

What does it take to build a B2B podcast that people actually want to listen to, in one of the most crowded content spaces out there?Producing a show with personality and purpose is the best way to spark interest, gain repeat listeners, and get people talking about your brand.In this episode, Amy sits down with Jess Cook, VP of Marketing at Vector, to talk about their fantastic podcast, This Meeting Could Have Been a Podcast – a show that we have the pleasure of working on at Content 10x. From scrapping the original concept to building a LinkedIn presence that's become a genuine awareness magnet, Jess shares how personality, specificity, and a smart content strategy combine to make a show that really stands out.Find out:Why Jess scrapped the original podcast concept and started over from scratchThe show's purpose: arming marketing leaders with how to have better conversations with their CEOs and solve problemsHow she named every episode like a Seinfeld script - and why that specificity worksThe decision to record in-person and how it transforms chemistry and production qualityHow LinkedIn personal branding has become Vector's most powerful awareness channel How encouraging the whole team at Vector to post has amplified their reachThe planned and surprise benefits of a strong B2B podcast How 'Vector-on-Vector' — using their own platform in their own marketing — has become their best proof pointWhat's coming next for Vector in 2026, including the “Ghost Tour Tour” and season 3 of the showImportant links & mentions:Jess on LinkedIn: https://www.linkedin.com/in/jesscook-contentmarketing/Josh on LinkedIn: https://www.linkedin.com/in/joshuaperk/Vector's Website: https://www.vector.coVector's podcast This Meeting Could've Been A Podcast: https://vector.transistor.fm/people/jess-cookVector episode Josh Overthrows Jess and Gets Cancelled: https://vector.transistor.fm/episodes/josh-overthrows-jess-and-gets-canceledContent 10x Podcast Episode 302: How to Maximize Content with a Small Team with Jess Cook: https://www.content10x.com/302Amy on LinkedIn https://www.linkedin.com/in/amywoods2/ Content 10x: https://www.content10x.com/Amy's book: www.content10x.com/book (Content 10x: More Content, Less Time, Maximum Results)Amy Woods is the CEO and founder of Content 10x, a creative agency that provides specialist content strategy, creation and repurposing support to B2B organizations. She's also a best-selling author, hosts two content marketing podcasts (The Content 10x Podcast and B2B Content Strategist), and speaks on stages all over the world about the power of content marketing.Join thousands of business owners, content creators and marketers and get the latest content marketing tips and advice delivered straight to your inbox every week https://www.content10x.com/newsletter

On this week's episode of the podcast, I am joined by Felix The, SVP of Product and Engineering - Advertising at Unity, to discuss the inner workings of Unity's Vector product and the strategic integration of engine-level data into the advertising ecosystem. We explore how Unity is rebuilding its machine learning infrastructure to provide more granular predictions and better performance for mobile gaming advertisers. Among other things, we discuss:How the integration of real-time game engine signals can improve user acquisition performance for mobile game advertisersWhy the shift toward massive unified models represents a fundamental departure from the traditional fragmented approach to machine learningWhether the use of runtime data provides a decisive competitive advantage over traditional software development kit signals for predictive modelingWhat the transition from manual creative production to generative exploration means for the long-term sustainability of performance marketing budgetsIf the ability to test core gameplay loops through playables before full development can significantly reduce traditional soft launch riskHow personalized creative units tailored to micro-cohorts will solve the persistent challenge of declining engagement in broad audience targetingThanks to the sponsors of this week's episode of the Mobile Dev Memo podcast:⁠⁠⁠⁠INCRMNTAL⁠⁠⁠. True attribution measures incrementality, always on.Xsolla⁠. With the Xsolla Web Shop, you can create a direct storefront, cut fees down to as low as 5%, and keep players engaged with bundles, rewards, and analytics.⁠Branch⁠. Branch is an AI-powered MMP, connecting every paid, owned, and organic touchpoint so growth teams can see exactly where to put their dollars to bring users in the door and keep them coming backVoyantis. Voyantis uses predictive AI to transform customer value into high-impact signals that boost ROAS across Google, Meta, and more.Interested in sponsoring the Mobile Dev Memo podcast? Contact Mobile Dev Memo advertising.

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?

Turbopuffer came out of a reading app.In 2022, Simon was helping his friends at Readwise scale their infra for a highly requested feature: article recommendations and semantic search. Readwise was paying ~$5k/month for their relational database and vector search would cost ~$20k/month making the feature too expensive to ship. In 2023 after mulling over the problem from Readwise, Simon decided he wanted to “build a search engine” which became Turbopuffer.We discuss:• Simon's path: Denmark → Shopify infra for nearly a decade → “angel engineering” across startups like Readwise, Replicate, and Causal → turbopuffer almost accidentally becoming a company • The Readwise origin story: building an early recommendation engine right after the ChatGPT moment, seeing it work, then realizing it would cost ~$30k/month for a company spending ~$5k/month total on infra and getting obsessed with fixing that cost structure • Why turbopuffer is “a search engine for unstructured data”: Simon's belief that models can learn to reason, but can't compress the world's knowledge into a few terabytes of weights, so they need to connect to systems that hold truth in full fidelity • The three ingredients for building a great database company: a new workload, a new storage architecture, and the ability to eventually support every query plan customers will want on their data • The architecture bet behind turbopuffer: going all in on object storage and NVMe, avoiding a traditional consensus layer, and building around the cloud primitives that only became possible in the last few years • Why Simon hated operating Elasticsearch at Shopify: years of painful on-call experience shaped his obsession with simplicity, performance, and eliminating state spread across multiple systems • The Cursor story: launching turbopuffer as a scrappy side project, getting an email from Cursor the next day, flying out after a 4am call, and helping cut Cursor's costs by 95% while fixing their per-user economics • The Notion story: buying dark fiber, tuning TCP windows, and eating cross-cloud costs because Simon refused to compromise on architecture just to close a deal faster • Why AI changes the build-vs-buy equation: it's less about whether a company can build search infra internally, and more about whether they have time especially if an external team can feel like an extension of their own • Why RAG isn't dead: coding companies still rely heavily on search, and Simon sees hybrid retrieval semantic, text, regex, SQL-style patterns becoming more important, not less • How agentic workloads are changing search: the old pattern was one retrieval call up front; the new pattern is one agent firing many parallel queries at once, turning search into a highly concurrent tool call • Why turbopuffer is reducing query pricing: agentic systems are dramatically increasing query volume, and Simon expects retrieval infra to adapt to huge bursts of concurrent search rather than a small number of carefully chosen calls • The philosophy of “playing with open cards”: Simon's habit of being radically honest with investors, including telling Lachy Groom he'd return the money if turbopuffer didn't hit PMF by year-end • The “P99 engineer”: Simon's framework for building a talent-dense company, rejecting by default unless someone on the team feels strongly enough to fight for the candidate —Simon Hørup Eskildsen• LinkedIn: https://www.linkedin.com/in/sirupsen• X: https://x.com/Sirupsen• https://sirupsen.com/aboutturbopuffer• https://turbopuffer.com/Full Video PodTimestamps00:00:00 The PMF promise to Lachy Groom00:00:25 Intro and Simon's background00:02:19 What turbopuffer actually is00:06:26 Shopify, Elasticsearch, and the pain behind the company00:10:07 The Readwise experiment that sparked turbopuffer00:12:00 The insight Simon couldn't stop thinking about00:17:00 S3 consistency, NVMe, and the architecture bet00:20:12 The Notion story: latency, dark fiber, and conviction00:25:03 Build vs. buy in the age of AI00:26:00 The Cursor story: early launch to breakout customer00:29:00 Why code search still matters00:32:00 Search in the age of agents00:34:22 Pricing turbopuffer in the AI era00:38:17 Why Simon chose Lachy Groom00:41:28 Becoming a founder on purpose00:44:00 The “P99 engineer” philosophy00:49:30 Bending software to your will00:51:13 The future of turbopuffer00:57:05 Simon's tea obsession00:59:03 Tea kits, X Live, and P99 LiveTranscriptSimon Hørup Eskildsen: I don't think I've said this publicly before, but I just called Lockey and was like, local Lockie. Like if this doesn't have PMF by the end of the year, like we'll just like return all the money to you. But it's just like, I don't really, we, Justine and I don't wanna work on this unless it's really working.So we want to give it the best shot this year and like we're really gonna go for it. We're gonna hire a bunch of people. We're just gonna be honest with everyone. Like when I don't know how to play a game, I just play with open cards. Lockey was the only person that didn't, that didn't freak out. He was like, I've never heard anyone say that before.Alessio: Hey everyone, welcome to the Leading Space podcast. This is Celesio Pando, Colonel Laz, and I'm joined by Swix, editor of Leading Space.swyx: Hello. Hello, uh, we're still, uh, recording in the Ker studio for the first time. Very excited. And today we are joined by Simon Eski. Of Turbo Farer welcome.Simon Hørup Eskildsen: Thank you so much for having me.swyx: Turbo Farer has like really gone on a huge tear, and I, I do have to mention that like you're one of, you're not my newest member of the Danish AHU Mafia, where like there's a lot of legendary programmers that have come out of it, like, uh, beyond Trotro, Rasmus, lado Berg and the V eight team and, and Google Maps team.Uh, you're mostly a Canadian now, but isn't that interesting? There's so many, so much like strong Danish presence.Simon Hørup Eskildsen: Yeah, I was writing a post, um, not that long ago about sort of the influences. So I grew up in Denmark, right? I left, I left when, when I was 18 to go to Canada to, to work at Shopify. Um, and so I, like, I've, I would still say that I feel more Danish than, than Canadian.This is also the weird accent. I can't say th because it, this is like, I don't, you know, my wife is also Canadian, um, and I think. I think like one of the things in, in Denmark is just like, there's just such a ruthless pragmatism and there's also a big focus on just aesthetics. Like, they're like very, people really care about like where, what things look like.Um, and like Canada has a lot of attributes, US has, has a lot of attributes, but I think there's been lots of the great things to carry. I don't know what's in the water in Ahu though. Um, and I don't know that I could be considered part of the Mafi mafia quite yet, uh, compared to the phenomenal individuals we just mentioned.Barra OV is also, uh, Danish Canadian. Okay. Yeah. I don't know where he lives now, but, and he's the PHP.swyx: Yeah. And obviously Toby German, but moved to Canada as well. Yes. Like this is like import that, uh, that, that is an interesting, um, talent move.Alessio: I think. I would love to get from you. Definition of Turbo puffer, because I think you could be a Vector db, which is maybe a bad word now in some circles, you could be a search engine.It's like, let, let's just start there and then we'll maybe run through the history of how you got to this point.Simon Hørup Eskildsen: For sure. Yeah. So Turbo Puffer is at this point in time, a search engine, right? We do full text search and we do vector search, and that's really what we're specialized in. If you're trying to do much more than that, like then this might not be the right place yet, but Turbo Buffer is all about search.The other way that I think about it is that we can take all of the world's knowledge, all of the exabytes and exabytes of data that there is, and we can use those tokens to train a model, but we can't compress all of that into a few terabytes of weights, right? Compress into a few terabytes of weights, how to reason with the world, how to make sense of the knowledge.But we have to somehow connect it to something externally that actually holds that like in full fidelity and truth. Um, and that's the thing that we intend to become. Right? That's like a very holier than now kind of phrasing, right? But being the search engine for unstructured, unstructured data is the focus of turbo puffer at this point in time.Alessio: And let's break down. So people might say, well, didn't Elasticsearch already do this? And then some other people might say, is this search on my data, is this like closer to rag than to like a xr, like a public search thing? Like how, how do you segment like the different types of search?Simon Hørup Eskildsen: The way that I generally think about this is like, there's a lot of database companies and I think if you wanna build a really big database company, sort of, you need a couple of ingredients to be in the air.We don't, which only happens roughly every 15 years. You need a new workload. You basically need the ambition that every single company on earth is gonna have data in your database. Multiple times you look at a company like Oracle, right? You will, like, I don't think you can find a company on earth with a digital presence that it not, doesn't somehow have some data in an Oracle database.Right? And I think at this point, that's also true for Snowflake and Databricks, right? 15 years later it's, or even more than that, there's not a company on earth that doesn't, in. Or directly is consuming Snowflake or, or Databricks or any of the big analytics databases. Um, and I think we're in that kind of moment now, right?I don't think you're gonna find a company over the next few years that doesn't directly or indirectly, um, have all their data available for, for search and connect it to ai. So you need that new workload, like you need something to be happening where there's a new workload that causes that to happen, and that new workload is connecting very large amounts of data to ai.The second thing you need. The second condition to build a big database company is that you need some new underlying change in the storage architecture that is not possible from the databases that have come before you. If you look at Snowflake and Databricks, right, commoditized, like massive fleet of HDDs, like that was not possible in it.It just wasn't in the air in the nineties, right? So you just didn't, we just didn't build these systems. S3 and and and so on was not around. And I think the architecture that is now possible that wasn't possible 15 years ago is to go all in on NVME SSDs. It requires a particular type of architecture for the database that.It's difficult to retrofit onto the databases that are already there, including the ones you just mentioned. The second thing is to go all in on OIC storage, more so than we could have done 15 years ago. Like we don't have a consensus layer, we don't really have anything. In fact, you could turn off all the servers that Turbo Buffer has, and we would not lose any data because we have all completely all in on OIC storage.And this means that our architecture is just so simple. So that's the second condition, right? First being a new workload. That means that every company on earth, either indirectly or directly, is using your database. Second being, there's some new storage architecture. That means that the, the companies that have come before you can do what you're doing.I think the third thing you need to do to build a big database company is that over time you have to implement more or less every Cory plan on the data. What that means is that you. You can't just get stuck in, like, this is the one thing that a database does. It has to be ever evolving because when someone has data in the database, they over time expect to be able to ask it more or less every question.So you have to do that to get the storage architecture to the limit of what, what it's capable of. Those are the three conditions.swyx: I just wanted to get a little bit of like the motivation, right? Like, so you left Shopify, you're like principal, engineer, infra guy. Um, you also head of kernel labs, uh, inside of Shopify, right?And then you consulted for read wise and that it kind of gave you that, that idea. I just wanted you to tell that story. Um, maybe I, you've told it before, but, uh, just introduce the, the. People to like the, the new workload, the sort of aha moment for turbo PufferSimon Hørup Eskildsen: For sure. So yeah, I spent almost a decade at Shopify.I was on the infrastructure team, um, from the fairly, fairly early days around 2013. Um, at the time it felt like it was growing so quickly and everything, all the metrics were, you know, doubling year on year compared to the, what companies are contending with today. It's very cute in growth. I feel like lot some companies are seeing that month over month.Um, of course. Shopify compound has been compounding for a very long time now, but I spent a decade doing that and the majority of that was just make sure the site is up today and make sure it's up a year from now. And a lot of that was really just the, um, you know, uh, the Kardashians would drive very, very large amounts of, of data to, to uh, to Shopify as they were rotating through all the merch and building out their businesses.And we just needed to make sure we could handle that. Right. And sometimes these were events, a million requests per second. And so, you know, we, we had our own data centers back in the day and we were moving to the cloud and there was so much sharding work and all of that that we were doing. So I spent a decade just scaling databases ‘cause that's fundamentally what's the most difficult thing to scale about these sites.The database that was the most difficult for me to scale during that time, and that was the most aggravating to be on call for, was elastic search. It was very, very difficult to deal with. And I saw a lot of projects that were just being held back in their ambition by using it.swyx: And I mean, self-hosted.Self-hosted. ‘causeSimon Hørup Eskildsen: it's, yeah, and it commercial, this is like 2015, right? So it's like a very particular vintage. Right. It's probably better at a lot of these things now. Um, it was difficult to contend with and I'm just like, I just think about it. It's an inverted index. It should be good at these kinds of queries and do all of this.And it was, we, we often couldn't get it to do exactly what we needed to do or basically get lucine to do, like expose lucine raw to, to, to what we needed to do. Um, so that was like. Just something that we did on the side and just panic scaled when we needed to, but not a particular focus of mine. So I left, and when I left, I, um, wasn't sure exactly what I wanted to do.I mean, it spent like a decade inside of the same company. I'd like grown up there. I started working there when I was 18.swyx: You only do Rails?Simon Hørup Eskildsen: Yeah. I mean, yeah. Rails. And he's a Rails guy. Uh, love Rails. So good. Um,Alessio: we all wish we could still work in Rails.swyx: I know know. I know, but some, I tried learning Ruby.It's just too much, like too many options to do the same thing. It's, that's my, I I know there's a, there's a way to do it.Simon Hørup Eskildsen: I love it. I don't know that I would use it now, like given cloud code and, and, and cursor and everything, but, um, um, but still it, like if I'm just sitting down and writing a teal code, that's how I think.But anyway, I left and I wasn't, I talked to a couple companies and I was like, I don't. I need to see a little bit more of the world here to know what I'm gonna like focus on next. Um, and so what I decided is like I was gonna, I called it like angel engineering, where I just hopped around in my friend's companies in three months increments and just helped them out with something.Right. And, and just vested a bit of equity and solved some interesting infrastructure problem. So I worked with a bunch of companies at the time, um, read Wise was one of them. Replicate was one of them. Um, causal, I dunno if you've tried this, it's like a, it's a spreadsheet engine Yeah. Where you can do distribution.They sold recently. Yeah. Um, we've been, we used that in fp and a at, um, at Turbo Puffer. Um, so a bunch of companies like this and it was super fun. And so we're the Chachi bt moment happened, I was with. With read Wise for a stint, we were preparing for the reader launch, right? Which is where you, you cue articles and read them later.And I was just getting their Postgres up to snuff, like, which basically boils down to tuning, auto vacuum. So I was doing that and then this happened and we were like, oh, maybe we should build a little recommendation engine and some features to try to hook in the lms. They were not that good yet, but it was clear there was something there.And so I built a small recommendation engine just, okay, let's take the articles that you've recently read, right? Like embed all the articles and then do recommendations. It was good enough that when I ran it on one of the co-founders of Rey's, like I found out that I got articles about, about having a child.I'm like, oh my God, I didn't, I, I didn't know that, that they were having a child. I wasn't sure what to do with that information, but the recommendation engine was good enough that it was suggesting articles, um, about that. And so there was, there was recommendations and uh, it actually worked really well.But this was a company that was spending maybe five grand a month in total on all their infrastructure and. When I did the napkin math on running the embeddings of all the articles, putting them into a vector index, putting it in prod, it's gonna be like 30 grand a month. That just wasn't tenable. Right?Like Read Wise is a proudly bootstrapped company and it's paying 30 grand for infrastructure for one feature versus five. It just wasn't tenable. So sort of in the bucket of this is useful, it's pretty good, but let us, let's return to it when the costs come down.swyx: Did you say it grows by feature? So for five to 30 is by the number of, like, what's the, what's the Scaling factor scale?It scales by the number of articles that you embed.Simon Hørup Eskildsen: It does, but what I meant by that is like five grand for like all of the other, like the Heroku, dinos, Postgres, like all the other, and this then storage is 30. Yeah. And then like 30 grand for one feature. Right. Which is like, what other articles are related to this one.Um, so it was just too much right to, to power everything. Their budget would've been maybe a few thousand dollars, which still would've been a lot. And so we put it in a bucket of, okay, we're gonna do that later. We'll wait, we will wait for the cost to come down. And that haunted me. I couldn't stop thinking about it.I was like, okay, there's clearly some latent demand here. If the cost had been a 10th, we would've shipped it and. This was really the only data point that I had. Right. I didn't, I, I didn't, I didn't go out and talk to anyone else. It was just so I started reading Right. I couldn't, I couldn't help myself.Like I didn't know what like a vector index is. I, I generally barely do about how to generate the vectors. There was a lot of hype about, this is a early 2023. There was a lot of hype about vector databases. There were raising a lot of money and it's like, I really didn't know anything about it. It's like, you know, trying these little models, fine tuning them.Like I was just trying to get sort of a lay of the land. So I just sat down. I have this. A GitHub repository called Napkin Math. And on napkin math, there's just, um, rows of like, oh, this is how much bandwidth. Like this is how many, you know, you can do 25 gigabytes per second on average to dram. You can do, you know, five gigabytes per second of rights to an SSD, blah blah.All of these numbers, right? And S3, how many you could do per, how much bandwidth can you drive per connection? I was just sitting down, I was like, why hasn't anyone build a database where you just put everything on O storage and then you puff it into NVME when you use the data and you puff it into dram if you're, if you're querying it alive, it's just like, this seems fairly obvious and you, the only real downside to that is that if you go all in on o storage, every right will take a couple hundred milliseconds of latency, but from there it's really all upside, right?You do the first go, it takes half a second. And it sort of occurred to me as like, well. The architecture is really good for that. It's really good for AB storage, it's really good for nvm ESSD. It's, well, you just couldn't have done that 10 years ago. Back to what we were talking about before. You really have to build a database where you have as few round trips as possible, right?This is how CPUs work today. It's how NVM E SSDs work. It's how as, um, as three works that you want to have a very large amount of outstanding requests, right? Like basically go to S3, do like that thousand requests to ask for data in one round trip. Wait for that. Get that, like, make a new decision. Do it again, and try to do that maybe a maximum of three times.But no databases were designed that way within NVME as is ds. You can drive like within, you know, within a very low multiple of DRAM bandwidth if you use it that way. And same with S3, right? You can fully max out the network card, which generally is not maxed out. You get very, like, very, very good bandwidth.And, but no one had built a database like that. So I was like, okay, well can't you just, you know, take all the vectors right? And plot them in the proverbial coordinate system. Get the clusters, put a file on S3 called clusters, do json, and then put another file for every cluster, you know, cluster one, do js O cluster two, do js ON you know that like it's two round trips, right?So you get the clusters, you find the closest clusters, and then you download the cluster files like the, the closest end. And you could do this in two round trips.swyx: You were nearest neighbors locally.Simon Hørup Eskildsen: Yes. Yes. And then, and you would build this, this file, right? It's just like ultra simplistic, but it's not a far shot from what the first version of Turbo Buffer was.Why hasn't anyone done thatAlessio: in that moment? From a workload perspective, you're thinking this is gonna be like a read heavy thing because they're doing recommend. Like is the fact that like writes are so expensive now? Oh, with ai you're actually not writing that much.Simon Hørup Eskildsen: At that point I hadn't really thought too much about, well no actually it was always clear to me that there was gonna be a lot of rights because at Shopify, the search clusters were doing, you know, I don't know, tens or hundreds of crew QPS, right?‘cause you just have to have a human sit and type in. But we did, you know, I don't know how many updates there were per second. I'm sure it was in the millions, right into the cluster. So I always knew there was like a 10 to 100 ratio on the read write. In the read wise use case. It's, um, even, even in the read wise use case, there'd probably be a lot fewer reads than writes, right?There's just a lot of churn on the amount of stuff that was going through versus the amount of queries. Um, I wasn't thinking too much about that. I was mostly just thinking about what's the fundamentally cheapest way to build a database in the cloud today using the primitives that you have available.And this is it, right? You just, now you have one machine and you know, let's say you have a terabyte of data in S3, you paid the $200 a month for that, and then maybe five to 10% of that data and needs to be an NV ME SSDs and less than that in dram. Well. You're paying very, very little to inflate the data.swyx: By the way, when you say no one else has done that, uh, would you consider Neon, uh, to be on a similar path in terms of being sort of S3 first and, uh, separating the compute and storage?Simon Hørup Eskildsen: Yeah, I think what I meant with that is, uh, just build a completely new database. I don't know if we were the first, like it was very much, it was, I mean, I, I hadn't, I just looked at the napkin math and was like, this seems really obvious.So I'm sure like a hundred people came up with it at the same time. Like the light bulb and every invention ever. Right. It was just in the air. I think Neon Neon was, was first to it. And they're trying, they're retrofitted onto Postgres, right? And then they built this whole architecture where you have, you have it in memory and then you sort of.You know, m map back to S3. And I think that was very novel at the time to do it for, for all LTP, but I hadn't seen a database that was truly all in, right. Not retrofitting it. The database felt built purely for this no consensus layer. Even using compare and swap on optic storage to do consensus. I hadn't seen anyone go that all in.And I, I mean, there, there, I'm sure there was someone that did that before us. I don't know. I was just looking at the napkin mathswyx: and, and when you say consensus layer, uh, are you strongly relying on S3 Strong consistency? You are. Okay.SoSimon Hørup Eskildsen: that is your consensus layer. It, it is the consistency layer. And I think also, like, this is something that most people don't realize, but S3 only became consistent in December of 2020.swyx: I remember this coming out during COVID and like people were like, oh, like, it was like, uh, it was just like a free upgrade.Simon Hørup Eskildsen: Yeah.swyx: They were just, they just announced it. We saw consistency guys and like, okay, cool.Simon Hørup Eskildsen: And I'm sure that they just, they probably had it in prod for a while and they're just like, it's done right.And people were like, okay, cool. But. That's a big moment, right? Like nv, ME SSDs, were also not in the cloud until around 2017, right? So you just sort of had like 2017 nv, ME SSDs, and people were like, okay, cool. There's like one skew that does this, whatever, right? Takes a few years. And then the second thing is like S3 becomes consistent in 2020.So now it means you don't have to have this like big foundation DB or like zookeeper or whatever sitting there contending with the keys, which is how. You know, that's what Snowflake and others have do so muchswyx: for goneSimon Hørup Eskildsen: Exactly. Just gone. Right? And so just push to the, you know, whatever, how many hundreds of people they have working on S3 solved and then compare and swap was not in S3 at this point in time,swyx: by the way.Uh, I don't know what that is, so maybe you wanna explain. Yes. Yeah.Simon Hørup Eskildsen: Yes. So, um, what Compare and swap is, is basically, you can imagine that if you have a database, it might be really nice to have a file called metadata json. And metadata JSON could say things like, Hey, these keys are here and this file means that, and there's lots of metadata that you have to operate in the database, right?But that's the simplest way to do it. So now you have might, you might have a lot of servers that wanna change the metadata. They might have written a file and want the metadata to contain that file. But you have a hundred nodes that are trying to contend with this metadata that JSON well, what compare and Swap allows you to do is basically just you download the file, you make the modifications, and then you write it only if it hasn't changed.While you did the modification and if not you retry. Right? Should just have this retry loops. Now you can imagine if you have a hundred nodes doing that, it's gonna be really slow, but it will converge over time. That primitive was not available in S3. It wasn't available in S3 until late 2024, but it was available in GCP.The real story of this is certainly not that I sat down and like bake brained it. I was like, okay, we're gonna start on GCS S3 is gonna get it later. Like it was really not that we started, we got really lucky, like we started on GCP and we started on GCP because tur um, Shopify ran on GCP. And so that was the platform I was most available with.Right. Um, and I knew the Canadian team there ‘cause I'd worked with them at Shopify and so it was natural for us to start there. And so when we started building the database, we're like, oh yeah, we have to build a, we really thought we had to build a consensus layer, like have a zookeeper or something to do this.But then we discovered the compare and swap. It's like, oh, we can kick the can. Like we'll just do metadata r json and just, it's fine. It's probably fine. Um, and we just kept kicking the can until we had very, very strong conviction in the idea. Um, and then we kind of just hinged the company on the fact that S3 probably was gonna get this, it started getting really painful in like mid 2024.‘cause we were closing deals with, um, um, notion actually that was running in AWS and we're like, trust us. You, you really want us to run this in GCP? And they're like, no, I don't know about that. Like, we're running everything in AWS and the latency across the cloud were so big and we had so much conviction that we bought like, you know, dark fiber between the AWS regions in, in Oregon, like in the InterExchange and GCP is like, we've never seen a startup like do like, what's going on here?And we're just like, no, we don't wanna do this. We were tuning like TCP windows, like everything to get the latency down ‘cause we had so high conviction in not doing like a, a metadata layer on S3. So those were the three conditions, right? Compare and swap. To do metadata, which wasn't in S3 until late 2024 S3 being consistent, which didn't happen until December, 2020.Uh, 2020. And then NVMe ssd, which didn't end in the cloud until 2017.swyx: I mean, in some ways, like a very big like cloud success story that like you were able to like, uh, put this all together, but also doing things like doing, uh, bind our favor. That that actually is something I've never heard.Simon Hørup Eskildsen: I mean, it's very common when you're a big company, right?You're like connecting your own like data center or whatever. But it's like, it was uniquely just a pain with notion because the, um, the org, like most of the, like if you're buying in Ashburn, Virginia, right? Like US East, the Google, like the GCP and, and AWS data centers are like within a millisecond on, on each other, on the public exchanges.But in Oregon uniquely, the GCP data center sits like a couple hundred kilometers, like east of Portland and the AWS region sits in Portland, but the network exchange they go through is through Seattle. So it's like a full, like 14 milliseconds or something like that. And so anyway, yeah. It's, it's, so we were like, okay, we can't, we have to go through an exchange in Portland.Yeah. Andswyx: you'd rather do this than like run your zookeeper and likeSimon Hørup Eskildsen: Yes. Way rather. It doesn't have state, I don't want state and two systems. Um, and I think all that is just informed by Justine, my co-founder and I had just been on call for so long. And the worst outages are the ones where you have state in multiple places that's not syncing up.So it really came from, from a a, like just a, a very pure source of pain, of just imagining what we would be Okay. Being woken up at 3:00 AM about and having something in zookeeper was not one of them.swyx: You, you're talking to like a notion or something. Do they care or do they just, theySimon Hørup Eskildsen: just, they care about latency.swyx: They latency cost. That's it.Simon Hørup Eskildsen: They just cared about latency. Right. And we just absorbed the cost. We're just like, we have high conviction in this. At some point we can move them to AWS. Right. And so we just, we, we'll buy the fiber, it doesn't matter. Right. Um, and it's like $5,000. Usually when you buy fiber, you buy like multiple lines.And we're like, we can only afford one, but we will just test it that when it goes over the public internet, it's like super smooth. And so we did a lot of, anyway, it's, yeah, it was, that's cool.Alessio: You can imagine talking to the GCP rep and it's like, no, we're gonna buy, because we know we're gonna turn, we're gonna turn from you guys and go to AWS in like six months.But in the meantime we'll do this. It'sSimon Hørup Eskildsen: a, I mean, like they, you know, this workload still runs on GCP for what it's worth. Right? ‘cause it's so, it was just, it was so reliable. So it was never about moving off GCP, it was just about honesty. It was just about giving notion the latency that they deserved.Right. Um, and we didn't want ‘em to have to care about any of this. We also, they were like, oh, egress is gonna be bad. It was like, okay, screw it. Like we're just gonna like vvc, VPC peer with you and AWS we'll eat the cost. Yeah. Whatever needs to be done.Alessio: And what were the actual workloads? Because I think when you think about ai, it's like 14 milliseconds.It's like really doesn't really matter in the scheme of like a model generation.Simon Hørup Eskildsen: Yeah. We were told the latency, right. That we had to beat. Oh, right. So, so we're just looking at the traces. Right. And then sort of like hand draw, like, you know, kind of like looking at the trace and then thinking what are the other extensions of the trace?Right. And there's a lot more to it because it's also when you have, if you have 14 versus seven milliseconds, right. You can fit in another round trip. So we had to tune TCP to try to send as much data in every round trip, prewarm all the connections. And there was, there's a lot of things that compound from having these kinds of round trips, but in the grand scheme it was just like, well, we have to beat the latency of whatever we're up against.swyx: Which is like they, I mean, notion is a database company. They could have done this themselves. They, they do lots of database engineering themselves. How do you even get in the door? Like Yeah, just like talk through that kind of.Simon Hørup Eskildsen: Last time I was in San Francisco, I was talking to one of the engineers actually, who, who was one of our champions, um, at, AT Notion.And they were, they were just trying to make sure that the, you know, per user cost matched the economics that they needed. You know, Uhhuh like, it's like the way I think about, it's like I have to earn a return on whatever the clouds charge me and then my customers have to earn a return on that. And it's like very simple, right?And so there has to be gross margin all the way up and that's how you build the product. And so then our customers have to make the right set of trade off the turbo Puffer makes, and if they're happy with that, that's great.swyx: Do you feel like you're competing with build internally versus buy or buy versus buy?Simon Hørup Eskildsen: Yeah, so, sorry, this was all to build up to your question. So one of the notion engineers told me that they'd sat and probably on a napkin, like drawn out like, why hasn't anyone built this? And then they saw terrible. It was like, well, it literally that. So, and I think AI has also changed the buy versus build equation in terms of, it's not really about can we build it, it's about do we have time to build it?I think they like, I think they felt like, okay, if this is a team that can do that and they, they feel enough like an extension of our team, well then we can go a lot faster, which would be very, very good for them. And I mean, they put us through the, through the test, right? Like we had some very, very long nights to to, to do that POC.And they were really our biggest, our second big customer off the cursor, which also was a lot of late nights. Right.swyx: Yeah. That, I mean, should we go into that story? The, the, the sort of Chris's story, like a lot, um, they credit you a lot for. Working very closely with them. So I just wanna hear, I've heard this, uh, story from Sole's point of view, but like, I'm curious what, what it looks like from your side.Simon Hørup Eskildsen: I actually haven't heard it from Sole's point of view, so maybe you can now cross reference it. The way that I remember it was that, um, the day after we launched, which was just, you know, I'd worked the whole summer on, on the first version. Justine wasn't part of it yet. ‘cause I just, I didn't tell anyone that summer that I was working on this.I was just locked in on building it because it's very easy otherwise to confuse talking about something to actually doing it. And so I was just like, I'm not gonna do that. I'm just gonna do the thing. I launched it and at this point turbo puffer is like a rust binary running on a single eight core machine in a T Marks instance.And me deploying it was like looking at the request log and then like command seeing it or like control seeing it to just like, okay, there's no request. Let's upgrade the binary. Like it was like literally the, the, the, the scrappiest thing. You could imagine it was on purpose because just like at Shopify, we did that all the time.Like, we like move, like we ran things in tux all the time to begin with. Before something had like, at least the inkling of PMF, it was like, okay, is anyone gonna hear about this? Um, and one of the cursor co-founders Arvid reached out and he just, you know, the, the cursor team are like all I-O-I-I-M-O like, um, contenders, right?So they just speak in bullet points and, and facts. It was like this amazing email exchange just of, this is how many QPS we have, this is what we're paying, this is where we're going, blah, blah, blah. And so we're just conversing in bullet points. And I tried to get a call with them a few times, but they were, so, they were like really writing the PMF bowl here, just like late 2023.And one time Swally emails me at like five. What was it like 4:00 AM Pacific time saying like, Hey, are you open for a call now? And I'm on the East coast and I, it was like 7:00 AM I was like, yeah, great, sure, whatever. Um, and we just started talking and something. Then I didn't know anything about sales.It was something that just comp compelled me. I have to go see this team. Like, there's something here. So I, I went to San Francisco and I went to their office and the way that I remember it is that Postgres was down when I showed up at the office. Did SW tell you this? No. Okay. So Postgres was down and so it's like they were distracting with that.And I was trying my best to see if I could, if I could help in any way. Like I knew a little bit about databases back to tuning, auto vacuum. It was like, I think you have to tune out a vacuum. Um, and so we, we talked about that and then, um, that evening just talked about like what would it look like, what would it look like to work with us?And I just said. Look like we're all in, like we will just do what we'll do whatever, whatever you tell us, right? They migrated everything over the next like week or two, and we reduced their cost by 95%, which I think like kind of fixed their per user economics. Um, and it solved a lot of other things. And we were just, Justine, this is also when I asked Justine to come on as my co-founder, she was the best engineer, um, that I ever worked with at Shopify.She lived two blocks away and we were just, okay, we're just gonna get this done. Um, and we did, and so we helped them migrate and we just worked like hell over the next like month or two to make sure that we were never an issue. And that was, that was the cursor story. Yeah.swyx: And, and is code a different workload than normal text?I, I don't know. Is is it just text? Is it the same thing?Simon Hørup Eskildsen: Yeah, so cursor's workload is basically, they, um, they will embed the entire code base, right? So they, they will like chunk it up in whatever they would, they do. They have their own embedding model, um, which they've been public about. Um, and they find that on, on, on their evals.It. There's one of their evals where it's like a 25% improvement on a very particular workload. They have a bunch of blog posts about it. Um, I think it works best on larger code basis, but they've trained their own embedding model to do this. Um, and so you'll see it if you use the cursor agent, it will do searches.And they've also been public around, um, how they've, I think they post trained their model to be very good at semantic search as well. Um, and that's, that's how they use it. And so it's very good at, like, can you find me on the code that's similar to this, or code that does this? And just in, in this queries, they also use GR to supplement it.swyx: Yeah.Simon Hørup Eskildsen: Um, of courseswyx: it's been a big topic of discussion like, is rag dead because gr you know,Simon Hørup Eskildsen: and I mean like, I just, we, we see lots of demand from the coding company to ethicsswyx: search in every part. Yes.Simon Hørup Eskildsen: Uh, we, we, we see demand. And so, I mean, I'm. I like case studies. I don't like, like just doing like thought pieces on this is where it's going.And like trying to be all macroeconomic about ai, that's has turned out to be a giant waste of time because no one can really predict any of this. So I just collect case studies and I mean, cursor has done a great job talking about what they're doing and I hope some of the other coding labs that use Turbo Puffer will do the same.Um, but it does seem to make a difference for particular queries. Um, I mean we can also do text, we can also do RegX, but I should also say that cursors like security posture into Tur Puffer is exceptional, right? They have their own embedding model, which makes it very difficult to reverse engineer. They obfuscate the file paths.They like you. It's very difficult to learn anything about a code base by looking at it. And the other thing they do too is that for their customers, they encrypt it with their encryption keys in turbo puffer's bucket. Um, so it's, it's, it's really, really well designed.swyx: And so this is like extra stuff they did to work with you because you are not part of Cursor.Exactly like, and this is just best practice when working in any database, not just you guys. Okay. Yeah, that makes sense. Yeah. I think for me, like the, the, the learning is kind of like you, like all workloads are hybrid. Like, you know, uh, like you, you want the semantic, you want the text, you want the RegX, you want sql.I dunno. Um, but like, it's silly to like be all in on like one particularly query pattern.Simon Hørup Eskildsen: I think, like I really like the way that, um, um, that swally at cursor talks about it, which is, um, I'm gonna butcher it here. Um, and you know, I'm a, I'm a database scalability person. I'm not a, I, I dunno anything about training models other than, um, what the internet tells me and what.The way he describes is that this is just like cash compute, right? It's like you have a point in time where you're looking at some particular context and focused on some chunk and you say, this is the layer of the neural net at this point in time. That seems fundamentally really useful to do cash compute like that.And, um, how the value of that will change over time. I'm, I'm not sure, but there seems to be a lot of value in that.Alessio: Maybe talk a bit about the evolution of the workload, because even like search, like maybe two years ago it was like one search at the start of like an LLM query to build the context. Now you have a gentech search, however you wanna call it, where like the model is both writing and changing the code and it's searching it again later.Yeah. What are maybe some of the new types of workloads or like changes you've had to make to your architecture for it?Simon Hørup Eskildsen: I think you're right. When I think of rag, I think of, Hey, there's an 8,000 token, uh, context window and you better make it count. Um, and search was a way to do that now. Everything is moving towards the, just let the agent do its thing.Right? And so back to the thing before, right? The LLM is very good at reasoning with the data, and so we're just the tool call, right? And that's increasingly what we see our customers doing. Um, what we're seeing more demand from, from our customers now is to do a lot of concurrency, right? Like Notion does a ridiculous amount of queries in every round trip just because they can't.And I'm also now, when I use the cursor agent, I also see them doing more concurrency than I've ever seen before. So a bit similar to how we designed a database to drive as much concurrency in every round trip as possible. That's also what the agents are doing. So that's new. It means just an enormous amount of queries all at once to the dataset while it's warm in as few turns as possible.swyx: Can I clarify one thing on that?Simon Hørup Eskildsen: Yes.swyx: Is it, are they batching multiple users or one user is driving multiple,Simon Hørup Eskildsen: one user driving multiple, one agent driving.swyx: It's parallel searching a bunch of things.Simon Hørup Eskildsen: Exactly.swyx: Yeah. Yeah, exactly. So yeah, the clinician also did, did this for the fast context thing, like eight parallel at once.Simon Hørup Eskildsen: Yes.swyx: And, and like an interesting problem is, well, how do you make sure you have enough diversity so you're not making the the same request eight times?Simon Hørup Eskildsen: And I think like that's probably also where the hybrid comes in, where. That's another way to diversify. It's a completely different way to, to do the search.That's a big change, right? So before it was really just like one call and then, you know, the LLM took however many seconds to return, but now we just see an enormous amount of queries. So the, um, we just see more queries. So we've like tried to reduce query, we've reduced query pricing. Um, this is probably the first time actually I'm saying that, but the query pricing is being reduced, like five x.Um, and we'll probably try to reduce it even more to accommodate some of these workloads of just doing very large amounts of queries. Um, that's one thing that's changed. I think the right, the right ratio is still very high, right? Like there's still a, an enormous amount of rights per read, but we're starting probably to see that change if people really lean into this pattern.Alessio: Can we talk a little bit about the pricing? I'm curious, uh, because traditionally a database would charge on storage, but now you have the token generation that is so expensive, where like the actual. Value of like a good search query is like much higher because they're like saving inference time down the line.How do you structure that as like, what are people receptive to on the other side too?Simon Hørup Eskildsen: Yeah. I, the, the turbo puffer pricing in the beginning was just very simple. The pricing on these on for search engines before Turbo Puffer was very server full, right? It was like, here's the vm, here's the per hour cost, right?Great. And I just sat down with like a piece of paper and said like, if Turbo Puffer was like really good, this is probably what it would cost with a little bit of margin. And that was the first pricing of Turbo Puffer. And I just like sat down and I was like, okay, like this is like probably the storage amp, but whenever on a piece of paper I, it was vibe pricing.It was very vibe price, and I got it wrong. Oh. Um, well I didn't get it wrong, but like Turbo Puffer wasn't at the first principle pricing, right? So when Cursor came on Turbo Puffer, it was like. Like, I didn't know any VCs. I didn't know, like I was just like, I don't know, I didn't know anything about raising money or anything like that.I just saw that my GCP bill was, was high, was a lot higher than the cursor bill. So Justine and I was just like, well, we have to optimize it. Um, and I mean, to the chagrin now of, of it, of, of the VCs, it now means that we're profitable because we've had so much pricing pressure in the beginning. Because it was running on my credit card and Justine and I had spent like, like tens of thousands of dollars on like compute bills and like spinning off the company and like very like, like bad Canadian lawyers and like things like to like get all of this done because we just like, we didn't know.Right. If you're like steeped in San Francisco, you're just like, you just know. Okay. Like you go out, raise a pre-seed round. I, I never heard a word pre-seed at this point in time.swyx: When you had Cursor, you had Notion you, you had no funding.Simon Hørup Eskildsen: Um, with Cursor we had no funding. Yeah. Um, by the time we had Notion Locke was, Locke was here.Yeah. So it was really just, we vibe priced it 100% from first Principles, but it wasn't, it, it was not performing at first principles, so we just did everything we could to optimize it in the beginning for that, so that at least we could have like a 5% margin or something. So I wasn't freaking out because Cursor's bill was also going like this as they were growing.And so my liability and my credit limit was like actively like calling my bank. It was like, I need a bigger credit. Like it was, yeah. Anyway, that was the beginning. Yeah. But the pricing was, yeah, like storage rights and query. Right. And the, the pricing we have today is basically just that pricing with duct tape and spit to try to approach like, you know, like a, as a margin on the physical underlying hardware.And we're doing this year, you're gonna see more and more pricing changes from us. Yeah.swyx: And like is how much does stuff like VVC peering matter because you're working in AWS land where egress is charged and all that, you know.Simon Hørup Eskildsen: We probably don't like, we have like an enterprise plan that just has like a base fee because we haven't had time to figure out SKU pricing for all of this.Um, but I mean, yeah, you can run turbo puffer either in SaaS, right? That's what Cursor does. You can run it in a single tenant cluster. So it's just you. That's what Notion does. And then you can run it in, in, in BYOC where everything is inside the customer's VPC, that's what an for example, philanthropic does.swyx: What I'm hearing is that this is probably the best CRO job for somebody who can come in and,Simon Hørup Eskildsen: I mean,swyx: help you with this.Simon Hørup Eskildsen: Um, like Turbo Puffer hired, like, I don't know what, what number this was, but we had a full-time CFO as like the 12th hire or something at Turbo Puffer, um, I think I hear are a lot of comp.I don't know how they do it. Like they have a hundred employees and not a CFO. It's like having a CFO is like a runningswyx: business man. Like, you know,Simon Hørup Eskildsen: it's so good. Yeah, like money Mike, like he just, you know, just handles the money and a lot of the business stuff and so he came in and just hopped with a lot of the operational side of the business.So like C-O-O-C-F-O, like somewhere in between.swyx: Just as quick mention of Lucky, just ‘cause I'm curious, I've met Lock and like, he's obviously a very good investor and now on physical intelligence, um, I call it generalist super angel, right? He invests in everything. Um, and I always wonder like, you know, is there something appealing about focusing on developer tooling, focusing on databases, going like, I've invested for 10 years in databases versus being like a lock where he can maybe like connect you to all the customers that you need.Simon Hørup Eskildsen: This is an excellent question. No, no one's asked me this. Um, why lockey? Because. There was a couple of people that we were talking to at the time and when we were raising, we were almost a little, we were like a bit distressed because one of our, one of our peers had just launched something that was very similar to Turbo Puffer.And someone just gave me the advice at the time of just choose the person where you just feel like you can just pick up the phone and not prepare anything. And just be completely honest, and I don't think I've said this publicly before, but I just called Lockey and was like local Lockie. Like if this doesn't have PMF by the end of the year, like we'll just like return all the money to you.But it's just like, I don't really, we, Justine and I don't wanna work on this unless it's really working. So we want to give it the best shot this year and like we're really gonna go for it. We're gonna hire a bunch of people and we're just gonna be honest with everyone. Like when I don't know how to play a game, I just play with open cards and.Lockey was the only person that didn't, that didn't freak out. He was like, I've never heard anyone say that before. As I said, I didn't even know what a seed or pre-seed round was like before, probably even at this time. So I was just like very honest with him. And I asked him like, Lockie, have you ever have, have you ever invested in database company?He was just like, no. And at the time I was like, am I dumb? Like, but I think there was something that just like really drew me to Lockie. He is so authentic, so honest, like, and there was something just like, I just felt like I could just play like, just say everything openly. And that was, that was, I think that that was like a perfect match at the time, and, and, and honestly still is.He was just like, okay, that's great. This is like the most honest, ridiculous thing I've ever heard anyone say to me. But like that, like that, whyswyx: is this ridiculous? Say competitor launch, this may not work out. It wasSimon Hørup Eskildsen: more just like. If this doesn't work out, I'm gonna close up shop by the end of the mo the year, right?Like it was, I don't know, maybe it's common. I, I don't know. He told me it was uncommon. I don't know. Um, that's why we chose him and he'd been phenomenal. The other people were talking at the, at the time were database experts. Like they, you know, knew a lot about databases and Locke didn't, this turned out to be a phenomenal asset.Right. I like Justine and I know a lot about databases. The people that we hire know a lot about databases. What we needed was just someone who didn't know a lot about databases, didn't pretend to know a lot about databases, and just wanted to help us with candidates and customers. And he did. Yeah. And I have a list, right, of the investors that I have a relationship with, and Lockey has just performed excellent in the number of sub bullets of what we can attribute back to him.Just absolutely incredible. And when people talk about like no ego and just the best thing for the founder, I like, I don't think that anyone, like even my lawyer is like, yeah, Lockey is like the most friendly person you will find.swyx: Okay. This is my most glow recommendation I've ever heard.Alessio: He deserves it.He's very special.swyx: Yeah. Yeah. Yeah. Okay. Amazing.Alessio: Since you mentioned candidates, maybe we can talk about team building, you know, like, especially in sf, it feels like it's just easier to start a company than to join a company. Uh, I'm curious your experience, especially not being n SF full-time and doing something that is maybe, you know, a very low level of detail and technical detail.Simon Hørup Eskildsen: Yeah. So joining versus starting, I never thought that I would be a founder. I would start with it, like Turbo Puffer started as a blog post, and then it became a project and then sort of almost accidentally became a company. And now it feels like it's, it's like becoming a bigger company. That was never the intention.The intentions were very pure. It's just like, why hasn't anyone done this? And it's like, I wanna be the, like, I wanna be the first person to do it. I think some founders have this, like, I could never work for anyone else. I, I really don't feel that way. Like, it's just like, I wanna see this happen. And I wanna see it happen with some people that I really enjoy working with and I wanna have fun doing it and this, this, this has all felt very natural on that, on that sense.So it was never a like join versus versus versus found. It was just dis found me at the right moment.Alessio: Well I think there's an argument for, you should have joined Cursor, right? So I'm curious like how you evaluate it. Okay, I should actually go raise money and make this a company versus like, this is like a company that is like growing like crazy.It's like an interesting technical problem. I should just build it within Cursor and then they don't have to encrypt all this stuff. They don't have to obfuscate things. Like was that on your mind at all orSimon Hørup Eskildsen: before taking the, the small check from Lockie, I did have like a hard like look at myself in the mirror of like, okay, do I really want to do this?And because if I take the money, I really have to do it right. And so the way I almost think about it's like you kind of need to ha like you kind of need to be like fucked up enough to want to go all the way. And that was the conversation where I was like, okay, this is gonna be part of my life's journey to build this company and do it in the best way that I possibly can't.Because if I ask people to join me, ask people to get on the cap table, then I have an ultimate responsibility to give it everything. And I don't, I think some people, it doesn't occur to me that everyone takes it that seriously. And maybe I take it too seriously, I don't know. But that was like a very intentional moment.And so then it was very clear like, okay, I'm gonna do this and I'm gonna give it everything.Alessio: A lot of people don't take it this seriously. But,swyx: uh, let's talk about, you have this concept of the P 99 engineer. Uh, people are 10 x saying, everyone's saying, you know, uh, maybe engineers are out of a job. I don't know.But you definitely see a P 99 engineer, and I just want you to talk about it.Simon Hørup Eskildsen: Yeah, so the P 99 engineer was just a term that we started using internally to talk about candidates and talk about how we wanted to build the company. And you know, like everyone else is, like we want a talent dense company.And I think that's almost become trite at this point. What I credit the cursor founders a lot with is that they just arrived there from first principles of like, we just need a talent dense, um, talent dense team. And I think I've seen some teams that weren't talent dense and like seemed a counterfactual run, which if you've run in been in a large company, you will just see that like it's just logically will happen at a large company.Um, and so that was super important to me and Justine and it's very difficult to maintain. And so we just needed, we needed wording for it. And so I have a document called Traits of the P 99 Engineer, and it's a bullet point list. And I look at that list after every single interview that I do, and in every single recap that we do and every recap we end with.End with, um, some version of I'm gonna reject this candidate completely regardless of what the discourse was, because I wanna see people fight for this person because the default should not be, we're gonna hire this person. The default should be, we're definitely not hiring this person. And you know, if everyone was like, ah, maybe throw a punch, then this is not the right.swyx: Do, do you operate, like if there's one cha there must have at least one champion who's like, yes, I will put my career on, on, on the line for this. You know,Simon Hørup Eskildsen: I think career on the line,swyx: maybe a chair, butSimon Hørup Eskildsen: yeah. You know, like, um, I would say so someone needs to like, have both fists up and be like, I'd fight.Right? Yeah. Yeah. And if one person said, then, okay, let's do it. Right?swyx: Yeah.Simon Hørup Eskildsen: Um. It doesn't have to be absolutely everyone. Right? And like the interviews are always the sign that you're checking for different attributes. And if someone is like knocking it outta the park in every single attribute, that's, that's fairly rare.Um, but that's really important. And so the traits of the P 99 engineer, there's lots of them. There's also the traits of the p like triple nine engineer and the quadruple nine engineer. This is like, it's a long list.swyx: Okay.Simon Hørup Eskildsen: Um, I'll give you some samples, right. Of what we, what we look for. I think that the P 99 engineer has some history of having bent, like their trajectory or something to their will.Right? Some moment where it was just, they just, you know, made the computer do what it needed to do. There's something like that, and it will, it will occur to have them at some point in their career. And, uh. Hopefully multiple times. Right.swyx: Gimme an example of one of your engineers that like,Simon Hørup Eskildsen: I'll give an eng.Uh, so we, we, we launched this thing called A and NV three. Um, we could, we're also, we're working on V four and V five right now, but a and NV three can search a hundred billion vectors with a P 50 of around 40 milliseconds and a p 99 of 200 milliseconds. Um, maybe other people have done this, I'm sure Google and others have done this, but, uh, we haven't seen anyone, um, at least not in like a public consumable SaaS that can do this.And that was an engineer, the chief architect of Turbo Puffer, Nathan, um, who more or less just bent this, the software was not capable of this and he just made it capable for a very particular workload in like a, you know, six to eight week period with the help of a lot of the team. Right. It's been, been, there's numerous of examples of that, like at, at turbo puff, but that's like really bending the software and X 86 to your will.It was incredible to watch. Um. You wanna see some moments like that?swyx: Isn't that triple nine?Simon Hørup Eskildsen: Um, I think Nathan, what's calledAlessio: group nine, that was only nine. I feel like this is too high forSimon Hørup Eskildsen: Nathan. Nathan is, uh, Nathan is like, yeah, there's a lot of nines. Okay. After that p So I think that's one trait. I think another trait is that, uh, the P 99 spends a lot of time looking at maps.Generally it's their preferred ux. They just love looking at maps. You ever seen someone who just like, sits on their phone and just like, scrolls around on a map? Or did you not look at maps A lot? You guys don't look atswyx: maps? I guess I'm not feeling there. I don't know, butSimon Hørup Eskildsen: you just dis What about trains?Do you like trains?swyx: Uh, I mean they, not enough. Okay. This is just like weapon nice. Autism is what I call it. Like, like,Simon Hørup Eskildsen: um, I love looking at maps, like, it's like my preferred UX and just like I, you know, I likeswyx: lotsAlessio: of, of like random places, soswyx: like,youswyx: know.Alessio: Yes. Okay. There you go. So instead of like random places, like how do you explore the maps?Simon Hørup Eskildsen: No, it's, it's just a joke.swyx: It's autism laugh. It's like you are just obsessed by something and you like studying a thing.Simon Hørup Eskildsen: The origin of this was that at some point I read an interview with some IOI gold medalistswyx: Uhhuh,Simon Hørup Eskildsen: and it's like, what do you do in your spare time? I was just like, I like looking at maps.I was like, I feel so seen. Like, I just like love, like swirling out. I was like, oh, Canada is so big. Where's Baffin Island? I don't know. I love it. Yeah. Um, anyway, so the traits of P 99, P 99 is obsessive, right? Like, there's just like, you'll, you'll find traits of that we do an interview at, at, at, at turbo puffer or like multiple interviews that just try to screen for some of these things.Um, so. There's lots of others, but these are the kinds of traits that we look for.swyx: I'll tell you, uh, some people listen for like some of my dere stuff. Uh, I do think about derel as maps. Um, you draw a map for people, uh, maps show you the, uh, what is commonly agreed to be the geographical features of what a boundary is.And it shows also shows you what is not doing. And I, I think a lot of like developer tools, companies try to tell you they can do everything, but like, let's, let's be real. Like you, your, your three landmarks are here, everyone comes here, then here, then here, and you draw a map and, and then you draw a journey through the map.And like that. To me, that's what developer relations looks like. So I do think about things that way.Simon Hørup Eskildsen: I think the P 99 thinks in offs, right? The P 99 is very clear about, you know, hey, turbo puffer, you can't run a high transaction workload on turbo puffer, right? It's like the right latency is a hundred milliseconds.That's a clear trade off. I think the P 99 is very good at articulating the trade offs in every decision. Um. Which is exactly what the map is in your case, right?swyx: Uh, yeah, yeah. My, my, my world. My world.Alessio: How, how do you reconcile some of these things when you're saying you bend the will the computer versus like the trade

We push past rankings and traffic to map the real skills SEOs need to influence AI answers. Duane Forrester explains the machine layer, vector embeddings, semantic density, and why structured data is a must if you want reliable retrieval.• AI reshapes marketing and elevates SEO's role across the business• Good SEO foundations as the prerequisite for AI performance• Writing for chunks with high semantic density• Structured data and entity clarity to validate facts• Vector embeddings as the new alignment target• KPIs beyond rankings: retrieval confidence and zero‑click presence• Why LLMs.txt lacks adoption and what matters instead• Practical tracking of AI answers and trend analysis• The gap between search engines and LLM information retrieval• Learning paths to keep pace with faster platform updatesGuest Contact Information: Website: duaneforrester.comLinkedIn: linkedin.com/in/dforresterTwitter/X: x.com/DuaneForresterMore from EWR and Matthew:Leave us a review wherever you listen: Spotify, Apple Podcasts, or Amazon PodcastFree SEO Consultation: ewrdigital.com/discovery-callWith over 5 million downloads, The Best SEO Podcast has been the go-to show for digital marketers, business owners, and entrepreneurs wanting real-world strategies to grow online. Now, host Matthew Bertram — creator of the LLM Visibility Stack™, and Lead Strategist at EWR Digital — takes the conversation beyond traditional SEO into the AI era of discoverability. Each week, Matthew dives into the tactics, frameworks, and insights that matter most in a world where search engines, large language models, and answer engines are reshaping how people find, trust, and choose businesses. From SEO and AI-driven marketing to executive-level growth strategy, you'll hear expert interviews, deep-dive discussions, and actionable strategies to help you stay ahead of the curve. Find more episodes here: youtube.com/@BestSEOPodcastbestseopodcast.combestseopodcast.buzzsprout.comFollow us on:Facebook: @bestseopodcastInstagram: @thebestseopodcastTiktok: @bestseopodcastLinkedIn: @bestseopodcastConnect With Matthew Bertram: Website: www.matthewbertram.comInstagram: @matt_bertram_liveLinkedIn: @mattbertramlivePowered by: ewrdigital.comSupport the show

Send us a textPeaches runs a solo Daily Drop Ops Brief and cuts through a wide slate of military news with zero patience for nonsense. From the Army's recruiting age creeping up and a 10th Mountain deployment to the Middle East, to a soldier sentenced for murder at Fort Novosel, this episode stays grounded in accountability and reality. Peaches breaks down why the Army paused the soldier-built VECTOR data tool, what Navy pilots flying Air Force F-35As actually learn from it, and why a former Marine drill instructor's post-release arrest is indefensible. The Air Force brings back no-notice ORIs, lessons learned from Midnight Hammer drive comms upgrades, Space Force stands up a Northern Command component, the Coast Guard responds to deadly maritime incidents, SECDEF Hegseth takes aim at legacy procurement at Blue Origin, and the White House pushes to end the government shutdown. Context over outrage—again.⏱️ Timestamps: 00:00 Ones Ready intro and Daily Drop kickoff 01:10 Hoist Hydration sponsor 02:30 OTS Alabama 2026 rundown 04:40 Army recruit age increase explained 05:10 10th Mountain Division Middle East deployment 05:45 VECTOR AI tool suspended pending review 07:10 Soldier sentenced for murder at Fort Novosel 08:10 Navy pilots fly Air Force F-35A jets 09:30 Marine drill instructor arrested after early release 10:00 Air Force reinstates no-notice ORIs 11:20 Comms lessons from Midnight Hammer 12:45 Space Force stands up NORTHCOM component 13:20 Coast Guard rescues 27 mariners near Galapagos 14:00 Lily Jean sinking investigation 14:50 SECDEF Hegseth criticizes legacy procurement 15:50 POTUS urges end to government shutdown 16:40 Counter-narcotics strikes continue 17:00 Iran rhetoric and regional posturing 17:40 Russian cargo aircraft arrives in Cuba 18:30 Wrap-up and final thoughts