Podcasts about engineers

From 03/19 Hour 2: The Sports Junkies react to Roger The Engineer's March Madness bracket.

In this episode, Alex catches up on some of the latest projects he's been working on between using Space Internet (Starlink) and the testing on the 3D Printed Starlink mount. The topic of "rethinking failure" has continued to stay in the zeitgiest after the new NASA Artemis plan. As a classically trained Aerospace Engineer, Alex thought it made sense to dive into this idea more. As a maker at heart, failure is thought of as a necessity in development so that you LEARN quickly. For the "classic" way of engineering that I was taught, failure was seen differently... Some 3D printing & Space News updates to start, a dive into what "Space Internet" has been like, and then a quick trip to rethinking "failure" as we look towards NASA's future and the eventual Artemis 2 launch in April (hopefully). Thanks for joining us 3D Printing Playlist for Starlink Deck Mount Testing: https://www.youtube.com/watch?v=5nao06nbw5U&list=PLu6GQO_0j48-zpTNyhsOzUJAR8vVo6_TJ&index=7 We'd like to thank our sponsors: AG3D Printing (go to ag3d-printing.com to learn more & start 3D printing today!) Support the podcast: • Buy a 3D printed gift from our shop - http://ag3dprinting.etsy.com Today In Space Merch: James Webb Space Telescope Model (3DPrinted) https://ag3dprinting.etsy.com/listing/1839142903 SpaceX Starship-Inspired Rocket Pen (3DPrinted) https://ag3dprinting.etsy.com/listing/1602850640  • Get a free quote on your next 3D printing project at http://ag3d-printing.com • Donate at todayinspace.net

Ever wondered why we lash out, shut down, or spiral emotionally, even when we don't want to? On this episode of Getting Better, JVN teams up with psychologist and author Dr. Nicole LePera (The Holistic Psychologist) to dive deep into inner child healing, parts work, and the shocking truth behind our nervous system's reactions. Dr. LePera reveals how our past molds our emotions, why connection is our biological imperative, and how to become your own adult parent. JVN opens up about their own "parts," and together they dissect black-and-white thinking, fear, and emotional overwhelm, uncovering real-world strategies to break free! If healing has ever felt messy, scary, or downright nonlinear, this conversation may help you truly "getting better." Dr. Nicole LePera's new book Reparenting the Inner Child: The New Science of Our Oldest Wounds and How to Heal Them is out March 24th. Full Getting Better Video Episodes now available on YouTube.  Follow Dr. Nicole LePera on Instagram @the.holistic.psychologist Follow us on Instagram @gettingbetterwithjvn Jonathan on Instagram @jvn Executive Producer, Chris McClure Producer, Editor & Engineer is Nathanael McClure Production support from Chad Hall Our theme music is also composed by Nathanael McClure. Check out the JVN Patreon for exclusive BTS content, extra interviews, and much much more - check it out here: www.patreon.com/jvn  Curious about bringing your brand to life on the show? Email podcastadsales@sonymusic.com. Learn more about your ad choices. Visit podcastchoices.com/adchoices

For more than 35 years, Frank has traveled the world interviewing remarkable people and capturing their stories on film. In this series, he introduces audiences to fascinating individuals whose lives and experiences deserve to be heard.Frank and Tom look back on their long history working together in the film world, including their collaboration on the award winning film The Basket. They also share memories from early productions, creative partnerships, and the filmmaking community that brought them together decades ago.Tom brings humor, honesty, and a few surprising stories to the conversation, proving that sometimes the most interesting people are the ones you've never heard of.

Kürzlich war Bundeskanzler Friedrich Merz zu Besuch in China, um auf Xi Jinping zu treffen, die Handelsbeziehungen zu verbessern und um sich einen Eindruck von der Weltmacht zu verschaffen. In Vorbereitung auf die Reise las er, wie vorab bekannt wurde, ein Buch: „Breakneck. China's Quest to Engineer the Future“ von Dan Wang.Der Autor, der in China geboren wurde und zuletzt die Covid-Jahre dort verbracht hat, präsentiert eine diskussionswürdige These: Während die amerikanische Wirtschaft und Politik von Anwälten bestimmt wird, regieren in China die Ingenieure. Nach Maos Tod setzt Deng gezielt auf Ingenieure in der Partei, um ein modernes China zu schaffen. Das bringt nicht nur Effizienz, sondern auch Probleme mit sich.In der neuen Folge von „Wohlstand für Alle“ diskutieren Ole Nymoen und Wolfgang M. Schmitt über „Breakneck“ und die Frage, was Friedrich Merz daraus gelernt hat. Als er zurückkehrte, erklärte er, die Deutschen müssten mehr arbeiten. Verbindet Merz etwa ideologisch etwas mit Xi? Literatur: Dan Wang: „Breakneck. China's Quest to Engineer the Future“, W. W. Norton & Company.Unsere Zusatzinhalte könnt ihr bei Apple Podcasts, Steady und Patreon hören. Vielen Dank!Apple Podcasts: https://podcasts.apple.com/de/podcast/wohlstand-f%C3%BCr-alle/id1476402723Patreon: https://www.patreon.com/oleundwolfgangSteady: https://steadyhq.com/de/oleundwolfgang/aboutTermine:Am 19. März ist Ole auf der Leipziger Buchmesse:https://www.leipziger-buchmesse.de/pco/de/buchmesse/69440335a4b3dfc56c0919b7Am 20. März ist Ole in Basel:https://mitte.ch/programm/um-politics-talks-mit-ole-nymoen/Am 24.3. sind wir in Bielefeld https://www.instagram.com/astaunibielefeld/p/DVQ-z4gjF-Q/Am 25.3. ist Wolfgang in Berlin:https://lfbrecht.de/events/2026-03-25/Am 26.3. ist Wolfgang in Hamburg:https://hamburgliest.de/programm/#elfenbeinturm-und-barrikade-2Am 11. 4. sind Ole und Wolfgang in Hamburg:https://tickets.centralkomitee.de/product/91257/wolfgang-m-schmitt-ole-nymoen-centralkomitee-hamburg-am-11-04-2026

On today’s news roundup we assess the White House’s new US cyber strategy (bellicose, bombastic, and boiler-plate), discuss a cyberattack attributed to Iran that used Windows to wipe thousands of devices, and dig into a Microsoft update on Entra passkeys. JJ isn’t impressed with new research that bypasses Wi-Fi client isolation, corporate spyware gets a... Read more »

On today’s news roundup we assess the White House’s new US cyber strategy (bellicose, bombastic, and boiler-plate), discuss a cyberattack attributed to Iran that used Windows to wipe thousands of devices, and dig into a Microsoft update on Entra passkeys. JJ isn’t impressed with new research that bypasses Wi-Fi client isolation, corporate spyware gets a... Read more »

Jessica Campbell is a hockey coach with the Seattle Kraken, and the first full-time female assistant coach in NHL history to work behind the bench. In this episode, Jessica and Adam reflect on the lessons from being the first or only girl on a team, break down Jessica's three core tenets of leadership, and discuss different ways of delivering effective feedback and tough love to help individuals and teams reach their full potential.Host & GuestAdam Grant (Instagram: @adamgrant | LinkedIn: @adammgrant | Website: https://adamgrant.net/)Jessica Campbell (Instagram: @soupy08 | Website: https://www.jessicaecampbell.com/)ReThinking is produced by Cosmic Standard. Our Senior Producer is Jessica Glazer, our Engineer is Aja Simpson, our Technical Director is Jacob Winik, and our Executive Producer is Eliza Smith.For the full text transcript, visit ted.com/podcasts/rethinking-with-adam-grant-transcriptsLearn more about our flagship conference happening this April at attend.ted.com/podcast Hosted on Acast. See acast.com/privacy for more information.

This week, we're talking: Hot & Healed Comedy Tour, Double Take Trend, Reba on TikTok, Melodyne vs. Autotune, Candace Cameron-Bure Attending Demonic Sex Parties and telling everyone about it, St. Patrick's Day Spelling Bee, Nick Fuentes on Women, Katie Couric's “use it or lose it” Reporting, CBS, Save America Act,  to have a kid or not to have a kid, and protein pop-tarts.  Get tix to the Hot & Healed Comedy Tour here.    The Monday Edit, now on YouTube!  Check out the JVN Patreon for exclusive content, bonus episodes, and more! www.patreon.com/jvn  Follow us on Instagram @gettingbetterwithjvn Jonathan on Instagram @jvn and senior producer Chris @amomentlikechris  Executive Producer, Chris McClure Producer, Editor & Engineer is Nathanael McClure Production support from Chad Hall Our theme music is also composed by Nathanael McClure.Curious about bringing your brand to life on the show? Email podcastadsales@sonymusic.com. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Alan interviews Dave Dussault. Dave Dussault grew up loving cold chilled coffee - except the flavor was lacking. So, he invented a way to snap chill hot coffee - for a tastier cold coffee. Today, his Snapchill coffee sells all over the U.S. through 200 roasters - allowing millions to experience full flavored cold coffee. Make sure to subscribe to the podcast at Apple Podcasts, or wherever you get your podcasts, so you won't miss a single episode. Website: www.Snapchill.com

Business success is often portrayed as the product of talent, hard work, and persistence. But what if success could be analyzed — and improved — using the logic of probability? Kyle Austin Young, a sought-after strategy consultant, maintains that most goals — whether launching a product, raising funds, or publishing a book — can be analyzed and improved by understanding the odds behind them. Kyle is the author of Success is a Numbers Game: Achieve Bigger Goals by Changing the Odds, a fresh and insightful exploration of goal-setting and goal-achieving. Drawing from his consulting work with entrepreneurs, nonprofits, and business leaders, Kyle reveals a practical framework he calls "probability hacking." The concept is simple but powerful: break ambitious goals into the individual steps required for success, estimate the likelihood of attaining each progression, and then deliberately improve the odds. Listeners will also learn why traditional "think positive" advice can sometimes sabotage success. Instead, Kyle advocates "think negative"— objectively identifying risks and obstacles so they can be reduced or eliminated. The odds are excellent that this episode will change the way you view business opportunity and risk. Monday Morning Radio is hosted by the father-son duo of Dean and Maxwell Rotbart. Photo: Kyle Austin YoungPosted: March 16, 2026 Monday Morning Run Time: 46:26  Episode: 14.37 Coming April 2026: All You Can Eat Business Wisdom: Second Helpings

Hygiene production problems don't start this week — they were built months ago through leading indicators you can track and influence. In this episode, Kirk Behrendt sits down with ACT Dental coach Ariel Siegel to explain why hygiene production is a lagging indicator and how to improve it by focusing on reappointment rate, perio diagnosis, and perio acceptance. You'll learn what hygiene breakdown looks like in real time, what predictable stability looks like when systems are working, and the simplest numbers to start tracking today so you can engineer future results instead of reacting to past ones.Listen to Episode 1021 of The Best Practices Show!Main TakeawaysHygiene production is a lagging indicator that is built three to six months before the appointment through daily behaviors and tracking.Reviewing last week or last month's numbers shows where you were, but it doesn't give you a chance to change those results now.Reappointment rate, perio diagnosis, and perio acceptance are leading indicators that drive future hygiene production.When hygiene is built poorly, teams scramble to rebuild schedules, cancellations feel disruptive, and there is little depth in future hygiene.Perio diagnosis will vary by provider when the department lacks alignment, consistent protocols, and consistent verbal skills.Tracking real reappointment data (patients seen vs. patients scheduled) immediately increases awareness and improves performance.Focusing on one KPI for 30 days creates clarity for the team and compounds into stronger, more predictable hygiene production.Snippets:00:00 Hygiene production problems are built months before today.02:16 Hygiene production is a lagging indicator driven by leading indicators.04:22 What it looks like when hygiene is built wrong: scrambling, inconsistency, and a weak schedule.06:33 What it looks like when you build hygiene right: stable, predictable hygiene three to six months out.09:23 Engineer hygiene production by tracking reappointment, perio diagnosis, and perio acceptance.11:16 The actionable first step: track patients seen vs. patients reappointed.13:08 Use perio diagnosis by provider to find alignment gaps and improve consistency.15:49 Pick one KPI at a time to create focus and compounding improvement.17:13 Data removes emotion and lets the team solve the problem together.18:35 New BPA resources added for hygiene systems and metrics.Guest Bio/Guest Resources:Ariel has a master's in healthcare administration and several years of dental experience in all aspects of the administrative roles within the dental office. Her passion is to work with dental teams to empower team members to realize their full potential in order to better serve patients, improve office systems to ensure a well-functioning team/office, and to help everyone have fun in the process!Resources mentioned in the episode:Best Practices Association (BPA) resources: https://www.actdental.com/free-resources/More Helpful Links for a Better Practice & a Better Life:The Best Practices Show: https://www.actdental.com/podcast/Best Practices Association: https://www.actdental.com/bpaUpcoming Events & Workshops: https://www.actdental.com/events/Smile Source: https://www.smilesource.com/Subscribe on Apple Podcasts: https://podcasts.apple.comSubscribe on Spotify: https://open.spotify.com

This week on History's Greatest Idiots (featuring Patreon member Ben Markwart), we explore the Chernobyl nuclear disaster: the catastrophic 1986 explosion that killed dozens, displaced 350,000 people, cost 700 billion dollars, and helped collapse the Soviet Union.The Safety Test That Wasn't Very SafeOn 26th April 1986 at 1:23 AM, Reactor 4 at the Chernobyl Nuclear Power Plant near Pripyat, Ukraine, exploded during a safety test. Engineers disabled the emergency core cooling system, ran the RBMK reactor at just 7% power (unstable below 20%), and withdrew most control rods. Within seconds, power surged to over 100 times normal output. Two explosions blew the 2,000 ton reactor lid off and ignited the graphite moderator, which burned for nine days, releasing massive radioactive contamination across Europe.The RBMK Reactor DesignThe Soviet RBMK reactor had catastrophic design flaws operators weren't informed about. It featured a positive void coefficient (coolant loss increased power), control rods with graphite tips that briefly increased reactivity when inserted, and no Western-style containment building. Deputy Chief Engineer Anatoly Diatlov, in charge during the accident, genuinely believed the reactor was safe.The Cover-up and Sweden's DiscoveryFor 36 hours, Soviet officials said nothing whilst Pripyat's 50,000 residents went about their normal lives at radiation levels 600,000 times background levels. On 28th April, radiation alarms triggered at Sweden's Forsmark Nuclear Power Plant, over 1,000 kilometres away. Only after Swedish authorities announced a Soviet nuclear accident did the USSR reluctantly admit to Chernobyl. Gorbachev didn't issue a statement until 14th May, 18 days later, calling it a "misfortune" and attacking Western media as spreading "malicious lies."The LiquidatorsFirst responders weren't told they were confronting an exposed reactor core. Firefighters handled radioactive graphite with ordinary equipment. 28 died within four months from acute radiation syndrome. Firefighter Vasily Ignatenko, aged 25, received 1,300 rem and died on 13th May 1986. About 600,000 liquidators cleaned up the site. Called "bio-robots," they shovelled radioactive debris from the roof in 40-second shifts because robots were destroyed by radiation. At least 1,800 children developed thyroid cancer from radioactive iodine-131.How Chernobyl Collapsed the Soviet UnionGorbachev later stated Chernobyl was "perhaps the real cause of the collapse of the Soviet Union," more than perestroika, glasnost, Afghanistan, or the Berlin Wall. The disaster shattered public trust, contradicting glasnost's promise of openness. Combined with Afghanistan casualties (15,000 troops), economic stagnation (2.6% GDP growth), and military spending (16% of GNP), Chernobyl's 18 billion rouble cost broke the system. The Berlin Wall fell in November 1989. The USSR dissolved in December 1991, less than six years after Chernobyl.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.patreon.com/HistorysGreatestIdiots⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/historysgreatestidiots⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://buymeacoffee.com/historysgreatestidiots⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Artist: Sarah Chey⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.fiverr.com/sarahchey⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

How do you build trust in a business environment where security reviews, compliance demands, and vendor risk checks can slow everything down just when companies are trying to move faster? In this episode, I sit down with Adam Markowitz, CEO and co-founder of Drata, to talk about why trust has become one of the most important business conversations in tech. Adam brings a fascinating perspective to the table. Before building Drata, he worked on NASA's space shuttle program, and today he leads a company that has grown rapidly by helping organizations rethink compliance, governance, risk, and assurance through automation and AI. What stood out to me in this conversation was how clearly he framed the real issue. Compliance may have been where many companies started, but trust is the bigger story. In a world shaped by cloud services, third party vendors, and constant security scrutiny, old point in time audits and reactive processes are starting to look painfully outdated. We also talked about Drata's acquisition of SafeBase and what that says about the direction of the market. Adam explained how security and GRC teams have too often been treated as back office functions, expected to stay quiet and keep the company out of trouble. But he sees things very differently. He argues that these teams can actively help close deals, accelerate revenue, and remove friction from the buying process. That shift matters because trust now plays a direct role in business growth. If customers can quickly get answers to security questions and understand how a company manages risk, sales cycles move faster and security teams stop being bottlenecks at the final stage of a deal. Another part of the conversation that really stayed with me was Adam's view on AI. He sees it as both a tailwind and a test. AI is helping automate highly manual GRC workflows, improve continuous compliance monitoring, and support newer frameworks tied to AI risk itself. At the same time, he is realistic about the pressure this puts on businesses. AI may introduce fresh concerns, but it also shines a harsher light on issues that have been around for years, things like access creep, weak controls, and data integrity problems. That honesty gave this discussion a lot of weight because it moved beyond hype and focused on what companies actually need to do. We also touched on Drata's momentum as a business, from opening a new San Francisco headquarters to expanding globally and moving further into the enterprise market. But even there, Adam kept coming back to culture, discipline, and a deep understanding of the customer problem. For me, that was the thread running through the whole episode. Trust is not a side issue. It is part of how modern companies grow, compete, and prove they can be relied on. If your business still sees compliance as a checkbox exercise or a cost center, this conversation will give you plenty to think about. Where do you see the relationship between trust, security, and growth heading next, and what did this episode make you question about the way your own organization handles compliance? Share your thoughts with me.

America Out Loud PULSE with Dr. Randall Bock – Iran lives a paradox: a clerical regime enforcing ideological rule and a vibrant society striving for modern life. Engineers, students, and entrepreneurs push forward while religious authorities guard revolutionary power. The tension between political Islam and an industrious intelligentsia raises a larger question about faith, governance, and Iran's future trajectory...

Alexis Sikorsky is a strategic advisor to founders who want to scale fast and exit strong, after building and selling his Switzerland-based banking software company, New Access, in a private equity deal worth over $100M. Drawing on decades of hard-won experience (including painful early failures, a 75% revenue collapse in one day, and a long post-crisis grind), he now helps £5–20M+ revenue businesses design exits instead of hoping for them. In his book Cashing Out: The Business Owner's Guide to Selling to Private Equity, Alexis introduces the APEX methodology, a practical roadmap for founders who want clarity, cashflow, and a life-changing deal beyond their business. On this episode we talk about: Why Alexis calls his early ventures “failures” and how those lessons funded a $100M+ win later The 2008 financial crisis, losing 75% of revenue in a day, and rebuilding New Access without pivoting His grandfather's trade wisdom and the simple “sell higher than you buy” rule most founders ignore Why raising VC money is usually a sign of commercial failure, not success The APEX methodology for planning and executing a private equity exit (from assessment to “dressing the bride”) Top 3 Takeaways Failure is the tuition you pay for wisdom: Alexis estimates the “cost” of his mistakes at 50 million and five years, and he uses that lens to help founders avoid repeating them. Profit is not optional if you want optionality: you must build a business where costs stay below revenue, instead of relying on endless fundraising to plug operational holes. A premium exit is engineered, not accidental: knowing your goal (lifestyle vs. exit, 100M vs. 1B), tracking real-time numbers, protecting your USP, and becoming “private equity ready” 18–24 months ahead are non-negotiable. Notable Quotes “I have a 100% success-rate, no-failure strategy: just don't try anything.” “Raising money is very often a commercial failure—your company isn't good enough yet to be profitable.” “We're not wealthy enough to buy cheap. If you can't afford it, don't buy it—but don't buy the cheap version either.” Connect with Alexis Sikorsky: LinkedIn: https://www.linkedin.com/in/alexis-sikorsky-consulting Website / Book: https://www.asikorsky.com/my-book (Cashing Out: The Business Owner's Guide to Selling to Private Equity) Travis Makes Money is made possible by High Level – the All-In-One Sales & Marketing Platform built for agencies, by an agency. Capture leads, nurture them, and close more deals—all from one powerful platform. Get an extended free trial at gohighlevel.com/travis. Learn more about your ad choices. Visit megaphone.fm/adchoices

America Out Loud PULSE with Dr. Randall Bock – Iran lives a paradox: a clerical regime enforcing ideological rule and a vibrant society striving for modern life. Engineers, students, and entrepreneurs push forward while religious authorities guard revolutionary power. The tension between political Islam and an industrious intelligentsia raises a larger question about faith, governance, and Iran's future trajectory...

Mike Stephen learns about inspiring the next generation of civil engineers from Pinpoint Scholars Foundation founder & president Michael Bempah, replays his visit to The Levee bar in the Hermosa neighborhood, and discovers the Secret History of local saxman Ed Wilkerson Jr.

Mike Matthews investigates the fascinating news from the week and Mike answers what is happening in the odd world of happiness. Join Mike as he podcasts live from Café Anyway in podCastro Valley with Chely Shoehart, Floyd the Floorman, and John Deer the Engineer. Next show Mike Talks to Benita, the Disgruntled Fiddle Player, and the Brewmaster.

Mike Matthews investigates the fascinating news from the week and Mike answers what is happening in the odd world of happiness. Join Mike as he podcasts live from Café Anyway in podCastro Valley with Chely Shoehart, Floyd the Floorman, and John Deer the Engineer. Next show Mike Talks to Benita, the Disgruntled Fiddle Player, and the Brewmaster.

How do you turn trillions of user interactions into meaningful decisions without drowning in data? In this episode of Tech Talks Daily, I sit down with Todd Olson, co-founder and CEO of Pendo, to talk about the future of product-led organizations and why AI is reshaping how software companies grow, build, and compete. Pendo tracks trillions of product usage events to help organizations understand how customers actually interact with their software. That level of data sounds powerful, but it also raises a challenge many teams face today. How do you turn massive data sets into clear signals that teams can act on without falling into analysis paralysis? Todd explains how Pendo approaches this problem by organizing product data around real user journeys, feature adoption, and areas where people drop off. Instead of leaving teams buried in dashboards, the goal is to surface insights that matter. Increasingly, AI is helping by acting as a kind of embedded analyst that highlights the patterns product teams should focus on. Our conversation also revisits the idea behind Todd's book, The Product-Led Organization. When it was published around the time of the pandemic, it argued that great products should do much of the heavy lifting traditionally done by sales or support teams. Looking back now, Todd believes the core idea remains intact. AI simply accelerates the model by allowing companies to experiment faster and scale product-driven experiences with far fewer people. But that shift is also creating tension in the software industry. We talk about the so-called reckoning in SaaS economics and the growing debate around whether AI will make traditional software companies obsolete. Todd offers a more measured perspective. While AI allows anyone to prototype software quickly, the companies that survive will still be the ones solving difficult problems, navigating compliance requirements, and building products that customers trust. Another theme we explore is geography and innovation. Pendo is headquartered in Raleigh, North Carolina, far from the usual coastal tech hubs. Todd shares how building outside Silicon Valley has shaped the company's culture, talent strategy, and mindset. There are advantages to being close to the center of the AI boom, but there is also value in building away from the echo chamber. We also spend time unpacking the rise of AI-assisted development and the trend many people call "vibe coding." Todd believes AI will dramatically reshape product teams, but he also pushes back against the idea that humans will disappear from the development process. Engineers will still need to review code, teach AI systems best practices, and ensure security and reliability. One of the most interesting moments in our conversation comes near the end when Todd shares a belief that originality will become one of the most valuable assets in the age of AI. As automated content and automated code become easier to generate, he believes people will increasingly value craft, taste, and original thinking. So in a world where AI can generate almost anything with a prompt, the real question becomes far more human. What problems are actually worth solving? If you care about the future of software, product strategy, and how AI is reshaping the economics of building companies, this is a conversation that offers plenty to think about. And after listening, I would love to hear your perspective. As AI becomes embedded in every product and workflow, do you believe originality and craft will become the true differentiators in the software industry?

Ocean microbes quietly power the planet. In this episode, we explore the microscopic organisms that regulate Earth's climate, produce much of the oxygen we breathe, and move enormous amounts of carbon through the ocean every day. These invisible life forms are not just background players in the ocean system; they are central to how the planet works. Synthetic biology is now pushing this idea even further. Dr. José Ángel Moreno-Cabezuelo, a synthetic biologist working in Oxford, is engineering ancient microorganisms called cyanobacteria to capture carbon dioxide using sunlight and biology. His work shows how living systems could become part of the climate solutions we desperately need. Science communication is another major theme of this conversation. After years working inside the scientific system, Dr. Moreno-Cabezuelo began questioning why so much scientific knowledge fails to connect with society. Through his book Heartbeats of Consciousness, he explores the intersection of biology, neuroscience, philosophy, and the human experience, asking a powerful question: if science understands life so well, why does it still struggle to help us understand how to live it? Listen to learn how microbes shape our planet, how biotechnology may help tackle climate change, and why clarity in science might be one of the most important tools we have for protecting the ocean. Website: https://drjoseangelmoreno.com/en/ LinkedIn: www.linkedin.com/in/josé-ángel-moreno-cabezuelo-phd Instagram: @joseangelmc_

Send a textJacob Broadbent didn't come from the typical consulting pipeline.He came from engineering – and still landed a PwC offer.In this episode, Jacob breaks down the exact moves that helped him make the pivot: how he positioned his technical background as a strength, got more comfortable networking, and built the case prep skills that actually moved the needle.In this episode:How Jacob turned an engineering background into an advantageThe networking approach that helped him stand out with firmsWhy case prep changed more than just his interview performanceThe mindset shifts that helped him navigate recruiting with confidenceIf you're coming from engineering or any non-traditional background, this conversation is proof that you do not need the “perfect” consulting resume to win.Resources:Join the Black Belt program for engineers breaking into consultingSee upcoming consulting application deadlinesBooks Mentioned:Never Split the Difference – Chris VossThe 2-Hour Job Search – Steve DaltonThe 20-Minute Networking Meeting – Marcia Ballinger & Nathan PerezMBB Undergrad Timelines Are This MonthApplication deadlines are the earliest we've ever seen; join Black Belt for an accelerated, MBB-led prep programConnect With Management Consulted Schedule free 15min consultation with the MC Team. Watch the video version of the podcast on YouTube! Follow us on LinkedIn, Instagram, and TikTok for the latest updates and industry insights! Join an upcoming live event - case interviews demos, expert panels, and more. Email us (team@managementconsulted.com) with questions or feedback.

In this insightful episode, host Ashish Kothari sits down with Eleanor Allen—a powerhouse leader who has navigated the peaks of the engineering world, led global social impact as the CEO of Water for People, and served as CEO of B Lab. Eleanor shares her "accidental" discovery of inner development and how moving from a rigid, "controlled" masculine leadership style to one of vulnerability and radical self-awareness transformed not just her life, but her global organization. This conversation is a must-listen for leaders who feel they must carry the world on their shoulders and are looking for a more sustainable, joyful, and high-performance way to lead.Main Topics CoveredThe Leader's Mirror: Why an organization's state of being is a direct reflection of its leader's personal flourishing.The Engineer's Armor: Eleanor's journey from a "got all the answers" professional upbringing to embracing vulnerability.Leading Through Crisis: How the lack of a "COVID playbook" forced a shift toward asking for help and experimenting.Head, Heart, and Plate: A simple, powerful meeting ritual to build connective tissue and psychological safety in teams.The Drama Triangle & Responsibility: Understanding your share of responsibility in workplace conflict.For-Profit vs. Non-Profit Flourishing: Common drivers and unique stressors (like the "philanthropy myth") in different sectors.The Flourishing Leader Summit: A preview of the upcoming Denver/Boulder intensive on April 29th.Key TakeawaysSelf-Care is Organizational Care: Leaders stuck in "survival mode" cannot create thriving ecosystems; your personal well-being is a strategic priority, not an indulgence.Vulnerability is a Catalyst: Admitting you don't have the answers during uncertain times invites the team to step up, innovate, and co-create solutions.Mattering and Appreciation: The universal need to feel valued is often the simplest and most effective lever for increasing engagement in any sector.Measure What Matters: Move beyond superficial "wellness perks" and start measuring root causes like absenteeism, financial stress, and psychological safety.The Power of Slower: Being "calmer" and more intentional in decision-making leads to better outcomes and more trusting team dynamics.

In Episode 320, Sean and Andy talk with Sage Tichenor, best known as front of house engineer for violinist and songwriter Lindsey Stirling, for a wide-ranging chat about all things live audio. Sage talks about migrating and selecting a console platform for her shows, what it's like mixing a NAMM showcase for a manufacturer, working with a wide range of artists from bluegrass to pop-classical/EDM crossover, and more. Plus plugins, snare sounds that don't suck, and more…nothing's off the table!Sage is a freelance touring FOH engineer and classically trained flautist. In December 2018, she graduated from Middle Tennessee State University with a B.M in Music Industry and a B.S. in Audio Production. While in school, she began working at a major local rehearsal studio, which she continued to pursue following graduation. She started touring as a FOH engineer in the fall of 2021 with country artist Riley Green.Episode Links:Lindsey Sterling On YouTube“Cadillacin'” by The Cadillac ThreeProfile: Sage TichenorSage's SoundGirls BlogEpisode 320 TranscriptConnect with the community on the Signal To Noise Facebook Group and Discord Server. Both are spaces for listeners to create to generate conversations around the people and topics covered in the podcast — we want your questions and comments!Also please check out and support The Roadie Clinic, Their mission is simple. “We exist to empower & heal roadies and their families by providing resources & services tailored to the struggles of the touring lifestyle.”The Signal To Noise Podcast on ProSoundWeb is co-hosted by pro audio veterans Andy Leviss and Sean Walker.Want to be a part of the show? If you have a quick tip to share, or a question for the hosts, past or future guests, or listeners at home, we'd love to include it in a future episode. You can send it to us one of two ways:1) If you want to send it in as text and have us read it, or record your own short audio file, send it to signal2noise@prosoundweb.com with the subject “Tips” or “Questions”2) If you want a quick easy way to do a short (90s or less) audio recording, go to https://www.speakpipe.com/S2N and leave us a voicemail there.

In this episode of the Altium OnTrack Podcast, host Zach Peterson sits down with Stephen Newberry, Victor Kronberg, and Ching-Ping Wong from Chipletz — a fabless advanced packaging company pushing the boundaries of die-to-die interconnect technology. The team shares their background, their work on chiplet-based package design, and the technical paper they presented at DesignCon, which introduces the wallstrip transmission line: a novel interconnect structure designed to improve insertion loss, manage crosstalk, and enable higher data rates in chiplet packages without the need for a silicon interposer.   The conversation dives deep into the signal integrity challenges of advanced packaging, including how the wallstrip structure compares to traditional microstrip and stripline configurations, the role of the UCIE standard in enabling chiplet interoperability, and the long-term potential for an open chiplet marketplace. Whether you're a PCB designer curious about making the leap into IC packaging or an SI/PI engineer tracking the cutting edge of high-bandwidth interconnect design, this episode offers rare, expert-level insight into one of the most exciting frontiers in electronics engineering.  

So far on this podcast we've generally used the noun "sediment" to describe sand, gravel, and maybe cobbles and boulders. But the same word also gets used for silts, clays, and muds - materials that behave so differently that lumping them together as "sediment" can blur important distinctions.  This podcast was overdue for a conversation about fine sediment, and I knew exactly who I wanted to talk to.In the notebook where I track episode ideas, I labeled this one the “ERDC Cohesive Brain Trust.” I wanted to sit down with the team for the Corps of Engineers that I call when I have questions about "very small sediment", and the team I point engineers toward when they need cohesive measurements or insight for a project or model.That team is Dr. Dave Perkey, Dr. Jarrell Smith, and Dr. Danielle Tarpley, all based at the USACE Coastal and Hydraulics Laboratory (CHL) at the Engineering Research and Development Center (ERDC) in Vicksburg. A lot of the Corps' sediment expertise lives there. We've had several guests from ERDC over the years, and I've spent a lot of my own career collaborating with sediment specialists there. But Dave, Jarrell, and Danielle work on a part of the sediment world that is very different from the sand-and-gravel problems that dominate a lot of my work.Their focus is sediment that is finer - often much finer - than about 60 to 70 microns, roughly the diameter of a human hair. In the first half of this conversation, they lay out the basic properties and processes of cohesive sediment. Then we move into the research they've done to push that science forward. So whether mud is new territory for you or already part of your world, I think there's a lot here that you will find useful.Dave Perkey has spent nearly two decades at ERDC studying cohesive sediment properties and processes, especially erosion, transport, and geochemical composition. He also manages the Regional Sediment Management program - the RSM behind the title of this podcast - and it is not much of a stretch to say this season would not exist without him.Jarrell Smith has been a research engineer at ERDC since 1994, working on sediment transport, hydrodynamics, cohesive and mixed beds, and sediment-vegetation-turbulence interactions. We also talk about one of the tools he's especially known for, the Particle Imaging Camera System, or PICS, which I recently recommended on one of our own reservoir projects.Danielle Tarpley is a research oceanographer whose work spans sediment transport and hydrodynamics in inland and coastal settings. She works across field data collection, analysis, and modeling, and brings a great project-grounded perspective to the conversation.Dave, Jarrell, and Danielle took different paths through the Carolinas for their master's work, but all earned PhDs through VIMS at William & Mary.And watch the HEC sediment YouTube channel for some videos illustrating the fine-sediment measurement techniques they describe.This series was funded by the Regional Sediment Management (RSM) program.Mike Loretto edited the first three seasons and created the theme music.Tessa Hall is editing most of Season 4.Stanford Gibson (HEC Sediment Specialist) hosts.Video shorts and other bonus content are available at the podcast website:https://www.hec.usace.army.mil/confluence/rasdocs/rastraining/latest/the-rsm-river-mechanics-podcast...but most of the supplementary videos are available on the HEC Sediment YouTube channel:https://www.youtube.com/user/stanfordgibsonIf you have guest recommendations or feedback you can reach out to me on LinkedIn or ResearchGate or fill out this recommendation and feedback form: https://forms.gle/wWJLVSEYe7S8Cd248

Why do some people get promoted within months of joining a company while others wait years? In this episode, we break down the hidden factor that drives visibility, opportunity, and advancement. Hint: it has everything to do with your brand.  FREE TRAINING Register for The Catapult Your Career Bootcamp (http://thecatapultbootcamp.com) WORK WITH US Join the Catapult Your Career Program (http://cycprogram.com) GET IN TOUCH Linkedin: https://www.linkedin.com/in/stellaodogwu/ Instagram: https://www.instagram.com/_intelle/ Email: contact@intelle.us Text: 949-519-4554

Mike Matthews investigates the fascinating news from the end of the week and Mike answers what is happening in the odd world of spending. Join Mike as he podcasts live from Café Anyway in podCastro Valley with Madame Rootabega, Valentino, and Bison Bentley. Next show Mike Talks to Chely Shoehart, Floyd the Floorman, and John Deer the Engineer.

In this episode Revathy Ramalingam, Senior Software Engineer and AI Engineer at a healthcare startup, shares her inspiring personal journey from over nine years in telecom software architecture to successfully transitioning back into the industry after a seven-year career break. We explore the evolution of the AI engineer role, the practical application of RAG pipelines, and the strategic use of AI tools to rebuild a technical career.You'll learn about:- AI Career Mapping: Using LLMs to design an upskilling roadmap.- Vibe Coding: Leveraging AI tools for rapid prototyping.- RAG Implementation: Building retrieval systems with LangChain.- Interview Strategy: Proving technical skills after a career gap.- Learning in Public: Building a network through community projects.TIMECODES:00:00 Why Move to AI? Using ChatGPT to Plan a Career Pivot11:00 Learning in Public: The Power of Community Support15:35 Telecom Capstone: Predicting Network Slices with ML22:15 "Vibe Coding" & Building Prototypes with AI Dev Tools28:00 The Interview Process: Navigating a 7-Year Career Break33:45 Practical Interview Tasks: Building a PDF Q&A Assistant39:40 Career Advice: Clear Plans, AI Mentors, and Hard Work44:30 Closing Thoughts: Scaling the Learning LadderThis talk is for developers and career-changers looking for a blueprint to enter the AI engineering space. It is ideal for those interested in RAG, healthcare tech, and practical career resets.Connect with Revathy- Github - https://github.com/RevathyRamalingam- Linkedin - https://www.linkedin.com/in/revathy-ramalingam/ Connect with DataTalks.Club:- Join the community - https://datatalks.club/slack.html- Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ- Check other upcoming events - https://lu.ma/dtc-events- GitHub: https://github.com/DataTalksClub- LinkedIn - https://www.linkedin.com/company/datatalks-club/ - Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/

Mike Matthews investigates the fascinating news from the end of the week and Mike answers what is happening in the odd world of spending. Join Mike as he podcasts live from Café Anyway in podCastro Valley with Madame Rootabega, Valentino, and Bison Bentley. Next show Mike Talks to Chely Shoehart, Floyd the Floorman, and John Deer the Engineer.

Host: Mark PratherGuest: Damian DrozdNote: Damian is a longtime parishioner at St. Paul the Apostle Parish in Chino Hills, CA. He has invited Mark to speak at parish events on multiple occasions. Support the show

Where did probability come from? In this episode, Brad Harris explores how the invention of probability reshaped humanity's relationship with uncertainty—and why artificial intelligence (AI) ultimately runs on the same mathematics of prediction. For most of human history, the future was not something people tried to calculate. It was fate, providence, or the will of the gods. Then in the summer of 1654, two French mathematicians—Blaise Pascal and Pierre de Fermat—began exchanging letters about a gambling problem. From that correspondence emerged one of the most powerful ideas in human history: probability. Once uncertainty could be quantified, the consequences were enormous. Insurance markets became possible. Medical treatments could be tested through clinical trials. Governments began measuring populations statistically. Engineers could calculate risk and safety margins. Modern science itself increasingly relied on statistical reasoning. But the story doesn't end there. Today, the same probabilistic thinking underlies the most powerful technology ever created: artificial intelligence. Large language models like ChatGPT are fundamentally prediction engines—systems trained to calculate what words are most likely to come next. From ancient gambling games to modern AI, this episode explores how the invention of probability transformed the modern world—and why we are now living inside the most powerful prediction machines ever built. If you like Context with Brad Harris, you can help keep the show going and access bonus episodes through Patreon or by subscribing through Apple Podcasts or Spotify.  Find Brad Harris on X @bradcoleharris

Why I Switched to a Hybrid Approach and Tripled My Team's Delivery RateAgile was supposed to be the answer. Stand-ups, sprints, retros, these rituals promised faster delivery, happier teams, and stakeholders who finally felt in sync with engineering. For a while, it worked. My team hit a rhythm, delivered features quickly, and felt engaged in the process.But over time, the cracks showed.Velocity slowed to a crawl. Stand-ups became theater. Engineers dreaded sprint planning. Stakeholders kept asking when features would actually be done. And remote work made it worse with Zoom fatigue, Slack overload, and endless context-switching draining the energy Agile was supposed to give us.At first, I blamed the team. Maybe we weren't “doing Agile right.” So I doubled down on the rituals. More retros, stricter sprints, tighter velocity tracking. But the harder I pushed, the more Agile turned into bureaucracy.How to connect with AgileDad:- [website] ⁠https://www.agiledad.com/⁠- [instagram] ⁠https://www.instagram.com/agile_coach/⁠- [facebook] ⁠https://www.facebook.com/RealAgileDad/⁠- [Linkedin] ⁠https://www.linkedin.com/in/leehenson/

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

Your Nebraska Update headlines for today, March 12, include: University of Nebraska College of Law is closing its 28-year-old immigration clinic, U.S. Army Corps of Engineers officials face questions about Nebraska's Perkins County Canal project during public hearing in Colorado, Nebraska Department of Health and Human Services opens applications for nearly $40 million in grants aimed at rural organizations, state senators weigh cuts and priorities as they work through $125 million budget deficit at the Capitol.

What if getting dressed could actually help you feel better? This week, JVN sits down with Marie Claire Editor-in-Chief Nikki Ogunnaike to talk about dopamine dressing, personal style, and why fashion is so much deeper than just clothes. Together, they get into how to figure out what your style really is, why “everything is fashion,” and how vintage, retail, and finding a good deal can all shape the way we express ourselves. BIO: Named editor-in-chief of Marie Claire (US), Nikki Ogunnaike is among a new wave of women driving fresh relevance across fashion titles (The Washington Post saluted her and her peers in a recent collective profile). Previously at Harper's Bazaar in the role of senior digital director, she has a strong following through social channels and an all-around style that resonates with younger readers. In this new chapter for the reliable women's magazine, Ogunnaike's direction signals broader representation of faces and voices through fashion, beauty and news coverage, while appearing sharper and more accessible than ever. Nikki is a Nigerian-American style expert who cut her teeth at publications such as Vanity Fair, InStyle, Glamour, ELLE, and GQ. Full Getting Better Video Episodes now available on YouTube.  Follow Nikki Ogunaike on Instagram @nikkiogun Follow us on Instagram @gettingbetterwithjvn Jonathan on Instagram @jvn Executive Producer, Chris McClure Producer, Editor & Engineer is Nathanael McClure Production support from Chad Hall Our theme music is also composed by Nathanael McClure. Check out the JVN Patreon for exclusive BTS content, extra interviews, and much much more - check it out here: www.patreon.com/jvn  Curious about bringing your brand to life on the show? Email podcastadsales@sonymusic.com. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Engineers copy God's designs because they are the best designs. And that's exactly what we'd expect starting with the truth that “in the beginning God.”

In this episode of Wine After Work, Bryce sits down with Elif Acar-Chiasson, P.E., founder of OPLE Leadership and former COO with over 30 years in the AEC industry. Elif built her consulting practice after living inside what she calls a "broken autonomy model." Brilliant engineers are promoted into leadership roles, then trapped in approval culture where every decision climbs uphill for permission. The leader becomes the bottleneck. The team stops growing. Everyone burns out. Together, Bryce and Elif unpack: • Why technical excellence and leadership requirements are often in conflict • The hidden addiction to approval and control inside engineering firms • Why autonomy is not "do whatever you want," but clear decision ownership with guardrails • How emotional intelligence supports decision-making under pressure • What stepping away from a COO role taught Elif about fit and courage • Why leading with both head and heart is not weakness but maturity • What competitive ballroom dancing at 50 revealed about starting over and discomfort Elif shares a systemic approach to leadership. Instead of coaching one overwhelmed leader in isolation, she looks at the entire decision architecture of a team. Who owns what? Where decisions stall. How trust is built or broken. Her core belief: the most critical structural integrity is not in buildings. It is in teams. About Elif: Elif Acar-Chiasson, P.E., is a Professional Engineer and founder of OPLE Leadership. After 12 years as an executive, including 8 as COO at CSRS/Westwood, she now works with technical professionals who are exceptional at their craft but struggling in leadership roles. She translates emotional intelligence into engineering frameworks and helps teams redesign how decisions are made so leaders are no longer the bottleneck. Originally from Istanbul, Turkey, Elif brings a multicultural lens to leadership and challenges the idea that "people skills" are separate from technical rigor.   https://www.elifchiasson.com/  

Throughout the 16th century, one man stood between the Ottoman Empire and European domination, yet his name has been largely forgotten. Gabriele Tadino was an Italian military engineer whose genius transformed medieval warfare and saved Europe from one of history's greatest conquerors, Sultan Suleiman the Magnificent. In 1522, Tadino defied his Venetian masters by sneaking away in the night to defend Rhodes, where 700 Knights Hospitaller faced an impossible siege against 100,000 Ottoman troops. His revolutionary innovations—from acoustic devices using stretched skins and bells to detect enemy tunnels, to star-shaped fortifications that could withstand cannon fire—turned him into a legend among Renaissance military minds. Despite losing an eye in combat, Tadino continued directing the defense, holding off Suleiman for six months and forcing the Sultan to negotiate a peaceful surrender rather than achieve outright victory. Today’s guest is Edoardo Albert, author of “The Man Who Stopped the Sultan.” We see how Tadino's expertise came at a crucial moment when gunpowder was rendering centuries-old walls obsolete and Europe's power-hungry rulers—Henry VIII, Francis I, and Charles V—were too divided to mount a unified defense against Ottoman expansion. He pioneered counter-mining techniques like "camouflets," controlled explosions that buried enemy sappers alive, and ventilation shafts that redirected the force of gunpowder blasts away from fortress walls. His genius extended from Crete's massive Martinengo Bastion, which still stands today, to the walls of Vienna in 1529, where his underground warfare tactics stopped Suleiman's advance into Central.See omnystudio.com/listener for privacy information.

Listen and subscribe to Money Making Conversations on iHeartRadio, Apple Podcasts, Spotify, www.moneymakingconversations.com/subscribe/ or wherever you listen to podcasts. New Money Making Conversations episodes drop daily. I want to alert you, so you don’t miss out on expert analysis and insider perspectives from my guests who provide tips that can help you uplift the community, improve your financial planning, motivation, or advice on how to be a successful entrepreneur. Keep winning! Two-time Emmy and three-time NAACP Image Award-winning television Executive Producer Rushion McDonald interviewed Michael Uadiale. A seasoned CPA and master tax advisor with 25+ years of experience, discussing how entrepreneurs can use strategic tax planning to accelerate wealth building and achieve financial freedom within 5–7 years. He introduces his trademarked DECIDE Framework, explains why most small business owners overpay taxes, and breaks down strategies such as employing children, capturing appreciation, digital asset taxation, and multigenerational wealth planning. Rushion plays the voice of the everyday entrepreneur—curious, intimidated by taxes, and eager to understand wealth strategies—while Michael emphasizes empowerment through education, intentional planning, and knowing the rules of the tax code.

Listen and subscribe to Money Making Conversations on iHeartRadio, Apple Podcasts, Spotify, www.moneymakingconversations.com/subscribe/ or wherever you listen to podcasts. New Money Making Conversations episodes drop daily. I want to alert you, so you don’t miss out on expert analysis and insider perspectives from my guests who provide tips that can help you uplift the community, improve your financial planning, motivation, or advice on how to be a successful entrepreneur. Keep winning! Two-time Emmy and three-time NAACP Image Award-winning television Executive Producer Rushion McDonald interviewed Michael Uadiale. A seasoned CPA and master tax advisor with 25+ years of experience, discussing how entrepreneurs can use strategic tax planning to accelerate wealth building and achieve financial freedom within 5–7 years. He introduces his trademarked DECIDE Framework, explains why most small business owners overpay taxes, and breaks down strategies such as employing children, capturing appreciation, digital asset taxation, and multigenerational wealth planning. Rushion plays the voice of the everyday entrepreneur—curious, intimidated by taxes, and eager to understand wealth strategies—while Michael emphasizes empowerment through education, intentional planning, and knowing the rules of the tax code.

In Episode 364 of the Mixing Music Podcast, Dee Kei and Lu revisit one of the most common pieces of advice in mixing: “mix fast.” While trusting your instincts and avoiding overthinking can be powerful, the guys explore the nuance behind when slowing down actually leads to better results.They discuss the value of the “next day listen,” how fresh ears can reveal problems you missed the night before, and why building extra time into your schedule can improve both your mixes and your revision process. From there, the conversation dives into practical ways to slow down intentionally, including detailed automation, vocal rides, automating effects and parallel compression, and taking the time to properly dial in EQ and compressor settings.The episode also highlights the importance of referencing and making intentional decisions rather than letting plugins or presets determine the direction of a mix. The core message is simple: instinct and speed are valuable, but great mixes often come from knowing when to pause, listen carefully, and refine the details.SUBSCRIBE TO OUR PATREON FOR EXCLUSIVE CONTENT!⁠SUBSCRIBE TO YOUTUBE⁠Join the ‘Mixing Music Podcast' Discord!HIRE DEE KEIHIRE LU⁠HIRE JAMES⁠Find Dee Kei and Lu on Social Media:Instagram: @DeeKeiMixes @MasteredbyLu @JamesParrishMixesTwitter: @DeeKeiMixes @MasteredbyLuThe Mixing Music Podcast is sponsored by ⁠Izotope⁠, ⁠Antares (Auto Tune)⁠, Sweetwater, ⁠Plugin Boutique⁠, ⁠Lauten Audio⁠, ⁠Filepass⁠, & ⁠Canva⁠The Mixing Music Podcast is a video and audio series on the art of music production and post-production. Dee Kei, Lu, and James are professionals in the Los Angeles music industry having worked with names like Odetari, 6arelyhuman, Trey Songz, Keyshia Cole, Benny the Butcher, carolesdaughter, Crying City, Daphne Loves Derby, Natalie Jane, charlieonnafriday, bludnymph, Lay Bankz, Rico Nasty, Ayesha Erotica, ATEEZ, Dizzy Wright, Kanye West, Blackway, The Game, Dylan Espeseth, Tara Yummy, Asteria, Kets4eki, Shaquille O'Neal, Republic Records, Interscope Records, Arista Records, Position Music, Capital Records, Mercury Records, Universal Music Group, apg, Hive Music, Sony Music, and many others.This podcast is meant to be used for educational purposes only. This show is filmed and recorded at Dee Kei's private studio in North Hollywood, California. If you would like to sponsor the show, please email us at ⁠deekeimixes@gmail.com⁠.Support this podcast at — https://redcircle.com/mixing-music-music-production-audio-engineering-and-music/donationsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Why do smart teams still deliver failed projects? Most project failures don't begin with a catastrophic mistake. Instead, they begin with small deviations—minor compromises that seem harmless in the moment. A warning sign gets ignored. A shortcut becomes acceptable. A risk is acknowledged but tolerated because "nothing bad happened last time." Over time, those deviations quietly become the new normal. In this episode of Project Management Happy Hour, Kim Essendrup and Kate Anderson sit down with Dr. Bill Brantley to explore one of the most dangerous patterns in project leadership: normalization of deviance. The concept comes from sociologist Diane Vaughan's analysis of the Challenger space shuttle disaster. Engineers had long observed problems with the shuttle's O-ring seals. But earlier launches survived those anomalies. Each successful launch reinforced the belief that the risk was acceptable. Gradually, what began as an abnormal warning became accepted behavior. As Dr. Brantley explains: "We survived that near miss. It's okay. Next time we'll be okay." Project teams fall into this pattern all the time. A design review is skipped because the team is behind schedule. A test failure gets dismissed because it hasn't caused a real problem yet. A risk gets documented—but never truly addressed. Nothing breaks immediately. So the project keeps moving. The conversation explores how this slow drift toward failure mirrors patterns seen in aviation, engineering disasters, and even mountaineering expeditions. Experienced professionals—people who know better—gradually normalize increasingly risky decisions until the system finally breaks. But the episode goes further than just diagnosing the problem. Dr. Brantley and the hosts dive into the decision dynamics inside projects. A typical project team makes dozens—or even hundreds—of decisions every week. Some have immediate consequences, while others take months or years to reveal their impact. One story from the Apollo program illustrates this perfectly: a weld defect made years earlier ultimately contributed to the crisis of Apollo 13. This delay between decision and consequence creates a dangerous blind spot. Dr. Brantley jokingly calls it the "White Castle effect." "White Castle burgers are great going down… and then at three in the morning you realize you made a bad decision." The same thing happens in project management. Decisions that seem harmless in the moment can produce painful consequences much later. One of the most powerful insights from the discussion is that organizations often fail to reflect on their decisions. Teams act, move forward, and stay busy—but rarely pause to ask whether their decisions are actually improving outcomes. That reflection step is critical. "Reflection really helps you break that normalization of deviance." Without it, teams never notice when small compromises start compounding into systemic risk. The episode also explores practical techniques for improving project decision-making. One of Dr. Brantley's favorites is red teaming—a method borrowed from military strategy and cybersecurity. In a red-team exercise, someone deliberately challenges the plan and tries to break it. Their job is to expose weaknesses before reality does. It's a powerful way to counter groupthink and create psychological safety for dissent. Another theme throughout the conversation is something many project managers intuitively know but rarely articulate: Every action—or inaction—on a project is ultimately a decision. "Everything is a decision. Nobody is going to come after you around anything other than decisions." Whether it's changing scope, delaying work, ignoring a risk, or choosing not to act at all, project leaders are constantly making decisions that shape the outcome of the project. The real question isn't whether decisions are happening. It's whether those decisions are intentional, visible, and thoughtfully examined. Because in many projects, failure doesn't arrive suddenly. It arrives slowly—one accepted deviation at a time. Love our content? Then join the PM Happy Hour membership at pmhappyhour.com/membership

Kyler Middleton, a software developer in the healthcare sector, builds and supports AI bots and AI agents that are now widely used inside the company where she works. Today on Packet Protector, Kyler stops by to talk about how and why she built these tools, how she (and her organization) address the risks these tools... Read more »

https://teachhoops.com/ Toughness in basketball is often misunderstood as "aggression" or "trash-talking," but true program toughness is the ability to execute the next right thing, regardless of the circumstances. It is a "quiet" quality found in the player who sprints to the floor for a loose ball, the guard who stays in a stance for 30 seconds of a defensive possession, and the teammate who is the first to high-five a peer after a mistake. To build a tougher team, you must move from "talking about it" to "training it." Toughness is a perishable skill that must be rehearsed daily in your practice environment. If you don't demand a "box-out" on every single shot in November, you shouldn't be surprised when your team "shrinks" during a physical postseason game in March. The most effective way to build toughness is through "Conditioning with a Purpose." Traditional "suicides" or "liners" build aerobic capacity, but they rarely build "Competitive Grit." Instead, utilize "Pressure-Cooker Drills" where the scoreboard dictates the level of fatigue. For example, run a "Perfect Shell" drill where the defense must get three consecutive stops without a single technical error (missed rotation, "lazy" closeout, or failure to talk). If they fail, the count resets to zero. This "mental weight-lifting" teaches players that "tired" is just a feeling, not a fact. By making the "standard" of the drill higher than the "stress" of the game, you ensure that your athletes are physically and psychologically prepared for the most chaotic moments of the season. Finally, you must reward the "Invisible Wins." Players will always value what the coach "celebrates." If you only celebrate scoring, your team will only focus on offense. To build a tough culture, you must have a "Toughness Board" in the locker room that tracks "Zero-Talent" metrics: deflections, floor dives, charges taken, and "Sprints to the Corner." Use your TeachHoops member calls to "audit" your feedback loop: are you calling out the player who didn't get back in transition, or are you just "moving on" to the next play? By making toughness a non-negotiable requirement for playing time, you create a "self-policing" locker room where the players hold each other to a championship standard. Basketball toughness, team culture, mental toughness, coaching philosophy, defensive grit, hustle stats, basketball IQ, high school basketball, youth basketball, basketball drills, pressure-cooker drills, coach development, athletic leadership, basketball strategy, "Next Play" mentality, basketball conditioning, physical play, coach unplugged, teach hoops, basketball success, leadership standards, program building, championship habits. SEO Keywords Learn more about your ad choices. Visit podcastchoices.com/adchoices

Kyler Middleton, a software developer in the healthcare sector, builds and supports AI bots and AI agents that are now widely used inside the company where she works. Today on Packet Protector, Kyler stops by to talk about how and why she built these tools, how she (and her organization) address the risks these tools... Read more »

This week we're talking: prepping for the Hot & Healed comedy tour, self-tape adventures, new Instagram follows, shopping quirks, our weekly spelling bee, dermatologist updates, geopolitical reflections on the military action Iran, answering your listener questions, and of course - our Hot B of the Week! The Monday Edit, now on YouTube!  Check out the JVN Patreon for exclusive content, bonus episodes, and more! www.patreon.com/jvn  Follow us on Instagram @gettingbetterwithjvn Jonathan on Instagram @jvn and senior producer Chris @amomentlikechris  Executive Producer, Chris McClure Producer, Editor & Engineer is Nathanael McClure Production support from Chad Hall Our theme music is also composed by Nathanael McClure.Curious about bringing your brand to life on the show? Email podcastadsales@sonymusic.com. Learn more about your ad choices. Visit podcastchoices.com/adchoices

1. Headline: The Secret Meeting at Uranaborg Guest Author: Mark PiesingSummary: Mark Piesing discusses the 1925 secret meeting in Norway where legendary explorer Roald Amundsen and Italian engineer Umberto Nobile planned their North Pole airship expedition. Driven by financial needs, unfinished business, and political pressure, these complex characters formed an uneasy, historic alliance. (17)

What happens when you meet someone who looks like your long-lost twin… and then they also have an iconic backstory to match?  JVN is joined by Matt Newman (aka MattLovesHair on social media) for one helluva delightful conversation. From photoshoot fiascos, an ANTM-era detour, and Matt's origin story as an OG Drybar stylist. From there, it's all the hits - strip club stories, “DollarStoreJVN,” frat hazing, first love, and how social media can shape (and sometimes warp) the way we see ourselves. Then we go deeper: how gender expression evolves, what it takes to feel safe being seen, and the confidence it requires to live more honestly—even when the world has opinions. And yes… JVN talks about potentially chopping their hair off, what it was like cutting their hair back in the day, and what it taught them about identity, control, and change. If you've ever felt like you were editing yourself to fit the room, this one will hit—and leave you feeling a little braver. Full Getting Better Video Episodes now available on YouTube.  Follow Matt Newman on Instagram @mattloveshair  Follow us on Instagram @gettingbetterwithjvn Jonathan on Instagram @jvn Executive Producer, Chris McClure Producer, Editor & Engineer is Nathanael McClure Production support from Chad Hall Our theme music is also composed by Nathanael McClure. Check out the JVN Patreon for exclusive BTS content, extra interviews, and much much more - check it out here: www.patreon.com/jvn  Curious about bringing your brand to life on the show? Email podcastadsales@sonymusic.com. Learn more about your ad choices. Visit podcastchoices.com/adchoices