Podcasts about prs

What happens when your autonomous coding agents need to navigate your core infrastructure? Do you hand them the keys and hope for the best? (gulp!) This week on Dev Interrupted, 1Password CTO Nancy Wang teaches the golden path for agentic security: just-in-time secrets that grants AI "access without custody." She also shares her CTO playbook for measuring true agentic ROI beyond raw PR volume, explains why 1Password has officially replaced traditional coding interviews with agent builder tests, and confesses she's shipping PRs again with her own fleet of agents between meetings. Like many CTOs we've had on the show, Nancy reminds us that code is cheap now, and review is what's expensive now. We get into tactics for addressing that bottleneck.Get the guide: The AI engineering productivity gap - how elite teams pull ahead in 2026Register: Dev Interrupted Presents: The Software Factory RoundtableFollow the show:Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelFollow the hosts:Follow AndrewFollow BenFollow DanFollow today's guest:1Password: Explore the enterprise password and identity platform at 1password.com1Password for Developers: Dive into the new developer tooling, credential brokering, and secure AI workflows at 1password.devOracle Red Bull Racing: Read more about the F1 team's systems engineering at redbullracing.comConnect with Nancy: LinkedIn OFFERSStart Free Trial: Get started with LinearB's AI productivity platform for free.Book a Demo: Learn how you can ship faster, improve DevEx, and lead with confidence in the AI era.LEARN ABOUT LINEARBAI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production.AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance.AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil.MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.

The power data you have from your 2026 season is a goldmine of insight for what worked, what did not and how to leverage your learnings to plan for an even better 2027. Join Coach Frank, and dive into your data with the 5 prompts +a bonus prompt to ask CoachCat about your season for planning 2027 ahead! Key Takeaways from this training tip: https://fascatcoaching.com/blogs/training-tips/using-power-data-to-review-your-season/ See below for 6 Prompts you can copy and paste into CoachCat's chat to review your season. Zoom out in steps. Last month, then 3 months, then 6 months, then the full year. Trends that hide at one zoom level jump out at another. Translate your Level into weekly hours. That is how you actually plan training around life. Compare your power PRs to a fixed reference point like January, not to your best day ever. Copy the prompts below into CoachCat and it builds every one of these charts from your own files. Want to be able to review your season and be able to follow a custom training plan?  Try CoachCat where the 1st week is free: https://fascatcoaching.com/app

What happens when something you've always used to define yourself suddenly disappears? In this episode, Angie talks with Heather Lacey about identity, running, career changes, injury, and the uncomfortable process of figuring out who you are when a familiar title no longer fits.Heather spent 20 years as a healthcare executive before being laid off. Running became an important coping tool during that transition, but she eventually realized she had transferred the same achievement-driven identity into running. From chasing career titles to chasing PRs, Heather shares what she learned about going all in, the pressure to prove yourself, and what happens when running is temporarily taken away by injury.Heather also shares the story of her son Luke's scoliosis surgeries during COVID and how running helped her manage the stress of months in the hospital. Her experience ultimately changed how she viewed racing, performance, and success. This conversation is a reminder that you are more than your job, your pace, your race results, or any other title you give yourself.Heather Lacy is a healthcare executive turned running coach, advisor, and author of The Other Side of the Mirror: What Happens When Your Title Disappears. After spending 20 years building her career, Heather experienced firsthand what happens when a title that has shaped your identity is suddenly gone. Her journey led her to explore who we are beyond our careers, achievements, and even our identities as runners. Through her story, Heather encourages others to embrace change, let go of past versions of themselves, and find freedom in discovering who they are in each season of life. If you want to connect with her, you can find her at the links below!Website: heather@heatherlacy.comInstagram: @heather.lacyBook: The Other Side of the Mirror: What Happens When Your Title Disappears00:28 Heather's running origin story05:18 Taking a pause to figure out what's next07:10 From chasing career titles to chasing PRs08:51 “You're faster than you think you are”10:37 Becoming a running coach13:10 Does a coach have to be fast?16:18 When running becomes your identity17:19 Injury and losing the ability to run19:34 The Other Side of the Mirror23:05 It's never too late24:22 Giving yourself time before you pivot26:05 Luke's scoliosis journey32:33 When a marathon isn't about the PR35:45 The power of the running community37:30 Why Heather wrote her book40:55 Authenticity and being yourself42:20 What running means to Heather nowGain access to my new secret podcast, Unbreakable: The Runner's Guide To Injury-Proofing Your Body After 40. Click here: https://www.realliferunners.com/secretJoin the Team! -->  https://www.realliferunners.com/team Thanks for Listening!!Be sure to hit FOLLOW on Apple Podcasts, Spotify, or your favorite podcast player Leave a review on Apple Podcasts. Your ratings and reviews really help and we read each one!Come find us on Instagram and say hi! Don't forget: The information on this website is not intended to treat or diagnose any medical condition or to provide medical advice. It is intended for general education in the areas of health and wellness. All information contained in this site is intended to be educational in nature. Nothing should be considered medical advice for your specific situation.

We Like Shooting We Like Shooting - Ep 676 August 17, 2026 Presented by This episode of We Like Shooting is brought to you by: Foxtrot Mike (Code: WLSISLIFE) C&G Holsters (Code: WLSISLIFE) Gideon Optics (Code: WLSISLIFE) Midwest Industries (Code: WLSISLIFE) Blue Alpha Night Fision (Code: WLSISLIFE) Otis Technology (Code: WELIKESHOOTING15) Giveaways!! GAW   Text Dear WLS or Reviews +1 743 500 2171 Public   Show Titles   Gear Chat Note Montana Knife Company stoned goat ultrahttps://www.montanaknifecompany.com/products/stoned-goat-ultra EAA Corp. Girsan Witness2311 CMX XXX Discover the Witness2311 CMX XXX, a compact double stack 1911 with 16+1 capacity, a slim grip, firing pin block safety, and two-tone finish. The Girsan Witness2311 CMX XXX is a compact single-action 9mm pistol from EAA Corp. with 16+1 capacity using Check-Mate magazines. It features an RMSc-footprint optic-ready slide, 3.4-inch coned barrel, two-tone Cerakote finish, low-profile 3-dot sights, ambidextrous thumb safety, 4-slot Picatinny rail, and EAA limited lifetime warranty. Availability: Available for purchase via Add to Cart on eaacorp.com (no explicit stock, release date or additional retailers stated) Cost: $899 Special: Streamlined compact grip with aggressive texturing, low-profile magwell, and automatic firing pin block safety replacing traditional grip safety for 16+1 capacity without added bulk Odysee (Nick) SecondWatch FTN.6 Suppressor Pack Update: We received overwhelming feedback that people did not like the text. The intention was to save on what needed to be engraved. Since it is so unpopular, all text has been removed from the model… The FTN.6 Suppressor Pack is a downloadable set of 3D-printable files for DIY suppressors released by SecondWatch on August 15, 2026, via Odysee. It includes updated designs for rimfire, 5.56, and 300 BLK models that are described as the quietest FTN variants to date, matching or surpassing many commercial suppressors in head-to-head testing. The pack continues the FTN (Fuck The NFA) series focused on accessible, low-cost polymer printed silencers. Availability: Released August 15, 2026 on Odysee (@SecondWatch); downloadable files Special: FTN.6 Air is a very lightweight (~10.6 oz) and slim rifle suppressor using thread adapters; modular flash hider and compensator add-ons; FTN.6 Rimfire offers similar sound reduction to FTN.5 but in a smaller package Defiance Machine (Nick) Defiance Machine Deviant Comp Rifle Action Deviant COMP – The new standard for PRS competitors. The Deviant COMP refines our popular Deviant model into a purpose-built precision rifle action designed specifically for PRS competitors who demand speed, consistency, and reliability under pressure. Built with the features competitive shooters actually want, the Deviant COMP features an oversized bolt for fast cycling, an AW magazine cut compatible with both AW and AICS magazines, and guaranteed headspace for repeatable accuracy and hassle-free builds. This makes the Deviant COMP a competition-ready package that is ideal for PRS. Finished with nitride included at no additional cost, the Deviant COMP delivers premium performance at an exceptional value. Specifications Integral scope mount/rail. Integral recoil lug. Defiance swept legacy bolt design. Oversized competition bolt knob. Smooth chrome-moly bolt action with anti-bind design. Recessed bolt lugs, Mini-16 extractor, and plunger ejector. AW magazine cut. Trigger pins included. Nitride finish included. Why choose the Deviant COMP? PRS competition-ready feature set. Integral rail and recoil lug means more rigidity and reliability when it matters most. Receiver is made from once piece of pre-hardened aircraft-certified 416 stainless steel, allowing for tight manufacturing tolerances and increased performance. One-piece legacy bolt, machined to exacting tolerances required to cycle as smooth as possible. Swept bolt handle design to allow plenty of clearance with your rifle scope. Precision extraction system that significantly increases initial extraction and improves smooth bolt cycling. Need an extra bolt? Extra bolts are available when purchasing your action over the phone with our team for $495 each (includes extractor, ejector, and fire control assembly). The Deviant Comp is a purpose-built short-action bolt-action receiver from Defiance Machine, refined from the standard Deviant for PRS competitors. It is machined from a single piece of pre-hardened 416 stainless steel with an integral scope rail and recoil lug for rigidity and guaranteed headspace. It features an oversized competition bolt knob, swept bolt handle, anti-bind design, AW/AICS magazine compatibility, nitride finish, and a smooth chrome-moly bolt with recessed lugs, Mini-16 extractor, and plunger ejector. Availability: Available through retailers including Red Hawk Rifles (add-to-cart with options) and Altus Shooting (currently out of stock for specific variants like RH/308) Cost: $1,495.00 Special: PRS-optimized with oversized bolt for fast cycling, AW magazine cut compatible with AW and AICS, integral rail/lug for rigidity, and included nitride finish at no extra cost 270 Videos Removed from YouTube for FRN and WLS in Recent Days 270 videos removed from youtube for FRN and WLS in the last several days. Supplementary Research: Firearms Radio Network (FRN) produces multiple gun-related podcasts including the long-running We Like Shooting (WLS) show, which features discussions on firearms, gear, training, and current events. The claim states that 270 videos associated with these channels were removed from YouTube over several days in 2026. YouTube's enforcement actions in 2026 have included widespread removals tied to updated policies on AI-generated content, community guidelines, and monetization standards, with millions of videos and channels affected platform-wide. Gun Fights Play the best Price Is Right-style GunBroker game on the internet. Gun Fights Live DisplayFollow the game, prices, and reveals as they happen.Open the live display BangRank A live cast ranking segment for anything and everything in the gun world, powered by questionable certainty, strong opinions, and audience voting. BangRank Live VotingScan or open the link to rank along with the show.https://welikeshooting.com/rank   WLS is Lifestyle GunCAD Index 2011 OPTICS MAXXING by Foaps Files Designed specifically for the Nightalliance 2011 Maxxing frames. There are two styles to choose from and six different optic mounting patterns. Each … This is a 3D model release on GunCAD Index containing STEP and STL files for optic mounts designed specifically for Nightalliance 2011 Maxxing frames. It offers two styles, six optic mounting patterns (including ACRO, Docter-Noblex, Pic Rail, RMR, RMSc, T1-T2), Gas Pedal and Non-Gas Pedal variants, plus length options for Full, Commander, and Short frames. The page serves as an indexed preview only; actual files must be acquired from the original source. Why it Matters: Enables precise red-dot integration on custom 2011 pistols in the growing 3D2A community, allowing shooters to upgrade iron-sight platforms with modern optics without factory limitations. The Vibe: Clean, modular CAD aesthetic with purposeful engineering details—gas pedal extensions, multi-pattern plates, and frame-specific lengths that emphasize performance-oriented customization over factory aesthetics. Hot Take: In the 2011 maxxing scene, bolting a quality optic directly to a printed or custom frame is now the baseline, not an afterthought. GunCAD Index Freedomware Sedco SP22:8 SPEDBRO SP22 Printable 22LR Pistol Don't like the standard Jennings J22? Well here's his neglected brother, the Sedco SP22. A knockoff of the already trash J22. NOT FOR DISTRIBUTION O… The SPEDBRO SP22 is a 3D-printable knockoff of the Sedco SP22 / Jennings J22 design by FreedomWare. It is a rimfire 22 Long Rifle handgun classified as a printed firearm using DIY barrel, bolt, and fire control with no firearm parts required. The release includes multiple STL files, reference images, a drill key, and README; total size 2.5 MiB; explicitly not for distribution on DEFCAD; tagged for FOSSCAD and 3D2A. Why it Matters: Provides a fully printable 22LR plinking handgun design that requires no commercial firearm parts, enabling DIY production of a simple rimfire pistol using consumer 3D printing and basic tools. The Vibe: Utilitarian homemade aesthetic with blocky printed polymer grips and frame, exposed metal DIY barrel/bolt, and reference photos showing side-by-side comparison to a Bryco 22; raw FOSSCAD open-source vibe with technical STL and drill-key files. Hot Take: A knockoff of the already trash J22 – the neglected brother Sedco SP22 now lives on as a fully printable FreedomWare project for the 3D2A community. Guncadindex Tritschi 60 Seconds Timer for Shooting Range A self-built horizontal hourglass-style mechanical countdown timer using a stepper motor, GT2 belt, Nema17, Arduino Nano, and 3D-printed parts. It provides a large 160 cm x 90 mm visual window that transitions from white to red over exactly 60 seconds for timing K20-K23 handgun events in DSU disciplines, with startup red LED/beeper sequence, green LED indicator, optional beeper, and planned light-sensor start. Powered by 3S Li-Ion with BMS; designed in TinkerCad and printed on Prusa MK4/Sovol SV08. Why it Matters: Best Use Case: Competition (K20-K23 handgun events in German DSU shooting sports; helps pace 18 shots in 60 seconds without digital distractions or crowd noise) Hot Take: Quick Pro/Con: Pro – Large peripheral-vision mechanical analog display improves focus and timing accuracy; Con – Self-built (requires 3D printing,...

Send us Fan MailNate and Liz each share 3 lessons they wish they knew when they first stepped into the gym, and they get honest about the mistakes that slowed progress for years, especially for lifters chasing muscle gain and bigger numbers on the squat, bench press, and deadlift.We dig into the truth behind gaining size: if you want to get bigger, you usually have to eat more than you think, consistently enough to create a real caloric surplus. From there, we move into the mindset that keeps you in the game when training feels awful. Missing a rep is not a reason to quit, it's a reason to adjust, finish what you can, and stack another day of work. We also talk about why not every workout should crush you, how recovery supports strength gains, and why patience and time are the best performance enhancers you'll ever find.Liz also shares a perspective that can instantly reduce meet anxiety: most people do not know your PRs, your totals, or what you weigh. They're there to support you and see you enjoy the process. We close with a practical conversation on when to change technique, why constant tinkering backfires, and an example of debating sumo vs conventional deadlift heading into a meet.If this helped, subscribe on Apple Podcasts or Spotify, share it with a training partner, and leave a review so more lifters can find their strong.Support the showThanks for listening! Please remember to subscribe to the podcast, leave us a rating and share it with your friends so we can continue to grow!-You can now become a Fortis After Hours Supporter by using the link below! This will help support the podcast as we continue to grow and we will give you a shoutout on the next episode after you subscribe as well as give you top priority for different topics or discussions you'd like us to have on the podcast. Thank you for your support!https://www.buzzsprout.com/1369834/support-Follow us on social media for daily fitness and powerlifting content including workouts, helpful tips and client success stories!@fortisfitnessstudio-HOSTED BY@lizribaudo_fortis@nateribaudo_fortis

What's your gold standard for deciding whether AI-written code is ready for production? In Episode 42 of Talking Postgres, Simon Willison—creator of Datasette, co-creator of Django, and prolific open-source developer—joins Claire to share how AI is changing the way he builds software today. We dig into why his test for shipping AI-generated code is “Could I explain this to somebody else?”, how engineering management skills can be surprisingly useful when managing AI agents, and how the bottleneck is no longer writing code but understanding it. Also: personal credibility, deep research, the Winchester Mystery House, slop proxies, and Simon's observation that “Features are cheap. That doesn't mean you should build them all.”Previously on Talking Postgres:Talking Postgres podcast Ep 30: AI for data engineers with Simon Willison Links mentioned in this episode:Blog: Simon Willison's BlogProject page: Datasette, for finding stories in dataGitHub repo: sqlite-utilsBlog post: Release of alchemy-utils 0.1a0 (featuring Postgres & DuckDB)Blog post: There are no lossless transformations of natural-language text, by Sophie AlpertPodcast episode: The Open Weight Revolution with Simon Willison, on Oxide and FriendsPodcast episode: An AI state of the union, on Lenny's Podcast Wikipedia: Winchester Mystery HouseIdea in Mythical Man-Month: Conceptual integrityBlog post: SQLite compressed text-history prototypes, by Simon WillisonTools: Simon's miscellaneous tools repoIn this episode, we covered:00:00 Intro & music04:00 A week of work before breakfast09:12 Red-green TDD makes agents exercise every line14:42 A million lines mean nothing if you don't understand it18:28 Finding low-hanging fruit among open PRs & issues22:07 Getting work done while walking the dog23:01 Gold standard: “Could I explain this to somebody else?”28:27 Slop proxies add no value at all30:49 Aggressive nitpicking reviews35:01 Everything in software engineering is about trade-offs41:16 Racoon heist game is only fun for 1 minute 15 seconds43:46 New Year's resolution to be more ambitious48:11 You have to learn to throw things away51:57 Features are cheap. That doesn't mean you should build them all1:00:45 Engineering management skills are so useful1:04:44 QA specialists should be having a great time1:07:53 Writing is thinking, don't outsource it1:08:23 Skill atrophy is a choice you make1:10:07 I believe in people who are motivated1:11:55 Systems are not set up to deal with this volume1:18:48 Research agents stopped being absolute garbage1:21:49 The whole point of the “human in the loop”1:26:10 Dream: I want there to be more small businesses

AI adoption among software developers is approaching 100%, AI-authored code now makes up more than half of merged code, and developers report saving more time with AI every quarter. But those gains aren't translating evenly into better outcomes.In this episode of Engineering Enablement, host Brian Houck, Distinguished Scientist at DX, sits down with Justin Reock, Deputy CTO at DX, to unpack findings from DX's latest AI Impact Report. They explore where AI is improving engineering velocity and developer experience, where concerns are emerging around PR size, change confidence, and failure rates, and why rising AI spend has yet to produce a comparable increase in innovation.They also discuss how AI is changing the meaning of code maintainability and where developers' AI-driven time savings may actually be going.Where to find Justin Reock:• LinkedIn: https://www.linkedin.com/in/justinreockWhere to find Brian Houck: • LinkedIn: https://www.linkedin.com/in/brianhouckIn this episode, we cover:(00:00) Intro(01:45) How the current AI impact report is tied to Core 4 (03:24) The state of AI adoption(05:12) How much time AI is saving developers and percentage of AI-authored code(07:47) AI's impact on PR throughput and deployment frequency(11:09) How EMs are shipping more code(13:02) Why larger PRs may be problematic(18:21) The growing gap between code maintainability and change confidence(21:48) How perceived code quality varies by organization size(23:49) The growing volatility in change failure rates(28:07) What the Developer Experience Index reveals(32:20) Cost, dev ramp-up, and innovation ratio (35:38) Where AI time savings are getting lost(37:11) Questions and wrap-upReferenced:• DX Core 4 Productivity Framework• AI Impact report• The AI-native developer - by Brian Houck• GitHub Copilot and Developer Productivity: An Observational Dose-Response Analysis• Writing Code vs. Shipping Code: Productivity Effects Across Generations of AI Coding Tools | NBER • The Productivity-Experience Paradox - Annie Vella• EngThrive: Make It Fast and Easy to Do Great Work• The AI efficiency plateau - by Brian Houck• Tradable Quality Hypothesis

This episode is presented by Namespace.so, building high-performance cloud infrastructure for modern software development and AI-powered engineering. Engineering leaders from Cursor, Temporal, Tailscale, Legora, and Namespace discuss how AI agents are rapidly reshaping software development. From generating hundreds of PRs and debugging complex systems to running long-lived agents in the cloud, the conversation explores what's changing—and what isn't—as AI becomes part of everyday engineering. The group dives into reliability, security, context, observability, and managing fleets of agents, while examining why systems thinking and human judgment may matter more than ever as writing code itself gets easier. (Co-host)Namespace's Founder & CEO, Hugo Santos - https://www.linkedin.com/in/hugomgsantos/ Temporal Technologies's Director of Engineering, Yimin Chen - https://www.linkedin.com/in/ACwAAAwmUjcBTcOPTLnB5Cq6T7DPoQdcertQGMo Legora's Director, Platform Engineering, Greg Bell - https://www.linkedin.com/in/ACwAAABMP8oBhtLWLYNuzRM0MrQjHIoHYypmIGk Cursor's VP, Forward Deployed Engineering, Pauline Brunet - https://www.linkedin.com/in/ACwAAAXbWW8BYDDbSHlGjbN4CKkAGXaxsUJB0BE Tailscale's Director of Engineering, Rhea Ghosh - https://www.linkedin.com/in/ACwAAADSrI4Blak2OHN5pdkscC_T_2otRzXDvd4

Tom Toumazis spent 8 years as EVP and Managing Director of Disney-ABC-ESPN in EMEA. Since stepping off the executive track a decade ago he has built a portfolio career which includes SID at PRS for Music, NED at Directors UK and Deputy Chair of the University of Westminster amongst others. Interested in what it takes to build a portfolio career? Tune in to hear about: How investing his own money became Tom's way into his first board seats (01:35) His rule for the money he put behind those first bets (05:20) What Tom didn't anticipate about small-table board life (07:51) How he figures out what he's actually bringing to a board beyond money (10:11) What nobody tells you about explaining a portfolio career at a dinner party (11:26) How Tom got his first board seat, and the mistake he admits he made once he had it (12:58) Do you need a stellar career to sit on a board? (15:48) Getting a board role is a numbers game (22:05) Tom's tips for board interviews (26:28) An easy way to enhance your networking strategy (29:39) Enter the Boardroom Community Q&A (32:42) ⚡The Lightning Round⚡(34:51)Host: Oliver CummingsProducer: Will FeltonEditor: Penelope CoumauMusic: Kate MacAudio: Nick KoldEmail: podcast@nurole.comWeb: https://www.nurole.com/nurole-podcast-enter-the-boardroom

What happens when you hear your own hit song playing in public, but never receive the royalty?In this episode of Riding Unicorns, James sits down with Ryan Edwards, Founder & CEO of Audoo, the music technology company rebuilding how public performance royalties are measured and distributed.The idea for Audoo came from Ryan's own experience as a musician. After hearing one of his songs playing in a London department store and discovering there was effectively no reliable way to track the royalty, he started investigating how the system actually worked.What he found was an industry still relying heavily on proxy data, manual surveys and people physically visiting venues with clipboards.Audoo's answer is the Audio Meter, a small connected device that identifies music being played in public venues without recording or storing conversations. The resulting data allows collecting societies to understand what was actually played and distribute royalties more accurately to artists and rights holders.Today, Audoo operates across 16 countries, with its technology deployed in environments ranging from cafés and retailers to gyms and leisure centres.Ryan shares how he built the first prototype on a Raspberry Pi at his kitchen table, validated the idea with the former Chairman of PRS for Music, and launched the first real-world deployment on the other side of the world in Australia during COVID.We also discuss the unusual group of investors Audoo has attracted along the way, including Björn Ulvaeus of ABBA, Paul McCartney, Elton John, Adam Clayton of U2 and Adele, and how those relationships have helped build credibility and open doors across the music industry.Topics Covered• Why the public performance royalty system needed rebuilding• The personal experience that led Ryan to start Audoo• Building the first Audio Meter prototype on a Raspberry Pi• Why privacy had to be designed into the technology from day one• The challenges of combining software, data and physical hardware• Landing Audoo's first major deployment in Australia during COVID• Why venues are willing to install Audio Meters• How better music recognition data changes royalty distributions• Raising capital from some of the biggest names in music• Expanding Audoo across 16 countries and into the Middle East• What Ryan has learned from eight years as a founder• Why founders need to celebrate wins and know when something can wait until MondayThis is a conversation about spotting an antiquated system, using technology to rebuild it from first principles, and creating the data infrastructure that could finally ensure artists are paid accurately when their music is played.

After dropping 5minutes off her personal best in Boston, Maryann Gong is shooting for an OTQ in Chicago.With a 2:38 marathon PB she is right on the cusp of qualifying for the Olympic Trials. She takes us through her training, mindset, and prep for her OTQ attempt at Chicago.She also shares about her injury history and her decision to get surgery on her Haglunds Deformity. She is also a founder of a run coaching app called Toga. Toga is a personalized run training app for serious runners who are chasing PRs while balancing a busy life. It builds you a custom plan tailored to your goals and history with running, strength and prehab that adapts based on your real workouts, schedule and life. Whether you're looking for a full coach or just a copilot, Toga can help you reach your goals. Syncs with Garmin, Coros, Apple Health, Strava, and more. Available on iOS.: https://apps.apple.com/app/apple-store/id6758282443?pt=128052523&ct=d3glorydays&mt=8Follow her on Insta for more updates: https://www.instagram.com/maryanngong/Tailwind Nutrition is sponsoring today's episode. Whatever your training looks like turn to Tailwind to fuel you.Complete Nutrition Made Simple - Tailwind offers easy-to-digest, all-in-one fueling, recovery, and hydration for endurance athletes. Made for Athletes, by Athletes - Born out of real experience on the trails and refined with customer feedback. Get 20% off your first order when you used code GloryDays20 at ⁠⁠⁠⁠⁠⁠tailwindnutrition.com/GLORYDAYS⁠⁠⁠⁠⁠⁠BoulderthonAre you looking for your next race? You hear Noah talk about how much he loves running in Boulder and now's your chance to see why he loves it so much. is Boulder, CO's signature downtown marathon series taking place on September 27, 2026!Boulderthon has it all. From the 5k to the marathon, there is a race for everyone. Believe you can and you will!Boulderthon is offering $20 off to our readers for the Half or Marathon. Use code D3GloryDays at boulderton.orgHow to Support D3 Glory Days:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠THE NEWSLETTER!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠D3 Glory Days Venmo⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠We launched a Patreon!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscribe and leave us a review on Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠,⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Strava⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

237: On this episode, Staccato pulls dealer accounts, Tony shoots his first PRS match and Jaki shoots and 80oz pistol, and awesome questions from you guys! Check Out Our Partners & Affiliates For The Best Deals On Gear:

237: On this episode, Staccato pulls dealer accounts, Tony shoots his first PRS match and Jaki shoots and 80oz pistol, and awesome questions from you guys!Check Out Our Partners & Affiliates For The Best Deals On Gear:

SPONSORS: Don't let your mind get in the way of a good time. Discover your options at https://BlueChew.com Shopify: Turns out you don't need a real job. Build your own business with a free trialat http://shopify.com/bears Head to https://acorns.com/bears or download the Acorns app to get started. New DraftKings customers, sign up with code BEARS spend five bucks to get one hundred fifty in rewards within 14 days, includes all markets. Over at https://dkng.co/bears. For a limited time, our listeners get 50% off FOR LIFE, Free Shipping, AND 3 Free Gifts at Mars Men at http://Mengotomars.com. This week on 2 Bears, 1 Cave, Tom Segura and Bert Kreischer are back in the cave after eight weeks apart, and they open with a full review of The Odyssey, Lupita Nyong'o as Helen of Troy, Matt Damon's rogue Boston accent, and why Jon Bernthal is Hollywood's most legendary napper. From there, Bert unveils his billionaire rebrand (Sabah shoes, LBJ Stetsons, and the top five shoes billionaires wear this fall) before getting real about sobriety, anxiety attacks, and self-diagnosing 12 terminal illnesses in a single month. The Bears also spiral into the movies that blindsided them, Primal Fear, The Sixth Sense, Memento, Fight Club, and why the DIY hits like Obsession prove Hollywood is in another pivot moment. Plus: Project Hail Mary vs. the 15-hour audiobook, Bert's theory that this is the funniest (and most jacked) generation of comics ever, college football weight-room PRs, Jason Kelce showing up for a 9 AM bench session, and a meet & greet at MacDill Air Force Base August 14. If you missed the Bears, this one's for you. 2 Bears, 1 Cave Ep. 335 https://tomsegura.com/tour https://www.bertbertbert.com/tour https://store.ymhstudios.com Bet with DK Sportsbook: Gambling Problem? Call 1-800 GAMBLER, 1-800 MY RESET. Connecticut: call 888-789-7777, visit http://CCPG.org. On behalf of Boot Hill Casino in Kansas. Bet tax pass-through may apply in Illinois. Twenty one plus. Void in Canada. Event contract trading with DraftKings Predictions involves risk of loss. Availability varies. Predictions offer void in New York. Bet to get Bonus bets that expire in seven days. Trade to get Predictions Dollars that expire in one year. Fifty dollars in rewards issued every seven days via click to claim for fourteen days. One non-withdrawable reward redeemable. Nationwide based on Sportsbook, Predictions, and Free-to-Play Sports Contest availability. Varies by State. Terms at http://dkng.co/offer. Limited time offer. Chapters 00:00:00 - Intro 00:00:26 - The Bears Review The Odyssey 00:10:34 - Bears At MacDill Air Force Base 00:11:15 - Project Hail Mary & Bert's Cute Shoes 00:23:37 - Bert's Drinking Again 00:33:36 - Obsession & The New Hollywood Pivot 00:39:00 - The Best Twist Movies Ever 00:52:33 - Everyone's Got Abs 00:56:02 - College Weight Room Energy 01:00:44 - Wrap Up Learn more about your ad choices. Visit megaphone.fm/adchoices

Cloudflare is rolling out crypto wallets with claimable handles as identity, and a real React compiler finally landed for regular hooks-based code. Plus: OpenAI's pricing war, Vue Vapor benchmarks, GitHub's new npm malware scanning, and an active supply chain attack hitting 868 packages. Show Notes 00:00 Welcome to Syntax! 01:02 Shai Hulud is back! New Shai-Hulud announcement Attacked keyv packages 05:27 GitHub scans your npm packages for malware 06:42 Your agent has a wallet now Make your own Cloudflare wallet announcement blog post X402 payments 12:10 Yet another React compiler? Ripple.ts Inferno.js Dominic Gannaway's launch post Octane Native Script Reactivity + Rendering Benchmark 27:19 Scott switched his browser AGAIN! Dia Knock off extension 31:56 AI Mental health survey 32:29 OpenAI models are becoming cheaper? 38:49 GitHub stacked PRs finally arrived 41:48 AI video podcasts HeyGen launch post Hank Green's unhealthy AI usage 48:15 Brought to you by Sentry! 49:28 News from the TC39 meeting ECMAScript news Await dictionary TC39 Process 56:58 Qwen 3.8 01:02:31 Latest and greatest in CSS and UI libraries Foley.dev Morphicons Lucide Nucleo 8bit library CSS radar Impeccable Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott: X Instagram Tiktok LinkedIn Threads Randy: X Instagram YouTube Threads

Send us Fan MailIf your training has started to feel like a checklist, that's a problem you can solve and it might be the difference between a good month and a great decade. We're Nate and Liz, and we're back from summer break with a mix of coaching talk and listener Q&A built around one theme: training has to be sustainable, and sustainability often comes from actually having fun in the gym.We dig into what “fun” looks like when you're not a beginner anymore: creating an environment you want to show up to, celebrating small PRs and rep PRs, and using better movement as a win instead of only chasing all-time maxes. We also talk about form and mindset in powerlifting and strength training, including the trap of over-critiquing every rep until progress stops feeling good. Sometimes the best move is focusing on one cue, getting the work done, and letting the rest be “good enough” so you keep moving forward.Then we hit your questions: how many clients we each coach, whether there's a real max capacity, and how we think about scaling coaching while still matching people with the right coach. We also get deep on injuries and ego: accepting what happened, setting a new baseline without pain, and stacking small steps so confidence comes back week by week. We wrap with gym pet peeves, why community matters, and practical advice for runners training for long distance who want to maintain muscle through minimal resistance training, smart bodyweight work, and nutrition basics like protein and calories.If this helped, subscribe, share it with a training partner, and leave a quick review. What's the hardest part of staying consistent for you right now?Support the showThanks for listening! Please remember to subscribe to the podcast, leave us a rating and share it with your friends so we can continue to grow!-You can now become a Fortis After Hours Supporter by using the link below! This will help support the podcast as we continue to grow and we will give you a shoutout on the next episode after you subscribe as well as give you top priority for different topics or discussions you'd like us to have on the podcast. Thank you for your support!https://www.buzzsprout.com/1369834/support-Follow us on social media for daily fitness and powerlifting content including workouts, helpful tips and client success stories!@fortisfitnessstudio-HOSTED BY@lizribaudo_fortis@nateribaudo_fortis

Got feedback about this episode? Send Carolyn a textHow did Johnny Coffin get so fast? That's the question my husband—and unofficial Inspired Soles co-host—gets asked all the time, so in this episode, we're finally digging into the story behind the speed. Johnny recently celebrated his 45th birthday and is currently in the best shape of his life, having run PRs at the 5K, 10K, 10-mile, half marathon, and marathon (2:36:39!) over the past year. But his journey to becoming a 2:36 marathoner was anything but overnight. We talk about his injury-plagued early years, the decade he spent focused primarily on getting faster at the 5K, his gradual transition to the marathon, and the training, fueling, recovery, strength, and patience that have allowed him to continue improving without major injury. Along the way, we weave in five principles of effective run training—and unpack why sometimes the best way to get faster is to slow down.SPONSOR: DIG DEEP ENDURANCE FUEL. Use code INSPIRED10 at checkout to save 10% on your online order at digdeepef.com.Register for TRACKTASTIC

Try Momentous Signature Spec Creatine at http://livemomentous.com and use code PRS for up to 35% off your entire first order. Don't let stigma stand in the way of support. Start therapy with BetterHelp. Sign up and get 10% off at http://betterhelp.com/punkrock Stephen Hilton had a life most people would kill for — eight years clean, two kids, a scoring career on Hans Zimmer's team (Megamind, Transformers, Pirates of the Caribbean), and a viral comedy empire he built with his wife, Laura Clery. Then a contractor walked off with the money on a house renovation, COVID sent his meetings to a screen he wouldn't open, and one lie to a doctor for anxiety pills started a cascade that took almost all of it: Xanax, Adderall, painkillers, alcohol, the marriage, and eventually his kids. This is the whole arc, in his own words — the relapse after years clean, the year he doesn't fully recognize, and the moment that finally turned him around: his nonverbal, severely autistic seven-year-old son, Alfie, climbing over a fence and being found at the grocery store between their two houses, trying to reach his dad. Two days shy of a year clean at this recording, Stephen talks about rebuilding co-parenting with Laura “by the Al-Anon book,” the “wizard school” story he told his daughter, and what it actually took to come back. In this episode: · The dream life — Hans Zimmer's scoring team, and building Laura Clery's following from a spare camera · “I thought I had 10 years. My sponsor pointed out it was really 8.” · The three most dangerous words: “I got this” · Checking into rehab with no next of kin · The son who climbed the fence, and why it was the thing that finally worked · Co-parenting rebuilt “by the Al-Anon book” — boundaries, the restraining order, not robbing someone of their rock bottom · The “wizard school” story · Nine meetings a week, and doing AI animation with his kids now If you or someone you love is struggling, you're not alone. In the US, call or text 988 (Suicide & Crisis Lifeline) or SAMHSA's free helpline at 1-800-662-4357. Guest: Stephen Hilton — film composer & online creator Host: Tyler Ramsey Laura Clery's book, What Doesn't Kill You Makes You Hotter (Simon & Schuster) Nothing in this episode is medical advice; it's one person's story. 0:00 The Life He Blew Up 2:27 “I Thought I Had 10 Years. It Was 8.” 5:25 One Lie for Anxiety Pills 6:17 The Three Most Dangerous Words 10:22 “I'm Not Going to Do What You Say” 14:29 Rehab, and No Next of Kin 15:48 Two Rehabs at Once 20:05 The First Rock Bottom (Years Earlier) 48:38 The Son Who Climbed the Fence 50:18 What Kids Remember 53:10 Wizard School 62:40 Co-Parenting by the Al-Anon Book #PunkRockSober #PainfulLessons #StephenHilton #LauraClery #Sobriety #Recovery #Relapse #CoParenting #Autism #MentalHealth

Episode 425 of Tom Clark's Main Event is the SummerSlam Review. Tom is joined by Chris Patton from Bachman's Basement and Double Meat Palace for a look at WWE's massive two-night event, with a complete rundown of the card, including KO's return, Nick Aldis's in-ring debut, and both World title matches. Plus, the guys cover AEW Grand Slam Mexico, focusing on Will Ospreay's main event match vs. Mark Davis. All that and a lot more! Boink Studios podcasts are created by humans. All hosts featured on our shows are human, and all podcast artwork, logos, and creative direction are created by humans. Subscribe on YouTube: https://www.youtube.com/@boinkstudios Visit us at: https://boinkstudios.com Appreciate the content? Support the channel: https://buymeacoffee.com/tomclark Follow the Main Event: Facebook: https://www.facebook.com/tomclarksmainevent Bluesky: https://bsky.app/profile/boinkstudios.bsky.social Listen to Boink Studios' Podcasts: Tom Clark's Main Event: https://podcasts.apple.com/us/podcast/tom-clarks-main-event/id910362334 Tom Clark's 6M Podcast: https://podcasts.apple.com/us/podcast/tom-clarks-6m-podcast/id1441274603 Bare Mode: A Podcast Review of The Bear: https://podcasts.apple.com/au/podcast/bare-mode-a-podcast-review-of-the-bear/id1828513020 Two Nations Under Ted: A Ted Lasso Podcast: https://podcasts.apple.com/us/podcast/two-nations-under-ted-a-ted-lasso-podcast/id169387035   Music by Mr Maph aka Dogman Rukus, PPL 0103166534, PRS 1136021800 © Boink Studios 2026

After four months away, Robert Santana is back—and a lot has changed.The Weights and Plates Podcast has officially evolved into Strong and Sleek, a new name and brand built around the idea that getting stronger, looking better, and building a more durable body doesn't have to mean living in the gym or chasing extreme numbers.Robert opens up about why he closed his old South Phoenix gym, moved to North Scottsdale, and built a completely new training environment. He explains the philosophy behind Strong and Sleek, why he wanted a more balanced and accessible approach to strength training, and what he's learned about the biggest obstacle facing most people: not motivation, but time and recovery.He also gets unusually candid about a major personal change: after years of training and making progress without steroids, Robert started testosterone replacement therapy earlier this year. He explains why he made the decision, what changed, what didn't, and how much testosterone actually contributed to his recent strength gains—including new PRs on the deadlift, bench, squat, and press.Along the way, Robert tackles genetics, muscle-building potential, weight cycling, recovery, aging, the realities of natural strength training, and why Instagram fitness promises don't apply to most people.The podcast isn't dead. It's evolving.Strong and Sleek is the new name. The mission is still the same: get stronger, get healthier, look better, and build a body that can handle real life.

Winning Nuno Bettencourt's “Play With Me” challenge at the age of 14 — and catching my attention just two years later at a semi-secret guitar event in Los Angeles — RANGGA RINGROSE has a fiery brand of shred guitar that is turning heads. He even caught the ears of Mr. Paul Reed Smith, who has made the young Southern California guitar phenom an endorsing artist. Now, having reached the whopping age of 17, Rangga becomes the youngest player ever to be featured on No Guitar Is Safe podcast, where, as you'll hear, he blazes on various PRS guitars for you, as I try to figure out how he became so good so fast. Huge thanks to GuitarPlayer.com for making this episode happen. To play better and sound better, follow Guitar Player ... and this podcast! — JUDE GOLD, host and creator, No Guitar Is Safe

Stop chasing cheap metrics in your youth only to end up a broken, thirty-five-year-old former athlete who doesn't even know how to properly brace. When high school geometry teachers double as strength coaches, young lifters pay the price decades later with wrecked spines and destroyed joints. Mark Valenti spent seventeen years on the road as a professional Highland Games athlete and Strongman before realizing that the real test of strength begins when the competition stops and you have to rebuild your movement from the ground up. INSIDE THIS CONVERSATION The Three-Phase Motivation Trap: How strength athletes cycle through vanity, money, and avoiding shame throughout a competitive career. Conjugate for Throwers: The exact Westside Barbell adjustments Louie Simmons gave Mark to build world-class power. The Highland Games Reality: Why competing twenty times a year develops elite competitors faster than powerlifting alone. Bracing vs. Breathing: The fundamental core stability mistake that continues to ruin everyday lifters and former high school athletes. Life After the Platform: How to lose one hundred pounds, restore joint mobility, and keep setting new PRs without destroying your body. MEET THE GUEST Mark Valenti is the owner of Blind Dog Gym and a StrongFirst Certified Elite Instructor and Team Leader with more than eighteen years of experience as a professional Highland Games heavy-events athlete. A former world-record holder in the sheaf toss and member of the 2008 World Team Champions, Mark built his strength under throw legend Jud Logan and trained directly at Louie Simmons' Westside Barbell. After retiring from professional competition, he transformed his philosophy of training—earning the 48 kg Beast Tamer Challenge, lifting the legendary Húsafell Stone in Iceland, and pulling a three-times-bodyweight deadlift after age fifty to prove that true performance is built for a lifetime. FIND MARK Website https://blinddogstrong.com Instagram (Mark Valenti) @mvalenti100 Instagram (Blind Dog Gym) @blinddogstrong Podcast The Refined Savage Become an elitefts Channel Member Get early access to Dave Tate's Table Talk, exclusive content, and member-only perks. ➡️ @eliteftsofficial Support Dave Tate's Table Talk Full Crew Access https://www.elitefts.com/join-the-crew Limited Edition Apparel https://www.elitefts.com/shop/apparel/limited-edition.html Programs & Exclusive Content https://www.elitefts.com/shop/dave-tate-s-table-talk-crew.html TYAO Coaching Application https://www.elitefts.com/dave-tate-s-tyao-application Best-Selling elitefts Products Pro Resistance Training Bands https://www.elitefts.com/shop/bands.html Specialty Barbells https://www.elitefts.com/shop/bars-weights/specialty-bars.html Wraps, Straps & Sleeves https://www.elitefts.com/shop/power-gear.html Official Sponsors & Discounts elitefts — Save 10% OFF with code TABLE TALK https://www.elitefts.com/ Marek Health — Save 10% OFF Labs with code TABLETALK https://marekhealth.com/tabletalk LMNT — Get a FREE 8-Count Sample Pack http://www.drinklmnt.com/tabletalk ChiliPad 2.0 — Save Up to $255 with code TABLETALK https://sleep.me/tabletalk Visionary Meals (Official Meal Prep Partner) — Save 10% OFF with code TABLETALK10 https://visionarymeals.com MASS Research Review — Save 20% OFF with code ELITEFTS20 https://massresearchreview.com/ RP Hypertrophy App — Save 10% OFF with code TABLE TALK https://rpstrength.com/pages/hypertrophy-app Support Massenomics https://www.massenomics.com/

In this episode, Dave and Jamison answer these questions: I work for a small software company on a team of about 7 or 8 engineers. I like working here. I like the people, the autonomy, the pay, my boss, and the stack among other things. I try to remind myself of this regularly so I don't take it for granted. I've been here for about 2.5 years and would love to continue working here. Our CTO, like many, has become a big AI cowboy coder. Every few months, he vibe codes a new project and then decides to interrupt the full workloads that we have a limited number of engineers to do to hand his project off to be cleaned up, worked into the product, and solve all of the problems that remain once actually put into practice. This usually ends up going to a different engineer per project, who is then tied up with the CTO's whims and is no longer available to do the work planned by product. Our EM knows this and knows the frustration and lost velocity, but what can he do? (rhetorical, not the question) Most recently, I was tasked with implementing some reporting dashboards he did into the product, but he specifically asked me to make it in such a way that he can continue to work on and add to because he can't be bothered to run the actual product. This is very concerning to several of us. He has no clue what he's writing or how bad it is. We've talked about perhaps making him do PRs, but a) who can make him, he's the CTO, and b) he'll have no clue what to do with PR pushback given that he has no clue what he wrote. And again, who can make him actually fix it if he asks us to rubber stamp it? (rhetorical, not the question) I've been listening to the show for years and I've talked to friends at other companies, so I know this is everywhere. Is it as everywhere as it seems? Is it worth finding a new place to work where the CTO isn't running so rampant? As I stated before, I'd rather not leave, but if I talked about that as a concern, I don't want it to sound like an ultimatum, even if maybe it is at some level. Is this just the new reality for us, or is there something that can be done? I am a senior software engineer at a big tech company. I live in central Europe but my team is in the US and I'm 9 hours ahead. I have 7:30 pm meetings and sometimes take an hour before and/or after this meeting to prep or follow up. Previously I slept in later and started later to deal with these meetings. However, now my daughter is starting kindergarten and I wake up early (5-6AM) to be with her, drop her off, etc. Now in the evening meetings my brain is fried and I can't even articulate myself well. The next day I think about so many things I wish I had said in those meetings. I can't quit as I make 160K right now and I would only be making 60-80K tops in my country and have some financial commitments. Relocation to the US is also not an option because I have kids and don't want them to move. So far I have been skipping meetings and my manager has not expressed concern but I feel so detached from my team. I don't even know what most of my peers are working on. It feels like I am out of ideas to make this better. Please share your space wisdom with me :)

Watch the full episode on YouTube:We first covered Baseten last year when DeepSeek mania was at peak hype. Now they have raised a monster $13B round and become one of the new cohort of AI Infra decacorns that are (with Nvidia, Intel, and the semis complex) chief beneficiaries of the Inference Inflection. We return to Baseten at the peak of the 2026 edition of Open Weights debate. Ali has published a viral breakdown of Kimi K3:And since you last saw him, Philip has spoken at AI Engineer and written the definitive book on Inference Engineering spotted all over SF:Three years ago, inference engineering barely existed as a category.Today, it is one of the most critical disciplines in AI. Inference engineering inherently tackles a different question than standard model training: “How do you turn those weights from training into a product that is fast, reliable, and affordable at scale?” Focusing on these creates an entirely new optimization problem.In one recent GLM-5.2 experiment, quantizing more of the model actually preserved its benchmark quality while increasing throughput by 20%, because the errors introduced in different layers could cancel each other out.Inference is no longer just the final step after training. It is becoming its own engineering discipline, with its own research problems, infrastructure, and increasingly specialized roles.In this episode, Baseten's Philip Kiely and Ali Taha join swyx and Vibhu to explain what actually happens after a new open model is released and what it takes to turn “we generated a token” into a fast, reliable, production-ready API.We go deep on cache-aware routing, disaggregated prefill and decode, quantization, speculative decoding, KV-cache movement, model parallelism, GPU kernels, and the race to make frontier models up to 10× faster. Philip and Ali explain why inference optimizations can still produce gains of 20%, 100%, or even 200%; how quantization errors can cancel one another out; why identical weights can behave differently across clusters; and how Baseten grafted a Kimi vision encoder onto GLM-5.2 without changing the underlying language model.The conversation then expands beyond LLMs into NVIDIA Dynamo, mega kernels, Rubin, AI-specific chips, local inference, video generation, diffusion versus autoregressive models, and the enormous compute barrier to generating coherent long-form video. Finally, we explore the convergence of training and inference, continual learning through persistent KV cache, and the emerging loop where models help optimize the infrastructure that runs them.We discuss:* What happens when a 200,000-token request enters an inference system* Cache-aware routing and reusing previously computed KV cache* Why prefill and decode are increasingly handled by different GPUs* When dedicated deployments become cheaper and more reliable than shared APIs* How speculative decoding uses a smaller model to accelerate a larger one* Tool calling, structured outputs, and what LLMs actually do* What it takes to support a new open model on day zero* Grafting Kimi's vision encoder onto GLM-5.2* Retrofitting inefficient model layers with components from other architectures* Why models sometimes collapse into repeating the same token* How hardware, kernels, and race conditions create nondeterministic failures* Preserving model fidelity while making inference faster* How quantization errors can cancel each other out* Why inference optimizations still deliver gains of 20%, 100%, and 200%* How optimized serving can make a model up to 10× faster* NVIDIA Dynamo, KV-aware routing, and distributed model serving* Speculative decoding the speculative decoder* Why local AI is about making models less dumb while data-center AI is about making them less slow* Tensor, expert, and pipeline parallelism across GPUs* Hardware-aware model design, auto-tuning, and the case against mega kernels* Rubin and why inference is becoming a systems problem* Whether modern GPUs are evolving into programmable AI ASICs* Why enormous models like Kimi K3 require GB300-class hardware* Why open-source video generation still trails Veo, Kling, and other closed models* The quadratic attention bottleneck behind long-form AI video* Autoregressive video, real-time generation, and compounding quality drift* Why future video systems may combine autoregressive and diffusion architectures* Training for inference and inference for training* Continuous post-training, deployment, evaluation, and improvement loops* How GLM-5.2 helped optimize the kernels serving GLM-5.2 itself* Why faster networking could unlock dramatically faster decoding* Continual learning, KV-cache compaction, and persistent model memoryShow Notes* How to build a day-0 API for Kimi K3* 22580: From GPT2 to Kimi3, ExplainedPhilip Kiely* LinkedIn: https://www.linkedin.com/in/philipkiely* X: https://x.com/philipkiely* Inference Engineering: https://www.baseten.co/inference-engineering/Ali Taha* LinkedIn: https://www.linkedin.com/in/aliestaha/* X: https://x.com/waterloointernTimestamps00:00:00 Introduction and the 200K-Token Prompt00:03:18 Dedicated Deployments, Speculative Decoding, and Tool Calling00:11:26 Launching Production-Ready Open Models00:19:06 Model Retrofits, Failure Modes, and Nondeterminism00:28:22 Quantization and Canceling Errors00:32:15 The Race to 10× Faster Inference00:40:48 Dynamo, Speculation, and Local vs. Data-Center AI00:50:18 Model Parallelism, Auto-Tuning, and Mega Kernels01:00:55 Rubin, GPUs vs. ASICs, and Custom AI Chips01:10:03 Giant Models and the Limits of GPU Memory01:12:42 AI Video, Quadratic Attention, and Autoregressive Generation01:21:47 Audio, Images, and Diffusion Models01:27:32 Training, Self-Optimizing Models, and Continual Learning01:40:06 Closing ThoughtsTranscriptIntroduction: Baseten, Waterloo Intern, and Inference EngineeringSwyx [00:00:00]: Okay, we're here in the studio with Philip, old friend from Inference Engineering, the book, as well as Baseten and everything that you've done, you and I have done before, as well as Ali. Welcome.Ali [00:00:15]: Pleasure to meet you.Swyx [00:00:15]: Waterloo intern.Ali [00:00:16]: Waterloo intern, always.Swyx [00:00:17]: When did you get “Waterloo intern” as a handle?Ali [00:00:19]: As a handle? Oh.Ali [00:00:20]: I think the rebranding happened mid-March. When I saw it was open, I was like, “I have to take it. Up for grabs.”Philip [00:00:26]: The problem is that Ali is really good at his job and is not gonna be an intern much longer.Philip [00:00:30]: So we have to figure out who's gonna get the handle.Ali [00:00:33]: Well, I'll pass the torch over to the next intern.Swyx [00:00:34]: Oh, okay. It can be, like, you just pass it to another Waterloo grad.Ali [00:00:37]: To another Waterloo intern. No, bruh.Philip [00:00:39]: Yeah.Ali [00:00:39]: Intern.Swyx [00:00:40]: Intern, yeah.Ali [00:00:40]: And no.Philip [00:00:41]: You gotta get an intern from Waterloo.Ali [00:00:42]: Yeah, I've gotta get an intern from Waterloo.Swyx [00:00:44]: Right.Ali [00:00:44]: But they have to follow the path.Swyx [00:00:45]: Oh, it could, but it could come from Baseten, so it's like whoever Baseten gets from Waterloo.Ali [00:00:48]: Right.Swyx [00:00:49]: Has the title of Waterloo.Ali [00:00:50]: It stays in the ecosystem.Philip [00:00:51]: Exactly.Ali [00:00:52]: Halfway through the internship, you either get it or you're out.Philip [00:00:55]: You should also do, like, a big graduation ceremony where you change the handle.Ali [00:00:59]: Just say it.Philip [00:00:59]: For everybody.Swyx [00:01:00]: You guys are good at ceremonies, clearly. We had a nice launch of the book, very successful. But before we get into all that, I wanna start off with a fun question for you. Okay, you're an expert inference engineer. What happens when I send a long query, say two hundred thousand tokens into Baseten's inference? What's the process of query through GPU model routing, balancing, all that? What is all the stuff that we don't think about?Long Context Requests, KV Cache, and Cache-Aware RoutingPhilip [00:01:26]: With a long query specifically, the first thing that I'm gonna ask is, “Have you sent me this query before, or at least part of it?” and I really hope you have, because it's gonna be a lot easier for me and a lot cheaper for you. So the first thing that we're gonna look at is some cache-aware routing, where we're going to see, we probably have a number of instances, a number of replicas up serving whatever model you're hitting. We want to send this one to something with, number one, available prefill workers, and number two, ideally some cached input already there so that we can skip prefill on at least part of these two hundred thousand tokens. If you're doing two hundred thousand tokens, it's probably coding or a multi-turn agent or something where you would expect to have that cached. If you don't, we're gonna have to send it to a prefill worker. We've at least on certain models disaggregated prefill and decode, so you're going to have one set of GPUs that's solely going to process the input, create the KV cache, and get you your first token, and then that's going to be passed over to a separate set of GPUs, which is going to run decode. We're going to iteratively make those tokens. We're probably going to have some speculator model in front of that. I'm going to assume that you're doing coding, and because of that, our speculator model, which assumes you're doing coding, is gonna have a high draft token acceptance rate. If I'm wrong and you're asking me to summarize every Harry Potter book, it's gonna be slower. And then we stream that output to you and account for it, charge you, a couple of pennies and say, “Hey, would you like to send another one?”Swyx [00:03:04]: Except Baseten doesn't charge by pennies.Philip [00:03:07]: Well, yeah, we charge. I'm assuming that we're talking about the public model APIs. If you are setting up a dedicated deployment, then yeah, it's not pennies.Public APIs vs. Dedicated DeploymentsSwyx [00:03:18]: Yeah, one of the key differentiators when I was talking with Baseten initially was that people who want very high volume just need to rent by the box, ‘cause then it's up to you to figure out how to saturate the box.Ali [00:03:31]: And more often than not, it's, like, way cheaper if you're pushing, like, millions of tokens per hour, if you just pay per hour instead of pay per token.Philip [00:03:37]: Yeah, they do. I think that we've increasingly seen a lot of demand for the pay per token APIs, just because everyone wants to try open models, and then once they find a use case that's really sticky, then they move over to dedicated.Swyx [00:03:51]: Is there a best practice on when it's time to swap over?Philip [00:03:54]: Couple reasons. Yeah, reliability, that's a big one, right?Ali [00:03:57]: Like, if they have a very specific use case, they want you to train something specifically for them, like they want their own spec dec, for instance, for their own traffic.Swyx [00:04:04]: Spec dec is speculative decoding.Speculative Decoding and Custom SpeculatorsAli [00:04:05]: Speculative decoding, yeah.Swyx [00:04:07]: You have to explain.Ali [00:04:07]: Sorry. Like, speculative decoding is like, if you have a huge model, right? And so the model is going to be generating one token at a time every single turn, every single forward pass. So we attach, like, this little, like, parasite, like this layer that goes on top of the model, and this model just has to predict. It does three very fast autoregressive forward passes, and it will predict, like, three certain tokens, and then you do one forward stage over the entire original model in order to see if those predictions were correct or not, and then you accept them or you reject them. Now, this draft model is traffic specific, so if you, like, Philip said, if you're summarizing Harry Potter books, I can train exclusively that draft model on Harry Potter books, and I can guarantee you that I'm gonna accept the three tokens every single time. And so with that case, I increase your decode speed. I wouldn't be able to provide this to you if you're a shared endpointSwyx [00:04:53]: YeahAli [00:04:53]: ‘cause I have no idea if you're doing Harry Potter, if you're doing coding, if you're doing English. We don't know. Also, there was a thing in the book that mentioned that if they really cared about a specific threshold, chapter four, I think. Do you remember that?Philip [00:05:06]: Yeah. The things that you can do is you can set a specific, like, batch sizing, a specific, like, parallelism strategy if you're trying to optimize for, like, throughput versus latency. You can. Maybe a NVFP4 quant doesn't pass your benchmarks and you wanna run a model at higher precision, you could do that. There's just a bunch of reasons why you might wanna have your own endpoint and the biggest one, of course, just being, like, you don't have to deal with someone else doing a hundred million tokens of benchmarking traffic at the endpoint when you happen to be trying to serve your users.Swyx [00:05:40]: Yeah. I think one thing that is. That is a classic journey. Like, it's people is asking the, what happens when you type Google into the browser. Tool calling, is that just, you're generating JSON or is there more complication beyond that?Tool Calling, JSON, and Structured OutputsAli [00:05:58]: Certain customers that we have, they have their own post-trained models, and so they demand a tool calling that's not just, like parse a file or go find the weather. It's something that's very specific and you have to do post-training on this. And if the post-training on the model is not good or if the quantization after the post-training to get the inference to be fast, the model will struggle reading the JSON file and reading the tool calling. But it doesn't require its own like sandbox. It's not like it's going to use that tool calling to like escape a sandbox or like it doesn't have to be contained. It can just be a normal dedicated deployment. The challenge with tool calling more and more seems to be that the companies want certain tool calling which is a very sensitive thing to train. And because you're dealing with all of the JSON outputs, if it doesn't like close the end of the request in a very certain manner, you end up with a model that did the tool calling and like the thinking and so as a result of that, it didn't see the result and just hallucinated the result as it decoded. That seems to be the most challenging thing with tool calling, not really the sandboxes model.Philip [00:06:56]: Yeah, that's a challenge on the training side and then on the inference side, there's work that you can do to scope the possible output. So we published this at this point close to two years ago, the solution to this problem which is you make a state machine and you use that to constrain the output to a specific format. So this is the structured output problem. If you remember backSwyx [00:07:27]: Yeah, the specific grammar is,Philip [00:07:29]: Yeah, exactlySwyx [00:07:30]: GML had this thing.Philip [00:07:31]: Yeah. So it's like the old-school “make sure this is only JSON”, return only JSON orSwyx [00:07:38]: YeahPhilip [00:07:38]: Grandma's gonna die type of prompts.Swyx [00:07:39]: Is it BNF grammar? At some point OpenAI had released a thing that was like, yeah, if you want to constrain your output, write BNF grammar, back as NOR.Philip [00:07:47]: In our inference system, it's just a specified output format. And you get the guarantee that your output's gonna be structured along that format. And so applying that to tool calls can like help cut down on. You can still call the wrong tool or call no tool. It doesn't solve the certainty problem but it at least solves the output structuring problemSwyx [00:08:10]: YeahPhilip [00:08:10]: Within tool calls.Swyx [00:08:12]: And MCP is just another form of tool, right.Philip [00:08:14]: Yeah, exactly.Swyx [00:08:15]: As far as there's no special thing there.Philip [00:08:16]: The thing I'm always like explaining to people is the LLM is not capable of doing anything. It's only capable of making suggestions of what to do and then if those suggestions are formatted in a certain way and applied to a system that knows what to do with them, then an action occurs.Swyx [00:08:32]: Yeah. Part of the fun stuff is, this is solved outside of tool calling too. Like in an agent loop if the output is not correct or you're right, like reasoning, tool calling was done in the reasoning trace, just be like, “Oh, I don't know what to do. Let me just try again.” And it might get there after a few tries. And on your point of training, sometimes this is harder in smaller models, so you don't have the same exact quality outputAli [00:08:56]: Right.Swyx [00:08:57]: When you just swap from a big model, right?Ali [00:08:59]: Yeah. I will say that, before, I think we need to go back to inference engineering proper.Ali [00:09:04]: But, I had expected that something would replace JSON because it's hard to stream JSON ‘cause JSON must be complete and you must have open and close brackets and everything. So it's hard to parse something or validate something while it's being streamed. So people invented all sorts of things that are like, I forget the name of some of these alternatives, but it's something like TOML, something like YAML. But JSON seems to be dominant still.Philip [00:09:30]: The JSON outputs aren't that long, right? Like you could have a long-- ‘cause tool calls also contain the arguments in them and perhaps for a certain tool you might pass like a very long argument. But my impression of the median tool call is that it's a relatively small number of tokens, right? So I would expect that speculators are generally fairly good at something as formatted as JSON. And so you would have like a pretty fast decode step there and that the streaming wouldn't be as valuable, but maybe I'm wrong about that.Ali [00:10:02]: I think you're also bounded by the software or that the model is gonna integrate with if the software is built with JSON for the tool calls or if the company that you'- if your customer says that this is how our software works and our tools are interfaced with JSON, you can ask them to like, change their software and say like, “Yeah, this is gonna be better for the model.” but like with the right training shouldn't be that much of a difference. Also more profitable if it outputs more tokens probably.Swyx [00:10:25]: Depends on your business model.Swyx [00:10:27]: It really depends. But I will say that, as a writer with like experience a lot with generated output, I do try to move from text to JSON text which is very long JSON, right? Like there's paragraphs in every field because I'm trying to structure it, right?Philip [00:10:44]: Right.Swyx [00:10:44]: I want you to first make factual statements, then make opinions then make bullet point summaries, have dates, have entity references have your sources for references, all these things. Anyway, so these are things that like I think people who really experiment with structural output have to really care about. But, let's, let's recurse up the stack a little bit. Before we started recording, you mentioned something really cool, which is that there's a lot of engineering that-- inference engineering that goes on when a new model provider releases a new model, right? So let's call it GLM-5.2, Kimi K3. I had previously assumed, especially if it's like, well, GLM 5 to 5.1 to GLM-5.2, like that you've supported them before. Is it that much work?What It Takes to Support a New Open ModelAli [00:11:26]: It's a lot of work.Swyx [00:11:28]: Yeah. Okay. So like, a lot of people, all you guys, right whenever a new model launch like, people rush to say like, “Oh, Hugging Face supports this, Fireworks supports this, Spacetime supports this,” and I'm like, “Yeah, of course we support it.” But what goes into that? What goes intoPhilip [00:11:40]: I think it's more than just support it too, right? It benefits the consumer a lot. Like I think it was with Kimi K2.5 or GLM-5.2 the latest, there was an inference war, right? X provider is at 90 tokens a second. The next day we're at 150. The nextSwyx [00:11:55]: I kinda kicked that off with the GLM-5.2.Swyx [00:11:58]: I wrote a Twitter article about. It got like half a million views,Ali [00:12:02]: Based on being numberSwyx [00:12:03]: YeahAli [00:12:04]: Or it's for something else.Swyx [00:12:05]: Yeah. Which,Ali [00:12:06]: Oh my GodSwyx [00:12:07]: Which then got everyone really excited about, hey, how can we, bend tracks a little bit further and,Philip [00:12:14]: There's a difference between support the model, as in I can make a token out of this model, and support a model, as in I have a production-ready API from this model.Philip [00:12:26]: Getting to the point of I can make a token out of this model is not that hard because generally the, open source inference engines, vLLM, SGLang of the world oftentimes even receive weights ahead of time, maintainers do, or the people making the model merge PRs to ensure support. So you generally can, just get it working on the standard open source stack without too much pain in most cases. The challenge is, every inference company is gonna have own proprietary stack. Some open source components, some in-house stuff. And for any arbitrary model, there's going to be some new stuff. Sometimes you get lucky, like K, two five to two six was, like, pretty similar.Quantization, Speculators, and Production ReadinessAli [00:13:16]: Yeah. It was pure continued post-trainingPhilip [00:13:18]: YeahAli [00:13:18]: If I remember correctly.Philip [00:13:19]: Even in those cases, there's still stuff you have to do. You have to redo the quantization work. You're taking the model from. Generally, these models are not released in NVFP4, and we want them to be in NVFP4 for maximum Blackwell compatibility. So we have to perform that quantization, and, calibrate the quantization to make sure that we're not causing any regression in the model's intelligence. And then we also have to train the speculator, as we've talked about. Generally, we have. We have ZDR, zero data retention on our model APIs, so we don't know exactly the traffic that people are sending us, but we know what's popular. We know that coding use cases are popular. We know that agents, agentic use cases are popular. So we can get public data sets that are representative of that traffic and train general speculators. Now, with speculators today, you need to train the speculator using the base model itself because you're getting hidden states out of the model from running inference on these specific prompts, and that is the training data you use to create the speculator. So there's that process which you need the real model weights for. And then there's of course just the process of, standing up all the infrastructure behind it, loading all this stuff, testing it. And then when there's a new model with a newer architecture, I think that, like, the DeepSeek models tend to be the most challenging as they have, like, the most novel architectural stuff going on, model after model. But every new model has something. Kimi K2 had. Oh, sorry, GLM-5.2 hadAli [00:14:53]: Sparse attention.Philip [00:14:54]: Yeah,Ali [00:14:54]: YeahPhilip [00:14:54]: the DSA.Ali [00:14:55]: Right. Which is brought from DeepSeek.Philip [00:14:57]: Yeah. AndAli [00:14:59]: So you can copy-paste then?Philip [00:15:01]: It kindAli [00:15:01]: I don't know how this works.Philip [00:15:02]: So, like we had to, like, build support for that into our runtime. And you're right, like it is really interesting the way that all of these open source labs borrow from each other. For example, like GLM-5.2 doesn't have vision. So something that, Haley, a guy on our team, if we could take a look at this, he, like, grafted the Kimi vision encoder onto GLM-5.2.Retrofitting Vision into GLM-5.2Ali [00:15:27]: We'll be training the projector.Philip [00:15:28]: Exactly. So if you think about, like, the encoder, there's the encoder, which is the part that looks at the image and turns it into latent information, and then there's the projector which likeAli [00:15:38]: You can say latent space. It's okay.Philip [00:15:41]: And then there's the projector that maps it onto, the model itself, and then there's the model weights. You don't wanna mess with the model weights because you run a chance of making the model dumber at something else for the purpose of giving it vision. So instead, Haley started with just a projector, which is only a handful of millions of parameters.Ali [00:16:02]: That would be, yeah.Philip [00:16:02]: Yeah.Ali [00:16:03]: Can you show the training one?Ali [00:16:04]: Like the way it groksPhilip [00:16:05]: YeahAli [00:16:06]: Very interesting.Philip [00:16:06]: And maybeAli [00:16:07]: That right therePhilip [00:16:07]: Maybe Ali, you should take it from here. You've got a betterAli [00:16:10]: Ooh, double the sandPhilip [00:16:11]: Understanding of this than I do.Ali [00:16:11]: Yeah. You can see, like, he. The way he trained this is really cool. At the beginning, he was training it using just like, “Here's a picture of a mountain. Can you describe what's in this mountain?” And that caused it just like the first, learning walls. Like here you can see this all we're trying to teach it is to translate the encoded. Like it's already taken the encoder from Kimi K. It's taken the image. It'Philip [00:16:31]: Yeah. FrozenAli [00:16:31]: FrozenPhilip [00:16:32]: With adapter.Ali [00:16:32]: Exactly.Philip [00:16:33]: Yeah.Ali [00:16:33]: So the brain is frozen and the eyes are frozen. It's just we're tryingPhilip [00:16:37]: AlignAli [00:16:38]: Interconnect between the eye and the brain, right? So the projector. And so you take the tokens and then he's like, “Oh, can you describe what's in this image?” And he's like, “Oh, it's a mountain,” or it's a person or it's a human, whatever the case is. But that didn't cause complete understanding. So he changed it such that every image was associated with a data set of questions. Like, does this image have a white male? Does this image have birds in the top corner? Does this image have a scientist in it? All of that stuff. And it would have to answer questions correctly. And using not just training on describing an image, but being able to answer question, another question, answer over time. Like you can see the grokking, which is like genuinely insane, that retrofitting vision into a large LLM can learn to that extent. And even for images that it doesn't perform well on, for instance, if you ask it a picture of like Stephen Hawking, “Who is this?” Maybe it doesn't get it, but it will say something like, “This is Albert Einstein.” Like it still understandsPhilip [00:17:25]: Close enoughAli [00:17:26]: That this is a scientist who is a man who has, some significant achievements, all that stuff. So that's like really cool.Philip [00:17:32]: Yeah. So, we've covered Hao Tian before, who the author of the LLaVA paper that did this, a while ago. And I think that's very foundational work for anyone who hasn't done vision work before.Ali [00:17:41]: Same with the CLIP and MetaCLIP, where you go from just captioning to building out questionsPhilip [00:17:47]: RightAli [00:17:47]: Off the image and how much better you can get performance.Philip [00:17:50]: Right. Right. Right. Yeah. But what's, what's so exciting about this is if you look at a model like this. Now, this is a little bit more of a research project. It's not. It got to 56% on MMLU Pro, I think. So not quite frontier. But if you're running this model, you haven't suffered any loss on your GLM-5.2 quality. If you don't have an image, it'll just behave exactly the way it used to. And ultimatelyAli [00:18:14]: Which in the inference code you literally do not include the other part, right?Philip [00:18:18]: Yeah. You would just skip the encoder if you don't have an image input.Ali [00:18:22]: Okay.Philip [00:18:22]: Just confirming.Philip [00:18:23]: YeahAli [00:18:23]: Does it affect a lot on the overall inference side? Like you're not adding much, you're adding a very small vision encoder. These are typically likePhilip [00:18:30]: They're super fineAli [00:18:31]: Less than a billion parameters, right?Philip [00:18:32]: Yeah. It's, - There's a little bit less standardization among vision encodersSwyx [00:18:37]: YeahPhilip [00:18:37]: So the support matrix can be a little bit, sparser. But overall, yeah, it's a pretty, it's a pretty minor component of the overall system. And ultimately what you get out of the system is all of a sudden you have Kimi Vision, GLM weights, and DeepSeek attention all in one model.Open Source Model Grafting and Franken-MergesPhilip [00:18:56]: And that's, I think, a lot of the power and beauty of open source, is that you can take all of these different components and combine them together into a system that's better than anyoneSwyx [00:19:05]: YeahPhilip [00:19:05]: Can be individually.Swyx [00:19:06]: People used to say that you would also do Franken-merges where you would take likePhilip [00:19:10]: YeahSwyx [00:19:10]: Layers from each model.Swyx [00:19:11]: Does anyone do that anymore?Ali [00:19:13]: Well, to your point previously when you were mentioning like, the work that goes into supporting a model when it first comes out, like GLM-5.2 or MiniMax M3 or whatever the case is. Sometimes you do have to like, you do have to switch out some things. Like, for instance, the MiniMax M3 head uses full attention, and with full attention you end up with this like insane bottleneck in spec dec ‘cause you're doing auto-regressive token generation for three tokens, and you're doing this like N squared over all of the tokens that are in your sequence. Your KV cache is like very large because it's not sparse, it's not top K. So we find it better to like, okay, we're gonna replace this, we're gonna replace this layer with a layer from another model that's using like GQA, for instance. And then just with the right training, you can get it to have the same acceptance rate. So it is very possible to retrofit layers from other models and very much needed. If a layer is like inefficient, the training just becomes the challenge, like how do you ensure that you train it properly? Which again to your earlier point is like the mesh between training and inference. As in like you need very good training in order to do fast inference. That's like, I feel like more and more becoming true.Swyx [00:20:21]: Yeah. Anything else on the support side when you say like get it to fully production ready?Loop Detection, Race Conditions, and Non-DeterminismPhilip [00:20:26]: Yeah. I think that there's also a question of just, we can test a model to a pretty extensive degree, but we're trying to get it out quickly and then you see a bunch of other people test it and you get interesting results. There was an issue with, GLM briefly where we had some like mode collapses where it would just output the same token over and over again for certain prompts on certain temperatures. Like once you expose an endpoint to the real world, there's going to be, so many more varieties of things given to it that you're able to, discover and patch things. So it's not just a, day zero process, it's then like for the first week, for the first month, if a model remains popular, like how do you both fix bugs and then continue to push the envelope on performance?Ali [00:21:21]: What do you mean you don't want your model outputting S?Swyx [00:21:24]: Is there loop detection on that stuff, by the way? It still happens like quite a lot, which is surprising.Ali [00:21:30]: We have like we, in our endpoint, like if a model was to output the same token like four plus times, we just cut the generation. We say like, “Oh, sorry, this-- Like try again,” or like we will reprocess the request. ‘Cause we know then, like if it, like if, yeah, it's four times the same token, it's probably collapsed.Swyx [00:21:45]: Yeah. Is there a way to opt out in case I really want that?Ali [00:21:48]: You want that?Ali [00:21:50]: I think there's a way that we have to handle it. I'm not exactly certain, but I feel like in certain models, like when they output something like you can imagine, like a table for instance, and so they want, they wanna draw like 12 dashes and 12 dashes. Yeah, I think there's a way for that to happen. I think we only do it on certain tokens. Like we exclude certain special characters.Swyx [00:22:07]: Yeah.Ali [00:22:07]: So we only do it on like certain like S is the most common almost. GLM-5.2Swyx [00:22:11]: OhAli [00:22:11]: And I think it was DSV 4 as well. Like you'd just have like looping issues where like you literallySwyx [00:22:17]: ItAli [00:22:17]: Just have like S.Swyx [00:22:18]: Yeah. Is there a special, something special about S? No, just randomlyAli [00:22:21]: It just seems to be the one token involved.Swyx [00:22:23]: Yeah. And it'Philip [00:22:24]: Is thereSwyx [00:22:24]: And it's only temperature 0Ali [00:22:27]: NoSwyx [00:22:27]: Even at other temperaturesAli [00:22:27]: Even at like 0.9 or whatever, it will still, it will still collapse.Swyx [00:22:30]: That's weird, right?Ali [00:22:30]: It's, it is an inference problem to be honest, like a software problem. Like oftentimes, the image you run will-- like NVIDIA will release an image for instance, and if we will upstream the changes from their latest TensorRT-LLM image into our stack, we'll find that it fixes it. Or oftentimes this will only happen in an inference engine that you're using like SGLang. But if you were to switch to vLLM, that isn't the case. So it seems to be like an extremely like deterministic software issue and not really a model issue. It's not like a weights problem. Like I'- we'll say like, “Oh, it's a problem with the quant. We did PTQ wrong,” right? But that isn't, that doesn't make sense because the same weights used with a different inference engine does not repeat the problem. And sometimes it's, the kernels that are being used in the backend have like these very subtle sometimes race conditions, where if you were to use this model hosted on one cluster, you will never get this problem.Swyx [00:23:19]: Oh my God.Ali [00:23:19]: But if you host it on a different cluster, you will. And the reason is the KV cache transfer from a node to node in that one cluster is using a slower interconnect than the node to node in another cluster. So that exposes the race, whereas in another cluster it doesn't. So then you end up just like, okay, this model is not gonna be hosted on this cluster. We're gonna host it on, another cluster because that cluster exposed that problem. But then it ends up with like, okay, is it the software? Is it the model weights or is it the hardware?Swyx [00:23:42]: There is a thing about this with temperature 0 still not being deterministic, right?Ali [00:23:46]: Right.Swyx [00:23:46]: Mostly because of hardware. Even at temperature 0 same model, you won't always get the same output.Swyx [00:23:52]: Even-- But I'm surprised by the race condition one because, I thought PyTorch was a graph that like guarantees that you at least, execute things in the right order.Ali [00:24:02]: Well, yeah, true. Like I'm not, I'm not saying that there is. Like well, you have things like PTL optimizations where like you can start a kernel before the end of the previous kernel, and that's like ‘cause you want to do that because there'sSwyx [00:24:12]: It's like pipeliningAli [00:24:12]: Expense. Exactly.Swyx [00:24:13]: Yeah.Ali [00:24:13]: But it'- But you don't do it cleanly. Like you overlap a little bit of the execution. No, it is very possible that the kernel itself, like that one block that is supposed to be running in this instance of time, that kernel itself has a race condition. For instance, like a missing barrier. Like often if you're designing a kernel and you want it to make it to be very fast, if you don't test it extensively, you'll, you'll have certain threads access data points from registers before they've been written to by other threadsSwyx [00:24:36]: YeahAli [00:24:36]: For example, because like your barrier is wrong or your synchronization was wrong. But yeah, like the testing itself is very difficult in those like, andSwyx [00:24:42]: And there's no like borrow checkerAli [00:24:45]: What does that mean?Swyx [00:24:46]: Like Rust. Like the. If you're trying to have like memory safety It sounds like a comparable problem.Ali [00:24:52]: Well, yes, but you're working in CUDA, right, NVIDIA GPUs. Like- You just need a higher level language like modular Maybe that's what modular is supposed to do. I don't know.Quantization Quality and Vendor FidelityVibhu [00:25:00]: How do you see keeping quality of the model? So you talked about all these steps of, okay, you gotta do quantization, train your own speculative decoderAli [00:25:07]: RightVibhu [00:25:07]: Run on different hardware. Looking at other model providers, okay, you kicked off a inference speed race on the consumer end. What goes into keeping quality the same across them, right? Sure, you can run benchmarksAli [00:25:22]: YeahVibhu [00:25:22]: But, like, how do you determine how much quantization are there standards? What goes intoPhilip [00:25:27]: There's a few things on quality. Most inference optimizations are lossless. KV caching, for example. You are just recomputing or preventing recomputing the same values. Speculation, of course, if a draft token is wrong, it gets rejected. The main lossy optimization is quantization. And that really comes down to, number one, data format, number two, which parts of the model you choose to quantize, which layers, and number three, like doing a lot of calibration on the quantized weights, to ensure that you're preserving all the outliers. There's other tricks that you can do, though. A big one is long context, ‘cause one thing you asked at, right at the beginning is, “Oh, what's gonna happen if I send a 200,000 token request in?” So with a long input sequence, you need to, store a lot more information. You need to process a lot more tokens. And so even if a model has a context of a certain length, you might, as an inference provider, choose to build an API with a shorter context length, and of course a full length one as well. Because if someone doesn't need the full million token context, for example, you can get them better performance. I don't know if that's exactly like quality of the model. The way that I think about quality is to what degree are we faithfully serving the original model? If you think of a golden implementation of a model that performs exactly the way the model is designed to perform, I think of quality as how close are we getting to that, 100% fidelity of the model.Philip [00:27:13]: You can also, of course, think about quality from the training side and how do you push yourself past 100%. But when I think about purely inference optimizations, it's getting faster while staying as close to that 100% fidelity mark as possible. And certainly our standard internally is that, like you should not be able to tell the difference between our API and a, official API. I think Kimi in particular does a good job of vendor benchmarking hereAli [00:27:41]: YesPhilip [00:27:41]: Where they haveAli [00:27:42]: They released an actual vendor benchmark.Philip [00:27:43]: Exactly, yeah.Ali [00:27:44]: ‘Cause they accused, some people, Amazon? There was some provider that was not doing very well on Kimi's benchmark.Philip [00:27:50]: Yeah.Philip [00:27:51]: So, with Reflect we probablyVibhu [00:27:52]: This was a long time ago, right?Philip [00:27:54]: No.Ali [00:27:54]: Yeah, like threeVibhu [00:27:55]: They alsoAli [00:27:55]: Four, five months agoVibhu [00:27:57]: This also happened with, I don't remember which model, but they pulled out quite a few, and then they started a whole chart about this. It might have beenPhilip [00:28:03]: Kimi Vendor Verifier.Ali [00:28:04]: Yeah.Philip [00:28:05]: Yeah.Ali [00:28:05]: Yeah, ‘cause you, ‘cause you'd be pissed, right? Like if you'Philip [00:28:07]: Yeah.Ali [00:28:07]: If like if I'm a consumer and I'm using like Amazon's endpoint for instance, and I've used Kimi and I'm like, “Oh my God, like this is bad,” I'm not gonna say, “Oh, Amazon quantized the model in a bad way.” I'm gonna say, “Oh, Kimi sucks.” Right?Philip [00:28:17]: Yeah.Ali [00:28:17]: So it seems like that makes sense.Philip [00:28:19]: Yeah, they care. They care.Vibhu [00:28:21]: Justifiably.Ali [00:28:21]: Yeah, justifiably.Vibhu [00:28:22]: This is probably a stupid question, but just checking, has anything improved from main quantization?Philip [00:28:28]: Yeah.Vibhu [00:28:28]: Like, is quantization always strictly worse?Ali [00:28:30]: Well technicallyVibhu [00:28:32]: NoAli [00:28:32]: It's a lossy. QuantizationPhilip [00:28:33]: YeahAli [00:28:33]: Is a lossy, it's a lossy implementation.Philip [00:28:36]: Speed improvesVibhu [00:28:36]: Speed improves.Ali [00:28:37]: It the number, likeVibhu [00:28:38]: No, I' always look for inverse scaling laws.Philip [00:28:40]: Yeah.Ali [00:28:40]: Yeah.Vibhu [00:28:40]: This is something I learned from Noam Brown, where like things that normally act in one direction sometimes do.Philip [00:28:45]: Well, technically when you run a benchmark, because these models are deterministic, sometimes your,Ali [00:28:52]: YeahPhilip [00:28:52]: NVFP4 quant is like, two basis points higher than yourAli [00:28:56]: No, it's noise. It's noise.Philip [00:28:57]: Yeah, exactly. I'm like, yeah, it's, it's within. That's why I always say within margin of error.Philip [00:29:01]: And I stopped saying that because everyone assumes that what is, well, within some margin of error, we're barely inside of that to the worst, so we're saying. But yeah, sometimes it's just like, gives you a higher output score. But like Ali said, that's noise. To my knowledge, you're not necessarily making the results better. You're just trying to, again, like keep your fidelity as close to 100% to the original model.Layer Selection, KL Divergence, and Better QuantizationAli [00:29:27]: There is, to your point, research that we did on MP. I don't know if you are able to pullPhilip [00:29:31]: YeahAli [00:29:32]: A tweet we did. One of our research interns, Joshua, I think it's a tweet on how we have 20% better quantized GLM-5.2 than NVIDIA. Essentially what we found throughout like this month research is, okay, quantization is a lossy. It's. You're compressing the data from, occupying 16 bits to occupying, four bits, for instance. And so you're losing some information, and you're trying to minimize that. And so when I say that I'm gonna quantize the model, my job becomes how do I find the layers that I can quantize, and how to find the layers to not. For instance, with image models, I don't quantize modulation layers, and I don't quantize out projections because those two are. Like out projection is what you see as the user. Modulation is what the model sees or understands. Right, exactly. And so to his paper, do you have the. It doesn't have the. Yeah. It's a long paper. I don't know if I can findVibhu [00:30:25]: If there's a part to search or it's probably in the thread.Ali [00:30:28]: It's probably in the thread.Vibhu [00:30:29]: Yeah.Ali [00:30:29]: But the long and the short is it is very possible that quantizing more of the model makes the results. Like if I have a model that I quantize layers one, five, and 10, and another model where I only quantize layers one and It is possible that the model in which I quantized more information is going to perform better because the quantization errors have canceled out. And so what Joshua showed in his mathematical proof where he had like a verifier in, is that you can predict which layers are going to have quantization errors that will cancel out with each other, and you choose to quantize those layers. And so the result of doing this mathematical quantization is you end up with a model that's 20% more quantized than another provider, so you get 20% more throughput of it because there's more layers than running an NVFP4, and your quality is better than that other quant because the layers that you chose to quantize have their errors cancel out, like one layer skewed to the right one layer skewed to the left, one layer skewed to the right. Your final logits distribution is more similar to the original distribution of the model, so you have better fidelity. And so the way we proved this was with KL divergence. So instead of just scoring on the benchmarks, we scored the KL divergence between the logit distribution of the quantized model and the logit distribution of the original full precision model, and we showed that with this technique we get. If your probability distribution on the logits which token it wants to select is more of the same as the original model, you're probably gonna end up staying true to the original model. So yeah, so it seems like previously before this, it seemed like the industry was, well, the more you quantize, the worse it's gonna be, ‘cause the more loss you introduce. That's not exactly, not necessarily true. So yeah, doesn't improve it, but can cancel out.Philip [00:31:57]: I think it might be this, but reminds me a good bit about pruning where you can prune off certain layers.Philip [00:32:03]: But very interesting. Didn't know this was a whole paper you guys put out.Ali [00:32:06]: It's. Fun fact, it was originally 72 pages, this paper, and then we decidedPhilip [00:32:11]: WowAli [00:32:11]: We can't tell. We couldn't release it. So it's now 45.Swyx [00:32:15]: Still 39 pages, so very substantive. We talked about evals and all these things and, like what's possible in terms of speedup? Like it's like probably like the numberInference Speedups and BenchmarkingSwyx [00:32:25]: Thing that people do wanna care about, and it's something that you wrote about in your post. Like official API is 70 tokens per second, and you push it up to 90. Is that like a normal thing?Philip [00:32:36]: So what's cool about working in inference, the reason that I think inference is going to be a useful place to do engineering for a long time, is that if you look at highly optimized domains like, say, finance, if you're in finance, you measure how much better you got in basis points. It's like, “Oh, I got five basis points better, like twentieth of 1% better,” that's huge news because everything is so optimized. When we publish optimizations, it's 20%, it's 100% it's 200%. So there's still probably like a lot further to go, honestly. Like you'll, you'll know that inference is pretty much solved when researchers start publishing about how they got 1% faster at something.Swyx [00:33:19]: Which by the way, because I am from the finance background, in the ‘70s, that was the margin at the time. When you did quantitative finance research, you would findAli [00:33:27]: And like 20%, tens of percent.Swyx [00:33:29]: That's. Yes.Philip [00:33:29]: Yeah.Swyx [00:33:30]: And now it'Philip [00:33:31]: Tiny fractionsSwyx [00:33:32]: For those people interested, look up Andrew Lo's paper. He had a really interesting illustration of quant, stat arb, distribution, narrowing down from like those kinds of 20% differences in the ‘70s, down to nothing today, which is very cool.Philip [00:33:48]: Exactly, and we're at the beginning of the same type of thing. Now benchmarking is hard. I think anyone will tell you that, and benchmarking provider speeds is hard because there's so many variables that go into it. What hardware are you using? How much load do you have on the system? What's the exact nature of the prompts and input and output sequence lengths? All that stuff. But overall, when you start stacking these improvements, you're looking at multiples. You can look at it. The most common form, of course, is TPS, tokens per second, which is bad naming by us in the industry, ‘cause there's two tokens per second. There's tokens per second, the throughput number, and the latency number.Ali [00:34:31]: TTMT, yeah.Philip [00:34:32]: Like total tokens per second out of the, out of the GPU as a throughput number. Most people only care about tokens per second as the latency number, which we should call ITL, intertoken latency, but we don't.Philip [00:34:44]: Anyway, so you can imagine a standard API without many optimizations for a 1 trillion parameter model operating somewhere in the 30 to 50 tokens per second range for reasonable traffic profile. And we generally see the goal of, pushing to 10X that. But, not necessarily day zero, but by stacking enough optimizations, if you have, say like four optimizations, each of which doubles performance. Or sorry, three optimizations, each of which doubles performance, then you stack that up, that's an 8X gain. That's the order of magnitude that we're working with in this space. We're trying to make things substantially faster, not just go from like 70 to 90.Swyx [00:35:38]: Are you saying you've. You have done that?Philip [00:35:40]: So let's say you have as a reasonable baseline, 30 or 40 tokens per second. You can achieve 10X that. So like on GLM-5.2, if you run it unquantized, perhaps on H100s even, and you're just using an off-the-shelf inference engine with no particular optimizations, no speculator, nothing extra around like KV routing, no disaggregation, you're, you're probably, yeah, looking at that like 30 to 40. You think that's like a reasonable baseline?Swyx [00:36:12]: Right. Right.Philip [00:36:12]: To get to something like 10X, there's a lot of trade-offs that you're making. If we're running at more like a 300, 400 tokens per second range, you are using the best hardware possible. You have a optimized speculator. You have done all of your quantization work. You are Seeing a pretty high cache hit rate. You are running with a reasonably small batch size and a parallelism configuration that is tuned for latency versus throughput, but it is possible. So the spreads that you see if you, like, go on artificial analysis or you go on OpenRouter and you look at, the worst provider to the best provider, oftentimes can hit that range. 10X is of course very aggressive. It's oftentimes maybe more of a four to six times improvement. But that's the performance that makes us really excited, is when we can get these huge gains, not just go from 70 to 90 tokens.Stacking Optimizations: NVFP4, Speculation, and DisaggregationAli [00:37:19]: It's also, like, hardware dependent. Like, ifPhilip [00:37:20]: YeahAli [00:37:20]: If you have a thing where you're serving it on just, like, a node of H100s and then you throw, like, you shard the model across, like, four nodes of B200s. Like, you can definitely increase the speed with just throwing more hardware at it. Like, normalizing for the same exact hardware and the same number of GPUs.Philip [00:37:35]: Yeah. Then you're looking at, like, a two to 4X improvementAli [00:37:38]: Right. RightPhilip [00:37:38]: Depending on the inference optimizations. So yeah, it's. Some of it's, what's the call, and some of it's who's the driver.Vibhu [00:37:46]: If you break down the two to 4X, say the example is run GLM-5.2Ali [00:37:51]: YeahVibhu [00:37:51]: On B200sAli [00:37:53]: YeahVibhu [00:37:53]: Single node, right? What's, like, the cost trade-off for effort to get, like, the last bit of juice out versus what should people just think of, right?Ali [00:38:01]: Spectre quantization. Yeah.Vibhu [00:38:03]: Spectre quantization.Ali [00:38:04]: That's, that's, that's like 95%. LikeVibhu [00:38:06]: And how far does that get you? And how easy is that for the average person to do? So say right I wanna throw the weights of GLM-5.2 on a node of B200s, how easy is it to find speculative decoder- decoder model or already quantized model? How much work goes into it?Philip [00:38:23]: If you're doing it up front, it's quite a lot of work. If you're doing it today, there's going to be people who have published things that you can just, you can just grab some NVFP4 weights. You can grab a speculator. Yeah, if we're thinking about, like, what are the 2Xs we're stacking, going from, BF16 to NVFP4 is, it's not quite a 2X, right? It's like. I think it's about, like, 30 to 40%, from 16 to 8, and then another 30 to 40% multiplied from, 8 to 4. So that doesn't quite get you a 2X, but, like, roughly a 2X. Speculator, roughly a 2X. Disagg on top of that if you're able to get enough hardware and put enough traffic through it, another roughly a 2X. And then you add in some, double-digit percent increase from having just a better runtime with, the latest kernels and stuff behind it. And that's how it stacks up.Ali [00:39:21]: YeahPhilip [00:39:21]: So building each of those, like, building the, quantized weights is, for someone who really knows what they're doing, hours to days of work. Building the speculator, again, like, hours to days of work. And the, disagg setup, hours to days. Well okay, but like once you haveAli [00:39:39]: Once set up. Once set up. YeahPhilip [00:39:40]: Yeah, getting disagg working for the first time, I'm saying, of course, is very difficult.Philip [00:39:44]: The marginal implementationAli [00:39:48]: Like, if you're just grabbing, like if you are a person, like just a normal consumer who has access to, like, a node of B200s and you're wondering, “How can I just host it myself?” You don't need to quantize the model yourself. There's always gonna be, like, an open source quantized checkpoint. NVIDIA's gonna push one out if no one else does. You. Usually, the providers will have their own spec dec that they've trained as well. You don't need to train your own spec dec. You can just use that as well.Philip [00:40:09]: Yeah. Like, GLM-5.2 has its own MTP.Ali [00:40:13]: Right. Right.Vibhu [00:40:14]: What's multi token prediction?Philip [00:40:15]: Yes.Ali [00:40:16]: I'm justVibhu [00:40:16]: Can you explain that?Ali [00:40:16]: I'm just an expert.Ali [00:40:18]: I can do it for you in case I get it wrong?Vibhu [00:40:20]: No.Vibhu [00:40:21]: Yeah, you should correct if we're wrong, but their multi-token prediction can be used for self-speculative decoding.Ali [00:40:27]: I'm not sure. I'm not gonna correct that.Vibhu [00:40:28]: Okay. I'm semi-confident in thatAli [00:40:30]: Okay. YeahVibhu [00:40:30]: But someone can check. But it's useful to paint the story of, okay, not just the average person, but say a company wants to switch from serverless inference I wanna throw this up on. I wanna rent some GPUs, throw it up. These are the steps you take to do significantly faster than just put it behind vLLM.Ali [00:40:48]: Right.Vibhu [00:40:49]: I was waiting for a mention of Dynamo.Vibhu [00:40:51]: I feel like, that's supposed to be the baseline that you measure against.Dynamo, KV Routing, and Disaggregation ToolkitsPhilip [00:40:55]: I would think of Dynamo as less of a box system and more of a toolkit for building with. So when we talk about doing aware routing, when we talk about doing KV offloading, when we talk about doing, PD disaggregation, Dynamo fundamentally is. By the way, Dynamo is an open source library from NVIDIA.Ali [00:41:17]: We've done a pod with KylePhilip [00:41:18]: OkayAli [00:41:19]: Kyle Cranin.Philip [00:41:19]: Cool. So then your listeners know then that it supports all the different inference frameworks. And it is multi hardware, which is interesting.Ali [00:41:28]: But it's just a router, it's not like an optimizer layer.Philip [00:41:30]: Yeah. All it does, like, what Dynamo is good at, it is a library for moving information around your cluster, around your hardware. So if you have, KV cache on one place and you need it to be somewhere else, Dynamo coordinates NIXL for you to move that around.Philip [00:41:49]: That doesn't mean that, like, out of the box, you just say, “Pip install Dynamo,” and then you get, like, a massive performance speed up. It's more of a developer toolkit.Ali [00:42:01]: Yeah. I would have said it would. It comes with a set of defaults that you can then swap out.Philip [00:42:06]: It does. If the industry at large, I think, was, like, rolling out all of these deployments, standard, then I think it would be, like, a credible baseline. But, we've got to, we've got to benchmark against, like, what we're seeing in the wild.Speculative Decoding Methods: Medusa, EAGLE, n-Gram, and Spec-SpecVibhu [00:42:23]: I did wanna talk a little bit more about PD disagg, because that is probably, like, number three after quantized and speculative decoding. In your book though, I was just gonna pull out the book.Philip [00:42:31]: Yeah.Vibhu [00:42:32]: Like section 522 on Medusa, 523 on EAGLEPhilip [00:42:35]: YeahVibhu [00:42:36]: 524 on gram.Philip [00:42:37]: It's 55, would be disaggregationAli [00:42:42]: Yeah. Well, no, I just wanted to dwell a little bitPhilip [00:42:44]: YeahAli [00:42:44]: The other. Like, so what do you choose to include? What do you choose to not to include? Because there was all these other techniques.Philip [00:42:51]: Yeah.Ali [00:42:51]: Are these still relevant? Because I think they came out, like, a year and a half ago maybe.Vibhu [00:42:55]: Medusa is quite old.Philip [00:42:56]: Yeah, Medusa's old.Ali [00:42:58]: It was old.Vibhu [00:42:58]: But is it in the book as a good, here'sPhilip [00:43:01]: BaselineVibhu [00:43:01]: Baseline vanilla understand it?Philip [00:43:02]: Like you should know this.Vibhu [00:43:03]: Like I read the paper, I'm like, “ it makes so much sense.”Philip [00:43:05]: Yeah.Philip [00:43:05]: So with the book, I had a couple goals. One was to give people just a working vocabulary for the space as a whole, and the other was to give them some intuition about how each of these techniques works. As I mentioned in my AI Engineer talk, which is the first public addendum to this, the speculation space has moved much faster than everything else. So yeah, even at the time that I wrote the book Medusa, I very much included as a way for people to understand how the space evolved rather than what the most modern technique is. And now of course, there's DFlash, dSpark. There's, there's newer techniques even than EAGLE, although EAGLE is still very commonly used.Ali [00:43:51]: SpecSpecta.Philip [00:43:52]: Yes. Speculative decoding.Vibhu [00:43:54]: What canAli [00:43:56]: Oh, it's a paper by Tri Dao and it's like, it's doing speculative decodingVibhu [00:44:00]: HuhAli [00:44:01]: For the speculative decoder.Philip [00:44:02]: Oh, in spec- oh my God.Ali [00:44:02]: It's literally just an another. It's like, yeah, that's the most simple way to explain it, and it seems like he got trivial speed ups there. But it seems that the complexity with training, it's almost like in our mind at least, it's almost as complex as training GANs. Like it's like a very delicate balance and oftentimes you, it's just but yeah, it's literally speculative decoding on speculative decoding.Vibhu [00:44:21]: Speculative.Ali [00:44:22]: Yeah. We saw this paper.Vibhu [00:44:24]: It's interesting, right?Ali [00:44:24]: Yeah.Vibhu [00:44:24]: I wouldn't even expect it to be very particular to train, I wouldAli [00:44:29]: Right.Vibhu [00:44:29]: The naive part of me is like, okay, train speculative decoder.Ali [00:44:32]: But like, and it makes sense, like the whole idea of speculative decoding is you. It's like, it's like almost like the iPhone auto predict version but for a normal model, right? Like you're just, you're just, generating three tokens and you're like, okay, I'll do prefill on them. And so you save those three turns for your original model. Now your speculative decoder is doing three turns of auto regression, so why not just have an even smaller model?Ali [00:44:53]: The other question there is what are the size of speculators? So say forPhilip [00:44:58]: Right. It's like a billion parameters.Ali [00:45:01]: Like for MiniMax, it's. Yeah. It's like one layer. It's like one 60th of the original model usually.Philip [00:45:06]: Yeah. I think we should do a paper when we get back to the office.Philip [00:45:10]: SpeculativeAli [00:45:11]: SpeculativePhilip [00:45:11]: Decoding.Ali [00:45:13]: No, it's, it does seem like how, when do you stop? But then it also seems like if you're able to train spec-spec decode for instance, right? Like if you're able to have a small model that is accurately predicts what the intermediate speculator is gonna predict, that is able to predict what the original target model's gonna predict, then why not just use that smallest model directly, right?Vibhu [00:45:34]: Yeah. This isAli [00:45:35]: Like it seems likeVibhu [00:45:35]: Adjacent to the routing problem.Ali [00:45:36]: Right.Vibhu [00:45:36]: Yeah.Ali [00:45:36]: Right.Philip [00:45:37]: The thing with speculators is one of the practical constraints on using them is that you do have to run a small model on the same hardware that you're running the big model on. There is a orchestration and resource competition problem inherent in that, and that is one of the constraints on speculation in general, is that draft tokens cost resources to create and cost software complexity to manage. And so if you have like infinitely recursive speculators, you add in quite a bit of that complexity on the actual implementation within the inference engine as well, not just in the training process.Vibhu [00:46:17]: I was gonna say, I would wonder if you could do similar, like distillation and pruning of, it's the same thing, it's just a model. Can we not just distill a lot of the weights, quantize the speculator, out of my domain? The question that also comes up is, this is all for big server workloads, right? How much of this applies to, say I have this MacBook, I wanna run Gemma really efficiently. Similar problems, not the same?Local AI vs. Data Center InferencePhilip [00:46:45]: Pretty different. I talked to Selo, about this on his podcast a couple weeks ago. The difference between inference engineering for the data center and for production workloads versus inference engineering for local AI, is that we start with fundamentally like different constraints and different goals. With local AI, it's how do I fit this model onto my hardware and then make it less dumb? And with data center influence, it's how do I load this model and then make it less slow? And we care about less dumb, and they care about less slow. But the local AI inference engineering ecosystem, I think has a lot for us to learn from in the data center space. They are experts in various forms of quantization, including dynamic quantization that we just don't touch, in the pruning, in the distillation, in the, layer removal. There'Ali [00:47:42]: Layer removal matters less.Philip [00:47:43]: Yeah. There'Ali [00:47:44]: No one loves pruning really.Philip [00:47:45]: Yeah. Well, but the, but they doVibhu [00:47:46]: Which is surprising, right? But that's, that's a whole different thingPhilip [00:47:48]: Just to fit something on the laptop.Ali [00:47:50]: Right.Philip [00:47:50]: So yeah, it's a, it's an interesting, it's an interesting space. Not necessarily that like their techniques make sense for us to do in the data center, because we have different resources and different goals, but more that the process as well as the openness of that field is something to, admire.Ali [00:48:12]: Yeah. Like to your point, like, certain optimizations that would. Like for instance, Turbo Quantum Sharper, like it made such huge hype on that and we did like a whole deep dive on Twitter and like said, what is it? How does it work? Why is it good or not? And it took off and it was implemented on local devices because your memory bandwidth is so slow on like a MacBook, for instance. But try putting the same thing on like an NVIDIA GPU on a B200 Turbo quant would not be. Like, it would not be used. Like, NVIDIA - Like, NVIDIA made it clear that this is not a good optimization, and we've seen it firsthand where the overhead of doing dequantization, quantization of, in the kernel itself with turbo quant kernel, each end is much slower than the time that you save from doing the bandwidth. ‘Cause on the B200s, you have like 3.5 terabytes per second. You don't need decrease the storage that much. You don't need to do, FP4 KV cache. You don't need to use a requant. There's, there's, there's better optimizations to be made. But on Edge devices, it's extremely important, it's extremely useful. So, seems to be, like, different optimizations there, but then they're all uniquely combined with like all you wanna quantize the model, you wanna do speculative decoding, like certain common prefixes with bothPhilip [00:49:18]: Principles.Ali [00:49:19]: Yeah, exactly. Exactly. Exactly.Philip [00:49:20]: They also do a lot of work on, model parallelism, especially over, heterogeneous topology, where you have, some sparks and they are wired together with, Ethernet, DGX sparks.Ali [00:49:35]: Yeah, this is the Exo Labs guys.Philip [00:49:36]: Yeah. You have, a nu

Buy one get one free, pick your combo: ⁠https://mapsbogo.com⁠   One of the most common questions the guys is also one of the simplest: what program should I run next? It matters more than most people think. Stack the wrong two programs back to back and you leave gains on the table. Stack the right two and you buy yourself six months of near zero plateaus, real strength PRs, and a body that keeps changing every week. In this episode, Sal, Adam, and Justin stop making you guess and lay out the definitive MAPS program pairings for every major goal.   They cover advanced muscle gain, pure strength, fat loss for both women and men (and why the programming is different), total beginners and postpartum lifters, athletic performance, and the people who barely have time to breathe, let alone train five days a week. For every goal you get the exact two program combo, why that order works, what each program sets up for the next, and the most common mistake people make by skipping steps. If you have ever jumped straight into a high volume program and wondered why you burned out, this is the explanation you needed.   There is a real buy one get one free deal running right now at mapsbogo.com, and you pick the combo. $157 gets you two full programs. The guys walk through every recommendation, so by the end of the episode you will know exactly which two to grab.   In this episode: MAPS Anabolic anchors almost every combo: it builds the strength and training frequency foundation that makes every follow up program far more effective, whether the goal is muscle, strength, or fat loss. The single biggest mistake the guys see from customers: jumping straight into MAPS Aesthetic without running Anabolic first. Aesthetic's volume is genuinely high, and the body is not ready to absorb it without that base. Fat loss for women is MAPS PowerLift, then MAPS Muscle Mommy. PowerLift builds the metabolic base and preserves muscle in a deficit, while Muscle Mommy targets the glutes, delts, and lower body that women most want to keep while getting lean. MAPS 40+ trades traditional back squats for box squats and straight bar deadlifts for trap bar deadlifts, cutting joint stress while hitting the identical movement patterns, and adds specific lifestyle recommendations for the higher stress loads that come with being over 40. For beginners and postpartum women alike, the prescription is MAPS Starter, then MAPS Anywhere. Treat yourself as a total beginner no matter your training history, because the body control and positional strength you build here pay enormous dividends on every loaded program that follows. The athletic performance combo is MAPS Symmetry first, then MAPS Performance. Symmetry's isometric and unilateral work corrects left to right imbalances and builds the ability to contract and control the body that sports demand, before performance specific training gets layered on. In a fat loss phase, the real success metric is maintaining strength on the key lifts, not the mirror. Holding strength in a deficit proves muscle is being preserved even when the scale or the reflection does not show obvious change. MAPS 15 paired with MAPS Anywhere is not just for the time crunched: the guys explicitly recommend it for anyone who is overworked, stressed, or grinding five to six day splits with diminishing returns, because scaling back volume often produces better results.   Chapters: 0:29 MAPS BOGO Deal Intro 0:44 Sponsor: Vuori 1:28 Episode Overview: Best Program Combos 3:11 Advanced Muscle Gain Combo 5:49 Why MAPS Aesthetic Follows Anabolic 7:43 Strength Goal Combo 9:10 Fat Loss Combos: Women and Men 9:37 Fat Loss for Women: PowerLift + Muscle Mommy 12:05 Fat Loss for Men: 40+ and Anabolic 15:59 Beginners and Postpartum: Starter + Anywhere 19:42 Athletic Performance Combo 21:03 Time-Restricted Combo: MAPS 15 + Anywhere   Sponsors: Vuori: ⁠https://vuoriclothing.com/mindpump

Episode 424 of Tom Clark's Main Event is a review of AEW Redemption. Tom dives into the match card and discusses all of the results, including Willow's AEW Women's Championship win over Thekla, as well as Kenny Omega vs Will Ospreay, and Chris Jericho's controversial brawl with Tommaso Ciampa. This PPV was the talk of the pro wrestling world heading in, possibly for the wrong reasons, but were the critics right? Tom also gets into the G1 tournament in New Japan, and why the heel vs babyface dynamic in AEW continues to be a problem. All that and a lot more! Boink Studios podcasts are created by humans. All hosts featured on our shows are human, and all podcast artwork, logos, and creative direction are created by humans. Subscribe on YouTube: https://www.youtube.com/@boinkstudios Visit us at: https://boinkstudios.com Appreciate the content? Support the channel: https://buymeacoffee.com/tomclark Follow the Main Event: Facebook: https://www.facebook.com/tomclarksmainevent Bluesky: https://bsky.app/profile/boinkstudios.bsky.social Listen to Boink Studios' Podcasts: Tom Clark's Main Event: https://podcasts.apple.com/us/podcast/tom-clarks-main-event/id910362334 Tom Clark's 6M Podcast: https://podcasts.apple.com/us/podcast/tom-clarks-6m-podcast/id1441274603 Bare Mode: A Podcast Review of The Bear: https://podcasts.apple.com/au/podcast/bare-mode-a-podcast-review-of-the-bear/id1828513020 Two Nations Under Ted: A Ted Lasso Podcast: https://podcasts.apple.com/us/podcast/two-nations-under-ted-a-ted-lasso-podcast/id169387035   Music by Mr Maph aka Dogman Rukus, PPL 0103166534, PRS 1136021800 © Boink Studios 2026

It's a common trajectory: Dental schools create great dentists, but they don't create good business owners. Kiera shares three critical (but attainable!) tips for creating a profitable, scalable, and enjoyable practice, so doctors can continue doing the work they love. Episode resources: Subscribe to The Dental A-Team podcast Schedule a Practice Assessment Leave us a review Transcript: Kiera Dent- Dental A Team (00:00) Hello, Dental A Team listeners. This is Kiera. And today I'm excited to chat with practice owners, office managers, and to kind of just talk about like what every practice owner should know. But I think a lot of us learn that too late. Myself included, I feel like business owners, I feel like we are great at our craft, but at business we learn it a little too late. And so I think that like I looked at all of our students at Midwestern and they learned how to be great dentists, but they didn't.   learn how to become great business owners. And we hear this all the time. I'm not saying anything new. I just think that a lot of practices hit ceilings because it's not their clinical skills. It's the business outgrows their knowledge. It's like, hey, take me to the moon. You're like, I've never been to the moon. And so I think just being able to help practice owners today realize in office managers, like leadership systems and financial decisions really are like the core. That's why we call it the yes success model. So you, that's the leadership,   systems and earnings. Like that's really what makes up a successful practice. But I feel like that feels so easy. But I want to just walk through like what are three things that every business owner needs to know to have a profitable, scalable and enjoyable practice. You guys the Dental A Team like we work with hundreds of practices across the nation from startup practices to multi-million dollar offices. And what I realize is the challenges are all the same. Like it's fundamentally stays the same. It just gets bigger or smaller based on the size of practice that you're in. And so   I think so many people know how to work really hard. I think so many people outproduce their problems. I think so many people they just it I hear all the time when people are calling to work with us, like Kiera, I just don't know what I don't know. And so today I just want to go through like, let's just talk about three things that I feel like every single business owner needs to know and some tactical ways that you can implement this. So hopefully it takes you from being stuck to unstuck. If you've heard this in the past, maybe you're hearing it at a different time. I know for me these are three fundamentals that I go back to no matter what phase of the business I'm in.   No matter what size of practice I'm in, none of that. So number one is going to be your leadership is like completely the like growth of your business. And your business will never outgrow your leadership. And so your business is a reflection of you as the leader. I remember reading Jocko Willink's book about that extreme ownership. And it was like everything about your business is a reflection of you. And when so when I'm frustrated of the systems or the scalability or the lack of accountability, that's me. And so when we have that.   I hate this, but I love this. Is where can we get consistency? Where can we stop the firefighting? Where can we like make sure that we've got stronger accountability? And where can we make sure that the doctor's not carrying everything? Because I think so many doctors are like, I'll just do it. I got this. Like, I I'm a hard worker. I know how to GSD. I know how to get through this. But I'm like, okay, we've got to figure out how like being a leader is not just a title. How do we create more clarity and how do we create more consistency? And how do we develop leaders and owners within our organization?   And so for this, like when I look at our leadership and how for you not to get stuck in that, like being a great leader is being able to make hard decisions. Being a great leader is how do I create clarity and consistency for my team? Being a great leader is how do I make sure that my team understands the numbers and we use those numbers to guide our decisions. we were going through a whole list the other day of of topics of leadership. And I was like, gosh, I like leadership is   It's a journey. It's an evolution. It's not something that you just do overnight. and I think about Kiera as a leader when I first started and she was erratic. I was like, I was turbulent. I had so many pieces. but leadership is maturity. it's how do I get people to buy into a vision? How do I rally them and how do I get them to buy into a vision? How am I to be a CEO versus a manager and really understanding the difference of those two hats? How do I have time management where I   Truly focus on the most important things, not just because I'm capable of doing it, but because I'm the only one that can do it. How do I delegate and work through my team? How do I like learn people and work to their strengths and work to their superpowers? Working through my team, not just working with my team, using my team. How do I have the art of influence? How do I grow my team members into incredible people? How do I see that potential when I'm hiring? How do I hire better? How do I figure   like leading, managing, and holding people accountable. How do I have consistency? How am I an example, but not the one who has to do everything? how do I value my team? Do I see them as an asset or a liability? How do I help my team feel valued without being the one who does it all? Like there's a there's a there's a great quote over here today that says I cannot give you the formula for success, but I can give you the formula for failure, which is try to please everybody. And that's by Herbert Swoop. And I thought about that as I was prepping for the podcast today of   That's I think in leadership where I'm not trying to please everybody. I'm going to make decisions that upset people, but I'm always going to make decisions that are in the best interest of the business. how do I own my mindset and make sure that I'm showing up with that clear, sharp mind? How do I have like mental health and grit and make sure I'm having that? What about creating culture, getting a team of ownership, having like my office manager, doctor, duo and having that relationship? What about performance management of my team?   So when I look at this and I think about this, like leadership, like you developing and growing as a leader. And I think that when I go back to this of like a lot of owners just think like I owned it, I got the title of a leader. But leadership is this evolution and this journey. It's becoming, it's evolving. It's all those pieces I listed off, and yet it's not a, it's not a checklist. Like, how do I learn to listen and not react? How do I learn to have my team come up with solutions rather than me?   So I rattled off a lot and all those can hit people at different phases of business. And I believe that I can check one of those off and then I can move. And then my team will double in size or our business will double in size. And I might have to go back to the beginning and the basics again of like, all right, I gotta figure out again how to work through my team. we went from having where me and our team was doing it to where now we're bringing on the C suites and the leader I need to become to manage a C suite versus the leader I needed to be.   Run when Tiff and I were just running the business together. The way I act and interact with my EA and personal assistant today versus when I first had one. It's an evolution. It's a leadership. It's an evolution of who you are. And so it's how do how do we become better at leadership? And I would say listen to podcasts, read books. some I I go back to fundamentals. I read the go giver constantly, I read traction a lot. It's so but boring. Like, sorry, Gino, it's very boring.   read the book, How to Be a Great Boss, Crucial Conversations, Discipline Without Punishment. Those are just some great books, but also look at great leaders and what do they do. For me, I'm a big mimic and mirror. So I talk to people, I talk to dentists that have really great cultures. This is why I love our mastermind group. I bring the best of the best of the best together. And I know because we work with all of them and I know our dentists personally, I have a lot of my great core leaders that I know are just dynamite leaders.   I have them share what do they do? How do they have it? How do they have performance reviews? How do they give cr like critical feedback? Some of the dentists early on in my career. I had them practice these conversations with me, like literally would have to send me voice memos. Practice your leadership skills. Use a consultant. Let's talk through how we're gonna have this conversation, how are we gonna talk to our team about this? But really I think like if I break it down to the nuts and bolts, it's how do I get a team to buy into a vision? How do I make sure that we hold accountability and ownership?   And how do I make sure that I maintain consistency and clarity? I think if I boiled it down and that's a rift on my own side, like not prepped, those would be the pieces I'd boil down. And so how do you become a stronger leader in those areas? And again, there's just indecision is worse than a wrong decision. And so just making those decisions, being more confident in yourself. someone once said like 2.0 is sitting here, and I think about Kiera 2.0, like she wasn't born, she was created.   Leaders are not born, they're created. You've got to like flex and strengthen that leadership skill because your practice can never outgrow your leadership. And if you want to get to the next level of growth, whether that's financially, whether that's profitability, you have to flex and become a different leader. If you've got pure chaos in your office, that's you. If you've got people who aren't falling through, that's you. And that doesn't mean you have to go fix it. I mean, that's you tolerating that. And that's the standards of your practice. Your business will always fall, not to what you say, but what you tolerate.   And so being that leader that raises the standards, I this year I was annoyed. I was like, okay, we're going for outcomes over activity. I realized I was tracking activity, but that's not moving our company forward. We need to be tracking outcomes. Our team is flourishing. But me as a leader, I need to be looking down the line and seeing, and I need to be developing myself as well. I go to the gym, I put myself into a complete fitness competition where I wanted to get to my best physical, like PRs, physical fitness. I went through   A cut. I've never done a cut before. I push myself physically, mentally, often because to me that's a a different pressure test that's gonna sh like allow me to show up better as a leader as well. So it doesn't even have to just be within your practice. Discipline at the gym, discipline in working out, discipline in how you show up, discipline in how you eat, those things are going to make you a far superior leader. I will tell you.   Going through a cut where I had the least amount of calories, I was the strongest, most sharpest leader I've ever been. And I was exhausted. But I knew I needed to show up and I needed to be stronger and I needed to think better ways. So those are going to be some zones hopefully that will help you on leadership. The other one that I found that a lot of people miss is we talk about so often, but systems truly do create freedom, not restrictions. And I think people think that they need to have really strong and lots of systems. And even our team was doing this, but realistically.   There's just a few core systems that need to be in place. There's not a lot of systems that actually need to be there, but they do need to be consistent. They do need to be scalable, and they do need to be followed through on. And so when we look at it, our team was going through and there's there's business fundamentals like core value, vision, mission, org chart, meeting cadences, figuring out our BAM, figuring out our projections, looking at our overhead. Like those are business fundamentals. And then there's systems. And we actually broke it down and we're like, gosh, if we just put into place like 10 core.   Most things are going to get better. Most things are going to get fixed. Most things are going to get resolved. But they're not sexy. They're not fun. They're not things that I'm like, my gosh, like, let me get on a podcast and tell everybody, like, let's just fix these seven items. But that's all it really is. But I think that what happens is we want to continue to scale. We want to continue to build. For me, I want to reinvent, reinvent, reinvent, reinvent. But that's actually not something that's going to grow us. And so it's like,   Just having KPIs that we track and monitor and we use those to make our decisions, having a solid morning huddle with an agenda, following set meeting cadences, having proper handoffs, having a proper scheduling protocol, having case acceptance protocols, having a collections protocol, working on new patients and referrals, having a period protocol, recare reactivation. Like those are really core items that if you have those systems where you follow them and we scale them and everybody's doing it the same way, 95% of your problems get fixed.   Of course, there's other ones. There's hiring, there's onboarding, there's leadership, there's all these other ones. But I think so many people don't want to just be at the basics. We want to reinvent the will. We want to do these things, like have job descriptions at the end of days. Like just do it. It's boring. It's not fun. People are like, wow, wow. We have to have a a morning huddle prep sheet. Why do pilots have checklists? Like the checklist manifesto. They create freedom, they create predictability, and they create systemization. That's all you need to do.   And I found that when offices follow it, when we have it in place. And for me, I also don't want systems to be something that people have to remember. How can I have it as a true system like Chick-fil-A where their burgers come out with three pickles every single time? How do I make sure that our schedule has the same system every single time? How do I make sure that our our handoffs have the same thing every single time? And I don't have to hope that 15 team members remember it. We're gonna put this in to where we have it consistent every single time, no matter who's doing it, no matter what new team member comes in.   That is scalability with systemization. And so have it documented, have it simple, have it repeatable. That's gonna get duplicated. So I think for offices, systemization really that that's the core. That's the systems. It's not sexy, but it is very, very effective. And then the third things that I think a lot of people don't realize, including myself, is you have to know your numbers better than anyone else. That's better than your CPA, better than your financial advisor. You have to know, and that's not just production, that's profit. Like I remember someone said,   production feeds the ego, profit feeds the family. And I think about this all the time. Like, you have to know your production. And I'm talking net, not gross, your collections, your overhead. Then within your overhead, like what is our payroll? What is our supplies? What's our marketing? What are our labs? What's our profitability? And then what's our billing and our AR? You know those numbers. You're solid. You can make so much stronger decisions. You don't, you have financial surprises, you make poor decisions, you're on reactive rather than proactive.   You grow, but you don't have profit. Like, I can't tell you how many offices I've that are singing the five, six, seven, eight million and they have no money. And I'm like, golly, you're making so much money, but you don't know how to keep the money. You gotta make the money and you gotta keep the money. All right. Like that's what we gotta do. So you have to make sure that our profit is there and we can't be willy-nilly. To me, you guys know I talk about the MMs. I do money and meditation in the morning. So triple for you morning, meditation, money. Look at it every single day. Look at your P and L.   If you don't know your overhead and your profit right now without looking, you gotta know it better. You have to. And that's a doctor and an OM. You must know this number. This number creates all the drive. Profit is the only number I actually care about. Like I can sit here, we can track all the KPIs, so many things, but if your profits down, everything else in your life is hard. Your profits up, most things in your life are really easy. Money solves a lot of problems. And so let's have profit. Let's have like I'm stressed out, I'm moving my hair around. Like   I don't enjoy this. This stresses me out because you've got to know your numbers better than anyone else. You don't sit here and lie, if your CPA is not delivering to you by the second of the month, like the second week of the month, get a better CPA. Like they work for you. You have to know your numbers. You have to be confident in them. And if things fill off, challenge it, question it until it gets right. Don't just sit here haphazardly. That is not a strong business owner. This one fires me up more than anything because I used to not know my numbers. My husband was like, Kiera, I don't get it. Why are you broke? And like,   I don't know. Well, I learned this great thing about AR. I had like a hundred grand sitting in AR that I didn't know about. We weren't collecting properly. You better believe I fixed that real fast to where I'm never gonna be in that situation again. And you layer by layer by layer, you get more and more and more financially savvy, but you have to know your numbers better than anyone else. You know your production numbers or so, I hope. If you don't know that number, but do you know your collections? Do you know your collection percentage? Do you know your overhead? Do you know your payroll percentage? Do you know your supply sip? If you don't,   You must learn that. So I'll get off my rant. But this was funny. They said production is a vanity, profitability is a reality. And I think that that's a good anchor line of yes, it is. Profitability is your reality. So your numbers are gonna tell the truth whether you choose to look at them or not. The truth is always there. Some of us don't want to like get on the scale and say weigh. I had a great trainer tell me, she's like, Kiera, that number means nothing other than giving us data and information. It's not my   Self-worth, it's nothing. Just like your profitability is just a number on a scale. It just gives us data. If we spend more money on payroll, this is the number that we get. We make better decisions if we know. But I will tell you, your success, your happiness, your stress is all tied to you knowing these numbers or not. And a lot of people are like, no, no, no, I don't want to. Yeah, right. You're sitting in stress constantly that you don't even realize. So know your numbers. Schedule a monthly financial review. Commit to knowing the story behind your numbers.   Like, do money meditation with me every morning. Just have your bank account on there. Just look at it every morning. Look at your PL every day. I don't care. Do not sit in excuses on your money. You're a business owner, you've got to know this. So I hope that wasn't too much of a rant. But I hope it gave you some good tips on how to have leadership. some good money books. I love Profit First by Mike McAllicks. I also love Money Master the Game by Tony Robbins. That was a long book, but it taught me a lot.   there's some great financial podcasts out there. there's also some really crummy ones. I The Psychology of Money was another great one that I read that was on financial. systems, the checklist manifesto is a great one. Come up for air is a great book. There's several great books based on where you're struggling. But if you notice, this is our yes success model. You as a leader, earnings and profitability, system structure and scale. That's what it is. And every single one of those will give you the yes success model.   You've got to take care of them. You've got to do leadership. You've got to do profitability. You gotta do systems. The yes success model follows constantly. So what part are you the weakest in? What part are you the strongest in? And where do you need to grow? This is the zone like you're not a great practice is not built by accident. It's intentional, it's focused, it's consistent. I had another great trainer. She said, Kiera, it's not about perfection, it's about consistency. That's I don't care if last month you didn't look at your numbers.   I do care if you consistently are not looking at the numbers. You aren't, I'm not expecting perfection, but we do have to have consistency. So how can you have more consistency? And if you're feeling overwhelmed, it doesn't mean you're failing. It just means that you've outgrown the current systems, you've outgrown where you're at, you've outgrown the knowledge. It's kind of like the Wi-Fi symbol. You're just popping up to the next level. And your next level of growth comes from working harder. Like it can, but it usually comes from knowing your business better, leading better, making better decisions with finances. So this is what we're obsessed with.   I love to help you. I love our team to help you. I love you to be a part of our community. We talk about this every single month. We talk about this in person. Come be a part of it. Like for me, I'm not going to get a six-pack without a trainer overseeing me. You might not be able to grow your business without a trainer overseeing you, an advisor helping you, somebody getting you out of the rut, somebody helping you get to that next Wi-Fi symbol. So let's help you out. Reach out. Hello at the Hello@TheDentalATeam.com. You guys, this is your life, your practice. And I feel like these things are not known. I feel like they're kind of known.   But knowing and executing are the difference between winning and losing. Are you just gonna know the facts or are you gonna actually execute on it? The challenge is there, the choice is there, and I hope that you choose to be somebody who executes. Reach out, let's get you out of the hole. Come on, let's do Hello@TheDentalATeam.com. And as always, thanks for listening, and I'll catch you next time on the Dental A Team podcast.  

#361: Picture a 6,000-line pull request landing in your project from someone you've never heard of. Every test passes - yours, theirs, all of it. And you can tell it was generated. Not assisted. Generated. What do you do with it? Viktor's first move is to poke the premise: how do you even know it was generated and not assisted? You can't. Nobody can. That distinction is already gone. So the real question isn't whether AI wrote it. It's what a maintainer is for. Viktor's answer is blunt - a maintainer's first job is to guide people in and help them contribute, and if you think your job is mainly to write code, you picked the wrong role. The moment you allow PRs, you stopped being an individual contributor and became a manager. That's the job. You don't get to complain about the job you signed up for. Don't want it? Fine - do what Ghostty did, do what curl did, turn PRs off and say so out loud. Just don't hide behind unknown contributors, because every single person on your project was an unknown contributor on their first commit, including you. A software developer says send me anything but a PR and lists four reasons: unknown contributors are a security risk, supply chain attacks are real, style disagreements eat maintainer time across time zones, and LLMs killed code-writing as the bottleneck so the stranger's PR doesn't help with the parts that are still hard. Viktor grants the security point and then points at XZ - social engineering, a long con, zero AI required. The risk was always there. What changed is quantity, not the percentage. And the maintainer who thinks a manual, line-by-line review still works in 2026 is, in his words, terribly wrong. Viktor guesses he can review 6,000 lines in about the time it takes to hand-review 600. CodeRabbit and Greptile clear the obvious junk so he can spend his attention on architecture and the feature itself - the stuff he never had energy for after slogging through nitpicks by hand. His read on the whole backlash: there's a new third group of maintainers now, the ones who aren't good enough with agents to fight agents, and they're the ones falling behind. Writing code is cheap. Reviewing it well is the expensive part - and the ones who refuse to use agents to review are drowning while blaming the contributors. There's a cost angle too. If you don't have tokens, you're in trouble, and not everyone can afford them. Tokens are becoming table stakes, like an internet connection. Which raises the question: what happens to open source when the reviewing tools cost money the maintainer doesn't have?   I don't want your PRs anymore https://dpc.pw/posts/i-dont-want-your-prs-anymore/   YouTube channel: https://youtube.com/devopsparadox   Review the podcast on Apple Podcasts: https://www.devopsparadox.com/review-podcast/   Slack: https://www.devopsparadox.com/slack/   Connect with us at: https://www.devopsparadox.com/contact/

Double Tap Double Tap - Ep 472 July 27, 2026 Presented by This episode of Double Tap is brought to you by: Foxtrot Mike (Code: WLSISLIFE) Gideon Optics (Code: WLSISLIFE) Flatline Fiber Co (Code: WLS15) Second Call Defense Bowers Group (Code: WLS) Giveaways!! GAW   Text Dear WLS or Reviews +1 743 500 2171 Public   Show Titles   GOA GOALS Aug 1-2 in Iowa. https://goals.goa.org/ Dear WLS Question from Anonymous Coward from NEBRASKA Quick question. From me. With printed holsters thinking of getting one. So which model of bambu should I be looking at? Also do I need AMS? I am cheap so probably only 2 models I am seeing so comes down to do I need or want the enclosed one. Question from Alex W. from Florida Dear WLS: Hey y'all. If all of our hopes and dreams were to come true and we could get mail order machine guns to our doors, what (other than boatloads of fun) do you think the most valid use for civilian full auto is? I was thinking maybe a select fire/burst fire subgun for home defense? Belt feds on pigs? Alex W. Question from Dependable Don from New York Dear Wls Dependable Don Why don't you just invite Lenny on so the Jeremy could just point to him when he he needs the needs a n bomb dropped? Question from Rob K from Connecticut Rob K From ConnecticutDear WLS The State of Connecticut has banned Glock and Glock style pistols starting on October 1st 2026. I don't own one, but now that the state is telling me I can't buy one, I need to spite purchase. I'm interested in picking up 2 Glock models and 2 Glock style pistols. If you were only able to own 2 Glocks, what would your suggestions be for gen and model? Also, what make and model of 2 Glock style pistols. Thanks guys. #stuckbehindenemylines WINNER Question from Travis from ILLINOIS Dear WLS this is Travis from not the people's republic of Illinois. Love the show you and all the content. Shawn over the past few shows you have mentioned your Kelby rifle. What do you like and not like. Would you do anything different. I personally don't know anyone who owns one and looking to purchase one for potential PRS matches. Thanks Travis Question from Anonymous Coward from Florida Dear WLS: Hey y'all. I was thinking, with the growing apparent popularity of “pdw” setups for pistols, I was wondering why no manufacturer seems to produce a factory firearm that fits that sort of form factor (other than sig selling factory 320's already in a raider chassis). The closest things I can think of currently would be the B&T TP9 or their USW. But I'm wondering why no one else is tapping into the whole oversized 9mm pistol with a brace/stock market trend. Has the industry just not caught up or is there a reason companies are not moving in that direction? Gun Industry News Guns CMP to Sell Military Surplus M14 Rifles The Civilian Marksmanship Program (CMP) announced it will sell a limited number of surplus U.S. military M14 rifles (7.62 NATO) produced 1959-1965 by H&R, Springfield Armory, TRW and Winchester. The rifles, from the total production run of 1.38 million, have been permanently modified to semi-automatic configuration to comply with ATF regulations and CMP enabling legislation for .30-caliber rifles. Sales are expected to use a lottery system and begin in late 2026 to early 2027. The Gist: Sales begin late 2026 to early 2027 via lottery system Bottom Line: Limited surplus M14 rifles (7.62 NATO) permanently converted to semi-auto; produced 1959-1965 with total output of 1.38 million; background includes 479,000 demilled and 321,000 provided as military aid Shootingnewsweekly Ramp Payment Processor Shows Inconsistent Policy Toward Gun Industry Payment processor Ramp denied services to Kent Cartridge Company in West Virginia, citing partner risk concerns, as highlighted in an NSSF report on industry discrimination. Simultaneously, Ramp has been actively courting Davidson's Inc. in Arizona with business development emails as recently as July 22, 2026. West Virginia Governor Patrick Morrisey and Attorney General JB McCuskey are investigating, noting potential violations of the state's FIND Act, a Trump executive order on fair access to banking, and OCC/FDIC rules prohibiting discrimination against lawful firearm businesses. The Gist: The Gist: Ramp denied payment processing to Kent Cartridge (WV) after NSSF discrimination report but sent ongoing outreach emails to Davidson's Inc. (AZ) as of July 22, 2026; state officials investigating for violations of WV FIND Act, Trump EO, and federal banking rules. Impact: Market Impact: Affects firearm and ammunition manufacturers and retailers seeking reliable payment processing; creates uncertainty for gun industry businesses in states with protective laws. Bottom Line: The Bottom Line: Demonstrates ongoing de-banking pressures on the firearms sector despite legal protections designed to ensure equal access to financial services for lawful industries. Breitbart Dan Wesson DWX Compact 9mm Pistol The Dan Wesson DWX Compact is a metal-framed 9mm pistol that blends design aspects of the CZ 75 and the venerable 3631. It features an aluminum frame, optics-ready slide, AmeriGlo tritium front sight with black rear, aluminum grips, accessory rail (available with or without), and ships with 10- and 15-round magazines. The article highlights its smooth action, excellent trigger, tight groups, and suitability as a real-world everyday carry self-defense pistol after testing over 1,100 rounds. Bottom Line: Key specs/features: 9mm caliber; 10- and 15-round magazines; aluminum frame providing heft; optics-ready; AmeriGlo tritium front sight, black rear sight; accessory rail (optional); aluminum grips; smooth DA/SA action with superb trigger; blends CZ 75 and 3631 characteristics for precision and durability Thefirearmblog Smith & Wesson M&P15 AXE Pistol and SBR in .300 Blackout Smith & Wesson has expanded its M&P15 line with the M&P15 AXE Pistol and corresponding SBR variant chambered in .300 Blackout. Both models feature an 8″ 5R rifled barrel with Armornite finish, GVAC direct impingement gas system optimized for suppressed shooting, 7″ Midwest Industries M-LOK handguard, enhanced BCG, Radian Raptor ambidextrous charging handle, and full ambidextrous controls. The pistol uses a Magpul BTR arm brace while the SBR includes a Magpul CTR stock and Williams folding sights. The Gist: Announced July 21, 2026; availability not explicitly stated beyond launch Bottom Line: Caliber .300 BLK, 8″ barrel (1:7.5 twist, 5/8×24 threaded), GVAC gas system, Midwest Industries 7″ M-LOK handguard, enhanced BCG, Radian Raptor CH, ambidextrous controls, M&P grip with interchangeable backstraps, Magpul BTR brace (pistol) or CTR stock (SBR) Xtechtactical XTech Tactical X-Flare Digital Mil-Spec Magwell BLK AR-15 / M4 The X-Flare Digital Mil-Spec Magwell is an injection-molded polymer flared magazine well designed to fit true mil-spec AR-15/M4 lowers without removing any parts. It creates a 1.75x larger funnel opening compared to a standard mil-spec magwell, features metal threaded sonic-welded inserts with included steel bolts, and adds only 28.5 grams of weight. Available in Black (with FDE and Grey color options), it installs in minutes and carries a lifetime warranty. The Gist: Available for immediate purchase from xtechtactical.com in single, two-pack or five-pack quantities Impact: $39.95 (single unit) Bottom Line: Injection molded glass-filled Super Tough Nylon; 1.75x larger funnel; fits all true mil-spec AR-15/M4 lowers (not billet/non-mil-spec); 6 × 4 × 1 in dimensions; 28.5 g weight; sonic-welded steel-threaded inserts Guns B&T Partners with Rare Breed for FRT-Equipped SPC9 and GHM9 B&T USA has partnered with Rare Breed Triggers to offer factory-integrated FRT-SG3 triggers in its 9mm SPC9 and GHM9 platforms. The guns are assembled and tested at B&T's facility prior to shipping as a complete, validated system. The FRT-SG3 features a three-position ambidextrous safety (safe, semi, FRT). The Gist: Factory-assembled and tested at B&T USA production facility before shipping Bottom Line: FRT-SG3 three-position ambidextrous safety (safe/semi/FRT); first factory-built FRT-equipped duty platforms from B&T Xtechtactical X Flare Digital Magwell Mil Spec Blk Ar 15 M4 Magwell https://pew.report/c/dTR56i Before we let you go – Join Gun Owners of America We'd love if you supported the show, join Agency 171 at agency171.com. Lot's of prizes, rewards and kick ass swag. No matter how tough your battle is today, we want you here fight with us tomorrow. Don't struggle in silence, you can contact the suicide prevention line by dialing 988 from your phone. Remember – Always prefer Dangerous Freedom over peaceful slavery. We'll see you next time! Nick – @busbuiltsystems | Bus Built Systems Jeremy – @ret_actual | Rivers Edge Tactical Aaron – @machinegun_moses Savage – @savage1r Shawn – @dangerousfreedomyt | @camorado.cam | Camorado

Creature Code welcomes Father Robert Bailey July 27th, 2026 EP: 17 Dealing with the Demonic: Spiritual Warfare Welcome back to the Creature Code Podcast! In this episode, we step directly into the spiritual trenches. We are joined by a legendary figure in the world of deliverance ministry and paranormal investigation: Father Robert "Bob" Bailey, widely known as the "Paranormal Padre." With over three decades of experience since his ordination in 1993, Father Bob brings an unparalleled level of theological authority and real-world experience to the table. We dive deep into the realities of spiritual warfare, the hierarchy of the angelic and demonic, and what it really takes to confront the darkness. Founder: The Holy Sword Apostolate. Active Consultant: Trusted clergy consultant for prestigious organizations including NESPR (New England Society for Psychic Research), PRS, and P.E.R.S. Iconic Collaborations: Honored to have worked closely alongside the late, legendary Lorraine Warren, as well as Michelle Belanger, Chip Coffey, and Ryan Buell. BIO Father Robert Bailey Father Bob Bailey, aka the "Paranormal Padre," is a retired Roman Catholic priest highly skilled in spiritual warfare, and in deliverance ministry, being well versed in the Angelic and Demonic. Father Bob is the founder of the Holy Sword Apostolate. He is also the clergy consultant for NESPR, PRS, P.E.R.S. Fr. Bob carries a Masters in Theology, and was ordained to the priesthood in 1993. He is honored to have had the privilege of working closely with the late Lorraine Warren, in addition to Michelle Belanger, Chip Coffey and Ryan Buell. Fr. Bob has appeared on A&E's ‘Paranormal State,' Animal Planet's ‘The Haunted,' as well as Discovery's ‘Expedition X,' and talk show, ‘Haunted Happenings' (later called ‘Confronting The Darkness.' As Seen On TV: A&E's Paranormal State Animal Planet's The Haunted Discovery's Expedition X Confronting The Darkness (formerly Haunted Happenings) United Public Radio & UFO Paranormal Radio www.uprntalkradio.com

Block's Buzz is an open, self-hostable workspace for humans, AI agents, chat, and code; and it may be the most Linux-friendly vision for what comes next.Sponsored By:Jupiter Party Annual Membership: Put your support on automatic with our annual plan, and get one month of membership for free!Managed Nebula: Meet Managed Nebula from Defined Networking. A decentralized VPN built on the open-source Nebula platform that we love.Support LINUX UnpluggedLinks:Jupiter Broadcasting Buzz CommunityWeb Boost — Send us a boost via sats or USD

Episode 423 of Tom Clark's Main Event is a preview of AEW Redemption. Tom and Chris Patton discuss the entire match card, including Andrade's National Championship match with Mark Davis, and whether the former member of the Don Callis Family will come out on top. The guys give their predictions for each match, and discuss current storylines, as well as the pushback from many fans that this even feels like a tacked-on show that seemingly doesn't have a purpose. From there, it's onto the G1 and the current block standings of the tournament so far. All that and a lot more! Boink Studios podcasts are created by humans. All hosts featured on our shows are human, and all podcast artwork, logos, and creative direction are created by humans. Subscribe on YouTube: https://www.youtube.com/@boinkstudios Visit us at: https://boinkstudios.com Appreciate the content? Support the channel: https://buymeacoffee.com/tomclark Follow the Main Event: Facebook: https://www.facebook.com/tomclarksmainevent Bluesky: https://bsky.app/profile/boinkstudios.bsky.social Listen to Boink Studios' Podcasts: Tom Clark's Main Event: https://podcasts.apple.com/us/podcast/tom-clarks-main-event/id910362334 Tom Clark's 6M Podcast: https://podcasts.apple.com/us/podcast/tom-clarks-6m-podcast/id1441274603 Bare Mode: A Podcast Review of The Bear: https://podcasts.apple.com/au/podcast/bare-mode-a-podcast-review-of-the-bear/id1828513020 Two Nations Under Ted: A Ted Lasso Podcast: https://podcasts.apple.com/us/podcast/two-nations-under-ted-a-ted-lasso-podcast/id169387035   Music by Mr Maph aka Dogman Rukus, PPL 0103166534, PRS 1136021800 © Boink Studios 2026

272 - Marc Diamond (the Dwarves) In episode 272 of “Have Guitar Will Travel”, presented by Vintage Guitar Magazine, host James Patrick Regan speaks with Marc Diamond guitarist with the Dwarves known as “the Fresh Prince of Darkness”. In their conversation Marc tells us about the trials and tribulations of living in LA and his history with the Dwarves including 26 years with the band and writing and playing on the new record “JENKEM”. Marc discusses growing up in the San Fernando Valley in California and his exposure to music including taking a lesson from Nino DeFranko from the DeFranko family and he tells us about his hero's Steve Jones, Johnny Thunders and Keith Richards. Marc describes getting signed early on during the end of the hair band era and the disappointments of the record industry at that time. Marc takes us through why he stopped touring and his day job as a teacher and his role in choosing the touring guitarists. Marc describes his gear now and through the years and the need for cheaper guitars for touring and the ease of having support acts provide backline. To find out more about Marc you can go to the Dwarves website: thedwarves.com Please subscribe, like, comment, share and review this podcast! #VintageGuitarMagazine #MarcDiamond. #theDwarves #GibsonGuitar #PunkScene #JENKEM #JamesPatrickRegan #theDeadlies #haveguitarwilltravelpodcast #HGWT #tourlife https://www.patreon.com/cw/HaveGuitarWillTravelPodcast . . . Please like, comment, and share this podcast! Download Link

Podcasting 2.0 July 24th 2026 Episode 266 - "Research Velocity" Show Notes -------------------------------------------------------------------------------------------------------------------------------------

Brian, Blake, and Richard are back for Episode 627 of the Chasing Tone Podcast - Experimental backing tracks, Fender vs the entire planet, and robot rock starsBrian has been experimenting in his secret laboratory and reveals that AI-generated backing tracks are getting scarily good. The guys explore how far this technology has come and their conclusions may surprise you. This leads to a deep and heartfelt conversation about why playing music matters, why it can never truly be replaced by technology, and whether robot rock stars performing on stage could actually become a thing. There are also some sad farewells to Jennifer Finch of L7 and Wayne Charvel, who both passed away.Brian has been renovating his studio with LED-lit pedal shelves and proper sound panels, and he has some new Bigler pickups to try. Meanwhile, the Fender legal saga has somehow gotten even worse - they're now going after Thomann, Yamaha, and an Australian secondhand guitar retailer. The guys are genuinely baffled and discuss whether Fender have managed to pull off the most spectacular act of brand self-destruction in guitar history. Richard has a PRS-shaped solution.The Rolling Stones have a new album out and Richard highly recommends it, Anthrax have a cracking new single, and the World Cup halftime show featured Madonna flanked by two footballing legends dressed as Teletubbies. Richard reveals that an Iron Maiden guitarist was fired for listening to the Eagles on the tour bus, and the guys debate the merits of mystery pedal boxes.Headstock Socks, The Defenderiser, Eastern European Clown Music, Brad Womp, Breaking the Fourth Wind...it's all in this week's Chasing Tone!We are on Patreon now too!Support the show (https://www.patreon.com/chasingtonepodcast)Courses and DIY mods:https://www.bluesguitarmethod.comhttps://www.betterguitartone.comhttps://www.wamplerdiy.comhttps://www.guitarpedalcourse.comCheck out Oliver Effects:https://oliverfx.co.ukYoutube:https://www.youtube.com/@chasingtonepodcastFind us at:https://www.wamplerpedals.com/https://www.instagram.com/WamplerPedals/https://www.facebook.com/groups/wamplerfanpage/Support the show

In this episode, Kat Cosgrove (SIG Docs Technical Lead, SIG Release Subproject Lead, and Steering Committee member) and Natali Vlatko (SIG Docs Co-Chair, Steering Committee member for the TODO Group, and Open Source Architect at Cisco) join hosts Kaslin Fields and Abdel Sghiouar to discuss the newly published Kubernetes AI usage policy. We dive into the legal and administrative reasoning behind the policy—including why AI tools cannot legally sign the Contributor License Agreement (CLA) or co-author PRs—and explore how maintainers manage the influx of "AI slop" PRs, spam comments, and restricted AI note-taker bots in community meetings. The discussion highlights the balance between human accountability and AI as an enhancer, while sharing actionable advice on how new contributors can sustainably get involved with SIG Docs, issue wrangling, and the Kubernetes Release Team. Do you have something cool to share? Some questions? Let us know: web: kubernetespodcast.com mail: kubernetespodcast@google.com twitter: @kubernetespod bluesky: @kubernetespodcast.com News of the week Apple Native Container Tool for macOS 1.0: Apple has shipped version 1.0 of its native container tool for macOS. Built in Swift specifically for Apple Silicon, it departs from traditional shared-VM setups like Docker Desktop by isolating every single Linux container inside its own dedicated micro-VM using the native macOS Virtualization framework. Read more on Cloud Native Now. Google OpenRL: Google launched OpenRL, a new open-source project designed to streamline the training and reinforcement learning loops of large language models. The tool brings declarative, Kubernetes-style resource orchestration concepts to the messy process of AI model fine-tuning. Read more on Cloud Native Now. CNCF Welcomes New Members: At KubeCon CloudNativeCon India, the CNCF announced they added 14 new members, end Users, and non-profit organizations, highlighting the continued growth of the Cloud Native Ecosystem. One of the new members is Loveable, who was a recent guest on the show. We highly recommend you go listen to Episode 268 about the Agent Sandbox. Read the full announcement on PR Newswire. Is a Pod the Right Deployment Unit for an AI Agent?: Lin Sun from Solo published a community post on the CNCF blog questioning whether the classic Kubernetes Pod primitive is still the best abstraction for hosting autonomous, long-running AI agents and introducing Agent-substrate, a project attempting to bring a solution to the table. Read more on the CNCF Blog. Links from the interview Kubernetes AI Usage Policy – Read the community's official guidelines and rules for AI-assisted contributions. TODO Group Steering Committee – A Linux Foundation project bringing OSPO professionals and enthusiasts together. Contributor License Agreement (CLA) – Standard agreement required for all human contributors, which AI agents cannot legally sign. Kubernetes SIG Docs – Get involved with the documentation community. SIG Docs Style Guide – Learn the style guidelines for contributing to Kubernetes docs. Kubernetes SIG Release – Details on how to get involved with the release cycle. Links from the post-interview chat Linus Torvalds on AI LinkedIn Post – Torvalds' clarification on using AI as a helper tool rather than writing kernel C++ code. Devoxx– A popular developer conference in Europe Prowbot GitHub Repo – Kubernetes' main CI/CD bot handling PR automation.

Dr. Dan Rossi joins Beast Over Burden to talk about strength training, aging, injury, confidence, and why muscle mass matters beyond the gym. As a hospitalist and internal medicine doctor, Dan sees older patients at some of the hardest points in life. That perspective has changed how he thinks about training. Strength is not just about chasing numbers, looking athletic, or reliving old football PRs. It is about building a foundation for the decades ahead. Dan shares how he returned to focused barbell training in his 40s, worked around a demanding seven-days-on, seven-days-off hospital schedule, recovered from a shoulder setback, and rebuilt confidence under the bar with the help of his coach, Nick Solon. This conversation covers what it means to get strong again, why form feedback matters, how strength changes the way you move through the world, and why you do not have to work on a farm to become "farm strong." PS - IF YOU'RE INTERESTED IN TAKING ONLINE COACHING FOR A TEST RUN, CHECK IT OUT HERE.    Connect with the hosts Niki on Instagram Andrew on Instagram Connect with the show Barbell Logic on Instagram Podcast Webpage Barbell Logic on Facebook Or email podcast@barbell-logic.com

271 - Paul Leary (Butthole Surfers, Producer) In episode 271 of “Have Guitar Will Travel”, presented by Vintage Guitar Magazine, host James Patrick Regan speaks with Paul Leary guitarist and producer from the Butthole Surfers. In their conversation Paul talks about the documentary on the band and a recent show they did at the screening… and the demise of the Butthole Surfers and his retirement. Paul describes his gear currently and throughout the run of the Butthole Surfers including a Fender Custom Shop Strat made by John Cruz and he takes us through guitars that got away. Paul takes us through growing up in San Antonio and how seeing the Beatles on tv gave him the guitar bug and his guitar education playing in jazz bands. Paul discusses how he and Gibby met in college and how they started the band that eventually became the Butthole Surfers and how the name came about. Paul tells us about being produced by John Paul Jones and himself being the producer for U2, Sublime the Meat Puppets and the Reverend Horton Heat. Paul then discusses the rigors of touring and traveling as the Butthole Surfers and he describes how the documentary came about. To find out more about you Paul can go to his website: buttholesurfers.com and the trailer to the documentary on the band is here: https://youtu.be/UFtkc11i3uE?is=eVs2-vOdh8cTr1Q- Please subscribe, like, comment, share and review this podcast! #VintageGuitarMagazine #PaulLeary #ButtholeSurfers #JohnPaulJones #FenderCustomShop #JohnCruz #Sublime #GibsonGuitar #JamesPatrickRegan #theDeadlies #haveguitarwilltravelpodcast #HGWT #tourlife https://www.patreon.com/cw/HaveGuitarWillTravelPodcast Please like, comment, and share this podcast! Download Link

In this episode, we travel through the time stream once again with the legendary philosopher, mystic, and esoteric teacher Manly P. Hall for his profound lecture, “The Openers of the Doors to the Invisible,” originally recorded on June 2, 1985, at the Philosophical Research Society in Los Angeles.Hall explores humanity's timeless search for a personal experience of reality and the hidden inner faculties that may allow us to move beyond the limitations of the physical world. He examines dreams, mystical visions, ancient wisdom traditions, our relationship with nature, the dangers of an undisciplined mind, and the deeper intelligence that exists behind our thoughts, emotions, and physical form.Throughout the lecture, Hall reminds us that we cannot discover something better without first becoming better ourselves. Opening the doors to the invisible is not achieved by escaping the world or searching endlessly outside ourselves. It requires quietude, patience, integrity, compassionate service, and the gradual cultivation of our inner lives.After the lecture, I return to explore Hall's message about the Over self, the importance of controlling how we respond to external forces, and the daily process of raising our frequency through conscious thought and action. As we bring the interior into harmony, the gates of wisdom begin to open, allowing greater awareness, love, and service to move through us.This is another timeless transmission from one of the greatest philosophical minds of the modern era.Drop In!Manly P. Hall Bio:Manly Palmer Hall (March 18, 1901 – August 29, 1990) was a renowned philosopher, author, and mystic who delved deeply into esoteric traditions and spiritual knowledge. Born in Peterborough, Ontario, Hall moved to the United States at a young age and soon became a prominent lecturer on occult and metaphysical topics. His curiosity and passion for ancient wisdom culminated in the publication of *The Secret Teachings of All Ages* in 1928, Over his lifetime, he authored more than 150 books and delivered over 8,000 lectures. His teachings spanned subjects such as Hermeticism, Rosicrucianism, astrology, comparative religion, and the symbolism found in sacred texts.In 1934, Hall founded the Philosophical Research Society (PRS) in Los Angeles, a center dedicated to the study of philosophy, comparative religion, and personal development. The PRS continues to preserve his vast collection of manuscripts and teachings.Hall's work has had a lasting impact on those seeking spiritual growth, often serving as a bridge between modern spiritual seekers and ancient wisdom traditions. Despite passing away in 1990 under mysterious circumstances, Hall's influence remains significant among students of esoteric and philosophical studies. Hosted on Acast. See acast.com/privacy for more information.

Episode 422 of Tom Clark's Main Event is an open assessment of AEW. Tom talks about some of his frustrations with Tony Khan's booking, and questions why some big name stars are currently M.I.A. Where is Swerve? Where is Hangman? What is happening with Redemption, and why does the event feel like a tacked-on pay-per-view that serves no purpose? Tom gets into that, and a lot more. What are your thoughts? Is Tom on track or is he missing the point? Let us know! Boink Studios podcasts are created by humans. All hosts featured on our shows are human, and all podcast artwork, logos, and creative direction are created by humans. Subscribe on YouTube: https://www.youtube.com/@boinkstudios Visit us at: https://boinkstudios.com Appreciate the content? Support the channel: https://buymeacoffee.com/tomclark Follow the Main Event: Facebook: https://www.facebook.com/tomclarksmainevent Bluesky: https://bsky.app/profile/boinkstudios.bsky.social Listen to Boink Studios' Podcasts: Tom Clark's Main Event: https://podcasts.apple.com/us/podcast/tom-clarks-main-event/id910362334 Tom Clark's 6M Podcast: https://podcasts.apple.com/us/podcast/tom-clarks-6m-podcast/id1441274603 Bare Mode: A Podcast Review of The Bear: https://podcasts.apple.com/au/podcast/bare-mode-a-podcast-review-of-the-bear/id1828513020 Two Nations Under Ted: A Ted Lasso Podcast: https://podcasts.apple.com/us/podcast/two-nations-under-ted-a-ted-lasso-podcast/id169387035   Music by Mr Maph aka Dogman Rukus, PPL 0103166534, PRS 1136021800 © Boink Studios 2026

Training through back pain does not mean forcing your old numbers or pretending nothing hurts. In this Beast Over Burden episode, Niki Sims and Andrew Jackson discuss Niki's long process of training through and around back pain. Niki shares how her mindset shifted from trying to get back to heavy barbell lifting as fast as possible to focusing on training consistently, building muscle, and finding movements that felt productive. That shift changed everything. Instead of measuring progress only by old PRs, Niki learned to use more exercises, modify movements, manage recovery, and train hard without constantly aggravating her back. Niki and Andrew also talk about the role of machines, belt squats, leg presses, controlled training, recovery, travel, jiu-jitsu, and patience during a long injury process. This episode is a realistic conversation about pain, progress, training identity, and learning how to keep going when your body does not cooperate the way you want. PS - IF YOU'RE INTERESTED IN TAKING ONLINE COACHING FOR A TEST RUN, CHECK IT OUT HERE.    Connect with the hosts Niki on Instagram Andrew on Instagram Connect with the show Barbell Logic on Instagram Podcast Webpage Barbell Logic on Facebook Or email podcast@barbell-logic.com

“Your intuition is giving you the truth.” In this episode, Nick shares insights on the importance of rest, self-awareness, and listening to your intuition to improve mental health and productivity. He discusses personal experiences and practical questions to help you recognize when you’re feeling “off” and how to realign. What to listen for: The importance of rest and self-care Recognizing signs of burnout and feeling off Using intuition and body signals to guide actions The role of self-awareness in mental health The process of pausing and realigning during busy times Personal stories of overcoming burnout The significance of small moments of reflection Tools for developing intuition and self-checks Encouragement to take regular rest and listen to oneself “Take a moment to rest and ask yourself what feels off, and then move along from there” Pausing for a moment between thought and action can drastically change our approach When we feel “off” inside, there's a signal being sent up to say “hey! There's something you need to look at in here” “We get to choose: Do I just put some dirt on it and keep going? Or do I pause for a second and ask, “What's up? Why am I feeling this? What am I actually feeling right now?” Understanding we have a choice in every moment, even if the only choice is how we respond Checking in with ourselves periodically brings attention to our feelings and can ultimately lead us to our desires When we know who we are at our core, we then have a gauge for when we're feeling “off” from that core. About Nick McGowan I'm Nick McGowan, an entrepreneur, podcaster, and mental health advocate, and I’ve been on a 20+ year journey of personal development, learning to master my mindset, emotions, and the art of living with purpose. As a Mindset and Self-Mastery Mentor, I work with ambitious men and women who want to live their most authentic and joyous lives by helping them master their mindset, emotional awareness, and authentic communication. My mission is to empower people to lead lives that feel aligned, grounded, and truly their own. Throughout my career, I've built teams, streamlined systems, and improved client experiences across SaaS, media, marketing, and personal development spaces. Whether I'm leading cross-functional projects, optimizing SEO, Podcasting, designing strategies, or guiding clients through transformation, I bring a hands-on, solution-focused approach to everything I do. I'm also the host of The Mindset and Self-Mastery Show, where my guests and I unpack the stories that shape us, challenge us, and ultimately guide us back to who we are at our core. On this show, we uncover the secret gems others have discovered through trial and error and breakthroughs, so you can fast-track your growth and master your mindset in your pursuit of self-mastery. Check out the latest episode here. With years of podcasting and two decades of marketing experience, I've mastered the storytelling, interview flow, strategy, and technical production that elevate a podcast from “just content” to something truly impactful. Whether you’re a leader looking to amplify your message, a seasoned speaker and podcast host looking to sharpen your edge, or even a beginner who is wondering how to share their message, I mentor thought leaders through every step of having the conversation they’re here to have on this planet. So, what message are you here to share?! https://nickmcgowan.com/ https://www.linkedin.com/in/thenickmcgowan/ Resources: Check out other episodes about adjusting our mindset for rest and transition Internal Reflection And Self-Care With Dr. Nekeshia Hammond How To Transform Your Mindset And Boost Performance With Steve Magness Interested in starting your own podcast or need help with one you already have?Learn how Nick can help! Learn more about our host, Nick McGowan: https://nickmcgowan.com/ Thank you for listening! Please subscribe to the show on iTunes and give us a 5-Star review! https://podcasts.apple.com/us/podcast/the-mindset-and-self-mastery-show/id1604262089 Listen to other episodes here: https://themindsetandselfmasteryshow.com/ Watch Clips and highlights: https://www.youtube.com/channel/UCk1tCM7KTe3hrq_-UAa6GHA Guest Inquiries right here: podcasts@themindsetandselfmasteryshow.com Your Friends at “The Mindset & Self-Mastery Show” Click Here To View The Episode Transcript Nick McGowan (00:04.814)Hello, and welcome to the Mindset and Self-Mastery Show. I’m your host, Nick McGowan. Today on the show, I want to talk about us just taking the time to give ourselves rest. I think there are times where we as people will just drive ourselves crazy. we drive ourselves mad, just doing all these things, all the things that we feel other people are telling us to do or the world tells us to do. Sometimes we just need to rest. And I wanted to take this time to share a message of suggesting that you rest, partially because it’s coming from a personal experience. I have been working a lot over the past few months, working a lot of a lot of projects for clients. I have my own strategy for the podcast and I’ve updated that. I six months of content I put out and all aligned so that we’re on the same page. I’m not just blasting out random messages and stuff like that. But doing all that work because of a really challenging end to a chapter that happened recently got me to a point about a week ago where I could feel there’s a little bit of burnout starting to set in. The reason why I’m doing this episode now is today is one of those days where I’ve canceled a few meetings and instead chosen to make a podcast episode. I have a client call later today, some project work to do, and then a bunch of music to play. And that is my choice, but it’s also my choice to make sure that I’m choosing those things for my health. I think there are times where we will do things consistently and we get into a pattern almost like how you can probably drive to the grocery store without even really thinking about it. We just we just do it subconsciously. We’re just travel there and we’re good. Sometimes we’ll be thinking about something else or you know, maybe you’re texting or looking at your phone or whatever, and you just magically end up at the store. Sometimes that happens in life more so than we think about it. Going to your office, picking up your kids, going out to meet with friends, whatever the things are, even if they’re novelty or something you don’t do all the time, you can still get in the habit and just be used to doing those things without actually asking yourself, why are you doing those things? Sometimes it’s also really tough to ask yourself, why am I still here? Or why am I doing this? Or Nick McGowan (02:34.358)Why with whatever it is? Could be a job, could be a relationship, could be something you’re experiencing inside, something that you’re trying to work on or work through. Either way, as those situations happen, we have an opportunity and a responsibility in some ways to be able to look at that and say, well, do I want this? Do I not want this? Is there something underneath that’s telling me, hey, something’s slightly off? And it can be really easy to not listen to that. You’ve probably gone through things where you look and it’s let’s say the holiday season. Next thing you know, it’s summer. Here we are. I’m recording this in June. So by the time you listen to it, it’ll probably be July, middle of the summer. You might be on vacation, you might be doing different things. There’s a lot of pushing and pulling, of taking people different places or vacations. People come into town, or you go visit different people or Just a weekend at the beach or the mountains or whatever that thing is. But those things aren’t always as restful as we need them to be. Sometimes the moment that we really need is a bit of a longer moment to just be restful. So let’s just hang out for a second. Just rest. Are you in your car? Are you at the office? Are you at home? You have a lot of people around you. Are you like in a coffee shop with everybody doing their thing around you? No matter where you’re at, I challenge you to take this moment just to be. Now, if you’re driving, don’t close your eyes. just be, just be present, just be here. And is there some feeling that comes up? Something that says, maybe this feels good, I don’t experience this enough, or something that says, you know, this feels really bad because I don’t feel like I can or should experience this. Those are telltale signs to tell us that there’s something that’s going on underneath. If we get past or through, or even around that, we think about there are times where we feel somewhat off. Nick McGowan (04:51.146)Let’s unpack that a bit. In those moments where you feel off, at least for me, when I feel off, there are different flavors to what’s off. The burnout that I feel at times is most often because I’m doing things that, yes, I may really enjoy those, because I really do my best to not do the things I don’t enjoy anymore. Obviously, there are responsibilities and things that we kind of have to do. Like, I don’t really want to pay for my car. But I want to keep my car so I will continue to pay the car note, you know, like that sort of thing. but then there are other things that we do that if we just adjust those slightly or take a pause, just a beat for a second, step back and say, what am I feeling? What’s feeling off right now? I’ve learned with myself that I can ask those questions and go maybe within like a 24, 48 hour range. What happened yesterday? Or is there something coming up in a few days? That I’m maybe concerned about or worried about or even just processing through. Like I have a I have a meeting coming up in a few days. It’s an event where I’m speaking and talking with lot of people and I’m excited. There’s also a little bit in there of like, what should I prep, or what else do I need to get ready for, or what have you. So we all have those little things that just they’re processing in the background. That’s different than not having the energy or the drive or the motivation even. To start or continue on with the thing. It’s in those moments where we get to choose: do I just put some dirt on it and just keep going? Or do I pause for a second and say, what is up? Why am I feeling this? What am I actually feeling? I had an experience the other day where I was at kind of a crux point in a sense, like a fork on the road, where I could keep on a path. I was working on a client project and I was at a spot where I don’t know, maybe another five, 10 minutes, and I could have been like, cool, I can put a bow on that. I can just move along and I can go do something else. But I felt for like a solid 15, 20 minutes leading up to this moment, just not right. Like I just didn’t want to do it anymore. There are different times where we as people can just like not want to do a thing. I don’t want to be here anymore. And you can just Irish exit or walk out or run or whatever. then there are other times where we think, well, I don’t want to be here because of something or some situation or this is Nick McGowan (07:19.042)Hard or tough or what have you. I go through those, like I’ll ask those questions. So I’ll take a little bit of a step back, especially in that moment. I sat back in my chair and was like, what am I feeling? Is it just that I don’t want to do this right now? That I just want to do something else? Like it is is it as simple as I just want to go walk outside for a minute? Like just not be in this energy? And asking those initial questions will help us understand if there’s something that’s really close to it. That we can say, it’s this thing. Duh, let me just take care of that. And then we’re good and you’re good to go. I’ve experienced that where it’s like, well, I felt like this nagging thing was in the background. Like I need to go switch over the laundry or something like that. Be well, instead of just pushing that off, let me go do that. Let me just take the five minutes to do it, come back and be good to go. Then you’re done. You’re no longer thinking about that. That’s no longer processing back there. But that’s vastly different than there’s something underneath it all. That is like, I don’t think this is the right time for you to do this. So that moment that I had, I went through, I went through my questions and was like, what is it? What am I feeling? What do I want? It wasn’t that I didn’t want to do the project. I could have just kept going with the project. It was literally one of those situations where I was like, you know, I could keep going on this thing and I could probably spend another three, four hours doing this. And it would have been okay. But not exactly what I needed to do. And I knew that. Nick McGowan (09:08.76)So when I asked myself, do I really want to stop this or do I just want to keep going? Like I knew I was at a time where I could keep going. Again, I could do it for another three, four hours, be totally good. And then maybe at the end of that, go, my God, I don’t even want to look at my computer. Let me go do something else, like out of the house or wherever, you know. but I felt in that moment, like this is one of those really good moments where I go, Well, I could keep down this path and I’d probably be okay. And not totally burn out or feel like I wasted the day or anything like that. Or I could sit here a little longer, another minute or two, and figure out what’s really underneath of it. So I ended up putting that project to the side, actually stopped at that moment, which I don’t think that I have OCD, but there are times where, and you’ve maybe experienced this, like if you just spent another five, 10 minutes on a thing, you would have gotten to a point where you go, cool, bow tied. I’m able to put that to the side. Then when I come back, I can kind of start freshly with it. I just stopped. I was like, this is where I’m at. I’m done. When I opened the project the next time, it did take me an extra few minutes to go, all right, cool. I see what I did. Cool. Perfect. And I was able to move from there. So it’s not like it messed anything up, but in that moment, I didn’t really care. It could have put me back another half hour, or it could have potentially put me ahead by doing something different. So stopping that thing, I felt the power that I have the ability to be able to say, no, and that doesn’t feel right for me to do right now. I also understand that this isn’t always the case for everybody. You can’t be in the middle of a meeting and say, I don’t want to be here right now and expect that it should just be okay. You can’t be in the middle of a conversation with your kid or your partner and just go, I don’t want to be here and expect that it’s going to be okay. That’s just not how those things work. But in these different little experiences, and especially when we’re by ourselves, I think that’s where we get to work on this stuff. So if you’re in your office or you’re at home or you’re wherever you’re at, and you feel that moment of this doesn’t feel right for me to do. And you start to ask yourself, is it because I just don’t want to do the thing anymore? Or is it because I feel like I really want to go do something else? Like I’ve experienced that at times where I’m like, there’s some basketball game or something on. Like, I don’t want to do this thing. I want to go watch the game. Nick McGowan (11:35.37)And sometimes I will, sometimes I’ll do both, and you know, whatever. Like, but we get to figure that stuff out in those moments. So if you ask yourself in those moments, like, what’s going on? What am I feeling? Do I really want to do this? Do I not want to do it? Is it is there something underneath of it all? And really what I’m trying to get to is that underneath layer. Like, find what’s underneath, like what’s what’s boiling the magma underneath there? It’s starting to make the ground shake in a sense. Because then in that moment you’re able to understand if I put my energy into that. That’s potentially going to help the rest of the energy that I have. And also probably that other project. So when I stopped working on that project the other day, I knew I could keep going. And there was a part of me that was like, man, you got it. Like you can just keep going. Just knock this thing out. Close this chapter of this project so you can move along to the next thing, which does make me feel really good. I love being able to kind of close things out and go, Great, I’m gonna hand it off to the client, or I’m gonna hand this off to this person. You take it. Great, and I’m good, and I can move along to the next thing. I also know about myself that I’m a project person. I really love my projects. I’m multi-passionate, but I love digging into the things that I do. You may be similar. So if you enjoy that, it can be hard at times to stop on a project. But again, back to that moment. I stopped that project a little earlier than I wanted to and moved along through a series of a few different events that led me to a breakthrough. And the reason why I put it that way. Is because it took me walking outside, getting in my car. I went to the post office because I had to drop some stuff off and came back, cleaned up the kitchen a little bit and went to the bathroom. It just like did odds and ends little things here and there, but also things that felt like I was led to do. Just like as simple as the bathroom. Like we know when our bladder’s like, yo, dude, you gotta go. So you just kind of walk your way on back. Same deal. could feel it intuitively of like, I’m gonna go step outside. I’m just gonna run to the post office. I’m gonna clean up the kitchen. I’m gonna go to the bathroom, I’m gonna do this, gonna do that. Within about, I don’t know, maybe 15, 20 minutes, 30 minutes, something like that. Post office is only a few minutes away, so it’s not that big a deal. But within a short period of time, I was back at my computer and had my guitar in my hand. And I just felt more at ease. Nick McGowan (13:59.862)It’s not like there was better or some major difference, but I could feel a little lighter and a little more at ease. I’ve realized that that tells us that we’re doing something more right for ourselves. Not like we were doing things wrong before, but this is one of those things that feels more right to do. Great. It can also go against the system of the world that says you’re not doing enough, you’re not producing enough, you’re not. Creating, you’re not blah, blah, blah, blah, blah, blah, blah. And I felt some of that where I was like, I’m not doing the project work stuff. That’s money and that’s clients. And I appreciate my clients. I appreciate the money. I love working with the people I do and like I’m on I’m on board with them and their projects and like I’m in it with them. And also can still pause that, take a step away, do some other things and work on our own projects. The main reason why I’m talking about this and that it stood out to me. was I’ve been writing an album for several years. You’ve probably heard me talk about how I reformatted a hard drive about a year ago and lost everything. so I’ve started over again. And even in the past two months, maybe month and a half, two months, I’ve taken the songs that are going to go on my album and I’ve said, great, I’m here where they’re at with their demo, and just put them to the side and start it over. I literally picked up my acoustic and just started to build the song again from a single player, a singer, songwriter, and just build it and then turn it to a band and all that stuff, et cetera. So I’ve been working through this and literally reworking these things. So that’s where I ended up getting to was one of these songs. I have been bashing my head in a way to try to figure out the chorus of one of the songs. And it’s just not feeling right. Just not. If you’re creative and you have different projects you work on, you know there are things, even if it’s with your hands, like playing an instrument or woodworking and stuff like that, where you’re just not fully there yet. It’s not fully done. Like a a piece maybe isn’t fully sanded down or fully completed. We know when it is. We can feel it inside of us. And in that, I don’t know, maybe thirty, forty-five minutes or so that I was just messing around, just getting my energy right, I figured out the chorus. Nick McGowan (16:24.566)And it literally came from a frustration point of saying, I don’t like this. I really don’t know where to go with it. But I know that there’s something here. I know that I know the messages within it. I just need to hear it. I need to feel it and then let it come out of me. So I literally hit record and just let it come out of me. And it did. I don’t think this is going to be like one of those classic songs that people will cover and sing for. eons, maybe, who cares? I don’t know. I don’t really care. But I know that that moment happened because of the other moments that happened. I took the moment to say something feels off. Huh. What do I do? Well, what can I do to feel on? You know? How can I make this change? And asking those questions and intentionally looking for the feeling that I would have inside for the intuition to go, go this way. Go that way. Try this thing, do that. I’ve learned with my intuition, and I believe this is probably true with everybody’s intuition, that it’s giving us the truth and it’s suggesting things that feel deeply connected to our bodies. That could be get the hell out of this place, or that could be go run toward that person and talk to them, or whatever it is. And it’s not a mental thing. It’s an intuitive, it’s a body, it’s an energy thing that we feel, this is it. This is where I’m going. This is where I feel led to. There was probably, I don’t know, a series of 10, 20 different ones of those, like little check-ins and stuff, just in that short, let’s say hour amount of time. The time from having the feeling and then starting to do things outside of that, and music and working on it and all, et cetera. That to me is life. Like those moments where we get to actually think about that and break that down, especially right now, as you’re listening to this and as we’re talking about this and breaking this stuff down, this is a safe kind of lab space to be able to work on this stuff. It’s because when we do that work now, when we get into those situations, we then get to go, you know, I’ve been here before. Even if it was mental reps or Nick McGowan (18:40.364)I’ve been somewhere close to it or I feel a little bit more confident in being able to go into this, even if I don’t know exactly what the hell’s going on or how it’s going to work out or whatever. We’re more equipped in that moment. I think about it as like game tape with athletes. They’ll watch what they did and then they’ll watch how terrible they played or whatever it was and look at the nuances and changes. Not so they can go, man, all right, well, I want to go back to yesterday and redo the game. No, you can’t do that. At least science hasn’t shown us how to do that yet. So they’ll take that and go, all right, cool. So next time when I’m in that exact spot, what I should do is actually go right instead of left and then pivot on one foot or whatever. They’ll lock that into their brain. Same for us. Like with that moment, I was like, something feels a little off. And I’ve learned from my years of doing this that I go, huh? Let me pause. What is it? And I don’t turn it into some big weird thing. Like, I mean, this is this is a teaching, an educational kind of experience in a sense. Where you’re listening and taking this in to go, all right, cool, I hear you, dude. And yeah, next time I’m in this sort of situation, I can do this thing. But it’s not like I’m in those situations. I’m like, my God, this is the biggest thing ever. I’m so excited. No, most times it literally just happens and I’m like, fuck, what the fuck do I feel all for? And I’ll start to work through this. And I’ve realized that these frameworks that work for me, work for other people, but that they they all work in the way that they work. Like I’m not a huge fan when somebody says, here’s a thing that I figured out. I don’t give a shit what your context is, just like go do it, and you will have the exact same experience. It doesn’t make any sense, like at all, because everybody’s context, everybody’s life, everybody’s experiences are so different. Even the same people who grew up the same way, the same house, experience different things. So those moments in that little framework, it’s just a series of questions of check-ins. Which you can do with nobody knowing. So you can be in your office thinking, do I really want to be here anymore? What’s going on? Why really want to slap that person in the face? Cause the thing they just said was the dumbest thing I’ve heard all day. well, I’m typically not a violent person, so why do I want to slap them? You know, like thinking through that sort of stuff. but really taking a moment just internally to check in and say, What am I feeling? What’s happening right now? Because if you know at your Nick McGowan (21:05.72)Core that you are naturally one way, or your tendency is toward one way, and you’re off from that, then that’s a simple deduction. Like those two things aren’t aligned, you’re off. I know at my core, I’m naturally curious and really inquisitive. Like I ask a lot of questions, I’m super curious, and I see patterns and things, and I’m joyous and I get all excited. I also know there are times where maybe I only slept four hours that night before. So I’m not naturally that way, but I can realize the difference between my body just feels drained, or I at a soul level feel drained. But it’s not often clear right up front. So my challenge to you is in those moments, next time one of those moments comes up where you feel slightly off, just pause and sit in yourself and ask what feels off. Again, if you’re in like a meeting or in front of people or something, you’ll need to just do that quickly internally. And I say quickly in the sense that I don’t want you to get through it just to get through it. I want you to figure out as quickly as you can, intuitively, like what feels off. And just ask, all right, intuition, what feels off right now? And if you don’t hear anything right up front, okay. I think sometimes we can kind of calcify our intuition. And make it hard to hear the certain things. And the more work that we do and the more hearing we can hear from it, the louder things get, the more we can feel that. I’ve seen that within my experience and that might be similar to yours. I’ve heard that is similar with other people as well. It’s like a muscle. The more you work it, the more you work and the more you can hear it. So doing this and asking these questions will also help with that, but also then help you understand there might be something that comes up that goes, man, you’re really upset about what happened this morning with you and your partner. But here I am, six hours later in the middle of a meeting, talking about some production thing or some product or whatever the thing is. Understanding where you’re at and what feels off then gives us an opportunity and again a responsibility to either do something with it in that moment or to pause with it, kind of put a pin and then come back to it and do some work with it. If you’re able to do something in the moment, like I was in my situation, where I went, pause, I’m gonna go. Nick McGowan (23:27.042)Do something else because I can feel slightly off, then do that. If you can’t in that moment, then just get back to it a little later and get back to that feeling of what were you feeling in that moment. That’s why I like to be able to do this stuff as quickly as possible, because you’re right there and you’re feeling it. You don’t have to think back to it or try to get your body to remember what it felt like. You can then just go right there, like it just happened. I feel it right now. But taking the rest that you need. And the moment to be able to understand what’s going on is vastly important. And oftentimes we can get so swept up in how life is and everything that’s going on that you wake up in the morning and the next thing you know, it’s 10, 11 o’clock at night, and the whole day has just flown by. I think about how sometimes we as people, and especially millennials, we seem to just be drawn toward toward our phones to just have that dopamine after a little while. And I do that too. There are times where I’ll end up on Instagram or LinkedIn or Facebook or something for something silly. Like I pulled up, I I’m a group expert in a Facebook group for podcasters. I think there’s like 120,000 people in the group. It’s a pretty large group. So I’ll hop on every once in a while, look at somebody’s question or apply something back. And then next thing you know, it’s like 20 minutes later I’m just thumbing through looking at dumb shit. It’s like, but we as people will subconsciously pull ourselves back to that because it’s familiar. It’s also a little dopamine hits, et cetera. And it’s in that moment of understanding that I’m aware of this right now, where we can go, I just want to put this down and go do something else. And those little moments where we get to do something else and the responsibility and the action that we take at that point actually helps us become better in those tougher moments. Now that moment that I had of saying, I’m at a project point where I can stop or keep going, but I feel like there’s something else for me to do, isn’t the same pivot point of a building’s about to fall down or the world’s going to collapse. I I don’t know. I’m just making stuff up, but like these aren’t these aren’t life and death experiences. But there are times where that stuff can happen. And it’s this stuff now and these moments now when we can work on this to then be potentially in a better spot. Nick McGowan (25:46.67)It’s like you don’t know what’s going to happen in those times, but you can at least do the work leading up to it so that you know, look, I can probably handle this a little better than I would have been able to hadn’t I not done any of this work. So my challenge to you is take some rest. Take it this weekend. Take it over the course of the next week, two weeks during that rest, and whatever amount of rest that you get. Just sitting there by yourself. And I’m not talking about sitting on your phone or even reading or something like that. I’m saying just being, being with ourselves, because then we can listen to ourselves. And it can be really hard to do that at times, especially if you’re not used to it. No, for me, I get into just a rhythm with life where I’m just moving and grooving. There are times when I really understand I need to slow down and just listen. And it can be really loud, white noise to just sit there and listen. So my challenge is for you to do some of that in whatever capacity you can. And whatever time that you have, if it’s 30 seconds, if it’s a minute, if it’s two hours, who cares? Just spend the time over, let’s say, the next week or even a few days to be able to check in with yourself and understand what am I feeling right now? What’s happening? What feels off? Or on the opposite side of that, what feels totally on. Because then we can say, these things aligned with me and make me feel really excited and really on. How I do more of those things? Hell, that’s kind of how I got into the podcasting stuff. I’ve had my podcast for almost five years at this point, but started working with clients, podcasters, and thought leaders, maybe about a year into the podcast. And over the years, it’s just grown and grown. And I get more and more excited about working with people who are brand new or people who’ve been doing it for a little bit and trying to figure out strategy and just how all this stuff works. Because of all the stuff that I’ve done in the past. Nick McGowan (27:48.166)different moments I can look back to and go, I really didn’t like this one job, but I loved this part of it. And I loved meeting with these people who helped me understand this, et cetera. I guess an easy example, I’m very process driven because if I wasn’t, I would be all over the place. And I understand that about me. And I’ve also had it kind of beaten into me with different agencies I worked with and worked for, where we have to have a process in place. And that process allows us to kind of play jazz in the middle of it. Makes total sense. Great. So now I incorporate that in basically everything I do. I use a project management tool for all of life and don’t always use it, but I still have it and I work on it and I do these things to be able to help myself be in a better spot where I can say, this is more of what I want. And that’s really what it’s about, being more aligned with who we are at our core and doing things more so of what we want because of that alignment. Not like I just don’t want to be at my job, so I’m just gonna leave. Or I want to go spend forty thousand dollars on some crazy dragon PRS or something. Like, cool. I mean, you can do whatever you want, but in all reality, why are you doing those? Like, what is what’s the alignment with that? And what is the purpose to it? So again, thinking about the situation I went through, I could have kept working on the client project. I really enjoy my clients. I enjoy the project work. I’m a nerd with this stuff, so I could keep at it. Or something feels off. I can go do something slightly different and then use that energy in a different way. I I hope I am able to do that a lot more throughout life. And I suspect I will be able to, because I’ve seen that I’ve been able to. Over the past few years, more and more and more and more of that happens, which is why I have more of these episodes to be able to talk about these things, because I want you to be able to understand. Not only are you capable of doing this, but probably better of doing it than I am. And in your own way. This isn’t a competition. In fact, any of the stuff that I go through, I’ve learned that it’s really part of my responsibility to share. And the way that I look at it and how I’ve experienced these things, to share with other people, to then take that in their own lives. You might listen to this and go, cool, Nick, heard, but fuck, that sounds stupid. Okay. Nick McGowan (30:14.316)You might listen to this and go, Nick, that is wonderful. I felt the same thing. I appreciate the framework. I’m going to do more of this. Great. My job is just to share. Your job is to interpret the information, figure out what you want to do with it, and use some of it or not, and move along from there. My encouragement to you is to be able to take those moments of rest and really to be self-aware enough to see that you need that rest or that something is slightly off. The more that we can do that in the smaller moments, the more it’ll add up in the long term. So if you need help figuring out how to go about this way, figuring out how to become more self-aware, or just really struggling with your mental health or overall mindsets and trying to figure out what self-mastery means for you, then reach out to me. Offer free clarity sessions to be able to figure out where you’re currently at, where you want to go, and how we can get there together. And I would love to work with you and at least hear where you’re at with things. And if I can give you some free resources or guidance or wisdom, I’d be happy to do so. And also if it makes sense for us to work together on a mentoring perspective, I’d love to explore that with you. But please try this. Try, try, try this. Just take that moment. When you feel off, just take a moment to rest and ask yourself what feels off, and then move along from there. Even if you don’t want help mentoring or don’t want to talk, totally fine. But I would love to hear from you how it has been working for you. Because I think these little pivotal moments for us start to shape things way down the road that we don’t know that we’re starting to work on, but we can do this work right now. So I appreciate you listening. I appreciate you being here. And I appreciate that you take this stuff and you do some work with it. Again, I’d love to hear how it’s working for you. And if you need some support and need some help. Please reach out. And again, thank you for listening today.

Today my guest is M.R. Madhavan, co-founder and president of PRS Legislative Research. We talked about the role and purpose of the Rajya Sabha, treatment of money bills in a Westminster system, how the anti-defection law and party whips have hollowed out parliamentary function, parliamentary procedure, the role of the governor, and much more. Recorded June 24th, 2026. Read a full transcript enhanced with helpful links. Connect with Ideas of India Follow us on X Follow Shruti on X Click here for the latest Ideas of India episodes sent straight to your inbox. Timestamps (00:00:00) - Intro (00:01:33) - The Role and Purpose of the Rajya Sabha (00:14:46) - Money Bills, No-Confidence Motions, and Design Flaws (00:22:47) - GST and Constitutional Design (00:30:33) - One Country, One Tax System? (00:35:31) - The Problem with Anti-Defection Laws and Whips (00:43:55) - Who Will Bell the Cat? (00:50:53) - Parliamentary Pressures: Constitutional vs. Constituent Expectations (01:02:04) - Challenges Faced by State Legislatures (01:15:37) - Reforming the Office of Governor (01:27:18) - The Role of PRS in Parliamentary Functioning (01:35:13) - Outro

Matt Wynne, co-creator of Cucumber and BDD practitioner, joins Joe for the first time in over a decade to talk about what two years inside a Silicon Valley AI startup taught him about the future of software testing. Matt spent time at Mechanical Orchard working alongside experienced XP practitioners to modernize legacy COBOL mainframes using LLMs, and then spent a week with the team that coined the term "software factory," where the rule was simple: humans never write the code, never read the code. In this episode, Matt breaks down what harness engineering actually means, why shared understanding is still the real bottleneck even in an agentic world, and how testers can use multiple LLMs to review AI-generated pull requests without reading every line. He also gets honest about the grief that comes with realizing you can encode years of hard-won expertise into a Markdown file, and why that does not mean your skills are worthless. If you are working in a brownfield codebase, wondering how to handle the flood of agentic PRs, or trying to figure out where testers fit in a world where agents write the code, this conversation is worth your time. Find Matt at: mattwynne.net leansoftware.ai Also check out his course: Build a Software Factory: Hands-off agentic coding for experienced engineers https://testgld.link/mattcourse

You're putting in the work at the gym, eating what you think is enough, and still not seeing the body you're training for. Sound familiar? In this episode of Mind Pump Show, Sal, Adam, and Justin break down the six most common mistakes women make when they start lifting — pulled straight from over two decades of training real clients, not from theory. These mistakes are still showing up everywhere, and they're the exact reason your strength training isn't delivering the results you were promised. From stacking too much cardio on top of your lifting sessions to underestimating how much weight your lower body can actually handle, the guys walk through every mistake with the kind of blunt, experience-tested clarity you only get from coaches who've seen it all. The biggest surprise? A full 60% of the time when a woman calls in saying she's not seeing results, the fix is simply to eat more. Your body cannot build what you refuse to feed it. They also make the case for ditching the scale entirely as your primary progress metric, and explain why strength, not body composition scans, is the single most reliable indicator that your training is working. If you've been chasing the scale while your PRs sit flat, this episode will completely reframe how you measure success. Plus, Adam shares exactly what happened when he started training Corinne with proper rest periods and a calorie surplus, and the PRs she started hitting speak for themselves. In this episode: • Cardio and strength training compete for the same adaptive resources: doing too much of both simultaneously means you get less of each, and the fix is often as simple as removing the cardio entirely and watching the muscle finally come. • Women chronically underestimate how much they can lift, especially in lower body movements like squats, hip thrusts, and deadlifts, where female clients often match or exceed male clients' numbers once coached to load properly. • Singles, doubles, and triples (1 to 3 rep sets) are not about hypertrophy directly but about recalibrating how much weight a lifter should actually be using for their working sets of 5 reps. • Roughly 60% of the time a female caller asks why she isn't seeing results, the answer is undereating: bumping calories by 600 to 700 per day consistently produces leaner, stronger bodies within 60 to 90 days. • Programming specifics, including exercise selection, order, sets, reps, and how the week and month are structured, can dramatically alter progress, and following a well-designed program from a credible strength background almost always outperforms winging favorite exercises. • Progressive strength gain is the most objective and reliable proxy for muscle growth: adding weight to the bar removes all the noise of lighting, bloat, and daily mirror perception, giving you an undeniable directional signal. • Three to five minute rest periods between heavy compound sets feel like 'not working out' but produce consistent week-over-week strength gains that shorter rest periods simply cannot, because you return to each set fully recovered and able to apply maximum effort. • The scale frequently goes UP in the early stages of correct strength training as muscle is built before fat comes off, making body composition testing a far better metric than body weight, and even then, at least two tests are needed to identify a real trend. Chapters: 0:25 MAPS Upper Lower Intro 0:51 Sponsor: Legion 1:52 Episode Intro: Six Mistakes Overview 5:46 Mistake 1: Too Much Cardio 10:44 Mistake 2: Lifting Too Light 12:35 Using Low-Rep Sets to Recalibrate Weight 14:41 Mistake 3: Not Eating Enough 16:47 Mistake 4: No Structured Program 18:24 Mistake 5: Not Tracking Strength Progress 21:52 The Long Rest Period Challenge 22:33 Mistake 6: Chasing the Scale 24:32 MAPS Upper Lower Outro Plug Products: MAPS Upper Lower — https://mapsupperlower.com (code: launch) Sponsors: Legion (code: MPB2G1) Mentioned: Corinne — Adam shares Corinne's training journey as an example of how proper rest periods and eating in a calorie surplus produced consistent PRs and visible progress.

In this episode, Dr. Erin Ayala sits down with Mireille Siné, MPH — a certified running coach, lupus endurance athlete, and advocate for athletes living with autoimmune and chronic conditions.Mireille has lived with lupus for 13 years and now coaches athletes who are navigating autoimmune disease, chronic illness, flares, fatigue, and identity shifts — while doing endurance sports.Together, Erin and Mireille discuss:Why autoimmune athletes carry a “double load”How training stress can interact with immune dysregulationHow to distinguish overtraining from a possible flareWhy “push through it” can be harmful adviceThe importance of symptom tracking and medical self-advocacyWhat coaches should ask athletes with autoimmune conditionsHow to build flexible training plansWhy performance is not just pace, PRs, and finish linesHow to stop chasing the athlete you used to be and build toward who you can still becomeMireille Siné is a USATF and 80/20 Endurance-certified run coach, 14-time marathoner, and ultramarathoner based in Los Angeles. She is the founder of Coached by Mireille LLC, a virtual coaching practice specializing in runners and endurance athletes managing autoimmune conditions and chronic illness. Mireille coaches with the philosophy "train with compassion" — building training plans that account for the full reality of her athletes' lives, not just their race goals. She has been featured in Runner's World and has spoken at the AIP Summit and Skadi Sports Psychology Athlete Summit. Living with lupus herself, Mireille brings both professional expertise and lived experience to her work, helping athletes redefine what strength and performance can look like with a chronic illness diagnosis.Follow Mireille on InstagramJoin us at Feisty Fest - September 18-20th, 2026: https://feisty.co/events/feisty-fest/Sign up to Receive The Feisty Women's Performance Newsletter:https://feisty.co/newsletters/feisty-womens-performance/Follow us on Instagram:@feisty_womens_performanceVisit the Feisty website at https://feisty.co/ for info on all of our events and podcastsSupport our Partners:Use code PERFORMANCE for 20% off at http://cozyearth.comMomentous: Head to https://www.livemomentous.com/ and use promo code PERFORMANCE for up to 35% off your first orderWahoo: Learn more about Wahoo Fitness Products at: https://wahoofitness.pxf.io/0GAByRTifosi Optics: Use code FEISTY2026 for 20% off at https://tifosioptics.com/

What if your barrel could shed heat faster, hold zero longer, and weigh significantly less — all at once? Avient's Yves Cordeaux joins Ryan Gresham to break down Composite Heat Release technology, the ceramic-injected carbon fiber barrel system that's turning heads in PRS, NRL, and hunting circles. This isn't your standard carbon wrap — it's a materials science breakthrough hiding inside your next rifle.This Gun Talk Nation is brought to you by Silent Steel USA, Silencer Central, Archon Firearms, Range Ready Studios, and Ruger.About Gun Talk NationGun Talk Media's Gun Talk Nation with Ryan Gresham is a weekly multi-platform podcast that offers a fresh look at all things firearms-related. Featuring notable guests and a lot of laughs. Gun Talk Nation is available as an audio podcast or in video format.For more content from Gun Talk Media, visit guntalk.com or subscribe on YouTube, Rumble, Facebook, Instagram, and X. Catch First Person Defender on the new Official FPD YouTube channel. Watch Gun Talk Nation on its new YouTube channel. Catch Gun Talk Hunt on the new dedicated YouTube Channel. Listen to all Gun Talk Podcasts with Spreaker, iHeart, Apple Podcasts, Spotify or wherever you find podcasts.Copyright ©2026 Freefire Media, LLCGun Talk Nation 07.08.26Become a supporter of this podcast: https://www.spreaker.com/podcast/gun-talk--6185159/support.

This episode tackles the growing pains of AI-assisted development, from the struggle of reviewing thousands of lines of agent-generated code to the mounting technical debt when teams merge PRs without meaningful human review. Scott and Wes also dig into local models, whether jujutsu really beats git, how freelancers should price work in the AI era, and getting your team on board with external libraries. Show Notes 00:00 Welcome to Syntax! 00:45 Understanding AI-Generated Code 06:24 The Challenges of Code Review in AI Development 11:21 What the heck are local models? CJ's Guide to Local AI 16:09 Exploring New Tools: Jujutsu and Beyond 20:35 Exploring Version Control Innovations 22:18 Pricing Strategies in the Age of AI 24:52 webkit-box-reflect not in the browsers. 27:44 The Angular vs. React Debate 31:46 Sick Picks & Shameless Plugs. Sick Picks Scott: Huggingface Reachy Mini Robot Wes: Bose QC35 Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott: X Instagram Tiktok LinkedIn Threads Randy: X Instagram YouTube Threads

Eric Dahl joins Niki Sims and Andrew Jackson on Beast Over Burden to share how he continues getting stronger with age, setting major PRs in his mid-40s while balancing work, family, coaching, and recovery. Eric has been part of the Barbell Logic family since 2017 and has built an impressive strength resume, including a 507-pound bench press and a 628-pound deadlift at 46 years old. But this conversation is about more than big lifts. Eric shares how strength training became his version of a midlife crisis, why hard training provides purpose, and how he has learned to adjust recovery, competition, and programming as life has changed. He also discusses his long-term coaching relationship with Caleb, his experience becoming a coach himself, and the powerful story of helping his mother-in-law begin strength training after an osteoporosis diagnosis. This episode is a reminder that strength is for everyone. Whether you are chasing PRs, training for independence, or simply looking for a meaningful outlet for hard work, getting stronger with age is possible. PS - IF YOU'RE INTERESTED IN TAKING ONLINE COACHING FOR A TEST RUN, CHECK IT OUT HERE.    Connect with the hosts Niki on Instagram Andrew on Instagram Connect with the show Barbell Logic on Instagram Podcast Webpage Barbell Logic on Facebook Or email podcast@barbell-logic.com