Podcasts about Zod

“He's at the height of his Lost powers here” - Ben on J.J. Abrams On this week's episode, we welcome Ben Worcester onto the Summer Blockbuster Extravaganza to chat about the super-fun action sequel, Mission: Impossible III! How great is this engagement party scene with Ethan working the room? Has there been a better M:I villain than the late, great Philip Seymour Hoffman's portrayal of Owen Davian? Is this the M:I flick with the most Ving? And how lucky is Ethan to have Aaron Paul for a brother-in-law? PLUS: Does Ethan Hunt have the same bartending skills as Brian Flanagan? Mission: Impossible III stars Tom Cruise, Ving Rhames, Billy Crudup, Michelle Monaghan, Jonathan Rhys Meyers, Keri Russell, Maggie Q, Simon Pegg, Eddie Marsan, Laurence Fishburne, and Philip Seymour Hoffman as Owen Davian; directed by J.J. Abrams. This episode is brought to you in part by Rocket Money! Cancel your unwanted subscriptions and reach your financial goals faster with Rocket Money. Download the Rocket Money app and enter our show name—We Hate Movies—in the survey so they know we sent you! Don't wait! Download the Rocket Money app today and tell them you heard about them from our show! Don't miss our next Worldwide Digital Event, happening Friday, June 20th at 9pm/eastern where we'll be LIVE talking about a total superhero all-timer, Superman II! Join us that night to revel in all the fun with Zod & Friends, everyone at the Daily Planet, and the two legendary performances from Christopher Reeve and Gene Hackman! Replay available for 14 days after broadcast!  Tickets are going fast for our three-night residency during the Oxford Comedy Festival! We'll be doing six shows over three nights from July 18 through 20. Tickets are going fast—our shows on Quantum of Solace and Hellraiser are already SOLD OUT—so don't wait, snag your tix today!  Throughout 2025, we'll be donating 100% of our earnings from our merch shop to the Center for Reproductive Rights. So head over and check out all these masterful designs and see what tickles your fancy! Shirts? Phone cases? Canvas prints? We got all that and more! Check it out and kick in for a good cause! Original cover art by Felipe Sobreiro.

“Hold on to your hats, folks, Chris Cabin likes this movie!” - Eric On this week's episode, we're going back to The Prequels on the Summer Blockbuster Extravaganza to do a proper episode on Star Wars: Episode III - Revenge of the Sith! How great is that Count Dooku exit at the beginning? How catty are all the sarcastic Battle Droids? Does this movie have the best-looking space battles in all the prequels? How funny is R2 lighting those guys on fire after whizzing oil all over them? And, yeah, that Vader shout at the end of the movie is still one of the most unintentionally hilarious moments in all of Star Wars! PLUS: Palpatine blurs out his Zoom background when making secret calls from the toilet! Star Wars: Episode III - Revenge of the Sith stars Ewan McGregor, Hayden Christian, Natalie Portman, Ian McDiarmid, Jimmy Smits, Samuel L. Jackson, Anthony Daniels, Christopher Lee, Bruce Spence, Silas Carson, Temuera Morrison, Kenny Baker, and Frank Oz as the voice of Yoda; directed by George Lucas. Don't miss our next Worldwide Digital Event, happening Friday, June 20th at 9pm/eastern where we'll be LIVE talking about a total superhero all-timer, Superman II! Join us that night to revel in all the fun with Zod & Friends, everyone at the Daily Planet, and the two legendary performances from Christopher Reeve and Gene Hackman! Replay available for 14 days after broadcast!  Tickets are going fast for our three-night residency during the Oxford Comedy Festival! We'll be doing six shows over three nights from July 18 through 20. Tickets are going fast—our shows on Quantum of Solace and Hellraiser are already SOLD OUT—so don't wait, snag your tix today!  Throughout 2025, we'll be donating 100% of our earnings from our merch shop to the Center for Reproductive Rights. So head over and check out all these masterful designs and see what tickles your fancy! Shirts? Phone cases? Canvas prints? We got all that and more! Check it out and kick in for a good cause! Original cover art by Felipe Sobreiro.

In this discussion of Berserk Volume 17, the participants explore various themes including Guts' imprisonment and escape, the character development of Farnese, the complexities of religious themes, Guts' trauma and flashbacks, military leadership dynamics, and the implications of prophecies within the narrative. The conversation delves into the psychological aspects of the characters, particularly Farnese's struggles with her beliefs and Guts' coping mechanisms, while also examining the overarching power dynamics between characters like Griffith and Zod. In this conversation, the speakers delve into the themes of prophecies, the nature of evil, and the complexity of human nature as depicted in the series 'Berserk'. They explore Guts' journey of personal growth, the impact of choices and consequences, and the moral implications of violence and torture. The discussion also touches on the dark humor present in the narrative and sets the stage for future conflicts within the story.takeawaysSend us a messageSupport the showFilm Chewing Podcast: https://www.buzzsprout.com/2235582/followLens Chewing on YouTube: https://www.youtube.com/@lenschewingSpeculative Speculations: https://creators.spotify.com/pod/show/speculative-speculationsSupport the podcast: https://www.paypal.com/ncp/payment/7EQ7XWFUP6K9EJoin Riverside.fm: https://riverside.fm/?via=steve-l

This week Zach is joined by Lance Laster from Always Hold On To Arrow to discuss the two hundred fifteenth episode of Smallville, “Dominion." They talk the return of Callum Blue as Zod, the episode's odd structure and pacing, its 300 influences, and the curious lack of any White Snake music. Always Hold On To Smallville is my world!Check out Lance on Always Hold On To Arrow.EPISODE ROUNDUPZach's Grade: C-Lance's Grade: C+IMDB Grade: 8.1Superman Homepage Grade: 5/5 Bechdel Test: PASSSERIES TALLY BOARD...From Metropolis: 17Amazing Technicolor Kryptonite: 22Amnesia Count: 82Blue Shirt/Red Jacket: 89Chloe's Unseen Connections: 29Clark Loses His Powers: 18Episode Title Said In Episode: 93Hospital Visits: 153In Media Res: 8Injection Count: 57Kent Truck Accidents: 10KOs to Keep Clark's Secret: 61KOs to Keep Oliver's Secret: 4Lana Kills: 7Let's Do The Time Warp Again: 12Lois Arm Punches: 10Lois' Costume Closet: 24Main Character Deaths: 26Mind Control Count: 26Monogram Jacket: 9Movie Plot As An Episode: 26Not The Last Son Of Krypton: 12*Possession Count: 32Product Placement Pete: 36Queen Airways: 9Shirtless Oliver: 18Shower Count: 25Shut It Down: 11Shut That Laptop: 35Smallville High School Faculty Deaths: 5Smallville High School Student Deaths: 17Under The Influence: 52Wakes Up Tied Up: 11Weddings: 6"You Weren't Yourself": 38Always Hold On To Smallville is brought you to by listeners like you. Special thanks to these Meteor Freaks on Patreon who's generous contributions help produce the podcast!Chris Fuchs / @crfuchs7Kevonte Chilous / @chill_usDJ Doena / @DjDoenaJoey Dienberg / @JoeyD94_13Isaiah GoodridgeCory MooreNathan RothacherAtif SheikhThomas NavenJohn CurcioMarc-ids FoppenPatricia Carrillo / @MsCarrillo92Michael HartfordJim CrawfordKasey Vach / @ThePandaSupremeMegan RichRouie HumphreyAlex Hamilton  / @Quiet_Storm_23Matt DouglasDaniel CurielMeryl Smith / @MelXtreme84Trevis HullRyan LoveAmy J.Mike FranzNathan MacKenzie / @maccamackenzieSteve Rogers / @SteveJRogersJrMollie FicarellaJames Lee / @Jae_El_52Jo Michael / @jweissbrod86Jason Davis / @superjay_92Patrick BravoJacob StevenartTae Tae / @doomsday994.Rob O'Connor / @TheGothamiteTina BDaryn Kirscht / @darynkirscht16Dylan DiAntonioNick Ryan Magdoza / @nickryanEddie Bissell / @Kal_Ed11Clunk Kant / @ClunkKantNicholas FanslerJohn LongRuth Anne Crews Travis Kill / @tjkill81Mike ThomasNeena J / @Sofiamom1Nicholas CosoJarrett GibbsAnthony Anderson / @NigandNogJasmine Magele / @Jas mindaMT_NZKeith FaulsJames Hart / @jaohartsAnthony Desiato /@DesiWestsideCrystal CrossJake C.John SweitzerKirin KumarLorenzo Valdes / @ClarksCreekKarenPATREON: patreon.com/alwaysmallvilleTWITTER: twitter.com/alwaysmallvilleFACEBOOK: facebook.com/alwaysmallvilleEMAIL: alwaysmallville@gmail.com

Em um podcast repleto de fofocas do mundo dos animes, mangás, e jogos, discutimos sobre a experiência de assistir animes como Dragon Ball Z e Cavaleiros do Zodíaco nos dias de hoje, a Gamescom Latam, o preço do Nintendo Switch no Brasil, e sobre a publicação não oficial de Urusei Yatsura no Brasil.⁠Siga-nos nas nossas redes sociais para nunca perder um novo episódio⁠⁠⁠⁠!

Sejam uma vez mais benvindos ao espaço AS ABOVE SO BELOW.Hoje é tempo de falar sobre as previsões de Maio, um mês que nos pedirá maturidade, consistência e claridade nos procedimentos. Plutão ficará retrógrado até Outubro; uma altura que nos pedirá mudanças internas. Estas serão apoiadas pela seriedade de Mercúrio em Touro, pelo ingresso de Saturno em Carneiro (pela primeira vez em 28 anos) e pela potente Lua Cheia em Escorpião. Remover o peso desnecessário para avançar com ideias novas que serão promovidas pelos insights, fruto dos cazimis da época de Gémeos.Eis os tempos a saber:Introdução: 00:00:00PREVISÕES: 00:04:384 MAIO- PLUTÃO RETRÓGRADO EM AQUÁRIO10 MAIO- MERCÚRIO TOURO12 MAIO- LUA CHEIA EM ESCORPIÃO20 MAIO- SOL EM GÉMEOS24 MAIO- SATURNO EM CARNEIRO25 MAIO- MERCÚRIO EM GÉMEOS27 MAIO- LUA NOVA EM GÉMEOSImpacto nos 12 signos do Zodíaco: 00:21:00CARNEIRO: 00:23:00TOURO: 00:26:09GÉMEOS: 00:29:46CARANGUEJO: 00:34:48LEÃO: 00:41:39VIRGEM: 00:46:33BALANÇA: 00:52:20ESCORPIÃO:00:57:29SAGITÁRIO:01:03:33CAPRICÓRNIO: 01:08:40AQUÁRIO: 01:11:11PEIXES: 01:13:40FIM E ATÉ BREVE :)

As armaduras de ouro do universo de Cavaleiros do Zodíaco são o máximo de força alcançada na obra, e como cada uma delas representa um signo, pensamos em que personagens de anime serviriam para cada uma, levando em conta apenas as descrições que cada signo tem, junto a personalidade dos mesmos. Com Markus Anisio Trolleis, Rodrigo Cardozo e Alex Guerra.

Chris started watching Smallville for the first time. We talk the ninth season! From the new iteration of Zod, to the big Absolute Justice two parter and more!WE HAVE A DISCORD! Join it here: https://discord.com/invite/QfDYKZSUKGFollow the Show:Linktr.ee/SupesandSabersSocials: @SupesandSabers 

Cavaleiros do Zodíaco aka Saint Seiya 聖闘士星矢セイントセイヤ

Qué Temas Quieres Escuchar Toca y Hablemos. TE LEO.Contar una historia no siempre es solo parte del trabajo. A veces, la noticia también te atraviesa. ¿Cómo se enfrenta un periodista a eventos que remueven su propia vida? ¿Cómo narrar una tragedia cuando tu propia voz tiembla? Lourdes Stephen, una de las periodistas más reconocidas de habla hispana, nos acompaña en este episodio para hablar sobre el lado humano del periodismo: las emociones, el impacto psicológico, y la manera en que cada historia deja huella.En este episodio de Cómo Curar, Lourdes comparte momentos clave de su carrera: desde su inicio en República Dominicana hasta su llegada a Univisión; desde entrevistas con asesinos hasta coberturas devastadoras como el terremoto en Haití o el 11 de septiembre. También nos revela cómo ha logrado mantenerse fiel a su vocación, enfrentando el dolor, abrazando su fe y transformando cada experiencia en una herramienta de vida.Lourdes inspira a mujeres de todo el mundo a perseguir sus sueños con valentía y determinación. ¿Quieres descubrir cuáles son las herramientas que pueden ayudarte a lograr tus propios sueños?Temas clave en este episodio:• Cómo el periodismo impacta emocionalmente a quienes lo ejercen.• Qué ocurre cuando la noticia toca heridas personales.• La importancia de la Fe para sostenerse frente al dolor.• El valor de la honestidad, la empatía y el humor en la narración de historias.• Qué hay detrás de la entrevista con el asesino del Zodíaco.Este episodio no es para personas que comparten la misma profesión. Es para todos los que han vivido algo que los ha marcado y buscan una forma de seguir adelante. Escucha esta conversación poderosa y transformadora.Suscríbete al canal de YouTube Cocó March N.M.D., activa la campanita, y accede a más episodios en ComoCurar.com o en tu plataforma de podcast favorita.#CocoMarch #DoctoraCocoMarch #TipsCocoMarch #ComoCurar #LourdesStephen #PodcastEnEspanol #PodcastLatino #PeriodismoHumano #HistoriasQueMarcan #ConversacionesQueInspiran #NarrarParaSanar #VocesDelPeriodismo #VocesQueTransforman #NoticiasQueDuelen #TestigoDeLaHistoria #Temporada3 #Episodio103 Adquiere el RenovaDetox:https://store.dracocomConsigue mis fórmulas en USA y México: https://store.dracocomarch.com/es/Consigue mis fórmulas en Europa:https://vitatiendaeuropa.com/es/Visita mi Podcast:https://comocurar.com/Sígueme en redes:https://www.facebook.com/CocoMarchNMDhttps://www.instagram.com/cocomarch.nmd/https://www.youtube.com/@CocoMarchNMDhttps://www.tiktok.com/@coco.march.nmd Aprende de mi blog:https://blog.dracocomarch.com

Judeu Ateu, Estranho, Luki e Izzo (Dentro da Chaminé) seguem no quadro “… dos Mangás“, no qual escolhem personagens da ficção dos mangás que se encaixariam em uma determinada categoria.Desta fez, cansados verem grupos de personagens tematizados como os Sete Pecados Capitais ou o Zodíaco Chinês, desta vez escolhem quais personagens fariam parte de um fictício grupo tematizado de Zodíaco Cigado (perdão, povo Romani). Acompanhem enquanto são escolhidos personagens para serem a Capela, a Estrela, a Roda e muito mais!Apoie o AoQuadrado² no APOIA.seCronologia do episódio(00:00:00) Zodíaco Cigano dos Mangás(01:04:30) Recomendação da Semana – Burn The House Down

Prepare seu navio pirata ou sua nuvem voadora, pois desta vez no ⁠⁠⁠⁠Mundo dos Animes⁠⁠⁠⁠, ⁠⁠⁠⁠Raul⁠⁠⁠⁠, ⁠⁠⁠⁠Vulpixs⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ e ⁠Pedro Lobato⁠⁠⁠⁠ (⁠Animes Overdrive⁠⁠⁠⁠) falam sobre mais 2 filmes de Os Cavaleiros do Zodíaco: Os Guerreiros do Armagedon (1989) e Prólogo do Céu (2014).SEJA NOSSO APOIADOR E AJUDE O PODCAST A CONTINUAR EXISTINDO: ⁠⁠⁠⁠Catarse⁠⁠⁠⁠Tempo de duração: 79 minutosPauta: Raul LimaArte da Vitrine: Lucas MáximoPauta: Raul LimaEdição: Raul Lima / Lucas Máximo⁠⁠⁠⁠VISITE O NOVO SITE DO MUNDO DOS ANIMES⁠⁠⁠⁠Mande um e-mail para nossa Caixa Postal comentando sobre o episódio: podcast@mundodosanimes.comRedes Sociais:⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠Discord⁠⁠

"Come to me, son of Jor-El! Kneel before Zod!" - General Zod (Superman II)Chris and Erik are joined once again by Justin Ache to talk some DC movies - this time we're delving into the long history of not-so-great Superman films, before James Gunn's long-awaited reboot... Superman Movies Discussed: Superman: The Movie (1978)Superman II (1981)Superman II: The Donner Cut (2006)Superman III (1983)Superman IV: The Quest for Peace (1987)Supergirl (1984)Steel (1997)Superman Returns (2006)Man of Steel (2013)Honorable Mention: "Superman and the Mole Men"?! (1951)(Episode edited by Erik Slader)Check out our blog at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ComicZombie.net⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for more! Follow us on Social Media:Instagram: @ComicZombiePodcastBlueSky: @ComicZombieNetwork InfoThis podcast is a production of the We Can Make This Work (Probably) Network. Follow us below to keep up with this show and discover our many other podcasts – including: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Epik Fails of History⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠2 Young 4 This Trek⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Podcasters Assemble⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠| ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠| ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: @probablywork⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.probablywork.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Email: ProbablyWorkPod@gmail.com

Sextou, bebê!

In this conversation, the panel discusses the intricacies of Berserk Volume 8, focusing on character motivations, themes of friendship and ownership, and the literary depth of the narrative. The group reflects on Griffith's strategic mind, Guts' journey, and the implications of their relationship, while also analyzing the foreshadowing and character development throughout the volume. In this conversation, the participants delve into the intricate themes of the manga 'Berserk', focusing on character motivations, the duality of ambition and friendship, and the representation of characters. They explore Guts' journey towards independence, Griffith's complex nature, and the significance of celebration amidst turmoil. The discussion also touches on character ages, growth, and the juxtaposition of nobility and misfits, leading to reflections on dreams and aspirations.Send us a messageSupport the showFilm Chewing Podcast: https://www.buzzsprout.com/2235582/followLens Chewing on YouTube: https://www.youtube.com/@lenschewingSpeculative Speculations: https://creators.spotify.com/pod/show/speculative-speculationsSupport the podcast: https://www.paypal.com/ncp/payment/7EQ7XWFUP6K9EJoin Riverside.fm: https://riverside.fm/?via=steve-l

Fala otakeiros e otakeiras, sejam bem-vindos a mais um Otakeiracast, seu podcast com 250 episódios falando sobre animes, filmes e tudo mais que for oriental, e às vezes, nem tão orientais assim. E no episódio de hoje, os guerreiros do OtakeiraCast JF, Gabriel e Milo irão se reunir nesse episódio para salvarem a deusa dessa podcast, Jhana Monteiro, enquanto falam de Cavaleiros do Zodíaco.#otakeiracast #podcast #podcastcollective #anime #animes #animebrasil #animelove #animelover #otaku #otakubr #otakubrasil #otakubrasileiro

O que assistimos nos anos 90 ou 2000 era entretenimento ou uma aula de sociologia?Exploramos o capitalismo selvagem em Bob Esponja, o nascimento do movimento queer em Cavaleiros do Zodíaco e a meritocracia por trás das animações da tv a cabo!!Apoie este podcast NA ORELO!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://orelo.cc/jogueinogrupo⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Ou no APOIA-SE:⁠⁠⁠⁠⁠⁠⁠⁠https://apoia.se/jogueinogrupopodcast⁠⁠⁠ ⁠⁠⁠⁠⁠Envie seu e-mail para:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠jogueinogrupo@gmail.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Assista o episódio em vídeo no youtube:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.youtube.com/@PodcastJogueiNoGrupo⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Siga o Joguei no Grupo: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.instagram.com/jogueinogrupo⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Siga a Dacota Monteiro: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.instagram.com/dacotamonteiroSiga a Jenny Prioli: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.instagram.com/jennyprioli⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Siga o Controle Y: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠w⁠ww.instagram.com/controle_y⁠

Today's episode is with Paul Klein, founder of Browserbase. We talked about building browser infrastructure for AI agents, the future of agent authentication, and their open source framework Stagehand.* [00:00:00] Introductions* [00:04:46] AI-specific challenges in browser infrastructure* [00:07:05] Multimodality in AI-Powered Browsing* [00:12:26] Running headless browsers at scale* [00:18:46] Geolocation when proxying* [00:21:25] CAPTCHAs and Agent Auth* [00:28:21] Building “User take over” functionality* [00:33:43] Stagehand: AI web browsing framework* [00:38:58] OpenAI's Operator and computer use agents* [00:44:44] Surprising use cases of Browserbase* [00:47:18] Future of browser automation and market competition* [00:53:11] Being a solo founderTranscriptAlessio [00:00:04]: Hey everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol.ai.swyx [00:00:12]: Hey, and today we are very blessed to have our friends, Paul Klein, for the fourth, the fourth, CEO of Browserbase. Welcome.Paul [00:00:21]: Thanks guys. Yeah, I'm happy to be here. I've been lucky to know both of you for like a couple of years now, I think. So it's just like we're hanging out, you know, with three ginormous microphones in front of our face. It's totally normal hangout.swyx [00:00:34]: Yeah. We've actually mentioned you on the podcast, I think, more often than any other Solaris tenant. Just because like you're one of the, you know, best performing, I think, LLM tool companies that have started up in the last couple of years.Paul [00:00:50]: Yeah, I mean, it's been a whirlwind of a year, like Browserbase is actually pretty close to our first birthday. So we are one years old. And going from, you know, starting a company as a solo founder to... To, you know, having a team of 20 people, you know, a series A, but also being able to support hundreds of AI companies that are building AI applications that go out and automate the web. It's just been like, really cool. It's been happening a little too fast. I think like collectively as an AI industry, let's just take a week off together. I took my first vacation actually two weeks ago, and Operator came out on the first day, and then a week later, DeepSeat came out. And I'm like on vacation trying to chill. I'm like, we got to build with this stuff, right? So it's been a breakneck year. But I'm super happy to be here and like talk more about all the stuff we're seeing. And I'd love to hear kind of what you guys are excited about too, and share with it, you know?swyx [00:01:39]: Where to start? So people, you've done a bunch of podcasts. I think I strongly recommend Jack Bridger's Scaling DevTools, as well as Turner Novak's The Peel. And, you know, I'm sure there's others. So you covered your Twilio story in the past, talked about StreamClub, you got acquired to Mux, and then you left to start Browserbase. So maybe we just start with what is Browserbase? Yeah.Paul [00:02:02]: Browserbase is the web browser for your AI. We're building headless browser infrastructure, which are browsers that run in a server environment that's accessible to developers via APIs and SDKs. It's really hard to run a web browser in the cloud. You guys are probably running Chrome on your computers, and that's using a lot of resources, right? So if you want to run a web browser or thousands of web browsers, you can't just spin up a bunch of lambdas. You actually need to use a secure containerized environment. You have to scale it up and down. It's a stateful system. And that infrastructure is, like, super painful. And I know that firsthand, because at my last company, StreamClub, I was CTO, and I was building our own internal headless browser infrastructure. That's actually why we sold the company, is because Mux really wanted to buy our headless browser infrastructure that we'd built. And it's just a super hard problem. And I actually told my co-founders, I would never start another company unless it was a browser infrastructure company. And it turns out that's really necessary in the age of AI, when AI can actually go out and interact with websites, click on buttons, fill in forms. You need AI to do all of that work in an actual browser running somewhere on a server. And BrowserBase powers that.swyx [00:03:08]: While you're talking about it, it occurred to me, not that you're going to be acquired or anything, but it occurred to me that it would be really funny if you became the Nikita Beer of headless browser companies. You just have one trick, and you make browser companies that get acquired.Paul [00:03:23]: I truly do only have one trick. I'm screwed if it's not for headless browsers. I'm not a Go programmer. You know, I'm in AI grant. You know, browsers is an AI grant. But we were the only company in that AI grant batch that used zero dollars on AI spend. You know, we're purely an infrastructure company. So as much as people want to ask me about reinforcement learning, I might not be the best guy to talk about that. But if you want to ask about headless browser infrastructure at scale, I can talk your ear off. So that's really my area of expertise. And it's a pretty niche thing. Like, nobody has done what we're doing at scale before. So we're happy to be the experts.swyx [00:03:59]: You do have an AI thing, stagehand. We can talk about the sort of core of browser-based first, and then maybe stagehand. Yeah, stagehand is kind of the web browsing framework. Yeah.What is Browserbase? Headless Browser Infrastructure ExplainedAlessio [00:04:10]: Yeah. Yeah. And maybe how you got to browser-based and what problems you saw. So one of the first things I worked on as a software engineer was integration testing. Sauce Labs was kind of like the main thing at the time. And then we had Selenium, we had Playbrite, we had all these different browser things. But it's always been super hard to do. So obviously you've worked on this before. When you started browser-based, what were the challenges? What were the AI-specific challenges that you saw versus, there's kind of like all the usual running browser at scale in the cloud, which has been a problem for years. What are like the AI unique things that you saw that like traditional purchase just didn't cover? Yeah.AI-specific challenges in browser infrastructurePaul [00:04:46]: First and foremost, I think back to like the first thing I did as a developer, like as a kid when I was writing code, I wanted to write code that did stuff for me. You know, I wanted to write code to automate my life. And I do that probably by using curl or beautiful soup to fetch data from a web browser. And I think I still do that now that I'm in the cloud. And the other thing that I think is a huge challenge for me is that you can't just create a web site and parse that data. And we all know that now like, you know, taking HTML and plugging that into an LLM, you can extract insights, you can summarize. So it was very clear that now like dynamic web scraping became very possible with the rise of large language models or a lot easier. And that was like a clear reason why there's been more usage of headless browsers, which are necessary because a lot of modern websites don't expose all of their page content via a simple HTTP request. You know, they actually do require you to run this type of code for a specific time. JavaScript on the page to hydrate this. Airbnb is a great example. You go to airbnb.com. A lot of that content on the page isn't there until after they run the initial hydration. So you can't just scrape it with a curl. You need to have some JavaScript run. And a browser is that JavaScript engine that's going to actually run all those requests on the page. So web data retrieval was definitely one driver of starting BrowserBase and the rise of being able to summarize that within LLM. Also, I was familiar with if I wanted to automate a website, I could write one script and that would work for one website. It was very static and deterministic. But the web is non-deterministic. The web is always changing. And until we had LLMs, there was no way to write scripts that you could write once that would run on any website. That would change with the structure of the website. Click the login button. It could mean something different on many different websites. And LLMs allow us to generate code on the fly to actually control that. So I think that rise of writing the generic automation scripts that can work on many different websites, to me, made it clear that browsers are going to be a lot more useful because now you can automate a lot more things without writing. If you wanted to write a script to book a demo call on 100 websites, previously, you had to write 100 scripts. Now you write one script that uses LLMs to generate that script. That's why we built our web browsing framework, StageHand, which does a lot of that work for you. But those two things, web data collection and then enhanced automation of many different websites, it just felt like big drivers for more browser infrastructure that would be required to power these kinds of features.Alessio [00:07:05]: And was multimodality also a big thing?Paul [00:07:08]: Now you can use the LLMs to look, even though the text in the dome might not be as friendly. Maybe my hot take is I was always kind of like, I didn't think vision would be as big of a driver. For UI automation, I felt like, you know, HTML is structured text and large language models are good with structured text. But it's clear that these computer use models are often vision driven, and they've been really pushing things forward. So definitely being multimodal, like rendering the page is required to take a screenshot to give that to a computer use model to take actions on a website. And it's just another win for browser. But I'll be honest, that wasn't what I was thinking early on. I didn't even think that we'd get here so fast with multimodality. I think we're going to have to get back to multimodal and vision models.swyx [00:07:50]: This is one of those things where I forgot to mention in my intro that I'm an investor in Browserbase. And I remember that when you pitched to me, like a lot of the stuff that we have today, we like wasn't on the original conversation. But I did have my original thesis was something that we've talked about on the podcast before, which is take the GPT store, the custom GPT store, all the every single checkbox and plugin is effectively a startup. And this was the browser one. I think the main hesitation, I think I actually took a while to get back to you. The main hesitation was that there were others. Like you're not the first hit list browser startup. It's not even your first hit list browser startup. There's always a question of like, will you be the category winner in a place where there's a bunch of incumbents, to be honest, that are bigger than you? They're just not targeted at the AI space. They don't have the backing of Nat Friedman. And there's a bunch of like, you're here in Silicon Valley. They're not. I don't know.Paul [00:08:47]: I don't know if that's, that was it, but like, there was a, yeah, I mean, like, I think I tried all the other ones and I was like, really disappointed. Like my background is from working at great developer tools, companies, and nothing had like the Vercel like experience. Um, like our biggest competitor actually is partly owned by private equity and they just jacked up their prices quite a bit. And the dashboard hasn't changed in five years. And I actually used them at my last company and tried them and I was like, oh man, like there really just needs to be something that's like the experience of these great infrastructure companies, like Stripe, like clerk, like Vercel that I use in love, but oriented towards this kind of like more specific category, which is browser infrastructure, which is really technically complex. Like a lot of stuff can go wrong on the internet when you're running a browser. The internet is very vast. There's a lot of different configurations. Like there's still websites that only work with internet explorer out there. How do you handle that when you're running your own browser infrastructure? These are the problems that we have to think about and solve at BrowserBase. And it's, it's certainly a labor of love, but I built this for me, first and foremost, I know it's super cheesy and everyone says that for like their startups, but it really, truly was for me. If you look at like the talks I've done even before BrowserBase, and I'm just like really excited to try and build a category defining infrastructure company. And it's, it's rare to have a new category of infrastructure exists. We're here in the Chroma offices and like, you know, vector databases is a new category of infrastructure. Is it, is it, I mean, we can, we're in their office, so, you know, we can, we can debate that one later. That is one.Multimodality in AI-Powered Browsingswyx [00:10:16]: That's one of the industry debates.Paul [00:10:17]: I guess we go back to the LLMOS talk that Karpathy gave way long ago. And like the browser box was very clearly there and it seemed like the people who were building in this space also agreed that browsers are a core primitive of infrastructure for the LLMOS that's going to exist in the future. And nobody was building something there that I wanted to use. So I had to go build it myself.swyx [00:10:38]: Yeah. I mean, exactly that talk that, that honestly, that diagram, every box is a startup and there's the code box and then there's the. The browser box. I think at some point they will start clashing there. There's always the question of the, are you a point solution or are you the sort of all in one? And I think the point solutions tend to win quickly, but then the only ones have a very tight cohesive experience. Yeah. Let's talk about just the hard problems of browser base you have on your website, which is beautiful. Thank you. Was there an agency that you used for that? Yeah. Herb.paris.Paul [00:11:11]: They're amazing. Herb.paris. Yeah. It's H-E-R-V-E. I highly recommend for developers. Developer tools, founders to work with consumer agencies because they end up building beautiful things and the Parisians know how to build beautiful interfaces. So I got to give prep.swyx [00:11:24]: And chat apps, apparently are, they are very fast. Oh yeah. The Mistral chat. Yeah. Mistral. Yeah.Paul [00:11:31]: Late chat.swyx [00:11:31]: Late chat. And then your videos as well, it was professionally shot, right? The series A video. Yeah.Alessio [00:11:36]: Nico did the videos. He's amazing. Not the initial video that you shot at the new one. First one was Austin.Paul [00:11:41]: Another, another video pretty surprised. But yeah, I mean, like, I think when you think about how you talk about your company. You have to think about the way you present yourself. It's, you know, as a developer, you think you evaluate a company based on like the API reliability and the P 95, but a lot of developers say, is the website good? Is the message clear? Do I like trust this founder? I'm building my whole feature on. So I've tried to nail that as well as like the reliability of the infrastructure. You're right. It's very hard. And there's a lot of kind of foot guns that you run into when running headless browsers at scale. Right.Competing with Existing Headless Browser Solutionsswyx [00:12:10]: So let's pick one. You have eight features here. Seamless integration. Scalability. Fast or speed. Secure. Observable. Stealth. That's interesting. Extensible and developer first. What comes to your mind as like the top two, three hardest ones? Yeah.Running headless browsers at scalePaul [00:12:26]: I think just running headless browsers at scale is like the hardest one. And maybe can I nerd out for a second? Is that okay? I heard this is a technical audience, so I'll talk to the other nerds. Whoa. They were listening. Yeah. They're upset. They're ready. The AGI is angry. Okay. So. So how do you run a browser in the cloud? Let's start with that, right? So let's say you're using a popular browser automation framework like Puppeteer, Playwright, and Selenium. Maybe you've written a code, some code locally on your computer that opens up Google. It finds the search bar and then types in, you know, search for Latent Space and hits the search button. That script works great locally. You can see the little browser open up. You want to take that to production. You want to run the script in a cloud environment. So when your laptop is closed, your browser is doing something. The browser is doing something. Well, I, we use Amazon. You can see the little browser open up. You know, the first thing I'd reach for is probably like some sort of serverless infrastructure. I would probably try and deploy on a Lambda. But Chrome itself is too big to run on a Lambda. It's over 250 megabytes. So you can't easily start it on a Lambda. So you maybe have to use something like Lambda layers to squeeze it in there. Maybe use a different Chromium build that's lighter. And you get it on the Lambda. Great. It works. But it runs super slowly. It's because Lambdas are very like resource limited. They only run like with one vCPU. You can run one process at a time. Remember, Chromium is super beefy. It's barely running on my MacBook Air. I'm still downloading it from a pre-run. Yeah, from the test earlier, right? I'm joking. But it's big, you know? So like Lambda, it just won't work really well. Maybe it'll work, but you need something faster. Your users want something faster. Okay. Well, let's put it on a beefier instance. Let's get an EC2 server running. Let's throw Chromium on there. Great. Okay. I can, that works well with one user. But what if I want to run like 10 Chromium instances, one for each of my users? Okay. Well, I might need two EC2 instances. Maybe 10. All of a sudden, you have multiple EC2 instances. This sounds like a problem for Kubernetes and Docker, right? Now, all of a sudden, you're using ECS or EKS, the Kubernetes or container solutions by Amazon. You're spending up and down containers, and you're spending a whole engineer's time on kind of maintaining this stateful distributed system. Those are some of the worst systems to run because when it's a stateful distributed system, it means that you are bound by the connections to that thing. You have to keep the browser open while someone is working with it, right? That's just a painful architecture to run. And there's all this other little gotchas with Chromium, like Chromium, which is the open source version of Chrome, by the way. You have to install all these fonts. You want emojis working in your browsers because your vision model is looking for the emoji. You need to make sure you have the emoji fonts. You need to make sure you have all the right extensions configured, like, oh, do you want ad blocking? How do you configure that? How do you actually record all these browser sessions? Like it's a headless browser. You can't look at it. So you need to have some sort of observability. Maybe you're recording videos and storing those somewhere. It all kind of adds up to be this just giant monster piece of your project when all you wanted to do was run a lot of browsers in production for this little script to go to google.com and search. And when I see a complex distributed system, I see an opportunity to build a great infrastructure company. And we really abstract that away with Browserbase where our customers can use these existing frameworks, Playwright, Publisher, Selenium, or our own stagehand and connect to our browsers in a serverless-like way. And control them, and then just disconnect when they're done. And they don't have to think about the complex distributed system behind all of that. They just get a browser running anywhere, anytime. Really easy to connect to.swyx [00:15:55]: I'm sure you have questions. My standard question with anything, so essentially you're a serverless browser company, and there's been other serverless things that I'm familiar with in the past, serverless GPUs, serverless website hosting. That's where I come from with Netlify. One question is just like, you promised to spin up thousands of servers. You promised to spin up thousands of browsers in milliseconds. I feel like there's no real solution that does that yet. And I'm just kind of curious how. The only solution I know, which is to kind of keep a kind of warm pool of servers around, which is expensive, but maybe not so expensive because it's just CPUs. So I'm just like, you know. Yeah.Browsers as a Core Primitive in AI InfrastructurePaul [00:16:36]: You nailed it, right? I mean, how do you offer a serverless-like experience with something that is clearly not serverless, right? And the answer is, you need to be able to run... We run many browsers on single nodes. We use Kubernetes at browser base. So we have many pods that are being scheduled. We have to predictably schedule them up or down. Yes, thousands of browsers in milliseconds is the best case scenario. If you hit us with 10,000 requests, you may hit a slower cold start, right? So we've done a lot of work on predictive scaling and being able to kind of route stuff to different regions where we have multiple regions of browser base where we have different pools available. You can also pick the region you want to go to based on like lower latency, round trip, time latency. It's very important with these types of things. There's a lot of requests going over the wire. So for us, like having a VM like Firecracker powering everything under the hood allows us to be super nimble and spin things up or down really quickly with strong multi-tenancy. But in the end, this is like the complex infrastructural challenges that we have to kind of deal with at browser base. And we have a lot more stuff on our roadmap to allow customers to have more levers to pull to exchange, do you want really fast browser startup times or do you want really low costs? And if you're willing to be more flexible on that, we may be able to kind of like work better for your use cases.swyx [00:17:44]: Since you used Firecracker, shouldn't Fargate do that for you or did you have to go lower level than that? We had to go lower level than that.Paul [00:17:51]: I find this a lot with Fargate customers, which is alarming for Fargate. We used to be a giant Fargate customer. Actually, the first version of browser base was ECS and Fargate. And unfortunately, it's a great product. I think we were actually the largest Fargate customer in our region for a little while. No, what? Yeah, seriously. And unfortunately, it's a great product, but I think if you're an infrastructure company, you actually have to have a deeper level of control over these primitives. I think it's the same thing is true with databases. We've used other database providers and I think-swyx [00:18:21]: Yeah, serverless Postgres.Paul [00:18:23]: Shocker. When you're an infrastructure company, you're on the hook if any provider has an outage. And I can't tell my customers like, hey, we went down because so-and-so went down. That's not acceptable. So for us, we've really moved to bringing things internally. It's kind of opposite of what we preach. We tell our customers, don't build this in-house, but then we're like, we build a lot of stuff in-house. But I think it just really depends on what is in the critical path. We try and have deep ownership of that.Alessio [00:18:46]: On the distributed location side, how does that work for the web where you might get sort of different content in different locations, but the customer is expecting, you know, if you're in the US, I'm expecting the US version. But if you're spinning up my browser in France, I might get the French version. Yeah.Paul [00:19:02]: Yeah. That's a good question. Well, generally, like on the localization, there is a thing called locale in the browser. You can set like what your locale is. If you're like in the ENUS browser or not, but some things do IP, IP based routing. And in that case, you may want to have a proxy. Like let's say you're running something in the, in Europe, but you want to make sure you're showing up from the US. You may want to use one of our proxy features so you can turn on proxies to say like, make sure these connections always come from the United States, which is necessary too, because when you're browsing the web, you're coming from like a, you know, data center IP, and that can make things a lot harder to browse web. So we do have kind of like this proxy super network. Yeah. We have a proxy for you based on where you're going, so you can reliably automate the web. But if you get scheduled in Europe, that doesn't happen as much. We try and schedule you as close to, you know, your origin that you're trying to go to. But generally you have control over the regions you can put your browsers in. So you can specify West one or East one or Europe. We only have one region of Europe right now, actually. Yeah.Alessio [00:19:55]: What's harder, the browser or the proxy? I feel like to me, it feels like actually proxying reliably at scale. It's much harder than spending up browsers at scale. I'm curious. It's all hard.Paul [00:20:06]: It's layers of hard, right? Yeah. I think it's different levels of hard. I think the thing with the proxy infrastructure is that we work with many different web proxy providers and some are better than others. Some have good days, some have bad days. And our customers who've built browser infrastructure on their own, they have to go and deal with sketchy actors. Like first they figure out their own browser infrastructure and then they got to go buy a proxy. And it's like you can pay in Bitcoin and it just kind of feels a little sus, right? It's like you're buying drugs when you're trying to get a proxy online. We have like deep relationships with these counterparties. We're able to audit them and say, is this proxy being sourced ethically? Like it's not running on someone's TV somewhere. Is it free range? Yeah. Free range organic proxies, right? Right. We do a level of diligence. We're SOC 2. So we have to understand what is going on here. But then we're able to make sure that like we route around proxy providers not working. There's proxy providers who will just, the proxy will stop working all of a sudden. And then if you don't have redundant proxying on your own browsers, that's hard down for you or you may get some serious impacts there. With us, like we intelligently know, hey, this proxy is not working. Let's go to this one. And you can kind of build a network of multiple providers to really guarantee the best uptime for our customers. Yeah. So you don't own any proxies? We don't own any proxies. You're right. The team has been saying who wants to like take home a little proxy server, but not yet. We're not there yet. You know?swyx [00:21:25]: It's a very mature market. I don't think you should build that yourself. Like you should just be a super customer of them. Yeah. Scraping, I think, is the main use case for that. I guess. Well, that leads us into CAPTCHAs and also off, but let's talk about CAPTCHAs. You had a little spiel that you wanted to talk about CAPTCHA stuff.Challenges of Scaling Browser InfrastructurePaul [00:21:43]: Oh, yeah. I was just, I think a lot of people ask, if you're thinking about proxies, you're thinking about CAPTCHAs too. I think it's the same thing. You can go buy CAPTCHA solvers online, but it's the same buying experience. It's some sketchy website, you have to integrate it. It's not fun to buy these things and you can't really trust that the docs are bad. What Browserbase does is we integrate a bunch of different CAPTCHAs. We do some stuff in-house, but generally we just integrate with a bunch of known vendors and continually monitor and maintain these things and say, is this working or not? Can we route around it or not? These are CAPTCHA solvers. CAPTCHA solvers, yeah. Not CAPTCHA providers, CAPTCHA solvers. Yeah, sorry. CAPTCHA solvers. We really try and make sure all of that works for you. I think as a dev, if I'm buying infrastructure, I want it all to work all the time and it's important for us to provide that experience by making sure everything does work and monitoring it on our own. Yeah. Right now, the world of CAPTCHAs is tricky. I think AI agents in particular are very much ahead of the internet infrastructure. CAPTCHAs are designed to block all types of bots, but there are now good bots and bad bots. I think in the future, CAPTCHAs will be able to identify who a good bot is, hopefully via some sort of KYC. For us, we've been very lucky. We have very little to no known abuse of Browserbase because we really look into who we work with. And for certain types of CAPTCHA solving, we only allow them on certain types of plans because we want to make sure that we can know what people are doing, what their use cases are. And that's really allowed us to try and be an arbiter of good bots, which is our long term goal. I want to build great relationships with people like Cloudflare so we can agree, hey, here are these acceptable bots. We'll identify them for you and make sure we flag when they come to your website. This is a good bot, you know?Alessio [00:23:23]: I see. And Cloudflare said they want to do more of this. So they're going to set by default, if they think you're an AI bot, they're going to reject. I'm curious if you think this is something that is going to be at the browser level or I mean, the DNS level with Cloudflare seems more where it should belong. But I'm curious how you think about it.Paul [00:23:40]: I think the web's going to change. You know, I think that the Internet as we have it right now is going to change. And we all need to just accept that the cat is out of the bag. And instead of kind of like wishing the Internet was like it was in the 2000s, we can have free content line that wouldn't be scraped. It's just it's not going to happen. And instead, we should think about like, one, how can we change? How can we change the models of, you know, information being published online so people can adequately commercialize it? But two, how do we rebuild applications that expect that AI agents are going to log in on their behalf? Those are the things that are going to allow us to kind of like identify good and bad bots. And I think the team at Clerk has been doing a really good job with this on the authentication side. I actually think that auth is the biggest thing that will prevent agents from accessing stuff, not captchas. And I think there will be agent auth in the future. I don't know if it's going to happen from an individual company, but actually authentication providers that have a, you know, hidden login as agent feature, which will then you put in your email, you'll get a push notification, say like, hey, your browser-based agent wants to log into your Airbnb. You can approve that and then the agent can proceed. That really circumvents the need for captchas or logging in as you and sharing your password. I think agent auth is going to be one way we identify good bots going forward. And I think a lot of this captcha solving stuff is really short-term problems as the internet kind of reorients itself around how it's going to work with agents browsing the web, just like people do. Yeah.Managing Distributed Browser Locations and Proxiesswyx [00:24:59]: Stitch recently was on Hacker News for talking about agent experience, AX, which is a thing that Netlify is also trying to clone and coin and talk about. And we've talked about this on our previous episodes before in a sense that I actually think that's like maybe the only part of the tech stack that needs to be kind of reinvented for agents. Everything else can stay the same, CLIs, APIs, whatever. But auth, yeah, we need agent auth. And it's mostly like short-lived, like it should not, it should be a distinct, identity from the human, but paired. I almost think like in the same way that every social network should have your main profile and then your alt accounts or your Finsta, it's almost like, you know, every, every human token should be paired with the agent token and the agent token can go and do stuff on behalf of the human token, but not be presumed to be the human. Yeah.Paul [00:25:48]: It's like, it's, it's actually very similar to OAuth is what I'm thinking. And, you know, Thread from Stitch is an investor, Colin from Clerk, Octaventures, all investors in browser-based because like, I hope they solve this because they'll make browser-based submission more possible. So we don't have to overcome all these hurdles, but I think it will be an OAuth-like flow where an agent will ask to log in as you, you'll approve the scopes. Like it can book an apartment on Airbnb, but it can't like message anybody. And then, you know, the agent will have some sort of like role-based access control within an application. Yeah. I'm excited for that.swyx [00:26:16]: The tricky part is just, there's one, one layer of delegation here, which is like, you're authoring my user's user or something like that. I don't know if that's tricky or not. Does that make sense? Yeah.Paul [00:26:25]: You know, actually at Twilio, I worked on the login identity and access. Management teams, right? So like I built Twilio's login page.swyx [00:26:31]: You were an intern on that team and then you became the lead in two years? Yeah.Paul [00:26:34]: Yeah. I started as an intern in 2016 and then I was the tech lead of that team. How? That's not normal. I didn't have a life. He's not normal. Look at this guy. I didn't have a girlfriend. I just loved my job. I don't know. I applied to 500 internships for my first job and I got rejected from every single one of them except for Twilio and then eventually Amazon. And they took a shot on me and like, I was getting paid money to write code, which was my dream. Yeah. Yeah. I'm very lucky that like this coding thing worked out because I was going to be doing it regardless. And yeah, I was able to kind of spend a lot of time on a team that was growing at a company that was growing. So it informed a lot of this stuff here. I think these are problems that have been solved with like the SAML protocol with SSO. I think it's a really interesting stuff with like WebAuthn, like these different types of authentication, like schemes that you can use to authenticate people. The tooling is all there. It just needs to be tweaked a little bit to work for agents. And I think the fact that there are companies that are already. Providing authentication as a service really sets it up. Well, the thing that's hard is like reinventing the internet for agents. We don't want to rebuild the internet. That's an impossible task. And I think people often say like, well, we'll have this second layer of APIs built for agents. I'm like, we will for the top use cases, but instead of we can just tweak the internet as is, which is on the authentication side, I think we're going to be the dumb ones going forward. Unfortunately, I think AI is going to be able to do a lot of the tasks that we do online, which means that it will be able to go to websites, click buttons on our behalf and log in on our behalf too. So with this kind of like web agent future happening, I think with some small structural changes, like you said, it feels like it could all slot in really nicely with the existing internet.Handling CAPTCHAs and Agent Authenticationswyx [00:28:08]: There's one more thing, which is the, your live view iframe, which lets you take, take control. Yeah. Obviously very key for operator now, but like, was, is there anything interesting technically there or that the people like, well, people always want this.Paul [00:28:21]: It was really hard to build, you know, like, so, okay. Headless browsers, you don't see them, right. They're running. They're running in a cloud somewhere. You can't like look at them. And I just want to really make, it's a weird name. I wish we came up with a better name for this thing, but you can't see them. Right. But customers don't trust AI agents, right. At least the first pass. So what we do with our live view is that, you know, when you use browser base, you can actually embed a live view of the browser running in the cloud for your customer to see it working. And that's what the first reason is the build trust, like, okay, so I have this script. That's going to go automate a website. I can embed it into my web application via an iframe and my customer can watch. I think. And then we added two way communication. So now not only can you watch the browser kind of being operated by AI, if you want to pause and actually click around type within this iframe that's controlling a browser, that's also possible. And this is all thanks to some of the lower level protocol, which is called the Chrome DevTools protocol. It has a API called start screencast, and you can also send mouse clicks and button clicks to a remote browser. And this is all embeddable within iframes. You have a browser within a browser, yo. And then you simulate the screen, the click on the other side. Exactly. And this is really nice often for, like, let's say, a capture that can't be solved. You saw this with Operator, you know, Operator actually uses a different approach. They use VNC. So, you know, you're able to see, like, you're seeing the whole window here. What we're doing is something a little lower level with the Chrome DevTools protocol. It's just PNGs being streamed over the wire. But the same thing is true, right? Like, hey, I'm running a window. Pause. Can you do something in this window? Human. Okay, great. Resume. Like sometimes 2FA tokens. Like if you get that text message, you might need a person to type that in. Web agents need human-in-the-loop type workflows still. You still need a person to interact with the browser. And building a UI to proxy that is kind of hard. You may as well just show them the whole browser and say, hey, can you finish this up for me? And then let the AI proceed on afterwards. Is there a future where I stream my current desktop to browser base? I don't think so. I think we're very much cloud infrastructure. Yeah. You know, but I think a lot of the stuff we're doing, we do want to, like, build tools. Like, you know, we'll talk about the stage and, you know, web agent framework in a second. But, like, there's a case where a lot of people are going desktop first for, you know, consumer use. And I think cloud is doing a lot of this, where I expect to see, you know, MCPs really oriented around the cloud desktop app for a reason, right? Like, I think a lot of these tools are going to run on your computer because it makes... I think it's breaking out. People are putting it on a server. Oh, really? Okay. Well, sweet. We'll see. We'll see that. I was surprised, though, wasn't I? I think that the browser company, too, with Dia Browser, it runs on your machine. You know, it's going to be...swyx [00:30:50]: What is it?Paul [00:30:51]: So, Dia Browser, as far as I understand... I used to use Arc. Yeah. I haven't used Arc. But I'm a big fan of the browser company. I think they're doing a lot of cool stuff in consumer. As far as I understand, it's a browser where you have a sidebar where you can, like, chat with it and it can control the local browser on your machine. So, if you imagine, like, what a consumer web agent is, which it lives alongside your browser, I think Google Chrome has Project Marina, I think. I almost call it Project Marinara for some reason. I don't know why. It's...swyx [00:31:17]: No, I think it's someone really likes the Waterworld. Oh, I see. The classic Kevin Costner. Yeah.Paul [00:31:22]: Okay. Project Marinara is a similar thing to the Dia Browser, in my mind, as far as I understand it. You have a browser that has an AI interface that will take over your mouse and keyboard and control the browser for you. Great for consumer use cases. But if you're building applications that rely on a browser and it's more part of a greater, like, AI app experience, you probably need something that's more like infrastructure, not a consumer app.swyx [00:31:44]: Just because I have explored a little bit in this area, do people want branching? So, I have the state. Of whatever my browser's in. And then I want, like, 100 clones of this state. Do people do that? Or...Paul [00:31:56]: People don't do it currently. Yeah. But it's definitely something we're thinking about. I think the idea of forking a browser is really cool. Technically, kind of hard. We're starting to see this in code execution, where people are, like, forking some, like, code execution, like, processes or forking some tool calls or branching tool calls. Haven't seen it at the browser level yet. But it makes sense. Like, if an AI agent is, like, using a website and it's not sure what path it wants to take to crawl this website. To find the information it's looking for. It would make sense for it to explore both paths in parallel. And that'd be a very, like... A road not taken. Yeah. And hopefully find the right answer. And then say, okay, this was actually the right one. And memorize that. And go there in the future. On the roadmap. For sure. Don't make my roadmap, please. You know?Alessio [00:32:37]: How do you actually do that? Yeah. How do you fork? I feel like the browser is so stateful for so many things.swyx [00:32:42]: Serialize the state. Restore the state. I don't know.Paul [00:32:44]: So, it's one of the reasons why we haven't done it yet. It's hard. You know? Like, to truly fork, it's actually quite difficult. The naive way is to open the same page in a new tab and then, like, hope that it's at the same thing. But if you have a form halfway filled, you may have to, like, take the whole, you know, container. Pause it. All the memory. Duplicate it. Restart it from there. It could be very slow. So, we haven't found a thing. Like, the easy thing to fork is just, like, copy the page object. You know? But I think there needs to be something a little bit more robust there. Yeah.swyx [00:33:12]: So, MorphLabs has this infinite branch thing. Like, wrote a custom fork of Linux or something that let them save the system state and clone it. MorphLabs, hit me up. I'll be a customer. Yeah. That's the only. I think that's the only way to do it. Yeah. Like, unless Chrome has some special API for you. Yeah.Paul [00:33:29]: There's probably something we'll reverse engineer one day. I don't know. Yeah.Alessio [00:33:32]: Let's talk about StageHand, the AI web browsing framework. You have three core components, Observe, Extract, and Act. Pretty clean landing page. What was the idea behind making a framework? Yeah.Stagehand: AI web browsing frameworkPaul [00:33:43]: So, there's three frameworks that are very popular or already exist, right? Puppeteer, Playwright, Selenium. Those are for building hard-coded scripts to control websites. And as soon as I started to play with LLMs plus browsing, I caught myself, you know, code-genning Playwright code to control a website. I would, like, take the DOM. I'd pass it to an LLM. I'd say, can you generate the Playwright code to click the appropriate button here? And it would do that. And I was like, this really should be part of the frameworks themselves. And I became really obsessed with SDKs that take natural language as part of, like, the API input. And that's what StageHand is. StageHand exposes three APIs, and it's a super set of Playwright. So, if you go to a page, you may want to take an action, click on the button, fill in the form, etc. That's what the act command is for. You may want to extract some data. This one takes a natural language, like, extract the winner of the Super Bowl from this page. You can give it a Zod schema, so it returns a structured output. And then maybe you're building an API. You can do an agent loop, and you want to kind of see what actions are possible on this page before taking one. You can do observe. So, you can observe the actions on the page, and it will generate a list of actions. You can guide it, like, give me actions on this page related to buying an item. And you can, like, buy it now, add to cart, view shipping options, and pass that to an LLM, an agent loop, to say, what's the appropriate action given this high-level goal? So, StageHand isn't a web agent. It's a framework for building web agents. And we think that agent loops are actually pretty close to the application layer because every application probably has different goals or different ways it wants to take steps. I don't think I've seen a generic. Maybe you guys are the experts here. I haven't seen, like, a really good AI agent framework here. Everyone kind of has their own special sauce, right? I see a lot of developers building their own agent loops, and they're using tools. And I view StageHand as the browser tool. So, we expose act, extract, observe. Your agent can call these tools. And from that, you don't have to worry about it. You don't have to worry about generating playwright code performantly. You don't have to worry about running it. You can kind of just integrate these three tool calls into your agent loop and reliably automate the web.swyx [00:35:48]: A special shout-out to Anirudh, who I met at your dinner, who I think listens to the pod. Yeah. Hey, Anirudh.Paul [00:35:54]: Anirudh's a man. He's a StageHand guy.swyx [00:35:56]: I mean, the interesting thing about each of these APIs is they're kind of each startup. Like, specifically extract, you know, Firecrawler is extract. There's, like, Expand AI. There's a whole bunch of, like, extract companies. They just focus on extract. I'm curious. Like, I feel like you guys are going to collide at some point. Like, right now, it's friendly. Everyone's in a blue ocean. At some point, it's going to be valuable enough that there's some turf battle here. I don't think you have a dog in a fight. I think you can mock extract to use an external service if they're better at it than you. But it's just an observation that, like, in the same way that I see each option, each checkbox in the side of custom GBTs becoming a startup or each box in the Karpathy chart being a startup. Like, this is also becoming a thing. Yeah.Paul [00:36:41]: I mean, like, so the way StageHand works is that it's MIT-licensed, completely open source. You bring your own API key to your LLM of choice. You could choose your LLM. We don't make any money off of the extract or really. We only really make money if you choose to run it with our browser. You don't have to. You can actually use your own browser, a local browser. You know, StageHand is completely open source for that reason. And, yeah, like, I think if you're building really complex web scraping workflows, I don't know if StageHand is the tool for you. I think it's really more if you're building an AI agent that needs a few general tools or if it's doing a lot of, like, web automation-intensive work. But if you're building a scraping company, StageHand is not your thing. You probably want something that's going to, like, get HTML content, you know, convert that to Markdown, query it. That's not what StageHand does. StageHand is more about reliability. I think we focus a lot on reliability and less so on cost optimization and speed at this point.swyx [00:37:33]: I actually feel like StageHand, so the way that StageHand works, it's like, you know, page.act, click on the quick start. Yeah. It's kind of the integration test for the code that you would have to write anyway, like the Puppeteer code that you have to write anyway. And when the page structure changes, because it always does, then this is still the test. This is still the test that I would have to write. Yeah. So it's kind of like a testing framework that doesn't need implementation detail.Paul [00:37:56]: Well, yeah. I mean, Puppeteer, Playwright, and Slenderman were all designed as testing frameworks, right? Yeah. And now people are, like, hacking them together to automate the web. I would say, and, like, maybe this is, like, me being too specific. But, like, when I write tests, if the page structure changes. Without me knowing, I want that test to fail. So I don't know if, like, AI, like, regenerating that. Like, people are using StageHand for testing. But it's more for, like, usability testing, not, like, testing of, like, does the front end, like, has it changed or not. Okay. But generally where we've seen people, like, really, like, take off is, like, if they're using, you know, something. If they want to build a feature in their application that's kind of like Operator or Deep Research, they're using StageHand to kind of power that tool calling in their own agent loop. Okay. Cool.swyx [00:38:37]: So let's go into Operator, the first big agent launch of the year from OpenAI. Seems like they have a whole bunch scheduled. You were on break and your phone blew up. What's your just general view of computer use agents is what they're calling it. The overall category before we go into Open Operator, just the overall promise of Operator. I will observe that I tried it once. It was okay. And I never tried it again.OpenAI's Operator and computer use agentsPaul [00:38:58]: That tracks with my experience, too. Like, I'm a huge fan of the OpenAI team. Like, I think that I do not view Operator as the company. I'm not a company killer for browser base at all. I think it actually shows people what's possible. I think, like, computer use models make a lot of sense. And I'm actually most excited about computer use models is, like, their ability to, like, really take screenshots and reasoning and output steps. I think that using mouse click or mouse coordinates, I've seen that proved to be less reliable than I would like. And I just wonder if that's the right form factor. What we've done with our framework is anchor it to the DOM itself, anchor it to the actual item. So, like, if it's clicking on something, it's clicking on that thing, you know? Like, it's more accurate. No matter where it is. Yeah, exactly. Because it really ties in nicely. And it can handle, like, the whole viewport in one go, whereas, like, Operator can only handle what it sees. Can you hover? Is hovering a thing that you can do? I don't know if we expose it as a tool directly, but I'm sure there's, like, an API for hovering. Like, move mouse to this position. Yeah, yeah, yeah. I think you can trigger hover, like, via, like, the JavaScript on the DOM itself. But, no, I think, like, when we saw computer use, everyone's eyes lit up because they realized, like, wow, like, AI is going to actually automate work for people. And I think seeing that kind of happen from both of the labs, and I'm sure we're going to see more labs launch computer use models, I'm excited to see all the stuff that people build with it. I think that I'd love to see computer use power, like, controlling a browser on browser base. And I think, like, Open Operator, which was, like, our open source version of OpenAI's Operator, was our first take on, like, how can we integrate these models into browser base? And we handle the infrastructure and let the labs do the models. I don't have a sense that Operator will be released as an API. I don't know. Maybe it will. I'm curious to see how well that works because I think it's going to be really hard for a company like OpenAI to do things like support CAPTCHA solving or, like, have proxies. Like, I think it's hard for them structurally. Imagine this New York Times headline, OpenAI CAPTCHA solving. Like, that would be a pretty bad headline, this New York Times headline. Browser base solves CAPTCHAs. No one cares. No one cares. And, like, our investors are bored. Like, we're all okay with this, you know? We're building this company knowing that the CAPTCHA solving is short-lived until we figure out how to authenticate good bots. I think it's really hard for a company like OpenAI, who has this brand that's so, so good, to balance with, like, the icky parts of web automation, which it can be kind of complex to solve. I'm sure OpenAI knows who to call whenever they need you. Yeah, right. I'm sure they'll have a great partnership.Alessio [00:41:23]: And is Open Operator just, like, a marketing thing for you? Like, how do you think about resource allocation? So, you can spin this up very quickly. And now there's all this, like, open deep research, just open all these things that people are building. We started it, you know. You're the original Open. We're the original Open operator, you know? Is it just, hey, look, this is a demo, but, like, we'll help you build out an actual product for yourself? Like, are you interested in going more of a product route? That's kind of the OpenAI way, right? They started as a model provider and then…Paul [00:41:53]: Yeah, we're not interested in going the product route yet. I view Open Operator as a model provider. It's a reference project, you know? Let's show people how to build these things using the infrastructure and models that are out there. And that's what it is. It's, like, Open Operator is very simple. It's an agent loop. It says, like, take a high-level goal, break it down into steps, use tool calling to accomplish those steps. It takes screenshots and feeds those screenshots into an LLM with the step to generate the right action. It uses stagehand under the hood to actually execute this action. It doesn't use a computer use model. And it, like, has a nice interface using the live view that we talked about, the iframe, to embed that into an application. So I felt like people on launch day wanted to figure out how to build their own version of this. And we turned that around really quickly to show them. And I hope we do that with other things like deep research. We don't have a deep research launch yet. I think David from AOMNI actually has an amazing open deep research that he launched. It has, like, 10K GitHub stars now. So he's crushing that. But I think if people want to build these features natively into their application, they need good reference projects. And I think Open Operator is a good example of that.swyx [00:42:52]: I don't know. Actually, I'm actually pretty bullish on API-driven operator. Because that's the only way that you can sort of, like, once it's reliable enough, obviously. And now we're nowhere near. But, like, give it five years. It'll happen, you know. And then you can sort of spin this up and browsers are working in the background and you don't necessarily have to know. And it just is booking restaurants for you, whatever. I can definitely see that future happening. I had this on the landing page here. This might be a slightly out of order. But, you know, you have, like, sort of three use cases for browser base. Open Operator. Or this is the operator sort of use case. It's kind of like the workflow automation use case. And it completes with UiPath in the sort of RPA category. Would you agree with that? Yeah, I would agree with that. And then there's Agents we talked about already. And web scraping, which I imagine would be the bulk of your workload right now, right?Paul [00:43:40]: No, not at all. I'd say actually, like, the majority is browser automation. We're kind of expensive for web scraping. Like, I think that if you're building a web scraping product, if you need to do occasional web scraping or you have to do web scraping that works every single time, you want to use browser automation. Yeah. You want to use browser-based. But if you're building web scraping workflows, what you should do is have a waterfall. You should have the first request is a curl to the website. See if you can get it without even using a browser. And then the second request may be, like, a scraping-specific API. There's, like, a thousand scraping APIs out there that you can use to try and get data. Scraping B. Scraping B is a great example, right? Yeah. And then, like, if those two don't work, bring out the heavy hitter. Like, browser-based will 100% work, right? It will load the page in a real browser, hydrate it. I see.swyx [00:44:21]: Because a lot of people don't render to JS.swyx [00:44:25]: Yeah, exactly.Paul [00:44:26]: So, I mean, the three big use cases, right? Like, you know, automation, web data collection, and then, you know, if you're building anything agentic that needs, like, a browser tool, you want to use browser-based.Alessio [00:44:35]: Is there any use case that, like, you were super surprised by that people might not even think about? Oh, yeah. Or is it, yeah, anything that you can share? The long tail is crazy. Yeah.Surprising use cases of BrowserbasePaul [00:44:44]: One of the case studies on our website that I think is the most interesting is this company called Benny. So, the way that it works is if you're on food stamps in the United States, you can actually get rebates if you buy certain things. Yeah. You buy some vegetables. You submit your receipt to the government. They'll give you a little rebate back. Say, hey, thanks for buying vegetables. It's good for you. That process of submitting that receipt is very painful. And the way Benny works is you use their app to take a photo of your receipt, and then Benny will go submit that receipt for you and then deposit the money into your account. That's actually using no AI at all. It's all, like, hard-coded scripts. They maintain the scripts. They've been doing a great job. And they build this amazing consumer app. But it's an example of, like, all these, like, tedious workflows that people have to do to kind of go about their business. And they're doing it for the sake of their day-to-day lives. And I had never known about, like, food stamp rebates or the complex forms you have to do to fill them. But the world is powered by millions and millions of tedious forms, visas. You know, Emirate Lighthouse is a customer, right? You know, they do the O1 visa. Millions and millions of forms are taking away humans' time. And I hope that Browserbase can help power software that automates away the web forms that we don't need anymore. Yeah.swyx [00:45:49]: I mean, I'm very supportive of that. I mean, forms. I do think, like, government itself is a big part of it. I think the government itself should embrace AI more to do more sort of human-friendly form filling. Mm-hmm. But I'm not optimistic. I'm not holding my breath. Yeah. We'll see. Okay. I think I'm about to zoom out. I have a little brief thing on computer use, and then we can talk about founder stuff, which is, I tend to think of developer tooling markets in impossible triangles, where everyone starts in a niche, and then they start to branch out. So I already hinted at a little bit of this, right? We mentioned more. We mentioned E2B. We mentioned Firecrawl. And then there's Browserbase. So there's, like, all this stuff of, like, have serverless virtual computer that you give to an agent and let them do stuff with it. And there's various ways of connecting it to the internet. You can just connect to a search API, like SERP API, whatever other, like, EXA is another one. That's what you're searching. You can also have a JSON markdown extractor, which is Firecrawl. Or you can have a virtual browser like Browserbase, or you can have a virtual machine like Morph. And then there's also maybe, like, a virtual sort of code environment, like Code Interpreter. So, like, there's just, like, a bunch of different ways to tackle the problem of give a computer to an agent. And I'm just kind of wondering if you see, like, everyone's just, like, happily coexisting in their respective niches. And as a developer, I just go and pick, like, a shopping basket of one of each. Or do you think that you eventually, people will collide?Future of browser automation and market competitionPaul [00:47:18]: I think that currently it's not a zero-sum market. Like, I think we're talking about... I think we're talking about all of knowledge work that people do that can be automated online. All of these, like, trillions of hours that happen online where people are working. And I think that there's so much software to be built that, like, I tend not to think about how these companies will collide. I just try to solve the problem as best as I can and make this specific piece of infrastructure, which I think is an important primitive, the best I possibly can. And yeah. I think there's players that are actually going to like it. I think there's players that are going to launch, like, over-the-top, you know, platforms, like agent platforms that have all these tools built in, right? Like, who's building the rippling for agent tools that has the search tool, the browser tool, the operating system tool, right? There are some. There are some. There are some, right? And I think in the end, what I have seen as my time as a developer, and I look at all the favorite tools that I have, is that, like, for tools and primitives with sufficient levels of complexity, you need to have a solution that's really bespoke to that primitive, you know? And I am sufficiently convinced that the browser is complex enough to deserve a primitive. Obviously, I have to. I'm the founder of BrowserBase, right? I'm talking my book. But, like, I think maybe I can give you one spicy take against, like, maybe just whole OS running. I think that when I look at computer use when it first came out, I saw that the majority of use cases for computer use were controlling a browser. And do we really need to run an entire operating system just to control a browser? I don't think so. I don't think that's necessary. You know, BrowserBase can run browsers for way cheaper than you can if you're running a full-fledged OS with a GUI, you know, operating system. And I think that's just an advantage of the browser. It is, like, browsers are little OSs, and you can run them very efficiently if you orchestrate it well. And I think that allows us to offer 90% of the, you know, functionality in the platform needed at 10% of the cost of running a full OS. Yeah.Open Operator: Browserbase's Open-Source Alternativeswyx [00:49:16]: I definitely see the logic in that. There's a Mark Andreessen quote. I don't know if you know this one. Where he basically observed that the browser is turning the operating system into a poorly debugged set of device drivers, because most of the apps are moved from the OS to the browser. So you can just run browsers.Paul [00:49:31]: There's a place for OSs, too. Like, I think that there are some applications that only run on Windows operating systems. And Eric from pig.dev in this upcoming YC batch, or last YC batch, like, he's building all run tons of Windows operating systems for you to control with your agent. And like, there's some legacy EHR systems that only run on Internet-controlled systems. Yeah.Paul [00:49:54]: I think that's it. I think, like, there are use cases for specific operating systems for specific legacy software. And like, I'm excited to see what he does with that. I just wanted to give a shout out to the pig.dev website.swyx [00:50:06]: The pigs jump when you click on them. Yeah. That's great.Paul [00:50:08]: Eric, he's the former co-founder of banana.dev, too.swyx [00:50:11]: Oh, that Eric. Yeah. That Eric. Okay. Well, he abandoned bananas for pigs. I hope he doesn't start going around with pigs now.Alessio [00:50:18]: Like he was going around with bananas. A little toy pig. Yeah. Yeah. I love that. What else are we missing? I think we covered a lot of, like, the browser-based product history, but. What do you wish people asked you? Yeah.Paul [00:50:29]: I wish people asked me more about, like, what will the future of software look like? Because I think that's really where I've spent a lot of time about why do browser-based. Like, for me, starting a company is like a means of last resort. Like, you shouldn't start a company unless you absolutely have to. And I remain convinced that the future of software is software that you're going to click a button and it's going to do stuff on your behalf. Right now, software. You click a button and it maybe, like, calls it back an API and, like, computes some numbers. It, like, modifies some text, whatever. But the future of software is software using software. So, I may log into my accounting website for my business, click a button, and it's going to go load up my Gmail, search my emails, find the thing, upload the receipt, and then comment it for me. Right? And it may use it using APIs, maybe a browser. I don't know. I think it's a little bit of both. But that's completely different from how we've built software so far. And that's. I think that future of software has different infrastructure requirements. It's going to require different UIs. It's going to require different pieces of infrastructure. I think the browser infrastructure is one piece that fits into that, along with all the other categories you mentioned. So, I think that it's going to require developers to think differently about how they've built software for, you know

Sejam uma vez mais benvindos ao espaço AS ABOVE SO BELOW.Hoje é tempo de falar sobre as previsões de Março, um mês cheio de oportunidades para novos começos intensos. Teremos não só a celebração do Equinócio da Primavera com a chegada do mês de Carneiro e o começo do novo ano astrológico mas também 2 eclipses, um ingresso histórico (Neptuno em Carneiro até 2039 anos) e claro os desconcertantes mas necessários Vénus e Mercúrio em Carneiro entre os signos de Peixes e Carneiro. O passado irá bater à porta e quem vai atender?Eis os tempos a saber:Introdução: 00:00:00Stellium em Peixes: 00:03:51Ingressos de Março: 00:15:501 MARÇO- VÉNUS RETRÓGRADO CARNEIRO3 MARÇO- MERCÚRIO EM CARNEIRO14 MARÇO- ECLIPSE LUNAR VIRGEM15 MARÇO- MERCÚRIO RETRÓGRADO20 MARÇO- SOL EM CARNEIRO27 MARÇO- VÉNUS RETRÓGRADO EM PEIXES29 MARÇO- ECLIPSE SOLAR CARNEIRO E MERCÚRIO RETRÓGRADO EM PEIXES30 MARÇO- NEPTUNO EM CARNEIRO Os personagens principais do mês de MARÇO: 00:37:00Impacto nos 12 signos do Zodíaco: 00:39:30CARNEIRO: 00: 39:39TOURO: 00:41:14GÉMEOS: 00:44:51CARANGUEJO: 00:49:10LEÃO: 00:52:00VIRGEM: 00:54:56BALANÇA: 00:57:20ESCORPIÃO:00:59:07SAGITÁRIO:01:01:45CAPRICÓRNIO: 01:05:00AQUÁRIO: 01:07:20PEIXES: 01:09:00FIM E ATÉ BREVE :) :01:15:00

Joël turns to fellow thoughtboter Jimmy Thigpen as he looks to expand his knowledge about the wide world of Typescripts. Together they discuss the differences between Typescript and other common systems such as Elm and Javascript, how to best handle their edge cases and error flags, as well as the benefits of using Zod as your typescript library. — Just starting out in Typescript? Try enabling Strict Mode! (https://www.typescriptlang.org/tsconfig/#strict) Try out Zod for yourself (https://zod-playground.vercel.app/) in their browser playground, or check out Zod's homepage (https://zod.dev/) for more info. If you'd like to contact Jimmy about all things Typescript he can be found over on LinkedIn (https://www.linkedin.com/in/thigpenjimmy/) Your host for this episode has been thoughtbot's own Joël Quenneville (https://www.linkedin.com/in/joel-quenneville-96b18b58/). If you would like to support the show, head over to our GitHub page (https://github.com/sponsors/thoughtbot), or check out our website (https://bikeshed.thoughtbot.com). Got a question or comment about the show? Why not write to our hosts: hosts@bikeshed.fm This has been a thoughtbot (https://thoughtbot.com/) podcast. Stay up to date by following us on social media - YouTube (https://www.youtube.com/@thoughtbot/streams) - LinkedIn (https://www.linkedin.com/company/150727/) - Mastodon (https://thoughtbot.social/@thoughtbot) - Instagram (https://www.instagram.com/thoughtbot/) © 2025 thoughtbot, inc.

The Return of Kara...and her amnesia?Clark takes a nice trip with Lois to the Phantom Zone and finds Kara there with some new dreads. While attempting to get back, the femdom wife of Zod takes over Lois' body in order to find her son...DAVIS?! Meanwhile, Tess continues to be annoying and Chloe uses Oliver just to steal and push him around.

Olá, jovens que aqui chegaram! Sejam bem vindos ao primeiro Chega de Sentimentalismo de 2025! Um episódio especial e tão grande que levou dois meses pra terminar de ser editado as custas da coluna e da sanidade do editor...E pra começar 2025 com o pé direito desenhando pelo """""mestre""""' Kurumada vamos falar do primeiro fracasso nos cinemas dos meninos enlatados muito antes de ser fracasso no cinema significar arrecadar metade da metade da metade do salário do estagiário que entrega cafezinho no set, como foi o recente live action! Vamos voltar a um tempo onde o filme fazer o dobre do orçamento já era considerado um fracasso vergonhoso! Vamos voltar a 2014 e falar de Os Cavaleiros do Zodíaco: A Lenda do Santuário, primeira tentativa da Toei de empurrar algo 100% inédito pro publico americano ao mesmo tempo que empurrava algo 100% requentado pro publico latino americano e europeu que ainda sustenta essa franquia.Então prepare-se pra conhecer uma Saori Kido que tem noção do quanto tudo que acontece ao seu redor é ridiculo demais pra ser verdade, um Seiya que parece que fugiu de um filme da Pixar e que dá duas vezes mais vontade de bater com um pé de mesa enrolado em arame farpado, um Hyoga que não apenas faz de tudo pra não trabalhar como se mostra full pistola por ter que bater ponto, um Shun que desiste na primeira oportunidade, um Shiryu que perdeu o manual de instruções da armadura e não sabe mais como tirar, um Ikki que aparece cheio de marra só pra apanhar na mão nua pro Shura , um Tatsumi PECAMINOSAMENTE com cabelo e um Mitsumasa Kido que não é um completo filho da puta arrombadaço!Juntos, eles terão que enfrentar os terríveis cavaleiros de ouro cuja as 12 casas ficam entre aquários de parques aquáticos e grandes banheirões coloniais e as armaduras ficam entre cortinas de banheiro e liteiras persas. Tudo isso em um Santuário que parece que a Asgard do filme do Thor teve um filho com o mundo de Final Fantasy 7 ao mesmo tempo que teve um caso com a Gotham de Joel Schumacher. Já deu pra ver que esse programa rendeu horrores em todos os sentidos, né? Então una-se a Hellbolha, Evandro, Kassius Klay e um silencioso, sorumbático e revoltado Godoka nesse GIGANTE!

Did you know that adding a simple Code Interpreter took o3 from 9.2% to 32% on FrontierMath? The Latent Space crew is hosting a hack night Feb 11th in San Francisco focused on CodeGen use cases, co-hosted with E2B and Edge AGI; watch E2B's new workshop and RSVP here!We're happy to announce that today's guest Samuel Colvin will be teaching his very first Pydantic AI workshop at the newly announced AI Engineer NYC Workshops day on Feb 22! 25 tickets left.If you're a Python developer, it's very likely that you've heard of Pydantic. Every month, it's downloaded >300,000,000 times, making it one of the top 25 PyPi packages. OpenAI uses it in its SDK for structured outputs, it's at the core of FastAPI, and if you've followed our AI Engineer Summit conference, Jason Liu of Instructor has given two great talks about it: “Pydantic is all you need” and “Pydantic is STILL all you need”. Now, Samuel Colvin has raised $17M from Sequoia to turn Pydantic from an open source project to a full stack AI engineer platform with Logfire, their observability platform, and PydanticAI, their new agent framework.Logfire: bringing OTEL to AIOpenTelemetry recently merged Semantic Conventions for LLM workloads which provides standard definitions to track performance like gen_ai.server.time_per_output_token. In Sam's view at least 80% of new apps being built today have some sort of LLM usage in them, and just like web observability platform got replaced by cloud-first ones in the 2010s, Logfire wants to do the same for AI-first apps. If you're interested in the technical details, Logfire migrated away from Clickhouse to Datafusion for their backend. We spent some time on the importance of picking open source tools you understand and that you can actually contribute to upstream, rather than the more popular ones; listen in ~43:19 for that part.Agents are the killer app for graphsPydantic AI is their attempt at taking a lot of the learnings that LangChain and the other early LLM frameworks had, and putting Python best practices into it. At an API level, it's very similar to the other libraries: you can call LLMs, create agents, do function calling, do evals, etc.They define an “Agent” as a container with a system prompt, tools, structured result, and an LLM. Under the hood, each Agent is now a graph of function calls that can orchestrate multi-step LLM interactions. You can start simple, then move toward fully dynamic graph-based control flow if needed.“We were compelled enough by graphs once we got them right that our agent implementation [...] is now actually a graph under the hood.”Why Graphs?* More natural for complex or multi-step AI workflows.* Easy to visualize and debug with mermaid diagrams.* Potential for distributed runs, or “waiting days” between steps in certain flows.In parallel, you see folks like Emil Eifrem of Neo4j talk about GraphRAG as another place where graphs fit really well in the AI stack, so it might be time for more people to take them seriously.Full Video EpisodeLike and subscribe!Chapters* 00:00:00 Introductions* 00:00:24 Origins of Pydantic* 00:05:28 Pydantic's AI moment * 00:08:05 Why build a new agents framework?* 00:10:17 Overview of Pydantic AI* 00:12:33 Becoming a believer in graphs* 00:24:02 God Model vs Compound AI Systems* 00:28:13 Why not build an LLM gateway?* 00:31:39 Programmatic testing vs live evals* 00:35:51 Using OpenTelemetry for AI traces* 00:43:19 Why they don't use Clickhouse* 00:48:34 Competing in the observability space* 00:50:41 Licensing decisions for Pydantic and LogFire* 00:51:48 Building Pydantic.run* 00:55:24 Marimo and the future of Jupyter notebooks* 00:57:44 London's AI sceneShow Notes* Sam Colvin* Pydantic* Pydantic AI* Logfire* Pydantic.run* Zod* E2B* Arize* Langsmith* Marimo* Prefect* GLA (Google Generative Language API)* OpenTelemetry* Jason Liu* Sebastian Ramirez* Bogomil Balkansky* Hood Chatham* Jeremy Howard* Andrew LambTranscriptAlessio [00:00:03]: Hey, everyone. Welcome to the Latent Space podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol AI.Swyx [00:00:12]: Good morning. And today we're very excited to have Sam Colvin join us from Pydantic AI. Welcome. Sam, I heard that Pydantic is all we need. Is that true?Samuel [00:00:24]: I would say you might need Pydantic AI and Logfire as well, but it gets you a long way, that's for sure.Swyx [00:00:29]: Pydantic almost basically needs no introduction. It's almost 300 million downloads in December. And obviously, in the previous podcasts and discussions we've had with Jason Liu, he's been a big fan and promoter of Pydantic and AI.Samuel [00:00:45]: Yeah, it's weird because obviously I didn't create Pydantic originally for uses in AI, it predates LLMs. But it's like we've been lucky that it's been picked up by that community and used so widely.Swyx [00:00:58]: Actually, maybe we'll hear it. Right from you, what is Pydantic and maybe a little bit of the origin story?Samuel [00:01:04]: The best name for it, which is not quite right, is a validation library. And we get some tension around that name because it doesn't just do validation, it will do coercion by default. We now have strict mode, so you can disable that coercion. But by default, if you say you want an integer field and you get in a string of 1, 2, 3, it will convert it to 123 and a bunch of other sensible conversions. And as you can imagine, the semantics around it. Exactly when you convert and when you don't, it's complicated, but because of that, it's more than just validation. Back in 2017, when I first started it, the different thing it was doing was using type hints to define your schema. That was controversial at the time. It was genuinely disapproved of by some people. I think the success of Pydantic and libraries like FastAPI that build on top of it means that today that's no longer controversial in Python. And indeed, lots of other people have copied that route, but yeah, it's a data validation library. It uses type hints for the for the most part and obviously does all the other stuff you want, like serialization on top of that. But yeah, that's the core.Alessio [00:02:06]: Do you have any fun stories on how JSON schemas ended up being kind of like the structure output standard for LLMs? And were you involved in any of these discussions? Because I know OpenAI was, you know, one of the early adopters. So did they reach out to you? Was there kind of like a structure output console in open source that people were talking about or was it just a random?Samuel [00:02:26]: No, very much not. So I originally. Didn't implement JSON schema inside Pydantic and then Sebastian, Sebastian Ramirez, FastAPI came along and like the first I ever heard of him was over a weekend. I got like 50 emails from him or 50 like emails as he was committing to Pydantic, adding JSON schema long pre version one. So the reason it was added was for OpenAPI, which is obviously closely akin to JSON schema. And then, yeah, I don't know why it was JSON that got picked up and used by OpenAI. It was obviously very convenient for us. That's because it meant that not only can you do the validation, but because Pydantic will generate you the JSON schema, it will it kind of can be one source of source of truth for structured outputs and tools.Swyx [00:03:09]: Before we dive in further on the on the AI side of things, something I'm mildly curious about, obviously, there's Zod in JavaScript land. Every now and then there is a new sort of in vogue validation library that that takes over for quite a few years and then maybe like some something else comes along. Is Pydantic? Is it done like the core Pydantic?Samuel [00:03:30]: I've just come off a call where we were redesigning some of the internal bits. There will be a v3 at some point, which will not break people's code half as much as v2 as in v2 was the was the massive rewrite into Rust, but also fixing all the stuff that was broken back from like version zero point something that we didn't fix in v1 because it was a side project. We have plans to move some of the basically store the data in Rust types after validation. Not completely. So we're still working to design the Pythonic version of it, in order for it to be able to convert into Python types. So then if you were doing like validation and then serialization, you would never have to go via a Python type we reckon that can give us somewhere between three and five times another three to five times speed up. That's probably the biggest thing. Also, like changing how easy it is to basically extend Pydantic and define how particular types, like for example, NumPy arrays are validated and serialized. But there's also stuff going on. And for example, Jitter, the JSON library in Rust that does the JSON parsing, has SIMD implementation at the moment only for AMD64. So we can add that. We need to go and add SIMD for other instruction sets. So there's a bunch more we can do on performance. I don't think we're going to go and revolutionize Pydantic, but it's going to continue to get faster, continue, hopefully, to allow people to do more advanced things. We might add a binary format like CBOR for serialization for when you'll just want to put the data into a database and probably load it again from Pydantic. So there are some things that will come along, but for the most part, it should just get faster and cleaner.Alessio [00:05:04]: From a focus perspective, I guess, as a founder too, how did you think about the AI interest rising? And then how do you kind of prioritize, okay, this is worth going into more, and we'll talk about Pydantic AI and all of that. What was maybe your early experience with LLAMP, and when did you figure out, okay, this is something we should take seriously and focus more resources on it?Samuel [00:05:28]: I'll answer that, but I'll answer what I think is a kind of parallel question, which is Pydantic's weird, because Pydantic existed, obviously, before I was starting a company. I was working on it in my spare time, and then beginning of 22, I started working on the rewrite in Rust. And I worked on it full-time for a year and a half, and then once we started the company, people came and joined. And it was a weird project, because that would never go away. You can't get signed off inside a startup. Like, we're going to go off and three engineers are going to work full-on for a year in Python and Rust, writing like 30,000 lines of Rust just to release open-source-free Python library. The result of that has been excellent for us as a company, right? As in, it's made us remain entirely relevant. And it's like, Pydantic is not just used in the SDKs of all of the AI libraries, but I can't say which one, but one of the big foundational model companies, when they upgraded from Pydantic v1 to v2, their number one internal model... The metric of performance is time to first token. That went down by 20%. So you think about all of the actual AI going on inside, and yet at least 20% of the CPU, or at least the latency inside requests was actually Pydantic, which shows like how widely it's used. So we've benefited from doing that work, although it didn't, it would have never have made financial sense in most companies. In answer to your question about like, how do we prioritize AI, I mean, the honest truth is we've spent a lot of the last year and a half building. Good general purpose observability inside LogFire and making Pydantic good for general purpose use cases. And the AI has kind of come to us. Like we just, not that we want to get away from it, but like the appetite, uh, both in Pydantic and in LogFire to go and build with AI is enormous because it kind of makes sense, right? Like if you're starting a new greenfield project in Python today, what's the chance that you're using GenAI 80%, let's say, globally, obviously it's like a hundred percent in California, but even worldwide, it's probably 80%. Yeah. And so everyone needs that stuff. And there's so much yet to be figured out so much like space to do things better in the ecosystem in a way that like to go and implement a database that's better than Postgres is a like Sisyphean task. Whereas building, uh, tools that are better for GenAI than some of the stuff that's about now is not very difficult. Putting the actual models themselves to one side.Alessio [00:07:40]: And then at the same time, then you released Pydantic AI recently, which is, uh, um, you know, agent framework and early on, I would say everybody like, you know, Langchain and like, uh, Pydantic kind of like a first class support, a lot of these frameworks, we're trying to use you to be better. What was the decision behind we should do our own framework? Were there any design decisions that you disagree with any workloads that you think people didn't support? Well,Samuel [00:08:05]: it wasn't so much like design and workflow, although I think there were some, some things we've done differently. Yeah. I think looking in general at the ecosystem of agent frameworks, the engineering quality is far below that of the rest of the Python ecosystem. There's a bunch of stuff that we have learned how to do over the last 20 years of building Python libraries and writing Python code that seems to be abandoned by people when they build agent frameworks. Now I can kind of respect that, particularly in the very first agent frameworks, like Langchain, where they were literally figuring out how to go and do this stuff. It's completely understandable that you would like basically skip some stuff.Samuel [00:08:42]: I'm shocked by the like quality of some of the agent frameworks that have come out recently from like well-respected names, which it just seems to be opportunism and I have little time for that, but like the early ones, like I think they were just figuring out how to do stuff and just as lots of people have learned from Pydantic, we were able to learn a bit from them. I think from like the gap we saw and the thing we were frustrated by was the production readiness. And that means things like type checking, even if type checking makes it hard. Like Pydantic AI, I will put my hand up now and say it has a lot of generics and you need to, it's probably easier to use it if you've written a bit of Rust and you really understand generics, but like, and that is, we're not claiming that that makes it the easiest thing to use in all cases, we think it makes it good for production applications in big systems where type checking is a no-brainer in Python. But there are also a bunch of stuff we've learned from maintaining Pydantic over the years that we've gone and done. So every single example in Pydantic AI's documentation is run on Python. As part of tests and every single print output within an example is checked during tests. So it will always be up to date. And then a bunch of things that, like I say, are standard best practice within the rest of the Python ecosystem, but I'm not followed surprisingly by some AI libraries like coverage, linting, type checking, et cetera, et cetera, where I think these are no-brainers, but like weirdly they're not followed by some of the other libraries.Alessio [00:10:04]: And can you just give an overview of the framework itself? I think there's kind of like the. LLM calling frameworks, there are the multi-agent frameworks, there's the workflow frameworks, like what does Pydantic AI do?Samuel [00:10:17]: I glaze over a bit when I hear all of the different sorts of frameworks, but I like, and I will tell you when I built Pydantic, when I built Logfire and when I built Pydantic AI, my methodology is not to go and like research and review all of the other things. I kind of work out what I want and I go and build it and then feedback comes and we adjust. So the fundamental building block of Pydantic AI is agents. The exact definition of agents and how you want to define them. is obviously ambiguous and our things are probably sort of agent-lit, not that we would want to go and rename them to agent-lit, but like the point is you probably build them together to build something and most people will call an agent. So an agent in our case has, you know, things like a prompt, like system prompt and some tools and a structured return type if you want it, that covers the vast majority of cases. There are situations where you want to go further and the most complex workflows where you want graphs and I resisted graphs for quite a while. I was sort of of the opinion you didn't need them and you could use standard like Python flow control to do all of that stuff. I had a few arguments with people, but I basically came around to, yeah, I can totally see why graphs are useful. But then we have the problem that by default, they're not type safe because if you have a like add edge method where you give the names of two different edges, there's no type checking, right? Even if you go and do some, I'm not, not all the graph libraries are AI specific. So there's a, there's a graph library called, but it allows, it does like a basic runtime type checking. Ironically using Pydantic to try and make up for the fact that like fundamentally that graphs are not typed type safe. Well, I like Pydantic, but it did, that's not a real solution to have to go and run the code to see if it's safe. There's a reason that starting type checking is so powerful. And so we kind of, from a lot of iteration eventually came up with a system of using normally data classes to define nodes where you return the next node you want to call and where we're able to go and introspect the return type of a node to basically build the graph. And so the graph is. Yeah. Inherently type safe. And once we got that right, I, I wasn't, I'm incredibly excited about graphs. I think there's like masses of use cases for them, both in gen AI and other development, but also software's all going to have interact with gen AI, right? It's going to be like web. There's no longer be like a web department in a company is that there's just like all the developers are building for web building with databases. The same is going to be true for gen AI.Alessio [00:12:33]: Yeah. I see on your docs, you call an agent, a container that contains a system prompt function. Tools, structure, result, dependency type model, and then model settings. Are the graphs in your mind, different agents? Are they different prompts for the same agent? What are like the structures in your mind?Samuel [00:12:52]: So we were compelled enough by graphs once we got them right, that we actually merged the PR this morning. That means our agent implementation without changing its API at all is now actually a graph under the hood as it is built using our graph library. So graphs are basically a lower level tool that allow you to build these complex workflows. Our agents are technically one of the many graphs you could go and build. And we just happened to build that one for you because it's a very common, commonplace one. But obviously there are cases where you need more complex workflows where the current agent assumptions don't work. And that's where you can then go and use graphs to build more complex things.Swyx [00:13:29]: You said you were cynical about graphs. What changed your mind specifically?Samuel [00:13:33]: I guess people kept giving me examples of things that they wanted to use graphs for. And my like, yeah, but you could do that in standard flow control in Python became a like less and less compelling argument to me because I've maintained those systems that end up with like spaghetti code. And I could see the appeal of this like structured way of defining the workflow of my code. And it's really neat that like just from your code, just from your type hints, you can get out a mermaid diagram that defines exactly what can go and happen.Swyx [00:14:00]: Right. Yeah. You do have very neat implementation of sort of inferring the graph from type hints, I guess. Yeah. Is what I would call it. Yeah. I think the question always is I have gone back and forth. I used to work at Temporal where we would actually spend a lot of time complaining about graph based workflow solutions like AWS step functions. And we would actually say that we were better because you could use normal control flow that you already knew and worked with. Yours, I guess, is like a little bit of a nice compromise. Like it looks like normal Pythonic code. But you just have to keep in mind what the type hints actually mean. And that's what we do with the quote unquote magic that the graph construction does.Samuel [00:14:42]: Yeah, exactly. And if you look at the internal logic of actually running a graph, it's incredibly simple. It's basically call a node, get a node back, call that node, get a node back, call that node. If you get an end, you're done. We will add in soon support for, well, basically storage so that you can store the state between each node that's run. And then the idea is you can then distribute the graph and run it across computers. And also, I mean, the other weird, the other bit that's really valuable is across time. Because it's all very well if you look at like lots of the graph examples that like Claude will give you. If it gives you an example, it gives you this lovely enormous mermaid chart of like the workflow, for example, managing returns if you're an e-commerce company. But what you realize is some of those lines are literally one function calls another function. And some of those lines are wait six days for the customer to print their like piece of paper and put it in the post. And if you're writing like your demo. Project or your like proof of concept, that's fine because you can just say, and now we call this function. But when you're building when you're in real in real life, that doesn't work. And now how do we manage that concept to basically be able to start somewhere else in the in our code? Well, this graph implementation makes it incredibly easy because you just pass the node that is the start point for carrying on the graph and it continues to run. So it's things like that where I was like, yeah, I can just imagine how things I've done in the past would be fundamentally easier to understand if we had done them with graphs.Swyx [00:16:07]: You say imagine, but like right now, this pedantic AI actually resume, you know, six days later, like you said, or is this just like a theoretical thing we can go someday?Samuel [00:16:16]: I think it's basically Q&A. So there's an AI that's asking the user a question and effectively you then call the CLI again to continue the conversation. And it basically instantiates the node and calls the graph with that node again. Now, we don't have the logic yet for effectively storing state in the database between individual nodes that we're going to add soon. But like the rest of it is basically there.Swyx [00:16:37]: It does make me think that not only are you competing with Langchain now and obviously Instructor, and now you're going into sort of the more like orchestrated things like Airflow, Prefect, Daxter, those guys.Samuel [00:16:52]: Yeah, I mean, we're good friends with the Prefect guys and Temporal have the same investors as us. And I'm sure that my investor Bogomol would not be too happy if I was like, oh, yeah, by the way, as well as trying to take on Datadog. We're also going off and trying to take on Temporal and everyone else doing that. Obviously, we're not doing all of the infrastructure of deploying that right yet, at least. We're, you know, we're just building a Python library. And like what's crazy about our graph implementation is, sure, there's a bit of magic in like introspecting the return type, you know, extracting things from unions, stuff like that. But like the actual calls, as I say, is literally call a function and get back a thing and call that. It's like incredibly simple and therefore easy to maintain. The question is, how useful is it? Well, I don't know yet. I think we have to go and find out. We have a whole. We've had a slew of people joining our Slack over the last few days and saying, tell me how good Pydantic AI is. How good is Pydantic AI versus Langchain? And I refuse to answer. That's your job to go and find that out. Not mine. We built a thing. I'm compelled by it, but I'm obviously biased. The ecosystem will work out what the useful tools are.Swyx [00:17:52]: Bogomol was my board member when I was at Temporal. And I think I think just generally also having been a workflow engine investor and participant in this space, it's a big space. Like everyone needs different functions. I think the one thing that I would say like yours, you know, as a library, you don't have that much control of it over the infrastructure. I do like the idea that each new agents or whatever or unit of work, whatever you call that should spin up in this sort of isolated boundaries. Whereas yours, I think around everything runs in the same process. But you ideally want to sort of spin out its own little container of things.Samuel [00:18:30]: I agree with you a hundred percent. And we will. It would work now. Right. As in theory, you're just like as long as you can serialize the calls to the next node, you just have to all of the different containers basically have to have the same the same code. I mean, I'm super excited about Cloudflare workers running Python and being able to install dependencies. And if Cloudflare could only give me my invitation to the private beta of that, we would be exploring that right now because I'm super excited about that as a like compute level for some of this stuff where exactly what you're saying, basically. You can run everything as an individual. Like worker function and distribute it. And it's resilient to failure, et cetera, et cetera.Swyx [00:19:08]: And it spins up like a thousand instances simultaneously. You know, you want it to be sort of truly serverless at once. Actually, I know we have some Cloudflare friends who are listening, so hopefully they'll get in front of the line. Especially.Samuel [00:19:19]: I was in Cloudflare's office last week shouting at them about other things that frustrate me. I have a love-hate relationship with Cloudflare. Their tech is awesome. But because I use it the whole time, I then get frustrated. So, yeah, I'm sure I will. I will. I will get there soon.Swyx [00:19:32]: There's a side tangent on Cloudflare. Is Python supported at full? I actually wasn't fully aware of what the status of that thing is.Samuel [00:19:39]: Yeah. So Pyodide, which is Python running inside the browser in scripting, is supported now by Cloudflare. They basically, they're having some struggles working out how to manage, ironically, dependencies that have binaries, in particular, Pydantic. Because these workers where you can have thousands of them on a given metal machine, you don't want to have a difference. You basically want to be able to have a share. Shared memory for all the different Pydantic installations, effectively. That's the thing they work out. They're working out. But Hood, who's my friend, who is the primary maintainer of Pyodide, works for Cloudflare. And that's basically what he's doing, is working out how to get Python running on Cloudflare's network.Swyx [00:20:19]: I mean, the nice thing is that your binary is really written in Rust, right? Yeah. Which also compiles the WebAssembly. Yeah. So maybe there's a way that you'd build... You have just a different build of Pydantic and that ships with whatever your distro for Cloudflare workers is.Samuel [00:20:36]: Yes, that's exactly what... So Pyodide has builds for Pydantic Core and for things like NumPy and basically all of the popular binary libraries. Yeah. It's just basic. And you're doing exactly that, right? You're using Rust to compile the WebAssembly and then you're calling that shared library from Python. And it's unbelievably complicated, but it works. Okay.Swyx [00:20:57]: Staying on graphs a little bit more, and then I wanted to go to some of the other features that you have in Pydantic AI. I see in your docs, there are sort of four levels of agents. There's single agents, there's agent delegation, programmatic agent handoff. That seems to be what OpenAI swarms would be like. And then the last one, graph-based control flow. Would you say that those are sort of the mental hierarchy of how these things go?Samuel [00:21:21]: Yeah, roughly. Okay.Swyx [00:21:22]: You had some expression around OpenAI swarms. Well.Samuel [00:21:25]: And indeed, OpenAI have got in touch with me and basically, maybe I'm not supposed to say this, but basically said that Pydantic AI looks like what swarms would become if it was production ready. So, yeah. I mean, like, yeah, which makes sense. Awesome. Yeah. I mean, in fact, it was specifically saying, how can we give people the same feeling that they were getting from swarms that led us to go and implement graphs? Because my, like, just call the next agent with Python code was not a satisfactory answer to people. So it was like, okay, we've got to go and have a better answer for that. It's not like, let us to get to graphs. Yeah.Swyx [00:21:56]: I mean, it's a minimal viable graph in some sense. What are the shapes of graphs that people should know? So the way that I would phrase this is I think Anthropic did a very good public service and also kind of surprisingly influential blog post, I would say, when they wrote Building Effective Agents. We actually have the authors coming to speak at my conference in New York, which I think you're giving a workshop at. Yeah.Samuel [00:22:24]: I'm trying to work it out. But yes, I think so.Swyx [00:22:26]: Tell me if you're not. yeah, I mean, like, that was the first, I think, authoritative view of, like, what kinds of graphs exist in agents and let's give each of them a name so that everyone is on the same page. So I'm just kind of curious if you have community names or top five patterns of graphs.Samuel [00:22:44]: I don't have top five patterns of graphs. I would love to see what people are building with them. But like, it's been it's only been a couple of weeks. And of course, there's a point is that. Because they're relatively unopinionated about what you can go and do with them. They don't suit them. Like, you can go and do lots of lots of things with them, but they don't have the structure to go and have like specific names as much as perhaps like some other systems do. I think what our agents are, which have a name and I can't remember what it is, but this basically system of like, decide what tool to call, go back to the center, decide what tool to call, go back to the center and then exit. One form of graph, which, as I say, like our agents are effectively one implementation of a graph, which is why under the hood they are now using graphs. And it'll be interesting to see over the next few years whether we end up with these like predefined graph names or graph structures or whether it's just like, yep, I built a graph or whether graphs just turn out not to match people's mental image of what they want and die away. We'll see.Swyx [00:23:38]: I think there is always appeal. Every developer eventually gets graph religion and goes, oh, yeah, everything's a graph. And then they probably over rotate and go go too far into graphs. And then they have to learn a whole bunch of DSLs. And then they're like, actually, I didn't need that. I need this. And they scale back a little bit.Samuel [00:23:55]: I'm at the beginning of that process. I'm currently a graph maximalist, although I haven't actually put any into production yet. But yeah.Swyx [00:24:02]: This has a lot of philosophical connections with other work coming out of UC Berkeley on compounding AI systems. I don't know if you know of or care. This is the Gartner world of things where they need some kind of industry terminology to sell it to enterprises. I don't know if you know about any of that.Samuel [00:24:24]: I haven't. I probably should. I should probably do it because I should probably get better at selling to enterprises. But no, no, I don't. Not right now.Swyx [00:24:29]: This is really the argument is that instead of putting everything in one model, you have more control and more maybe observability to if you break everything out into composing little models and changing them together. And obviously, then you need an orchestration framework to do that. Yeah.Samuel [00:24:47]: And it makes complete sense. And one of the things we've seen with agents is they work well when they work well. But when they. Even if you have the observability through log five that you can see what was going on, if you don't have a nice hook point to say, hang on, this is all gone wrong. You have a relatively blunt instrument of basically erroring when you exceed some kind of limit. But like what you need to be able to do is effectively iterate through these runs so that you can have your own control flow where you're like, OK, we've gone too far. And that's where one of the neat things about our graph implementation is you can basically call next in a loop rather than just running the full graph. And therefore, you have this opportunity to to break out of it. But yeah, basically, it's the same point, which is like if you have two bigger unit of work to some extent, whether or not it involves gen AI. But obviously, it's particularly problematic in gen AI. You only find out afterwards when you've spent quite a lot of time and or money when it's gone off and done done the wrong thing.Swyx [00:25:39]: Oh, drop on this. We're not going to resolve this here, but I'll drop this and then we can move on to the next thing. This is the common way that we we developers talk about this. And then the machine learning researchers look at us. And laugh and say, that's cute. And then they just train a bigger model and they wipe us out in the next training run. So I think there's a certain amount of we are fighting the bitter lesson here. We're fighting AGI. And, you know, when AGI arrives, this will all go away. Obviously, on Latent Space, we don't really discuss that because I think AGI is kind of this hand wavy concept that isn't super relevant. But I think we have to respect that. For example, you could do a chain of thoughts with graphs and you could manually orchestrate a nice little graph that does like. Reflect, think about if you need more, more inference time, compute, you know, that's the hot term now. And then think again and, you know, scale that up. Or you could train Strawberry and DeepSeq R1. Right.Samuel [00:26:32]: I saw someone saying recently, oh, they were really optimistic about agents because models are getting faster exponentially. And I like took a certain amount of self-control not to describe that it wasn't exponential. But my main point was. If models are getting faster as quickly as you say they are, then we don't need agents and we don't really need any of these abstraction layers. We can just give our model and, you know, access to the Internet, cross our fingers and hope for the best. Agents, agent frameworks, graphs, all of this stuff is basically making up for the fact that right now the models are not that clever. In the same way that if you're running a customer service business and you have loads of people sitting answering telephones, the less well trained they are, the less that you trust them, the more that you need to give them a script to go through. Whereas, you know, so if you're running a bank and you have lots of customer service people who you don't trust that much, then you tell them exactly what to say. If you're doing high net worth banking, you just employ people who you think are going to be charming to other rich people and set them off to go and have coffee with people. Right. And the same is true of models. The more intelligent they are, the less we need to tell them, like structure what they go and do and constrain the routes in which they take.Swyx [00:27:42]: Yeah. Yeah. Agree with that. So I'm happy to move on. So the other parts of Pydantic AI that are worth commenting on, and this is like my last rant, I promise. So obviously, every framework needs to do its sort of model adapter layer, which is, oh, you can easily swap from OpenAI to Cloud to Grok. You also have, which I didn't know about, Google GLA, which I didn't really know about until I saw this in your docs, which is generative language API. I assume that's AI Studio? Yes.Samuel [00:28:13]: Google don't have good names for it. So Vertex is very clear. That seems to be the API that like some of the things use, although it returns 503 about 20% of the time. So... Vertex? No. Vertex, fine. But the... Oh, oh. GLA. Yeah. Yeah.Swyx [00:28:28]: I agree with that.Samuel [00:28:29]: So we have, again, another example of like, well, I think we go the extra mile in terms of engineering is we run on every commit, at least commit to main, we run tests against the live models. Not lots of tests, but like a handful of them. Oh, okay. And we had a point last week where, yeah, GLA is a little bit better. GLA1 was failing every single run. One of their tests would fail. And we, I think we might even have commented out that one at the moment. So like all of the models fail more often than you might expect, but like that one seems to be particularly likely to fail. But Vertex is the same API, but much more reliable.Swyx [00:29:01]: My rant here is that, you know, versions of this appear in Langchain and every single framework has to have its own little thing, a version of that. I would put to you, and then, you know, this is, this can be agree to disagree. This is not needed in Pydantic AI. I would much rather you adopt a layer like Lite LLM or what's the other one in JavaScript port key. And that's their job. They focus on that one thing and they, they normalize APIs for you. All new models are automatically added and you don't have to duplicate this inside of your framework. So for example, if I wanted to use deep seek, I'm out of luck because Pydantic AI doesn't have deep seek yet.Samuel [00:29:38]: Yeah, it does.Swyx [00:29:39]: Oh, it does. Okay. I'm sorry. But you know what I mean? Should this live in your code or should it live in a layer that's kind of your API gateway that's a defined piece of infrastructure that people have?Samuel [00:29:49]: And I think if a company who are well known, who are respected by everyone had come along and done this at the right time, maybe we should have done it a year and a half ago and said, we're going to be the universal AI layer. That would have been a credible thing to do. I've heard varying reports of Lite LLM is the truth. And it didn't seem to have exactly the type safety that we needed. Also, as I understand it, and again, I haven't looked into it in great detail. Part of their business model is proxying the request through their, through their own system to do the generalization. That would be an enormous put off to an awful lot of people. Honestly, the truth is I don't think it is that much work unifying the model. I get where you're coming from. I kind of see your point. I think the truth is that everyone is centralizing around open AIs. Open AI's API is the one to do. So DeepSeq support that. Grok with OK support that. Ollama also does it. I mean, if there is that library right now, it's more or less the open AI SDK. And it's very high quality. It's well type checked. It uses Pydantic. So I'm biased. But I mean, I think it's pretty well respected anyway.Swyx [00:30:57]: There's different ways to do this. Because also, it's not just about normalizing the APIs. You have to do secret management and all that stuff.Samuel [00:31:05]: Yeah. And there's also. There's Vertex and Bedrock, which to one extent or another, effectively, they host multiple models, but they don't unify the API. But they do unify the auth, as I understand it. Although we're halfway through doing Bedrock. So I don't know about it that well. But they're kind of weird hybrids because they support multiple models. But like I say, the auth is centralized.Swyx [00:31:28]: Yeah, I'm surprised they don't unify the API. That seems like something that I would do. You know, we can discuss all this all day. There's a lot of APIs. I agree.Samuel [00:31:36]: It would be nice if there was a universal one that we didn't have to go and build.Alessio [00:31:39]: And I guess the other side of, you know, routing model and picking models like evals. How do you actually figure out which one you should be using? I know you have one. First of all, you have very good support for mocking in unit tests, which is something that a lot of other frameworks don't do. So, you know, my favorite Ruby library is VCR because it just, you know, it just lets me store the HTTP requests and replay them. That part I'll kind of skip. I think you are busy like this test model. We're like just through Python. You try and figure out what the model might respond without actually calling the model. And then you have the function model where people can kind of customize outputs. Any other fun stories maybe from there? Or is it just what you see is what you get, so to speak?Samuel [00:32:18]: On those two, I think what you see is what you get. On the evals, I think watch this space. I think it's something that like, again, I was somewhat cynical about for some time. Still have my cynicism about some of the well, it's unfortunate that so many different things are called evals. It would be nice if we could agree. What they are and what they're not. But look, I think it's a really important space. I think it's something that we're going to be working on soon, both in Pydantic AI and in LogFire to try and support better because it's like it's an unsolved problem.Alessio [00:32:45]: Yeah, you do say in your doc that anyone who claims to know for sure exactly how your eval should be defined can safely be ignored.Samuel [00:32:52]: We'll delete that sentence when we tell people how to do their evals.Alessio [00:32:56]: Exactly. I was like, we need we need a snapshot of this today. And so let's talk about eval. So there's kind of like the vibe. Yeah. So you have evals, which is what you do when you're building. Right. Because you cannot really like test it that many times to get statistical significance. And then there's the production eval. So you also have LogFire, which is kind of like your observability product, which I tried before. It's very nice. What are some of the learnings you've had from building an observability tool for LEMPs? And yeah, as people think about evals, even like what are the right things to measure? What are like the right number of samples that you need to actually start making decisions?Samuel [00:33:33]: I'm not the best person to answer that is the truth. So I'm not going to come in here and tell you that I think I know the answer on the exact number. I mean, we can do some back of the envelope statistics calculations to work out that like having 30 probably gets you most of the statistical value of having 200 for, you know, by definition, 15% of the work. But the exact like how many examples do you need? For example, that's a much harder question to answer because it's, you know, it's deep within the how models operate in terms of LogFire. One of the reasons we built LogFire the way we have and we allow you to write SQL directly against your data and we're trying to build the like powerful fundamentals of observability is precisely because we know we don't know the answers. And so allowing people to go and innovate on how they're going to consume that stuff and how they're going to process it is we think that's valuable. Because even if we come along and offer you an evals framework on top of LogFire, it won't be right in all regards. And we want people to be able to go and innovate and being able to write their own SQL connected to the API. And effectively query the data like it's a database with SQL allows people to innovate on that stuff. And that's what allows us to do it as well. I mean, we do a bunch of like testing what's possible by basically writing SQL directly against LogFire as any user could. I think the other the other really interesting bit that's going on in observability is OpenTelemetry is centralizing around semantic attributes for GenAI. So it's a relatively new project. A lot of it's still being added at the moment. But basically the idea that like. They unify how both SDKs and or agent frameworks send observability data to to any OpenTelemetry endpoint. And so, again, we can go and having that unification allows us to go and like basically compare different libraries, compare different models much better. That stuff's in a very like early stage of development. One of the things we're going to be working on pretty soon is basically, I suspect, GenAI will be the first agent framework that implements those semantic attributes properly. Because, again, we control and we can say this is important for observability, whereas most of the other agent frameworks are not maintained by people who are trying to do observability. With the exception of Langchain, where they have the observability platform, but they chose not to go down the OpenTelemetry route. So they're like plowing their own furrow. And, you know, they're a lot they're even further away from standardization.Alessio [00:35:51]: Can you maybe just give a quick overview of how OTEL ties into the AI workflows? There's kind of like the question of is, you know, a trace. And a span like a LLM call. Is it the agent? It's kind of like the broader thing you're tracking. How should people think about it?Samuel [00:36:06]: Yeah, so they have a PR that I think may have now been merged from someone at IBM talking about remote agents and trying to support this concept of remote agents within GenAI. I'm not particularly compelled by that because I don't think that like that's actually by any means the common use case. But like, I suppose it's fine for it to be there. The majority of the stuff in OTEL is basically defining how you would instrument. A given call to an LLM. So basically the actual LLM call, what data you would send to your telemetry provider, how you would structure that. Apart from this slightly odd stuff on remote agents, most of the like agent level consideration is not yet implemented in is not yet decided effectively. And so there's a bit of ambiguity. Obviously, what's good about OTEL is you can in the end send whatever attributes you like. But yeah, there's quite a lot of churn in that space and exactly how we store the data. I think that one of the most interesting things, though, is that if you think about observability. Traditionally, it was sure everyone would say our observability data is very important. We must keep it safe. But actually, companies work very hard to basically not have anything that sensitive in their observability data. So if you're a doctor in a hospital and you search for a drug for an STI, the sequel might be sent to the observability provider. But none of the parameters would. It wouldn't have the patient number or their name or the drug. With GenAI, that distinction doesn't exist because it's all just messed up in the text. If you have that same patient asking an LLM how to. What drug they should take or how to stop smoking. You can't extract the PII and not send it to the observability platform. So the sensitivity of the data that's going to end up in observability platforms is going to be like basically different order of magnitude to what's in what you would normally send to Datadog. Of course, you can make a mistake and send someone's password or their card number to Datadog. But that would be seen as a as a like mistake. Whereas in GenAI, a lot of data is going to be sent. And I think that's why companies like Langsmith and are trying hard to offer observability. On prem, because there's a bunch of companies who are happy for Datadog to be cloud hosted, but want self-hosted self-hosting for this observability stuff with GenAI.Alessio [00:38:09]: And are you doing any of that today? Because I know in each of the spans you have like the number of tokens, you have the context, you're just storing everything. And then you're going to offer kind of like a self-hosting for the platform, basically. Yeah. Yeah.Samuel [00:38:23]: So we have scrubbing roughly equivalent to what the other observability platforms have. So if we, you know, if we see password as the key, we won't send the value. But like, like I said, that doesn't really work in GenAI. So we're accepting we're going to have to store a lot of data and then we'll offer self-hosting for those people who can afford it and who need it.Alessio [00:38:42]: And then this is, I think, the first time that most of the workloads performance is depending on a third party. You know, like if you're looking at Datadog data, usually it's your app that is driving the latency and like the memory usage and all of that. Here you're going to have spans that maybe take a long time to perform because the GLA API is not working or because OpenAI is kind of like overwhelmed. Do you do anything there since like the provider is almost like the same across customers? You know, like, are you trying to surface these things for people and say, hey, this was like a very slow span, but actually all customers using OpenAI right now are seeing the same thing. So maybe don't worry about it or.Samuel [00:39:20]: Not yet. We do a few things that people don't generally do in OTA. So we send. We send information at the beginning. At the beginning of a trace as well as sorry, at the beginning of a span, as well as when it finishes. By default, OTA only sends you data when the span finishes. So if you think about a request which might take like 20 seconds, even if some of the intermediate spans finished earlier, you can't basically place them on the page until you get the top level span. And so if you're using standard OTA, you can't show anything until those requests are finished. When those requests are taking a few hundred milliseconds, it doesn't really matter. But when you're doing Gen AI calls or when you're like running a batch job that might take 30 minutes. That like latency of not being able to see the span is like crippling to understanding your application. And so we've we do a bunch of slightly complex stuff to basically send data about a span as it starts, which is closely related. Yeah.Alessio [00:40:09]: Any thoughts on all the other people trying to build on top of OpenTelemetry in different languages, too? There's like the OpenLEmetry project, which doesn't really roll off the tongue. But how do you see the future of these kind of tools? Is everybody going to have to build? Why does everybody want to build? They want to build their own open source observability thing to then sell?Samuel [00:40:29]: I mean, we are not going off and trying to instrument the likes of the OpenAI SDK with the new semantic attributes, because at some point that's going to happen and it's going to live inside OTEL and we might help with it. But we're a tiny team. We don't have time to go and do all of that work. So OpenLEmetry, like interesting project. But I suspect eventually most of those semantic like that instrumentation of the big of the SDKs will live, like I say, inside the main OpenTelemetry report. I suppose. What happens to the agent frameworks? What data you basically need at the framework level to get the context is kind of unclear. I don't think we know the answer yet. But I mean, I was on the, I guess this is kind of semi-public, because I was on the call with the OpenTelemetry call last week talking about GenAI. And there was someone from Arize talking about the challenges they have trying to get OpenTelemetry data out of Langchain, where it's not like natively implemented. And obviously they're having quite a tough time. And I was realizing, hadn't really realized this before, but how lucky we are to primarily be talking about our own agent framework, where we have the control rather than trying to go and instrument other people's.Swyx [00:41:36]: Sorry, I actually didn't know about this semantic conventions thing. It looks like, yeah, it's merged into main OTel. What should people know about this? I had never heard of it before.Samuel [00:41:45]: Yeah, I think it looks like a great start. I think there's some unknowns around how you send the messages that go back and forth, which is kind of the most important part. It's the most important thing of all. And that is moved out of attributes and into OTel events. OTel events in turn are moving from being on a span to being their own top-level API where you send data. So there's a bunch of churn still going on. I'm impressed by how fast the OTel community is moving on this project. I guess they, like everyone else, get that this is important, and it's something that people are crying out to get instrumentation off. So I'm kind of pleasantly surprised at how fast they're moving, but it makes sense.Swyx [00:42:25]: I'm just kind of browsing through the specification. I can already see that this basically bakes in whatever the previous paradigm was. So now they have genai.usage.prompt tokens and genai.usage.completion tokens. And obviously now we have reasoning tokens as well. And then only one form of sampling, which is top-p. You're basically baking in or sort of reifying things that you think are important today, but it's not a super foolproof way of doing this for the future. Yeah.Samuel [00:42:54]: I mean, that's what's neat about OTel is you can always go and send another attribute and that's fine. It's just there are a bunch that are agreed on. But I would say, you know, to come back to your previous point about whether or not we should be relying on one centralized abstraction layer, this stuff is moving so fast that if you start relying on someone else's standard, you risk basically falling behind because you're relying on someone else to keep things up to date.Swyx [00:43:14]: Or you fall behind because you've got other things going on.Samuel [00:43:17]: Yeah, yeah. That's fair. That's fair.Swyx [00:43:19]: Any other observations just about building LogFire, actually? Let's just talk about this. So you announced LogFire. I was kind of only familiar with LogFire because of your Series A announcement. I actually thought you were making a separate company. I remember some amount of confusion with you when that came out. So to be clear, it's Pydantic LogFire and the company is one company that has kind of two products, an open source thing and an observability thing, correct? Yeah. I was just kind of curious, like any learnings building LogFire? So classic question is, do you use ClickHouse? Is this like the standard persistence layer? Any learnings doing that?Samuel [00:43:54]: We don't use ClickHouse. We started building our database with ClickHouse, moved off ClickHouse onto Timescale, which is a Postgres extension to do analytical databases. Wow. And then moved off Timescale onto DataFusion. And we're basically now building, it's DataFusion, but it's kind of our own database. Bogomil is not entirely happy that we went through three databases before we chose one. I'll say that. But like, we've got to the right one in the end. I think we could have realized that Timescale wasn't right. I think ClickHouse. They both taught us a lot and we're in a great place now. But like, yeah, it's been a real journey on the database in particular.Swyx [00:44:28]: Okay. So, you know, as a database nerd, I have to like double click on this, right? So ClickHouse is supposed to be the ideal backend for anything like this. And then moving from ClickHouse to Timescale is another counterintuitive move that I didn't expect because, you know, Timescale is like an extension on top of Postgres. Not super meant for like high volume logging. But like, yeah, tell us those decisions.Samuel [00:44:50]: So at the time, ClickHouse did not have good support for JSON. I was speaking to someone yesterday and said ClickHouse doesn't have good support for JSON and got roundly stepped on because apparently it does now. So they've obviously gone and built their proper JSON support. But like back when we were trying to use it, I guess a year ago or a bit more than a year ago, everything happened to be a map and maps are a pain to try and do like looking up JSON type data. And obviously all these attributes, everything you're talking about there in terms of the GenAI stuff. You can choose to make them top level columns if you want. But the simplest thing is just to put them all into a big JSON pile. And that was a problem with ClickHouse. Also, ClickHouse had some really ugly edge cases like by default, or at least until I complained about it a lot, ClickHouse thought that two nanoseconds was longer than one second because they compared intervals just by the number, not the unit. And I complained about that a lot. And then they caused it to raise an error and just say you have to have the same unit. Then I complained a bit more. And I think as I understand it now, they have some. They convert between units. But like stuff like that, when all you're looking at is when a lot of what you're doing is comparing the duration of spans was really painful. Also things like you can't subtract two date times to get an interval. You have to use the date sub function. But like the fundamental thing is because we want our end users to write SQL, the like quality of the SQL, how easy it is to write, matters way more to us than if you're building like a platform on top where your developers are going to write the SQL. And once it's written and it's working, you don't mind too much. So I think that's like one of the fundamental differences. The other problem that I have with the ClickHouse and Impact Timescale is that like the ultimate architecture, the like snowflake architecture of binary data in object store queried with some kind of cache from nearby. They both have it, but it's closed sourced and you only get it if you go and use their hosted versions. And so even if we had got through all the problems with Timescale or ClickHouse, we would end up like, you know, they would want to be taking their 80% margin. And then we would be wanting to take that would basically leave us less space for margin. Whereas data fusion. Properly open source, all of that same tooling is open source. And for us as a team of people with a lot of Rust expertise, data fusion, which is implemented in Rust, we can literally dive into it and go and change it. So, for example, I found that there were some slowdowns in data fusion's string comparison kernel for doing like string contains. And it's just Rust code. And I could go and rewrite the string comparison kernel to be faster. Or, for example, data fusion, when we started using it, didn't have JSON support. Obviously, as I've said, it's something we can do. It's something we needed. I was able to go and implement that in a weekend using our JSON parser that we built for Pydantic Core. So it's the fact that like data fusion is like for us the perfect mixture of a toolbox to build a database with, not a database. And we can go and implement stuff on top of it in a way that like if you were trying to do that in Postgres or in ClickHouse. I mean, ClickHouse would be easier because it's C++, relatively modern C++. But like as a team of people who are not C++ experts, that's much scarier than data fusion for us.Swyx [00:47:47]: Yeah, that's a beautiful rant.Alessio [00:47:49]: That's funny. Most people don't think they have agency on these projects. They're kind of like, oh, I should use this or I should use that. They're not really like, what should I pick so that I contribute the most back to it? You know, so but I think you obviously have an open source first mindset. So that makes a lot of sense.Samuel [00:48:05]: I think if we were probably better as a startup, a better startup and faster moving and just like headlong determined to get in front of customers as fast as possible, we should have just started with ClickHouse. I hope that long term we're in a better place for having worked with data fusion. We like we're quite engaged now with the data fusion community. Andrew Lam, who maintains data fusion, is an advisor to us. We're in a really good place now. But yeah, it's definitely slowed us down relative to just like building on ClickHouse and moving as fast as we can.Swyx [00:48:34]: OK, we're about to zoom out and do Pydantic run and all the other stuff. But, you know, my last question on LogFire is really, you know, at some point you run out sort of community goodwill just because like, oh, I use Pydantic. I love Pydantic. I'm going to use LogFire. OK, then you start entering the territory of the Datadogs, the Sentrys and the honeycombs. Yeah. So where are you going to really spike here? What differentiator here?Samuel [00:48:59]: I wasn't writing code in 2001, but I'm assuming that there were people talking about like web observability and then web observability stopped being a thing, not because the web stopped being a thing, but because all observability had to do web. If you were talking to people in 2010 or 2012, they would have talked about cloud observability. Now that's not a term because all observability is cloud first. The same is going to happen to gen AI. And so whether or not you're trying to compete with Datadog or with Arise and Langsmith, you've got to do first class. You've got to do general purpose observability with first class support for AI. And as far as I know, we're the only people really trying to do that. I mean, I think Datadog is starting in that direction. And to be honest, I think Datadog is a much like scarier company to compete with than the AI specific observability platforms. Because in my opinion, and I've also heard this from lots of customers, AI specific observability where you don't see everything else going on in your app is not actually that useful. Our hope is that we can build the first general purpose observability platform with first class support for AI. And that we have this open source heritage of putting developer experience first that other companies haven't done. For all I'm a fan of Datadog and what they've done. If you search Datadog logging Python. And you just try as a like a non-observability expert to get something up and running with Datadog and Python. It's not trivial, right? That's something Sentry have done amazingly well. But like there's enormous space in most of observability to do DX better.Alessio [00:50:27]: Since you mentioned Sentry, I'm curious how you thought about licensing and all of that. Obviously, your MIT license, you don't have any rolling license like Sentry has where you can only use an open source, like the one year old version of it. Was that a hard decision?Samuel [00:50:41]: So to be clear, LogFire is co-sourced. So Pydantic and Pydantic AI are MIT licensed and like properly open source. And then LogFire for now is completely closed source. And in fact, the struggles that Sentry have had with licensing and the like weird pushback the community gives when they take something that's closed source and make it source available just meant that we just avoided that whole subject matter. I think the other way to look at it is like in terms of either headcount or revenue or dollars in the bank. The amount of open source we do as a company is we've got to be open source. We're up there with the most prolific open source companies, like I say, per head. And so we didn't feel like we were morally obligated to make LogFire open source. We have Pydantic. Pydantic is a foundational library in Python. That and now Pydantic AI are our contribution to open source. And then LogFire is like openly for profit, right? As in we're not claiming otherwise. We're not sort of trying to walk a line if it's open source. But really, we want to make it hard to deploy. So you probably want to pay us. We're trying to be straight. That it's to pay for. We could change that at some point in the future, but it's not an immediate plan.Alessio [00:51:48]: All right. So the first one I saw this new I don't know if it's like a product you're building the Pydantic that run, which is a Python browser sandbox. What was the inspiration behind that? We talk a lot about code interpreter for lamps. I'm an investor in a company called E2B, which is a code sandbox as a service for remote execution. Yeah. What's the Pydantic that run story?Samuel [00:52:09]: So Pydantic that run is again completely open source. I have no interest in making it into a product. We just needed a sandbox to be able to demo LogFire in particular, but also Pydantic AI. So it doesn't have it yet, but I'm going to add basically a proxy to OpenAI and the other models so that you can run Pydantic AI in the browser. See how it works. Tweak the prompt, et cetera, et cetera. And we'll have some kind of limit per day of what you can spend on it or like what the spend is. The other thing we wanted to b

A new challenger to rival OpenAI's best ChatGPT model has arisen from China named DeepSeek R1. The reason it's causing even more of a stir is because the creators claim DeepSeek R1 was trained for under $5M - a mere fraction of the cost of comparable models to date - and they've open sourced the code, the models, all of it.In the same vein, both TJ and Paige had the chance to try out AI coding assistant Devin.ai firsthand last week. Devin is best described as an energetic junior programmer, and while it offers unique ways of interacting with it: Slack threads, PR comments, and has oversight over multiple repos so it can be asked to do things like compare documentation in one repo to SDK endpoints in another repo, its end value is still questionable.TypeScript validation libraries have been catching on in recent years, and the creators of some of the most popular ones (Zod, ArkType, and Valibot) have gotten together to promote a common interface for libraries called Standard Schema.News:Paige - Standard Schema promotes a common interface for TypeScript validation librariesJack - DeepSeek R1TJ - Our firsthand experiences with Devin.ai and jokes about AI trained coding assistantsBonus News:Matt Biilman coins the next big term in web dev experience: AX (“agent experience”)Vercel acquires dashboard and chart library TremorHas the “Rust wave” crested?Fire Starters:toReversed, toSorted, and toSplicedWhat Makes Us Happy this Week:Paige - The Recruit TV seriesJack - The Subtle Art of Not Giving a F*ckTJ - Onyx StormThanks as always to our sponsor, the Blue Collar Coder channel on YouTube. You can join us in our Discord channel, explore our website and reach us via email, or Tweet us on X @front_end_fire and BlueSky.Front-end Fire websiteBlue Collar Coder on YouTubeBlue Collar Coder on DiscordReach out via emailTweet at us on X @front_end_fireFollow us on Bluesky @front-end-fire.com

It's a whole new Smallville this week as we enter the CW era in Season 6 Episode 1: ZOD. After we wrap things up with Michael's black trench coat Zod arch, Tom's warm-ups in the Phantom Zone, and exploring the complexities of Lana's games with Lex… we discuss the move of Smallville to its new home on the CW and what it was like working with new faces in Season 6. Thank you to our sponsors: ❤️ This episode is sponsored by by BetterHelp. Give online therapy a try at https://betterhelp.com/talkville and get on your way to being your best self.

Fortune favors the brave.Powerful forces begin the week and make you cocky about the influence you yield. Watch out for power struggles and others lashing out at you. Stay ahead of the competition by focusing on your own work.This is the perfect time to make changes because they will happen quickly and relatively smoothly.Get ready to celebrate yourself and all you have already accomplished this month!Show Notes: January 2025 Monthly Star Planner Podcast: https://www.kimwoods.com/podcastepisodes/your-star-path-to-success-episode-135-january-2025-forecast-bold-new-beginnings/January 2025 Monthly Star Planner BLOG:https://www.kimwoods.com/january-2025-astrology-forecast/Have a wonderful, successful, and bountiful start to your year! Don't forget to rate, review, and share with friends! Until next time, happy soul tidings!

We're unpacking Episode 4, “Can't Say I Remember No At Attin.” The crew of the Onyx Cinder has made it home, or have they? Wim, Fern, KB, Neel, Zod, and SM-33 find themselves in the middle of a conflict in a place that seems like At Attin, yet it's vastly different. With live phone calls bringing your thoughts, theories, and questions, we explore the latest twists and turns of STAR WARS: SKELETON CREW. Get full show video, ad-free shows, bonus exclusive podcasts, early bird releases and more with  RFR on PATREON: https://www.patreon.com/RebelForceRadio OFFICIAL WEBSITE: https://www.rebelforceradio.com FACEBOOK - Like RFR! https://www.facebook.com/rebelforceradio TWITTER - Follow RFR! https://twitter.com/RFRRebelForce INSTAGRAM: https://www.instagram.com/rebelforceradio YOUTUBE: https://www.youtube.com/rebelforceradio THREADS: https://www.threads.net/@rebelforceradio BLUESKY: https://bsky.app/profile/rebelforceradio.bsky.social

“Silly old sod* (*General Zod)” The panel of peril emerge from their fortress of solitude (the toilet), wherein they have lost quite a lot of their own power (…). With their last ounce of strength, they pop themselves onto a comfy chair to watch this week's film Superman II (Richard Lester, 1980). Superman/Clark Kent (Christopher Reeve) has settled into life in Metropolis in fine style maintaining his dual identity of clumsy reporter and messiah figure with aplomb. But when he chucks a bomb into space and releases his father's arch enemies, led by General Zod (Terence Stamp), his life is about to become an absolute disaster area! Watch the trailer here: https://www.youtube.com/watch?v=jxD8RlGnP64 ********PLOT SPOILER ALERT******** As (bad) luck would have it, Kal-El has forsaken his powers in a grand gesture of love towards the ever-spunk ace reporter Lois Lane (Margot Kidder). Needless to say, that makes planet Earth easy pickings for Zod and the gang, who are joined by snitch extraordinaire Lex Luthor (Gene Hackman) as he guides Kryptonian crims towards revenge for their imprisonment! Is the Earth doomed, or can the Man of Steel return to save the day? What did the heck panel think of this week's movie? How in all that is holy can they improve upon the villain's masterplan? And which evil schemer will be christened this week's most diabolical? https://bsky.app/profile/diabolicalpod.bsky.social https://twitter.com/diabolicalpod https://www.instagram.com/diabolicalpod/ https://www.facebook.com/diabolicalpod Email diabolicalpod@gmail.com

Join Tom Welling and Michael Rosenbaum for the penultimate Season 5 episode and the return of a familiar face in Episode 21: ORACLE! After getting a much needed history lesson on the truth behind Season 5 from Al Gough, we discuss the good evil intentions of Lex Luthor's venture into biowarfare and his Zod-like transformation in the last couple episodes here. Thank you to our sponsors: ❤️ Betterhelp: https://betterhelp.com/talkville

In part one of Red Eye Radio with Gary McNamara and Eric Harley, the ladies on The View are just not happy (despite names like Joy, Sunny and Whoopi). Also Ellen DeGeneres decides to leave the country citing the outcome of the election, Rand Paul against using the military for deportation, audio from the incoming border czar on the Laken Riley conviction. Also the radical left transgender movement and audio from Nancy Mace with her passionate stance on women's privacy as well as AOC's response, Donald Trump releases limited edition line of guitars, must hear audio from Senator John Kennedy. Also a black Jedi is in demand, a discussion on bad movies and good documentaries. As well as audio from Scott Jennings on MSNBC's Mika & Joe bow down to Zod. For more talk on the issues that matter to you, listen on radio stations across America Monday-Friday 12am-5am CT (1am-6am ET and 10pm-3am PT), download the RED EYE RADIO SHOW app, asking your smart speaker, or listening at RedEyeRadioShow.com Learn more about your ad choices. Visit podcastchoices.com/adchoices

Host Anthony Desiato and guest Dan Greenfield (13th Dimension) dig into the 1980 film SUPERMAN II, a beloved entry in the franchise despite — or perhaps because of? — being the product of two directors' visions. A combination of original director Richard Donner's more grounded, earnest approach and replacement Richard Lester's campier leanings, the movie follows Christopher Reeve's Superman as he relinquishes his powers to begin a romance with Lois Lane (Margot Kidder)...just as Kryptonian trio of Zod, Non, and Ursa escape the Phantom Zone. The specific focus of this episode is the official theatrical cut, though Anthony and Dan do discuss the long-fabled Donner Cut, which was finally released in 2006 — and offer their final word on what the "best" version of SUPERMAN II truly is.Support the show and receive exclusive podcast content at Patreon.com/AnthonyDesiato, including the spinoff podcasts BEYOND METROPOLIS and DIGGING FOR JUSTICE!Visit BCW Supplies and use promo code FSP to save 10% on your next order of comics supplies. FACEBOOK GROUP: Digging for Kryptonite: A Superman Fan GroupFACEBOOK PAGE: @diggingforkryptonitepodINSTAGRAM: @diggingforkryptonitepodTWITTER: @diggingforkrpodEMAIL: flatsquirrelproductions@gmail.comWEBSITE: FlatSquirrelProductions.com Digging for Kryptonite is a Flat Squirrel Production. Key art by Isaiah Simmons (2020-2024 version by Gregg Schigiel). Theme music by Basic Printer.Mentioned in this episode:Aw Yeah ComicsAlways Hold On To SmallvilleHang On To Your Shorts Film FestivalFat Moose Comics

Ski-bi dibby dib yo da dub dub! Nesta edição, Cleber Facchi (@cleberfacchi), Isadora Almeida (@almeidadora), Renan Guerra (@_renanguerra) e Nik Silva (@niksilva) voltam no tempo para conversar sobre a origem da Eurodance, o ápice na década de 1990 e toda a movimentação que revelou nomes como Haddaway, Corona, Technotronic, Aqua e La Bouche. Apoie a gente: https://apoia.se/podcastvfsm Não Paro De Ouvir ➜ The Cure https://tinyurl.com/mpb8twkj➜ Teto Preto https://tinyurl.com/2p8xwt65➜ LCD Soundsystem https://tinyurl.com/4kcdnusc➜ Fabiana Palladino https://tinyurl.com/3j5pctzj➜ Kokoroko https://tinyurl.com/5985p65u➜ Ruthven https://tinyurl.com/tsemns38➜ Marcelo D2 https://tinyurl.com/3eymv4b5➜ Paira https://tinyurl.com/n3a788ha➜ Murcielago https://tinyurl.com/bdddk2wb➜ George Daniel https://tinyurl.com/29yw5a75➜ Tunde Adebimpe https://tinyurl.com/yum9ncau➜ Ethel Cain https://tinyurl.com/4uph6mnh➜ Nina Maia https://tinyurl.com/5bm86tp7➜ Zopelar https://tinyurl.com/4xpn6xff➜ Sergio Estranho https://tinyurl.com/ycy426b9➜ Mount Eerie https://tinyurl.com/5xj7vft6 Você Precisa Ouvir Isso ➜ Young Justice (MAX)➜ Aqui Quem Fala É o Zodíaco (Netflix)➜ Bleach Thousand-Year Blood War (Disney +) Playlist Seleção VFSM: https://bit.ly/3ETG7oEContato: sobremusicavamosfalar@gmail.com

Mikey & Jeremy watch S6E1 of Smallville, "Zod". They discuss kryptonian super powers, the Bonecracker, and Martha's mission from Jor-El.

Entre nuestra experiencia de ir descubriendo el género a los treinta y tantos (Dani) y cómo consumir anime desde la infancia nos ha marcado y lo seguimos viendo a los casi 40 años (Bolu), en este episodio hablamos de Jujutsu Kaisen, Kaiju No.8, Dan Da Dan y el remake de Ranma 1/2, además de Caballeros del Zodíaco, Dragon Ball Z, Sailor Moon, Akira y Evangelion, el doblaje latino del anime y su valor para nosotros.

Mikey & Jeremy watch S5E21 of Smallville, "Oracle". They discuss kyryptonian Robots, how to spell ZOD, and lopsided cake.

On this week's podcast we review the Smallville Season 6 premiere: Zod. GET YOUR 30 DAY FREE TRIAL OF AMAZON PRIME HERE

Host Anthony Desiato and guest Tyler Patrick (Krypton Report) dig into SMALLVILLE's television adaptations of the major villains from the Superman mythology: recurring/season-long antagonists Brainiac, Zod, Bizarro, Doomsday, and Darkseid. They discuss how the series brought each villain to life in terms of characterization, backstory, comic book fidelity, and role in Clark's larger journey.PLUS! For even more SMALLVILLE villains talk — including Mr. Mxyzptlk, Toyman, Metallo, Silver Banshee, Maxima, and Ultraman — be sure to tune in for a special BONUS episode on 10/18/24!"A Superboy Fan Journey" Chapter XXII.Support the show and receive exclusive podcast content at Patreon.com/AnthonyDesiato, including the spinoff podcasts BEYOND METROPOLIS and DIGGING FOR JUSTICE!Visit BCW Supplies and use promo code FSP to save 10% on your next order of comics supplies. FACEBOOK GROUP: Digging for Kryptonite: A Superman Fan GroupFACEBOOK PAGE: @diggingforkryptonitepodINSTAGRAM: @diggingforkryptonitepodTWITTER: @diggingforkrpodEMAIL: flatsquirrelproductions@gmail.comWEBSITE: FlatSquirrelProductions.com Digging for Kryptonite is a Flat Squirrel Production. Key art by Isaiah Simmons (2020-2024 version by Gregg Schigiel). Theme music by Basic Printer.Mentioned in this episode:Hang On To Your Shorts Film FestivalAlways Hold On To SmallvilleFat Moose ComicsAw Yeah Comics

Jurandir Filho, Thiago Siqueira e Rogério Montanare recomendam 30 filmes e séries do gênero suspense policial, também conhecido como thriller. O tema é muito popular no cinema e streaming, focando em narrativas envolventes e cheias de tensão, nas quais o mistério e o perigo caminham lado a lado. Nesses enredos, a trama geralmente gira em torno de investigações complexas conduzidas por detetives que buscam capturar assassinos, muitas vezes serial killers. O ponto central dessas histórias é a investigação criminal, onde o detetive - seja ele um policial experiente, um investigador particular ou até mesmo um personagem fora do círculo tradicional da justiça - tenta desvendar os segredos por trás dos crimes brutais. A narrativa geralmente acompanha a busca pelo assassino, muitas vezes trazendo dilemas morais, enigmas psicológicos e a pressão constante do tempo. Os detetives precisam, com frequência, enfrentar seus próprios demônios enquanto lutam contra a inteligência e a crueldade do assassino. O sucesso do suspense policial está na construção da tensão, no mistério que se desenrola aos poucos, e nos momentos de revelação surpreendente, onde as pistas se encaixam de forma inesperada. O espectador é levado a um verdadeiro quebra-cabeça, onde cada peça descoberta pode mudar completamente o curso da investigação. Esse é mais um podcast da nossa série Listão! = 00:00 Abertura 02:58 Começo da lista! 09:09 Os Suspeitos (2013) 12:33 Garota Exemplar (Disney+) 15:57 O Silêncio dos Inocentes (Prime) 19:35 Se7en - Os Sete Crimes Capitais (Max) 22:37 True Detective (Max) 25:39 Sobre Meninos e Lobos (Max) 28:23 Os Homens que Não Amavam as Mulheres (Max) 31:38 Terra Selvagem (Netflix) 35:28 Jogos Mortais (Netflix) 39:11 Mindhunter (Netflix) 42:04 Sicario: Terra de Ninguém (Netflix) 46:13 Fargo (Prime) 48:46 Operação França (Disney+) 52:24 Zodíaco (Max) 55:29 Dexter (Netflix) 01:00:33 O Caçador 01:03:48 Amnésia 01:07:12 Instinto Selvagem 01:13:00 Um Corpo que Cai (Telecine) 01:16:32 The Killing (Disney+) 01:18:13 Fogo Contra Fogo (Disney+) 01:22:38 Los Angeles - Cidade Proibida (Disney+) 01:24:52 Os Suspeitos (1995) 01:28:10 A Cela 01:31:49 Mare of Easttown (Max) 01:33:36 O Segredo dos Seus Olhos (Disney+) 01:36:01 O Lobo Atrás da Porta (Disney+) 01:39:18 Arquivo X - Eu Quero Acreditar (Disney+) 01:44:29 A Escuta (Max) 01:48:10 Twin Peaks

A protagonista é Clarice Starling, mas é ela também a grande personagem de Thomas Harris em O Silêncio dos Inocentes? Por aqui, discutimos como nos simpatizamos com Clarice mas não torcemos por ela, simplesmente porque é difícil ter tanto carisma quando se é mentorado por Hannibal Lecter. Quer participar dessa discussão? Então vem ouvir! Comentado no episódio O Silêncio dos Inocentes, romance de Thomas Harris Dragão Vermelho, romance de Thomas Harris O Silêncio dos Inocentes (1991 ‧ Terror/Crime ‧ 1h 58m) Se7en - Os Sete Crimes Capitais (1995 ‧ Crime/Terror ‧ 2h 7m) Zodíaco (2007 ‧ Thriller/Crime ‧ 2h 40m) O Silêncio dos Inocentes e a vitória do antagonista, artigo por Andreia D'Oliveira (02/09/2016) Vivos (1993 ‧ Aventura/Ação ‧ 2 horas) A Sociedade da Neve (2023 ‧ Aventura/Thriller ‧ 2h 24m) O Personagem do Romance, por Antônio Cândido Livros em Cartaz 004 – Quem não está perdida? (A Filha Perdida) Tiger King: Murder, Mayhem and Madness (2020 ‧ Documentário ‧ 2 temporadas) Chimp Crazy (2024 ‧ Documentário ‧ 1 temporada) Último Tango em Paris (1972 ‧ Erótica/Romance ‧ 2h 9m), dirigido por Bernardo Bertolucci Taxi Driver – Motorista de Táxi (1976 ‧ Crime/Noir ‧ 1h 54m) Revelação (2020 ‧ Documentário/LGBT ‧ 1h 40m), dirigido por Sam Feder Cabo do Medo (1991 ‧ Crime/Terror ‧ 2h 8m), dirigido por Martin Scorsese

Erik Hanchett, senior developer advocate at AWS Amplify, explores the world of Fullstack TypeScript. He discusses the significance of end-to-end type safety, the tools to achieve it, and delves into the benefits and functionalities of AWS Amplify. Links https://www.programwitherik.com https://x.com/erikch https://www.youtube.com/c/programwitherik https://www.linkedin.com/in/erikhanchett https://trpc.io https://orval.dev https://docs.amplify.aws We want to hear from you! How did you find us? Did you see us on Twitter? In a newsletter? Or maybe we were recommended by a friend? Let us know by sending an email to our producer, Emily, at emily.kochanekketner@logrocket.com (mailto:emily.kochanekketner@logrocket.com), or tweet at us at PodRocketPod (https://twitter.com/PodRocketpod). Follow us. Get free stickers. Follow us on Apple Podcasts, fill out this form (https://podrocket.logrocket.com/get-podrocket-stickers), and we'll send you free PodRocket stickers! What does LogRocket do? LogRocket provides AI-first session replay and analytics that surfaces the UX and technical issues impacting user experiences. Start understand where your users are struggling by trying it for free at [LogRocket.com]. Try LogRocket for free today.(https://logrocket.com/signup/?pdr) Special Guest: Erik Hanchett.

Your heroes kneel before Zod to discuss Superman II! In this episode we share what we liked, discuss at length what doesn't work, and explain The Donner Cut.  Superman: The Movie is directed by Richard Lester; written by Mario Puzo, David Newman, and Leslie Newman; and stars and stars Christopher Reeve, Margot Kidder, Gene Hackman, and Terence Stamp.Follow ComiClub on Instagram @ComiClubPodcastComiClub is hosted by Blaine McGaffigan and Adam Cook.

On this episode of The AIE Podcast... We say farewell to a good friend So, play any games recently? Congradudolences are in order for Corley The RISING is imminent And, we have an interview with Dr Gameology! All that and more coming up right now... Podcast Audio Raw Video http://youtu.be/69D8qJllCsU Open Welcome to episode #426 of the podcast celebrating you, the Alea Iacta Est gaming community, the die has been podcast. This is Mkallah: To my left is Mewkow: - (catch phrase here). And to my right is Tetsemi: (catch phrase here). This week we are joined by special guest Dr. Gameology ( Dr. Daniel Kaufmann) who is here to talk to us about his new book, The Gamer's Journey. Welcome! Just a note before we get too far into the show. As you may or may not know, AIE lost one of our greats on August 16th. Our dear friend, guildmate, fellow member of FERT, creator of Overly Dramatic news, and podcast co-host, James “Acuzod” Jefferies lost his battle with cancer. He was loved by so many and made all of us who knew him just a little better. He is survived by his amazing wife Jodi, their kids, Jennifer, Kimberly, and Sami, and grandson Nathan. Zod will be remembered for his humor and his kindness, and his voice will live in this podcast, as it is his voice you hear on all of the bumpers! Oh, and if you see Acuzod online, it is his grandson, Nathan, playing on his Papa's account. Ok, we'll be digging into this week's news shortly, but first, let's talk to our esteemed guest, Dr Gamelolgy, himself! GAME NEWS Mkallah- We had you back on the show in episode 389 and you talked about your psych research as it relates to gaming and the gaming persona podcast. Now, it's all come together in your new book, The Gamer's Journey- tell us about the journey and how you got there. Mewkow- Did you find gaming an escape while working on the book, or did it evolve into being in research mode? Tetsemi- What was your biggest surprise while working on The Gamer's Journey? Mkallah (if needed)- And, the big one, where can everyone find your book? Dr. Gameology ( Dr. Daniel Kaufmann ) - https://drgameology.com/ Youtube: https://www.youtube.com/@DrGameology The Gamer's Journey is a book that explores all the stages of the Hero's Journey, but using only video games. The sources of knowledge across the book include mythology, psychology, philosophy, anthropology, and many others. Almost 200 games were used in the analysis over the 19 chapters. Barnes & Noble: https://www.barnesandnoble.com/w/the-gamers-journey-daniel-kaufman-phd/1145608008;jsessionid=72D67ABDB12601FCBA38CEB1CA541A19.prodny_store01-atgap15?ean=9781955406239 Amazon: https://www.amazon.com/Gamers-Journey-Daniel-Kaufman-PhD/dp/1955406235 AIE News Community Mandatory Fun Nights Where the fun is mandatory but the attendance is not. Sunday - Destiny 2 8:30 pm Eastern Monday - GW2 9:30 pm Eastern Monday - STO 10:00 pm Eastern Tuesday - SWTOR 9:00 pm Eastern Wednesday - HFO Mythic+ Mayhem (WoW) 8:00 pm Eastern Thursday- Board Game Night (1st and 3rd Thursdays) 7:00 pm Eastern/6:00 pm Central Friday - ESO 9:00 pm Eastern Saturday - LotRO 8:30 pm Eastern Saturday - FFXIV (Maps) 9:30 pm Eastern Saturday - WoW Classic Hardcore 9:30 pm Eastern Saturday - Noob Raid (WoW) 11:00 pm Eastern Streaming and Guild Podcast News We have a ton of AIE member podcasts! Want to know where to find them? Look no further than here- New Overlords Podcast (Max and Sema) https://www.newoverlords.com Working Class Nerds (Marcus and Nick) - NSFL https://workingclassnerdscom.wordpress.com Boards and Swords (Chris and Philip) https://boardsandswords.com/blog?category=Boards%20%26%20Swords Dr. Gameology ( Dr. Daniel Kaufmann ) https://drgameology.com/ STO - Fleet Action Report (Grebog and Nikodas) https://www.youtube.com/@fleetactionreport A Podcast Reborn: A FFXIV Community Podcast (Brandon aka Old M...

Jace and Rocky talk about the DC Comics titles for the week of August 7, 2024. It's not the best week with some titles leaning towards underwhelming, but the Absolute Power event marches on with tons of action. Plus Batman and Catwoman are trying to pull off a heist with huge stakes and things go about as badly as they could. We get the end of the Zod and Beetle titles, and the launch of a new Gotham City Sirens. Join us to hear about these titles and more!

In this episode, James Quick, seasoned JavaScript developer, speaker, and teacher, chats about full stack web development. From single-page applications and static site generators to the latest in server components and hybrid rendering, he covers the evolution of modern web development practices and gives personal insights on navigating these new technologies. Links https://www.jamesqquick.com https://www.youtube.com/c/jamesqquick https://www.tiktok.com/@jamesqquick https://www.learnbuildteach.com https://x.com/jamesqquick We want to hear from you! How did you find us? Did you see us on Twitter? In a newsletter? Or maybe we were recommended by a friend? Let us know by sending an email to our producer, Emily, at emily.kochanekketner@logrocket.com (mailto:emily.kochanekketner@logrocket.com), or tweet at us at PodRocketPod (https://twitter.com/PodRocketpod). Follow us. Get free stickers. Follow us on Apple Podcasts, fill out this form (https://podrocket.logrocket.com/get-podrocket-stickers), and we'll send you free PodRocket stickers! What does LogRocket do? LogRocket provides AI-first session replay and analytics that surfaces the UX and technical issues impacting user experiences. Start understand where your users are struggling by trying it for free at [LogRocket.com]. Try LogRocket for free today.(https://logrocket.com/signup/?pdr) Special Guest: James Q. Quick.

Uma das cenas de filme mais marcantes da minha vida, do tipo pesadelo e trauma, é de um filme que vi com 5 anos: Superman, o Filme, sim, aquele com o Christopher Reeve, o melhor Superman. É logo no início, ainda em Krypton, quando o Pai do Super, o Marlon Brando, condena três criminosos a serem banidos para todo sempre na Zona Fantasma.A parte dessa cena que me deixou chocado é na hora que os três vilões são jogados na tal zona fantasma. Eles ficam em um círculo com uns bambolês em volta, a grande redoma que eles estavam abre, eles ficam em um facho de luz que vai até o espaço. Aí vem um… espelho espacial? Um quadrado brilhante, que passa por cima deles, que ficam presos ali naquele espaço apertado, as mãos no vidro, voando pelo espaço gritando de desespero.Aaaaaah, você me paga, Jorel!!!Como a gente vai ver no filme seguinte, o general Zod não era nenhum santo, eu não tava lá para ver, mas deve ter merecido. Mas aquele desespero de ficar ali preso naquele espelhinho sideral me marcou muito e é essa cena que me vem à cabeça quando em penso no tema dessa semana do Boa Noite Internet: cultura do cancelamento.Eu defendo já tem tempo que a internet deu voz a pessoas que nunca tiveram plataforma antes, gerando o que eu chamo de “eu não tô maluco sozinho”. As conversas online fizeram com que a gente conseguisse ver que um monte de coisa não era coincidência, “só um caso isolado” ou invenção da nossa cabeça. É por isso que eu digo que apesar de a gente adorar falar mal da internet, ela ainda tem um saldo positivo para o mundo. Em 10 anos a sociedade mudou radicalmente, por conta das conversas que aconteceram online.Eu defendo a internet e as xoxal redes como ferramenta de mudança. Só que, ao mesmo tempo… Eu sempre fiquei muito incomodado com a cultura do cancelamento, que é quando alguém faz alguma coisa considerada errada e então começa o que eu costumo chamar de “Tribunal da Internet”, onde o veredito é decidido e executado ali na hora, que nem em Krypton, só que no feed de alguma rede social, de preferência o Twitter. O que me incomoda nessa dinâmica é o sentimento de que a pessoa é culpada até prova em contrário, de que se ela foi acusada, coisa boa não fez. E que se você ousar ponderar, ei, peraí, não é bem assim… plau! Você também é culpado.E nessa eu vi muita gente que eu gosto ser cancelada sumariamente, o que foi um dos motivos de eu ter largado o Twitter já tem aí quase 2 anos.Mas… o tempo passa. A teoria vira prática e a gente descobre que as coisas não são tão simples assim. Daí, enquanto a gente estava montando a pauta dessa temporada do Boa Noite Internet, o tema “cultura do cancelamento” estava lá na lista e me fez lembrar que um cara que eu conheço já tem aí mais de 10 anos estava para lançar um livro sobre o assunto. Eu mandei um Zap pra saber como estava o projeto e descobri que ele ia lançar o livro na semana seguinte.Eu estou falando do Pedro Tourinho, que é comunicólogo e especialista em entretenimento e mídia. Ele já tinha escrito o livro “Eu, eu mesmo e minha selfie. Como cuidar da sua imagem no século XXI”. Foi meu chefe quando eu estava de saída do BuzzFeed ali no auge da loucura de 2020. Desde o início de 2023 o Pedro atua como Secretário de Cultura e Turismo de Salvador e agora acabou de lançar o livro “Ensaio sobre o cancelamento”.A gente correu, agendou o estúdio e agora você escuta esse papo sobre a origem da cultura do cancelamento, vê que de novidade ela não tem nada — a humanidade já cancela tem tempo — mas também o que ela traz de diferente agora e, principalmente, a parte que me fez querer falar desse assunto em 2024: entender o que mudou, o que a gente aprendeu nessa última década e, pra fechar, um guia prático pra quando for você a pessoa cancelada da vez. Porque um dia todos serão cancelados por 15 minutos. Inclusive eu, por conta desse programa.Sei lá, vamos ver. Mas eu fiquei muito feliz com o papo, que me fez ver toda essa dinâmica de um jeito diferente, menos violento.Links do episódio e transcrição em https://boanoiteinternet.com.br/ This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit boanoiteinternet.com.br/subscribe

Jace and Rocky chat about the DC Comic titles for the week of June 4, 2024. There is a huge fundamental change for Billy Batson and Shazam, while the Birds of Prey continue to hop around from one plane of existence to the next having no idea where they will end up after each jump. The My Adventures With Superman title is the equivalent of the Christmas Episode for fans of the show and should not be missed, while Zod confronts a surprise character who may be friend or foe. Finally we get the end of the Batman/Failsafe/Zur En Arrh story and the consequences for the Bat-Family remain to be seen.

This week Zach is joined by Anthony Polinick from The Grund to discuss the one hundred ninety fourth episode of Smallville, “Sacrifice." They talk the end of Checkmate, how this should've been a bottle episode about Chloe and Tess being trapped inside Watchtower, the House of Zod symbol, and the tragic death of Faora and her unborn child. Don't worry, there have been no security upgrades to the latest Always Hold On To Smallville!Check out Anthony on The Grund!EPISODE ROUNDUPZach's Grade: B-Leah's Grade: C+IMDB Grade: 8.3Superman Homepage Grade: 3.5/5 Bechdel Test: PASSSERIES TALLY BOARD...From Metropolis: 17Amazing Technicolor Kryptonite: 17Amnesia Count: 73Blue Shirt/Red Jacket: 89Chloe's Unseen Connections: 29Clark Loses His Powers: 15Episode Title Said In Episode: 80Hospital Visits: 149In Media Res: 8Injection Count: 57Kent Truck Accidents: 10KOs to Keep Clark's Secret: 59KOs to Keep Oliver's Secret: 4Lana Kills: 7Let's Do The Time Warp Again: 9Lois Arm Punches: 10Lois' Costume Closet: 17Main Character Deaths: 25Mind Control Count: 26Movie Plot As An Episode: 21Not The Last Son Of Krypton: 46Possession Count: 30Product Placement Pete: 32Queen Airways: 8Shirtless Oliver: 12Shower Count: 25Shut It Down: 10Shut That Laptop: 34Smallville High School Faculty Deaths: 5Smallville High School Student Deaths: 17Under The Influence: 45Wakes Up Tied Up: 11Weddings: 4"You Weren't Yourself": 37Always Hold On To Smallville is brought you to by listeners like you. Special thanks to these Meteor Freaks on Patreon who's generous contributions help produce the podcast!Chris Fuchs / @crfuchs7Kevonte Chilous / @chill_usJoey Dienberg / @JoeyD94_13DJ Doena / @DjDoenaIsaiah GoodridgeCory MooreNathan RothacherAtif SheikhThomas NavenJohn CurcioAndrew Parker / @parkerstpaulMadameRougeMarc-ids FoppenPatricia Carrillo / @MsCarrillo92Tim MillerMichael HartfordJim CrawfordKasey Vach / @ThePandaSupremeMegan RichRouie HumphreyAlex HamiltonMatt DouglasDaniel CurielBish Bash BoshJan RollinsTrevis HullDavid ForshawMartin RyanNathan MacKenzie / @maccamackenzieSteve Rogers / @SteveJRogersJrMollie FicarellaJames Lee / @Jae_El_52Jo Michael / @jweissbrod86Jason Davis / @superjay_92Patrick BravoJacob StevenartDana BiusTae Tae / @doomsday994Meryl Smith / @MelXtreme84Daryn Kirscht / @darynkirscht16Dylan DiAntonioNick Ryan Magdoza / @nickryanEddie Bissell / @Kal_Ed11Jim ThomasClunk Kant / @clunkKantNicholas FanslerJohn LongRuth Anne CrewsTravis Kill / @tjkill81Mike ThomasNicholas CosoJarrett GibbsAnthony Anderson / @NigandNogJasmine Magele / @Jas mindaMT_NZKeith FaulsRob O'Connor / @TheGothamiteJames Hart / @jaohartsAnthony DesiatoCrystal CrossJake C.John SweitzerKirin KumarPATREON: patreon.com/alwaysmallvilleTWITTER: twitter.com/alwaysmallvilleFACEBOOK: facebook.com/alwaysmallvilleEMAIL: alwaysmallville@gmail.com

Jurandir Filho, Edu Aurrai, Felipe Mesquita e Bruno Carvalho batem um papo sobre "Dragon Ball", a obra máxima de Akira Toriyama. O famoso mangaká faleceu em 2024 e deixou um grande legado! Muitas gerações cresceram assistindo e lendo suas obras. "Dragon Ball", uma das mais icônicas séries de anime já produzidas, desempenhou um papel significativo na história da televisão brasileira. Desde sua estreia nas telas nacionais, o anime cativou não apenas crianças e adolescentes, mas também adultos, tornando-se uma parte essencial da cultura pop do país. Ao lado de "Os Cavaleiros do Zodíaco", o anime introduziu muitos brasileiros ao mundo do anime e mangá. Antes deles, a maioria das pessoas no Brasil estava mais familiarizada com desenhos animados ocidentais. No entanto, a chegada de Goku e seus amigos trouxe uma nova dimensão à programação infantil e juvenil, mostrando histórias mais complexas e emocionantes, repletas de aventura, amizade e valores morais. Esse é mais um episódio da série Na TV!! || PATROCINADOR DO PODCAST- ⁠IMERSÃO PYTHON DA ALURA⁠ | Faça aulas DE GRAÇA! ⁠SE INSCREVE AQUI!⁠ || LINKS COMENTADOS NO PROGRAMA- [DICA] Compre o console R36S!- [IMGS] Coleções de Dragon Ball do Felipe | Foto o nome! - [VÍDEO] Todas as aberturas de Dragon Ball

This week Zach is joined by Matt Tuex from Always Hold On To DC's Legends Of Tomorrow and Rob O'Connor from the All Star Superfan Podcast to discuss theone hundred ninetieth episode of Smallville, “Escape." They talk the Lois/Clark/Chloe/Oliver love square, Tess and Zod's out-of-place but strangely compelling subplot, theme park rides, and if the Silver Banshee is Irish, Scottish...or both! Escape into the latest Always Hold On To Smallville!Check out Matt's work including Lois & Clark'd: The New Podcasts of Superman at The Daily Knockoff.And his current podcast Always Hold On To DC's Legends Of Tomorrow.Check out the Rob on the All Star Superfan Podcast!EPISODE ROUNDUPZach's Grade: B+Matt's Grade: B+Rob's Grade: BIMDB Grade: 7.5Superman Homepage Grade: 2.5/5 Bechdel Test: PASSSERIES TALLY BOARD...From Metropolis: 17Amazing Technicolor Kryptonite: 16Amnesia Count: 73Blue Shirt/Red Jacket: 89Chloe's Unseen Connections: 29Clark Loses His Powers: 15Episode Title Said In Episode: 77Hospital Visits: 147In Media Res: 7Injection Count: 54Kent Truck Accidents: 10KOs to Keep Clark's Secret: 57KOs to Keep Oliver's Secret: 3Lana Kills: 7Let's Do The Time Warp Again: 9Lois Arm Punches: 10Lois' Costume Closet: 16Main Character Deaths: 24Mind Control Count: 25Movie Plot As An Episode: 21Not The Last Son Of Krypton: 46Possession Count: 30Product Placement Pete: 32Queen Airways: 8Shirtless Oliver: 11Shower Count: 25Shut It Down: 10Shut That Laptop: 34Smallville High School Faculty Deaths: 5Smallville High School Student Deaths: 17Under The Influence: 44Wakes Up Tied Up: 11Weddings: 4"You Weren't Yourself": 37Always Hold On To Smallville is brought you to by listeners like you. Special thanks to these Meteor Freaks on Patreon who's generous contributions help produce the podcast!Chris Fuchs / @crfuchs7Kevonte Chilous / @chill_usJoey Dienberg / @JoeyD94_13DJ Doena / @DjDoenaIsaiah GoodridgeCory MooreNathan RothacherAtif SheikhThomas NavenJohn CurcioAndrew Parker / @parkerstpaulMadameRougeMarc-ids FoppenPatricia Carrillo / @MsCarrillo92Tim MillerMichael HartfordJim CrawfordKasey Vach / @ThePandaSupremeMegan RichRouie HumphreyAlex HamiltonMatt DouglasDaniel CurielBish Bash BoshJan RollinsTrevis HullDavid ForshawMartin RyanNathan MacKenzie / @maccamackenzieSteve Rogers / @SteveJRogersJrMollie FicarellaJames Lee / @Jae_El_52Jo Michael / @jweissbrod86Jason Davis / @superjay_92Patrick BravoJacob StevenartDana BiusTae Tae / @doomsday994Meryl Smith / @MelXtreme84Daryn Kirscht / @darynkirscht16Dylan DiAntonioNick Ryan Magdoza / @nickryanEddie Bissell / @Kal_Ed11Jim ThomasClunk Kant / @clunkKantNicholas FanslerJohn LongRuth Anne CrewsTravis Kill / @tjkill81Mike ThomasNicholas CosoJarrett GibbsAnthony Anderson / @NigandNogJasmine Magele / @Jas mindaMT_NZKeith FaulsRob O'Connor / @TheGothamiteJames Hart / @jaohartsAnthony DesiatoCrystal CrossJake C.John SweitzerKirin KumarPATREON: patreon.com/alwaysmallvilleTWITTER: twitter.com/alwaysmallvilleFACEBOOK: facebook.com/alwaysmallvilleEMAIL: alwaysmallville@gmail.com

Legend has it that when the store used to be a Zod's a tragic double murder-suicide unfolded in the upstairs stockroom, involving a couple who were employees of Zody's. Allegedly, the boyfriend discovered that his girlfriend cheated on him with another male coworker,, leading to a violent outburst where he used a box cutter to fatally wound them both before taking his own life by slashing his wrists and carotid artery. It's said that the spirits of all three individuals now haunt the premises. As reports of strange phenomena continued to mount, even after the store turned into the big K-Mart I know it is as today… K-Mart #7625… Kmart headquarters in Michigan received word of the unsettling events, and were spooked… prompting them to engage paranormal investigators to delve into the matter. While the investigation was discreet, its findings revealed the presence of four distinct spirits inhabiting the building, with the fourth spirit's origins remaining a mystery.Social Media:Instagram: https://www.instagram.com/thescarecast/?hl=enTikTok: https://www.tiktok.com/@thescarecast?lang=enGo Subscribe to my YouTube channel: https://www.youtube.com/@scarecastBuy Merch: https://thescarecast.com/store/Contact me through email: mike@thescarecast.com for any story requests or inquiries, concerns, or advertising inquiries.Our Sponsors:* Check out Factor 75 and use my code scarecast50 for a great deal: https://www.factor75.com/Support this podcast at — https://redcircle.com/the-scarecast/exclusive-contentAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy