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The Twenty Minute VC: Venture Capital | Startup Funding | The Pitch
Elena Verna is the Head of Growth at Lovable, one of the fastest growing companies in the world having hit $400M in ARR in just 18 months. Prior to Lovable, Elena was Head of Growth at both Dropbox and Miro. AGENDA: 00:00 – Why "Growth Is Now a Trust Problem" (Not a Marketing Problem) 06:10 – Is SEO Dying Because of AI Search? 07:00 – Did Lovable's Growth Come From the Founder's Personal Brand? 08:30 – Why Every Founder Should Push Employees to Be Marketers? 13:10 – Why Every Employee at Lovable Ships Code (Even Marketing) 21:20 – Why Paid Marketing in Year One Is a "Death Trap" 31:50 – Why Annual Subscriptions Are the Wrong Monetization Model for AI 37:00 – If Elena Had an Unlimited Marketing Budget, What Would She Do? 48:00 – How Lovable Does Product Launches
Motorcycles aren't meant to back up. If they were, they'd all come with reverse. Sometimes, turning around requires a little creativity—especially on dead-end trails, in parking lots, on hills, or even in your garage. In this episode of RIDER SKILLS, we have Clinton Smout walking us through a number of turnaround methods. Some you might expect, while others may raise your eyebrows—but all of them can be useful tools in your rider skills toolbox.
Tout part d'un déjeuner avec Pablo Servigne — chercheur sur les effondrements, que j'avais reçu quelques semaines plus tôt sur VLAN. Une conversation qui dérive vers la géopolitique, les polycrises, le contexte général. J'utilise le mot "chaos" comme je le fais tout le temps, dans mes newsletters, mes conférences, mes conversations quotidiennes. Et Pablo me regarde avec un sourire tranquille et me dit : "Mais tu parles du chaos comme si c'était un problème. La vie, elle danse toujours au bord du chaos." Quelques secondes de silence. Et la réalisation que j'utilisais peut-être ce mot depuis des années avec une erreur fondamentale dedans. Dans cet épisode, je vous parle de ce que j'ai découvert en creusant cette phrase : l'étymologie grecque du chaos, les travaux de Stéphane Gastello sur les systèmes dynamiques, la théorie du chaos des carrières de Robert Pryor et Jim Bright, Roy Bird sur la vie comme phénomène chaotique, Michael Conrad sur l'adaptabilité, Donna Brother sur l'anxiété cartésienne, Hartmut Rosa sur l'accélération sociale et la résonance manquée, Byung-Chul Han sur la transparence, Matthew Welsh sur la responsabilité adaptative, Viktor Frankl sur le sens — et Cécile Wendling, que je reçois cette semaine sur VLAN, qui m'a rappelé que le mot "crise" lui-même est une construction sociale qui génère ses propres angles morts. J'ai questionné tout ce que je pensais savoir sur notre rapport collectif à l'imprévisible : pourquoi notre cerveau traite l'incertitude comme une menace mortelle, ce qui distingue vraiment les systèmes qui s'effondrent de ceux qui se transforment, et ce que la recherche dit concrètement sur comment naviguer dans ce qui, par nature, ne sera jamais stable. Ce n'est pas du développement personnel. C'est plus fondamental que ça. CITATIONS MARQUANTES 1. "La vie, elle danse toujours au bord du chaos."— Pablo Servigne (rapporté par Grégory, 01:48) 2. "Le chaos, ce n'est pas l'opposé de l'ordre. C'est le processus par lequel l'ordre émerge, de façon non planifiée."— Grégory Pouy (08:49) 3. "On ne souffre pas du chaos, on souffre du fait que le chaos n'est pas ce que nous pensions que le monde devrait être."— Grégory Pouy (13:09) 4. "La fourmilière n'est pas construite malgré l'absence de plan central — elle est construite précisément grâce à cette absence."— Grégory Pouy (09:37) 5. "Les individus, les collectifs qui traverseront le mieux ces turbulences, ce ne seront pas ceux qui auront eu les meilleurs plans. Ce seront ceux qui auront développé la capacité à naviguer dans l'incertitude."— Grégory Pouy (49:19) BIG IDEAS 1. Le chaos n'est pas le désordre — c'est la condition du vivant [05:20 – 08:49]KHAOS en grec = vide primordial, espace de possibilités pures. Au sens scientifique (Gastello), le chaos désigne des dynamiques précises qui génèrent des structures stables — les fractales, le rythme cardiaque sain, la croissance des arbres. Le chaos n'est pas l'opposé de l'ordre : c'est le processus par lequel l'ordre émerge.Pourquoi c'est important :Toute la façon dont on traite l'imprévisible est fondée sur une erreur de définition. On combat ce qui est, en réalité, la condition de base de la vie. 2. Notre cerveau est biologiquement câblé pour traiter l'incertitude comme une menace mortelle [10:36 – 13:09]L'amygdale ne distingue pas un lion d'une incertitude professionnelle. L'anxiété cartésienne (Donna Brother) ajoute une couche culturelle : depuis Descartes, la certitude est l'idéal. On souffre donc deux fois — de l'incertitude réelle, et de la croyance qu'elle ne devrait pas exister.Pourquoi c'est important :Comprendre l'origine biologique et culturelle de notre rapport au chaos permet d'arrêter de se battre contre soi-même, avant même d'agir sur le monde. 3. L'orée du chaos — ni trop stable, ni effondré — c'est là que tout se passe [18:36 – 20:20]Les chercheurs en systèmes complexes ont identifié une zone spécifique d'instabilité intermédiaire ("edge of chaos") où l'innovation émerge, où la créativité devient possible, où les transformations profondes ont lieu. Ni dans la stabilité confortable, ni dans l'effondrement total.Pourquoi c'est important :Cela change radicalement la lecture des périodes de turbulence : ce ne sont pas des anomalies à corriger, ce sont des espaces de transformation réelle. 4. Effondrement ≠ chaos : la distinction que personne ne fait [29:00 – 30:50]Cécile Wendling : tous les systèmes chaotiques ne se réorganisent pas en quelque chose de mieux. Certains s'effondrent. Pablo Servigne : certains scénarios ne produisent pas quelque chose de préférable à ce qui existait. Romantiser le chaos serait une erreur aussi grave que d'en avoir peur.Pourquoi c'est important :Nuance indispensable pour ne pas tomber dans un optimisme naïf ou un relativisme commode face aux vraies crises. 5. Flexibilité > solidité — et la résilience a un coût réel [30:50 – 35:11]Ce qui protège les systèmes face au chaos, ce n'est pas la rigidité mais la capacité à se laisser traverser et réorganiser. Et la résilience — souvent présentée comme un idéal — a un coût corporel réel (charge allostatique) qu'on invisibilise systématiquement.Pourquoi c'est important :Arrêter de vendre la résilience sans mentionner ce qu'elle coûte. Reconnaître que "tenir" n'est pas la même chose qu'"être indemne". 6. L'optimalisme et la joie rebelle comme posture de navigation [43:55 – 45:35]Ni déni ("la tech va tout résoudre"), ni résignation ("on n'y peut rien"). L'optimalisme = regarder lucidement la réalité, y compris ses parties sombres, et agir quand même avec engagement et créativité. La joie rebelle = une discipline, pas une humeur. Un choix, pas un confort.Pourquoi c'est important :C'est la troisième voie que VLAN essaie de tenir depuis le début. Elle s'ancre ici dans une littérature de recherche solide, pas dans un vœu pieux. QUESTIONS POSÉES OU POSABLES 1. Tu utilises le mot "chaos" en permanence — mais qu'est-ce que tu voulais dire par là, avant ce déjeuner avec Pablo ?2. Cette phrase de Pablo — "la vie danse au bord du chaos" — elle t'a arrêté net. Qu'est-ce qui s'est passé dans ta tête à ce moment précis ?3. Comment expliquer que le sens commun du mot "chaos" soit aussi éloigné de son sens scientifique ou étymologique ?4. Le cerveau qui traite l'incertitude comme une menace : est-ce qu'on peut vraiment reconditionner ça, ou est-ce qu'on apprend juste à composer avec ?5. Tu cites Pryor et Bright sur les trajectoires non linéaires. Est-ce que ça voulait dire que planifier est inutile, ou juste qu'il faut changer de rapport au plan ?6. Toi tu as quitté le marketing digital sans plan. C'était du courage, de la naïveté, ou les deux ?7. Où est-ce que tu traces la ligne entre accepter le chaos et se résigner ?8. La résilience a un coût réel — charge allostatique, usure du système nerveux. Comment on en tient compte sans décourager les gens qui "tiennent" ?9. L'optimalisme que tu décris, c'est difficile à tenir dans les périodes de vraie turbulence. Qu'est-ce qui t'y aide concrètement ?10. La joie rebelle — c'est un concept que tu as créé. C'est quoi la différence avec ce qu'on appellerait simplement de la "résilience positive" ? RÉFÉRENCES CITÉES Personnes Pablo ServigneChercheur sur les effondrements ; déjeuner déclencheur ; "la vie danse au bord du chaos" — 00:55Stéphane GastelloPsychologue américain ; théorie des systèmes dynamiques appliquée aux humains — 06:13Robert Pryor & Jim BrightChercheurs australiens ; théorie du chaos des carrières ; trajectoires non linéaires — 13:09Roy BirdChercheur britannique ; livre sur chaos, évolution et pensée ; "la vie est un phénomène chaotique" — 16:38Michael ConradChercheur américain ; article des années 80 : What is the use of chaos? ; chaos = adaptabilité — 17:38Donna BrotherPsychanalyste américaine ; concept d'anxiété cartésienne — 12:12Hartmut RosaSociologue allemand ; accélération sociale, stabilisation dynamique, résonance manquée — 23:39Byung-Chul HanPhilosophe coréen-allemand ; société de la transparence — 26:23Cécile WendlingProspectiviste, invitée de l'épisode suivant de VLAN ; effondrement ≠ chaos ; le mot "crise" comme construction sociale — 27:14Matthew WelshChercheur britannique ; gestion sociopolitique de l'incertitude ; responsabilité adaptative — 42:13Viktor FranklPsychiatre autrichien, survivant des camps ; logothérapie ; le sens comme ancre dans le chaos — 38:22Mathieu DardaillonAmi de Grégory ; bootcamp + boussole anti-chaos — 39:19 Concepts & œuvres What is the use of chaos?Michael Conrad — 17:38Théorie du chaos des carrièresPryor & Bright — 13:09Anxiété cartésienneDonna Brother — 12:12Accélération sociale / stabilisation dynamiqueHartmut Rosa — 24:25Résonance / résonance manquéeHartmut Rosa — 40:15Société de la transparenceByung-Chul Han — 26:23Responsabilité adaptativeMatthew Welsh — 43:02Optimalisme / Joie rebelleGrégory Pouy — 43:55 / 44:42 TIMESTAMPS CLÉS 00:00 — Introduction VLANJingle signature + annonce de l'épisode solo sur le chaos 00:55 — Le déjeuner avec Pablo ServigneLa phrase qui a tout changé : "la vie danse au bord du chaos" 02:40 — L'ordre absolu = la mortSi l'inverse du chaos est la mort, alors le chaos est la condition du vivant 05:20 — Le sens original du mot "chaos"Étymologie grecque : KHAOS = espace de possibilités pures, pas le désordre 07:04 — Le chaos scientifique : attracteurs, fractales, effet papillonGastello : le chaos génère des structures stables et reconnaissables 09:37 — La fourmilière sans architecteL'auto-organisation comme principe universel du vivant 10:36 — Pourquoi notre cerveau déteste l'incertitudeBiologie de la peur : l'amygdale ne distingue pas un lion d'une incertitude 12:12 — L'anxiété cartésienne (Donna Brother)Souffrir non du chaos, mais de la croyance qu'il ne devrait pas exister 14:11 — La théorie du chaos des carrières (Pryor & Bright)Personne n'arrive là où il pensait aller — et c'est une information, pas un échec 16:38 — Roy Bird : la vie EST un phénomène chaotiqueSans le chaos, ni la pieuvre, ni l'orchidée, ni le cerveau humain 18:36 — L'orée du chaos : la zone où tout se transformeNi trop stable, ni effondré : c'est là qu'émerge l'innovation 21:47 — Mon histoire : quitter le marketing digital sans planUn mini-chaos qui a rendu possible ce que je fais aujourd'hui 22:42 — Notre société simule la certitudeMarchés, plans stratégiques, promesses politiques : on préfère une certitude fausse 24:25 — Hartmut Rosa : courir pour rester à la même placeL'accélération sociale et la résonance manquée 27:14 — Cécile Wendling : le mot "crise" n'est pas neutreConstruction sociale qui crée ses propres angles morts 29:45 — Effondrement ≠ chaos : la distinction crucialePablo Servigne : certains systèmes ne se réorganisent pas en mieux 31:51 — Flexibilité > soliditéCe qui protège n'est pas la rigidité, mais la capacité à se laisser traverser 33:27 — Le bambou vs le chêneRésilience vs robustesse : ce qui compte dans un monde fondamentalement chaotique 34:19 — La résilience a un coût réelCharge allostatique : rebondir ne signifie pas être indemne 37:32 — Pratique : l'incertitude positive (Pryor & Bright)Traiter l'imprévu comme une information, pas comme une menace 38:22 — La curiosité comme boussole + Viktor FranklLe sens résiste au chaos. La question à se poser en turbulence 43:55 — L'optimalisme et la joie rebelleNi déni, ni résignation : la troisième voie 46:24 — Ce qui a vraiment changé après le déjeuner avec PabloReconnaître le réflexe de contrôle sans en être l'esclave 50:17 — Question finale à l'audience + outroFace à votre prochaine turbulence : naviguer ou résister ? Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.
Nvidia anuncia $26.000M para modelos open-weight y lanza Nemotron 3 Super. Cursor negocia una valoración de $60.000M por su editor con IA. Replit levanta $400M y apunta a $1.000M en ARR. Robotaxis de Uber, Nissan y Wayve llegan a Tokio. Y Atlassian despide 1.600 empleados para "invertir en IA"
Ce n'est pas en économisant sur tes Starbucks que tu vas régler tes problèmes financiers ☕En 2019, je me retrouve à 32 ans, diplômée de Sciences Po, avec moins de 5 000 € sur mes comptes et de retour chez mes parents. Mon premier réflexe ? Faire des économies. Arrêter les Starbucks. Revendre des trucs. Optimiser chaque dépense.Résultat ?200 ou 300 € de côté par-ci par-là. 2 400 € par an au mieux. Autant dire : rien qui change une vie. J'ai compris une chose fondamentale : Il y a une limite à ce que tu peux économiser mais il n'y a (quasi) aucune limite à ce que tu peux gagner.Alors au programme de cet épisode :
Dans cet épisode, j'enlève ma casquette de coach et je mets celle de cliente. Parce que je travaille au quotidien avec des freelances, des assistants virtuels, des graphistes, des monteurs, des développeurs... et je vois exactement ce qui donne envie de continuer la collaboration, mais aussi ce qui fait fuir vos clients.Je vous partage les 5 erreurs que j'observe le plus souvent (avec des exemples concrets tirés de mon expérience de coach et de cliente) pour vous aider à rendre votre business véritablement attractif et à attirer des clients qui voudront bosser avec vous sur le long terme.✨Au programme :➡️ Le positionnement qui perd vos clients en 5 seconde➡️ La posture pro qu'on oublie quand on est trop à l'aise (avec une anecdote personnelle dont j'ai un peu honte)➡️ Le piège des tarifs non justifiés➡️ Pourquoi votre meilleur marketing reste un client satisfait.✨ À écouter aussi (épisodes mentionnés) :269. Pourquoi il est nécessaire de justifier ses tarifs[BDF#148] Arrêtez de douter de tout, vous êtes déjà dans le top 1% (et je vais vous le prouver)✨ Chapitres :00:42 - Fin de l'intro02:46 - Pourquoi je vois les deux côtés du miroir04:45 - Le conseil de mon père qui m'a marquée08:29 - Erreur #1 : On vous donne 5 secondes (et vous les ratez)11:41 - Erreur #2 : LE truc qui refroidit instantanément n'importe quel client13:39 - Erreur #3 : Pourquoi on ne vous fait pas confiance (même si vous êtes compétent)17:21 - Erreur #4 : Mon anecdote honteuse chez L'Occitane en Provence20:39 - Erreur #5 : Deux assistantes virtuelles, deux tarifs élevés, deux impressions opposées
Con la Semana Santa cada vez más próxima, charlamos con Héctor Arráiz, uno de los principales responsables de la Cofradía de Nuestro Padre Genarín. La entrevista nos permite interesarnos por los detalles y preparativos de una nueva edición de su multitudinaria procesión pagana, así como por la previa celebración de otra entrega más de su Certamen de Versos Burlescos inspirados en pellejero borrachín más popular de León.
Cette semaine, au Podcast Pas Ordinaire, j'ai reçu Vicky Powell, l'avocate criminaliste que tout le monde voit sur les réseaux sociaux.On plonge dans l’univers du droit criminel, du système de justice québécois et de la réalité derrière les procès.Vicky explique comment fonctionne réellement le système judiciaire, comment les avocats défendent leurs clients et pourquoi certaines personnes peuvent être acquittées même lorsque une condamnation semble évidente pour le public.On parle aussi de la pression du métier, des défis émotionnels, de la gestion des clients et de la réalité du travail d’avocat criminaliste.Un épisode fascinant pour comprendre :comment fonctionne la justicele rôle d’un avocat de la défenseles mythes autour du droit criminella réalité du système judiciaireBon Épisode!----------------------------------------------------Merci à nos commanditaires de l'Épisode :
Aujourd'hui je reçois Matthieu Stéfani, l'une des voix les plus connues du podcast en France. Matthieu a créé Génération Do It Yourself, un podcast dans lequel il interviewe depuis des années des entrepreneurs, des créateurs, des artistes, des sportifs… tous ceux et celles qui construisent, innovent, inventent leur chemin.Son truc à lui, c'est l'écoute : poser les bonnes questions, laisser de l'espace, faire parler les gens. Sauf qu'à un moment, Mathieu a eu envie de passer un cap. Arrêter seulement d'écouter… pour aller voir. Aller sur le terrain. Voyager. Se confronter à des réalités qu'on commente beaucoup depuis la France, sans toujours les comprendre.Et ça l'a emmené loin : les États-Unis d'abord, le Brésil ensuite… et puis la Chine. Un voyage pas tout à fait comme les autres. Un voyage pour comprendre un pays dont on parle beaucoup, mais que peu d'entre nous connaissent vraiment. Un voyage pour tester ses idées reçues, mesurer la vitesse, sentir le pouls d'un monde qui avance selon d'autres règles.De ce séjour, Mathieu a tiré un documentaire de 90 minutes : “Comment la Chine est devenue imbattable”. Un film ambitieux, parfois dérangeant parce que la Chine ne laisse jamais indifférent. Et parce que regarder la Chine en face, ça oblige aussi à se regarder nous-mêmes : nos dépendances, nos certitudes, notre confort… et parfois, nos angles morts.Dans cet épisode, on va parler de ce que le voyage fait à un entrepreneur, de ce que le terrain change par rapport aux idées, et de ce qu'on découvre quand on accepte de sortir de sa bulle. On va parler d'audace, de liberté, de peur aussi… et de cette question qui traverse tout Beau Voyage : qu'est-ce qu'on devient quand on se déplace ?Un podcast produit et réalisé par Sakti Productions & Beau Voyage
Helena Bueno, higienista bucodental, y Pedro Valiente, fisioterapeuta‑osteópata, son dos sanitarios de Ciudad Real que forman una combinación perfecta cuando se juntan para hacer lo que más disfrutan: música. Helena canta y Pedro toca la guitarra, un tándem sencillo que llevan tiempo compartiendo.Entre consultas, pacientes y jornadas intensas, sacan tiempo para ensayar, preparar temas y subirse a un escenario cuando pueden. Nos cuentan cómo compaginan sus profesiones con esta afición que mantienen con constancia y ganas.Además, nos ofrecen un pequeño regalo en directo: interpretan “Mi rincón del paraíso”, versión del tema de José Carlos Escobar, y “Arráncame”, de Vanesa Martín.Escuchar audio
REDIFF - Le 25 novembre était la journée internationale de lutte contre les violences faites aux femmes. Quelles sont les mesures du nouveau plan interministériel mis en place ? - Violences Info Service : 39 19 (anonyme, gratuit, 24h/7) - Association "M'endors pas" : www.mendorspas.org - Fédération nationale solidarité femmes : www.solidaritefemmes.org - Femmes Solidiares : www.femmes-solidaires.org - Fédération nationale des Centres d'Information sur les Droits des Femmes et des Familles : www.infofemmes.com Retrouvez toutes les associations sur le site national "Arrêtons les violences" : https://arretonslesviolences.gouv.fr/ Dans ce podcast, découvrez une partie des coulisses de l'émission "Parlons-Nous". En compagnie de Caroline Dublanche, Paul Delair revient sur les témoignages et autres moments qui ont marqué le direct.Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.
Salut les sportifs intelligents ! Tu as l'impression que ta perte de poids est un combat permanent contre ta propre volonté ? Tu comptes tes calories, tu fais des efforts, mais tu finis toujours par craquer ? Ce n'est pas un manque de discipline, c'est de la biologie. Dans cet épisode, on décrypte ensemble l'étude choc de Kevin Hall (NIH) qui a prouvé que la nature de tes aliments court-circuite ton cerveau. Tu vas découvrir pourquoi manger "ultra-transformé" te force mécaniquement à consommer 508 calories de plus par jour sans même t'en rendre compte. Au programme de cet épisode : L'étude Kevin Hall : Comment 20 volontaires ont pris du gras avec les mêmes macros, mais des aliments différents. Le piratage hormonal : Pourquoi la ghréline (faim) reste haute et le PYY (satiété) s'effondre face aux produits industriels. La densité calorique vs nutritionnelle : L'illusion qui affame ton métabolisme. Mes 3 piliers concrets : Comment rééduquer ton corps pour automatiser ton déficit calorique sans souffrir. Mon approche est claire : Comprendre avant d'agir. Arrête les régimes miracles et commence à piloter ton métabolisme.
Mistral schwenkt ins Beratungsgeschäft. Sam Altman nennt den Pentagon-Deal "opportunistisch und sloppy", ändert den Vertrag nachträglich und erntet Community Notes. ChatGPT-Uninstalls steigen um 295%, Claude verzeichnet Rekord-Downloads. Dario Amodei entschuldigt sich für ein internes Memo - Elon Musk lässt Grok ihn verspotten. Anthropic nähert sich $20 Mrd. ARR, OpenAI meldet $25 Mrd. Die Washington Post bestätigt Claudes Rolle beim Iran-Angriff über Palantirs MAVEN-System. Nvidia baut einen eigenen Inferenz-Chip. Oracle entlässt Tausende für Data-Center-Investitionen, Cursor durchbricht $2 Mrd. ARR. OpenAI stampft Shopping-Pläne ein, Meta startet ein KI-Shopping-Tool. Sea Limited, CrowdStrike und On Running mit Earnings. Google und Epic einigen sich - Tim Sweeney darf den Play Store bis 2032 nicht kritisieren. Meta öffnet WhatsApp für KI-Rivalen. Die USA planen eine Genehmigungspflicht für Chip-Exporte weltweit. Unterstütze unseren Podcast und entdecke die Angebote unserer Werbepartner auf doppelgaenger.io/werbung. Vielen Dank! Philipp Glöckler und Philipp Klöckner sprechen heute über: (00:00:00) Apple MacBook Neo für $599 (00:04:50) Mistral wird zur Beratungsfirma (00:14:39) Sloppy Sam und Cancel ChatGPT +295% (00:28:55) Amodei-Memo und Musk-Grok-Attacke (00:47:04) Anthropic $20 Mrd. vs. OpenAI $25 Mrd. ARR (00:53:21) Claude im Iran, Anduril $4 Mrd. und Nvidia Inferenz-Chip (00:57:47) Oracle-Entlassungen und Cursor $2 Mrd. ARR (01:04:42) OpenAI stampft Shopping ein, Meta startet KI-Shopping (01:13:08) Earnings: Sea Limited, CrowdStrike, On Running (01:21:56) Google/Epic: Sweeney-Maulkorb bis 2032 (01:26:10) WhatsApp öffnet für KI-Rivalen (01:26:50) Polymarket, Strompreise und Chip-Exportkontrollen (01:42:48) Neura Robotics 1 Mrd. Euro von Tether und Lio $30 Mio. von a16z Shownotes Levi Penell Dubai - Instagram Mistral wird zum Berater? - bloomberg.com OpenAI ändert Pentagon-Deal - ft.com Sam Altman auf X zum Pentagon-Deal - x.com ChatGPT-Deinstallationen +295% - techcrunch.com Anthropic CEO: Trump wollte "Dictator-Style Praise" - theinformation.com Altman: Regierung soll mächtiger sein als Firmen - cnbc.com Anthropic klagt gegen Supply Chain Risk - cnbc.com Big Tech unterstützt Anthropic - reuters.com Anthropic-CEO entschuldigt sich für Trump-Memo - axios.com Anthropic nähert sich $20 Mrd. Umsatz - bloomberg.com OpenAI: $25 Mrd. Umsatz, Anthropic holt auf - theinformation.com Claude zentral in US-Iran-Kampagne - washingtonpost.com Anduril: $4 Mrd. Runde - bloomberg.com Nvidia plant neuen KI-Chip - wsj.com Oracle: Tausende Entlassungen - bloomberg.com Cursor: $2 Mrd. Jahresumsatz - trendingtopics.eu OpenAI reduziert ChatGPT-Shopping - theinformation.com Meta testet KI-Shopping-Tool - bloomberg.com Sea verfehlt Schätzungen - bloomberg.com CrowdStrike übertrifft Erwartungen - barrons.com On Running -14% nach schwacher Prognose - cnbc.com Google teilt Play-Store-Katalog - bloomberg.com Sweeney: Google öffnet Android - x.com Meta öffnet WhatsApp für KI-Rivalen - reuters.com Polymarket entfernt Nuklear-Wette - businessinsider.com Trump trifft Tech-Giganten - reuters.com USA erwägen KI-Chip-Exportregeln - bloomberg.com Kenianische Arbeiter über Meta-Brillen - futurezone.at Meta-Brillen zeichnen heimlich auf - x.com Neura sammelt 1 Mrd. mit Tether - bloomberg.com Lio: $30M von a16z - techcrunch.com
On a mountain road on Colorado's Guanella Pass, motorcyclist Adam Lamb spots a moose stepping out of the brush. Two seconds later, he's airborne, both arms broken and stranded off the road without cell service. Just behind him is Roger Matthews—a board-certified physician and search-and-rescue volunteer—who arrives and immediately begins managing the scene. In this episode, Adam recounts the moments leading up to the crash while Roger explains how he approached scene safety, organized bystanders, and assessed Adam's injuries as they waited for help to arrive. We explore wildlife hazards, speed and stopping distance, emergency braking, and why first aid training and preparation can make a critical difference when riding remote roads.
Ranjan Roy from Margins is back for our weekly discussion of the latest tech news. We cover: 1) OpenAI hits $25 billion ARR, Anthropic hits $19 billion ARR 2) Are ARR numbers trustworthy? 3) OpenAI's insane revenue expectations 4) Did Apple actually play this perfectly? 5) We need a Tim Cook with claw hands Apple ad 6) AI lab IPOs are brewing, what will the S-1s look like? 7) Anthropic's still talking with the Pentagon 8) Dario's internal memo 9) Wait, was this actually marketing for Anthropic? 10) Or was it a real worry about AI-enabled surveillance? 11) McDonald's CEO's unwitting viral moment --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. Want a discount for Big Technology on Substack + Discord? Here's 25% off for the first year: https://www.bigtechnology.com/subscribe?coupon=0843016b Learn more about your ad choices. Visit megaphone.fm/adchoices
Hannah is ready to make her first hire and is seriously considering looking beyond U.S. borders — but she doesn't know what she doesn't know. In this episode, Preston is joined by Brian Samson, a three-time founder who has scaled recruiting agencies to $4 million ARR by building teams across Latin America and beyond. Together they walk Hannah through exactly how to approach international hiring for the first time: where to start, which regions tend to excel at what, how to think about time zones, and the blind spots that trip up most first-time international managers — including the costly "follow-the-sun" communication trap that can burn a full week on a single misunderstood task. Support our show sponsors -> https://freelancetofounder.com/sponsors Submit your own question -> https://freelancetofounder.com/ask Learn more about your ad choices. Visit megaphone.fm/adchoices
Simon Swords founded Fundipedia after starting in a backyard shed building bespoke software. Originally a custom development shop, his firm built a data governance platform for major buy-side asset managers including HSBC, Barclays, and Legal & General. Over time, Fundipedia evolved into a high-retention enterprise SaaS platform with strong net revenue retention and Rule of 40 performance. Simon navigated long consultative sales cycles, regulatory tailwinds, and a tightly networked financial services market to build a durable recurring revenue engine. After turning down an initial offer, Simon grew ARR further and ultimately sold in 2024 at approximately 10x ARR. He exited fully, used ChatGPT extensively in diligence, and now reflects on endurance, discipline, and surviving long enough for luck to compound. Key Takeaways Survive First — Don't make a mistake that kills you or the business. Staying alive creates the opportunity for luck to compound. Enterprise Patience — Two-year sales cycles are normal at the top end. Persistence and reputation matter more than speed. Rule Of 40 Discipline — Strong growth plus profitability gives founders leverage in exit timing and valuation. Problems Over Product — Founders obsess over product; buyers care about solving painful, expensive problems. Build To Exit Cleanly — Structure the company so it runs without you before you start acquisition conversations. Quote from Simon Swords, Founder of Fundipedia "I think the most important thing is not to make a mistake that kills you or the business. While you're in the arena and you've not been taken out yet, dragged off by the hyenas or lions, whatever they used back in the Roman days, you've still got a chance to make something magical happen. "You do something stupid, kill the business, kill your reputation, you're done. Entrepreneurs hate the word luck. I do feel luck. I am lucky. Of course I'm lucky. I have to be lucky. You make your own luck. "But I'll tell you what I didn't do. I didn't make a mistake that killed me or the business and the entire way through. Even when I was going through hell, never, no matter how neurotic or anxious or all the negative kind of traits you can imagine would have flown through me. I never made a mistake that killed the business." Links Simon Swords on LinkedIn Fundipedia on LinkedIn Fundipedia website FE fundinfo website Podcast Sponsor – LaunchBay LaunchBay helps B2B software companies automate client onboarding and implementation so customers activate faster and everyone stays aligned. If your onboarding includes data collection, setup steps, approvals, training, or any level of customization, LaunchBay replaces the messy mix of emails, spreadsheets, and meetings with a clear, all-in-one onboarding system. Teams use LaunchBay to onboard clients faster, stay on top of follow-ups automatically, and deliver a smoother experience, without hiring more people or adding more tools. Visit launchbay.com/practical and get 25% off your first 3 months on any LaunchBay plan. The Practical Founders Podcast Tune into the Practical Founders Podcast for weekly in-depth interviews with founders who have built valuable software companies without big funding. Subscribe to the Practical Founders Podcast using your favorite podcast app or view on our YouTube channel. Get the weekly Practical Founders newsletter and podcast updates at practicalfounders.com. Practical Founders CEO Peer Groups Be part of a committed and confidential group of practical founders creating valuable software companies without big VC funding. A Practical Founders Peer Group is a committed and confidential group of founders/CEOs who want to help you succeed on your terms. Each Practical Founders Peer Group is personally curated and moderated by Greg Head.
Reltio crossed $185M in ARR and saw 58% growth in the second half of the year. That kind of acceleration in an enterprise platform signals strong market pull. At the DataDriven Conference 2026, I sat down with Alyson Welch, CRO of Reltio, to talk about what customers are actually asking for in the age of AI.Alyson owns the full customer journey, from acquisition to support, and also leads the partner ecosystem. Her lens is simple. If the customer does not see value in their data, nothing else matters.One insight stood out. Enterprises are drowning in applications. One former CIO shared she had 1,500 enterprise apps to manage. That means data is locked everywhere. The real demand today is not just dashboards or models. It is a trusted, unified data layer that sits between enterprise systems and AI.That is where Reltio is focused. Bringing accuracy, trust, and unification so companies can actually use their data across environments.We also discussed agentic workflows. In an agent-driven world, your data foundation cannot be average. Every automated decision depends on it. This is not just a tech shift. It is a cultural shift. Leaders now have to think about how humans and AI agents work together and how to build capability across both.The momentum reflects this shift. This conversation was about trust, scale, and what it really takes to lead in the AI era.#data #ai #datadriven #reltio #theravitshow
The Twenty Minute VC: Venture Capital | Startup Funding | The Pitch
AGENDA: 04:13 Anthropic vs The Pentagon: Who Wins 13:54 Was Sam Altman Wrong to Take the Deal 24:28 OpenAI's $110BN Mega Round: The Breakdown 28:22 Who Has a Bigger Valuation Premium: Sam Altman or Elon Musk 34:38 Why We Got the SaaS Apocalypse Wrong? 43:24 Why Salesforce Could be the Best Buy in Public Markets 47:46 Block Lays Off 40% of Team: AI or Overhiring 01:00:16 Cursor Hits $2BN in ARR… so not Dead? 01:18:15 How to Pick Winners in AI?
The reception to our recent post on Code Reviews has been strong. Catch up!Amid a maelstrom of discussion on whether or not AI is killing SaaS, one of the top publicly listed SaaS companies in the world has just reported record revenues, clearing well over $1.1B in ARR for the first time with a 28% margin. As we comment on the pod, Aaron Levie is the rare public company CEO equally at home in both worlds of Silicon Valley and Wall Street/Main Street, by day helping 70% of the Fortune 500 with their Enterprise Advanced Suite, and yet by night is often found in the basements of early startups and tweeting viral insights about the future of agents.Now that both Cursor, Cloudflare, Perplexity, Anthropic and more have made Filesystems and Sandboxes and various forms of “Just Give the Agent a Box” cool (not just cool; it is now one of the single hottest areas in AI infrastructure growing 100% MoM), we find it a delightfully appropriate time to do the episode with the OG CEO who has been giving humans and computers Boxes since he was a college dropout pitching VCs at a Michael Arrington house party.Enjoy our special pod, with fan favorite returning guest/guest cohost Jeff Huber!Note: We didn't directly discuss the AI vs SaaS debate - Aaron has done many, many, many other podcasts on that, and you should read his definitive essay on it. Most commentators do not understand SaaS businesses because they have never scaled one themselves, and deeply reflected on what the true value proposition of SaaS is.We also discuss Your Company is a Filesystem:We also shoutout CTO Ben Kus' and the AI team, who talked about the technical architecture and will return for AIE WF 2026.Full Video EpisodeTimestamps* 00:00 Adapting Work for Agents* 01:29 Why Every Agent Needs a Box* 04:38 Agent Governance and Identity* 11:28 Why Coding Agents Took Off First* 21:42 Context Engineering and Search Limits* 31:29 Inside Agent Evals* 33:23 Industries and Datasets* 35:22 Building the Agent Team* 38:50 Read Write Agent Workflows* 41:54 Docs Graphs and Founder Mode* 55:38 Token FOMO Culture* 56:31 Production Function Secrets* 01:01:08 Film Roots to Box* 01:03:38 AI Future of Movies* 01:06:47 Media DevRel and EngineeringTranscriptAdapting Work for AgentsAaron Levie: Like you don't write code, you talk to an agent and it goes and does it for you, and you may be at best review it. That's even probably like, like largely not even what you're doing. What's happening is we are changing our work to make the agents effective. In that model, the agent didn't really adapt to how we work.We basically adapted to how the agent works. All of the economy has to go through that exact same evolution. Right now, it's a huge asset and an advantage for the teams that do it early and that are kinda wired into doing this ‘cause you'll see compounding returns. But that's just gonna take a while for most companies to actually go and get this deployed.swyx: Welcome to the Lane Space Pod. We're back in the chroma studio with uh, chroma, CEO, Jeff Hoover. Welcome returning guest now guest host.Aaron Levie: It's a pleasure. Wow. How'd you get upgraded to, uh, to that?swyx: Because he's like the perfect guy to be guest those for you.Aaron Levie: That makes sense actually, for We love context. We, we both really love context le we really do.We really do.swyx: Uh, and we're here with, uh, Aaron Levy. Welcome.Aaron Levie: Thank you. Good to, uh, good to be [00:01:00] here.swyx: Uh, yeah. So we've all met offline and like chatted a little bit, but like, it's always nice to get these things in person and conversation. Yeah. You just started off with so much energy. You're, you're super excited about agents.I loveAaron Levie: agents.swyx: Yeah. Open claw. Just got by, got bought by OpenAI. No, not bought, but you know, you know what I mean?Aaron Levie: Some, some, you know, acquihire. Executiveswyx: hire.Aaron Levie: Executive hire. Okay. Executive hire. Say,swyx: hey, that's my term. Okay. Um, what are you pounding the table on on agents? You have so many insightful tweets.Why Every Agent Needs a BoxAaron Levie: Well, the thing that, that we get super excited by that I think is probably, you know, should be relatively obvious is we've, we've built a platform to help enterprises manage their files and their, their corporate files and the permissions of who has access to those files and the sharing collaboration of those files.All of those files contain really, really important information for the enterprise. It might have your contracts, it might have your research materials, it might have marketing information, it might have your memos. All that data obviously has, you know, predominantly been used by humans. [00:02:00] But there's been one really interesting problem, which is that, you know, humans only really work with their files during an active engagement with them, and they kind of go away and you don't really see them for a long time.And all of a sudden, uh, with the power of AI and AI agents, all of that data becomes extremely relevant as this ongoing source of, of answers to new questions of data that will transform into, into something else that, that produces value in your organization. It, it contains the answer to the new employee that's onboarding, that needs to ramp up on a project.Um, it contains the answer to the right thing to sell a customer when you're having a conversation to them, with them contains the roadmap information that's gonna produce the next feature. So all that data. That previously we've been just sort of storing and, and you know, occasionally forgetting about, ‘cause we're only working on the new active stuff.All of that information becomes valuable to the enterprise and it's gonna become extremely valuable to end users because now they can have agents go find what they're looking for and produce new, new [00:03:00] value and new data on that information. And it's gonna become incredibly valuable to agents because agents can roam around and do a bunch of work and they're gonna need access to that data as well.And um, and you know, sometimes that will be an agent that is sort of working on behalf of, of, of you and, and effectively as you as and, and they are kind of accessing all of the same information that you have access to and, and operating as you in the system. And then sometimes there's gonna be agents that are just.Effectively autonomous and kind of run on their own and, and you're gonna collaborate and work with them kind of like you did another person. Open Claw being the most recent and maybe first real sort of, you know, kind of, you know, up updating everybody's, you know, views of this landscape version of, of what that could look like, which is, okay, I have an agent.It's on its own system, it's on its own computer, it has access to its own tools. I probably don't give it access to my entire life. I probably communicate with it like I would an assistant or a colleague and then it, it sort of has this sandbox environment. So all of that has massive implications for a platform that manage that [00:04:00] enterprise data.We think it's gonna just transform how we work with all of the enterprise content that we work with, and we just have to make sure we're building the right platform to support that.swyx: The sort of shorthand I put it is as people build agents, everybody's just realizing that every agent needs a box. Yes.And it's nice to be called box and just give everyone a box.Aaron Levie: Hey, I if I, you know, if we can make that go viral, uh, like I, I think that that terminology, I, that's theswyx: tagline. Every agentAaron Levie: needs a box. Every agent needs a box. If we can make that the headline of this, I'm fine with this. And that's the billboard I wanna like Yeah, exactly.Every agent needs a box. Um, I like it. Can we ship this? Like,swyx: okay, let's do it. Yeah.Aaron Levie: Uh, my work here is done and I got the value I needed outta this podcast Drinks.swyx: Yeah.Agent Governance and IdentityAaron Levie: But, but, um, but, but, you know, so the thing that we, we kind of think about is, um, is, you know, whether you think the number 10 x or a hundred x or whatever the number is, we're gonna have some order of magnitude more agents than people.That's inevitable. It has to happen. So then the question is, what is the infrastructure that's needed to make all those agents effective in the enterprise? Make sure that they are well governed. Make sure they're only doing [00:05:00] safe things on your information. Make sure that they're not getting exposed. The data that they shouldn't have access to.There's gonna be just incredibly spectacularly crazy security incidents that will happen with agents because you'll prompt, inject an agent and sort of find your way through the CRM system and pull out data that you shouldn't have access to. Oh, weJeff Huber: have God,Aaron Levie: right? I mean, that's just gonna happen all over the place, right?So, so then the thing is, is how do you make sure you have the right security, the permissions, the access controls, the data governance. Um, we actually don't yet exactly know in many cases how we're gonna regulate some of these agents, right? If you think about an agent in financial services, does it have the exact same financial sort of, uh, requirements that a human did?Or is it, is the risk fully on the human that was interacting or created the agent? All open questions, but no matter what, there's gonna need to be a layer that manages the, the data they have access to, the workflows that they're involved in, pulling up data from multiple systems. This is the new infrastructure opportunity in the era of agents.swyx: You have a piece on agent identities, [00:06:00] which I think was today, um, which I think a lot of breaking news, the security, security people are talking about, right? Like you basically, I, I always think of this as like, well you need the human you and then there you need the agent. YouAaron Levie: Yes.swyx: And uh, well, I don't know if it's that simple, but is box going to have an opinion on that or you're just gonna be like, well we're just the sort of the, the source layer.Yeah. Let's Okta of zero handle that.Aaron Levie: I think we're gonna have an opinion and we will work with generally wherever the contours of the market end up. Um, and the reason that we're gonna have an opinion more than other topics probably is because one of the biggest use cases for why your agent might need it, an identity is for file system access.So thus we have to kind of think about this pretty deeply. And I think, uh, unless you're like in our world thinking about this particular problem all day long, it might be, you know, like, why is this such a big deal? And the reason why it's a really big deal is because sometimes sort of say, well just give the agent an, an account on the system and it just treats, treat it like every other type of user on the system.The [00:07:00] problem is, is that I as Aaron don't really have any responsibility over anybody else's box account in our organization. I can't see the box account of any other employee that I work with. I am not liable for anything that they do. And they have, I have, I have, you know, strict privacy requirements on everything that they're able to, you know, that, that, that they work on.Agents don't have that, you know, don't have those properties. The person who creates the agent probably is gonna, for the foreseeable future, take on a lot of the liability of what that agent does. That agent doesn't deserve any privacy because, because it's, you know, it can't fully be autonomously operated and it doesn't have any legal, you know, kind of, you know, responsibility.So thus you can't just be like, oh, well I'll just create a bunch of accounts and then I'll, I'll kind of work with that agent and I'll talk to it occasionally. Like you need oversight of that. And so then the question is, how do you have a world where the agent, sometimes you have oversight of, but what if that agent goes and works with other people?That person over there is collaborating with the agent on something you shouldn't have [00:08:00] access to what they're doing. So we have all of these new boundaries that we're gonna have to figure out of, of, you know, it's really, really easy. So far we've been in, in easy mode. We've hit the easy button with ai, which is the agent just is you.And when you're in quad code and you're in cursor, and you're in Codex, you're just, the agent is you. You're offing into your services. It can do everything you can do. That's the easy mode. The hard mode is agents are kind of running on their own. People check in with them occasionally, they're doing things autonomously.How do you give them access to resources in the enterprise and not dramatically increased the security risk and the risk that you might expose the wrong thing to somebody. These are all the new problems that we have to get solved. I like the identity layer and, and identity vendors as being a solution to that, but we'll, we'll need some opinions as well because so many of the use cases are these collaborative file system use cases, which is how do I give it an agent, a subset of my data?Give it its own workspace as well. ‘cause it's gonna need to store off its own information that would be relevant for it. And how do I have the right oversight into that? [00:09:00]Jeff Huber: One thing, which, um, I think is kind interesting, think about is that you know, how humans work, right? Like I may not also just like give you access to the whole file.I might like sit next to you and like scroll to this like one part of the file and just show you that like one part and like, you know,swyx: partial file access.Jeff Huber: I'm just saying I think like our, like RA does seem to be dead, right? Like you wanna say something is dead uhhuh probably RA is dead. And uh, like the auth story to me seems like incredibly unsolved and unaddressed by like the existing state of like AI vendors.ButAaron Levie: yeah, I think, um, we're, I mean you're taking obviously really to level limit that we probably need to solve for. Yeah. And we built an access control system that was, was kind of like, you know, its own little world for, for a long time. And um, and the idea was this, it's a many to many collaboration system where I can give you any part of the file system.And it's a waterfall model. So if I give you higher up in the, in the, in the system, you get everything below. And that, that kind of created immense flexibility because I can kind of point you to any layer in the, in the tree, but then you're gonna get access to everything kind of below it. And that [00:10:00] mostly is, is working in this, in this world.But you do have to manage this issue, which is how do I create an agent that has access to some of my stuff and somebody else's stuff as well. Mm-hmm. And which parts do I get to look at as the creator of the agent? And, and these are just brand new problems? Yeah. Crazy. And humans, when there was a human there that was really easy to do.Like, like if the three of us were all sharing, there'd be a Venn diagram where we'd have an overlapping set of things we've shared, but then we'd have our own ways that we shared with each other. In an agent world, somebody needs to take responsibility for what that agent has access to and what they're working on.These are like the, some of the most probably, you know, boring problems for 98% of people on, on the internet, but they will be the problems that are the difference between can you actually have autonomous agents in an enterprise contextswyx: Yeah.Aaron Levie: That are not leaking your data constantly.swyx: No. Like, I mean, you know, I run a very, very small company for my conference and like we already have data sensitivity issues.Yes. And some of my team members cannot see Yes. Uh, the others and like, I can't imagine what it's like to run a Fortune 500 and like, you have to [00:11:00] worry about this. I'm just kinda curious, like you, you talked to a lot like, like 70, 80% of your cus uh, of the Fortune 500, your customers.Aaron Levie: Yep. 67%. Just so we're being verySEswyx: precise.So Yeah. I'm notAaron Levie: Okay. Okay.swyx: Something I'm rounding up. Yes. Round up. I'm projecting to, forAaron Levie: the government.swyx: I'm projecting to the end of the year.Aaron Levie: Okay.swyx: There you go.Aaron Levie: You do make it sound like, like we, we, well we've gotta be on this. Like we're, we're taking way too long to get to 80%. Well,swyx: no, I mean, so like. How are they approaching it?Right? Because you're, you don't have a, you don't have a final answer yet.Why Coding Agents Took Off FirstAaron Levie: Well, okay, so, so this is actually, this is the stark reality that like, unfortunately is the kinda like pouring the water on the party a little bit.swyx: Yes.Aaron Levie: We all in Silicon Valley are like, have the absolute best conditions possible for AI ever.And I think we all saw the dke, you know, kind of Dario podcast and this idea of AI coding. Why is that taken off? And, and we're not yet fully seeing it everywhere else. Well, look, if you just like enumerated the list of properties that AI coding has and then compared it to other [00:12:00] knowledge work, let's just, let's just go through a few of them.Generally speaking, you bring on a new engineer, they have access to a large swath of the code base. Like, there's like very, like you, just, like new engineer comes on, they can just go and find the, the, the stuff that they, they need to work with. It's a fully text in text out. Medium. It's only, it's just gonna be text at the end of the day.So it's like really great from a, from just a, uh, you know, kinda what the agent can work with. Obviously the models are super trained on that dataset. The labs themselves have a really strong, kind of self-reinforcing positive flywheel of why they need to do, you know, agent coding deeply. So then you get just better tooling, better services.The actual developers of the AI are daily users of the, of the thing that they're we're working on versus like the, you know, probably there's only like seven Claude Cowork legal plugin users at Anthropic any given day, but there's like a couple thousand Claude code and you know, users every single day.So just like, think about which one are they getting more feedback on. All day long. So you just go through this list. You have a, you know, everybody who's a [00:13:00] developer by definition is technical so they can go install the latest thing. We're all generally online, or at least, you know, kinda the weird ones are, and we're all talking to each other, sharing best practices, like that's like already eight differences.Versus the rest of the economy. Every other part of the economy has like, like six to seven headwinds relative to that list. You go into a company, you're a banker in financial services, you have access to like a, a tiny little subset of the total data that's gonna be relevant to do your job. And you're have to start to go and talk to a bunch of people to get the right data to do your job because Sally didn't add you to that deal room, you know, folder.And that that, you know, the information is actually in a completely different organization that you now have to go in and, and sort of run into. And it's like you have this endless list of access controls and security. As, as you talked about, you have a medium, which is not, it's not just text, right? You have, you have a zoom call that, that you're getting all of the requirements from the customer.You have a lot of in-person conversations and you're doing in-person sales and like how do you ever [00:14:00] digitize all of that information? Um, you know, I think a lot of people got upset with this idea that the code base has all the context, um, that I don't know if you follow, you know, did you follow some of that conversation that that went viral?Is like, you know, it's not that simple that, that the code base doesn't have all the knowledge, but like it's a lot, you're a lot better off than you are with other areas of knowledge work. Like you, we like, we like have documentation practices, you write specifications. Those things don't exist for like 80% of work that happens in the enterprise.That's the divide that we have, which is, which is AI coding has, has just fully, you know, where we've reached escape velocity of how powerful this stuff is, and then we're gonna have to find a way to bring that same energy and momentum, but to all these other areas of knowledge work. Where the tools aren't there, the data's not set up to be there.The access controls don't make it that easy. The context engineering is an incredibly hard problem because again, you have access control challenges, you have different data formats. You have end users that are gonna need to kind of be kind of trained through this as opposed to their adopting [00:15:00] these tools in their free time.That's where the Fortune 500 is. And so we, I think, you know, have to be prepared as an industry where we are gonna be on a multi-year march to, to be able to bring agents to the enterprise for these workflows. And I think probably the, the thing that we've learned most in coding that, that the rest of the world is not yet, I think ready for, I mean, we're, they'll, they'll have to be ready for it because it's just gonna inevitably happen is I think in coding.What, what's interesting is if you think about the practice of coding today versus two years ago. It's probably the most changed workflow in maybe the history of time from the amount of time it's changed, right? Yeah. Like, like has any, has any workflow in the entire economy changed that quickly in terms of the amount of change?I just, you know, at least in any knowledge worker workflow, there's like very rarely been an event where one piece of technology and work practice has so fundamentally, you know, changed, changed what you do. Like you don't write code, you talk to an agent and it goes and [00:16:00] does it for you, and you may be at best review it.And even that's even probably like, like largely not even what you're doing. What's happening is we are changing our work to make the agents effective. In that model, the agent didn't really adapt to how we work. We basically adapted to how the agent works. Mm-hmm. All of the economy has to go through that exact same evolution.The rest of the economy is gonna have to update its workflows to make agents effective. And to give agents the context that they need and to actually figure out what kind of prompting works and to figure out how do you ensure that the agent has the right access to information to be able to execute on its work.I, you know, this is not the panacea that people were hoping for, of the agent drops in, just automates your life. Like you have to basically re-engineer your workflow to get the most out of agents and, uh, and that, that's just gonna take, you know, multiple years across the economy. Right now it's a huge asset and an advantage for the teams that do it early and that are kinda wired into doing this.‘cause [00:17:00] you'll see compounding returns, but that's just gonna take a while for most companies to actually go and get this deployed.swyx: I love, I love pushing back. I think that. That is what a lot of technology consultants love to hear this sort of thing, right? Yeah, yeah, yeah. First to, to embrace the ai. Yes. To get to the promised land, you must pay me so much money to a hundred percent to adopt the prescribed way of, uh, conforming to the agents.Yes. And I worry that you will be eclipsed by someone else who says, no, come as you are.Aaron Levie: Yeah.swyx: And we'll meet you where you are.Aaron Levie: And, and, and and what was the thing that went viral a week ago? OpenAI probably, uh, is hiring F Dees. Yeah. Uh, to go into the enterprise. Yeah. Yeah. And then philanthropic is embedded at Goldman Sachs.Yeah. So if the labs are having to do this, if, if the labs have decided that they need to hire FDE and professional services, then I think that's a pretty clear indication that this, there's no easy mode of workflow transformation. Yeah. Yeah. So, so to your point, I think actually this is a market opportunity for, you know, new professional services and consulting [00:18:00] firms that are like Agent Build and they, and they kind of, you know, go into organizations and they figure out how to re-engineer your workflows to make them more agent ready and get your data into the right format and, you know, reconstruct your business process.So you're, you're not doing most of the work. You're telling agents how to do the work and then you're reviewing it. But I haven't seen the thing that can just drop in and, and kinda let you not go through those changes.swyx: I don't know how that kind of sales pitch goes over. Yeah. You know, you're, you're saying things like, well, in my sort of nice beautiful walled garden, here's, there's, uh, because here's this, here's this beautiful box account that has everything.Yes. And I'm like, well, most, most real life is extremely messy. Sure. And like, poorly named and there duplicate this outdated s**tAaron Levie: a hundred percent. And so No, no, a hundred percent. And so this is actually No. So, so this is, I mean, we agree that, that getting to the beautiful garden is gonna be tough.swyx: Yeah.Aaron Levie: There's also the other end of the spectrum where I, I just like, it's a technical impossibility to solve. The agent is, is truly cannot get enough context to make the right decision in, in the, in the incredibly messy land. Like there's [00:19:00] no a GI that will solve that. So, so we're gonna have to kind of land in somewhere in between, which is like we all collectively get better at.Documentation practices and, and having authoritative relatively up-to-date information and putting it in the right place like agents will, will certainly cause us to be much better organized around how we work with our information, simply because the severity of the agent pulling the wrong data will be too high and the productivity gain of that you'll miss out on by not doing this will be too high as well, that you, that your competition will just do it and they'll just have higher velocity.So, uh, and, and we, we see this a lot firsthand. So we, we build a series of agents internally that they can kind of have access to your full box account and go off and you give it a task and it can go find whatever information you're looking for and work with. And, you know, thank God for the model progress, but like, if, if you gave that task to an agent.Nine months ago, you're just gonna get lots of bogus answers because it's gonna, it's gonna say, Hey, here's, here are fi [00:20:00] five, you know, documents that all kind of smell like the right thing. And I'm gonna, but I, but you're, you're putting me on the clock. ‘cause my assistant prompt says like, you know, be pretty smart, but also try and respond to the user and it's gonna respond.And it's like, ah, it got the wrong document. And then you do that once or twice as a knowledge worker and you're just neverswyx: again,Aaron Levie: never again. You're just like done with the system.swyx: Yeah. It doesn't work.Aaron Levie: It doesn't work. And so, you know, Opus four six and Gemini three one Pro and you know, whatever the latest five 3G BT will be, like, those things are getting better and better and it's using better judgment.And this sort of like the, all of these updates to the agentic tool and search systems are, are, we're seeing, we're seeing very real progress where the agent. Kind of can, can almost smell some things a little bit fishy when it's getting, you know, we, we have this process where we, we have it go fan out, do a bunch of searches, pull up a bunch of data, and then it has to sort of do its own ranking of, you know, what are the right documents that, that it should be working with.And again, like, you know, the intelligence level of a model six months ago, [00:21:00] it'd be just throwing a dart at like, I'm just, I'm gonna grab these seven files and I, I pray, I hope that that's the right answer. And something like an opus first four five, and now four six is like, oh, it's like, no, that one doesn't seem right relative to this question because I'm seeing some signal that is making that, you know, that's contradicting the document where it would normally be in the tree and who should have access.Like it's doing all of that kind of work for you. But like, it still doesn't work if you just have a total wasteland of data. Like, it's just not, it's just not possible. Partly ‘cause a human wouldn't even be able to do it. So basically if a, if a really, really smart human. Could not do that task in five or 10 minutes for a search retrieval type task.Look, you know, your agent's not gonna be able to do it any better. You see this all day long. SoContext Engineering and Search Limitsswyx: this touches on a thing that just passionate about it was just context engineering. I, I'm just gonna let you ramble or riff on, on context engineering. If, if, if there's anything like he, he did really good work on context fraud, which has really taken over as like the term that people use and the referenceAaron Levie: a hundred percent.We, we all we think about is, is the context rob problem. [00:22:00]Jeff Huber: Yeah, there's certainly a lot of like ranking considerations. Gentech surgery think is incredibly promising. Um, yeah, I was trying to generate a question though. I think I have a question right now. Swyx.Aaron Levie: Yeah, no, but like, like I think there was this moment, um, you know, like, I don't know, two years ago before, before we knew like where the, the gotchas were gonna be in ai and I think someone was like, was like, well, infinite context windows will just solve all of these problems and ‘cause you'll just, you'll just give the context window like all the data and.It's just like, okay, I mean, maybe in 2035, like this is a viable solution. First of all, it, it would just, it would just simply cost too much. Like we just can't give the model like the 5,000 documents that might be relevant and it's gonna read them all. And I've seen enough to, to start believing in crazy stuff.So like, I'm willing to just say, sure. Like in, in 10 years from now,swyx: never say, never, never.Aaron Levie: In, in 10 years from now, we'll have infinite context windows at, at a thousandth of the price of today. Like, let's just like believe that that's possible, but Right. We're in reality today. So today we have a context engineering [00:23:00] problem, which is, I got, I got, you know, 200,000 tokens that I can work with, or prob, I don't even know what the latest graph is before, like massive degradation.16. Okay. I have 60,000 tokens that I get to work with where I'm gonna get accurate information. That's not a lot of tokens for a corpus of 10 million documents that a knowledge worker might have across all of the teams and all the projects and all the people they work with. I have, I have 10 million documents.Which, you know, maybe is times five pages per document or something like that. I'm at 50 million pages of information and I have 60,000 tokens. Like, holy s**t. Yeah. This is like, how do I bridge the 50 million pages of information with, you know, the couple hundred that I get to work with in that, in that token window.Yeah. This is like, this is like such an interesting problem and that's why actually so much work is actually like, just like search systems and the databases and that layer has to just get so locked in, but models getting better and importantly [00:24:00] knowing when they've done a search, they found the wrong thing, they go back, they check their work, they, they find a way to balance sort of appeasing the user versus double checking.We have this one, we have this one test case where we ask the agent to go find. 10 pieces of information.swyx: Is this the complex work eval?Aaron Levie: Uh, this is actually not in the eval. This is, this is sort of just like we have a bunch of different, we have a bunch of internal benchmark kind of scenarios. Every time we, we update our agent, we have one, which is, I ask it to find all of our office addresses, and I give it the list of 10 offices that we have.And there's not one document that has this, maybe there should be, that would be a great example of the kind of thing that like maybe over time companies start to, you know, have these sort of like, what are the canonical, you know, kind of key areas of knowledge that we need to have. We don't seem to have this one document that says, here are all of our offices.We have a bunch of documents that have like, here's the New York office and whatever. So you task this agent and you, you get, you say, I need the addresses for these 10 offices. Okay. And by the way, if you do this on any, you know, [00:25:00] public chat model, the same outcome is gonna happen. But for a different kind of query, you give it, you say, I need these 10 addresses.How many times should the agent go and do its search before it decides whether or not, there's just no answer to this question. Often, and especially the, the, let's say lower tier models, it'll come back and it'll give you six of the 10 addresses. And it'll, and I'll just say I couldn't find the otherswyx: four.It, it doesn't know what It doesn't know. ItAaron Levie: doesn't know what It doesn't know. Yeah. So the model is just like, like when should it stop? When should it stop doing? Like should it, should it do that task for literally an hour and just keep cranking through? Maybe I actually made up an office location and it doesn't know that I made it up and I didn't even know that I made it up.Like, should it just keep, re should it read every single file in your entire box account until it, until it should exhaust every single piece of information.swyx: Expensive.Aaron Levie: These are the new problems that we have. So, you know, something like, let's say a new opus model is sort of like, okay, I'm gonna try these types of queries.I didn't get exactly what I wanted. I'm gonna try again. I'm gonna, at [00:26:00] some point I'm gonna stop searching. ‘cause I've determined that that no amount of searching is gonna solve this problem. I'm just not able to do it. And that judgment is like a really new thing that the model needs to be able to have.It's like, when should it give up on a task? ‘cause, ‘cause you just don't, it's a can't find the thing. That's the real world of knowledge, work problems. And this is the stuff that the coding agents don't have to deal with. Because they, it just doesn't like, like you're not usually asking it about, you're, you're always creating net new information coming right outta the model for the most part.Obviously it has to know about your code base and your specs and your documentation, but, but when you deploy an agent on all of your data that now you have all of these new problems that you're dealing withJeff Huber: our, uh, follow follow-up research to context ride is actually on a genetic search. Ah. Um, and we've like right, sort of stress tested like frontier models and their ability to search.Um, and they're not actually that good at searching. Right. Uh, so you're sort of highlighting this like explore, exploit.swyx: You're just say, Debbie, Donna say everything doesn't work. Like,Aaron Levie: well,Jeff Huber: somebody has to be,Aaron Levie: um, can I just throw out one more thing? Yeah. That is different from coding and, and the rest [00:27:00] of the knowledge work that I, I failed to mention.So one other kind of key point is, is that, you know, at the end of the day. Whether you believe we're in a slop apocalypse or, or whatever. At the end of the day, if you, if you build a working product at the end of, if you, if you've built a working solution that is ultimately what the customer is paying for, like whether I have a lot of slop, a little slop or whatever, I'm sure there's lots of code bases we could go into in enterprise software companies where it's like just crazy slop that humans did over a 20 year period, but the end customer just gets this little interface.They can, they can type into it, it does its thing. Knowledge work, uh, doesn't have that property. If I have an AI model, go generate a contract and I generate a contract 20 times and, you know, all 20 times it's just 3% different and like that I, that, that kind of lop introduces all new kinds of risk for my organization that the code version of that LOP didn't, didn't introduce.These are, and so like, so how do you constrain these models to just the part that you want [00:28:00] them to work on and just do the thing that you want them to do? And, and, you know, in engineering, we don't, you can't be disbarred as an engineer, but you could be disbarred as a lawyer. Like you can do the wrong medical thing In healthcare, you, there's no, there's no equivalent to that of engineering.Like, doswyx: you want there to be, because I've considered softwareJeff Huber: engineer. What's that? Civil engineering there is, right? NotAaron Levie: software civil engineer. Sure. Oh yeah, for sure. But like in any of our companies, you like, you know, you'll be forgiven if you took down the site and, and we, we will do a rollback and you'll, you'll be in a meeting, but you have not been disbarred as an engineer.We don't, we don't change your, you know, your computer science, uh, blameJeff Huber: degree, this postmortem.Aaron Levie: Yeah, exactly. Exactly. So, so, uh, now maybe we collectively as an industry need to figure out like, what are you liable for? Not legally, but like in a, in a management sense, uh, of these agents. All sorts of interesting problems that, that, that, uh, that have to come out.But in knowledge work, that's the real hostile environments that we're operating in. Hmm.swyx: I do think like, uh, a lot of the last year's, 2025 story was the rise of coding agents and I think [00:29:00] 2026 story is definitely knowledge work agents. Yes. A hundredAaron Levie: percent.swyx: Right. Like that would, and I think open claw core work are just the beginning.Yes. Like it's, the next one's gonna just gonna be absolute craziness.Aaron Levie: It it is. And, and, uh, and it's gonna be, I mean, again, like this is gonna be this, this wave where we, we are gonna try and bring as many of the practices from coding because that, that will clearly be the forefront, which is tell an agent to go do something and has an access to a set of resources.You need to be responsible for reviewing it at the end of the process. That to me is the, is the kind of template that I just think goes across knowledge, work and odd. Cowork is a great example. Open Closet's a great example. You can kind of, sort of see what Codex could become over time. These are some, some really interesting kind of platforms that are emerging.swyx: Okay. Um, I wanted to, we touched on evals a little bit. You had, you had the report that you're gonna go bring up and then I was gonna go into like, uh, boxes, evals, but uh, go ahead. Talk about your genetic search thing.Jeff Huber: Yeah. Mostly I think kinda a few of the insights. It's like number one frontier model is not good at search.Humans have this [00:30:00] natural explore, exploit trade off where we kinda understand like when to stop doing something. Also, humans are pretty good at like forgetting actually, and like pruning their own context, whereas agents are not, and actually an agent in their kind of context history, if they knew something was bad and they even, you could see in the trace the reason you trace, Hey, that probably wasn't a good idea.If it's still in the trace, still in the context, they'll still do it again. Uhhuh. Uh, and so like, I think pruning is also gonna be like, really, it's already becoming a thing, right? But like, letting self prune the con windowsswyx: be a big deal. Yeah. So, so don't leave the mistake. Don't leave the mistake in there.Cut out the mistake but tell it that you made a mistake in the past and so it doesn't repeat it.Jeff Huber: Yeah. But like cut it out so it doesn't get like distracted by it again. ‘cause really, you know, what is so, so it will repeat its mistake just because it's been, it's inswyx: theJeff Huber: context. It'sAaron Levie: in the context so much.That's a few shot example. Even if it, yeah.Jeff Huber: It's like oh thisAaron Levie: is a great thing to go try even ifJeff Huber: it didn't work.Aaron Levie: Yeah,Jeff Huber: exactly.Aaron Levie: SoJeff Huber: there's like a bunch of stuff there. JustAaron Levie: Groundhogs Day inside these models. Yeah. I'm gonna go keep doing the same wrongJeff Huber: thing. Covering sense. I feel like, you know, some creator analogy you're trying like fit a manifold in latent space, which kind is doing break program synthesis, which is kinda one we think about we're doing right.Like, you know, certain [00:31:00] facts might be like sort of overly pitting it. There are certain, you know, sec sectors of latent space and so like plug clean space. Yeah. And, uh, andswyx: so we have a bell, our editor as a bell every time you say that. SoJeff Huber: you have, you have to like remove those, likeswyx: you shoulda a gong like TPN or something.IfJeff Huber: we gong, you either remove those links to like kinda give it the freedom, kind of do what you need to do. So, but yeah. We'll, we'll release more soon. That'sAaron Levie: awesome.Jeff Huber: That'll, that'll be cool.swyx: We're a cerebral podcast that people listen to us and, and sort of think really deep. So yeah, we try to keep it subtle.Okay. We try to keep it.Aaron Levie: Okay, fine.Inside Agent Evalsswyx: Um, you, you guys do, you guys do have EVs, you talked about your, your office thing, but, uh, you've been also promoting APEX agents and complex work. Uh, yeah, whatever you, wherever you wanna take this just Yeah. How youAaron Levie: Apex is, is obviously me, core's, uh, uh, kind of, um, agent eval.We, we supported that by sort of. Opening up some data for them around how we kind of see these, um, data workspaces in, in the, you know, kind of regular economy. So how do lawyers have a workspace? How do investment bankers have a workspace? What kind of data goes into those? And so we, [00:32:00] we partner with them on their, their apex eval.Our own, um, eval is, it's actually relatively straightforward. We have a, a set of, of documents in a, in a range of industries. We give the agent previously did this as a one shot test of just purely the model. And then we just realized we, we need to, based on where everything's going, it's just gotta be more agentic.So now it's a bit more of a test of both our harness and the model. And we have a rubric of a set of things that has to get right and we score it. Um, and you're just seeing, you know, these incredible jumps in almost every single model in its own family of, you know, opus four, um, you know, sonnet four six versus sonnet four five.swyx: Yeah. We have this up on screen.Aaron Levie: Okay, cool. So some, you're seeing it somewhere like. I, I forget the to, it was like 15 point jump, I think on the main, on the overall,swyx: yes.Aaron Levie: And it's just like, you know, these incredible leaps that, that are starting to happen. Um,swyx: and OP doesn't know any, like any, it's completely held out from op.Aaron Levie: This is not in any, there's no public data which has, you know, Ben benefits and this is just a private eval that we [00:33:00] do, and then we just happen to show it to, to the world. Hmm. So you can't, you can't train against it. And I think it's just as representative of. It's obviously reasoning capabilities, what it's doing at, at, you know, kind of test time, compute capabilities, thinking levels, all like the context rot issues.So many interesting, you know, kind of, uh, uh, capabilities that are, that are now improvingswyx: one sector that you have. That's interesting.Industries and Datasetsswyx: Uh, people are roughly familiar with healthcare and legal, but you have public sector in there.Aaron Levie: Yeah.swyx: Uh, what's that? Like, what, what, what is that?Aaron Levie: Yeah, and, and we actually test against, I dunno, maybe 10 industries.We, we end up usually just cutting a few that we think have interesting gains. All extras, won a lot of like government type documents. Um,swyx: what is that? What is it? Government type documents?Aaron Levie: Government filings. Like a taxswyx: return, likeAaron Levie: a probably not tax returns. It would be more of what would go the government be using, uh, as data.So, okay. Um, so think about research that, that type of, of, of data sets. And then we have financial services for things like data rooms and what would be in an investment prospectus. Uhhuh,swyx: that one you can dog food.Aaron Levie: Yeah, exactly. Exactly. Yes. Yes. [00:34:00] So, uh, so we, we run the models, um, in now, you know, more of an agent mode, but, but still with, with kinda limited capacity and just try and see like on a, like, for like basis, what are the improvements?And, and again, we just continue to be blown away by. How, how good these models are getting.swyx: Yeah, I mean, I think every serious AI company needs something like that where like, well, this is the work we do. Here's our company eval. Yeah. And if you don't have it, well, you're not a serious AI company.Aaron Levie: There's two dimensions, right?So there's, there's like, how are the models improving? And so which models should you either recommend a customer use, which one should you adopt? But then every single day, we're making changes to our agents. And you need to knowswyx: if you regressed,Aaron Levie: if you know. Yeah. You know, I've been fully convinced that the whole agent observability and eval space is gonna be a massive space.Um, super excited for what Braintrust is doing, excited for, you know, Lang Smith, all the things. And I think what you're going to, I mean, this is like every enter like literally every enterprise right now. It's like the AI companies are the customers of these tools. Every enterprise will have this. Yeah, you'll just [00:35:00] have to have an eval.Of all of your work and like, we'll, you'll have an eval of your RFP generation, you'll have an eval of your sales material creation. You'll have an eval of your, uh, invoice processing. And, and as you, you know, buy or use new agentic systems, you are gonna need to know like, what's the quality of your, of your pipeline.swyx: Yeah.Aaron Levie: Um, so huge, huge market with agent evals.swyx: Yeah.Building the Agent Teamswyx: And, and you know, I'm gonna shout out your, your team a bit, uh, your CTO, Ben, uh, did a great talk with us last year. Awesome. And he's gonna come back again. Oh, cool. For World's Fair.Aaron Levie: Yep.swyx: Just talk about your team, like brag a little bit. I think I, I think people take these eval numbers in pretty charts for granted, but No, there, I mean, there's, there's lots of really smart people at work during all this.Aaron Levie: Biggest shout out, uh, is we have a, we have a couple folks at Dya, uh, Sidarth, uh, that, that kind of run this. They're like a, you know, kind of tag tag team duo on our evals, Ben, our CTO, heavily involved Yasha, head of ai, uh, you know, a bunch of folks. And, um, evals is one part of the story. And then just like the full, you know, kind of AI.An agent team [00:36:00] is, uh, is a, is a pretty, you know, is core to this whole effort. So there's probably, I don't know, like maybe a few dozen people that are like the epicenter. And then you just have like layers and layers of, of kind of concentric circles of okay, then there's a search team that supports them and an infrastructure team that supports them.And it's starting to ripple through the entire company. But there's that kind of core agent team, um, that's a pretty, pretty close, uh, close knit group.swyx: The search team is separate from the infra team.Aaron Levie: I mean, we have like every, every layer of the stack we have to kind of do, except for just pure public cloud.Um, but um, you know, we, we store, I don't even know what our public numbers are in, you know, but like, you can just think about it as like a lot of data is, is stored in box. And so we have, and you have every layer of the, of the stack of, you know, how do you manage the data, the file system, the metadata system, the search system, just all of those components.And then they all are having to understand that now you've got this new customer. Which is the agent, and they've been building for two types of customers in the past. They've been building for users and they've been building for like applications. [00:37:00] And now you've got this new agent user, and it comes in with a difference of it, of property sometimes, like, hey, maybe sometimes we should do embeddings, an embedding based, you know, kind of search versus, you know, your, your typical semantic search.Like, it's just like you have to build the, the capabilities to support all of this. And we're testing stuff, throwing things away, something doesn't work and, and not relevant. It's like just, you know, total chaos. But all of those teams are supporting the agent team that is kind of coming up with its requirements of what, what do we need?swyx: Yeah. No, uh, we just came from, uh, fireside chat where you did, and you, you talked about how you're doing this. It's, it's kind of like an internal startup. Yeah. Within the broader company. The broader company's like 3000 people. Yeah. But you know, there's, there's a, this is a core team of like, well, here's the innovation center.Aaron Levie: Yeah.swyx: And like that every company kind of is run this way.Aaron Levie: Yeah. I wanna be sensitive. I don't call it the innovation center. Yeah. Only because I think everybody has to do innovation. Um, there, there's a part of the, the, the company that is, is sort of do or die for the agent wave.swyx: Yeah.Aaron Levie: And it only happens to be more of my focus simply because it's existential that [00:38:00] we get it right.swyx: Yeah.Aaron Levie: All of the supporting systems are necessary. All of the surrounding adjacent capabilities are necessary. Like the only reason we get to be a platform where you'd run an agent is because we have a security feature or a compliance feature, or a governance feature that, that some team is working on.But that's not gonna be the make or break of, of whether we get agents right. Like that already exists and we need to keep innovating there. I don't know what the right, exact precise number is, but it's not a thousand people and it's not 10 people. There's a number of people that are like the, the kind of like, you know, startup within the company that are the make or break on everything related to AI agents, you know, leveraging our platform and letting you work with your data.And that's where I spend a lot of my time, and Ben and Yosh and Diego and Teri, you know, these are just, you know, people that, that, you know, kind of across the team. Are working.swyx: Yeah. Amazing.Read Write Agent WorkflowsJeff Huber: How do you, how do you think about, I mean, you talked a lot about like kinda read workflows over your box data. Yep.Right. You know, gen search questions, queries, et cetera. But like, what about like, write or like authoring workflows?Aaron Levie: Yes. I've [00:39:00] already probably revealed too much actually now that I think about it. So, um, I've talked about whatever,Jeff Huber: whatever you can.Aaron Levie: Okay. It's just us. It's just us. Yeah. Okay. Of course, of course.So I, I guess I would just, uh, I'll make it a little bit conceptual, uh, because again, I've already, I've already said things that are not even ga but, but we've, we've kinda like danced around it publicly, so I, yeah, yeah. Okay. Just like, hopefully nobody watches this, um, episode. No.swyx: It's tidbits for the Heidi engaged to go figure out like what exactly, um, you know, is, is your sort of line of thinking.Sure. They can connect the dots.Aaron Levie: Yeah. So, so I would say that, that, uh, we, you know, as a, as a place where you have your enterprise content, there's a use case where I want to, you know, have an agent read that data and answer questions for me. And then there's a use case where I want the agent to create something.And use the file system to create something or store off data that it's working on, or be able to have, you know, various files that it's writing to about the work it's doing. So we do see it as a total read write. The harder problem has so far been the read only because, because again, you have that kind of like 10 [00:40:00] million to one ratio problem, whereas rights are a lot of, that's just gonna come from the model and, and we just like, we'll just put it in the file system and kinda use it.So it's a little bit of a technically easier problem, but the only part that's like, not necessarily technically hard, it is just like it's not yet perfected in the state of the ecosystem is, you know, building a beautiful PowerPoint presentation. It's still a hard problem for these models. Like, like we still, you know, like, like these formats are just, we're not built for.They'reswyx: working on it.Aaron Levie: They're, they're working on it. Everybody's working on it.swyx: Every launch is like, well, we do PowerPoint now.Aaron Levie: We're getting, yeah, getting a lot, getting a lot of better each time. But then you'll do this thing where you'll ask the update one slide and all of a sudden, like the fonts will be just like a little bit different, you know, on two of the slides, or it moved, you know, some shape over to the left a little bit.And again, these are the kind of things that, like in code, obviously you could really care about if you really care about, you know, how beautiful is the code, but at the end, user doesn't notice all those problems and file creation, the end user instantly sees it. You're [00:41:00] like, ah, like paragraph three, like, you literally just changed the font on me.Like it's a totally different font and like midway through the document. Mm-hmm. Those are the kind of things that you run into a lot of in the, in the content creation side. So, mm-hmm. We are gonna have native agents. That do all of those things, they'll be powered by the leading kind of models and labs.But the thing that I think is, is probably gonna be a much bigger idea over time is any agent on any system, again, using Box as a file system for its work, and in that kind of scenario, we don't necessarily care what it's putting in the file system. It could put its memory files, it could put its, you know, specification, you know, documents.It could put, you know, whatever its markdown files are, or it could, you know, generate PDFs. It's just like, it's a workspace that is, is sort of sandboxed off for its work. People can collaborate into it, it can share with other people. And, and so we, we were thinking a lot about what's the right, you know, kind of way to, to deliver that at scale.Docs Graphs and Founder Modeswyx: I wanted to come into sort of the sort of AI transformation or AI sort of, uh, operations things. [00:42:00] Um, one of the tweets that you, that you wanted to talk about, this is just me going through your tweets, by the way. Oh, okay. I mean, like, this is, you readAaron Levie: one by one,swyx: you're the, you're the easiest guest to prep for because you, you already have like, this is the, this is what I'm interested in.I'm like, okay, well, areAaron Levie: we gonna get to like, like February, January or something? Where are we in the, in the timelines? How far back are we going?swyx: Can you, can you describe boxes? A set of skills? Right? Like that, that's like, that's like one of the extremes of like, well if you, you just turn everything into a markdown file.Yeah. Then your agent can run your company. Uh, like you just have to write, find the right sequence of words toAaron Levie: Yes.swyx: To do it.Aaron Levie: Sorry, isthatswyx: the question? So I think the question is like, what if we documented everything? Yes. The way that you exactly said like,Aaron Levie: yes.swyx: Um, let's get all the Fortune five hundreds, uh, prepared for agents.Yes. And like, you know, everything's in golden and, and nicely filed away and everything. Yes. What's missing? Like, what's left, right? LikeAaron Levie: Yeah.swyx: You've, you've run your company for a decade. LikeAaron Levie: Yeah. I think the challenge is that, that that information changes a week later. And because something happened in the market for that [00:43:00] customer, or us as a company that now has to go get updated, and so these systems are living and breathing and they have to experience reality and updates to reality, which right now is probably gonna be humans, you know, kinda giving those, giving them the updates.And, you know, there is this piece about context graphs as as, uh, that kinda went very viral. Yeah. And I, I, I was like a, i, I, I thought it was super provocative. I agreed with many parts of it. I disagree with a few parts around. You know, it's not gonna be as easy as as just if we just had the agent traces, then we can finally do that work because there's just like, there's so much more other stuff that that's happening that, that we haven't been able to capture and digitize.And I think they actually represented that in the piece to be clear. But like there's just a lot of work, you know, that that has to, you just can't have only skills files, you know, for your company because it's just gonna be like, there's gonna be a lot of other stuff that happens. Yeah. Change over time.Yeah. Most companies are practically apprenticeships.swyx: Most companies are practically apprenticeships. LikeJeff Huber: every new employee who joins the team, [00:44:00] like you span one to three months. Like ramping them up.Aaron Levie: Yes. AllJeff Huber: that tat knowledgeAaron Levie: isJeff Huber: not written down.Aaron Levie: Yes.Jeff Huber: But like, it would have to be if you wanted to like give it to an Asian.Right. And so like that seems to me like to beAaron Levie: one is I think you're gonna see again a premium on companies that can document this. Mm-hmm. Much. There'll be a huge premium on that because, because you know, can you shorten that three month ramp cycle to a two week ramp cycle? That's an instant productivity gain.Can you re dramatically reduce rework in the organization because you've documented where all the stuff is and where the answers are. Can you make your average employee as good as your 90th percentile employee because you've captured the knowledge that's sort of in the heads of, of those top employees and make that available.So like you can see some very clear productivity benefits. Mm-hmm. If you had a company culture of making sure you know your information was captured, digitized, put in a format that was agent ready and then made available to agents to work with, and then you just, again, have this reality of like add a 10,000 person [00:45:00] company.Mapping that to the, you know, access structure of the company is just a hard problem. Is like, is like, yeah, well, you just, not every piece of information that's digitized can be shared to everybody. And so now you have to organize that in a way that actually works. There was a pretty good piece, um, this, this, uh, this piece called your company as a file is a file system.I, did you see that one?swyx: Nope.Aaron Levie: Uh, yes. You saw it. Yeah. And, and, uh, I actually be curious your thoughts on it. Um, like, like an interesting kind of like, we, we agree with it because, because that's how we see the world and, uh,swyx: okay. We, we have it up on screen. Oh,Aaron Levie: okay. Yeah. But, but it's all about basically like, you know, we've already, we, we, we already organized in this kind of like, you know, permission structure way.Uh, and, and these are the kind of, you know, natural ways that, that agents can now work with data. So it's kind of like this, this, you know, kind of interesting metaphor, but I do think companies will have to start to think about how they start to digitize more, more of that data. What was your take?Jeff Huber: Yeah, I mean, like the company's probably like an acid compliant file system.Aaron Levie: Uh,Jeff Huber: yeah. Which I'm guessing boxes, right? So, yeah. Yes.swyx: Yeah. [00:46:00]Jeff Huber: Which you have a great piece on, but,swyx: uh, yeah. Well, uh, I, I, my, my, my direction is a little bit like, I wanna rewind a little bit to the graph word you said that there, that's a magic trigger word for us. I always ask what's your take on knowledge graphs?Yeah. Uh, ‘cause every, especially at every data database person, I just wanna see what they think. There's been knowledge graphs, hype cycles, and you've seen it all. So.Aaron Levie: Hmm. I actually am not the expert in knowledge graphs, so, so that you might need toswyx: research, you don't need to be an expert. Yeah. I think it's just like, well, how, how seriously do people take it?Yeah. Like, is is, is there a lot of potential in the, in the HOVI?Aaron Levie: Uh, well, can I, can I, uh, understand first if it's, um, is this a loaded question in the sense of are you super pro, super con, super anti medium? Iswyx: see pro, I see pros and cons. Okay. Uh, but I, I think your opinion should be independent of mine.Aaron Levie: Yeah. No, no, totally. Yeah. I just want to see what I'm stepping into.swyx: No, I know. It's a, and it's a huge trigger word for a lot of people out Yeah. In our audience. And they're, they're trying to figure out why is that? Because whyAaron Levie: is this such aswyx: hot item for them? Because a lot of people get graph religion.And they're like, everything's a graph. Of course you have to represent it as a graph. Well, [00:47:00] how do you solve your knowledge? Um, changing over time? Well, it's a graph.Aaron Levie: Yeah.swyx: And, and I think there, there's that line of work and then there's, there's a lot of people who are like, well, you don't need it. And both are right.Aaron Levie: Yeah. And what do the people who say you don't need it, what are theyswyx: arguing for Mark down files. Oh, sure, sure. Simplicity.Aaron Levie: Yeah.swyx: Versus it's, it's structure versus less structure. Right. That's, that's all what it is. I do.Aaron Levie: I think the tricky thing is, um, is, is again, when this gets met with real humans, they're just going to their computer.They're just working with some people on Slack or teams. They're just sharing some data through a collaborative file system and Google Docs or Box or whatever. I certainly like the vision of most, most knowledge graph, you know, kind of futuristic kind of ways of thinking about it. Uh, it's just like, you know, it's 2026.We haven't seen it yet. Kind of play out as as, I mean, I remember. Do you remember the, um, in like, actually I don't, I don't even know how old you guys are, but I'll for, for to show my age. I remember 17 years ago, everybody thought enterprises would just run on [00:48:00] Wikis. Yeah. And, uh, confluence and, and not even, I mean, confluence actually took off for engineering for sure.Like unquestionably. But like, this was like everything would be in the w. And I think based on our, uh, our, uh, general style of, of, of what we were building, like we were just like, I don't know, people just like wanna workspace. They're gonna collaborate with other people.swyx: Exactly. Yeah. So you were, you were anti-knowledge graph.Aaron Levie: Not anti, not anti. Soswyx: not nonAaron Levie: I'm not, I'm not anti. ‘cause I think, I think your search system, I just think these are two systems that probably, but like, I'm, I'm not in any religious war. I don't want to be in anybody's YouTube comments on this. There's not a fight for me.swyx: We, we love YouTube comments. We're, we're, we're get into comments.Aaron Levie: Okay. Uh, but like, but I, I, it's mostly just a virtue of what we built. Yeah. And we just continued down that path. Yeah.swyx: Yeah.Aaron Levie: And, um, and that, that was what we pursued. But I'm not, this is not a, you know, kind of, this is not a, uh, it'sswyx: not existential for you. Great.Aaron Levie: We're happy to plug into somebody else's graph.We're happy to feed data into it. We're happy for [00:49:00] agents to, to talk to multiple systems. Not, not our fight.swyx: Yeah.Aaron Levie: But I need your answer. Yeah. Graphs or nerd Snipes is very effective nerd.swyx: See this is, this is one, one opinion and then I've,Jeff Huber: and I think that the actual graph structure is emergent in the mind of the agent.Ah, in the same way it is in the mind of the human. And that's a more powerful graph ‘cause it actually involved over time.swyx: So don't tell me how to graph. I'll, I'll figure it out myself. Exactly. Okay. All right. AndJeff Huber: what's yours?swyx: I like the, the Wiki approach. Uh, my, I'm actually
⬥EPISODE NOTES⬥ The security operations center has always been a battleground of volume, velocity, and human endurance. Analysts have long faced the impossible math of too many alerts, too few hours, and too much at stake. For years, the industry promised automation would change that equation -- but the technology was never quite ready to deliver. That moment, according to Richard Stiennon, has now arrived. Stiennon, Chief Research Analyst at IT-Harvest, has spent two decades tracking every corner of the cybersecurity vendor landscape. His data now shows more than 61 net-new SOC automation vendors -- companies that did not exist a few years ago -- built from the ground up to replace the work of tier-one, tier-two, and tier-three analysts. Some of these vendors launched in January 2024 and reached $1 million in ARR by April. By the end of 2025, several were reporting $3 million ARR. These are not incremental improvements. They represent a structural shift in how security operations can be run. What makes this generation of SOC automation different from earlier SIEM and SOAR tooling is scope and autonomy. The value proposition is blunt: 100% alert triage, 24 hours a day, 7 days a week -- with automated case building, threat investigation, and response actions including machine isolation and reimaging. Stiennon points to a CISO he met, speaking under Chatham House rules, who disclosed that a large enterprise had already eliminated its entire human SOC team. He predicts that disclosure will go public before long. The conversation also explores the business context question that security leaders frequently wrestle with: are these AI-driven SOC tools operating with a narrow cyber mandate, potentially optimizing for security metrics at the expense of business continuity? Stiennon pushes back on that concern, arguing that large language models are already trained on the full breadth of human knowledge -- they understand business context at a level that exceeds most organizations' internal documentation. The more pressing risk, he suggests, is not that AI will act outside business intent, but that organizations will move too slowly to benefit. Waiting six months for a proof-of-concept report while spending a million dollars on human SOC operations is not due diligence -- it is opportunity cost. The conversation also touches on data privacy in AI-driven security, the role of federated learning and fully homomorphic encryption for compliance-sensitive environments, and what security leaders can do today to evaluate and accelerate their own adoption timeline. Stiennon will be at RSA Conference 2026 with his new book, Guardians of the Machine Age: Why AI Security Will Define Digital Defense, continuing to make the case for a field that is moving faster than most organizations are prepared to acknowledge. ⬥GUEST⬥ Richard Stiennon, Chief Research Analyst at IT-Harvest | Website: https://it-harvest.com/ On LinkedIn: https://www.linkedin.com/in/stiennon/ ⬥HOST⬥ Sean Martin, Co-Founder at ITSPmagazine, Studio C60, and Host of Redefining CyberSecurity Podcast & Music Evolves Podcast | Website: https://www.seanmartin.com/ ⬥RESOURCES⬥ IT-Harvest | https://it-harvest.com/ Richard Stiennon on LinkedIn | https://www.linkedin.com/in/stiennon/ Guardians of the Machine Age: Why AI Security Will Define Digital Defense (Richard Stiennon) | Available via IT-Harvest and major booksellers RSAC Conference 2026 Coverage on ITSPmagazine | https://www.itspmagazine.com/rsac-2026-conference-san-francisco-usa-cybersecurity-event-infosec-conference-coverage The Future of Cybersecurity Newsletter | https://www.linkedin.com/newsletters/7108625890296614912/ More Redefining CyberSecurity Podcast episodes | https://www.seanmartin.com/redefining-cybersecurity-podcast Redefining CyberSecurity Podcast on YouTube | https://www.youtube.com/playlist?list=PLnYu0psdcllS9aVGdiakVss9u7xgYDKYq ⬥ADDITIONAL INFORMATION⬥ On Podcast: https://www.seanmartin.com/redefining-cybersecurity-podcast On YouTube: https://www.youtube.com/playlist?list=PLnYu0psdcllS9aVGdiakVss9u7xgYDKYq Newsletter: https://itspm.ag/future-of-cybersecurity Contact Sean: https://www.seanmartin.com/ ⬥KEYWORDS⬥ richard stiennon, it-harvest, sean martin, soc automation, ai security, security operations center, threat detection, autonomous response, alert triage, security operations, cybersecurity vendors, ai agents, large language models, federated learning, siem, soar, redefining cybersecurity, cybersecurity podcast, redefining cybersecurity podcast Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
✅ Check out Investorlift Here: https://investorlift.pro/4byViou In the high-stakes world of tech and real estate, most startups are a "death sentence," with only 1 in 10,000 actually reaching a major exit. In this episode, Jesse pulls back the curtain on how he went from earning less than $40k a year at age 29 to building a software empire that generated $120 million in lifetime revenue—all without taking a single dollar of Venture Capital.We dive deep into the "Infinite Money Glitch" of skip tracing, the brutal reality of losing $10 million in ARR in just three months, and why Jesse believes raising VC money makes you an employee rather than an owner. Plus, Jesse shares the discipline required to not only scale a 250-person company but also to lose 100 pounds and escape the "mental prison" of being out of shape while successful.✅ Check out Investorlift Here: https://investorlift.pro/4byViou****TimeStamps****00:00 - Intro & The Rolex "Trophy" 01:26 - The Reality of Selling Your Company 03:10 - Jesse's Origins: From $40k/Year to Real Estate 06:11 - Meeting the Partners: Andy & Evo 07:11 - Batch Skip Tracing: The "Infinite Money Glitch" 09:18 - Pivoting to SaaS: The Birth of Batch Leads 11:15 - Managing 250 People & Dealing with Bloat 13:18 - Reaching $120 Million in Lifetime Revenue 16:17 - The $10M Loss: Navigating Market Shifts 17:55 - Post-Exit Strategy & Liquidity 21:01 - Why VC is the "Next Fool" Syndrome 23:43 - Partnerships: Protecting Yourself with "Kinship" Clauses 33:41 - Bootstrapping vs. Raising Money 36:14 - A Contrarian Take on Sam Altman & OpenAI 39:23 - The Solopreneur vs. The Committee 45:15 - Real Estate Legend: The Doug Hopkins Story 50:03 - Physical Transformation: Losing 100 Pounds 56:14 - SOPs for Health: Meal Prep & Discipline 59:00 - One Piece of Advice: The Reward is the JourneyFollow Us!Robert Wensley: https://www.instagram.com/robertwensley/Zack Kepes: https://www.instagram.com/zakventures/Jesse Burrell: https://www.instagram.com/jesseburrellInvestorlift: https://www.instagram.com/investorlift/
⬥EPISODE NOTES⬥ The security operations center has always been a battleground of volume, velocity, and human endurance. Analysts have long faced the impossible math of too many alerts, too few hours, and too much at stake. For years, the industry promised automation would change that equation -- but the technology was never quite ready to deliver. That moment, according to Richard Stiennon, has now arrived. Stiennon, Chief Research Analyst at IT-Harvest, has spent two decades tracking every corner of the cybersecurity vendor landscape. His data now shows more than 61 net-new SOC automation vendors -- companies that did not exist a few years ago -- built from the ground up to replace the work of tier-one, tier-two, and tier-three analysts. Some of these vendors launched in January 2024 and reached $1 million in ARR by April. By the end of 2025, several were reporting $3 million ARR. These are not incremental improvements. They represent a structural shift in how security operations can be run. What makes this generation of SOC automation different from earlier SIEM and SOAR tooling is scope and autonomy. The value proposition is blunt: 100% alert triage, 24 hours a day, 7 days a week -- with automated case building, threat investigation, and response actions including machine isolation and reimaging. Stiennon points to a CISO he met, speaking under Chatham House rules, who disclosed that a large enterprise had already eliminated its entire human SOC team. He predicts that disclosure will go public before long. The conversation also explores the business context question that security leaders frequently wrestle with: are these AI-driven SOC tools operating with a narrow cyber mandate, potentially optimizing for security metrics at the expense of business continuity? Stiennon pushes back on that concern, arguing that large language models are already trained on the full breadth of human knowledge -- they understand business context at a level that exceeds most organizations' internal documentation. The more pressing risk, he suggests, is not that AI will act outside business intent, but that organizations will move too slowly to benefit. Waiting six months for a proof-of-concept report while spending a million dollars on human SOC operations is not due diligence -- it is opportunity cost. The conversation also touches on data privacy in AI-driven security, the role of federated learning and fully homomorphic encryption for compliance-sensitive environments, and what security leaders can do today to evaluate and accelerate their own adoption timeline. Stiennon will be at RSA Conference 2026 with his new book, Guardians of the Machine Age: Why AI Security Will Define Digital Defense, continuing to make the case for a field that is moving faster than most organizations are prepared to acknowledge. ⬥GUEST⬥ Richard Stiennon, Chief Research Analyst at IT-Harvest | Website: https://it-harvest.com/ On LinkedIn: https://www.linkedin.com/in/stiennon/ ⬥HOST⬥ Sean Martin, Co-Founder at ITSPmagazine, Studio C60, and Host of Redefining CyberSecurity Podcast & Music Evolves Podcast | Website: https://www.seanmartin.com/ ⬥RESOURCES⬥ IT-Harvest | https://it-harvest.com/ Richard Stiennon on LinkedIn | https://www.linkedin.com/in/stiennon/ Guardians of the Machine Age: Why AI Security Will Define Digital Defense (Richard Stiennon) | Available via IT-Harvest and major booksellers RSAC Conference 2026 Coverage on ITSPmagazine | https://www.itspmagazine.com/rsac-2026-conference-san-francisco-usa-cybersecurity-event-infosec-conference-coverage The Future of Cybersecurity Newsletter | https://www.linkedin.com/newsletters/7108625890296614912/ More Redefining CyberSecurity Podcast episodes | https://www.seanmartin.com/redefining-cybersecurity-podcast Redefining CyberSecurity Podcast on YouTube | https://www.youtube.com/playlist?list=PLnYu0psdcllS9aVGdiakVss9u7xgYDKYq ⬥ADDITIONAL INFORMATION⬥ On Podcast: https://www.seanmartin.com/redefining-cybersecurity-podcast On YouTube: https://www.youtube.com/playlist?list=PLnYu0psdcllS9aVGdiakVss9u7xgYDKYq Newsletter: https://itspm.ag/future-of-cybersecurity Contact Sean: https://www.seanmartin.com/ ⬥KEYWORDS⬥ richard stiennon, it-harvest, sean martin, soc automation, ai security, security operations center, threat detection, autonomous response, alert triage, security operations, cybersecurity vendors, ai agents, large language models, federated learning, siem, soar, redefining cybersecurity, cybersecurity podcast, redefining cybersecurity podcast Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
The Twenty Minute VC: Venture Capital | Startup Funding | The Pitch
Monday has been hit harder than almost any other public SaaS company. With $1.3BN in ARR, the company is valued at just $3.8BN; a more than 60% fall since IPO. Today, Eran Zinman, Monday's CEO joins Harry Stebbings in the hotseat to walkthrough six of the biggest threats to Monday's business; what is real, what is not and what are the unknowns. AGENDA: 05:47 Six Threats Monday Faces Today 07:04 Threat #1: Vibe Coding: Will Companies Vibe Code Everything 11:24 Threat #2: Will OpenAI and Anthropic Own the Application Layer 13:52 Threat #3: Will Agents Turn Monday and Salesforce into a Database 18:43 Why is Monday Adding 15% Headcount When Everyone is Cutting? 21:40 How Monday is Using AI to be More Efficient 27:49 What Happens to Seat Pricing? What Comes Next? 34:17 What No One Sees About Enterprise AI Adoption 37:13 How Google AI Overview Smashed 10% of our Customer Acquisition 38:49 If Bullish on Monday, Why Has Eran Not Bought More Stock… 40:38 How to Manage Internal Morale When Stock is Down 60% 44:08 Do Private Companies Have Advantages Public Companies Do Not Have 47:28 With $1.5BN in Cash, Why is Eran Not Buying More Companies… 53:30 What is the Most Offensive Bet Eran Would Like to Take? 57:13 Quickfire: Marriage, Biggest Short, Mentors
Citrini Research claims AI agents will replace white-collar jobs by 2028, triggering a massive economic crash (and repricing of SaaS stocks). Sam Jacobs, AJ Bruno, and Asad Zaman analyze the validity of this thesis and the immediate impact on enterprise valuation multiples. The discussion moves to the practical realities of the innovator's dilemma, specifically how legacy software companies must cannibalize their own revenue to survive. They cover strategies for GTM transformation, the loss of pricing power in traditional SaaS, and why Gong's pivot to "Chief Revenue Architect" signals a deeper identity crisis in the market. Key Takeaways: * The hardest part of adapting to AI is destroying your current margins. Sam Jacobs argues that leaders get emotionally attached to ARR, noting that "the hardest part of the innovator's dilemma is price... the only way to get out of it is to... go towards a worse business" in the short term. * Pivoting sounds great on paper, but is far harder in practice. Asad Zaman highlights the operational difficulty of telling investors about the actual steps involved; e.g. "I'm going to do a reorg and I'm then going to change my strategy that's actually going to increase churn... That's a war at the board level." * Title changes don't fix structural issues. Asad Zaman and Sam Jacobs advise revenue leaders against accepting Gong's new "Chief Revenue Architect" title because "it's going to hurt your career moving forward... This sounds like you were demoted to rev ops to me." Your Hosts: Host: Sam Jacobs Host: AJ Bruno Host: Asad Zaman Topline is more than a Podcast! Subscribe to Topline Newsletter: https://www.joinpavilion.com/topline-newsletter Watch on the YouTube channel: https://www.youtube.com/@TOPLINE-Media Join the free Topline Slack channel to connect with 600+ revenue leaders to keep the conversation going beyond the podcast: https://www.joinpavilion.com/topline-slack Chapters: 00:00 Intro 02:04 The Citrini Report Examined 07:05 Startups vs. Innovator's Dilemma 12:35 SaaS Valuation Repricing 15:29 Losing Pricing Leverage to AI 21:29 Is White Collar Work Dead? 25:10 Margin Compression Strategy 31:17 Restructuring Engineering Teams 35:09 Microsoft's Product Pivot 39:54 How AI Improves CEO Workflow 44:50 Gong's Chief Revenue Architect 51:17 Why the CRO Title Matters 55:14 AI Predictions Looking Ahead
Jim Caci, CFO of AvePoint (AVPT), highlights their latest quarterly results, calling them a “strong end to a strong year.” AvePoint is a data protection platform. He discusses how they are prioritizing profit and working in an AI world. He notes that 50% of their ARR is outside of America, giving them plenty of international exposure and creating “balance and visibility.” Jim talks about how AvePoint is making AI into an accelerator rather than a risk.======== Schwab Network ========Empowering every investor and trader, every market day.Options involve risks and are not suitable for all investors. Before trading, read the Options Disclosure Document. http://bit.ly/2v9tH6DSubscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about
Kevin Rubin, CFO of Zscaler (ZS), talks about his company's earnings which shows a 25% ARR increase. With AI accelerating year-over-year, Kevin talks to investors about ways ZScaler is using the evolving tech to protect against outside AI risks. He later notes the company's acquisitions and long-term growth opportunities they present. ======== Schwab Network ========Empowering every investor and trader, every market day.Options involve risks and are not suitable for all investors. Before trading, read the Options Disclosure Document. http://bit.ly/2v9tH6DSubscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about
Anna Tsymbalist, Head of Account-Based Marketing (ABM) at Influ2, explores the rapid rise of ABM and its impact on modern B2B marketing. She unpacks the evolution of Influ2's platform, highlighting how it enables marketers to target specific decision-makers, build dynamic audiences, and track contact-level intent and engagement with precision. Anna explains why this shift—from account-level to person-level marketing—has been critical for delivering more relevant, measurable campaigns. Throughout the conversation, Anna emphasizes that successful ABM hinges on tight alignment between marketing and sales, long-term strategy, and a deep understanding of buyer behavior. She also discusses common pitfalls, such as over-reliance on intent data and lack of cross-team coordination. About Influ2 Influ2 is a B2B marketing platform built to bring precision and transparency to account-based marketing. Instead of targeting entire accounts, Influ2 enables marketers to reach specific decision-makers within buying committees, delivering highly personalized ads and tracking engagement at the individual level. By connecting marketing activities directly to sales outcomes, Influ2 helps teams align more effectively, optimize campaigns with real data, and drive measurable revenue impact. With Influ2, you can act on contact-level intent, reach specific buyers with ads, and make the revenue impact clear. 180+ enterprises and mid-market companies worldwide, including industry leaders such as Capgemini, AppsFlyer, and Hexaware, love the Influ2 technology. About Anna Tsymbalist Anna's expertise has fueled 123% growth in ABM-generated revenue at Influ2, and contributed to a $52.5M Series B fundraising round at Shelf, alongside a year of 4x ARR growth. Anna is passionate about data-driven ABM campaigns that convert top-tier accounts. Time Stamps 00:00:17 - Guest Introduction: Anna Tsymbalist 00:04:12 - Influ2 Overview and Its Role in ABM 00:04:30 - Challenges in ABM and the Need for Precision 00:08:07 - Contact-Level Targeting vs. Account-Level Targeting 00:12:39 - Key Elements for Successful ABM Campaigns 00:15:03 - The Importance of Data and Timing in ABM 00:17:57 - Common Mistakes in ABM Campaigns 00:26:18 - Best Marketing Advice Received 00:27:13 - Advice for New Marketing Graduates Quotes "ABM is like this interesting mixture of strategic campaigns, demand gen and content, basically.” Anna Tsymbalist, Head of Account Based Marketing at Influ2. "Human behavior is at the core of any purchase. And that's what I always keep in mind that people are people and they're going to be behaving the way people behave." Anna Tsymbalist, Head of Account Based Marketing at Influ2. “ABM is not just a marketing initiative. So ABM can't be something that a couple of marketers are doing in their free time because it's just not going to work that way.” Anna Tsymbalist, Head of Account Based Marketing at Influ2 Follow Anna: Anna Tsymbalist on LinkedIn: https://www.linkedin.com/in/anna-tsymbalist Influ2 website: https://www.influ2.com/ Influ2 on LinkedIn: https://www.linkedin.com/company/influ2/ Follow Mike: Mike Maynard on LinkedIn: https://www.linkedin.com/in/mikemaynard/ Napier website: https://www.napierb2b.com/ Napier LinkedIn: https://www.linkedin.com/company/napier-partnership-limited/ If you enjoyed this episode, be sure to subscribe to our for more discussions about the latest in Marketing B2B Tech and connect with us on social media to stay updated on upcoming episodes. We'd also appreciate it if you could leave us a review on your favorite podcast platform. Want more? Check out Napier's other podcast - The Marketing Automation Moment: https://podcasts.apple.com/ua/podcast/the-marketing-automation-moment-podcast/id1659211547
En aquel tiempo, Jesús dijo a sus discípulos: “Les aseguro que si su justicia no es mayor que la de los escribas y fariseos, ciertamente no entrarán ustedes en el Reino de los cielos.Han oído que se dijo a los antiguos: No matarás y el que mate será llevado ante el tribunal. Pero yo les digo: Todo el que se enoje con su hermano, será llevado también ante el tribunal; el que insulte a su hermano, será llevado ante el tribunal supremo, y el que lo desprecie, será llevado al fuego del lugar de castigo.Por lo tanto, si cuando vas a poner tu ofrenda sobre el altar, te acuerdas allí mismo de que tu hermano tiene alguna queja contra ti, deja tu ofrenda junto al altar y ve primero a reconciliarte con tu hermano, y vuelve luego a presentar tu ofrenda.Arréglate pronto con tu adversario, mientras vas con él por el camino; no sea que te entregue al juez, el juez al policía y te metan a la cárcel. Te aseguro que no saldrás de allí hasta que hayas pagado el último centavo”.Mateo 5,20-26
“Ve primero a reconciliarte con tu hermano.”Del santo Evangelio según san Mateo: 5, 20-26.Lectura y reflexión: Pbro. Emanuel Álvarez Ceja.En aquel tiempo, Jesús dijo a sus discípulos: «Les aseguro que si su justicia no es mayor que la de los escribas y fariseos, ciertamente no entrarán ustedes en el Reino de los cielos.Han oído que se dijo a los antiguos: No matarás y el que mate será llevado ante el tribunal. Pero yo les digo: Todo el que se enoje con su hermano, será llevado también ante el tribunal; el que insulte a su hermano, será llevado ante el tribunal supremo, y el que lo desprecie, será llevado al fuego del lugar de castigo.Por lo tanto, si cuando vas a poner tu ofrenda sobre el altar, te acuerdas allí mismo de que tu hermano tiene alguna queja contra ti, deja tu ofrenda junto al altar y ve primero a reconciliarte con tu hermano, y vuelve luego a presentar tu ofrenda.Arréglate pronto con tu adversario, mientras vas con él por el camino; no sea que te entregue al juez, el juez al policía y te metan a la cárcel. Te aseguro que no saldrás de allí hasta que hayas pagado el último centavo».Palabra del Señor. Gloria a ti, Señor Jesús.
Nasiru Ibrahim — an architect from Nigeria and a new adventure rider — sets out on his first true motorcycle journey with a simple idea: ride his Yamaha Ténéré to the Ténéré Desert. It's an ambitious first trip, fueled by equal parts curiosity and confidence. Heading north through regions where the language and culture feel familiar, he anticipates the usual challenges — long distances, fatigue, border crossings, and the uncertainties of travelling solo. Instead, a routine stop in a small desert town leads to his arrest and detention in a politically tense region. What follows is a two-week ordeal far from home, as he navigates uncertainty, bureaucracy, and the stark realization of how quickly an adventure can take an unexpected turn.
La catequesis del dìa de Tiziana, Apòstol de la Vida Interior
+ Del Evangelio según San Mateo +En aquel tiempo, Jesús dijo a sus discípulos: "Les aseguro que si su justicia no es mayor que la de los escribas y fariseos, ciertamente no entrarán ustedes en el Reino de los cielos.Han oído ustedes que se dijo a los antiguos: No matarás y el que mate será llevado ante el tribunal. Pero yo les digo: Todo el que se enoje con su hermano, será llevado también ante el tribunal; el que insulte a su hermano, será llevado ante el tribunal supremo, y el que lo desprecie, será llevado al fuego del lugar de castigo.Por lo tanto, si cuando vas a poner tu ofrenda sobre el altar, te acuerdas allí mismo de que tu hermano tiene alguna queja contra ti, deja tu ofrenda junto al altar y ve primero a reconciliarte con tu hermano, y vuelve luego a presentar tu ofrenda.Arréglate pronto con tu adversario, mientras vas con él por el camino; no sea que te entregue al juez, el juez al policía y te metan a la cárcel. Te aseguro que no saldrás de ahí hasta que hayas pagado el último centavo".Palabra del Señor.
In episode #356, Ben shares the results from the FP&A category of his 7th Annual SaaS Tech Stack Survey, highlighting the top financial planning and analysis solutions used in software companies today. With 37 FP&A solutions named in the survey, this remains one of the most competitive and fast-moving segments in the back-office tech stack. While spreadsheets still dominate usage—by a wide margin—dedicated FP&A platforms are gaining traction, especially as companies scale past $10M+ ARR and investor reporting requirements increase. Ben also compares this year's results to prior years and explains how FP&A tool adoption shifts by ARR size. Resources Mentioned 7th Annual SaaS Tech Stack Survey: https://www.thesaascfo.com/surveys/finance-accounting-tech-stack-survey/ What You'll Learn The most widely used FP&A solutions in SaaS and AI companies Why spreadsheets still dominate financial modeling workflows Which platforms are gaining momentum (Drivetrain, Mosaic, Aleph, Pigment, Planful, and others) How FP&A adoption changes as companies scale beyond $10M ARR Why enterprise-grade tools like Workday appear in larger organizations How funding and competition are reshaping the FP&A software landscape Why It Matters FP&A systems power your forecasting, budgeting, and board reporting Spreadsheet-based processes eventually break as complexity increases As ARR grows, investors expect more sophisticated financial modeling and analytics Selecting the right FP&A tool impacts forecasting accuracy, KPI visibility, and strategic planning Understanding market adoption trends helps founders and CFOs benchmark their financial systems
Stripe, the programmable financial services company, has signed agreements with investors to provide liquidity to current and former Stripe employees through a tender offer at a $159B (€135B) valuation. While the majority of funds for the tender offer are being provided by investors including Thrive Capital, Coatue, a16z, and others, Stripe will also use a portion of its own capital to repurchase shares. Stripe also published its 2025 annual letter to the Stripe community, detailing a strong year for businesses on Stripe and the internet economy overall. Businesses running on Stripe generated $1.9 trillion in total volume, up 34% from 2024, and equivalent to roughly 1.6% of global GDP. Beyond payments, Stripe's Revenue suite (comprising Stripe Billing, Invoicing, Tax, and more) is on track to hit an annual run rate of $1 billion this year. In the letter, cofounders Patrick and John Collison wrote: "Our programmable financial services now power more than 5 million businesses directly or via platforms, including all of the top AI companies, many of the largest blue-chip companies (90% of the Dow Jones Industrial Average), most of the biggest tech companies (80% of the Nasdaq 100), and a significant fraction of freshly minted startups (25% of all Delaware corporations are now created with Stripe Atlas) […] Stripe remained robustly profitable, allowing us to continue investing heavily in product development (with more than 350 product updates last year) as well as acquisitions. […] All in all, 2025 was a strong year for the internet economy, and we're delighted to see so many of Stripe's customers do so well." Kareem Zaki, partner at Thrive Capital, said: "After a decade of partnership and seeing their work up close, we believe Stripe has built the premiere financial infrastructure stack for the internet economy, relied on by the fastest growing companies for payments, billing, fraud prevention, tax, and more. While their core business has never been stronger, we believe their most transformative chapters are being written right now. We believe Stripe's lead will only expand across the future of money movement due to their leadership in agentic commerce, stablecoins, and more." New businesses on Stripe are scaling at record speed The 2025 cohort of new businesses on Stripe is the highest performing in the company's history. More new companies joined Stripe in 2025 than ever before, with more than half (57%) based outside the US. Businesses in the 2025 cohort grew around 50% faster than the 2024 cohort. The number of companies reaching $10 million ARR within 3 months of launch was double the 2024 count. Companies incorporated via Stripe Atlas are also monetising sooner: in 2025, 20% of Atlas startups charged their first customer within 30 days, up from 8% in 2020. Businesses on Stripe are increasingly global by default Over the last few years, the country-by-country expansion model has melted away. The "domestic market" for a new generation of internet businesses is the internet itself. Nearly every recognisable AI product launched globally by default, including ChatGPT, Claude, Replit, Lovable, Base44, Vercel, Cursor, Midjourney, and many more. Among Stripe businesses with mostly international revenue, 30% of that revenue comes from countries that are neither their home market nor one of the top 10 global economies. "This isn't merely about incremental revenue from a 'long tail' of international users. In many cases, the 'long tail' is much of the dog," the Collisons wrote. Building the economic infrastructure for AI Agentic commerce has moved into a phase of building and real-world experimentation. As with the early internet, the future success of agentic commerce is contingent on universal interoperability. To that end, Stripe has been working with a broad set of partners across AI labs, retailers, and leading ecommerce platforms to lay the groundwork for this generational shift: With OpenAI, Stripe developed the Agentic Comm...
Paddy Srinivasan, CEO of DigitalOcean (DOCN), joins to discuss their latest financial report and the company's future with AI. DOCN allows companies to build horizontal and vertical SaaS services, which have been squarely in the AI crosshairs in recent trading. He explains how their value proposition still holds up amid these worries, and how they're attracting AI-native customers, as well as how these customers use open vs closed-source AI. He notes record incremental ARR and accelerating growth for DigitalOcean. ======== Schwab Network ========Empowering every investor and trader, every market day.Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – / schwabnetwork Follow us on Facebook – / schwabnetwork Follow us on LinkedIn - / schwab-network About Schwab Network - https://schwabnetwork.com/about
MY NEWSLETTER - https://nikolas-newsletter-241a64.beehiiv.com/subscribeJoin me, Nik (https://x.com/CoFoundersNik), as I interview Tarek Arafat (https://x.com/@tarekarafat_), the co-founder of Table One! In this episode, we dive into the incredible story of how Tarek and his co-founder, Frank, built a membership platform that's generating over $200,000 in annual recurring revenue (ARR) with nearly 99% margins and zero paid ads.We explore how Table One is solving the epidemic of restaurant reservation scalping in New York City and empowering diners to access high-demand spots. Tarek shares how a personal problem led to a wildly successful, bootstrapped business, including the challenges of initially shutting down due to SMS message costs and the unexpected boost from being featured in The New Yorker.We also discuss their unconventional approach to community funding and Tarek's valuable advice for aspiring entrepreneurs.Questions This Episode Answers:• What major pain point does Table One solve for diners in New York City's high-demand restaurant scene?• How did Table One achieve 99% margins and $200K ARR with no paid ads and just two founders?• What pivotal moment, including an unexpected feature in The New Yorker, accelerated Table One's organic growth?• How did Tarek Arafat overcome challenges, like the initial shutdown of Table One's service, to achieve product-market fit?• What unconventional method did Table One use to raise over $600,000 in investment interest directly from its community?Enjoy the conversation!__________________________Love it or hate it, I'd love your feedback.Please fill out this brief survey with your opinion or email me at nik@cofounders.com with your thoughts.__________________________MY NEWSLETTER: https://nikolas-newsletter-241a64.beehiiv.com/subscribeSpotify: https://tinyurl.com/5avyu98yApple: https://tinyurl.com/bdxbr284YouTube: https://tinyurl.com/nikonomicsYT__________________________This week we covered:00:00 Introduction to Table One: A New Dining Experience03:05 The Problem with Current Reservation Systems05:54 Building a Solution: How Table One Works09:08 The Business Model and Pricing Strategy12:00 The Journey of Building Table One14:51 From Idea to Execution: The Founder's Story18:10 Navigating Challenges and Growth21:05 The Future of Table One and Dining Reservations29:09 Balancing Work and Startup Life30:34 The Crazy Growth Journey32:58 Navigating Press and Publicity34:56 The Importance of Distribution38:50 Managing Rapid Growth43:13 Lessons from the Journey46:00 Building Community and Investment51:16 Innovating Through Events55:59 Strategic Fundraising and Valuation
Ancien secrétaire général de l'UDPS, le parti présidentiel, ancien vice-président de l'Assemblée nationale et longtemps considéré comme l'un des plus proches collaborateurs de Félix Tshisekedi, Jean-Marc Kabund a progressivement basculé dans l'opposition. En février 2022, après des propos virulents contre le chef de l'État, il tombe en disgrâce et radicalise son discours à l'encontre du pouvoir. Arrêté en août 2022, il est condamné en septembre 2023 par la Cour de cassation à sept ans de servitude pénale. L'ancien chef du parti présidentiel a quitté, vendredi 21 février 2025 dans la soirée, la prison centrale de Makala. Aujourd'hui figure de l'opposition congolaise, il plaide pour l'organisation d'un dialogue inclusif. Grand invité Afrique de RFI aujourd'hui, il est interrogé par Patient Ligodi. À lire aussiDialogue national en RDC: le président Félix Tshisekedi pose ses conditions
This year marks the 20th anniversary of the Artist's Resale Right in the UK, the royalty that allows artists and their estates to receive compensation when their works are resold. Since its introduction in 2006, ARR has generated significant income for artists while also sparking ongoing debate about who truly benefits and how it affects the art market. To explore its impact and evolution, host Adam Green speaks with Christian Zimmermann, CEO of DACS (the Design and Artists Copyright Society), the organization responsible for collecting and distributing resale royalties to visual artists and their beneficiaries in the UK. In the conversation, Christian explains how the Artist's Resale Right works in practice, the history and policy context behind its adoption, and how the art world responded at the time. They discuss common misconceptions about resale royalties, examine the evidence around who benefits most from them, and consider how resale royalty legislation has spread globally over the past two decades, as well as whether the framework may need to evolve to reflect today's increasingly international art market.
#332 | Dave is joined by Domi de Saint-Exupéry, CMO at Lemlist, a bootstrapped $40M ARR sales engagement platform, to break down exactly how she turned $1.2M in marketing spend into $31M in new ARR in 2025. Domi shares the full breakdown of every channel, agency, influencer strategy, and partnership play that drove results. This includes how they went from $0 to $500K in paid ads, why partnerships are the most underrated B2B growth channel, how they built a micro-influencer program, and what AI use cases are actually working (and which are overrated). If you want real numbers and real playbooks, this one's for you.Timestamps(00:00) - Introduction: $1.2M in spend, $31M in new ARR (03:36) - What Lemlist does and how the company got to $40M ARR (06:51) - Going from $0 to $500K in paid ads: what triggered the shift (11:06) - How to execute paid ads well: outsourcing vs. in-house, and scaling by channel (17:21) - LinkedIn ads creative: why "on-brand and safe" was the wrong approach (21:51) - Mistakes made in paid: Snapchat, Spotify, and channels that didn't work (25:21) - The micro-influencer playbook: how to find, brief, and measure creators (35:59) - How influencer content compounds with paid ads and outbound (the Julio story) (41:29) - Partnerships: why $450K went here and why it's the most underrated B2B channel (49:59) - AI in marketing: what's overrated (content generation) and what's actually working Join 50,0000 people who get Dave's Newsletter here: https://www.exitfive.com/newsletterLearn more about Exit Five's private marketing community: https://www.exitfive.com/***Brought to you by:Knak - A no-code, campaign creation platform that lets you go from idea to on-brand email and landing pages in minutes, using AI where it actually matters. Learn more at knak.com/exitfive.Optimizely - An AI platform where autonomous agents execute marketing work across webpages, email, SEO, and campaigns. Get a free, personalized 45-minute AI workshop to help you identify the best AI use cases for your marketing team and map out where agents can save you time at optimizely.com/exitfive (PS - you'll get a FREE pair of Meta Ray Bans if you do). Customer.io - An AI powered customer engagement platform that help marketers turn first-party data into engaging customer experiences across email, SMS, and push. Learn more at customer.io/exitfive. ***Thanks to my friends at hatch.fm for producing this episode and handling all of the Exit Five podcast production.They give you unlimited podcast editing and strategy for your B2B podcast.Get unlimited podcast editing and on-demand strategy for one low monthly cost. Just upload your episode, and they take care of the rest.Visit hatch.fm to learn more
Jolly és Szuperák Barbara New Yorkban – Ázsia Expressz titkok, világsiker és... MÓKA Podcast Ebben az epizódban a vendégeink Jolly és Szuperák Barbara (Barbi), akik 2025. december 28-án érkeztek Amerikába, és New Yorkban töltötték az újévet. Beszélgetünk arról: • Milyen volt szilveszterkor magyar közönség előtt fellépni az Egyesült Államokban • Miben más a New York-i metró a budapestihez képest • Hogyan navigáltak GPS-szel térerő nélkül a föld alatt • Milyen volt mínusz 10 fokban a Coney Island-i jeges víz partján állni január 1-jén Az epizód egyik legerősebb része az Ázsia Expressz kulisszatitkai. Barbi meséli el, hogyan fordult ki a bokája egy több tíz kilós zsák cipelése közben, mégis végigcsinálta a napot az adrenalinnak köszönhetően. Este viszont megérkezett a fájdalom. A történet őszinte, nyers és inspiráló. A műsor kapcsán kiderül az is, hogy míg Jolly ma már nem menne vissza az Ázsia Expresszbe, addig Barbi azonnal újra belevágna, ha hívnák. Szó esik: • Extrém alvási körülményekről • Komfortzónából való kilépésről • Mentális és fizikai határokról • Egy 15 centis csótányos éjszakáról • Arról, mit tanított a túlélésről az Ázsia Expressz A beszélgetés másik fontos témája Jolly 30 éves zenei pályafutása. Jolly őszintén beszél arról, hogy hosszú éveken keresztül a zene volt az első, még a család előtt is. Ma már tudatosabban választ fellépéseket, figyel az egészségére, és a magánélet került előrébb. Külön szó esik a nemzetközi sikerről is. A Ciki Ciki Bám Bám című dal nemcsak Magyarországon lett sláger, hanem Ázsiában és Olaszországban is berobbant, sőt Amerikában line dance koreográfiák készültek rá. Magyar nyelvű dal, nemzetközi közönséggel. Ez az epizód egyszerre szól: • Jolly karrierjéről • Szuperák Barbara személyes fejlődéséről • Az Ázsia Expressz extrém kihívásairól • Magyar előadók amerikai fellépéseiről • Komfortzónán túli tapasztalatokról • Újratervezésről 40 felett Ha érdekel: • Jolly világsikere • Barbi Ázsia Expressz élményei • Magyarok New Yorkban • Hogyan változik meg az ember gondolkodása a siker után akkor ez az epizód neked szól. Iratkozz fel a MÓKA Podcast csatornára, és írd meg kommentben: Te elmennél az Ázsia Expresszbe? Támogasd a MÓKA Podcastet: Bercode.com/mokapodcast https://bit.ly/MOKAPodcatsSign Kövess minket Facebookon: @mokapodcast Instagramon: @mokapodcastusa Web: mokapodcast.com Spotify (https://bit.ly/mokapodcast) Apple Podcast (https://bit.ly/moka2021) [Google Podcast](https://bit.ly/MokaGoogle) [Deezer](https://bit.ly/MokaDeezer) [LibSyn](https://bit.ly/MokaLibsyn) [Facebook](https://bit.ly/MokaFB)
Motorcycles have evolved, and with that evolution comes more electronics — including CAN bus systems that many riders still misunderstand. If you've ever seen a mysterious warning light or struggled with adding accessories like auxiliary lights, you've probably heard CAN bus blamed. In this episode, we break down what CAN bus actually is, why it's not the enemy of customization, and how modern systems can actually create more opportunity for riders who understand them.
In this episode of Run the Numbers, CJ sits down with Varsha Udayabhanu of Invisible to unpack what enterprise AI adoption actually looks like beyond the hype. They cover forward deployed engineers, eight-week solution sprints, value-based pricing when outcomes are hard to meter, ARR vs. services revenue, and why “momentum” beats traditional SaaS metrics. A tactical look at trust, expansion, and building durable AI revenue.—SPONSORS:Brex is an intelligent finance platform that combines corporate cards, built-in expense management, and AI agents to eliminate manual finance work. By automating expense reviews and reconciliations, Brex gives CFOs more time for the high-impact work that drives growth. Join 35,000+ companies like Anthropic, Coinbase, and DoorDash at https://www.brex.com/metricsMetronome is real-time billing built for modern software companies. Metronome turns raw usage events into accurate invoices, gives customers bills they actually understand, and keeps finance, product, and engineering perfectly in sync. That's why category-defining companies like OpenAI and Anthropic trust Metronome to power usage-based pricing and enterprise contracts at scale. Focus on your product — not your billing. Learn more and get started at https://www.metronome.comRightRev is an automated revenue recognition platform built for modern pricing models like usage-based pricing, bundles, and mid-cycle upgrades. RightRev lets companies scale monetization without slowing down close or compliance. For RevRec that keeps growth moving, visit https://www.rightrev.comRillet is an AI-native ERP built for modern finance teams that want to close faster without fighting legacy systems. Designed to support complex revenue recognition, multi-entity operations, and real-time reporting, Rillet helps teams achieve a true zero-day close—with some customers closing in hours, not days. If you're scaling on an ERP that wasn't built in the 90s, book a demo at https://www.rillet.com/cjTabs is an AI-native revenue platform that unifies billing, collections, and revenue recognition for companies running usage-based or complex contracts. By bringing together ERP, CRM, and real product usage data into a single system of record, Tabs eliminates manual reconciliations and speeds up close and cash collection. Companies like Cortex, Statsig, and Cursor trust Tabs to scale revenue efficiently. Learn more at https://www.tabs.com/runAbacum is a modern FP&A platform built by former CFOs to replace slow, consultant-heavy planning tools. With self-service integrations and AI-powered workflows for forecasting, variance analysis, and scenario modeling, Abacum helps finance teams scale without becoming software admins. Trusted by teams at Strava, Replit, and JG Wentworth—learn more at https://www.abacum.ai—LINKS: Varsha: https://www.linkedin.com/in/varshaudayabhanu/Company: https://invisibletech.ai/CJ: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—RELATED EPISODES:Marketing as a Form of Capital Allocation With Carta's Head of Growth Angela Winegarhttps://youtu.be/rG09ehsrWv8—TIMESTAMPS:00:00 Intro03:21 What Invisible Technologies Does05:34 Enterprise AI Adoption Gap07:38 Forward Deployed Engineers09:44 Evolving GTM in AI Services10:36 Solution Sprints12:37 Sponsor — Brex | Metronome | RightRev15:56 Upfront Investment vs. Upside18:38 Bespoke Deals20:37 Value-Based Pricing in Enterprise AI22:12 Value Sold vs. Value Delivered23:31 Enterprise Revenue as a Portfolio of Bets24:53 Time-Bound Solution Sprints27:06 Sponsor — Rillet | Tabs | Abacum30:32 Humans in the Loop & Expert Incentives33:38 Niche Human Expertise34:10 Rethinking KPIs Beyond ARR35:44 Momentum Metrics39:00 Evaluating GenAI Financial Profiles40:47 Expansion as the Atomic Unit42:19 AdTech Lessons on Distribution & Brand43:23 Why Brand Matters for Enterprise47:10 Commoditization Risk48:31 Long-Ass Lightning Round53:20 Credits
In episode #354, Ben shares the results from his 7th Annual SaaS Tech Stack Survey and reveals the top accounting solutions used by software, SaaS, and AI companies today. With participation across 22 software categories, this year's survey highlights both the consistent market leaders and the rise of newer, AI-first ERP platforms. While legacy players continue to dominate, new entrants are gaining meaningful traction. Ben breaks down the “Power Six” accounting platforms and what their market concentration tells us about the current state of financial systems in tech companies. Resources Mentioned 7th Annual SaaS Tech Stack Survey: https://www.thesaascfo.com/surveys/finance-accounting-tech-stack-survey/ Light, sponsor of the core accounting category: https://light.inc/ What You'll Learn The top accounting and ERP systems used by SaaS and AI companies How the “Power Six” now dominate the accounting stack landscape Which newer AI-first ERP platforms are gaining traction How concentrated is the accounting software market among SaaS companies Why accounting system selection matters as companies scale ARR Why It Matters Your accounting system is the foundation of your financial reporting, SaaS metrics, and KPI tracking Poor financial systems limit your ability to calculate ARR, revenue retention, and other recurring revenue metrics As revenue grows, moving from SMB accounting tools to more robust ERP and financial systems becomes critical Investors and auditors expect scalable accounting infrastructure as companies mature Understanding market trends helps founders and CFOs evaluate whether their current financial systems can support growth
Kiren Sekar (CPO @ Samsara) joins us to deconstruct the "Innovation Engine" behind Samsara, and how this system drives real-world impact and ROI across their products. We explore Samsara's decade-long compound product strategy and the mechanics of accelerating feedback loops in an era where the primary bottlenecks shift from code generation to customer feedback and absorption of change. Kiren details how their data flywheel expands the aperture of what is possible to build and we dive into the system of customer-driven innovation: advisory boards, “spark sessions” to test hypotheses and gain unfiltered feedback. Plus we talk about the power of embedding engineers in frontline environments (from truckyards to construction sites) to cultivate “taste,” customer empathy and trigger non-linear ideas. ABOUT KIREN SEKARKiren Sekar is the Chief Product Officer at Samsara (NYSE: IOT), where he has helped lead the company from a hardware-hacking startup in a basement to a global leader in Connected Operations with over $1.5B in ARR. An early leader at Meraki (acquired by Cisco for $1.2B) and an Apple veteran with multiple patents, Kiren specializes in the rare intersection of hardware, massive-scale data, and AI. He is the architect of a platform that now processes trillions of data points for the industries that keep the world running—trucking, construction, and logistics. This episode is brought to you by Retool!What happens when your team can't keep up with internal tool requests? Teams start building their own, Shadow IT spreads across the org, and six months later you're untangling the mess…Retool gives teams a better way: governed, secure, and no cleanup required.Retool is the leading enterprise AppGen platform, powering how the world's most innovative companies build the tools that run their business. Over 10,000 organizations including Amazon, Stripe, Adobe, Brex, and Orangetheory Fitness use the platform to safely harness AI and their enterprise data to create governed, production-ready apps.Learn more at Retool.com/elc SHOW NOTES:Real-world ROI The Intersection of Bits and Atoms: How Samsara supported customers through a once-in-a-century snowstorm using real-time AI insights (3:59)The Practicality Filter: Why low-margin, high-utility businesses are the best "BS detectors" for product builders (9:25)Deconstructing the compound product strategy: 10 years of feedback loops, scaling empathy, and technical capabilities (10:53)Accelerating your innovation flywheel, customer and product feedback loops (14:39)The New Bottleneck: Why writing code is no longer the constraint, and how to optimize for customer absorption of change (19:58)The Data Flywheel: Leveraging trillions of proprietary data points to solve new problems and expand your innovation engine into new capabilities (23:36)Embedding engineers in customer problems: Why there is no substitute for engineers seeing the frontline environment firsthand (29:56)How customer empathy and "taste" amplify the benefits of AI coding agents (33:26)Building a system of customer-driven innovation: Utilizing Advisory Boards and "Spark Sessions" to turn 10,000+ customers into co-creators (37:40)Rapid fire questions (47:50)This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
⚔️ Notre Programme Rox Evolution : https://bit.ly/roxevolution-podcast
How do you build a $30 million ARR business with just three people and a fleet of AI agents doing the heavy lifting? In this episode of Tech Talks Daily, I connected with Amos Joseph, CEO of Swan AI. From the moment we joked about AI notetakers silently observing our conversation, it was clear this discussion would go beyond surface-level automation talk. Amos is attempting something bold. He is building what he calls an autonomous business, one designed to scale with intelligence rather than headcount. Amos has already built and exited two B2B startups using the traditional growth-at-all-costs model. Raise early, hire fast, expand the vision, chase valuation. This time, he is rewriting that script entirely. Swan AI is built around ARR per employee, human-AI collaboration, and what he describes as scaling employees rather than scaling the org chart. With more than 200 customers and only three founders, Swan is already testing whether AI agents can run real go-to-market operations autonomously. We explored why over 90 percent of AI implementations fail and why grassroots experimentation consistently outperforms executive mandates. Amos argues that companies looking outward for AI solutions before understanding their internal bottlenecks are simply scaling chaos. The organizations that succeed start with process clarity, define what humans should do versus what should be automated, and then allow AI to execute within that structure. It is a powerful reminder that becoming AI-native has less to do with tools and more to do with operational self-awareness. We also unpacked the difference between automation and agentic AI. Traditional automation follows deterministic steps coded in advance. Agentic AI shifts decision-making power to the model itself. The AI decides what to do next, introducing statistical reasoning rather than predefined logic. That shift in agency changes everything about how workflows operate and how leaders think about control. Perhaps most fascinating is how Swan generates pipeline entirely through LinkedIn. No paid ads. No outbound. Amos has built an AI-driven engine that creates content, monitors engagement, qualifies prospects, and nurtures relationships at scale. It is an experiment in trust-based distribution powered by agents, not marketing budgets. This conversation reframes what growth can look like in an AI-native world. If scaling no longer equals hiring, and if every employee becomes a manager of AI agents, what does leadership look like next? How do founders build organizations that amplify human zones of genius rather than bury them under coordination overhead? If you are questioning long-held assumptions about team size, growth, and AI adoption, this episode will give you plenty to think about.
What happens when two seasoned overland riders trade full-size adventure bikes for 50cc, 50-year-old two-strokes? German engineers Bea Höbenreich and Helmut Koch set out to prove that real motorcycle adventure isn't about horsepower or gear—it's about mindset. From Australia's punishing outback to Cape York's legendary Old Telegraph Track, they battled bike drownings, deep sand, brutal creek crossings, and relentless headwinds on the smallest machines in the landscape.
The Twenty Minute VC: Venture Capital | Startup Funding | The Pitch
AGENDA: 03:43 Anthropic Predicts $149B in ARR in 2029 09:27 Will FDEs Become More or Less Powerful 26:17 Harvey Raises $200M at an $11BN Valuation 42:45 Is Customer Support a Terrible or Terrific Investment Category 56:14 Anthropic's Superbowl Ad: Who Won and Who Lost 01:11:30 Do CEOs Have to Work Harder Today Than Ever
In this episode of Liftoff, Keith sits down with Amos Bar-Joseph, Co-Founder and CEO of Swan AI, to explore a radical shift in how modern companies scale.Amos shares why the traditional belief that growth equals headcount is breaking down—and how AI is enabling a new model: the autonomous business. At Swan, scale is no longer about adding people—it's about increasing ARR per employee by embedding intelligence directly into workflows.They unpack:Why the old “cog culture” model is collapsing What collaborative autonomy really meansHow Swan's AI GTM Engineer turns ideas into live go-to-market workflowsWhy execution—not creativity—is what AI should automateAnd why go-to-market innovation is now more important than product innovationThis is a must-listen for founders, operators, and GTM leaders navigating the AI-native era.Connect with Amos Bar-Joseph: Website: https://getswan.com/ LinkedIn: https://www.linkedin.com/in/amos-bar-joseph/ Subscribe for more founder insights and hit the bell for notifications! Follow us on our channels for exclusive startup content and behind-the-scenes insights from interviews like this one. - Spotify: https://open.spotify.com/show/3cFpLXfYvcUsxvsT9MwyAD?si=f5a14e779777487dApple Podcasts: https://podcasts.apple.com/ca/podcast/liftoff-with-keith-newman/id1560219589Substack: https://keithnewman.substack.com/Newman Media Studios: https://newmanmediastudios.com/ LinkedIn: https://www.linkedin.com/company/liftoffwithkeithTikTok: https://www.tiktok.com/@keithnewman74 For sponsorship inquiries, please contact: sponsorships@wherewithstudio.com#AutonomousBusiness #AIinBusiness #CollaborativeAutonomy #FutureOfWork #GTMInnovation #SaaSFounders #StartupScaling #AIWorkflows #AgenticAI
a16z Head of Investor Relations Jen Kha speaks with general partner David George about the state of AI and private technology markets. David shares data on why AI companies are growing 2.5x faster than traditional software while spending significantly less on sales and marketing, driven by massive market pull and record-breaking ARR per employee. They discuss the rise of Model Busters, which are companies that grow faster and longer than anyone would have modeled, like the iPhone. They also highlight real-world adoption at Chime and Rocket Mortgage alongside portfolio breakouts like Harvey, Abridge, and ElevenLabs. Resources:Follow David on X: https://x.com/DavidGeorge83Follow Jen on X: https://x.com/jkhamehlRead The State of Markets - https://a16z.com/state-of-markets/ Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://twitter.com/eriktorenberg](https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
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