Podcasts about Alessio

Dopo tre mesi di stop estivo, Alessio e Katia vi aspettano per una nuova stagione piena di curiosità, cultura ed espressioni utili per il vostro italiano!In questa prima puntata ripartiamo con una bella chiacchierata sui libri e parliamo del Premio Strega, il premio letterario più importante d'Italia. Sapete perché si chiama così? E cosa c'entra un famoso liquore campano con la letteratura? Katia ci svela la storia di questo riconoscimento, nato nel 1947, e ci presenta il libro vincitore di quest'anno: "I convitati di pietra" di Michele Mari.Cosa imparerai in questo episodio?Scopriamo insieme tre utilissime espressioni italiane:Andare sul sicuroFar ripartireIncuriosire Ascolta la puntata, scopri la magia del Premio Strega e lasciaci un commento sui nostri social (Instagram -  Facebook - TikTok) per dirci se hai mai letto un libro premiato!

Adattamento audio: Matteo D'Alessandro - www.matteodalessandro.com Per approfondire gli argomenti della puntata: La nostra serie Imperatores, sugli imperatori romani : https://youtube.com/playlist?list=PLpMrMjMIcOkkIDocjNI3Q7gCk-4bOiVVO Le altre puntate sulla storia di Roma antica : https://youtube.com/playlist?list=PLpMrMjMIcOkkVlao9HeDl3jIHVKO3IcR_ Learn more about your ad choices. Visit megaphone.fm/adchoices

GP di Baku che come sempre ci regala una gara caotica e piena di sorprese. Nel marasma, la porta a casa un ritrovato George Russell, che convince tutto il weekend dalla prima sessione di prove libere all'ultimo giro della gara, gestendo in maniera perfetta sia le ripartenze dopo la Safety Car che il duello con Verstappen. Incredibile che con una prestazione del genere il vantaggio su Max sia meno di 2 decimi. Completa il podio Hadjar, benissimo al suo ritorno dopo 3 gare di sosta per l'infortunio al polso. Ferrari massimizza su una pista su cui non si trova del tutto a proprio agio, arrivando addirittura davanti a Kimi con uno dei due piloti. Dal canto suo il giovane italiano fa una gara solida, ma ciò che lo penalizza è l'erroraccio al sabato. Occhio, perchè la matematica ancora non dice che è campione del mondo.Di questo parliamo nella nuova puntata di ZonaDRS con Giacomo e l'ospite speciale di oggi, Alessio!

Fluent Fiction - Italian: Finding Inspiration: How Alessio's Art Transformed Find the full episode transcript, vocabulary words, and more:fluentfiction.com/it/episode/2026-09-25-07-38-20-it Story Transcript:It: Alessio era seduto su una panchina di legno nei giardini di Villa Borghese.En: Alessio was sitting on a wooden bench in the gardens of Villa Borghese.It: Le foglie autunnali cadevano leggere intorno a lui, dipingendo il terreno di colori vivaci—rossi, gialli, arancioni.En: The autumn leaves were falling lightly around him, painting the ground in vibrant colors—reds, yellows, oranges.It: Gli altri studenti chiacchieravano in lontananza, ma Alessio era concentrato sul suo blocco da disegno.En: The other students were chatting in the distance, but Alessio was focused on his sketchbook.It: Doveva finire un progetto importante per la sua classe d'arte.En: He had to finish an important project for his art class.It: Voleva impressionare la sua insegnante e, forse, ricevere una borsa di studio per un campo d'arte.En: He wanted to impress his teacher and maybe earn a scholarship for an art camp.It: Ma il parco era pieno di distrazioni.En: But the park was full of distractions.It: C'erano turisti che scattavano foto, bambini che ridevano e giocavano, e gruppi di studenti che correvano e scherzavano.En: There were tourists taking photos, children laughing and playing, and groups of students running and joking.It: Tra loro, Giulia era la più vivace.En: Among them, Giulia was the most lively.It: Con il suo sorriso contagioso e la sua risata cristallina, attirava sempre tutti attorno a sé.En: With her contagious smile and crystalline laughter, she always attracted everyone around her.It: "Alessio, vieni con noi!"En: "Alessio, come with us!"It: lo chiamò Giulia, avvicinandosi.En: called Giulia, approaching him.It: "Il parco è così bello oggi.En: "The park is so beautiful today.It: Devi divertirti!"En: You need to have fun!"It: Alessio esitò.En: Alessio hesitated.It: Sentiva il desiderio di unirsi a loro, ma l'immagine perfetta che voleva disegnare gli riempiva la mente.En: He felt the desire to join them, but the perfect image he wanted to draw filled his mind.It: "Devo disegnare," rispose piano, concentrandosi sul suo lavoro.En: "I have to draw," he replied softly, focusing on his work.It: Giulia si sedette accanto a lui per un momento, curiosa.En: Giulia sat next to him for a moment, curious.It: "Posso vedere?En: "Can I see?"It: ", chiese, mentre sporgeva la testa per sbirciare il suo schizzo.En: she asked, leaning her head to peek at his sketch.It: Era un disegno promettente.En: It was a promising drawing.It: Un angolo della villa, con alberi che incorniciavano la scena.En: A corner of the villa, with trees framing the scene.It: Ma qualcosa mancava.En: But something was missing.It: Feeling frustrato, Alessio abbassò la matita.En: Feeling frustrated, Alessio lowered his pencil.It: "Non riesco a finire," confessò.En: "I can't finish it," he confessed.It: Sentiva che il disegno era freddo, privo di vita.En: He felt the drawing was cold, devoid of life.It: Giulia sorrise e gli disse, "Forse ti manca un po' di ispirazione.En: Giulia smiled and said, "Maybe you need a bit of inspiration.It: A volte, un po' di divertimento aiuta!"En: Sometimes, a little fun helps!"It: Alessio guardò Giulia e i suoi compagni di classe che ridevano non lontano.En: Alessio looked at Giulia and his classmates who were laughing not far away.It: Decise di seguirli per un po'.En: He decided to join them for a while.It: Si alzò, si unì al gruppo e sentì una leggerezza che non provava da tempo.En: He got up, joined the group, and felt a lightness he hadn't felt in a while.It: Videro un giovane suonatore di violino, e tutti cominciarono a improvvisare una danza.En: They saw a young violinist, and everyone started to improvise a dance.It: Mentre li osservava, Alessio sentì qualcosa cambiare.En: As he watched them, Alessio felt something change.It: La vista dei suoi amici, così pieni di gioia e spensieratezza, aggiungeva una nuova dimensione al suo disegno.En: The sight of his friends, so full of joy and carefreeness, added a new dimension to his drawing.It: C'erano sorrisi, movimenti fluidi, e l'energia del momento che Alessio percepiva fortemente.En: There were smiles, fluid movements, and the energy of the moment that Alessio perceived strongly.It: Ritornato alla panchina, afferrò la sua matita con nuovo vigore.En: Returning to the bench, he grabbed his pencil with renewed vigor.It: Iniziò a disegnare di nuovo, questa volta catturando non solo la bellezza del posto, ma anche l'anima di quel pomeriggio.En: He began to draw again, this time capturing not only the beauty of the place but also the soul of that afternoon.It: Le risate, l'armonia dei colori, l'attimo in cui il tempo sembrava fermarsi.En: The laughter, the harmony of colors, the moment when time seemed to stand still.It: Alla fine della giornata, l'insegnante di Alessio esaminò il suo lavoro.En: At the end of the day, Alessio's teacher examined his work.It: "È incredibile," disse con ammirazione.En: "It's incredible," she said with admiration.It: "Hai catturato qualcosa di veramente speciale."En: "You've captured something truly special."It: Alessio sorrise, soddisfatto.En: Alessio smiled, satisfied.It: Aveva imparato che a volte, un po' di gioia e compagnia possono ispirare più di quanto credesse.En: He had learned that sometimes, a little joy and company can inspire more than he believed.It: Riuscì a trovare equilibrio tra il lavoro e il divertimento, e quella lezione l'avrebbe portata con sé per sempre.En: He managed to find a balance between work and fun, and he would carry that lesson with him forever. Vocabulary Words:the bench: la panchinathe gardens: i giardinithe leaves: le foglieto paint: dipingerevibrant: vivacito chat: chiacchierarethe sketchbook: il blocco da disegnothe scholarship: la borsa di studiothe distraction: la distrazionevivacious: vivacecontagious: contagiosocrystalline: cristallinato hesitate: esitarethe desire: il desiderioperfect: perfettato lean: sporgersithe corner: l'angolothe scene: la scenafrustrated: frustratothe inspiration: l'ispirazionecarefreeness: la spensieratezzathe lightness: la leggerezzathe movement: il movimentothe harmony: l'armoniathe moment: l'attimoto freeze: fermarsithe admiration: l'ammirazioneto satisfy: soddisfarethe balance: l'equilibriothe company: la compagnia

Fluent Fiction - Italian: Unveiling Secrets: A Journey Through Forest and Family Ties Find the full episode transcript, vocabulary words, and more:fluentfiction.com/it/episode/2026-09-24-22-34-01-it Story Transcript:It: Nel cuore di un autunno dorato, Alessio percorse un sentiero tra gli alberi della foresta.En: In the heart of a golden autumn, Alessio walked along a path through the forest trees.It: Le foglie, in mille sfumature di arancione e oro, coprivano il terreno come un morbido tappeto.En: The leaves, in a thousand shades of orange and gold, covered the ground like a soft carpet.It: Accanto a lui, il suo fratello maggiore, Carlo, avanzava con passo deciso ma pieno di scetticismo.En: Beside him, his older brother, Carlo, advanced with a determined but skeptical step.It: Bianca, la loro nonna, era rimasta nel villaggio.En: Bianca, their grandmother, had stayed in the village.It: Lei aveva raccontato ad Alessio di un segreto della famiglia, nascosto da tempo nel cuore della foresta.En: She had told Alessio about a family secret, long hidden in the heart of the forest.It: Le sue parole erano state sussurrate con calma e un tono di mistero.En: Her words had been whispered calmly and with a tone of mystery.It: "Cerca il salice," aveva detto, "e il passato si rivelerà."En: "Seek the willow," she had said, "and the past will be revealed."It: Alessio sentiva l'emozione che cresceva dentro di sé.En: Alessio felt the excitement growing within him.It: Carlo, d'altra parte, scuoteva la testa.En: Carlo, on the other hand, shook his head.It: "Sono solo storie, Alessio.En: "They're just stories, Alessio.It: Perché perdere tempo?"En: Why waste time?"It: Ma Alessio non si fermò.En: But Alessio did not stop.It: Ascoltava il vento tra gli alberi, sentiva il canto antico della natura.En: He listened to the wind among the trees, felt the ancient song of nature.It: Decise di seguire il consiglio della nonna e le sue sensazioni.En: He decided to follow his grandmother's advice and his own feelings.It: Dopo ore di cammino, arrivarono a una radura nascosta.En: After hours of walking, they arrived at a hidden clearing.It: Al centro, un grande salice si ergeva solitario.En: In the center, a large willow stood solitary.It: Le sue fronde formavano una cortina segreta.En: Its branches formed a secret curtain.It: Mentre Carlo osservava, curioso malgrado se stesso, Alessio si avvicinò lentamente.En: While Carlo watched, curious despite himself, Alessio approached slowly.It: Dietro le fronde del salice, trovò un vecchio baule, coperto di muschio e polvere.En: Behind the willow's branches, he found an old chest, covered in moss and dust.It: Il cuore gli batteva forte.En: His heart was pounding.It: Con mani tremanti, aprì il coperchio.En: With trembling hands, he opened the lid.It: All'interno, un antico diario e un piccolo ciondolo che sembrava brillare di una luce propria.En: Inside, an ancient diary and a small pendant that seemed to shine with its own light.It: Leggendo il diario ad alta voce, Alessio scoprì che la loro famiglia discendeva da antichi esploratori, custodi di terre lontane e conoscenze perdute.En: Reading the diary aloud, Alessio discovered that their family descended from ancient explorers, keepers of distant lands and lost knowledge.It: Il ciondolo era la chiave di un segreto tramandato di generazione in generazione, un simbolo di unità e saggezza.En: The pendant was the key to a secret passed down through generations, a symbol of unity and wisdom.It: Carlo, che inizialmente era scettico, ascoltava con attenzione, svelando l'importanza del legame famigliare e delle radici storiche.En: Carlo, who was initially skeptical, listened attentively, unveiling the importance of the family bond and historical roots.It: Una nuova luce brillava nei suoi occhi.En: A new light shone in his eyes.It: Ritornarono al villaggio per raccontare la scoperta a Bianca.En: They returned to the village to tell Bianca about their discovery.It: La saggezza e la calma della nonna accolsero i ragazzi.En: The grandmother's wisdom and calm welcomed the boys.It: "Avete trovato più di un segreto," disse con un sorriso, "avete trovato voi stessi."En: "You've found more than a secret," she said with a smile, "you've found yourselves."It: Alessio ora camminava con più sicurezza, grato per la verità scoperta.En: Alessio now walked with more confidence, grateful for the truth discovered.It: Carlo, colpito dai racconti del passato, capì che c'erano mondi più vasti di quelli visibili.En: Carlo, struck by the tales of the past, understood that there were worlds wider than the visible ones.It: La foresta ora non era solo una massa di alberi per lui, ma un luogo di connessione e storia.En: The forest was now not just a mass of trees for him, but a place of connection and history.It: Il vento autunnale sussurrava tra le foglie, portando con sé l'eco di antichi tempi e nuove scoperte.En: The autumn wind whispered among the leaves, carrying with it the echo of ancient times and new discoveries.It: La famiglia si era riunita, più forte che mai nel loro legame con il passato e con il futuro.En: The family had come together, stronger than ever in their bond with the past and the future. Vocabulary Words:the heart: il cuorethe autumn: l'autunnothe path: il sentierodetermined: decisoskeptical: scetticothe village: il villaggiothe secret: il segretoto reveal: rivelarethe advice: il consigliothe clearing: la radurasolitary: solitariothe branches: le frondethe chest: il baulethe moss: il muschiothe dust: la polverethe lid: il coperchiothe diary: il diariothe pendant: il ciondoloto descend: discenderethe keepers: i custodithe lands: le terrethe wisdom: la saggezzato unveil: svelarethe roots: le radicithe bond: il legamestruck: colpitothe tales: i raccontithe connection: la connessioneto whisper: sussurrarethe echo: l'eco

Introduzione e problemi tecniciApertura della puntata de Il Cortocircuito con i consueti problemi tecnici audio/video e siparietti tra i conduttori (Pierpaolo, Francesco e Alessio), presentazione della scaletta della giornata e degli ospiti.Ospite POW3R: L'esperienza da sviluppatore e il mercato videoludicoIntervista a Giorgio Calandrelli (POW3R) incentrata sulla sua collaborazione allo sviluppo del videogioco italiano The Alighieri Circle: Dante's Bloodlines. Giorgio racconta il suo percorso nel team (One O One Games), il contributo al game design, ai puzzle e ai collectibles, oltre alle dinamiche di produzione e ai ritmi di lavoro. La chiacchierata spazia poi sui suoi generi preferiti (survival ed extraction shooter), sulle critiche a Marathon e Wolverine, sul passaggio al digitale e sui titoli più attesi.Il caso Hideo Kojima, Physint e la mossa di Asha Sharma (Xbox)Ampio dibattito sul presunto passaggio/finanziamento di Physint (e OD) da parte di Microsoft/Xbox con Asha Sharma a capo della divisione gaming, analizzando le dinamiche con Sony PlayStation. Discussione sui costi di produzione, sulla prolificità di Kojima, sulle strategie aziendali dei publisher e sull'impatto sul brand Xbox.Lo stato del mercato: Nintendo, Sony e Microsoft a confrontoAnalisi approfondita sullo stato di salute e sulle prospettive future dei tre colossi del gaming: la solidità e gestione oculata di Nintendo, le incognite legate ai costi e ai progetti a lungo termine di Sony, e le strategie di Microsoft tra Game Pass, Cloud Gaming e hardware di nuova generazione.Il caso Me Contro Te, copyright, strike e diritto di critica (Il caso Sbortus)Discussione sul matrimonio-evento a pagamento dei Me Contro Te, sulle reazioni dei creator (in particolare Sbortus) e sugli strike per violazione di copyright applicati ai video di commento/critica. Confronto acceso tra i conduttori sulla normativa italiana in materia di diritto d'autore, eccezioni, fair use, diritto di cronaca/critica e funzionamento del Content ID sulle piattaforme online.

Can metabolic dysfunction be the cause of anxiety?Join Dr. Emily Cooper, Andrea Taylor, and guest Alessio De Martis as they explore the fascinating intersection of metabolic health, anxiety, and the struggle with traditional diet advice. Learn how under-fueling can exacerbate metabolic issues and what that means for your overall health. KEY TAKEAWAYSAlessio's experience highlights the struggle of self-managing metabolic health in Europe.Under-fueling can worsen metabolic dysfunction, disrupting body stability.The body's response to hypoglycemia can mirror symptoms of anxiety. NOTABLE QUOTE"If you have a history of hypoglycemia, you're gonna have a lot less tolerance than other people." — Dr. Emily Cooper GUEST BIOAlessio De Martis is a 41-year-old listener from Rome, Italy, who shares his experiences with metabolic dysfunction, hypoglycemia, and anxiety. His journey represents the challenges faced by many in understanding their metabolic health. Links & ResourcesPodcast Home: fatsciencepodcast.comCooper Center for Metabolism: coopermetabolic.comResources from Dr. Cooper: coopermetabolic.com/resourcesJoin Our Community: patreon.com/cw/FatSciencePodcastSubmit Your Question: questions@fatsciencepodcast.com or dr.c@fatsciencepodcast.comFat Science is supported by the Diabesity Institute, a nonprofit dedicated to increasing access to effective, science-based metabolic care.This podcast is for informational purposes only and is not intended as medical advice. Please consult with a qualified healthcare provider for personalized recommendations.

Lo sponsor di questo episodio è Shopify! Prova adesso Shopify: www.shopify.com Nell'Iliade gli dèi scendevano a combattere fra gli uomini per il destino del mondo. Qui scendono in campo per un vecchio re, in una terra ai margini della Grecia. È il secondo episodio dell'arco tesprozio: la storia di Odisseo cambia registro, dalla pace di un regno appena fondato a una guerra con le divinità schierate una contro l'altra, Ares e Atena. Un episodio su cosa diventa un eroe quando il mito lo ingrandisce fino a farne il pretesto di uno scontro fra dèi. E su una domanda che riguarda chi è rimasto ad aspettare a casa. Sostieni Mitologia su Tipeee: link in descrizione. Grazie a chi rende possibile questo racconto: Alessia, Federica, Maddalena, Beniamino, Giacomo, George (il Ruandese Bresciano) e Sisifo felice. E insieme a loro: Alessia, Anna Arcoìris, Costanza Scaloni, Cristina, Daniela, Giulia, Marina, Sara e Vanessa. Alessandro, Alex, Chiara Miriam, Ergys dall'Australia, Fabio, Jimbo dal Belgio, Juan, Lidsanel da Cambridge, Michele, Mirko, Nhi Vanye i Chya, Nicola, Raul, Santo e TommasoB. Grazie ad Alessandra e ad Alessio. Grazie a tutti! .-.-. Vuoi saperne di più sull'episodio? Vai qui e leggi gli approfondimenti: https://it.tipeee.com/mitologia-le-meravigliose-storie-del-mondo-antico/news .-.-. Per avere informazioni su come puoi supportare questo podcast vai qui: https://it.tipeee.com/mitologia-le-meravigliose-storie-del-mondo-antico/ Se ti va di dare un'occhiata al libro “Il Re degli Dei”, ecco qui un link (affiliato: a te non costa nulla a me dà un piccolissimo aiuto): https://amzn.to/3Q50uFR Se ti va di dare un'occhiata al libro “Eracle, la via dell'eroe”, ecco qui un link: https://amzn.to/46dAFYZ Altri link affiliati: Lista dei libri che consiglio (lista in continuo aggiornamento): https://amzn.to/3Q3ZYI9 Lista dei film che consiglio (lista in continuo aggiornamento): https://amzn.to/3DoqTa7 Lista hardware che consiglio per chi è curioso del mondo per podcast (lista in continuo aggiornamento): https://amzn.to/44TYKTW Uso plugin audio da questa Software House: Waves. Se vuoi dare un'occhiata, anche questo è un link affiliato: https://www.waves.com/r/1196474 Ami musiche rilassanti e i suoni della natura? Iscriviti a questo meraviglioso canale  https://www.youtube.com/channel/UCbRZLgwT37437fYK4YYKhXQ?sub_confirmation=1 Learn more about your ad choices. Visit megaphone.fm/adchoices

What happens when three siblings, three distinctive voices and a lifetime of shared musical experience come together?In this episode of MyMusic, Graham Coath talks to Miccoli, the British-Italian alternative folk-pop band formed by twin brothers Alessio and Adriano Miccoli and their sister Francesca.They discuss the close harmonies at the heart of Miccoli's sound, growing up surrounded by music and the creative disagreements that inevitably arise when three siblings make records together.The conversation follows their journey from the UK and southern Italy to California, Japan and Malaysia, including appearances at legendary Los Angeles venues, recording their debut album Arrhythmia in Penang and performing on stages at London's Olympia and Wembley.Miccoli also talk about making authentic music in an attention economy, why audiences are beginning to gravitate back towards real voices and organic musicianship, and the importance of creating music they genuinely believe in rather than chasing the next algorithm-friendly hit.There are stories of videos filmed in a deserted St Mark's Square, guitar played on an Icelandic iceberg, and the near-disasters that happened behind the finished footage. The band also reveal what is coming next, including their new song “Words”, which brings Miccoli's signature sound into more uptempo territory.It is a warm, funny, wide-ranging conversation about family, creativity, authenticity, and three voices that have spent a lifetime learning how to become one.MyMusic is hosted by Graham Coath and proudly sponsored by 13th Floor Sound, the independent Las Vegas record label dedicated to keeping real music alive

Fluent Fiction - Italian: Finding Friendship Among Medieval Towers: Giulia's Journey Find the full episode transcript, vocabulary words, and more:fluentfiction.com/it/episode/2026-09-19-07-38-19-it Story Transcript:It: Nel cuore dell'autunno, quando le foglie si tingono di giallo e rosso, Giulia cammina nervosamente verso la sua nuova scuola nel villaggio di San Gimignano, con le sue torri medievali che sembrano toccare il cielo.En: In the heart of autumn, when the leaves turn yellow and red, Giulia walks nervously toward her new school in the village of San Gimignano, with its medieval towers that seem to touch the sky.It: Il sole del mattino illumina le stradine di pietra, dove gli altri studenti corrono eccitati al primo giorno di scuola.En: The morning sun lights up the cobblestone streets, where other students run excitedly on the first day of school.It: Giulia è una ragazza intelligente ma timida, nuova in città, e desidera trovare amici che la accettino per com'è.En: Giulia is an intelligent but shy girl, new in town, and she wishes to find friends who accept her for who she is.It: La paura del rifiuto, però, la frena.En: However, the fear of rejection holds her back.It: Entra nella classe, osserva Lorenzo, il ragazzo carismatico al centro dell'attenzione.En: She enters the classroom and observes Lorenzo, the charismatic boy at the center of attention.It: Tutti sembrano seguire Lorenzo, il quale ha paura che il suo vero sé possa non essere accettato.En: Everyone seems to follow Lorenzo, who fears that his true self might not be accepted.It: Nella stessa aula, un po' distante da tutti, siede Alessio.En: In the same room, sitting a bit away from everyone, is Alessio.It: È tranquillo e sempre osservatore, con il desiderio nascosto di trovare qualcuno che comprenda il suo mondo interiore.En: He is quiet and always observant, with a hidden desire to find someone who understands his inner world.It: Durante la pausa pranzo, Giulia sente un annuncio: "Oggi inizia il club di creatività dopo scuola!"En: During lunch break, Giulia hears an announcement: "Today, the creativity club starts after school!"It: È l'occasione giusta per Giulia di uscire dalla sua comfort zone.En: It's the perfect opportunity for Giulia to step out of her comfort zone.It: Decide di partecipare, anche se con un misto di ansia ed eccitazione.En: She decides to join, though with a mix of anxiety and excitement.It: Quando arriva al club, il cuore le batte velocemente.En: When she arrives at the club, her heart is racing.It: La stanza è piena di studenti e, con sua sorpresa, vede Lorenzo e Alessio lì.En: The room is full of students, and to her surprise, she sees Lorenzo and Alessio there.It: Mentre il club inizia, l'insegnante chiede chi ha un'idea per un progetto.En: As the club begins, the teacher asks who has an idea for a project.It: Giulia, raccogliendo tutto il suo coraggio, alza la mano e condivide un'idea per un murale sulla storia di San Gimignano.En: Giulia, gathering all her courage, raises her hand and shares an idea for a mural on the history of San Gimignano.It: Gli occhi di tutti sono su di lei.En: Everyone's eyes are on her.It: C'è un momento di silenzio, poi Lorenzo si alza, sorridendo.En: There is a moment of silence, then Lorenzo stands up, smiling.It: "È una splendida idea!"En: "It's a wonderful idea!"It: esclama, rompendo la tensione.En: he exclaims, breaking the tension.It: Alessio, che raramente parla, annuisce e aggiunge, "Potremmo fare delle ricerche insieme, ci sono storie affascinanti sulle torri."En: Alessio, who rarely speaks, nods and adds, "We could do some research together; there are fascinating stories about the towers."It: Giulia non riesce a credere alla sua fortuna.En: Giulia can't believe her luck.It: La sua idea ha creato un ponte tra lei, Lorenzo e Alessio.En: Her idea has built a bridge between her, Lorenzo, and Alessio.It: Lavorano insieme per il progetto, e ogni giorno che passa, Giulia si sente sempre più sicura di sé.En: They work together on the project, and with each passing day, Giulia feels increasingly confident in herself.It: Lorenzo scopre che può essere sia popolare che genuino e, attraverso le conversazioni con Giulia, Alessio trova qualcuno che lo capisce.En: Lorenzo discovers he can be both popular and genuine, and through conversations with Giulia, Alessio finds someone who understands him.It: Alla fine dell'anno scolastico, il murale è completo.En: At the end of the school year, the mural is complete.It: È un'opera d'arte che riflette la storia e i colori vibranti di San Gimignano.En: It is a work of art that reflects the history and vibrant colors of San Gimignano.It: Giulia, Lorenzo e Alessio stanno insieme a guardare il risultato del loro lavoro.En: Giulia, Lorenzo, and Alessio stand together, looking at the result of their work.It: Giulia sorride, ora sa che essere se stessa è sufficiente per trovare veri amici.En: Giulia smiles, now knowing that being herself is enough to find true friends.It: Le torri di San Gimignano brillano sotto il sole al tramonto, e tra quelle antiche mura, una nuova amicizia si è formata, forte come la pietra e colorata come l'autunno.En: The towers of San Gimignano shine under the setting sun, and among those ancient walls, a new friendship has formed, strong as stone and colorful as autumn. Vocabulary Words:the heart: il cuorenervously: nervosamentethe village: il villaggiothe tower: la torrethe morning: il mattinothe cobblestone: la pietraintelligent: intelligentethe fear: la paurarejection: il rifiutothe classroom: l'aulathe attention: l'attenzionecharismatic: carismaticoobservant: osservatorehidden: nascostothe announcement: l'annunciothe opportunity: l'occasioneanxiety: l'ansiathe surprise: la sorpresathe project: il progettoto gather: raccoglierecourage: il coraggiothe mural: il muralethe idea: l'ideathe silence: il silenzioto nod: annuirefascinating: affascinanteto believe: crederea bridge: un ponteconfident: sicuragenuine: genuino

Çdo gjë që ndodh rreth e qark nesh, drejtëpërdrejtë nga kryeqyteti. Revista ditore e ndodhive brenda dhe jashtë vendit vjen e trajtuar 360 gradë nga Top Albania Radio me të ftuar në studio, lidhje direkte dhe komunikim direkt me dëgjuesit përmes rrjeteve sociale.

Irgendwas bereuen wir doch alle: Dem oder der Ex geschrieben zu haben, zum Beispiel. Oder, einer wichtigen Person nie gesagt zu haben, dass man sie liebt. Muddern wollte wissen: Was bereut ihr? Alessio bereut, dass er seine Friends in letzter Zeit zu wenig gesehen hat – und Theo ist nach Portugal ausgewandert und nach drei Wochen zurückgekehrt.

L'Odissea finisce con il ritorno a casa. Ma un poema perduto, la Telegonia, non si accontenta: rimette Odisseo in cammino e gli regala un'altra vita, in un'altra terra. Lo seguiamo verso l'Epiro, la terra dei Tesproti, ai confini del mondo greco, dove scorre un fiume degli inferi e si scende a parlare con i morti. È la parte della sua storia che comincia dove Omero si è fermato. Un episodio su come cresce un mito, e su cosa diventa un eroe quando la tradizione lo ama troppo per lasciarlo riposare. .-.-. Grazie a chi rende possibile questo racconto:Alessia, Federica, Maddalena, Beniamino, Giacomo, George (il Ruandese Bresciano) e Sisifo felice.E insieme a loro: Alessia, Anna Arcoìris, Costanza Scaloni, Cristina, Daniela, Giulia, Marina, Sara e Vanessa. Alessandro, Alex, Chiara Miriam, Ergys dall'Australia, Fabio, Jimbo dal Belgio, Juan, Lidsanel da Cambridge, Michele, Mirko, Nhi Vanye i Chya, Nicola, Raul, Santo e TommasoB. Grazie ad Alessandra e ad Alessio. Grazie a tutti! .-.-. Vuoi saperne di più sull'episodio? Vai qui e leggi gli approfondimenti: https://it.tipeee.com/mitologia-le-meravigliose-storie-del-mondo-antico/news .-.-. Per avere informazioni su come puoi supportare questo podcast vai qui: https://it.tipeee.com/mitologia-le-meravigliose-storie-del-mondo-antico/ Se ti va di dare un'occhiata al libro “Il Re degli Dei”, ecco qui un link (affiliato: a te non costa nulla a me dà un piccolissimo aiuto): https://amzn.to/3Q50uFR Se ti va di dare un'occhiata al libro “Eracle, la via dell'eroe”, ecco qui un link: https://amzn.to/46dAFYZ Altri link affiliati: Lista dei libri che consiglio (lista in continuo aggiornamento): https://amzn.to/3Q3ZYI9 Lista dei film che consiglio (lista in continuo aggiornamento): https://amzn.to/3DoqTa7 Lista hardware che consiglio per chi è curioso del mondo per podcast (lista in continuo aggiornamento): https://amzn.to/44TYKTW Uso plugin audio da questa Software House: Waves. Se vuoi dare un'occhiata, anche questo è un link affiliato: https://www.waves.com/r/1196474 Ami musiche rilassanti e i suoni della natura? Iscriviti a questo meraviglioso canale  https://www.youtube.com/channel/UCbRZLgwT37437fYK4YYKhXQ?sub_confirmation=1 Learn more about your ad choices. Visit megaphone.fm/adchoices

The following article of the Entrepreneurs industry is: 'Family Offices: From Wealth Preservation to Strategic Capital' by Alessio Mazzanti, Managing Director, Latam Investment Banking. 

Siamo davvero noi a gestire i nostri strumenti o sono loro a gestire noi? In questo episodio con Alessio Carciofi esploriamo il confine tra iper-connessione, benessere mentale e attenzione quotidiana, per scoprire come proteggere la nostra serenità dal sovraccarico informativo. Questo è Tressessanta, il podcast sul benessere a 360° di Virginia Gambardella e Vois! Troverai un nuovo episodio, ogni mercoledì alle 17.30

Fluent Fiction - Italian: Mystery in the Canals: Livia's Quest to Save the Regata Storica Find the full episode transcript, vocabulary words, and more:fluentfiction.com/it/episode/2026-09-07-07-38-19-it Story Transcript:It: Nel cuore pulsante di Venezia, la Piazza San Marco era in piena festa.En: In the beating heart of Venezia, Piazza San Marco was in full celebration.It: Il sole di fine estate rifletteva scintille d'oro sull'acqua dei canali, e la Regata Storica prometteva spettacolo e tradizione.En: The late summer sun reflected golden sparks on the canal waters, and the Regata Storica promised spectacle and tradition.It: La folla, in ebbro festeggiamento, attendeva con ansia l'inizio della corsa.En: The crowd, in happy celebration, eagerly awaited the start of the race.It: Le gondole, decorate con nastri e fiori colorati, stavano schierate lungo il Canal Grande.En: The gondolas, decorated with colorful ribbons and flowers, were lined up along the Canal Grande.It: Livia, un'aspirante gondoliera, guardava l'orologio con preoccupazione.En: Livia, an aspiring gondolier, looked at the clock with concern.It: Il suo mentore, Giovanni, era in agitazione.En: Her mentor, Giovanni, was in agitation.It: La sua amata gondola, "La Speranza", era misteriosamente scomparsa.En: His beloved gondola, "La Speranza," had mysteriously disappeared.It: "Non possiamo iniziare senza di essa," disse Giovanni, i suoi occhi riflettendo il tormento dell'ingiustizia.En: "We can't start without it," said Giovanni, his eyes reflecting the torment of injustice.It: Alessio, un gondoliere noto per la sua competitività, si aggirava con aria di vittoria nonostante l'assenza della gondola di Giovanni.En: Alessio, a gondolier known for his competitiveness, wandered with an air of victory despite the absence of Giovanni's gondola.It: La tensione tra Livia e Alessio era palpabile.En: The tension between Livia and Alessio was palpable.It: "Forse Giovanni sa più di quanto dica," insinuò Alessio con un sorriso malizioso.En: "Maybe Giovanni knows more than he says," insinuated Alessio with a malicious smile.It: Ma Livia, determinata e sospettosa, non cadde nella provocazione.En: But Livia, determined and suspicious, did not fall for the provocation.It: Doveva scoprire la verità per dimostrare l'innocenza di Giovanni.En: She had to uncover the truth to prove Giovanni's innocence.It: Con un coraggio che non sapeva di possedere, decise di investigare da sola.En: With a courage she didn't know she possessed, she decided to investigate on her own.It: Seguendo un'intuizione, Livia si diresse verso un vecchio magazzino vicino al canale.En: Following a hunch, Livia headed towards an old warehouse near the canal.It: Le mani tremanti, aprì la porta cigolante e lì, tra le ombre, trovò "La Speranza", la gondola scomparsa.En: With trembling hands, she opened the creaky door and there, among the shadows, she found "La Speranza," the missing gondola.It: Inorridita, notò segni che indicavano che era stata nascosta con deliberata furtività.En: Horrified, she noticed signs indicating it had been deliberately hidden.It: Un rumore dietro di lei fece voltare Livia di scatto.En: A noise behind her made Livia turn around suddenly.It: Era Alessio, il suo sguardo traditore non lasciava dubbi.En: It was Alessio, his treacherous look leaving no doubt.It: "Era tutta una farsa," confessò, "volevo solo sbarazzarmi di Giovanni per vincere facilmente."En: "It was all a farce," he confessed, "I just wanted to get rid of Giovanni to win easily."It: Infuriata ma concentrata, Livia si sbrigò a ritornare in piazza, la folla ignara dei drammi che si stavano svolgendo.En: Furious but focused, Livia hurried back to the square, the crowd unaware of the dramas unfolding.It: Con voce forte e risoluta, spiegò l'inganno di Alessio al pubblico.En: With a strong and resolute voice, she explained Alessio's deception to the public.It: Gli occhi dei veneziani si riempirono di comprensione e sostegno.En: The eyes of the Venetians filled with understanding and support.It: Giovanni fu rapidamente libero da ogni sospetto.En: Giovanni was quickly cleared of any suspicion.It: La Regata Storica poteva finalmente iniziare con lo spirito rinnovato.En: The Regata Storica could finally start with renewed spirit.It: "La Speranza" solcò le acque come simbolo di verità e onore, guidata da Giovanni, con Livia al suo fianco come promessa di una nuova generazione di talenti.En: "La Speranza" sailed the waters as a symbol of truth and honor, guided by Giovanni, with Livia at his side as a promise of a new generation of talents.It: Quel giorno, Livia non trovò solo la gondola: scoprì in sé stessa la forza e la saggezza della propria eredità, e il valore dell'onestà e della fiducia.En: That day, Livia not only found the gondola: she discovered within herself the strength and wisdom of her heritage, and the value of honesty and trust.It: Mentre il sole calava, lasciando un'aura dorata su Venezia, la città celebrava le sue tradizioni, e Livia sorrideva, pronta per il futuro.En: As the sun set, leaving a golden aura over Venezia, the city celebrated its traditions, and Livia smiled, ready for the future. Vocabulary Words:the heart: il cuorethe race: la corsathe canal: il canalethe gaze: lo sguardothe warehouse: il magazzinothe deception: l'ingannothe heritage: l'ereditàthe crowd: la follathe tension: la tensionethe excitement: l'agitazionethe mentor: il mentorethe injustice: l'ingiustiziathe shadows: le ombrethe noise: il rumorethe suspicion: il sospettothe courage: il coraggiothe celebration: la festathe promise: la promessathe victory: la vittoriathe drama: il drammathe race: la garathe provocation: la provocazionethe support: il sostegnothe understanding: la comprensionethe truth: la veritàthe instinct: l'intuizionethe resolve: la determinazionethe strength: la forzathe wisdom: la saggezzathe tradition: la tradizione

Lo sponsor di questo episodio è Shopify! Prova adesso Shopify: www.shopify.com Ricordi la profezia di Tiresia: prendere un remo, camminare fino a un popolo che non conosce il mare, piantarlo nella terra e tornare. Una storia che sembra già raccontata. Eppure dietro quel gesto si nasconde molto di più, e per capirlo dobbiamo partire da un ragazzo di cui forse hai già dimenticato il nome. Torniamo indietro, a quando Odisseo è ancora vivo e gli resta da compiere l'ultimo viaggio della sua vita: un episodio sulla memoria e su ciò che resta di un uomo quando il mare lo lascia andare. Con questa puntata si apre un nuovo tempo del racconto, non più cosa è successo a Odisseo, ma cosa i secoli hanno fatto di lui. Sostieni il podcast su Tipeee. Un saluto ai custodi di questa storia: Alessia, Federica, Maddalena, Beniamino, Giacomo, George (il Ruandese Bresciano), Emanuele, Marco M. e Sisifo felice. E insieme a loro: Alessia, Anna Arcoìris, Costanza Scaloni, Cristina, Daniela, Giulia, Marina, Sara e Vanessa. Alessandro, Alex, Chiara Miriam, Ergys dall'Australia, Fabio, Jimbo dal Belgio, Juan, Lidsanel da Cambridge, Michele, Mirko, Nhi Vanye i Chya, Nicola, Raul, Santo e TommasoB. Grazie ad Alessandra e Alessio, che hanno voluto sostenere il progetto con un contributo. Grazie! .-.-. Vuoi saperne di più sull'episodio? Vai qui e leggi gli approfondimenti: https://it.tipeee.com/mitologia-le-meravigliose-storie-del-mondo-antico/news .-.-. Per avere informazioni su come puoi supportare questo podcast vai qui: https://it.tipeee.com/mitologia-le-meravigliose-storie-del-mondo-antico/ Se ti va di dare un'occhiata al libro “Il Re degli Dei”, ecco qui un link (affiliato: a te non costa nulla a me dà un piccolissimo aiuto): https://amzn.to/3Q50uFR Se ti va di dare un'occhiata al libro “Eracle, la via dell'eroe”, ecco qui un link: https://amzn.to/46dAFYZ Altri link affiliati: Lista dei libri che consiglio (lista in continuo aggiornamento): https://amzn.to/3Q3ZYI9 Lista dei film che consiglio (lista in continuo aggiornamento): https://amzn.to/3DoqTa7 Lista hardware che consiglio per chi è curioso del mondo per podcast (lista in continuo aggiornamento): https://amzn.to/44TYKTW Uso plugin audio da questa Software House: Waves. Se vuoi dare un'occhiata, anche questo è un link affiliato: https://www.waves.com/r/1196474 Ami musiche rilassanti e i suoni della natura? Iscriviti a questo meraviglioso canale  https://www.youtube.com/channel/UCbRZLgwT37437fYK4YYKhXQ?sub_confirmation=1 Learn more about your ad choices. Visit megaphone.fm/adchoices

Dall'origine del Servizio Civile Universale ai progetti culturali in Sardegna: nell'intervista Alessio Colacchi racconta opportunità, benefici e prospettive per gli studenti che desiderano acquisire competenze concrete Secondo il responsabile Alessio Colacchi, il Servizio Civile Universale rappresenta oggi una delle opportunità più interessanti per i giovani che desiderano mettersi al servizio della comunità, acquisendo allo stesso tempo competenze utili per il proprio futuro. Nell'intervista rilasciata a Unica Radio, Colacchi, impegnato nella gestione dei progetti di Servizio Civile Universale, ripercorre la storia di questo importante strumento e ne evidenzia i vantaggi, soffermandosi anche sull'esperienza maturata in Sardegna con il progetto "Giovani per la Cultura". Le origini del Servizio Civile Universale Il Servizio Civile Universale affonda le proprie radici negli anni Settanta. Nato nel 1972 come alternativa al servizio militare obbligatorio per gli obiettori di coscienza, aveva già allora un obiettivo preciso: permettere ai giovani di contribuire al bene comune attraverso attività rivolte ai cittadini. Con la sospensione della leva obbligatoria, il servizio si è trasformato profondamente. Dal 2001 è diventato una scelta volontaria aperta a ragazze e ragazzi, mantenendo però la stessa missione: favorire la partecipazione civica e promuovere valori come solidarietà, inclusione e cittadinanza attiva. Gli enti che promuovono il Servizio Civile Come spiega Colacchi, possono attivare progetti principalmente enti senza scopo di lucro. Tra questi figurano associazioni di volontariato, cooperative sociali, imprese sociali ed enti pubblici. Le opportunità sono numerose e coinvolgono realtà conosciute a livello nazionale, come Caritas, Croce Rossa, Legambiente e Arci, ma anche ministeri, università, città metropolitane e piccoli Comuni. Una rete capillare che consente ai giovani di scegliere percorsi molto diversi tra loro, in base ai propri interessi e alle proprie aspirazioni. Giovani per la Cultura, un progetto che valorizza la Sardegna Tra le esperienze raccontate durante l'intervista emerge il progetto "Giovani per la Cultura", sviluppato interamente in Sardegna. L'iniziativa coinvolge numerosi piccoli Comuni dell'isola e punta a rafforzare i servizi culturali nei territori interni. Biblioteche, musei, centri culturali e spazi polivalenti diventano luoghi di aggregazione grazie al contributo degli operatori volontari. Secondo Colacchi, questo tipo di attività produce benefici concreti. Mantenere aperta una biblioteca o organizzare iniziative culturali significa offrire occasioni di crescita alla comunità, contrastare l'isolamento e creare nuovi punti di incontro per cittadini di tutte le età. Un'esperienza che forma competenze Uno degli aspetti più importanti del Servizio Civile Universale riguarda la formazione personale e professionale. Colacchi ricorda che il servizio richiede impegno e va valutato con attenzione, soprattutto da chi frequenta l'università. Tuttavia, rappresenta anche un'occasione preziosa per affiancare allo studio un'esperienza pratica, spesso difficile da ottenere durante il p

Fluent Fiction - Italian: Unveiling Secrets: An Artistic Journey in Venice Find the full episode transcript, vocabulary words, and more:fluentfiction.com/it/episode/2026-08-29-22-34-02-it Story Transcript:It: Il sole d'estate splendeva brillante sopra il Museo d'Arte di Venezia.En: The summer sun shone brightly over the Museo d'Arte di Venezia.It: Tra i tanti turisti, Alessio camminava nervoso per i corridoi, lanciando sguardi concentrati sulle opere appese.En: Among the many tourists, Alessio walked nervously through the corridors, casting focused glances at the artworks hanging there.It: Accanto a lui, Gianna osservava con occhi attenti le delicate sfumature nascoste sotto gli strati di polvere.En: Beside him, Gianna carefully observed the delicate nuances hidden beneath layers of dust.It: "Devi fidarti di me, Alessio," disse Gianna toccandosi una ciocca di capelli biondi.En: "You must trust me, Alessio," said Gianna, touching a lock of her blonde hair.It: "Quell'opera è qui, ne sono sicura.En: "That artwork is here, I'm sure of it."It: "Alessio sospirò, nascondendo la sua insicurezza dietro un sorriso forzato.En: Alessio sighed, hiding his insecurity behind a forced smile.It: “Sei così sicura di questo?En: "Are you so sure about this?It: L'hanno dichiarato disperso da decenni.En: It's been declared lost for decades."It: ”"Ho visto libri e descrizioni che coincidono," rispose Gianna, con una nota di passione nella voce.En: "I've seen books and descriptions that match," replied Gianna, with a note of passion in her voice.It: "C'è una mostra dimenticata nel seminterrato, lì potrebbe nascondersi.En: "There's a forgotten exhibit in the basement; it might be hidden there."It: "La decisione era difficile.En: The decision was difficult.It: Alessio conosceva il suo dovere: trovare quel quadro.En: Alessio knew his duty: to find that painting.It: Era l'eredità della sua famiglia, simbolo di valore e di storia.En: It was his family's legacy, a symbol of value and history.It: Tuttavia, non poteva rischiare la sua credibilità senza una vera pista.En: However, he couldn't risk his credibility without a real lead.It: Camminarono, passando tra le stanze affollate di voci e di arte.En: They walked, passing through rooms crowded with voices and art.It: Scese la prima rampa di scale verso il seminterrato, un luogo ignorato dai più.En: They descended the first flight of stairs toward the basement, a place ignored by most.It: Le pareti scure erano coperte di ragnatele, e l'aria era ferma e silenziosa.En: The dark walls were covered with cobwebs, and the air was still and silent.It: "Credi in me," disse Gianna con un sorriso dolce.En: "Believe in me," said Gianna with a sweet smile.It: "A volte, la bellezza è nascosta, basta solo guardare oltre la superficie.En: "Sometimes, beauty is hidden; you just have to look beyond the surface."It: "In un angolo polveroso, coperto da un vecchio lenzuolo, trovarono il dipinto dimenticato.En: In a dusty corner, covered by an old sheet, they found the forgotten painting.It: Era il lavoro della vita del bisnonno di Alessio, e il cuore di quest'ultimo si riempì di emozione.En: It was the life's work of Alessio's great-grandfather, and his heart filled with emotion.It: "Lo stanno per spostare per restauri," disse Gianna mentre svelavano il pezzo, "ma se agiamo subito, riusciremo a salvarlo.En: "They're about to move it for restoration," said Gianna as they unveiled the piece, "but if we act quickly, we can save it."It: "La scoperta fu un successo.En: The discovery was a success.It: Gli occhi di Alessio brillavano mentre presentava il quadro davanti al consiglio del museo.En: Alessio's eyes shone as he presented the painting to the museum board.It: Finalmente, la storia della sua famiglia era al sicuro, e lui aveva dimostrato il suo valore.En: Finally, his family's history was safe, and he had proven his worth.It: Gianna, dal canto suo, ricevette il meritato riconoscimento.En: Gianna, for her part, received the recognition she deserved.It: La sua intuizione artistica aveva salvato una parte importante della storia, ed ora si sentiva apprezzata.En: Her artistic intuition had saved an important piece of history, and now she felt appreciated.It: Alessio e Gianna uscirono dal museo, accarezzati dalla brezza veneziana.En: Alessio and Gianna left the museum, caressed by the Venetian breeze.It: Il sole tramontava dipingendo il cielo di arancio e oro.En: The sun was setting, painting the sky with orange and gold.It: Entrambi avevano trovato qualcosa di prezioso: per Alessio, la fiducia in se stesso, per Gianna, la consapevolezza della sua bravura.En: They had both found something precious: for Alessio, confidence in himself; for Gianna, the awareness of her prowess.It: Insieme, avevano riscritto una pagina di storia.En: Together, they had rewritten a page of history. Vocabulary Words:the corridors: i corridoicarefully observed: osservava con occhi attentithe nuances: le sfumaturethe basement: il seminterratodeclared lost: dichiarato dispersothe decision: la decisionelegacy: l'ereditàcredibility: la credibilitàthe cobwebs: le ragnatelethe surface: la superficiea dusty corner: un angolo polverosothe sheet: il lenzuoloemotional: di emozionefor restoration: per restaurithe discovery: la scopertathe museum board: il consiglio del museothe recognition: il riconoscimentoartistic intuition: l'intuizione artisticaprecious: preziosoconfidence: la fiduciaprowess: la bravuraa page of history: una pagina di storiafocused glances: sguardi concentratinervously walked: camminava nervosothe forgotten exhibit: la mostra dimenticatathe flight of stairs: la rampa di scaleignored by most: ignorato dai piùsilent air: l'aria silenziosasweet smile: un sorriso dolcelife's work: il lavoro della vita

The following article of the Finance & Fintech industry is: “Financing Beyond Banks: Alternatives for Mexican Businesses” by Alessio Mazzanti, Managing Director, Latam Investment Banking. (AA1638)

Fluent Fiction - Italian: Savannah Reunion: Siblings' Journey to Family Unity Find the full episode transcript, vocabulary words, and more:fluentfiction.com/it/episode/2026-08-16-22-34-02-it Story Transcript:It: Nel cuore dell'estate a Savannah, Georgia, il sole scaldava l'antica locanda circondata da muschio spagnolo ondeggiante.En: In the heart of summer in Savannah, Georgia, the sun warmed the ancient inn surrounded by waving Spanish moss.It: I fratelli erano lì per un incontro di famiglia.En: The siblings were there for a family gathering.It: Alessio, il più grande, sentiva il peso di tenere uniti i suoi fratelli.En: Alessio, the oldest, felt the weight of keeping his siblings united.It: Aveva organizzato tutto con cura.En: He had organized everything with care.It: La locanda era piena di fascino del sud, un luogo perfetto per unirsi come famiglia.En: The inn was full of southern charm, a perfect place to come together as a family.It: Bianca, la sorella di mezzo, era distratta.En: Bianca, the middle sister, was distracted.It: Aveva trascorso gli ultimi mesi cercando di capire la sua vita.En: She had spent the last few months trying to figure out her life.It: Era artista per natura, ma recentemente non trovava ispirazione.En: She was an artist by nature, but recently she couldn't find inspiration.It: Si sentiva disconnessa, quasi persa, e temeva il giudizio dei fratelli sulle sue scelte recenti.En: She felt disconnected, almost lost, and feared her brothers' judgment on her recent choices.It: Carlo, il più giovane, era appena tornato da uno dei suoi viaggi avventurosi.En: Carlo, the youngest, had just returned from one of his adventurous trips.It: Ovunque andasse, trovava nuove storie, nuove avventure.En: Wherever he went, he found new stories, new adventures.It: La cena era pronta.En: Dinner was ready.It: Alessio aveva scelto piatti tradizionali per portare un po' di casa al loro ritrovo.En: Alessio had chosen traditional dishes to bring a bit of home to their gathering.It: Mentre mangiavano, parlarono del passato, di quando erano più giovani.En: As they ate, they talked about the past, about when they were younger.It: Ma poi la conversazione cambiò.En: But then the conversation shifted.It: "Così Bianca, cosa hai fatto ultimamente?"En: "So Bianca, what have you been up to lately?"It: chiese Carlo con un sorriso.En: Carlo asked with a smile.It: Bianca esitò, sentendosi giudicata.En: Bianca hesitated, feeling judged.It: Rispose lentamente, cercando di evitare domande più profonde: "Sto pensando a nuovi progetti, ma è tutto in evoluzione."En: She answered slowly, trying to avoid deeper questions: "I'm thinking of new projects, but it's all evolving."It: Alessio poteva sentire la tensione.En: Alessio could feel the tension.It: Voleva che quella cena fosse un'opportunità per riconnettersi, non per discutere.En: He wanted this dinner to be an opportunity to reconnect, not to argue.It: "Ho una novità," interruppe Carlo.En: "I have news," Carlo interrupted.It: "Sto pensando di partire di nuovo, ma questa volta per un viaggio più lungo."En: "I'm thinking of leaving again, but this time for a longer trip."It: Le parole di Carlo colpirono tutti.En: Carlo's words struck everyone.It: Alessio lo guardò, preoccupato.En: Alessio looked at him, worried.It: "Perché non resti un po'?En: "Why don't you stay a while?It: È importante che rimaniamo vicini," disse Alessio.En: It's important we stay close," Alessio said.It: Carlo continuò: "Voglio esplorare il mondo, ma non voglio perdere voi due.En: Carlo continued, "I want to explore the world, but I don't want to lose you two.It: Posso fare entrambe le cose."En: I can do both."It: Bianca si sentì improvvisamente coraggiosa.En: Bianca suddenly felt brave.It: "Capisco cosa intendi, Carlo.En: "I understand what you mean, Carlo.It: Anche io sto cercando un nuovo inizio, ma ho paura di sbagliare."En: I'm also looking for a new start, but I'm afraid of making mistakes."It: La conversazione si fece intensa.En: The conversation grew intense.It: Alessio si trovò a dover mediare.En: Alessio found himself having to mediate.It: "Forse dobbiamo essere più aperti, più comprensivi."En: "Maybe we need to be more open, more understanding."It: Bianca annuì, sentendosi per la prima volta accettata.En: Bianca nodded, feeling accepted for the first time.It: Carlo, con lo sguardo sereno, disse: "Non lascerò mai che i viaggi mi allontanino da voi."En: Carlo, with a serene look, said, "I'll never let my travels take me away from you."It: Alla fine della serata, i fratelli si ritrovarono cambiati.En: By the end of the evening, the siblings found themselves changed.It: Alessio capì che doveva lasciare che ognuno seguisse il proprio cammino, senza paura.En: Alessio realized he had to let each follow their own path, without fear.It: Bianca sentì il calore del supporto familiare.En: Bianca felt the warmth of family support.It: Carlo prometteva di restare più connesso, indipendentemente dai suoi viaggi futuri.En: Carlo promised to stay more connected, regardless of his future travels.It: Mentre si congedavano, il vento leggero della sera si mescolava ai loro sorrisi.En: As they bade farewell, the gentle evening breeze mingled with their smiles.It: Una nuova comprensione li univa.En: A new understanding united them.It: La locanda storica, con il suo fascino immutabile, testimoniava un legame rinnovato.En: The historic inn, with its unwavering charm, witnessed a renewed bond.It: Ogni fratello, ora, sapeva che il vero viaggio era la famiglia stessa.En: Each sibling now knew that the true journey was the family itself. Vocabulary Words:the heart: il cuorewarm: scaldarethe inn: la locandathe moss: il muschiothe sibling: il fratellothe gathering: il ritrovothe charm: il fascinothe artist: l'artistainspiration: l'ispirazionejudgment: il giudiziotradition: la tradizionethe dish: il piattothe tension: la tensionethe opportunity: l'opportunitàthe adventure: l'avventurathe mistake: l'erroreto mediate: mediarethe support: il supportothe evening: la seratathe breeze: il ventoto mingle: mescolarethe charm: il fascinothe bond: il legamethe journey: il viaggiothe fear: la paurato promise: prometterethe farewell: il congedoto unite: unireto explore: esplorarebrave: coraggioso

Fluent Fiction - Italian: Sailing to New Beginnings: An Architect and Writer's Adventure Find the full episode transcript, vocabulary words, and more:fluentfiction.com/it/episode/2026-08-15-07-38-20-it Story Transcript:It: Il sole splendeva alto nel cielo azzurro di Capri.En: The sun shone high in the blue sky of Capri.It: Il caffè sulla scogliera era pieno di vita.En: The café on the cliff was full of life.It: Il profumo del mare si mescolava all'aroma del caffè fresco.En: The scent of the sea mingled with the aroma of fresh coffee.It: Era Ferragosto, e la gente festeggiava con allegria.En: It was Ferragosto, and people were celebrating with joy.It: Tra i tavoli colorati d'ombrelloni, Alessio guardava il mare, cercando pace dai suoi pensieri.En: Among the tables colored with umbrellas, Alessio was looking at the sea, seeking peace from his thoughts.It: Alessio era un giovane architetto, appena trasferito qui dalle luci e dai rumori della città.En: Alessio was a young architect, having just moved here from the lights and noises of the city.It: Voleva ritrovare la sua passione perduta.En: He wanted to rediscover his lost passion.It: Vicino a lui, Livia stava seduta con un taccuino chiuso.En: Near him, Livia sat with a closed notebook.It: Era una scrittrice di viaggi in cerca di nuove storie.En: She was a travel writer in search of new stories.It: Anche lei cercava un po' di tranquillità e ispirazione.En: She too was looking for a bit of tranquility and inspiration.It: Si incontrarono per caso.En: They met by chance.It: Alessio fissava il mare, perdendosi nei suoi pensieri, quando Livia lo interruppe chiedendo se il posto accanto fosse libero.En: Alessio was staring at the sea, lost in his thoughts, when Livia interrupted him asking if the seat next to him was free.It: Alessio annuì e, con un sorriso, iniziò una conversazione che cambiò le loro vite.En: Alessio nodded, and with a smile, began a conversation that changed their lives.It: Parlarono del mare.En: They talked about the sea.It: Alessio raccontò di come il mare rappresentasse la libertà.En: Alessio spoke of how the sea represented freedom.It: Livia si illuminò, condividendo l'amore per il mare nei suoi viaggi.En: Livia lit up, sharing her love for the sea in her travels.It: Entrambi avevano bisogno di un nuovo inizio e il mare sembrava promettere quello.En: Both needed a fresh start, and the sea seemed to promise just that.It: Alessio parlò delle sue incertezze professionali.En: Alessio spoke about his professional uncertainties.It: Temendo di non trovare mai un vero scopo nell'architettura, sentiva di non essere all'altezza.En: Fearing he might never find true purpose in architecture, he felt he was not up to the task.It: Livia, nel frattempo, confessò il suo blocco dello scrittore.En: Livia, in the meantime, confessed her writer's block.It: Pressioni editoriali la stavano soffocando, lasciandola senza idee fresche.En: Editorial pressures were stifling her, leaving her without fresh ideas.It: Decisero di esplorare insieme.En: They decided to explore together.It: Alessio voleva trovare nuove ispirazioni nell'architettura, forse attraverso la natura.En: Alessio wanted to find new inspirations in architecture, perhaps through nature.It: Livia desiderava creare storie che rompessero la monotonia del passato.En: Livia wished to create stories that broke the monotony of the past.It: Organizzarono un'uscita in barca.En: They planned a boat trip.It: Navigando lungo la costa, il sole brillava sopra di loro.En: Sailing along the coast, the sun shone above them.It: Tuttavia, una tempesta improvvisa arrivò all'orizzonte e insieme si trovarono a fronteggiare il vento e la pioggia.En: However, a sudden storm appeared on the horizon, and together they found themselves facing the wind and rain.It: Nonostante il pericolo, la situazione li avvicinò, costringendoli a fare affidamento l'uno sull'altra.En: Despite the danger, the situation drew them closer, forcing them to rely on each other.It: Dopo l'avventura, Alessio sentì finalmente la sicurezza crescere dentro di lui.En: After the adventure, Alessio finally felt confidence growing within him.It: Poteva vedere un nuovo approccio all'architettura, legato alla natura e al mare.En: He could see a new approach to architecture, connected to nature and the sea.It: Livia, invece, trovò una nuova voce nei racconti delle esperienze condivise, una nuova narrazione che il suo pubblico avrebbe amato.En: Livia, on the other hand, found a new voice in the tales of shared experiences, a new narrative that her audience would love.It: Tornati al caffè, la tempesta era passata e con essa le loro paure.En: Back at the café, the storm had passed along with their fears.It: Alessio trovò la fiducia e la pace che cercava.En: Alessio found the confidence and peace he was seeking.It: Livia si sentì ispirata, pronta a scrivere con entusiasmo ritrovato.En: Livia felt inspired, ready to write with newfound enthusiasm.It: Il sole tramontava sul Mediterraneo, le onde si muovevano leggere e i due nuovi amici brindavano alla scoperta di nuove passioni.En: The sun set over the Mediterranean, the waves moved gently, and the two new friends toasted to the discovery of new passions.It: Capri e il suo mare avevano concesso loro un dono prezioso: il coraggio di ricominciare.En: Capri and its sea had granted them a precious gift: the courage to begin again. Vocabulary Words:the scent: il profumothe aroma: l'aromato mingle: mescolarsithe architect: l'architettothe tranquility: la tranquillitàthe inspiration: l'ispirazioneto stare: fissareto nod: annuirethe storm: la tempestato rely: fare affidamentothe fear: la paurathe narrative: la narrazionethe confidence: la fiduciathe enthusiasm: l'entusiasmoto illuminate: illuminarethe uncertainty: l'incertezzathe freedom: la libertàeditorial: editorialethe block: il bloccoto confess: confessarethe journey: il viaggiothe passion: la passionethe coast: la costato explore: esplorarethe horizon: l'orizzonteto face: fronteggiarethe wave: l'ondato toast: brindarethe courage: il coraggioto seek: cercare

My plan to celebrate the Tabletop Miniature Hobby Podcast's fifth birthday was simple. Create an open recording session and invite a handful of legendary former guests to drop in for a chat. Then, when nobody turns up, just sit there and paint a second edition Space Marine in peace.But my plans were scuppered when Jervis Johnson actually went and turned up. I was about to tell him I had a monopose Space Marine to finish when Andy Chambers dropped in, too. By the time Tuomas Pirinen arrived, my painting ambitions were in tatters. And when Alessio Cavatore pinged up on the screen, I threw my crusty old pot of Goblin Green against the wall in a fit of rage.Still, there was nothing else for it but to listen to the guys chat and make sure I kept my foot pressed firmly on the ‘record' pedal. With the recording now cut into a wax cylinder (and made available as an RSS-distributed digital audio file), I'm delighted to present it to you.Maybe it'll help you get some painting done.In all seriousness, this was a fantastic experience and truly surreal to sit on the digital wall like a large pink fly. I'm unbelievably grateful to Tuomas, Alessio, Jervis, and Andy for giving up some of their valuable time for this humble podcast, and I'll never tire of listening to any of them. Thanks for everything, chaps.What Are They Up To?The apprentice becomes the master. Jervis and Andy now serve Lord Pirinen in his all-conquering Trench Crusade empire at Factory Fortress.There are big Mantic connections, too – Jervis on DreadBall: All-Stars and Alessio on The Ghost in the Shell: Tabletop Roleplaying Game (at the time of writing, you have about 30 hours left to back this one on BackerKit!)Jervis has been working on the Perry's Valour & Fortitude 4th Edition, and Godzilla: The Roleplaying Game, too. Tuomas is also heavily involved in the final project of the legendary John Blanche – En Garde is a 54mm duelling game.Previous Tabletop Miniature Hobby Podcast AppearancesAlessio Cavatore – “There Is No Such Thing as ‘Too Simple' a Game”Hobby Q&A With Andy Chambers – “Jervis Beat Me Many Times!”Hobby Q&A With Tuomas Pirinen – “We Crave the Reality of Physical Things”Trench Crusade's Tuomas Pirinen on Narrative Gaming, Storytelling, & Running CampaignsThe 100th episode of the Tabletop Miniature Hobby PodcastThis Episode is Supported ByThe Sharp End of the BrushSupport the Show on Patreon

Fluent Fiction - Italian: Finding Freedom: An Artist's Leap into the Unknown Find the full episode transcript, vocabulary words, and more:fluentfiction.com/it/episode/2026-08-02-07-38-19-it Story Transcript:It: Il sole estivo brillava alto nel cielo azzurro sopra le Cinque Terre.En: The summer sun shone high in the blue sky above the Cinque Terre.It: Le onde si infrangevano con delicatezza contro i robusti scogli, portando con sé il profumo salmastro del mare.En: The waves gently crashed against the sturdy rocks, carrying with them the salty scent of the sea.It: Tra le vivaci case color pastello che sembravano aggrappate alle ripide colline, Alessio camminava lentamente, perduto nei suoi pensieri artistici.En: Among the vibrant pastel-colored houses that seemed to cling to the steep hillsides, Alessio walked slowly, lost in his artistic thoughts.It: Alessio era da sempre un artista alla ricerca del suo posto nel mondo.En: Alessio had always been an artist in search of his place in the world.It: Amava dipingere il paesaggio che lo circondava, ma ultimamente sentiva un vuoto dentro di sé.En: He loved painting the landscape around him, but lately, he felt an emptiness inside.It: Il suo cuore desiderava qualcosa di più, ma era combattuto tra la sicurezza della sua piccola città e il desiderio di scoprire nuovi orizzonti.En: His heart longed for something more, but he was torn between the safety of his small town and the desire to explore new horizons.It: Bianca, una vecchia amica dei tempi dell'università, era arrivata in visita.En: Bianca, an old friend from university days, had come to visit.It: Spirito libero e avventuriera, Bianca portava con sé l'energia delle terre lontane che aveva visitato.En: A free spirit and adventurer, Bianca brought with her the energy of the distant lands she had visited.It: Non vedeva l'ora di incontrare Alessio, ricordando le lunghe chiacchierate di un tempo.En: She couldn't wait to meet Alessio, recalling the long conversations of the past.It: Quando si incontrarono al piccolo caffè sulla piazza principale di Monterosso, Bianca abbracciò Alessio con entusiasmo.En: When they met at the small café on the main square of Monterosso, Bianca hugged Alessio enthusiastically.It: "Alessio!En: "Alessio!It: Che bello rivederti!"En: How wonderful to see you again!"It: disse con un grande sorriso.En: she said with a big smile.It: Alessio sorrise, ma nei suoi occhi c'era ancora un'ombra di incertezza.En: Alessio smiled, but there was still a shadow of uncertainty in his eyes.It: "Io sto bene, Bianca," rispose lui.En: "I'm fine, Bianca," he replied.It: "Ma mi sento perso.En: "But I feel lost.It: Dipingere qui non mi basta più.En: Painting here is no longer enough for me.It: Tu come stai?"En: How are you?"It: Bianca gli raccontò delle sue avventure.En: Bianca told him about her adventures.It: Era tornata per una pausa, ma già pianificava il suo prossimo viaggio.En: She had returned for a break but was already planning her next trip.It: "Perché non vieni con me?"En: "Why don't you come with me?"It: propose, gli occhi luccicanti di entusiasmo.En: she suggested, her eyes sparkling with enthusiasm.It: "Puoi dipingere ovunque.En: "You can paint anywhere.It: E io vorrei un compagno di viaggio come te."En: And I'd love a travel companion like you."It: Alessio esitò, il cuore diviso tra il desiderio di novità e la paura dell'ignoto.En: Alessio hesitated, his heart torn between the desire for new experiences and the fear of the unknown.It: Decisero di fare una passeggiata verso le colline.En: They decided to take a walk towards the hills.It: Si fermarono su un'alta scogliera, dove il vento scompigliava i capelli e il panorama mozzafiato del mare si apriva davanti a loro.En: They stopped on a high cliff, where the wind tousled their hair and the breathtaking view of the sea stretched out before them.It: "Non so se riesco a lasciare tutto," confessò Alessio, guardando l'orizzonte.En: "I don't know if I can leave everything," Alessio confessed, looking at the horizon.It: "E se non ce la faccio?En: "What if I can't handle it?It: E se perdo me stesso nel cambiamento?"En: What if I lose myself in the change?"It: Bianca gli posò una mano sulla spalla.En: Bianca placed a hand on his shoulder.It: "Il cambiamento fa paura, sì," disse dolcemente.En: "Change is frightening, yes," she said gently.It: "Ma a volte bisogna perdersi per ritrovarsi.En: "But sometimes you have to lose yourself to find yourself.It: Io sarò al tuo fianco."En: I will be by your side."It: Dopo un momento di silenzio, Alessio guardò Bianca.En: After a moment of silence, Alessio looked at Bianca.It: Nei suoi occhi c'era una nuova determinazione.En: In his eyes was a new determination.It: "Voglio provare," disse finalmente.En: "I want to try," he finally said.It: "Non posso continuare a vivere nella paura."En: "I can't keep living in fear."It: Con quella decisione presa, Alessio sentì un peso sollevarsi.En: With that decision made, Alessio felt a weight lift off him.It: Era pronto a lasciare la comodità del noto per abbracciare l'avventura con Bianca.En: He was ready to leave the comfort of the familiar to embrace adventure with Bianca.It: La vita era troppo breve per non rischiare.En: Life was too short not to take risks.It: Al tramonto, tornarono in paese, il cuore di Alessio leggero come mai prima.En: At sunset, they returned to the village, Alessio's heart lighter than ever before.It: Il mare continuava a cantare sotto di loro, mentre il futuro li attendeva, misterioso e pieno di promesse.En: The sea continued to sing below them, while the future awaited them, mysterious and full of promises.It: Alessio non sapeva dove lo avrebbe portato quel viaggio, ma sapeva con certezza di essere finalmente sulla strada giusta.En: Alessio didn't know where this journey would take him, but he knew for sure that he was finally on the right path. Vocabulary Words:the cliff: la scoglierathe landscape: il paesaggiothe emptiness: il vuotothe adventure: l'avventurathe scent: il profumothe horizon: l'orizzontethe future: il futurothe rocks: i scoglithe hillsides: le collinethe view: il panoramathe determination: la determinazionethe weight: il pesothe change: il cambiamentothe promise: la promessathe small town: la piccola cittàthe conversation: la chiacchieratathe adventure: l'avventurathe sea: il marethe wind: il ventothe fear: la paurathe artist: l'artistathe trip: il viaggiothe unknown: l'ignotothe spirit: lo spiritothe heart: il cuorethe place: il postothe safety: la sicurezzathe path: la stradathe village: il paesethe main square: la piazza principale

EP03: What we've learned from Alessio Dionisi's pre season Hello and welcome to the Watford Buzz Podcast! The Home of your Watford FC chat, featuring journalist Tom Bodell (@TBBodell), analyst Jordan Wiemer (@JordanWeimer) and hosted by commentator and presenter Matt Mesiano (@MessyMesiano) We all have one thing in common, we're all huge Watford fans and we LOVE talking about the Hornets! On today's show, Matt, Tom and Jordan discussed:The confirmation of Ravaglia (GK) and Payero (CM)How Dionisi's side is shaping up and what we've learned so far...If you want to get in touch you can do so really easily – just ping a message across on Twitter , BlueSky, OR send us an email to WatfordBuzzPodcast@gmail.com Hosted on Acast. See acast.com/privacy for more information.

Podcast 30.07.2026 Alessio Puccio Learn more about your ad choices. Visit megaphone.fm/adchoices

How do you beat the industry leader when everyone says you don't belong?In this episode of Lead The Team, Ben Fanning sits down with Alessio Artuffo, CEO of Docebo, who helped transform a small Italian startup into a global SaaS leader, scaling the business from roughly $1 million to more than $200 million in ARR.Alessio shares the pivotal moments that shaped both the company and his leadership—from being underestimated because of his accent, to winning an enterprise customer that was ten times larger than Docebo's annual revenue by competing against the industry's biggest player.He also explains why authenticity beats polish, how clarity becomes a competitive advantage as organizations grow, and why the best leaders inspire rather than control.In this episode, you'll learn:How underdogs can outperform industry leadersWhy proving people wrong became Alessio's greatest source of motivationThe leadership principles behind scaling from startup to global SaaS companyHow to build teams that thrive through trust, clarity, and accountabilityWhy AI is transforming workplace learning—and what leaders need to do differentlyWhether you're building a startup, leading a growing organization, or competing against companies much larger than your own, this conversation offers practical lessons on leadership, resilience, and scaling with purpose.Chapters:00:00 – How an underdog startup challenged the market leader02:18 – Why Alessio joined a 15-person company06:39 – The challenges of expanding into North America09:22 – The customer who criticized his accent13:35 – Winning an enterprise deal against the industry's biggest competitor20:19 – Scaling a culture built on clarity and trust24:28 – How AI is reshaping workplace learning33:10 – Why great leaders choose grace over force-----Connect with the Host, #1 bestselling author Ben FanningSpeaking and Training inquiresSubscribe to my Youtube channelLinkedInInstagramTwitter

Alessio Rega"La tela di Svevo"Les Flaneurs Edizioniwww.lesflaneursedizioni.itSvevo Altomare ha settant'anni, una carriera artistica consacrata dalla critica e un passato che continua a reclamare spazio nei suoi pensieri. Ritiratosi nella sua Molfetta, vive tra la pittura, la nostalgia e il ricordo di Sophie, l'unica donna che abbia mai amato davvero. Quando gli viene commissionato un dipinto della Madonna per una celebrazione cittadina, la sua esistenza apparentemente immobile è scossa dall'incontro con Anna Desio, una giovane arpista all'inizio di una brillante carriera internazionale. Anna è talentuosa, inquieta, combattuta tra il desiderio di libertà e una vita già tracciata da aspettative, affetti e convenzioni.Tra i due nasce un rapporto intenso e difficile da definire, fatto di dialoghi profondi, reciproche fascinazioni e domande che mettono in discussione certezze consolidate. Mentre Anna cerca il coraggio di scegliere il proprio futuro, Svevo si trova costretto a fare i conti con i rimpianti, il tempo che passa e le ferite che non si sono mai rimarginate.La tela di Svevo è un romanzo elegante e malinconico sull'amore, sull'arte e sulla libertà di essere sé stessi, anche quando il prezzo da pagare sembra troppo alto.Alessio Rega (Bari, 1984) editore. Ha fondato il Gruppo Editoriale Les Flâneurs. Ha collaborato con diverse testate giornalistiche e si è occupato di numerosi progetti di comunicazione per enti e aziende. Ha partecipato all'organizzazione di festival letterari ed eventi culturali. Nel 2014 ha esordito con il romanzo di formazione Giro di vita.  Alcuni suoi testi sono stati inseriti all'interno di saggi e raccolte.Diventa un supporter di questo podcast: https://www.spreaker.com/podcast/il-posto-delle-parole--1487855/support.IL POSTO DELLE PAROLEascoltare fa pensarehttps://ilpostodelleparole.it/

We've been running a bit of an Agent Cloud series surveying all the top inference/compute/cloud providers, from Databricks to Daytona to Railway and, even further back, E2B, but we're excited to conclude this series returning to Modal, which has just raised a monster $355M Series C.The cloud was built for developers. But agents are now changing that.The old infra stack was designed for a human who could read docs, reason through YAML, and understand dashboards to figure out what they need when something broke. While this was painful for developers, it worked since they could fill in missing context in their heads.However, agents don't have that luxury. Now in this new era of agents, everything has to be tighter.They need a place to write code, run it, inspect the output, change the environment, debug failures, and try again. Fast iteration and feedback loops with all the necessary context are crucial for agents to operate properly. Furthermore, sandboxes are a clear representation of this shift as agents can easily spin up isolated environments. This programmatic infra even extends to research:Two years ago, we were one of the first to cover Modal with CEO Erik Bernhardsson and Alessio designed our favorite LS thumbnail of all time:At the time, Modal was just a teeny little company with a $17M Series A.Today, fresh off their $355M Series C, Modal is one of the clearest examples of the agent cloud future being built in real time: a cloud platform moving past traditional web app assumptions toward the workloads AI actually creates such as elastic inference, sandboxes, GPU burst, post-training, background agents, and infrastructure that agents themselves can operate.In this episode, Modal CTO Akshat Bubna joins swyx and Vibhu to unpack why AI applications don't fit traditional cloud assumptions, why Kubernetes was never designed for bursty compute-heavy workloads, and why Modal is now shifting from developer experience to agent experience.We go deep on Modal's AI infra stack: serverless functions, decorator-based infrastructure, elastic inference for custom models, GPU snapshotting, DeFlash, speculative decoding, Auto Endpoints, sandboxes, persistent storage, networked containers, private IPv6, RDMA, multi-node training, and Modal's capacity pool across 17 cloud providers. Akshat also explains why RL rollouts can require 100,000 sandboxes, why production agents need hard guardrails, why observability may matter more than reading code, and why AI has made infrastructure exciting again.We discuss:* Why Kubernetes wasn't built for bursty AI workloads* How Modal started as a better runtime before becoming an AI cloud* Why Modal added GPUs before ChatGPT* The shift from developer experience to agent experience* Why observability matters when agents are writing the code* Elastic inference for custom models across audio, video, robotics, and comp bio* GPU snapshotting, cold starts, and why inference workloads are so bursty* Why RL rollouts can require 100,000 sandboxes* DeFlash, speculative decoding, and frontier-level inference performance* Auto Endpoints and making optimized inference easier to deploy* What Modal adds beyond vLLM, SGLang, and raw GPU rental* Modal's 17-cloud capacity pool and supercloud strategy* Networked sandboxes, sidecars, private IPv6, and RDMA* Serverless multi-node training for post-training and research workloads* Auto-research, model-guided sweeps, and agents launching GPU experiments* Compute strategy, capacity planning, and batch tiers* Why production agents need specialized sandboxes and hard guardrails* Modal's take on managed agents, CI, Gitpod/Ona, Python, TypeScript, and Modal BenchAkshat Bubna* LinkedIn: https://www.linkedin.com/in/akshat-bubna-188885103* X: https://x.com/akshat_bModal* Website: https://modal.comTimestamps00:00:00 Introduction00:00:39 Modal's origin and why Kubernetes wasn't enough00:04:32 Developer Experience → Agent Experience00:06:21 Modal's AI cloud primitives00:09:14 Sandboxes, agent loops, and proto-Cognition00:12:12 Elastic inference, GPU snapshotting, and 100,000 sandboxes00:15:24 DeFlash, speculative decoding, and Auto Endpoints00:19:59 Production-grade inference beyond raw GPUs00:22:00 Background agents, Ramp Inspect, and the agent lifecycle00:24:08 Modal's 17-cloud supercloud strategy00:26:40 Networked sandboxes, private IPv6, and RDMA00:32:48 Multi-node training, post-training, and auto research00:37:36 Compute strategy, capacity planning, and batch tiers00:40:55 Open models, real-time AI, and production agent infra00:43:06 Hard guardrails, managed agents, and specialized sandboxes00:46:06 Why AI made infrastructure exciting again00:48:30 Model APIs, differentiated products, and agentic video00:51:50 CI, coding-agent infra, SDKs, and Modal Bench00:57:28 Closing ThoughtsTranscriptIntroduction: Modal, Series C, and the Art PartySwyx [00:00:00]: We're here with Akshat, CTO of Modal, together with Vibhu. Congrats on your Series C.Akshat [00:00:10]: Thank you.Swyx [00:00:11]: Your party yesterday was amazing.Akshat [00:00:15]: Yeah.Swyx [00:00:15]: From all the photos and all the swag.Akshat [00:00:17]: We had a bunch of art installations, which was fun, seeing, like, our products on pedestals next to, like, Rodin.Swyx [00:00:25]: Very nice. Very nice. When you started, it was not the GPU inference company. Maybe it was in your mind. Take us back to the origin story.Modal's Origin: A New Runtime Beyond KubernetesAkshat [00:00:39]: I first met Eric, who's the CEO, through an investor. Back then Eric was already thinking about building, a new runtime, and he got there thinking through why are workflow orchestration products so hard to use. It's because you have to run them on Kubernetes. Kubernetes is hard to manage. It's not built for burstiness and, custom images,Swyx [00:01:03]: YeahAkshat [00:01:03]: It has a terrible developer experience.Swyx [00:01:05]: And I'll, I'll interjectAkshat [00:01:06]: YeahSwyx [00:01:07]: For listeners, who are new, we interviewed Eric two years ago, and there's a bit more of the story there from Spotify and all those things.Swyx [00:01:14]: And I came across Eric through Data Council because he did that talk on the serverless container stack that you guys did, which was like, that was my first like, “Okay, I need to take Modal very seriously” moment.Akshat [00:01:26]: Yeah.Swyx [00:01:26]: But it was still very unclear, like, do I need all this for just my data pipelines?Akshat [00:01:33]: Yeah. initially what we were thinking about was if we build a better runtime, it's a very useful primitive in itself. It's There's a lot of things that, get solved by serverless functions, like you can do, ETL stuff, you can do job queues, you can do all this, like, bursty processing, which it turns out every company had needs for. but then we also were thinking about this as like, this is a primitive that we can build a whole collection of products on, which are very verticalized. So perhaps data engineering would've been the first one, but we were thinking about inference. Back then it was more classical inference, like computer vision stuff and running XGBoosts and whatnot. But we added GPUs to the product a year before ChatGPT came out.From Serverless Containers to GPU WorkloadsSwyx [00:02:19]: Nice.Akshat [00:02:19]: We just didn't think it would be that big of a deal.Swyx [00:02:22]: Yeah, just like add A100.Vibhu [00:02:23]: Was there any, like, early key problem that really sparked off why you built it?Akshat [00:02:28]: Yeah. Primarily it's just, none of the tooling that was out there was built for, one, a really great developer experience, and also there's a general trend of, a lot of the workloads that we were seeing were very. I wish there was a better word for it, but compute-heavy. Like, they need, one, like, need a lot more resources, so you need to burst up and down a lot, versus like Kubernetes designed for, like, slow scaling and, more for, like, web server use cases. And also there's just a lot more specialization in, like, what kinds of environments these workloads run in. Like, we had sometimes they need accelerators, sometimes they need different kinds of images, and this is just like a consistent thing that we saw across a lot of companies. That would be the next step.Software-Defined Infrastructure and Decorator-Based DXSwyx [00:03:13]: Yeah. Yeah. Be nice. I don't know how much this factored into the early story, but I wrote a post when I was at Temporal about infrastructure, software-defined infrastructure or something like that.Akshat [00:03:22]: Yeah, the self-provisioningSwyx [00:03:23]: Self-provisioning.Akshat [00:03:24]: Yeah.Swyx [00:03:24]: Yeah. I can't even remember my own post.Swyx [00:03:26]: And then you put me on the landing page.Akshat [00:03:28]: Yeah. We really like, the term and so we stole it.Swyx [00:03:32]: Because you had the insight that everything can just be in decorators co-located with the code, right?Akshat [00:03:37]: Yeah.Swyx [00:03:37]: Was that a big part of the originalAkshat [00:03:39]: YesSwyx [00:03:39]: Story or it was just like a DX layer?Akshat [00:03:41]: That was, really important because we really didn't want people to spend, so much time, writing YAML, and it seemed like you could really condense the surface area of what you're doing, put it in code so you can operate on it just like you operate on other code, and like build stuff that's more expressive and dynamic. and so yeah, that was always a very important part.Swyx [00:04:04]: Then the pushback is this is a DSL.Akshat [00:04:07]: Yeah.Swyx [00:04:07]: It's you're closed source. I am locked into Modal.Akshat [00:04:11]: Yeah. We never really got pushback for that because the nice thing about Modal is you can bring whatever code you have, and sure, the DSL is at the configuration layer for, what hardware you're using, how you're scaling things up, but you still own the code.Akshat [00:04:27]: And that's, that's been an important, part of our story, even as we do inference now.Swyx [00:04:32]: Yeah.Vibhu [00:04:32]: How much of do you think still stays the same today? Like if you were to build something today, DevX very important, but I feel like, a lot of this has been changed with just hook it up to an agent, have Claude Code, have Codex implement a tool. there's very agent native primitives that are different than if I'm doing this myself, right?Developer Experience → Agent ExperienceAkshat [00:04:54]: We've changed our SDK team to think about agent experience instead of, developer experience and we think that the same benefits that apply for DX also apply for AX, which is why would you have an agent read through hundreds of Kubernetes files and like write YAML that's not even typed when it can make a couple of changes in a decorator and it gets this self-provisioning runtime of, being able to see its changes live in action? yeah, it just seems from the customers we talk to, they find Modal is much faster for agents to use versus operating on a different substrate.Swyx [00:05:34]: Yeah, because like you, again, you co-locate the infrastructure requirements to the code that runs it.Akshat [00:05:38]: Yeah.Swyx [00:05:38]: Well, the negative thesis now is that nobody's looking at their code anymore, so there's no point.Akshat [00:05:44]: Yeah, people aren't looking at code. one thing we still see is really important is observability.Swyx [00:05:51]: Yeah.Akshat [00:05:51]: Like how good is your dashboard? And of course, like we have, we push a lot of it to the CLI so the agents can do their own investigation, but you still need humans to go interpret what's going on and, make judgment calls and whatnot. and that's I feel like, Maybe more important now than looking at the code itself.Swyx [00:06:11]: Yes, because like, you can try to treat the code as a black box and then use, see the observable action that comes out of it, and then just prompt a change.What Modal Is For: AI Cloud PrimitivesAkshat [00:06:21]: Yeah.Swyx [00:06:22]: So I think it takes a bit of restraint to not specialize, to say, “I want to ship a new primitive,” and then just be general purpose.Swyx [00:06:31]: People ask you, “What are you for?” You're like, “ I don't know. We can do this, we can do that.”Vibhu [00:06:36]: Well, I'd be curious to see, like, okay, if we were to ask you, like, what is Modal for even at a high level? There's a lot you guys do, sandboxes, GPUs, everything. How do you answer?Akshat [00:06:46]: Modal is a cloud platform that's built for, where we've built the primitives from scratch for AI applications. and right now it covers, inference, training, batch processing, and sandbox workloads.Akshat [00:07:00]: But we're building a lot moreSwyx [00:07:02]: I noticed you didn't say web server, so there is still a role for, like, the always-on large-scale Kubernetes type things.Akshat [00:07:09]: Yeah, absolutely. We're, we're not trying to compete with the renders of the world, because yeah, we think the differentiator for us is the, are the workloads that need specialized compute, need to scale up and down a lot. yeah, they're, they're, they're just shaped differently.Working Alongside Frontier StartupsVibhu [00:07:26]: I think you're building a lot of it alongside the startups, right? They're innovating quite a bit, even in your, like, latest blog post. Like, even in the series C, the customers that you mention here, the cognitions, technical ones, ramps and whatnot, they're, they're innovating with you, right? And that's not something AWS is doing directly with.Akshat [00:07:45]: Yeah, absolutely. I think, this is again classic. We're a small team. We can move really fast. our engineers are working with our customers and figuring it out. Yeah.Swyx [00:07:54]: So my first week at Cognition, I walked in, there was someone wearing a Modal shirt. I was like, “What are you doing here?” They're like, “Yeah, I just. I am embedded inside of Cog.”Akshat [00:08:05]: Yeah, I think that was Peyton. We sent him overSwyx [00:08:07]: Yeah.Akshat [00:08:07]: Because, the latency of communication was too high otherwise.Swyx [00:08:12]: Yeah, distributed node, you have to - you have to place one and collocate.Vibhu [00:08:16]: Yeah.Swyx [00:08:16]: So I had a, I had direct personal experience, right? So I worked on smol developer three years ago. it was inspired by Claude 1. I think you onboarded me at some point, like, just before, and I was like, “Oh, like, I need some bursty compute. Like, I was just gonna try using Modal.” And it was a, it was a pretty pleasant experience. apparently, I showed up in the board meeting, like the analytics.smol developer, Sandboxes, and Proto-CognitionAkshat [00:08:39]: Yeah, you blew up on Hacker News and,Swyx [00:08:41]: YeahAkshat [00:08:41]: We got a big traffic spike. I. I think the way you used smol developer was Modal functions for running stuff, which was. Like, the, that was a good use case. but then, yeah.Swyx [00:08:53]: Yeah. That - So to me, that was proto-cognition.Akshat [00:08:55]: Right.Swyx [00:08:56]: If only I had, like, stuck to it.Swyx [00:08:58]: Like, that was like, if - did you say draw the tech treeAkshat [00:09:00]: AbsolutelySwyx [00:09:00]: You're just like, “Yeah, like, probably this will happen.”Akshat [00:09:02]: Yeah. Like, he was so close. You were just rebuilding upon usSwyx [00:09:04]: I just didn't realize.Akshat [00:09:05]: But the funny story there is at the same time, we were talking to a bunch of customers who needed something like sandboxing.Swyx [00:09:14]: Yeah.Akshat [00:09:14]: This is like twenty-three.Swyx [00:09:15]: Yeah.Akshat [00:09:16]: So we builtSwyx [00:09:17]: You introduced a new API right after that.Akshat [00:09:18]: Yeah.Swyx [00:09:19]: Yes.Akshat [00:09:19]: Like, we built sandboxes in May of twenty-three before anyone was even knew this was gonna be a thing. And the first example we published was, we took smol developerSwyx [00:09:28]: Smol developerAkshat [00:09:28]: And put it in a loop, so the agent can iterate on itself.Swyx [00:09:33]: Loops are hot these days.Vibhu [00:09:34]: It's the looper.Akshat [00:09:34]: Yeah.Vibhu [00:09:35]: Loops in. When was this, twenty-three?Akshat [00:09:38]: Yeah.Vibhu [00:09:39]: A small check.Akshat [00:09:39]: Yeah.Swyx [00:09:39]: It's like twenty-three. so the. the, those for listeners, like, the problem was the models are not built for any of this, right?Swyx [00:09:46]: Like, you're just trying to like. They're not post-training to understand, like, looping and, like, self-correction and tool calling was there, but, like, also not that great.Akshat [00:09:55]: Yeah.Akshat [00:09:55]: I don't remember if you used tool calling in this one, but yeah, the models would just diverge after like ten iterations and not produce anything meaningful.Swyx [00:10:03]: Yeah. But like, then. So okay, like now talking to myself three years ago, the answerVibhu [00:10:08]: Of course they will get betterSwyx [00:10:09]: Collect all the failures, build benchmark, and then collect all the, examples, build the RL environmentAkshat [00:10:15]: RightSwyx [00:10:15]: Sell it for like ten billion dollars to Meta.Swyx [00:10:17]: And then also train a model and then sell that for sixty billion dollars to Elon. And this isAkshat [00:10:23]: Yeah, of courseSwyx [00:10:23]: The funny machine. Like, it's like, it's about the hardware.Akshat [00:10:28]: It's hard to have that inherent conviction that the stuff will get that much better.Swyx [00:10:33]: In retrospect, it's so f*****g obvious.Akshat [00:10:36]: Fair enough.Swyx [00:10:37]: Like, what else were we doing back then? I don't know. anyway. Yeah. So this. That was the start of your sandboxing journey, right? I feel like it didn't blow up until, like, last year.Akshat [00:10:49]: Yeah.Swyx [00:10:50]: So there was like a couple years of quietness.Akshat [00:10:52]: Exactly, yeah. We wereVibhu [00:10:53]: I think very underrated product value. Like, my experience with Modal, Charles, before he had joined Modal, met this guy at a hackathon, and he really insisted we wanted to run some small model, not hosted anywhere, and he's like, “ there's this cool company, Modal. They'll like spin up a GPU sandbox, we can throw it on there. They'll take a Hugging Face link.” And like there's so much value just right there, right? Like instant hosting, spin it up, spin it down. It'll stay cold, but we run the demo a few days later, it'll come back up and like all this stuff in retrospect, like it's still what we needed like today.Akshat [00:11:27]: Yeah, it's still needed today. workload shapes have changed a lot as, we run stuff for people with really massive production scale and, there it's it's not about scaling from zero to one, but it's how do we scale really elastically, from like thousand to fifteen hundred GPUs very quickly in a given region. It's the same shape problem.Elastic Inference, GPU Autoscaling, and Custom ModelsVibhu [00:11:50]: Okay. So you look at, say, Cursor Composer, right?Akshat [00:11:53]: Yeah.Vibhu [00:11:53]: They had a. “We'll do RL on a model every couple hours.” you guys have a whole version of RL inference gym and whatnot.Vibhu [00:12:01]: When you look at workloads like that, you're doing train runs where you need to scale up, scale down every hour thousands of GPUs, right? That's the example for we do need it, right?Akshat [00:12:12]: Yeah. Well, so I'll, I'll take a step back and, maybe talk about like how people use Modal today. because our biggest use case is, elastic inference. And the thing we first found product market fit, with was inference for custom models. So we stayed away from the LLM space, and we were serving companies like Suno for audio, Runway for video, robotics, comp bio companies that train their own model elsewhere. But Modal is the best black box that for deployment, scaling to however many GPUs you need as your traffic pattern changes. And we saw all of them like have a very unpredict- predict- predictable, traffic pattern. it's like diurnal. It's Some days, like the company will do a launch and, they'll need like, way more. And it's not just one model that they deploy. They-- all these companies deploy, lots of different models in different regions, and so the autoscaling problem becomes even harder because then you have to scale within a certain region, and those cycles are offset. So different times you scale up in different regions.Akshat [00:13:20]: So that's like our sortVibhu [00:13:22]: And thatAkshat [00:13:22]: YeahVibhu [00:13:22]: That in and of itself is a huge category. There's a bunch of inference providers which, provide this fireworks, does this as a service together, whatnot, Base10. that's carved into its own niche for language models, at least right now.Akshat [00:13:36]: Yeah. the thing that we have specialized in is the autoscaling aspect.Vibhu [00:13:41]: Yeah.Akshat [00:13:41]: Because we found that it's not universally true that everyone else can autoscale, and we've gone deeper into it on the tech side by, we've incorporated GPU snapshotting into the product so we can take the GPU state, like your torch.compile model, snapshot it, and the next cold start is way faster. And so going back to your question, it's That's why you need a lot of burstiness for inference. But then people also do a lot of demand training, like for RL stuff, your rollouts are bursty, as you said. People also do a lot of batch jobs. So we'll see, a lot of companies, before they have a training run, they'll need thousands of GPUs to run encoding or something like that. And I think those things are much more bursty than. I agree that agents are not that bursty. sandboxes are, except when you're doing RL. RL is justRL, Batch Jobs, and 100,000 SandboxesVibhu [00:14:28]: Or commerceAkshat [00:14:28]: Insanely bursty.Vibhu [00:14:29]: Yeah.Akshat [00:14:30]: Yeah. Like when you're doing, rollouts, you sometimes need a hundred thousand sandboxes in your sandboxes.Vibhu [00:14:37]: Yeah. I'm curious if you've seen early sparks of continual learning. There are some people, like our friends, ngram, recently announced thisAkshat [00:14:45]: YeahVibhu [00:14:45]: They're, they're trying to do training. That also seems like a different workload, right? If you're doing training twenty-four/seven per se, there's a very weird dynamic of how you're using GPUs between people and whatnot, but seems like something you guys would work for.Akshat [00:15:00]: As you said, we're, we're fortunate to work with a number of, customers at the frontier and grab some of our customers. and they are taking the primitives we have, and trying to use them in very interesting ways, like continual learning. It's possible as the stuff gets better, some of that will be part of, our offering as well if, more people need it. but we're, we're just waiting to seeVibhu [00:15:23]: YeahAkshat [00:15:23]: How it shakes out.Vibhu [00:15:24]: Is there a primitive that you added after sandboxing that was the next step in the story?LLM Inference, DeFlash, and Speculative DecodingAkshat [00:15:32]: I guess we've been going much deeper into LLM inferenceVibhu [00:15:35]: YeahAkshat [00:15:35]: Because we realized that some of the advantages we have with like autoscaling, again, especially in different regions and whatnot, are, not present elsewhere. and the place where we had a gap was we weren't, working on the model layer itself. Like we were a black box. And, we realized that, we can get to frontier-level model performance, with, by having great people who work on this. And, we've been open sourcing a lot of our work, in terms of, Recently, we, shared our work on DeFlash, which is a block-based, speculator, and we've open sourced, all of it. So, you can - By using open source DeFlash, you can get the same performance as you would with one of the proprietary providers. And the next thing we're thinking about hereVibhu [00:16:23]: I thought this wasAkshat [00:16:24]: YeahVibhu [00:16:24]: An interesting blog post as well, right? Like, I think in here you make a claim that. Not a claim, just that how effective speculative deco-decoding really just get to.Akshat [00:16:33]: Yeah.Vibhu [00:16:33]: Anything you wanna point out from this around, what people should know?Akshat [00:16:39]: Yeah, absolutely. the high-level summary is, it would help to describe what speculative decoding is.Vibhu [00:16:44]: Yes.Akshat [00:16:44]: I will, yes.Vibhu [00:16:45]: I think, likeAkshat [00:16:46]: YeahVibhu [00:16:46]: So we've covered like Eagle and all thisAkshat [00:16:47]: YeahVibhu [00:16:47]: Like Hydra and all those things, but it was like two years ago.Akshat [00:16:51]: Yeah.Vibhu [00:16:51]: I think it doesn't hurt, right?Akshat [00:16:52]: Yeah. Speculative decoding is you have a smaller model, called a draft model, predict tokens ahead of the bigger model, and then you have the bigger model, verify all of this, all the tokens are predicted. And the reason it's faster is if you're predicting, one token at once, you're bound by memory bandwidth. But if you can batch the verification of, the draft model, then you're much more efficient using compute, and it's faster, and as long as your draft model is producing a lot of tokens that can get accepted, which is called the accept length, you can get a speed up that's, multiple times of, the original model speed. and well, that's what we highlight here. It's Like people talk a lot about we made these kernels faster and whatnot, but improving kernel will only give you like few percentage points of improvement, and, increasing accept length, literally is a multiplicative decreaseVibhu [00:17:47]: Like two to four X.Akshat [00:17:48]: Yeah, exactly.Vibhu [00:17:48]: Without much head-on performance.Akshat [00:17:50]: Yeah. I think it may - you are running a second model, right? So it may be something more expensive in the compute,Vibhu [00:17:57]: I meant quality performanceAkshat [00:17:58]: Probably not by muchVibhu [00:17:58]: But yeah. I thinkAkshat [00:17:59]: So there's no drop in quality performanceVibhu [00:18:01]: YeahAkshat [00:18:01]: Because you're always. You're never accepting a token that the big modelVibhu [00:18:04]: It's strictly betterAkshat [00:18:05]: YeahVibhu [00:18:05]: Or it's same.Akshat [00:18:06]: Exactly.Vibhu [00:18:07]: Right. Yeah.Akshat [00:18:08]: And so we've been working a bunch on DeFlash, which is a block-based speculator. so it's instead of predicting, one token at a time, it's predicting a block. And we've been open sourcing our work with it. The next thing for us here is for helping people train speculators and custom models. it's it's something that traditionally is very forward-deployed engineering driven, support deployed, engineer driven, like you work with customers and help them do that. And our vision for. This is why we launched Auto Endpoints, is we want to make frontier-level performance available to everyone. And so, we mentioned this in the announcement, we teased it. The next thing we're, we're launching is, as you run an auto endpoint, we shadow trafficAuto Endpoints and Frontier-Level PerformanceVibhu [00:18:54]: Do you want to explain what auto endpoints are?Akshat [00:18:57]: Yeah.Vibhu [00:18:57]: I lovely, yeah.Akshat [00:18:58]: Yeah. So, this is, I guess, going back to your Modal is you touch the code, but, sometimes people don't wanna touch the code, and they wanna get started with an endpoint that works and has all the great performance and, scalability that Modal has. So we've made that easier with, a way to create an endpoint from our UI, from the CLI, that has all of our optimizations that we talked about, like the DeFlash stuff already baked in, and there's full transparency. So we give you the code, you can go run it yourself, and if you want, you can eject out into the full Modal experience, which we see as people get sophisticated, they do wanna tweak the models, they wanna, fine-tune stuff. You can still do all of that. It's it's not a black box. And yeah, the next thing, as we teased later in the post, is how do we give you value even beyond this in terms of having your draft models evolve as your data distribution evolves, again, without having to talk to a person and, yeah.Vibhu [00:19:59]: I guess just to understand it directly, you have the GPUs, you have an endpoint that's compatible, you serve open model. If someone was to do this themselves, what's the delta that you guys provide? So you do a lot of open source great work on effective inference. how does it compare to, say, I take the same model, 5.2 FP8, take shelf inference engine, vLLM, SGLang, get compute of similar capacity, similar cost. What's the delta that plugging into something this, like this offers outside of the benefit of, scaling?Production Inference Beyond Raw GPUsAkshat [00:20:34]: It's interesting because we've taken the approach of open sourcing our contributions and upstreaming them. we work closely with the SGLang team. We want the improvements that our team, comes up with to be, there in open source for others to use, even outside of Modal. The benefit to us is we have a team that has significant expertise in terms of if you do have something that is not there, our team can help you get that performance, first. the other thing is with these endpoints, we are way more elastic, as you said, than, anyone else, and you have true scaling to zero. you have true, burstiness, and in practice, that matters a lot more to people than just finding, the GPU and, running Modal code on something.Vibhu [00:21:20]: Yeah. And I will say it's not that straightforward to just. like what I said is easier said than done, right?Akshat [00:21:26]: Yeah.Vibhu [00:21:27]: It's I think still for the average person, still hard to just gut check using different. There's, there's quite a bit of combinations you can make there. the trade-offs aren't really known at face value.Akshat [00:21:40]: Yeah. it's it's not just that. I think it's it's that running production-grade inference is a hard infer problem.Vibhu [00:21:49]: YeahAkshat [00:21:49]: Even if you subtract out the autoscalingVibhu [00:21:50]: YeahAkshat [00:21:51]: Is controlling things like tail latency and, making sure every, request is delivered at least once and whatnot.The Model and Agent LifecycleVibhu [00:22:00]: There's a lot of innovation that you can do here. I think, it's very interesting that you're starting to encroach on, like as you become a full cloud, you're starting to encroach on other people's turf.Vibhu [00:22:09]: What will you not do?Akshat [00:22:13]: Well, we wanna follow our users and, make sure they get like a platform that has everything that works well together. so right now we're focused on the model lifecycle and the agent, lifecycle. so both like going from data prep to training to inference, and then also if I want to deploy a background agent, let's say, sandbox, do persistent storage, a whole bunch of other stuff.Vibhu [00:22:38]: We talked to Cole, who did, OpenInspect. Yeah.Akshat [00:22:42]: Yeah.Vibhu [00:22:42]: And RealInspect also is on Modal.Akshat [00:22:44]: Yeah. So Ramp Inspect was a great example of a background agent that was really successful because they, were able to use some of the primitives like snapshotting and fast scaling to just have something that feels really reactive and works well.Ramp Inspect and Background AgentsVibhu [00:23:02]: Yeah. That's the new CTO of, Ramp right there.Akshat [00:23:05]: Yeah, Rahul.Vibhu [00:23:08]: It was really fun. yeah, okay, I think, all very bullish. Like, one of my reflections was also I did not originally. So when I met you guysThe Inference Inflection: CPU, GPU, and Co-LocationVibhu [00:23:19]: You weren't that much in the GPU game, and now you're all about, inference. And one of the points that I hinged on for Jensen's keynote at GTC this year was, what we're calling like the inference inflection, right? That let's say in AI workloads or machine learning workloads, it used to be like, let's call it eight to one GPU to CPU, and now it's more like one to one, which is like a interesting. Like, - because of how much agents are blocked or call out to this, to CPU heavy stuff the actual, like, limiting factor, like, swings back and forth from GPU to CPU a lot more than it used to be all GPU and then occasional CPU.Akshat [00:24:01]: Yeah.Vibhu [00:24:02]: GPU, CPU. And now it's like just constantly, and you just have to locate everything.Seventeen Clouds and the Supercloud StrategyAkshat [00:24:08]: Yeah. And that's one of the things that, again, we see as, something appealing about Modal, which is we've built this capacity pool that spans, 17 cloud providers, so we're, we're very good at Running on various kinds of cloud capacity across the worldSwyx [00:24:24]: You don't have your own data centers?Akshat [00:24:25]: We don't have our own data centers. We just run across a lot of neo cloudsSwyx [00:24:29]: Yeah. AreAkshat [00:24:30]: Metal providers.Swyx [00:24:30]: Yeah. Question mark.Swyx [00:24:31]: Yeah. You're, you're running the math, and you're like, “What's the cutover point where you're like.”Akshat [00:24:36]: Yeah, it's a good question. part of it is we see our differentiator in the software layer, and, being capital light and focusing on the software helps us move really fast. so far it's worked out well because there are so many other people building data centers that we're able to work effectively with them, and again, focus on what makes us, special.Swyx [00:24:55]: Yeah.Swyx [00:24:56]: 17 gets you into, like, the local providers sometimes. LikeAkshat [00:25:00]: The,Swyx [00:25:01]: Which was the most interesting one?Akshat [00:25:02]: There are a lot more neo clouds than you expect, and they all have various degrees of, various levels of reliability. And, that's why it's something we've invested a lot of time in, is building our own reliability layer on top. so if the GPU falls off the bus or something happens, we user workloads are not affected, and that lets us use a lot more capacity than,Swyx [00:25:30]: YeahAkshat [00:25:30]: You as a user would be able to.Swyx [00:25:32]: It's a useful thing to have because like now everyone knows, like, what layer you are and, like, you optimize for being the super cloud of all clouds.Akshat [00:25:41]: Yeah. That's, that's, that's the idea. and so I guess when you mentioned colocation, that's, that's another interesting thing where, one thing we've seen is people come to us when they want, very specifically located, CPUs or GPUs, like they wantSwyx [00:25:57]: Oh, they pin it in likeAkshat [00:25:58]: YeahSwyx [00:25:58]: EU?Akshat [00:25:59]: Exactly. Or EU, US.Swyx [00:26:01]: Right. Data resiliencyAkshat [00:26:02]: AustraliaSwyx [00:26:02]: Locality thing or performance or what?Akshat [00:26:04]: It's either data locality or latency, yeah.Swyx [00:26:07]: Yeah.Akshat [00:26:07]: Like, you want your. They're running sandboxes and model. They want them to be right next to aSwyx [00:26:10]: Yeah, it's easy thenAkshat [00:26:11]: YeahSwyx [00:26:12]: To. That is important in all those things. and so, like, you've accidentally, I don't know if it's accident, but, like, you've built the perfect primitive for agents to express themselves. And then, like, it's almost very funny how every extra development just involves more file system, just involves more CPU.Akshat [00:26:30]: Yeah.Swyx [00:26:31]: Just like the things that you already have. I don't know much about, if there's any, like, networking usages that are interesting, but you've also done some good work on networking.Networking, Sidecars, Private IPv6, and SandboxesAkshat [00:26:40]: Yeah, that's exactly right. Like, we're just taking compute storage and networking and building stuff on that layer, for, again, the stuff people need.Swyx [00:26:49]: YeahAkshat [00:26:50]: We see a few interesting networking things coming up. one is people want networked sandboxes. so we haveSwyx [00:26:57]: For like a Docker cluster type thing.Akshat [00:26:59]: Yeah.Swyx [00:26:59]: Sorry, Docker Swarm. Oh, f**k. What is it called?Akshat [00:27:02]: Compose.Swyx [00:27:03]: Compose type thing.Akshat [00:27:04]: Yeah. So if you want Docker Compose, our sandboxes now support, this thing called sidecars. So you can. A sandbox is a pod of containers, and you can run multiple containers in, a sandbox. also useful because, going back to networking, people want a lot of control over, outbound networking from a sandbox.Swyx [00:27:23]: Yeah.Akshat [00:27:23]: Like, they might wanna run a middle proxy for, like, maybe logging stuff for RL or, controlling how egress can happen to a domain, injecting credentials. and yeah. So we've, we've had to build a lot of that stuff ourselves.Swyx [00:27:38]: Yeah.Akshat [00:27:39]: But then also sometimes people want, sandboxes spanning multiple nodes to talk to each other, which is an emerging thing we're seeing. We have support for that for a different reason, and yeah, we'll see if that becomes stable.Swyx [00:27:52]: Like, just an open socket. It's a. This is directly like mTLS.Akshat [00:27:56]: We do support that, which is you can, expose a tunnel inside a sandbox.Swyx [00:28:01]: Yeah.Akshat [00:28:01]: And then you can either expose it to public internet or it can be, you can add like a HTTP, auth layer above it. But we have this thing called I6PN, which we haven't talked about, which is this, like, overlay network using IPv6 addresses. so if Modal containers, within the same workspace, when this is enabled, can address each other using this private IPv6 address, and no one else can.Akshat [00:28:28]: So it's like private networking, for containers. We built it because we needed it as a primitive for our distributed training product. so we have this other feature, which is you can add a decorator to a function, and you get a cluster of GPUs. and they have RDMA networking. so you can run a distributed training job, that's truly serverless. and we did the overlay network for that. But then we've seen that people are using it for other reasons, and, I'm intrigued to yeah, what would people do with it.Swyx [00:28:59]: Build primitives and let people figure it out, right?Akshat [00:29:01]: Yeah, exactly.Swyx [00:29:02]: You put out a pretty interestingAkshat [00:29:03]: They're like, they read the docs webpage. Let me use thatSwyx [00:29:06]: YeahAkshat [00:29:06]: Something they never intended to work. This is literally not even in our docs page. People somehow found it, and they're using it.RDMA, Memory Movement, and Distributed TrainingSwyx [00:29:12]: Huh.Swyx [00:29:14]: The way you portrayed it with, like, RDMA versus TCP, like, very well laid out, but just the transfer speed change at scale for RL, like yeah, you have it, you have it built in. I'm sure someone found it. It's found it to be a lot more efficient before you made a thing out of it, right?Akshat [00:29:32]: Yeah. And not to split hairs, I guess the overlay network is the TCP overlay network.Akshat [00:29:39]: The reason we have that is you need that to do the key exchange for RDMA before you set up the RDMA network on top of that. but then people found the TCP part.Swyx [00:29:48]: Can I tell you, this is like a big aha moment for me becauseAkshat [00:29:51]: YeahSwyx [00:29:51]: So I review 2,200 submissions for the World's Fair.Akshat [00:29:56]: Yeah.Swyx [00:29:57]: And then I got this from John OsterhoutAkshat [00:29:58]: HuhSwyx [00:29:59]: Who I don't know if. Do John Osterhout by name?Akshat [00:30:01]: The name sounds familiar.Swyx [00:30:02]: He published a. He's a well-known professor, published a lot of interesting software design books, and this is the talk he chose to submit, is on RDMA at Inference. And I'm like, you wouldn't think that this guy, who is like operating systems guy, would care about RDMA.Akshat [00:30:20]: I, it makes sense to me because I,Swyx [00:30:24]: This is the cloud, right? YeahAkshat [00:30:25]: Like, the way you move around your KV cache and how efficiently you can do it, how efficiently you move, your weights from your training GPUs to your inference GPUs in RL is there's a lot of degrees of freedom, and it is a systems problemSwyx [00:30:41]: YeahAkshat [00:30:41]: Moving memory aroundSwyx [00:30:42]: YeahAkshat [00:30:43]: Scheduling.Swyx [00:30:44]: This shows you how primitive my understanding of networking stuff is.Swyx [00:30:46]: Is this like the domain of WireGuard as well?Akshat [00:30:50]: Not quite.Swyx [00:30:51]: It's adjacent?Swyx [00:30:53]: Explain everything.Akshat [00:30:54]: Sure.Swyx [00:30:56]: How do we move memory around GPUs?Akshat [00:30:58]: Well, so sorry. Yeah, that is memory. Sorry, I was talking more, and maybe I was talking like five minutes back, about the private IPv6, addressing that you've set up.Swyx [00:31:09]: Yeah.Akshat [00:31:09]: Is it like it's a VPN?Swyx [00:31:10]: Yeah, it is like a VPN, and yeah, WireGuard is, yeah, you're right. It is,Akshat [00:31:16]: Right. Yeah, you already moved on to new topicsSwyx [00:31:17]: A similarAkshat [00:31:18]: OkaySwyx [00:31:19]: In the same space, WireGuard is, encrypted and this is,Akshat [00:31:23]: And you don't need encryption.Swyx [00:31:23]: Yeah.Akshat [00:31:24]: Yeah.Swyx [00:31:24]: This is not encrypted. that's the main difference. This is TCP and we have eBPF programs that will reject or allow the TCP connection based on whether you're allowed to do it.Akshat [00:31:35]: Used to involve a full sidecar, but now you have eBPF in the Linux kernel.Swyx [00:31:39]: Yeah.Akshat [00:31:40]: Yeah. I don't know if this is a natural follow-on to the topic of like my skepticism on distributed training is that while, like, people spend a lot of money on, like, cables to hook up GPUs, and even that is not, like, fast enough, and that's the bottleneck, is your networking fast enough?Swyx [00:31:59]: Yeah. So I guess you're talking about fully distributed training like, Dialog or something which is like cross data centerAkshat [00:32:06]: That would be, yes.Swyx [00:32:07]: That's the extreme.Akshat [00:32:08]: Yeah.Swyx [00:32:08]: You're in the middle, and then other people would have like the Mellanox cables up in, like, their actual data center.Akshat [00:32:14]: When you run multi-node training on Modal, RDMA, I think Mellanox, is, or InfiniBand is like a, is all seen as RDMA. but it's a way to bypass the TCP networking stack and, transfer, stuff much faster, between one node, to the other. And we have I think like 3 terabit per second, internal networkingSwyx [00:32:40]: OkayAkshat [00:32:40]: Which is the standard that's needed.Swyx [00:32:42]: Okay. So I misunderstood whatAkshat [00:32:43]: 50Swyx [00:32:43]: What part of the stack you wereAkshat [00:32:44]: 50 gigs overSwyx [00:32:45]: YeahAkshat [00:32:45]: If you wentSwyx [00:32:45]: YeahAkshat [00:32:46]: RDMA.Swyx [00:32:46]: Okay.Swyx [00:32:48]: Yeah. I, very impressive work.Multi-Node Training, Post-Training, and Auto ResearchSwyx [00:32:52]: So effectively you're extending like the model philosophy to the training cluster, like, yeah.Akshat [00:32:59]: Yeah. And we're, we're not going for like large scale training runs. the thing that we've built multi-node training for is, we see a lot of, smaller scale post-training. like, people are post-training like medium sized fund models, so they can, get higher quality on inference. this is a perfect fit, for something like that.Swyx [00:33:21]: Yeah. That is my impression of how a lot of these labs explore branches in post-training and then eventually merge whatever they find in.Akshat [00:33:31]: Yeah. The other use case we've seen for multi-node training is even if you have a big cluster, your researchers are still doing small runsSwyx [00:33:38]: YesAkshat [00:33:39]: Having elasticity thereSwyx [00:33:40]: Right, sureAkshat [00:33:40]: Matters a lot more.Swyx [00:33:41]: Yeah. the, like, this is like the current limiting factor for auto research, which is like you need to give your model some GPUs in order for it to completely run.Akshat [00:33:51]: We have a blog post on auto resource and model is,Swyx [00:33:55]: YeahAkshat [00:33:56]: Yeah, like, turns out to be pretty good substrate for that.Swyx [00:33:59]: So my impression is auto research means many things, likeAkshat [00:34:01]: YeahSwyx [00:34:01]: Anything that Andrej coins. Right now it's still science fair, right? Like not like, I don't know how many people are doing this.Akshat [00:34:08]: We're having a golf.Swyx [00:34:08]: Yeah.Akshat [00:34:09]: I thought the same thing.Swyx [00:34:11]: Yeah, you would know.Akshat [00:34:12]: We, like, our internal both training and inference teams use this the general shape of this quite a bit. like we have this one internal repo called auto inference, which essentially we've automated our own forward-deployed engineering efforts using, this harness, which is, the agent will just spin up a sweep of different things. It'll even run like, NVIDIA inside profiler and it'll like tweak configs and it'll arrive the right thing. it'll change your GPUs both from H200 to B200, and works really well.Swyx [00:34:47]: Nice.Akshat [00:34:47]: So yeah.Swyx [00:34:48]: By the way, I enjoy that your forward-deployed engineering is so technical that you have to do these things.Swyx [00:34:52]: It's very different from forward-deployed engineering from other people.Akshat [00:34:54]: Yeah. For our forward-deployed engineering team is, essentially they're like applied inference researchers or applied training researchers.Swyx [00:35:02]: Someone told me like they have to be able to build, but they also have to be able to sell. do they have to sell or are they like they're good, they're just like post-sale type of thing?Akshat [00:35:09]: It does, being able to talk to a customer and engage effectively with themSwyx [00:35:13]: YeahAkshat [00:35:13]: Matters a lot.Swyx [00:35:14]: They want the same thing.Akshat [00:35:15]: Yeah.Swyx [00:35:15]: ?Akshat [00:35:15]: But it's it's not really a sales, thing. We pair them with-- We have solution architects as well that are more on the sales side.Swyx [00:35:23]: Okay. Let's spend a bit more time on auto research. This is a big focus for for this year. Where does this go? like, have people explored enough? Like, there's all these beautiful charts of like improve and then level off a bit and then you find the next thing. Is this one abstraction up from normal training? Is that how we think about it, or do you think about it differently? Like model level training versus high, like driven hyperparameter search.Auto Inference and Modal BenchAkshat [00:35:51]: Yeah, like,Swyx [00:35:51]: Someone, some people call it like neural architecture search or whatever, right? Like.Akshat [00:35:54]: Yeah, - So the stuff I've seen people do with it is nowhere on the architecture level. It's pretty much tweaking parameters, but it's it's a hyperparameter sweep that's guided by some model intuition, so it's like much more efficient than, whatever other, sweep you would have.Swyx [00:36:12]: Yeah, it's just, it's just a question of where you want to spend your compute?Akshat [00:36:16]: Right.Swyx [00:36:16]: ‘Cause yeah, you can just throw infinite amounts of money on this and somehow you'll bang out Shakespeare?Akshat [00:36:22]: Yeah, infinite monkey.Swyx [00:36:24]: Yeah, so like the very good for model. and I think it's also very important that agents can spin up other agents, can spin up their infrastructure. Like very good for you. how good is our LLMs at generating model code? Like the benefit of existing LLMs is that you are in the data.Akshat [00:36:42]: Yeah. They're, they're surprisingly good. I think like pre Cloud 4 they were not, and then now they're able to shot, stuff out of the box. But we're playing around with releasing like a Modal Bench for like the harderSwyx [00:36:55]: YeahAkshat [00:36:55]: Things, that the LLMs cannot do yet and maybeSwyx [00:36:59]: What's an example of that?Akshat [00:37:01]: I think the things that- Sometimes agents struggle with, without right guidance and a skill is, how to, use the rest of our observability. Like how to. Something is failing, like how do you look at the logs and then update the right thing? It's reasoning about that. But they're able to shot, likeSwyx [00:37:23]: Yeah. You can just add a skill to it?Compute Strategy and Capacity PlanningAkshat [00:37:26]: Yeah. So we have a Modal skill now that. Which is why we built this Modal Bench. It's to find things like that, so we can address them in our tool.Swyx [00:37:35]: Tune a skill. Yeah.Akshat [00:37:36]: Yeah.Swyx [00:37:36]: No. it's it's good. are you facing any shortages? like we talk a lot about GPU shortages, but also CPU, also memory.Swyx [00:37:44]: Yeah.Akshat [00:37:45]: We have had a lot of growth, which means that, there's - we've had to be much better aboutSwyx [00:37:53]: PlanningAkshat [00:37:54]: Proactive capacity planning.Swyx [00:37:55]: Yeah.Akshat [00:37:55]: So we have,Swyx [00:37:57]: Which by the way, like it's like a MBA's like dreamAkshat [00:38:00]: YesSwyx [00:38:00]: Is like just planning this stuff. I think last time you and I talked about something maybe about this.Akshat [00:38:03]: Yeah. we have a really competent team of people that we call, The role is called compute strategy. so yeah, if anyone listening here or wants to work on thatSwyx [00:38:13]: Compute strategy?Akshat [00:38:13]: Yeah.Swyx [00:38:14]: I think,Akshat [00:38:14]: I feel like,Swyx [00:38:15]: I think the normies call it FP&A or something.Akshat [00:38:18]: Well, it's more It's it's not FP&A. It's it's There's a lot of interesting financial questions of like what is the blend between one year and three-year reservations? how do we forecast our own capacity? how do we. especially since our capacity is very fungible across different GPU types and different regions, like you have to model a lot of it. and you also have to have an opinion on how the supply chain is gonna evolve, and then you have to like, take bets,Swyx [00:38:49]: YeahAkshat [00:38:49]: Based on that.Swyx [00:38:50]: Tokenomics.Akshat [00:38:50]: Yeah.Swyx [00:38:51]: This is like probably a not a real point, but, I was trying to think about like what other industries. I was trying to think about like, we cannot be first to like these kinds of problems.Akshat [00:38:59]: Yeah.Swyx [00:39:00]: And what other industries have had this? And I was like, airlines with fuel and like they have to hedge their fuel and like, I think for a long time Southwest because they made like a hero fuel bet, they like were like super low cost becauseAkshat [00:39:12]: OhSwyx [00:39:12]: Compared to everyone else.Akshat [00:39:14]: Yeah. I hadn't thought about that.Vibhu [00:39:16]: We're at a fun time too?Akshat [00:39:18]: Yeah. It's. A lot of the compute business in general, for us is also about being very good about capacity management. That is how you have great unit, economics. but also over time it's how you can unlock more value for customers. Like, one of the things we're building now is like a way for customers to get, If they don't care about latency, like get much cheaper pricing and they'll get results back in like next 24 hours or something, like a batch tier essentially.Batch Tiers and Latency-Insensitive WorkloadsSwyx [00:39:47]: Yeah.Akshat [00:39:47]: And those are levers we have because we control the whole stack and scheduling and whatnot to give people a sufficientSwyx [00:39:53]: Yeah. I feel like they're not as popular. Like those, like the Frontier Labs have all those APIs. They're not as popular as they should be.Akshat [00:40:00]: The demand that we see for something like that is not for LLMs. although sometimes people wanna run evals andSwyx [00:40:08]: OkayAkshat [00:40:08]: Synthetic data prep and there it makes sense.Swyx [00:40:10]: Okay.Akshat [00:40:11]: But it's from a lot of LLM companies, like people who are doing computational bio, like they have to run really big batch jobs and they don't care about when they get it back.Swyx [00:40:22]: Yeah. And like they have a reasonable. It's it's also like a cousin to the stopping problem of like, will this finish in time?Akshat [00:40:30]: Yeah. You can bound it.Swyx [00:40:33]: Yeah.Akshat [00:40:33]: Like you can give peopleSwyx [00:40:34]: YeahAkshat [00:40:34]: SLAs on it.Swyx [00:40:35]: Yeah. I think what's, what's interesting is like the next phase of model.Swyx [00:40:38]: Like what, do people expect from you, now that you're established and you're like well-known compute player among all these leading companies. You had an inference launch week, and we talked a little bit about the launches. like what else? Like what else should people know?What Modal Builds NextAkshat [00:40:55]: We are building primitives that make our users' lives much easier. So, I think for example, with LLM inference, thousands more companies are gonna post-train their own models and, deploy open source models for inference. so we're thinking a lot about what is the best product shape for that. And, that involves everything from our training gym to, then, endpoints that get frontier-level performance. again, but I haven't talked to anyone. It looks somewhat different on other verticals. Like, we're also seeing a lot of real-time, audio-video stuff in there, which is why like, we're working on things like regional routing, with fallbacks. So you can get GPUs that are as close to users as possible. so you get like low latency for video streaming and whatnot. And then on the agent side, it's,Akshat [00:41:52]: We're still working very closely with our customers because stuff is changing so fast in terms of what they need. And, I think beyond sandboxes and persistent file systems, there's a lot of other things people will need from this agent stack as they build production agents. So yeah, we're thinking about those other things that fit in there.Swyx [00:42:13]: I want to ask what the other things are.Akshat [00:42:15]: Yeah. I probably should share right now.Swyx [00:42:17]: I think-- I think, okay, so, I do think a lot about the principal components of cloud, and you do talk about compute storage networking.Akshat [00:42:25]: Yeah.Swyx [00:42:25]: Because so far for me, it's fine. so far for the. the first couple generations of cloud, it's fine. What's different, qualitatively different about agents that you need some new permission level? Like a lot of people, okay, and I'll just kinda spew tokens at you until it like hopefully sparks something.Akshat [00:42:43]: Yeah.Swyx [00:42:44]: Like the new level now is whatever Claude Code does, which is dangerously scope permissions or like allow list by command or like whatever, right? And sometimes they're like, “Well, okay, we have like this adaptive thinking mode where like, just trust me, bro. I will make the calls for you.” Is that it? like mediated permissions.Hard Guardrails vs. LLM-Mediated PermissionsVibhu [00:43:03]: Now you're looping it with a goal and letting it roll.Akshat [00:43:06]: Yeah, I'm, I'm skeptical of LLM media permission for stuff that is at the sandbox level because you do want hard boundaries.Swyx [00:43:16]: Yeah.Akshat [00:43:16]: Otherwise, someone can exfiltrate stuff.Swyx [00:43:20]: But likeAkshat [00:43:20]: YeahSwyx [00:43:20]: Maybe that's old school thinking. Maybe we're the dinosaurs.Swyx [00:43:23]: Maybe the AI OS or the LLM OS is really the kernel is a goddamn LLM.Swyx [00:43:30]: Like it makes you feel uncomfortable.Akshat [00:43:31]: Yeah, I'm, I'm toldSwyx [00:43:32]: But that's what trusting the LLM is. Like imagine a spherical cow perfect LLM.Akshat [00:43:36]: Right.Swyx [00:43:37]: That it.Akshat [00:43:39]: Maybe.Swyx [00:43:41]: I wanna test the boundaries, right?Akshat [00:43:42]: Yeah.Swyx [00:43:42]: Like, and I don't believe that, but I wanna see where I'm wrong ‘cause that's, that's the consensus.Akshat [00:43:49]: Yeah. I think you always need hard guardrails when you want, And you can pair those with softer guardrails, right? And that's gonna be a lot of mediated.Managed Agents and Specialized SandboxesSwyx [00:44:00]: There. I'll also get you a end with a couple of your commentary on like the ecosystem outside of Modal. Manage agents. Everyone has one. Gemini, OpenAI, Claude, very useful for you, but also like it is their way of starting to edge into your space.Akshat [00:44:17]: Yeah.Swyx [00:44:17]: What's going on?Akshat [00:44:19]: Yeah, we're, very excited to partner with Anthropic and some of the other foundation labs, will not name who we're also working with. the way we see it is the manage agent thing is a great place to start if you're starting out building an agent and, But then when you get to, building something more production grade, like you're a company that's like Ramp that's building their own, Ramp also runs their accounting agent on us, so their external-facing agent. You need a lot more control over, your compute primitive on things like, what sort - how do you persist different files that the agent has access to, and how do you snapshot and restore? How do you control the networking? maybe you want GPUs. When you get to that point, you kinda want, a specialized sandbox provider, that gives you those things, and that's the role that we are trying to play.Swyx [00:45:15]: YeahAkshat [00:45:16]: We don't really have an opinion on the harness, whether it runs - it's a cloud-managed agent, and you hook it up to Model Sandbox, or you run the harness in Model Sandbox. We'll see where people converge with that.Swyx [00:45:26]: Yeah. Do you any opinions on like the meta harnesses, or just another layer on top of these things?Akshat [00:45:31]: You mean like the OpenPipeSwyx [00:45:33]: OpenPipe is one. I think Vercel had one, which I can't remember the name of right now. Fredshot had one. and then, to me, most recently was Data Databricks that had Omnigen. All these are meta harness. Like it's kinda pseudo agent cloud type things.Akshat [00:45:50]: I personally have not played around with them.Swyx [00:45:53]: Yeah.Akshat [00:45:53]: Build agents with them.Swyx [00:45:54]: Everything's bullish Modal, as long as it consumes more infra.Akshat [00:45:57]: That's why we're focusing on the infra layer. It's somewhere where our, relative competence is and, also it's a hard problem to solve.Swyx [00:46:06]: Yeah. I will say like just generally reflecting on that, I don't know if - if there's other topics on Modal, but like just generally reflecting as an infra person, not as intense as you, but in that field, this has like been the most exciting time in infra. Like it was boring for a while, and you couldn't really get people excited about data infrastructure. Like Eric would get on Data Console, everyone just watched the video and like say, “Look at how many sandboxes I can spin up,” and no one gave a crap.Why Infrastructure Became Exciting AgainAkshat [00:46:39]: Yeah.Swyx [00:46:40]: And like now everyone gives a crap.Akshat [00:46:42]: That's true. It is a very exciting time, and I think a lot of that's driven by just the amount of scale all of this stuff needs.Swyx [00:46:50]: I think the, like a lot of your initiatives or a lot of your like product directions make sense in retrospect, which is like the best kind, but I wouldn't necessarily have thought about it myself, which.Akshat [00:47:00]: We need the predictions.Swyx [00:47:02]: I think there's a lot that you just don't even see, right? Like you have the batch, you have the voice, you have the multimodal, but what else?Akshat [00:47:10]: What else is coming up for usSwyx [00:47:11]: Yeah. Where do you see things going?Akshat [00:47:13]: Yeah. I, in generalBiotech, Robotics, and Non-LLM AI WorkloadsAkshat [00:47:15]: It's it's clear that there's there's a huge shift happening. I think one thing that's not as obvious to people because LLM inference gets talked about so much and is also we work a lot of companies that are, doing things like drug discovery and computational bio, like the Chai Discoveries of the world. Big things are probably gonna happen there. we work a lot of robotics companies that are putting robots in like active deployments and getting good results out of them.Swyx [00:47:45]: Is there Air Gap Modal? Is there a version that is like prem air gapped whatever?Akshat [00:47:50]: No. We,Swyx [00:47:51]: You should cloud only.Akshat [00:47:51]: Yeah.Swyx [00:47:52]: Yeah. Okay. But yeah, so what you're saying is like because you're focused on primitives and they're good primitives, you find use cases in all these kinds of things.Akshat [00:48:01]: Yeah.Swyx [00:48:01]: Probably diversifies you a little bit away from LMS all the time.Akshat [00:48:05]: Yeah, absolutely. We're, we'- our goal isn't to only serve the LLM inference market.Swyx [00:48:10]: There are a lot just on the website, the audio,Akshat [00:48:12]: Yeah. We said both onSwyx [00:48:14]: Computational bio images. Yeah, there's a lot here. There's QTA TTS, customizing. Oh, Chatterbox. there was customizing Whisper.Akshat [00:48:24]: Okay. Yeah.Swyx [00:48:25]: This screen reminds me of a fallen competitor, which Replicate.Model APIs vs. Differentiated AI ProductsSwyx [00:48:31]: What's your postmortem on what happened?Akshat [00:48:34]: This is one thing we've stayed away from is providing an API for models because I think providing model APIs is some of it ends up serving like a really hobbyist market, which is much less sticky.Swyx [00:48:50]: Yeah.Akshat [00:48:50]: And we've always wanted to build for companies that are building products and need more flexibility that's not just an API.Swyx [00:48:57]: Which you can build an API for a model and this is clearly what it is. But you - but what you're saying, you can wrap it into a more fully functioning back end that you run.Akshat [00:49:06]: Yeah. So all of our examples, it's not that spin up this model, here's an API token, use it. They're all code.Swyx [00:49:13]: Okay.Akshat [00:49:13]: And so the point is that this is just an example.Swyx [00:49:16]: Starter code.Akshat [00:49:17]: Yeah. But you can tweak it however you want.Swyx [00:49:20]: Yeah.Akshat [00:49:21]: And if you're like a company building a product, like, computational bio whatnot, yeah.Swyx [00:49:26]: I guess I'm trying to tease out for listenersAkshat [00:49:28]: YeahSwyx [00:49:28]: When does it stop becoming, oh, you're just an API call and you're just a wrapper on API to becoming what you call a product, right?Swyx [00:49:36]: Like, what is that layer? Like what-- Like, more lines of code, but like beyond that, what is the substance that people add that qualifies it to be something more?Akshat [00:49:46]: I think there's a little bit of like a selection effect of like a lot of the companies who do wanna get deeper into that level are probably building something that's more differentiated. And, I think, an example is like - with LLM inference, originally we, worked with companies that were building their own post-training frameworks or they were, - Ramp early in the day was training their own tokenizer and like swapping out the tokenizer in Llama and whatnot. I'm not saying that's, that successful, in that case. But a better example is like, let's say Suno. because Suno, does not use Modal for training.Swyx [00:50:26]: Mikey on the pod. Yeah.Akshat [00:50:27]: But they use Modal for all their inference and that's because they have like a custom-- They have completely custom model architecture and that means that they have to be at the code level and tweak things that are not, just an API.Swyx [00:50:41]: It's interesting as well, like we had, Ethan, most recently on the xAI Groq team make a prediction that like the next tier in video gen is not a better video model, it's a better model or agent that orchestrates video models.Video Agents and Production WorkflowsAkshat [00:50:56]: Oh, interesting.Vibhu [00:50:56]: Language model backbone that can use toolsAkshat [00:50:58]: RightVibhu [00:50:59]: And write code.Akshat [00:51:00]: Like, yes, I can make my second video or my second video from Groq, but I want my minute video.Akshat [00:51:06]: And I'm not going there through normal video gen.Swyx [00:51:10]: Yeah, that's interesting. I - So we have GPU sandboxes and recently have seen a few companies doing agents that do video manipulation or,Akshat [00:51:22]: Yeah. Give it FFmpeg and just do it.Swyx [00:51:23]: Run FFmpeg. But likeAkshat [00:51:25]: That's not enough.Swyx [00:51:25]: Yeah.Akshat [00:51:26]: You need to give it Adobe.Swyx [00:51:27]: Yeah, I hadn't put it together with like it would be a video production thing. in my mind these things were going more towards editingAkshat [00:51:36]: Yeah.Vibhu [00:51:36]: Well, shout out Mantis.Akshat [00:51:37]: I think about this a lot.Swyx [00:51:38]: .Akshat [00:51:41]: Yeah. Sorry.Vibhu [00:51:41]: Luma. Luma Agent is a version of this for video production, but it's a off.Swyx [00:51:46]: I was gonna get your quick takes, on some other stuff that happensGitpod/Ona, CI, and Runtime SandboxesSwyx [00:51:50]: In recent news and just-just see if you have anything interesting. Gitpod, very li

Fluent Fiction - Italian: Tuscany Vineyards: Balancing Tradition & Innovation Find the full episode transcript, vocabulary words, and more:fluentfiction.com/it/episode/2026-07-08-22-34-02-it Story Transcript:It: Il sole estivo scaldava dolcemente i colli toscani.En: The summer sun gently warmed the Tuscan hills.It: Le vigne si estendevano come un mare verdeggiante sotto il cielo azzurro.En: The vineyards stretched out like a verdant sea under the blue sky.It: L'aria profumava di uva matura e fiori selvatici.En: The air was fragrant with ripe grapes and wildflowers.It: Alessio, con il volto leggermente segnato dalla fatica, sedeva pensieroso al tavolo sotto il pergolato.En: Alessio, his face slightly marked by fatigue, sat thoughtfully at the table under the pergola.It: Le foglie offrivano un po' di ombra, mentre l'odore di terra e vino li circondava.En: The leaves offered some shade, while the scent of earth and wine surrounded them.It: Gemma arrivò con passo leggero, portando con sé l'energia dell'arte e nuove idee.En: Gemma arrived with a light step, bringing with her the energy of art and new ideas.It: Aveva un sogno: trasformare parte del vigneto in un rifugio culturale.En: She had a dream: to transform part of the vineyard into a cultural retreat.It: Voleva integrare l'arte e la natura, un ponte tra tradizione e innovazione.En: She wanted to integrate art and nature, a bridge between tradition and innovation.It: Poco dopo, Luca si unì a loro.En: Soon after, Luca joined them.It: Il giovane appariva rilassato, ma dentro di sé lottava per trovare il suo ruolo tra le responsabilità familiari.En: The young man appeared relaxed but inside he struggled to find his role amidst the family responsibilities.It: Voleva fare la differenza, ma non sapeva come.En: He wanted to make a difference, but he didn't know how.It: "Allora, di cosa parliamo oggi?" chiese Luca, rompendo il silenzio.En: "So, what are we talking about today?" Luca asked, breaking the silence.It: "Tradizione," rispose Alessio fermo.En: "Tradition," Alessio replied firmly. "The vineyard must maintain its prestige.It: "Il vigneto deve mantenere il suo prestigio. Ogni anno ne va della nostra reputazione."En: Every year our reputation is at stake."It: Gemma si sporse in avanti, facendo tintinnare i bicchieri sul tavolo.En: Gemma leaned forward, making the glasses on the table clink.It: "Posso capirlo, ma immagina quante persone potremmo attrarre con un rifugio d'arte.En: "I can understand that, but imagine how many people we could attract with an art retreat.It: Porterebbe nuova vita qui."En: It would bring new life here."It: Alessio sospirò. "E se tutto questo fallisce? Rischiamo troppo."En: Alessio sighed. "And if all this fails? We risk too much."It: Luca guardò entrambi.En: Luca looked at both of them.It: Sentiva il peso delle loro aspettative.En: He felt the weight of their expectations.It: Poi, con un lampo di intuizione, intervenne.En: Then, with a flash of insight, he intervened.It: "E se provassimo con una parte piccola? Mantenendo il resto come sempre?"En: "What if we tried with a small part? Keeping the rest as it is?"It: Silenzio, poi un sorriso affiorò sul volto di Gemma.En: Silence, then a smile appeared on Gemma's face.It: "Una piccola parte... Potrei accettarlo."En: "A small part...I could accept that."It: Alessio esitò, poi annuì lentamente.En: Alessio hesitated, then nodded slowly.It: "D'accordo. Un esperimento. Vediamo come va."En: "Alright. An experiment. Let's see how it goes."It: Così, nacque un nuovo capitolo per la famiglia.En: Thus, a new chapter was born for the family.It: Alessio si sentiva più leggero condividendo il carico.En: Alessio felt lighter sharing the burden.It: Gemma aveva il suo spazio per creare.En: Gemma had her space to create.It: E Luca aveva finalmente trovato il suo scopo: gestire il progetto, un ponte tra il vecchio e il nuovo.En: And Luca had finally found his purpose: managing the project, a bridge between the old and the new.It: Il sole calava lentamente, tingendo il cielo di arancione e rosa.En: The sun slowly set, tinting the sky orange and pink.It: I tre fratelli brindarono sotto il pergolato, il vino riflettendo i colori di una nuova speranza.En: The three siblings toasted under the pergola, the wine reflecting the colors of newfound hope.It: La famiglia era unita, e la terra toscana accoglieva il loro sogno.En: The family was united, and the Tuscan land embraced their dream. Vocabulary Words:the summer: l'estatethe hills: i collithe vineyards: le vignethe fatigue: la faticathe table: il tavolothe pergola: il pergolatothe leaves: le fogliethe scent: l'odorethe wildflowers: i fiori selvaticithe dream: il sognothe retreat: il rifugiothe bridge: il pontethe tradition: la tradizionethe innovation: l'innovazionethe responsibilities: le responsabilitàthe difference: la differenzathe silence: il silenziothe prestige: il prestigiothe reputation: la reputazionethe glasses: i bicchierithe shade: l'ombrathe burden: il caricothe purpose: lo scopothe sunset: il tramontothe sky: il cielothe wine: il vinothe hope: la speranzathe family: la famigliathe land: la terrathe siblings: i fratelli

Fluent Fiction - Italian: Unraveling Tuscany's Mystery: A Summer of Secrets and Growth Find the full episode transcript, vocabulary words, and more:fluentfiction.com/it/episode/2026-07-03-07-38-19-it Story Transcript:It: La villa storica in Toscana splendeva sotto il sole estivo.En: The historic villa in Tuscany shone under the summer sun.It: Era un luogo magico, con vigneti che si estendevano a perdita d'occhio e giardini rigogliosi.En: It was a magical place, with vineyards stretching as far as the eye could see and lush gardens.It: Le stanze erano luminose, con soffitti alti e mobili ornati.En: The rooms were bright, with high ceilings and ornate furniture.It: In un angolo della Villa c'era un piccolo segreto: l'antica biblioteca, un luogo perfetto per riflessioni e indagini.En: In one corner of the villa, there was a little secret: the ancient library, a perfect place for reflection and investigation.It: Sofia, giovane e acuta osservatrice, era lì per passare l'estate con i suoi cugini, Matteo e Alessio.En: Sofia, a young and keen observer, was there to spend the summer with her cousins, Matteo and Alessio.It: Matteo era spensierato e affascinante, sempre pronto a una risata, mentre Alessio preferiva i libri alla compagnia, riservato ma profondo nei suoi pensieri.En: Matteo was carefree and charming, always ready for a laugh, while Alessio preferred books to company, reserved but deep in his thoughts.It: Un giorno, un prezioso cimelio di famiglia scomparve misteriosamente.En: One day, a precious family heirloom mysteriously disappeared.It: Era un oggetto di grande valore, sia economico che affettivo.En: It was an object of great value, both economic and sentimental.It: Sofia sentì immediatamente il peso del mistero.En: Sofia immediately felt the weight of the mystery.It: Non voleva che i suoi cugini fossero accusati ingiustamente.En: She didn't want her cousins to be unjustly accused.It: Si mise al lavoro, fingendo una certa indifferenza mentre investigava.En: She set to work, pretending a certain indifference while she investigated.It: Osservava ogni dettaglio, ogni sguardo, raccogliendo piccoli indizi.En: She observed every detail, every glance, gathering small clues.It: Chiacchierava casualmente con Matteo e Alessio, cercando di capire cosa fosse davvero successo.En: She chatted casually with Matteo and Alessio, trying to understand what had really happened.It: La tensione cresceva nella villa.En: The tension in the villa was growing.It: Matteo si sentiva accusato a causa delle sue marachelle passate.En: Matteo felt accused because of his past pranks.It: Alessio temeva di essere colpevole per la sua distrazione.En: Alessio feared he might be guilty due to his distraction.It: Ma Sofia era determinata a trovare la verità.En: But Sofia was determined to find the truth.It: Dopo giorni di indagini silenziose, Sofia convocò i suoi cugini in biblioteca.En: After days of silent investigations, Sofia summoned her cousins to the library.It: C'era un'aria di suspense.En: There was an air of suspense.It: Con calma, rivelò ciò che aveva scoperto: Matteo aveva nascosto il cimelio come uno scherzo.En: Calmly, she revealed what she had discovered: Matteo had hidden the heirloom as a prank.It: Però lo scherzo era sfuggito di mano.En: However, the joke had gotten out of hand.It: In un attimo di dramma, Matteo capì l'importanza della responsabilità.En: In a moment of drama, Matteo realized the importance of responsibility.It: Si scusò con sincerità e restituì l'oggetto.En: He apologized sincerely and returned the object.It: I cugini si guardarono negli occhi, sentendo il peso delle parole non dette e delle tensioni sciogliersi come neve al sole.En: The cousins looked each other in the eye, feeling the weight of unspoken words and tensions dissolve like snow in the sun.It: La villa tornò serena.En: The villa returned to serenity.It: Con il cimelio al suo posto, i tre giovani godettero del resto dell'estate senza tensioni.En: With the heirloom back in place, the three young people enjoyed the rest of the summer without tensions.It: Sofia guadagnò fiducia nelle sue capacità; Matteo imparò il valore delle sue azioni; Alessio scoprì quanto il suo legame con i cugini fosse prezioso.En: Sofia gained confidence in her abilities; Matteo learned the value of his actions; Alessio discovered how precious his bond with his cousins was.It: Il sole tramontava sui vigneti, gettando lunghe ombre che nascondevano i segreti dal passato.En: The sun set over the vineyards, casting long shadows that hid secrets from the past.It: Ma per Sofia, Matteo e Alessio, il futuro era luminoso e pieno di nuove esperienze da condividere.En: But for Sofia, Matteo, and Alessio, the future was bright and full of new experiences to share.It: La villa risuonava di risate e complicità, un'estate in Toscana che nessuno di loro avrebbe mai dimenticato.En: The villa echoed with laughter and camaraderie, a summer in Tuscany that none of them would ever forget. Vocabulary Words:the villa: la villathe summer: l'estatethe vineyard: i vignetithe ceiling: il soffittoornate: ornatilush: rigogliosithe secret: il segretoreflection: riflessionethe investigation: l'indaginethe heirloom: il cimeliocarefree: spensieratocharming: affascinantereserved: riservatothe gaze: lo sguardothe tension: la tensioneto accuse: accusarethe prank: la marachellasincerely: con sinceritàto dissolve: sciogliersithe drama: il drammato apologize: scusarsithe responsibility: la responsabilitàthe bond: il legameprecious: preziosothe laughter: le risatethe camaraderie: la complicitàthe mystery: il misterothe shadow: l'ombrathe sunset: il tramontothe clue: l'indizio

L'estate in Italia è sinonimo di piazze vive, musica all'aperto e, soprattutto, tanto buon cibo. Ma ti sei mai chiesto qual è la differenza esatta tra una sagra e un festival? O perché una manifestazione non è sempre una protesta?Nell'ultimo episodio della stagione 13 di

Vi è mai capitato di discutere con qualcuno che continua a fare ipotesi impossibili su cose ormai passate? "Se avessi fatto così...", "Se fossi partito prima...". In Italia abbiamo un modo decisamente originale, ironico e un po' bizzarro per stroncare questi discorsi: tirare in ballo i nonni... e le ruote!In questa puntata di Italiano ON-Air, Katia e Alessio prendono spunto da una recentissima e virale conferenza stampa di Carlo Ancelotti ai Mondiali di calcio 2026 per fare un viaggio semiserio tra i proverbi regionali più divertenti d'Italia e la grammatica del quotidiano.

Simone Zullo, titolare con il fratello Alessio della pizzeria Fratelli Pulcinella di Parramatta, ha vinto la XXIII edizione del Campionato Mondiale del Pizzaiuolo – Caputo Cup, nella prestigiosa categoria Pizza Napoletana S.T.G. (Specialità Tradizionale Garantita).Seguici su Facebook e Instagram o abbonati ai nostri podcast cliccando qui. 

Fluent Fiction - Italian: Discovering Leonardo: A Journey of Art and Innovation Find the full episode transcript, vocabulary words, and more:fluentfiction.com/it/episode/2026-06-21-22-34-01-it Story Transcript:It: Alessio e Ginevra camminano fianco a fianco nel Museo della Scienza e della Tecnologia Leonardo da Vinci.En: Alessio and Ginevra walk side by side in the Museo della Scienza e della Tecnologia Leonardo da Vinci.It: È estate e il sole entra dalle grandi finestre, illuminando i modelli e le stazioni interattive.En: It's summer, and the sun streams in through the large windows, illuminating the models and interactive stations.It: Il museo è affollato di visitatori, affascinati dalle invenzioni geniali esposte.En: The museum is crowded with visitors, fascinated by the brilliant inventions on display.It: Alessio, con gli occhi scintillanti, è pieno di entusiasmo.En: Alessio, with sparkling eyes, is full of enthusiasm.It: "Guarda, Ginevra!En: "Look, Ginevra!It: Hanno un'intera sezione dedicata ai macchinari di Leonardo."En: They have an entire section dedicated to Leonardo's machinery."It: Ginevra sorride, osservando con calma.En: Ginevra smiles, observing calmly.It: "Sì, è incredibile.En: "Yes, it's incredible.It: Ammiravo sempre la sua capacità di fondere arte e scienza."En: I always admired his ability to merge art and science."It: Arrivano al negozio di souvenir.En: They arrive at the souvenir shop.It: È pieno di scaffali con libri e modelli intricati.En: It's filled with shelves of books and intricate models.It: Alessio si precipita subito verso una figura in movimento che riproduce un uomo vitruviano meccanico.En: Alessio immediately rushes towards a moving figure that reproduces a mechanical Vitruvian Man.It: "Ginevra, non è fantastico?"En: "Ginevra, isn't it fantastic?"It: chiede Alessio, impaziente di passare al prossimo oggetto.En: asks Alessio, impatient to move on to the next object.It: "L'idea mi piace, ma dobbiamo scegliere con cura.En: "I like the idea, but we must choose carefully.It: Ogni oggetto ha una storia," risponde Ginevra, con calma.En: Every item has a story," Ginevra responds calmly.It: Mentre lei esamina con attenzione una collezione di quaderni, Alessio si allontana, alla ricerca di qualcosa che lo colpisca immediatamente.En: While she carefully examines a collection of notebooks, Alessio wanders off, searching for something that immediately strikes him.It: La sua voglia di trovare un oggetto unico lo spinge a esplorare ogni angolo del negozio.En: His desire to find a unique object drives him to explore every corner of the store.It: Finalmente, raggiungono una sezione del negozio con in mostra un modello in edizione limitata della macchina volante di Leonardo.En: Finally, they reach a section of the shop displaying a limited edition model of Leonardo's flying machine.It: Alessio e Ginevra si fermano, entrambi attratti dalla meraviglia di quell'opera.En: Both Alessio and Ginevra stop, drawn by the wonder of that work.It: "Ginevra, è perfetto!En: "Ginevra, it's perfect!It: Rappresenta la sua innovazione e il suo splendore storico," esclama Alessio con entusiasmo condiviso.En: It represents his innovation and historical splendor," exclaims Alessio with shared enthusiasm.It: Ginevra annuisce, percependo l'unione ideale di tecnologia e storia.En: Ginevra nods, sensing the ideal union of technology and history.It: "Hai ragione, Alessio.En: "You're right, Alessio.It: Questo è qualcosa che rappresenta entrambi i nostri interessi."En: This is something that represents both of our interests."It: Acquistano il modello con un senso di soddisfazione.En: They purchase the model with a sense of satisfaction.It: Mentre escono dal museo, Alessio apprezza la riflessione di Ginevra sui dettagli, mentre Ginevra impara a godere dell'energia di Alessio verso l'innovazione.En: As they leave the museum, Alessio appreciates Ginevra's reflection on details, while Ginevra learns to enjoy Alessio's energy towards innovation.It: Insieme, escono nel luminoso sole estivo, contenti della scelta condivisa.En: Together, they step into the bright summer sun, pleased with their shared choice.It: Entrambi hanno imparato qualcosa di più l'uno dall'altro, lasciando alle spalle una giornata splendidamente memorabile nel cuore del genio di Leonardo da Vinci.En: Both have learned something more about each other, leaving behind a beautifully memorable day in the heart of the genius of Leonardo da Vinci. Vocabulary Words:the genius: il geniothe window: la finestrathe visitor: il visitatorethe invention: l'invenzionethe souvenir shop: il negozio di souvenirthe shelf: lo scaffaleintricate: intricatothe notebook: il quadernoenthusiasm: l'entusiasmoto merge: fonderebrilliant: genialesparkling: scintillanteto admire: ammirarethe reflection: la riflessionethe detail: il dettagliomechanical: meccanicomoving: in movimentoto examine: esaminareto explore: esplorareunique: unicothe corner: l'angolothe model: il modellolimited edition: edizione limitatathe flying machine: la macchina volantethe splendor: lo splendoreto purchase: acquistaresatisfaction: la soddisfazionehistorical: storicoto enjoy: goderebright: luminoso

Adattamento audio: Matteo D'Alessandro - www.matteodalessandro.com Per approfondire gli argomenti della puntata: La nostra serie Imperatores, sugli imperatori romani : https://youtube.com/playlist?list=PLpMrMjMIcOkkIDocjNI3Q7gCk-4bOiVVO Le altre puntate sulla storia di Roma antica : https://youtube.com/playlist?list=PLpMrMjMIcOkkVlao9HeDl3jIHVKO3IcR_

Avete mai fatto caso a cosa c'è disegnato sul retro degli euro italiani? In questa nuova puntata di

Eddie and Carducci tell Capper about the UFC fight he missed. Also Capper compiles theworst warehousing job stories. Join the PATREON HERE - Just $7 (AUD) for bonus eps and content - get tons of behind the scenes hacks and pranks and help keep this podcast going! Go watch Capper's special Hold Me Closer Tiny Cancer HERE Follow CAPPER and ROHAN and PHONE HACKS on Instagram Subscribe where you're listening and leave a review to get the word out thereSee omnystudio.com/listener for privacy information.

EP01: Who is the new Head Coach Alessio Dionisi? Hello and welcome to the Watford Buzz Podcast! The Home of your Watford FC chat, featuring journalist Tom Bodell (@TBBodell), analyst Jordan Wiemer (@JordanWeimer) and hosted by commentator and presenter Matt Mesiano (@MessyMesiano) We all have one thing in common, we're all huge Watford fans and we LOVE talking about the Hornets! On today's show, Matt, Tom and Jordan discussed:Pay our respects to Kenny JacketChat Watford Players at the World CupDiscuss the new head coach Alessio DionisiIf you want to get in touch you can do so really easily – just ping a message across on Twitter , BlueSky, OR send us an email to WatfordBuzzPodcast@gmail.com Hosted on Acast. See acast.com/privacy for more information.

Alessio e Katia ci portano a fare un viaggio emozionante nel tempo e attraverso l'Oceano, partendo dalle celebrazioni della Festa della Repubblica fino a toccare le storie dei milioni di italiani emigrati all'estero, grazie alle pagine di un grande capolavoro della letteratura italiana contemporanea: Novecento di Alessandro Baricco

In questo episodio di

We've talked a lot about how money works and why countries have their own currencies here on “Million Bazillion.” But listener Alessio wants to know: Why DOESN'T the whole world use the same money? And could the world's nations all decide to just use one shared currency? In this bonus mini-episode, we'll get some answers!

We've talked a lot about how money works and why countries have their own currencies here on “Million Bazillion.” But listener Alessio wants to know: Why DOESN'T the whole world use the same money? And could the world's nations all decide to just use one shared currency? In this bonus mini-episode, we'll get some answers!

Take the 2026 AI Engineering Survey and get >$2k in credits and AIE WF tickets!This was recorded before Railway suffered a major GCP outage on May 19, despite being a multi-AZ, multi-zone mesh ring, with HA fiber interconnects between their Metal GCP AWS, because workload discoverability was unintentionally still tied to GCP. All has been resolved with a post-mortem.Railway did not start as an AI infrastructure company.It was founded in 2020 years before agents became the default way people thought about deploying software. Jake Cooper, formerly at Bloomberg and Uber, started Railway with a simple obsession: the activation energy to ship something to production should be near zero. Push code, get a URL, iterate. No Docker files, no Kubernetes manifests, no Ansible scripts stacked on Ansible scripts.For years, this was a slow grind. Railway spent its first 18 months hand-acquiring its first 100 users with Jake personally greeting every Discord signup on a second monitor.Today, Railway has raised $124m and is growing very fast. A 35-person team supports 3 million users, adding roughly 100,000 signups a week. Their bare metal data centers have a 3-month payback period vs. renting in the cloud, with 70% margins funding aggressive cloud bursting when needed. The servers they own have actually appreciated in value as RAM prices have climbed basically meaning the value of their hardware now exceeds the capital they've raised.From rebuilding Railway's network overlay over a weekend to moving the vast majority of workloads onto its own bare metal data centers, Jake Cooper is trying to build a new cloud for an agent-native world. In this episode, Railway's founder and “conductor” joins swyx and Alessio to unpack why the next era of software infrastructure is not just “Heroku but newer,” what agents need that humans did not, and why the old deployment loop of Git, PRs, CI/CD, and static cloud resources may be heading for a rewrite.We go deep on Railway's infrastructure stack: own-metal data centers, three-month cloud payback periods, cloud bursting, data center debt, Railpack, Nixpacks, Temporal, feature flags, Central Station, content-addressable filesystems, agent-safe production forks, and why the CLI may become more important than the canvas in an agent world. Jake also shares the founder journey behind Railway, how the company survived losing $500K/month, why it now serves millions of users with only 35 people, and why he believes the pull request is dying.We discuss:* How Railway went from a slow six-year grind to adding 100,000 users a week* How Railway thinks about agents as the next dominant software species* Why agents need version control, observability, compute, storage, and orchestration at 1000x scale* The economics of Railway's own-metal data centers and three-month payback* How Railway uses cloud bursting while scaling its own infrastructure* Why data center debt can be a better tool than venture debt for infra startups* Central Station, Railway's internal system for clustering customer feedback and incidents* Why responsible disclosure and over-communication matter for platforms* Why feature flags, progressive rollouts, and shadow traffic are essential for agents* Temporal's strengths, pain points, and why workflows matter for agents* Railpack, Nixpacks, Nix, and lazy-loaded content-addressable filesystems* Why “cattle, not pets” may change if you can clone the pets* Why Railway is building a new cloud from scratch instead of copying hyperscalers* The solo founder path, focus, writing, and how Jake thinks about company buildingRailway:* Website: https://railway.com/* X: https://x.com/RailwayJake Cooper:* LinkedIn: https://www.linkedin.com/in/thejakecooper/* X: https://x.com/JustJakeTimestamps00:00:00 Introduction: What Is Railway?00:02:07 Jake's Path to Railway00:06:13 Railway's Six-Year Growth Story00:08:52 Rebuilding the Business After the Free Tier00:11:17 Agents as the Next Software Platform00:13:29 Railway's Infrastructure Philosophy00:15:42 Bare Metal, Cloud Economics, and the Compute Crunch00:17:22 Cloud Bursting and Five-Cloud Networking00:20:20 Data Center Debt and Infra Financing00:23:31 Data Centers in Space00:25:24 What Agents Need From Infrastructure00:28:24 CLIs, Canvas, and Agent-Native UX00:35:15 Central Station, Incidents, and Responsible Disclosure00:40:30 Safe Rollouts, SRE Agents, and Production Forks00:45:00 AI SRE, Specs, Code, and Tests00:48:24 Self-Replicating Infrastructure and the New Serverless00:53:18 Heroku, Temporal, and Workflow Engines01:04:07 Railpack, Nixpacks, and Lazy-Loaded Filesystems01:06:01 Coding Agents, Token Spend, and Roadmap Acceleration01:10:56 The Pull Request Is Dying01:12:28 Feature Flags and the Agent-Era SDLC01:16:15 Cattle, Pets, and Cloning Machines01:19:29 Solo Founder Lessons01:24:12 Focus, GPUs, and Building a New Cloud01:28:20 Closing ThoughtsTranscriptAlessio [00:00:00]: Hey, everyone. Welcome to the Latent Space Podcast. This is Alessio, founder of Kernel Labs, and I'm joined by Swyx, editor of Latent Space.Swyx [00:00:10]: Hey, hey, hey. Today we're in the studio with Jake Cooper of Railway.Alessio [00:00:14]: Conductor of Railway.Swyx [00:00:15]: Conductor at Railway. Yeah.Alessio [00:00:16]: Choo-choo.Swyx [00:00:17]: Do you actually have that anywhere, like on your business card?Jake [00:00:20]: We call some of our volunteer moderators conductors. I don't have a business card. We're not that big yet. At some point I will. I got handed a nice business card from the Supermicro folks, and I was like, “Damn, this is pretty official.”Swyx [00:00:30]: Business cards are coming back.Jake [00:00:32]: They're cool. They're hip. The conductor thing is good. We're trying to figure out what we want to call each other internally. Some people think it's super cringe and say, “You don't need a name for people internally.” Some people want to call each other something. We still don't have a really good one.Jake [00:00:55]: We've got New Railcrews, Trainiacs. Nothing has stuck yet.Swyx [00:01:00]: I like Trainiac. Trainiac sounds good. Railwayians. For those who don't know, what is Railway? Let's give people a crisp definition up front.Jake [00:01:09]: Railway is the easiest way to ship anything. You go to the canvas, or you talk with Claude, and you say, “Deploy a Postgres instance, deploy my GitHub repository, run this code,” and you're off to the races.Swyx [00:01:22]: You've got a nice animation on the landing page.Jake [00:01:24]: Thank you. None of my work, by the way. They don't let me touch the design stuff anymore.Jake [00:01:25]: We want to make it trivially easy not just to deploy things, but to evolve applications over time. Most tooling right now stacks entropy on top of entropy: Docker, Kubernetes, Ansible scripts, and all these other things. If we can version all of your software and keep track of all the changes, then we can make it trivial to clone environments, fork into a parallel universe, get copies of production data, get copies of any services, make changes, validate them, and collapse them back in without reproducing everything across a staging environment.The Railway Origin Story: From Uber Systems to a New CloudSwyx [00:02:07]: I was looking at your background: Bloomberg, Uber. Nothing immediately stands out as, “This guy is going to found the next great platform as a service.” What prepared you for Railway?Jake [00:02:21]: It was curiosity to keep going deeper. I started out on front-end stuff, working on Wolfram Mathematica and porting it over. Then I briefly moved to Bloomberg, then toward Uber and distributed systems, taking the Jump Bikes systems and moving them to a distributed system built on top of Cadence, the pre-Temporal Temporal.Swyx [00:02:44]: Which, by the way, I'm happy to talk about, pros and cons.Jake [00:02:48]: Totally.Swyx [00:02:51]: But let's do the Railway story.Jake [00:02:52]: It has been a continual step of wanting an experience. Whether it's walking up to a bike, unlocking it, and having it work frictionlessly, or something else, the depth required to make that happen follows from the experience. A lot of the work I do, and a lot of the team does, is in service of that experience. We fundamentally don't care how deep we have to go. We will swim to the bottom of the swimming pool to get the experience.Jake [00:03:17]: I don't have a physics PhD. I did an EECS degree. It has always been about figuring out the next step: how do we get there? That's what led to starting Railway for that experience and then moving all the way to bare metal data centers. I was adding patches to the kernel this week to get the experience there because I can see how much better it can be.Swyx [00:03:49]: Other patches to the Linux kernel this week?Jake [00:03:51]: Yeah. Not upstream. Our fork.Swyx [00:03:52]: That's a flex. Railpack? No, this is different. This is the OS on top of Railpack?Jake [00:03:57]: No, this is an actual kernel patch. It's always literally: what do we have to do to get that experience? Then figure it out. Anything is figureoutable.Swyx [00:04:10]: Would you send the patch upstream, or does it not fit other use cases?Jake [00:04:13]: Maybe. We have to work out the experience internally. It has to do with the storage layer we're building for some of the agentic stuff. Maybe it'll be useful upstream, but it's deeply useful for us internally.Open Source, Forks, and Non-Deterministic VersioningSwyx [00:04:29]: You mentioned open source before. How do you think about starting from open source, and then coding agents letting you do a lot more from forks of it?Jake [00:04:38]: GitHub's original sin is that it's almost a series of broken pointers. You have this thing, then you clone it, and now you've lost the whole upstream. How do we make it trivial for people to modify really small pieces of it?Jake [00:04:51]: We think of Git in a discrete sense: I've either made a change and merged upstream, or I haven't. What would it look like if it were percentage-based, a little more non-deterministic, or a stream of changes that users traverse as a percentage rolled out in general and then rolled all the way up?Jake [00:05:13]: We have the open-source kickback program and let you deploy templates because we want to make it trivial for people to version these shards over time. It solves a large problem around authentication, authorization, and security. NPM has a way to define, “Don't take any new packages.” The ideal end state is that you roll out progressively to users with the minimum impact zone and continue rolling up. JPMorgan should probably be the last one on the patch line, for all our sakes, because our money and livelihoods are there.Jake [00:05:53]: It's okay if Johnny Vibe Coder gets a broken patch because there's so much entropy in the system that the rubber has to meet the road at some point. You have to test at varying levels.The Long Grind: First Users, Free Tier, and Making the Business WorkSwyx [00:06:13]: I wanted to pull up this glorious chart, which is your usage or number of daily signups?Jake [00:06:22]: Daily signups, I think.Swyx [00:06:24]: You started six years ago. It was a slow grind, and now you're on a rocket ship. You say, “Don't doubt your fight and don't quit.” Maybe pick out certain points that were key inflections for the company.Jake [00:06:40]: At the start, it's about getting your first 100 users, hell or high water. We had a website and a support link. The support link was the Discord channel. I had notifications on with two monitors: the monitor I was working on and the other monitor with Discord. If anybody came in, I was immediately like, “Hey, how's it going?” It was rare, so getting those first 100 users to come back was the start.Jake [00:07:14]: Then you build a consultancy factory because users want all these things. You have to go back to the board and ask, “What is the actual product offering I want to build on top of this?”Jake [00:07:28]: VCs want charts that always go up and to the right, but in reality you don't necessarily want charts that look like that. For us, there have been periods of expansion where we add features to test use cases, and periods of compaction where we ask, “If the experience we have is good, how do we make it significantly better?” Maybe we strip out features that don't fit our ICP anymore.Jake [00:07:57]: The boom from 2022 to 2023 came from the free tier. Everybody under the sun was using it.Swyx [00:08:09]: A lot of Reddit bots and Discord bots.Jake [00:08:12]: And crypto miners. When you build an open product on the internet where anybody can sign up, the internet is a horrible place with so many things. You go through periods of asking, “How do I reach as many people as possible?” Then, “How do I fit the exact use case for the people who really matter and are really excited about this specific thing?”Jake [00:08:39]: Then there was a two-year period of making the actual business work. During the free-tier era, we were losing about half a million dollars a month.Swyx [00:08:59]: On a $20 million bank account.Jake [00:09:02]: On a $20 million bank account with maybe $50,000 a month in revenue. That's a horrible business. I don't know how anybody invested. But you have to go through it and say, “We have an experience people love, but the business has to work.”Jake [00:09:17]: There are two schools of thought. You can run the horrible business all the way up with bad margins, or you can go back and make it work. We've always wanted a super lean team. We're 35 people right now. It's very small.Swyx [00:09:36]: Supporting three million already?Jake [00:09:38]: Yeah. We're adding 100,000 users a week right now, so it's growing fast. We don't want to add headcount for the sake of headcount or throw bodies at problems. We want to build systems. It's hard to build systems during expansion because you're adding things to the system because people are asking for them or things are breaking.Jake [00:10:00]: We had to cut off the free users for a little while, rebuild the business, and make sure it worked. We want to reach as many people as possible because software is important. It's become difficult to create things in the physical world, so it's important to make it easy for people to build in the virtual world and have access to creation. But there are legs to that journey.Jake [00:10:30]: You can see divots in the charts. If you follow between 2025 and 2026, it's either summer or winter. People go on holiday with family.Swyx [00:10:50]: It affects that much?Jake [00:10:51]: Yeah. It's kind of B2C and kind of B2B. People are shipping constantly, then they stop. Our activation curve now shows more people activating on weekdays because we have more business users, so it smooths out over time.Agents as the New Interface to DeploymentSwyx [00:11:17]: Was there a point where you started prioritizing AI development or agent development?Jake [00:11:24]: We've prioritized agentic as a top-of-funnel thing. Over the last six months, we've deeply prioritized agentic as a mechanism to build and deploy things because we believe the curve is so steep and that is how people will build and deploy software.Jake [00:11:42]: It almost fundamentally doesn't matter whether this is dot-com or not because we're all on the internet anyway. If agents are going to deploy a bunch of things and we hit an inference wall at some point, we'll fix those problems. The dominant species over the next 10 years is that we've moved from assembly to C to C++ to JavaScript to words. You're going to need to close that loop.Swyx [00:12:13]: When you say this is dot-com, did you mean buying the domain, or the general case?Jake [00:12:17]: I mean the dot-com era, when companies had a huge run-up because people understood the internet was important. Then they hit bottlenecks, fundamental laws of physics, math didn't work, and everybody came back down to earth. But it didn't matter because the internet became so impactful. If you operate on a long enough time horizon, you should build these things anyway because you can see where it's going.Jake [00:12:45]: That's where I think a lot of agent stuff is. You get to a point where you're running thousands of agents in parallel. What is the inference cost? What is the compute cost? How do you make that efficient? How do you coordinate all this? We have issues coordinating humans; we don't even have good tooling for that. Now we have to figure out how to get agents to coordinate, safely version changes, and know when to raise their hand for someone to intervene. Otherwise it becomes an interrupt factory.Railway's Infrastructure Thesis: Network, Compute, Storage, and MetalSwyx [00:13:19]: Let's go right into the technical side. What are the core infrastructure or architectural beliefs of Railway that allow you to do what you do?Jake [00:13:29]: The primitives matter a lot for us. We need network, compute, storage, and orchestration around it. You need control over a lot of those things. We've talked a lot about how we don't really use Kubernetes because we want higher-order control to place workloads in very specific places.Jake [00:13:48]: The reason is that you have to be very efficient with agents: memory reuse and all these other things, or you're going to massively blow up your cost structure. Being able to rack and stack your own servers and build your own metal unlocks performance and cost. Experiences where you're running 1,000 agents in parallel are not massively cost prohibitive.Jake [00:14:13]: Token use and compute use are blowing up. Over time, those things have to get a lot more efficient. You can get a lot of margin to make those experiences solid by building your own metal. That's all in service of offering a differentiated experience to as many people as humanly possible.Swyx [00:14:51]: You have a data center in Singapore.Jake [00:14:53]: Yeah. We have two in every other region now. In Singapore, we're adding a second one in Q3.Swyx [00:14:58]: What's it like? I've never built a data center. Do you go to Equinix and say, “I want some slots?”Jake [00:15:05]: Yeah. Equinix. You basically go and say, “I want power and I want a cage.” They say, “Great, here's what it's going to be.” You rent the cage for a period of time, fill it with racks and servers, and hook up internet to it. That's all the pieces.Swyx [00:15:36]: Then you handle everything else.Jake [00:15:37]: You handle everything else.Swyx [00:15:39]: What's the math versus clouds doing it for you?Jake [00:15:43]: If we rented in the cloud, our payback period when we go to metal is about three months.Swyx [00:15:50]: Which is crazy.Jake [00:15:51]: It's nuts. That's four years of depreciated hardware. You're going to see a lot of this compute crunch because hyperscalers are buying up a lot of stuff. We're working directly with OEMs, resellers, and people building these machines: Supermicro, Dell, and others.Jake [00:16:11]: Upstream, there's a bunch of supply pressure. When we raised our last round, between deploying capital for servers and now, the amount of money we've raised is less than the amount of money we have in the bank plus the value of the servers because the servers have appreciated as RAM has gone up. It's nuts how valuable hardware has become.Jake [00:16:50]: If you look at hyperscalers, they deployed around $80 billion of capital expenditures this year, and next year will be more. That's a massive infrastructure build-out. You look at that and think it's crazy that they're spending way more than the Manhattan Project. But if every person is going to run dozens or hundreds of agents in parallel, you have no conceptual idea how much compute is required to make that experience happen, even if you're deeply efficient and sharing resources. And that doesn't even count inference.Swyx [00:17:22]: How do you plan the build-out? The growth chart is so vertical. Are you usually at 100% utilization as soon as racks are live? How far ahead are you planning?Jake [00:17:33]: We still maintain cloud presence for bursting. We work with AWS, GCP, and a few other clouds. We can rent, and then the moment we get space or power, we compact those workloads off the cloud. We started on the clouds, then built a system to migrate to our own metal. There's nothing that says you can't continually do that again, and that's exactly what we do. We never want to be compute constrained.Jake [00:18:09]: At the start of the year, we actually became compute constrained because one upstream provider wasn't able to give us quota at the rate we needed, and the hardware was slower. I spent a weekend rebuilding our entire network overlay so we could straddle five clouds: Oracle, AWS, ourselves, GCP, and one other one. We can do more than that now.Jake [00:18:38]: We got into a spot where we were trying to pack instances tight because we couldn't get enough compute. That led to a few reliability issues, which are now past us. I made a tweet pointing out that it's becoming harder and harder to acquire compute at the rate these models need to acquire compute. We got bit by it.Swyx [00:19:15]: How do you think about pricing knowing you might not have your own metal available at all times? Are you pricing assuming you need extra margin if you end up going into the cloud?Jake [00:19:26]: Because we've built out our metal data centers, our margins on metal are around 70%. We can deeply subsidize the cloud business if we want to scale at a reasonable rate. We have a few levers: metal, which makes the margins; cloud burst; debt to buy servers; and venture capital. It's an interesting operational problem: how much cash do we have, how much should we raise, how quickly can we deploy it, and can we scale revenue as quickly as we scale compute?Jake [00:20:05]: If we continue making it trivially easy for people to build and deploy, then the faster we close that loop and the more operationally excellent we are with capital, the faster the business can scale. It's almost a straight linear deployment rate.Financing Infrastructure: Hardware Debt, VC, and Operational LeverageSwyx [00:20:20]: I think infra startups raising debt is a tool people don't utilize enough or know enough about. What can you tell us about that? Is it secured against your CPUs?Jake [00:20:32]: It's secured against our hardware.Swyx [00:20:37]: What rates do you get? Who are the lenders?Jake [00:20:39]: We pay prime plus a spread, and we can refinance any of the debt as rates go down. The terms are pretty good. The unfortunate thing is that Twitter has no nuance, so people say, “Venture debt bad.” But as with all things, there are specific tools and areas where you can be deliberate instead of using one tool as a hammer. Venture capital is not the hammer for everything. You have to explore and figure out what works.Swyx [00:21:12]: VC is usually the most expensive financing you can get.Jake [00:21:15]: Yeah. I also think people think about VC incorrectly from a capital-raising perspective. Most people think, “How do I raise as much money as possible from whoever is probably the best I can get at that time?” That's close to right, but what we've tried to do is figure out what unfair advantage we can buy with that equity.Jake [00:21:34]: It's the most expensive equity you're going to give away at that point in time, assuming the company keeps getting better. How do you use it to work with someone stellar who complements you? In the seed stage, I had never started a company. Ray Tonsing had good advice, and I could text him all the time. He was really fast. Awesome.Jake [00:22:01]: Then with John and Erica at Unusual, they said, “You roughly know what you're doing building a product. We'll mostly leave you alone and be available for advice.” Amazing. Then we got to Series A and the business was an operational tire fire because we didn't know how to scale a business. Work with Erica, and Jordan is over at Redpoint, so bonus.Jake [00:22:28]: Now we've raised from TQ and FPV as we're moving into enterprises. Every step of the way, we've asked: who can we partner with at this specific time to unlock the next section of the journey? I don't know enterprise sales. As an engineer, I can eyeball what features we might need, and we have wonderful people internally who can help. But you want boardroom dynamics where everyone is aligned and asking, “How do we win this?” instead of bickering about strategy.Data Centers in Space and the Physics of ComputeSwyx [00:23:31]: You had a tweet about data centers in space. Why no data centers in space?Jake [00:23:37]: It's not “no data centers in space.” My hot take is that I think it is solvable. I've just never seen anybody solve it.Swyx [00:23:49]: You said, “How are you going to dissipate that much heat in a vacuum?” You're making a physics claim.Jake [00:23:55]: I haven't seen anybody prove how you're going to dissipate that much heat in a vacuum. It doesn't mean it's not possible. It just means nobody has brought it up yet.Swyx [00:24:05]: Astrophage.Jake [00:24:06]: I don't know what that is.Swyx [00:24:07]: The Martian thing. Okay, you're very logical.Jake [00:24:09]: It could work. A lot of people are putting the cart before the horse. They say, “We're going to put data centers in space.” Okay, but how? “We have time to figure it out.” It's like in The Martian where they ask how they're going to intercept something and say, “We'll figure it out.”Swyx [00:24:36]: Making a bet on human invention is weird because you blind trust that it can be solved. But with physics, there are first-principles bounds you can put on it. Maybe not. Maybe you're asking to travel time or break a fundamental thermodynamic law.Jake [00:24:57]: I don't know how VCs do this either. How do you know what's not possible and a grift versus what's possible but sounds completely insane? “We're going to put data centers in space.” Coin flip as to which it is, and I guess you'll know in 10 years. That's one cycle.What Agents Need: Versioning, Observability, and 1,000x ScaleSwyx [00:25:23]: Moving back to agents. The branching, fast spin-up, and orchestration you do feels like pre-work that happened to be exactly what agents want. What do agents want differently than humans?Jake [00:25:37]: They want the ability to version things. It's not that different; it materializes slightly differently. Agents want a way to test changes incrementally. Engineers have feature flags. Is there a reason agents can't use feature flags? I don't think so.Jake [00:25:54]: They want version control. Can we use Git or not Git? That one is up in the air. I think something outside Git will emerge for how we version these things over time. They need observability. You need to query what happened, when it happened, which steps failed, traces, logs, metrics, and all the rest. They need network, compute, and storage. They need to write files, save files, iterate on files, and snapshot file systems.Jake [00:26:25]: A lot of what humans needed is in line with what agents need. Branching and forking are not different; we're just moving 1,000 times quicker. It can look like you need something massively different, but what you need is something massively better than what existed. You need orchestration massively better than Kubernetes. You need networking probably better than Envoy. It goes all the way down the stack.Jake [00:26:55]: If the workload profile doesn't change so much as it gets massively compressed because you need thousands of these things, what assumptions change? etcd is going to melt. You need to replace it with something. You can go all the way down the stack and say, “That part has to change, that part has to change, and that part has to change.”Jake [00:27:19]: The interesting thing about the super-exponential curve is that you have to build systems where you can rip out those parts at any time because a new bottleneck might emerge. You get good at parallel agents, and a different part of the system breaks. So it's similar to what humans needed, but at 1,000x scale.Jake [00:27:55]: How do you do code review in the age of agents?Swyx [00:28:00]: You throw more agents at it.Jake [00:28:01]: You don't. But then who reviews for CVEs and all these other things?Swyx [00:28:07]: More agents.Jake [00:28:08]: And that's how we hit the inference wall. You can continually throw agents at the problem, but I think there's a limit to the number of agents you can throw at a problem.CLI, Agent Handles, and Closing the LoopSwyx [00:28:24]: You already had a CLI before it was cool. How is the shape of what you're exposing changing, if at all?Jake [00:28:28]: CLIs have always been cool. The CLI changes because we think about how to give Claude, Codex, ChatGPT, or any model a handhold.Jake [00:28:50]: A CLI is a single command: deploy, get logs, and so on. Things that were prohibitively annoying to humans are not annoying to agents. They're nice. If I handed you a CLI with 40 arguments and 600 flags, you'd think, “I'm never going to use all of this.” But if you hand it to an agent, it says, “This is excellent. I have so many handles to work with.”Jake [00:29:24]: If you're going to expose things to agents that way, you want as many handles as possible where they can get information, query dynamic information, and close the loop quickly. Most problems right now are about how to close the loop as quickly as possible. Where does the agent get stuck, and how can you remove that?Jake [00:29:49]: Telemetry is important. If you can tell where the agent gets stuck from the CLI and say, “12% of people deviate from the happy path because of this, and now I add this argument and drive it down to 2%,” you massively increase the rate of loop closure.Jake [00:30:03]: That's how we think about not just the CLI, but every point in the dashboard. It's a user journey: I hear about Railway. I get something deployed. I get my first green build or aha moment. I see an endpoint, logs, whatever. Then I iterate. The iteration loop is indefinite. The user wants to deploy a new thing, a Postgres instance, change code, and keep iterating.Jake [00:30:36]: If you focus on the iteration loops and what's blocking them from closing quickly, one thing we say internally is: you never want to be waiting on compute anymore. You always want to be waiting on intelligence. If you're waiting on compute, there's a bottleneck that needs to be destroyed because eventually that bottleneck becomes so large that another workflow emerges to change it.Jake [00:31:04]: We've built a product where you push code, build it, and so on. But I fundamentally believe the push-pull loop is going away. We'll get to a point where you make a small change in production, that change is versioned across your infrastructure, you're working alongside copy-on-write versions of your database and infrastructure, and then you merge it in and it's instantaneously live. That's the holy grail of loops. The push-pull-rebuild thing is a point of friction that we're removing entirely.Canvas as Output: Dashboards, Context Anchors, and HyperstructuresSwyx [00:31:43]: It's incredibly fast. If anyone hasn't tried it, that fast feedback is great. My hot take is that Railway was famous for its canvas, which visualizes your infrastructure and lets you manipulate it visually. But that was for humans. For the next phase of growth, Railway CLI is more important than canvas.Jake [00:32:05]: The canvas is funny because it's a mechanism to show changes over time. You're right that previously we used it a lot as an input. Moving forward, its goal is more like an output. You would go to the canvas, make changes, see them, and watch your infrastructure evolve. Now agents have access to the CLI and can make those changes. So the canvas becomes an output: what information does the human need at this moment to make suitable decisions about control requests? Do I approve this or not?Jake [00:32:57]: It also has to be an anchor for your context, a port in the storm. Think of it like layers in a file system. You start with a project, then drill down into services, then into a function or code, because you want to represent the entire thing not just in your head, but in the canvas. Other people can share that representation, think on the same wavelength, and move quickly.Jake [00:33:33]: A lot of organizations get in trouble as they scale because all the context lives in someone's head. “How does this microservice work?” “I have no idea; go ask this person.” Then you have whole categories of products built around context discovery. A lot of that melts away if you have a solid hierarchy and can infinitely nest services, code, context, and everything else all the way down. That's what lets you build these structures over time.Jake [00:34:18]: It's also what lets us build what I've called hyperstructures: things that are way bigger. You look at the Golden Gate Bridge and ask, “How did we build that?” There's a meme that we lost the technology. To some extent, yes, because the coordination that built those things evolved and changed. We lost some of the art of building structure as we jammed everything into Slack.Swyx [00:34:52]: But you jam everything in Discord.Jake [00:34:53]: Same point. It doesn't matter. It's message passing and interrupts, message passing and interrupts.Swyx [00:35:00]: So you're arguing there should be something better and more structured than Slack?Jake [00:35:04]: Yeah. For sure. I think Slack is awful, and Discord is awful too.Central Station: Context Routing, Support, and Incident ClustersSwyx [00:35:09]: This is the equivalent of my mom test. What have you done that has your solution to this?Jake [00:35:15]: Internally, we've built a tool called Central Station that aggregates all the context from our users. Every piece of feedback, every customer support item, everything gets aggregated into clusters. If an incident is brewing, we can determine how many users are affected and break off a discussion based on that.Jake [00:35:40]: That is more helpful than long-running channels where you're trying to decide which channel to put something in. If you can dynamically aggregate information and dynamically route it to the right person based on context, it works better. We know internally that these four people are close to networking. If we see a networking thing, we can drill it down to those four people. If it's with this part, we can look at the commits. This is no longer a manual process internally.Jake [00:36:13]: If you go to station or help.railway.com, that's why we built it. We wanted to scale with a massive amount of leverage by aggregating feedback.Swyx [00:36:27]: This is built in-house?Jake [00:36:28]: Yep.Swyx [00:36:29]: I remember helping out on this one with Angelo in 2023. You scale a lot with a very small team.Jake [00:36:38]: Yeah. We're about 10 times bigger now.Swyx [00:36:40]: You have your full developer code here? Very cool.Jake [00:36:44]: If you go to railway.com/stats, we expose this as a pub-sub-able thing. It's all real-time metrics. There's a way to get it as JSON somewhere if you care.Jake [00:37:01]: We're big on trying to build everything in public and talk about what we're working on. We've had issues in the past, and we'll say, “Here's how we're fixing these things.” We've gotten compliments and flak for incident reports. We're always trying to make them better and talk with people.Incidents, Disclosure, and Progressive RolloutsSwyx [00:37:20]: You had a big one recently. I liked that it was scoped to 3,000. You presumably used Central Station. Talk through what happened and how you address it internally as a team.Jake [00:37:38]: Internally, this one really sucked. It had to do with an upstream provider that didn't do the behavior it said it documented, which is unfortunate given they wrote the RFC for how the behavior should work. We rolled those things out, and Central Station caught it initially when a couple users said caches weren't invalidating. We turned it off immediately.Jake [00:38:03]: When you roll out to a large user base of three million people, you get a lot of disparate behaviors. We tested in staging and had tests, but we hit an edge case. We've hardened those systems, and now we can make that better. But it was a tough one.Swyx [00:38:39]: I always wonder how private disclosure is supposed to work if people find an issue. Are they supposed to contact you first? When you run a platform, these things will happen. What channels should people pursue to quietly resolve it before it becomes a bigger incident?Jake [00:38:59]: There's responsible disclosure. We err on the side of over-disclosing and letting you know something is wrong versus having your provider gaslight you. We've erred on sharing those things more publicly, even if they impact a small subset of users. That's a decision we've made internally. We have four values. One is honor. The honorable thing is to notify people to the widest degree at which they may have been affected or there was an issue, and then confront it head-on: why did it happen, what can we do better?Swyx [00:39:45]: Not the whole user base. That's because of incremental rollouts and other things?Jake [00:39:50]: Yeah. Progressive rollouts.Swyx [00:39:54]: That should be the norm at all large platforms.Jake [00:39:58]: It should. A variety of companies do this. There's the quote that Meta runs 10,000 different versions of Meta. To our earlier point about agents, they need the same thing. They need shadow traffic and all these other things. We've built so much ceremony around production being sacred that we need to make it trivially easy to test different behaviors in a safe environment. Then you can make mistakes in a safe environment.Safe AI SRE: Customer Agents, Forked Environments, and Production ParityAlessio [00:40:30]: Do you see a world where these things get automatically caught, not necessarily by your agent, but by your customer's agent? The cache invalidation issue seems easy to check if you know to look for it.Jake [00:40:44]: It's hard because to determine it, we almost need to hook into your observability infrastructure. That's why we have the template loop on the platform: so you can roll things out progressively. You can roll out to Johnny Vibe Coder initially, or push a shard that someone consumes at their own leisure. Or you can roll it out over weeks: 0.1% of people, 1% of people, early adopters, then all the way up. That's the non-deterministic version control we talked about earlier.Jake [00:41:30]: I believe that's where most things should go, because most companies end up building staged rollout systems in-house. It's the same thing built again and again at every company. There's a massive opportunity to consolidate developer debt.Alessio [00:41:45]: You should have a free tier. Model providers give free tokens if you let them use the data. You could give free compute if someone is the number-one shard that goes out and lets you plug into their observability.Jake [00:41:55]: We do that. That's why we talked about the impact on 3,000 people. We start with lower-impact people. Larger companies on the platform are last to receive those rollouts so they have a version of the platform that's deeply stable.Alessio [00:42:16]: I have three services, so I'm sure I get the first rollout. You can nuke my thing at any time. There are all these SRE agent companies. Observability people also want agents that fix upstream problems. You have your own agent in the canvas now. How do you see that playing out?Jake [00:42:39]: It's the stacking entropy problem. If you don't have primitives to make iteration in production safe, it becomes difficult. If you're an observability provider saying, “Here's the fix to this error,” assume 80% are good and make sense. But in the last 20% long tail of complex issues, if you let somebody stamp it, you create an opportunity for an incident.Jake [00:43:08]: That's why forked environments are important. People have staging, but it always drifts from production. You need primitives, workflows, and experience built first-party on the platform so you can fork any service at any point in time.Jake [00:43:33]: I think of the canvas as a sheet of transparency paper. The agent is a little guy you push up into the canvas. It should say, “I need to copy that service and that service so I can test these two things.” It gets a read-only copy of production. Anything that's PII gets marked as a transform when we clone the database, create a copy-on-write version, or read from it. Then the agent makes changes and asks, “Does this actually work?” as close to production as possible.Jake [00:44:22]: That's how close you have to be, or you get massive drift. The system becomes unstable. You see this with massive systems built on Docker for local, Kubernetes for production, and a specific thing for something else. That complexity slows developers and becomes unstable at scale, making it hard to iterate. We want to compress that way down and say, “As close to prod as possible is where we want to be.”From AISRE Skeptic to Agent BelieverSwyx [00:45:00]: I was texting Erica for questions, and she says you were originally not a believer in AISRE. Have you come around on it?Jake [00:45:10]: I flipped, but I'm still not a believer in AISRE if you don't have the primitives to make it safe. If you unleash AISRE on production infrastructure without safe primitives for copying volumes and making sure things are fine, it's going to nuke your production database. It's not a matter of if, but when. I'm a big believer in making those loops safe.Jake [00:45:33]: I was a deep AI skeptic until 2023. In 2024, I thought, “Maybe I can roughly make this thing do it.” In 2025, I thought, “Now I can hold this.” Over winter break, everybody came back saying, “It's almost impossible to hold this.”Swyx [00:46:01]: Did you see this on the Claude docs? CloudBot? OpenCloud?Jake [00:46:06]: It's gotten to a point where it's harder to hold it wrong than to hold it right. There's a scene in Avengers where Vision picks up Thor's hammer and says it's terribly well-balanced. It self-balances and works well. I'm a deep believer at this point that this will be the dominant species: assembly, C, C++, JavaScript, words.Swyx [00:46:35]: It feels like a big jump.Jake [00:46:37]: It is. But it's not like you abandon CPU-based discrete logic and move straight to fuzzy logic. You need both. Your skills should call code or applications or some static structure. You can use skills to distill what the procedure should be or how the code should act.Jake [00:47:02]: I'm coming to a thesis: you need three points. You need a clear spec defining the system, the code, and the tests. When you say it out loud, if you've been in engineering long enough, you're like, “Of course. That's an RFC, tests, and code.” But they all matter. Having them together lets them reinforce each other: the spec and tests match, but the code doesn't, so reconcile it. Or the tests and code match but the spec doesn't, so reconcile that. That's the iteration loop.Jake [00:47:41]: That's why you're seeing people talk about software factories, docs, and reconciliation. Some of that is architectural astronomy if you don't implement it, but that loop is where most things will end up.Swyx [00:48:07]: For listeners, we've been talking about this on the pod for three years: the holy trinity of specs and tests. Itamar Friedman from Qodo is the reference if people want to look it up.Self-Modifying Infrastructure and the End of Push-Pull-RebuildSwyx [00:48:18]: One thing I want to mention on the OpenCloud idea is self-modification. I don't know how Railway would support it, but I have my OpenClaw, and I just tell it it has the Railway CLI and can do whatever. In theory, whatever capabilities or new infra it needs, it can call the Railway CLI, provision it, and add it to itself. The agent can modify its own infra.Jake [00:48:45]: It's nuts. I have a loop set up where you put the Railway CLI on top of something that runs on Railway. You're authenticated as whatever the current box is, and you can make any changes to it. Then you call Railway deploy, and it deploys itself.Jake [00:49:04]: It's like: “I need to spin up this instance of this environment. I already exist in this environment. Excellent, I have access to a Postgres instance now.” That's where we want to go with agentic, self-replicating infrastructure. That's your loop: iterate in production. You continue making changes. If it works, merge it upstream. If it doesn't, throw it away.Jake [00:49:37]: How do you make throwaway copies trivial to spin up and super cheap? The era of “I have an AWS instance with four vCPU and 16 gigs of RAM” is going to get destroyed. If you do that for agents, you need a thousand of those machines. It's prohibitively expensive compared with what we've spent a ton of time figuring out: the atomic unit of deploy, whether you call it isolates, sandboxes, or something else. Only pay for what you use, spin up instantaneously, and close the loop as quickly as possible.Jake [00:50:15]: If the system can self-replicate safely and say, “This is my environment, I'm making these changes,” it can come back with, “Does this look good? This is a new state of infrastructure given this prompt. I think I've solved it.” Then you go back and say, “Actually, it looks different.” It does the loop again. Then you say, “Cool. Apply.”Swyx [00:50:38]: That's retroactively obvious, which is the most useful kind. Any other comments on agent deployment on Railway?Jake [00:50:51]: It's getting better every day. I'm on X or Twitter. You can always yell at me about the parts not working as well as they should, because plenty of things should work way better.The New Serverless: Stateful, Long-Running, Pay-for-What-You-Use LinuxSwyx [00:51:04]: At this stage, when people want massively or embarrassingly parallel compute, they usually talk serverless. I feel like there's a new serverless compared to the previous five years of serverless. You're in that new bucket. Do you have comparisons or philosophical differences you want to call out?Jake [00:51:31]: It's somewhere in between. It's the ability to run stateful, long-running workflows or executions.Swyx [00:51:42]: Vercel has Fluid Compute, Cloudflare has some container thing, Google has App Runner and others.Jake [00:51:55]: That's where everything is roughly going, and it's why we've been working on this for six years. We believe users need access to a computer: a box that speaks Linux. They need to deploy what they want. Other systems change the surface area of what you can build. For us, users need a computer and need to deploy anything they truly want. That's why we've focused on the primitives: network, compute, storage. If we give you those and expose them so you can run things indefinitely, that's where we believe it's going.Jake [00:52:43]: Twitter has no nuance, so everyone says “servers” or “serverless.” It's always somewhere in the middle: I want to run it for a long time, but I don't want to provision the resource statically or pay for things I'm not using. That's been our thesis from day one: pay only for what you use, run it indefinitely, and it is full Linux.Swyx [00:53:12]: That's why I like the naming of Fluid. It's fluid. Flexible.Heroku, Focus, and Carrying the Torch Without Becoming the PastSwyx [00:53:18]: Another milestone is the Heroku official deprecation. You're one of the presumptive new Herokus. “New Heroku” has been a category for as long as I've been in developer tooling. It's finally happening. What was that like? Any behind-the-scenes of, “This is the moment”?Jake [00:53:42]: You have people where you're like, “You were running stuff on here? You, as this company?” It's crazy that names you would know are running on it and now coming to us saying, “We want to move a lot of this off.”Swyx [00:54:00]: Any behind-the-scenes on why Salesforce let Heroku stagnate?Jake [00:54:05]: I can only guess. It's hard when it's not your business. Salesforce's business is to build a great CRM. That's their focus. Then you acquire a compute business as an offshoot. A lot of early Meta people talk about focus. Boz has a write-up about how in the early days of Meta they had no money, so they were forced to focus. Then they turned on the money tree and had no reason not to split their focus.Jake [00:54:52]: But that dilutes your product. You get offshoots where you ask, “Is this the focus of the business?” If it's not core, it languishes. A lot of companies get in trouble when they split focus because they're fighting a multi-front war, not just externally but internally for alignment. Where are we going? What are we doing? What is our purpose?Jake [00:55:24]: If you're Salesforce-built and mission-driven, you want to work on Salesforce. Heroku is off to the side. It's not core to the business. Getting resources, budget, focus, and alignment internally becomes hard. It was a matter of time.Swyx [00:56:06]: Kudos for them to call it out instead of leaving it unknown.Jake [00:56:12]: Their release was a little odd. They called it out, but they didn't say they were shutting it down. Behind the scenes, I think they issued messages to people saying they should close accounts and that they were going to deprecate and remove things over time.Jake [00:56:30]: It's crazy because some of my first deployment experiences were on Heroku. You start with dragging things into an FTP server, then you try to get a deploy working, and then it's Heroku. It was the on-ramp for us. But the wheel turns. New things emerge. We're happy to carry the torch for a lot of that. But we don't want to be the new Heroku. We want to be the way people build and deploy software, and ultimately the way people monetize software over time.Swyx [00:57:19]: It's still a big crown to be the new Heroku. There are 50 companies that fought for that.Jake [00:57:23]: Everybody is holding some portion of it. We're happy to support people and companies. The platform works differently. The game loop is similar, but we've been dogmatic about where these things are going: primitives, agents, fan-out. Some things fit; some workflows need to change. We have an approximation of Heroku pipelines with the environment system. It's exciting. We've got a ton of people we can support, and it's growing a lot.Temporal, Workflow Engines, and State MachinesSwyx [00:58:12]: I have one more technical question about Temporal. I've sold my shares. You're a power user and one of our earliest customers. I met you through Temporal. You built on Temporal. You have complaints. This may be the most neutral and informed conversation anyone will hear about Temporal without someone working at the company.Jake [00:58:39]: That's fair. I've used Temporal for almost 10 years because of Cadence at Uber.Swyx [00:58:52]: Give people a sense of what Cadence was at Uber.Jake [00:58:57]: Cadence was the precursor to Temporal. It powers trip actions, rides, when you rent a Jump bike or scooter or car. You're running workflows for a period of time and saying, “This ride will run indefinitely until it finishes.” You attach information: you paused in this zone, so add this charge to the bill. When you end the trip, the workflow is done. That experience was powered by Cadence at the time.Swyx [00:59:34]: I used to say it's like programming the entire user journey top-down as one function.Jake [00:59:39]: It's a powerful idea and important. It's also important for the next phase of the agentic journey. You want an agent to do a specific task, be complete or incomplete on that task, and move on to the next thing. You need a way to manage workflows dynamically.Jake [00:59:59]: Temporal was always great in theory, and great when you got it working the way you wanted in production. But it required you to model the entire journey in your head. If you didn't, you could cause issues where replaying the state of the workflow causes non-determinism.Swyx [01:00:25]: Because it works on deterministic workflow history.Jake [01:00:28]: Exactly. I describe it as a jet engine. If you know how to operate it and run it, it's great. But you can't hand it to people trying to build complicated things if they don't have the whole state in their head.Jake [01:00:48]: We run our whole deployment pipeline on top of it. That's a reasonably complicated workflow: pre-commit hooks, signaling, queuing, and all the rest. We ran into the same thing at Uber. As you express a large workflow, it gets more complicated, with more states in the state machine that you have to map back to the workflow.Swyx [01:01:15]: It's a lot of ifs.Jake [01:01:16]: Exactly. At Uber, we built a system for doing the state machine and testing it. We've started to build some of those things here because it's grown heavily. It's not quite love-hate. When it works well, it works super well. But if someone who doesn't have full context puts something into the system that invalidates state or causes non-determinism, or spins off a ton of activities, you have to keep track of underlying SRE knobs like activity slots. Those should scale with memory, vCPU, and so on. It becomes a bear to scale.Swyx [01:02:10]: You need a capable sysadmin running things behind the scenes. If you moved off, what would you do?Jake [01:02:19]: We'd build our own workflow engine. We have a few internally that we've worked on.Swyx [01:02:27]: This is one of those classes of things you typically wouldn't vibe code, but I'm wondering if you can.Jake [01:02:33]: I still don't think you should vibe code it. You still want to run decent tests to make sure it works.Swyx [01:02:39]: Timo didn't invent that from scratch either. There are libraries you can run. On top of that, it's just a state machine that you have to map out. Ultimately, you define the instructions you want and run them through a state machine.Jake [01:03:00]: It's very doable. Workflow stuff is interesting. Restate is doing neat stuff here.Swyx [01:03:10]: You're tied into JavaScript. Are you a JavaScript maxi?Jake [01:03:13]: Internally, we have TypeScript, Rust, and Go. We don't add more languages. Actually, we have a little C because we write BPF code and hooks. But those are the languages.Swyx [01:03:28]: Is this for sidecars?Jake [01:03:32]: No. It's for the networking stack, volumes, and things like that. We use TypeScript a lot because it powers the dashboard, but we're moving a lot of workflow stuff off the dashboard stack and into the infrastructure stack.Railpack, Nixpacks, and Content-Addressable FilesystemsSwyx [01:04:00]: Cool. Any other technical infrastructure stuff? Railpacks?Jake [01:04:07]: We built an engine for determining dependencies based on source code. It's called Railpack. We built the first version, Nixpacks, on top of Nix, and then we moved.Swyx [01:04:17]: People have been trying to get me to adopt Nix and NixOS for four years. Is it ever going to be a thing?Jake [01:04:23]: I don't know. We're excited about it, but it has pain points. Think of it as a stack of versioned binaries at specific slices in time. If you want version X and version Y, you bloat the package space, which blows up image size and makes real-world workloads difficult.Swyx [01:04:53]: But you content-address it and cache it. In theory, there are optimizations.Jake [01:05:00]: In theory, yes. But with a large enough user base and disparate enough machines, you run into a problem Meta described in the XFAAS paper, their internal serverless system. It becomes difficult at scale unless you break out specific runtimes.Jake [01:05:24]: We didn't want to do that because we wanted to truly allow you to deploy anything. That was our initial thing with Nix. But we've moved toward interesting work around content-addressable file systems that can lazy-load anything from any point and page it into memory.Swyx [01:05:48]: Amazing.Jake [01:05:49]: The future is very bright. It's crazy, and it's going to be nuts.Coding Agent Spend, Roadmaps, and Token ROISwyx [01:05:54]: Founder journey stuff?Alessio [01:05:56]: Your cloud usage: you tweeted you're going to spend $300K this month?Jake [01:06:01]: I think we got to $200K.Alessio [01:06:02]: Coding agents?Jake [01:06:03]: Yeah.Swyx [01:06:04]: Across the company?Alessio [01:06:05]: You only have 35 people, so I'm sure they're not all spending $10K a month. What's the distribution?Jake [01:06:10]: I think I'm at about $25K. We have power users all the way down. We came back from winter break, and I basically said, “If you're writing code by hand, you're doing this wrong.” The tools are good enough now that you can move extremely quickly. There are issues and pain points, but you should be reviewing the code you are writing instead of writing it by hand.Jake [01:06:40]: Architectural patterns matter more now than ever, but you shouldn't spend your time generating code you would write. If you know how to write it, ask the agent to write it and reconcile it until it looks like you would have written it yourself.Jake [01:06:58]: People misconstrue my propensity to push people toward agents as connected to our growth and some reliability bumps. They're not necessarily related. The tools are good enough to move extremely quickly and build things way larger than you could before.Jake [01:07:19]: To the earlier point about cooling data centers in space: I don't know. But with software, you can ask, “How would I build block storage from scratch? How would I do these things?” I have ideas because I have history and have read papers. Let me work them out and build massive test benches with thousands of tests, because those are now free to author. If you're not using AI systems to speed-run your roadmap and reconcile your existing system onto the future, you're missing a large point of what's happening.Alessio [01:08:12]: What's the path to spending $3 million a month? Is it bound by ideas and things customers can absorb?Jake [01:08:19]: For most companies, it's bound by deployment at this point. That's why we've seen a massive boom in users and companies, from Fortune 50s down, asking how to get developers to move faster. You'll probably hit your CFO before any technical limits because they'll look at the eye-watering amount of money spent on tokens. Inference costs have to come down, but we're inference constrained now. There will be price discovery around what makes sense for an org to adopt.Jake [01:09:06]: I think you'll end up with the F1 driver concept. If someone is really adept at these things, it makes sense to put them in a $3 million car. If they're not, it probably doesn't make sense. You'll take a few people and say, “You can drive the F1 car. We need to go in this direction. Figure out if it works and prototype it.”Jake [01:09:33]: We've done some of that and vastly accelerated our roadmap. We thought we'd ship something in a few years; now we can probably ship it in a few months because we validated it and don't have to build it incrementally. We can skip steps and move toward our vision.Alessio [01:09:58]: A lot of people are realizing the roadmap doesn't always have a business impact, so they say tokens are too expensive. But if your roadmap were built to make more money by the time you built it, you'd have token pricing for it, the same way you do with sales. You'd spend a billion dollars on sales if you knew you would get $2 billion of revenue.Jake [01:10:19]: Exactly. A naive way to measure this is the percentage of tokens that end up in production. If you can measure impact because those tokens end up in production, that's awesome. But the burden of proof will rise. Internally, we have a growing number of pull requests that haven't merged. The question becomes: how do you get this into production? It's about how quickly you can build and deploy software, which is exciting because that's our whole thing.The SDLC Shift: Prompt Requests, Feature Flags, and Safe RolloutsSwyx [01:10:56]: The SDLC is changing. One thesis is that the pull request is dying. It's going to be the prompt request. Beyond that, code review is also kind of dying if you have all the other systems in place. What else is changing about the SDLC?Jake [01:11:19]: The AISRE and the tools to make it happen. AISRE is pie-in-the-sky aspirational. What does it take to get an AISRE? What tools do you need to build?Swyx [01:11:32]: You should expose your tooling to customers at some point. The Central Station command center.Jake [01:11:39]: We have it for template maintainers. Template maintainers can deploy and maintain templates, and they get feedback. We're going to expose those things incrementally.Swyx [01:11:51]: Clustering around incidents. Everyone has a version of that, but I don't think anyone has solved it.Jake [01:11:56]: I won't say we've solved it internally, but it's gotten so good that we can see incidents forming pretty quickly. At some point, those will be things either someone else builds or we build. We've always built things purpose-built for us. If it makes sense to make it useful for users, monetize it, or turn that loop into a profit center instead of a cost center, we want to do that.Jake [01:12:28]: Pull request is definitely dying.Swyx [01:12:29]: Do you do first-party feature flagging and incremental rollout stuff?Jake [01:12:34]: We have a feature-flagging engine we built internally and will eventually roll out.Swyx [01:12:38]: I don't see it as a user. How come you didn't give us what you have?Jake [01:12:43]: We have to beta test it. We care a lot about the quality of the things. There's plenty we've used internally that doesn't make it all the way through the journey because it fails. It works for one service but not multiple services. We'd have to build it for multiple services and know that if we released it, we'd rebuild it again and again. Some things are worth that, but many inform the roadmap.Jake [01:13:18]: We don't want to dilute the experience by saying, “This works, but only for this service,” unless it's a core initiative. Over the next few months, we'll roll out things that work for a single service, then multiple services, then multiple services across the environment. You have to be deliberate. Otherwise you create broken disparate experiences and support load because people ask how to use the feature.Jake [01:13:52]: It's the earlier expansion and compaction pattern. You expand the company to get features, then compact and smooth them out so the experience is stellar. You told me in the hallway, “It's gotten so much better.” Internally we're saying, “This part really sucks. We need to make it significantly better.”Swyx [01:14:11]: I can attest to that over the last three years watching you build Railway. For listeners, feature flagging is a huge part of Uber culture. So much so that they have too many feature flags and another thing to remove feature flags. Facebook has Gatekeeper. Agents are going to need this. It's fundamental to incremental rollouts. OpenAI acquired Statsig. GPT-5 is routing and flagging through different models.Jake [01:14:56]: It's super important. If the software development lifecycle is going to change because we're doing things 1,000 times faster and 1,000 times more concurrently, what becomes important at scale?Jake [01:15:16]: Before I started Railway, I built a feature-flagging product and tried to sell it. It was an easier version of LaunchDarkly. I ran into a problem: anyone small enough to adopt your technology doesn't care about feature flags, and anyone large enough to need feature flags needs so much scale that you have to build out all the infrastructure. I scrapped it.Jake [01:15:42]: But what is old is new again. Companies are trying to move quickly, but you can't YOLO a vibe-coded thing straight into production. You need to say, “Here's my blast radius, my impact, and I want to shadow it for these users.” Feature flags. You're going to need the tools larger companies built to maintain their structures. Everything gets compressed by 1,000x so everybody can build those structures quickly.Jake [01:16:07]: That's exactly where we are: compressing the software development lifecycle, then expanding it and adding more new things.Cattle, Pets, and Clonable InfrastructureSwyx [01:16:15]: Another term that comes to mind for newer developers is “cattle, not pets.” People treat production like a pet. It has a name. You baby it and keep it alive. With cattle, you can mass farm, roll out, portion parts out, and kill them.Jake [01:16:37]: I think that might change. You can move toward having pets as long as you have a cloning machine for your pets.Swyx [01:16:52]: Yeah.Jake [01:16:52]: If you can snapshot every single thing at every frame, it doesn't matter if something gets obliterated because you have a snapshot of it. The things we've built right now are designed to block changes from the hermetically sealed DevOps line. You have to write a Dockerfile because you nee