Podcasts about IDE

Pour l'épisode #311 je recevais Samy Lastmann. On en débrief avec Thomas.

If you've ever been to PyCon, you know one of the best parts of the expo hall is Startup Row, a stretch of booths where early-stage companies built on Python show off what they're creating. But only attendees get to walk that lane, so let's bring it to everyone. In this episode, we stroll down Startup Row together. We kick things off with the organizers, Jason and Shay, who share the program's origin story going back to Paul Graham and the PSF, plus some surprising stats, including two unicorns among the alumni. Then we meet five startups: Tetrix, bringing AI to institutional investing in private markets. Arcjet, security that lives inside your app as an SDK. Phemeral.dev, serverless hosting built for Python web apps. CapiscIO, an identity and authority layer for AI agents. And Pixeltable, a multimodal database from Marcel Kornacker, co-creator of Apache Parquet. See if you can spot the theme running through them all. Let's go for a walk. Episode sponsors AgentField AI Talk Python Courses Links from the show Guests Naunidh Bhalla: linkedin.com Grant Gittes: linkedin.com Marcel Kornacker: linkedin.com Beon de Nood: linkedin.com Chinmaya Joshi: linkedin.com David Mytton: linkedin.com Shea Tate-Di Donna: linkedin.com Jason Rowley: linkedin.com Azul Garza: github.com Renée Rosillo: linkedin.com Tetrix: tetrix.co Tetrix Jobs: tetrix.co Arcjet: arcjet.com Pixeltable: pixeltable.com Phemeral.dev: phemeral.dev CapiscIO: capisc.io Episode #551 deep-dive: talkpython.fm/551 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Ktoré zložky vám spôsobujú choroby a alergie? Nové informácie! ❤️Pozrite si aj hodnotné kurzy: https://skola.odznova.sk/ - ❤️Využite zľavy na nákupy: https://40plus.sk/vychytavkyPorovnanie produktov v priamom prenose. Čomu sa treba vyhnúť?Som rada, že podporujete svojimi darmi podcast ODznova. Vďaka vám vzniká tento obsah, milí členovia od úrovne PARTAK. *********************************************************Ďakujem, že ma podporujete svojimi darmi na HeroHero alebo tu na YouTube. Aj vďaka vám vzniká tento obsah. Chcete ma začať podporovať? Info tu: https://herohero.co/odznova Podpora je možná aj tu na YouTube.. zmysel to má od 5,99€ (50% z vášho predplatného mi zoberie YouTube ako províziu. Tak si to viete spočítať...Hero berie len 12,3%) INFO: Predplatné 2,99 na YT je bez nároku na obsah vopred. Ide len o sympatizovanie, za čo ďakujem... Ak nechcete platiť kartou, možné je podporovať aj cez číslo účtu o.z. : SK45 8330 0000 0022 0165 1060 - názov účtu: Institut Trvaleho Rozvoja 40+ do poznámky uveďte, že ide o DAR ĎAKUJEM a nezabudnite pozrieť info a linky o podujatiach ... ( INFO: Podujatia ❤ - https://www.40plus.sk/podujatia-odznova/ Buďte zdraví Martina Valachová• Web: http://www.40plus.sk • Facebook: http://fb.com/40plus.sk • Instagram: / odznovapodcast

"C'est important que je comprenne le code qui a été généré." Le D.E.V. de la semaine est Guillaume Lours, Software Engineer chez Docker. Avec lui, on plonge dans les coulisses de Docker Sandbox, cette solution pensée pour sécuriser l'automatisation et l'exécution de code par IA. Guillaume nous explique comment limiter les risques sans sacrifier l'efficacité, et détaille l'architecture technique : micro VM légère, man-in-the-middle pour la gestion des credentials, profils de sécurité personnalisables, le tout pour une expérience fluide. Il partage aussi des astuces d'usage au quotidien pour tester, reviewer ou itérer plus sereinement. Un éclairage concret sur le futur du développement outillé par l'IA.Chapitrages00:00:53 : Docker et Magie Noire00:01:32 : Présentation de Guillaume00:03:15 : Docker et les Générations00:04:50 : Résumé de Docker00:07:12 : Utilisation de Docker pour Tous00:08:51 : Écosystèmes et Docker00:12:43 : Complexité vs Simplicité00:17:20 : Introduction à Docker Compose00:20:23 : Fonctionnement de Docker Compose00:22:43 : Responsabilités de Compose et Engine00:28:19 : Ordonnancement et Réconciliation00:32:45 : Conteneurisation vs Virtualisation00:37:31 : Introduction à Docker Sandbox00:40:04 : Fonctionnement de Docker Sandbox00:45:58 : Usages de Docker Sandbox00:52:28 : Philosophie de Docker sur le Code00:58:44 : Recommandations et Conclusion Liens évoqués pendant l'émission YT Devoxx France Construire une application indépendante de la tech US en 2025 | Eventuallycoding2025, Europe Vs USA : la tech à l'heure des choix | EventuallycodingLe mythe de la neutralité : quand la tech devient politique

Tajný svet mocných. Čo sa deje za oponou a ako to súvisí s aférou Epsteina a teraz Zelenského? ❤️Pozrite si aj hodnotné kurzy: https://skola.odznova.sk/ - ❤️Využite zľavy na nákupy: https://40plus.sk/vychytavkyVítam v rozhovore Mira Šimoniča a som rada, že sa budeme rozprávať... Užite si rozhovor. Ďakujem za podporu členom kanála...*********************************************************Ďakujem, že ma podporujete svojimi darmi na HeroHero alebo tu na YouTube. Aj vďaka vám vzniká tento obsah. Chcete ma začať podporovať? Info tu: https://herohero.co/odznova Podpora je možná aj tu na YouTube.. zmysel to má od 5,99€ (50% z vášho predplatného mi zoberie YouTube ako províziu. Tak si to viete spočítať...Hero berie len 12,3%) INFO: Predplatné 2,99 na YT je bez nároku na obsah vopred. Ide len o sympatizovanie, za čo ďakujem... Ak nechcete platiť kartou, možné je podporovať aj cez číslo účtu o.z. : SK45 8330 0000 0022 0165 1060 - názov účtu: Institut Trvaleho Rozvoja 40+ do poznámky uveďte, že ide o DAR ĎAKUJEM a nezabudnite pozrieť info a linky o podujatiach ... ( INFO: Podujatia ❤ - https://www.40plus.sk/podujatia-odznova/ Buďte zdraví Martina Valachová• Web: http://www.40plus.sk • Facebook: http://fb.com/40plus.sk • Instagram: / odznovapodcast

Topics covered in this episode: Vulnerability and malware checks in uv HTTP GET requests with the Python standard library Millions of AI agents imperiled by critical vulnerability in open source package alembic-git-revisions Extras Joke Watch on YouTube About the show Goodbye and Thanks Brian Thanks Calvin for being part of this and future episodes! Also new time for the live show. Thanks Brian for all the hard work over the years. Calvin #1: Vulnerability and malware checks in uv release just yesterday by Astral https://astral.sh/blog/uv-audit uv audit scans dependencies for known vulnerabilities and abandoned packages via the OSV database — runs 4–10x faster than pip-audit Malware check runs on every install/sync, catching actively malicious packages (credential stealers, etc.) before they execute — including ones PyPI quarantined but lockfiles can still reference Enable malware scanning with UV_MALWARE_CHECK=1 — it's opt-in and in preview Future roadmap includes a resolver that steers toward vulnerability-free versions and install-time warnings scoped to newly added deps only Michael #2: HTTP GET requests with the Python standard library If you're doing HTTP in Python, you're probably using one of three popular libraries: requests, httpx, or urllib3. There have been issues with httpx lately. Niquest is another option: Drop-in replacement for Requests. Automatic HTTP/1.1, HTTP/2, and HTTP/3. WebSocket, and SSE included. But maybe less is more, especially in the age of agentic AI A good candidate needs two things to be true at once, not one: the used surface is small, and the behavior behind that surface is shallow. Calvin #3: Millions of AI agents imperiled by critical vulnerability in open source package "BadHost" (CVE-2026-48710) is a critical vulnerability in Starlette — the ASGI framework underlying FastAPI — with 325 million weekly downloads; also affects vLLM, LiteLLM, and most MCP server tooling The exploit is trivial: injecting a single character into an HTTP Host header bypasses path-based authentication, and can lead to credential theft, SSRF, and in some cases remote code execution MCP servers are a prime target since they store credentials for external services (email, databases, cloud accounts) — exposed data in the wild includes biopharma clinical trial DBs, full mailboxes, HR/PII pipelines, and AWS topology Fix is available — patch to Starlette 1.0.1 immediately; use the free scanner at mcp-scan.nemesis.services to check if your servers are still running a vulnerable version Open source sustainability footnote: the maintainer triages near-daily security reports solo, in his free time — most are AI-generated noise, and real ones like this still compete for the same evenings and weekends Michael #4: alembic-git-revisions By Julien Danjou from Mergify Automatic Alembic migration chaining based on git commit history. No more Multiple head revisions are present for given argument 'head'. See the introductory article Caused by two migrations landed with the same down_revision, and Alembic doesn't know which one comes first. The fix is always the same: someone manually edits the migration file to re-chain the revisions. The insight: git already knows the order Extras Calvin: GNU make can do pattern matching in the target. Not new at all, mentioned in the 1994-era docs. just and task don't have this super power on the target name yet. train-%: uv run ./train.py $* --save-hyper-params --overwrite $(TRAIN_ARGS) Michael: Updated my HTTP client using packages from httpx to httpx2: listmonk, umami, and memberful. For motivation, see this reddit thread. Joke: Accurate

In this episode: Martin transforms Neovim into an unyielding modeless VSCode-style IDE with CUA keybindings. Some of this was achieved with novim-mode and snacks.nvim. Mark has been playing Solasta: Crown of the Magister. Alan wants you all to install flatpak with a snap. Gather round children, it’s story time. You can send your feedback via show@linuxmatters.sh or the Contact Form. If you’d like to hang out with other listeners and share your feedback with the community, you can join us on: The Linux Matters Chatters on Telegram. The Linux Matters Subreddit. If you enjoy the show, please consider supporting us.

Fredrik snackar Kotlinconf 2026 och språket Kotlin i allmänhet med Johan Blomgren och Emil Kantis. Hur var konferensen? Hur fungerar utvecklingen av Kotlin, och vad är på gång i språket? Det blir tips på intressanta presentationer värda att se när de släpps på nätet, och en förklaring av varför Kotlinconfs officiella app inte känns helt hemma på Appletelefoner. Vi snuddar också - inte helt oväntat - vid språkmodeller. Vi pratar om AI, teknikutvecklingen, och presentationen av saker som oundvikliga kontra att bygga en bättre värld genom att helt enkelt prata mer med andra människor. Gärna öga mot öga också. Det är en mänsklig superkraft! Som avslutning bjuds på en snabb genomgång av anledningar att byta till Kotlin från Java. Ett stort tack till Cloudnet som sponsrar vår VPS! Har du kommentarer, frågor eller tips? Vi är @kodsnack, @thieta, @krig, och @bjoreman på Mastodon, har en sida på Facebook och epostas på info@kodsnack.se om du vill skriva längre. Vi läser allt som skickas. Gillar du Kodsnack får du hemskt gärna recensera oss i iTunes! Du kan också stödja podden genom att ge oss en kaffe (eller två!) på Ko-fi, eller handla något i vår butik. Länkar Johan Emil Java Kotlin Komma igång med Kotlin som Java-utvecklare Att övertyga andra om Kotlins storhet Helping decision makers say yes to Kotlin React Vue ATG Junit Kotest Kotlin-test Kotlinconf 2026 Keynoten för Kotlinconf 2026 Jetbrains utvecklar både IDE:er och Kotlin Javazone i Oslo Kotlin på Youtube - inklusive inspelninigar från Kotlinconf 2026 när de släpps KEEP - Kotlin evolution and enhancement process Local lifetimes i Kotlin Value semantics i Kotlin Rich errors i Kotlin Sum types Union types Javas projekt Leyden och projekt Valhalla Virtual threads i Java Kotlin multiplatform Compose multiplatform Kotlinconf-appen Stöd oss på Ko-fi! Erik Hellman Eriks presentation på Kotlinconf 2025 om IOT MQTT Matter Spec-driven development Jake Wharton - pratade om composebaserat terminal-UI-bibliotek Jesse Wilson Okhttp - Squarebyggt ramverk Lena Reinhard snackade om utvecklares roll i AI-världen Professional development - presentation från Google IO 2026 Clean code Kotlins LSP Junie - Jetbrains kodagent Lars Wikman Coursera-kurs om Kotlin för Javautvecklare Kotlin-övningar Builder pattern Bygga DSL:er med Kotlin WASM Uber snackar Kotlin Titlar Min Kotlinbana Kotlin på många olika sätt (Min upplevelse av) Sex år i Kotlin Bypassa hela stdout Jag är ju redan i utlandet Här slutade nullpointers En konstruktor som har alla parametrar

Parlament definitívne schválil rozsiahlu novelu zákona o cestnej premávke, nové dopravné predpisy, pravidlá parkovania a pre kurzy autoškoly majú začať platiť od septembra. Slovenských vodičov, chodcov aj používateľov elektrických kolobežiek po novom čakajú ďalšie zmeny v pravidlách cestnej premávky. Národná rada SR (NR SR) v utorok 2. júna 2026 definitívne schválila novelu zákona č. 8/2009 Z. z. o cestnej premávke, ktorú pred časom predložilo ministerstvo vnútra. Väčšina zmien má nadobudnúť účinnosť od septembra tohto roka, definitívne však treba počítať s tým, že zákon ešte čaká štandardný legislatívny proces po schválení v parlamente, teda podpis prezidenta a vyhlásenie v Zbierke zákonov. Nižšie vám uvádzame najdôležitejšie body, ktoré so sebou novela prináša.Otáčanie na svetelnej križovatkeJednou z najpraktickejších zmien je vypustenie všeobecného zákazu otáčania sa v križovatke s riadenou premávkou. Doteraz bol tento zákaz súčasťou § 22 ods. 4 písm. b). Po novom sa však toto znenie zo zákona stráca. V praxi to znamená, že vodič sa bude môcť otočiť aj na svetelnej križovatke, pokiaľ to situácia dovolí a zároveň to nebude zakazovať dopravná značka a neporuší pravidlá cestnej premávky iným spôsobom.Doterajší zákaz rezort vnútra označil za medzinárodne neštandardný. Po novom sa teda pravidlo mení. Otáčanie bude vo všeobecnosti možné, no správca cesty ho bude môcť na konkrétnom mieste zakázať štandardnou značkou znemožňujúcou otáčanie. Pre vodičov to podľa dôvodovej správy k predloženej novele znamená jednoduchšiu, logickejšiu a zrozumiteľnejšiu alternatívu v podobe umiestnenia zákazkovej značky priamo na danom mieste.Za extrémnu rýchlosť budú vyššie pokutyUž v minulosti sme vás informovali, že ministerstvo plánuje aj pomerne zásadným spôsobom zmeniť výšku sankcií za prekročenie rýchlosti. Zároveň viaceré médiá nedávno nesprávne informovali o novej výške pokút, ktoré mali začať platiť od 1. mája 2026 a boli previazané práve s touto novelou. To sa teraz skutočne stáva realitou. Novela totiž sprísňuje sankcie za výrazné prekročenie rýchlosti. Týka sa to prípadov, keď vodič prekročí povolenú rýchlosť v obci o viac ako 50 km/h alebo mimo obce o viac ako 60 km/h.Čo sa teda zásadne mení, je sankcia za najzávažnejšie prekročenie rýchlosti. V blokovom konaní sa pokuta pri prekročení rýchlosti v obci o viac ako 50 km/h alebo mimo obce o viac ako 60 km/h zvyšuje z dnešných 250 až 800 eur na 500 až 1 000 eur. Následne v riadnom konaní pôjde namiesto 500 až 1 000 eur o pokutu od 800 do 1 300 eur.V pešej zóne najviac 10 km/hZmena sa dotkne aj vozidiel, ktorým dopravné značenie umožňuje vjazd do pešej zóny. Po novom budú môcť jazdiť rýchlosťou najviac 10 km/h. Ide najmä o prípady zásobovania, rezidentov, komunálnych služieb alebo iných vozidiel, ktoré majú do pešej zóny povolený vjazd.Pre vodiča to znamená, že v pešej zóne už nebude stačiť len „ísť pomaly“. Zákon stanoví konkrétnu hranicu. V miestach, kde sa prirodzene pohybujú chodci, deti, cyklisti alebo turisti, má ísť o praktické zníženie rizika kolízií.Chodci nesmú vstupovať na priechod náhle ani so zníženou pozornosťouNovela upravuje aj správanie chodcov na priechode. Chodec nebude môcť vstúpiť na priechod náhle a zároveň nebude môcť používať telefón alebo podobné zariadenie takým spôsobom, ktorý znižuje jeho schopnosť sledovať situáciu v cestnej premávke.Zmyslom tejto úpravy nie je zobrať chodcom ochranu, ale jasnejšie pomenovať ich vlastnú zodpovednosť. Vodič bude musieť aj naďalej dávať pozor na priechody, no chodec sa nebude môcť spoliehať na to, že môže bez sledovania premávky vstúpiť priamo pred prichádzajúce vozidlo. Stále tak platí, že na Slovensku nemajú chodci absolútnu prednosť.Prísnejšie pravidlá pre elektrické kolobežkyJednou z najzásadnejších úprav novely je časť, ktorá rieši malé elektrické vozidlá, teda najmä elektrické kolobežky a podobné dopravné prostriedky. Po novom bude v cestnej premávke zakázané používať kolobežky s pomocným motorčekom alebo elektromotorom, ktoré umožňujú vyvinúť rýchlosť vyššiu ako 25 km/h.Schválená novela totiž zavádza do zákona pojem malé elektrické vozidlo. Pod túto kategóriu majú patriť práve elektrické kolobežky s pomocným motorčekom, ak ich elektromotor neumožňuje vyvinúť rýchlosť vyššiu ako 25 km/h. Zároveň sa medzi závažné porušenia pravidiel cestnej premávky dopĺňa používanie kolobežky alebo samovyvažovacieho vozidla, ktorého elektromotor umožňuje jazdu rýchlejšiu ako 25 km/h.Alkohol sa bude riešiť aj pri spolujazdcoch na niektorých vozidláchNovela zavádza aj toľkokrát zmienený zákaz alkoholu aj pre spolujazdcov v prípade motocyklov a viacmiestnych bicyklov. Týkať sa to má aj turistických atrakcií typu beerbike, kde sa viac osôb aktívne podieľa na jazde napríklad šliapaním, brzdením alebo ovplyvňovaním rovnováhy vozidla. V praxi to znamená, že zákon nebude riešiť iba vodiča, ale aj osoby, ktoré síce nesedia za volantom v tradičnom zmysle slova, no svojím správaním môžu ovplyvniť bezpečnosť jazdy.Objektívna zodpovednosť sa rozšíri, obce však nedostanú všetkoPolicajný zbor bude môcť cez objektívnu zodpovednosť držiteľa vozidla riešiť širší okruh porušení pravidiel cestnej premávky. Vládny návrh uvádzal napríklad rýchlosť, zákaz predchádzania, zákaz jazdy v protismere, povinnosť zastaviť na stopke alebo na červenú, zákaz otáčania a cúvania, zákaz státia, prejazd cez železničné priecestie v zakázanom čase či používanie telefónu počas vedenia vozidla.Z definitívne schválenej úpravy však podľa zverejnených dokumentov vypadlo rozšírenie pôsobnosti obcí pri objektívnej zodpovednosti. Obce tak majú naďalej využívať tento režim len pri parkovaní. Pre vodičov to znamená, že pri viacerých priestupkoch môže sankcia prísť držiteľovi vozidla bez toho, aby polícia priamo zastavila vodiča na mieste.Autoškoly čaká zmena, pri skupine B pribudne podmienka vzdelaniaNovela mení aj systém výcviku v autoškolách. Žiadateľ o vodičské oprávnenie má najskôr absolvovať teoretickú časť kurzu a skúšku z teórie. Až po jej úspešnom zvládnutí bude pokračovať v praktickej časti vodičského kurzu. Zavádza sa aj nová podmienka pre zápis do vodičského kurzu na skupinu B, ktorou má byť získanie aspoň nižšieho stredného vzdelania.Pre budúcich vodičov to môže znamenať dlhší a prísnejšie rozdelený proces získania vodičského preukazu. Zároveň sa tým má zvýšiť šanca, že žiak sadne za volant až po zvládnutí základných pravidiel cestnej premávky.Zmeny v parkovacej politike obcíSúčasťou schváleného návrhu je aj úprava parkovania v mestách a obciach. Nejde však priamo o zmenu zákona o cestnej premávke, ale časť novely, ktorou sa novelizuje zákon č. 135/1961 Zb. o pozemných komunikáciách, teda cestný zákon. Mení sa jeho § 6a, ktorý obciam umožňuje organizovať a regulovať platené parkovanie. Po novom sa spresňuje, že táto regulácia sa netýka iba krátkodobého parkovania, ale aj dlhšie trvajúceho státia, najmä rezidentského parkovania. Obce budú môcť vo všeobecne záväznom nariadení presnejšie určiť podmienky parkovacích kariet, ich územnú a časovú platnosť, počet oprávnení na jedného žiadateľa alebo jednu nehnuteľnosť, vzťah žiadateľa k vozidlu či k nehnuteľnosti, zľavy alebo pravidlá predčasného zrušenia parkovacieho oprávnenia.Novela prešla hlasmi koalície. Kedy začnú nové pravidlá platiť?Novela ešte nezačne platiť okamžite po hlasovaní v parlamente. Národná rada SR ju definitívne schválila v utorok 2. júna 2026, no zákon musí ešte podpísať prezident a následne musí vyjsť v Zbierke zákonov. Väčšina zmien má podľa schváleného znenia nadobudnúť účinnosť od 1. septembra 2026. To sa týka aj viacerých praktických zmien pre vodičov, napríklad prísnejších pokút za najvýraznejšie prekročenie rýchlosti či novej rýchlosti v pešej zóne. Časť úprav však môže mať inú účinnosť, preto bude pri konkrétnych povinnostiach rozhodujúce finálne vyhlásené znenie zákona.Novela prešla najmä hlasmi koalície. Zo 126 prítomných poslancov hlasovalo za návrh 78, proti boli dvaja a 46 sa zdržalo. „Za“ hlasovali prítomní poslanci klubov Smer-SD, Hlas-SD a SNS, pridali sa aj viacerí nezaradení poslanci. Opozičné kluby PS, KDH a SaS sa pri hlasovaní zdržali. V klube Slovensko hlasovali dvaja poslanci proti a ostatní prítomní sa tiež zdržali.

Igor má patenty registrované po celom svete. ❤️Pozrite si aj hodnotné kurzy: https://skola.odznova.sk/ - ❤️Využite zľavy na nákupy: https://40plus.sk/vychytavkyRobí produkciu aj pre zdravých (tenisky, barefoot, šlapky) ale aj pre nohy s rôznymi diagnózami. Ale melie z posledného! Prečo? Ničí ho Ázia a podvodná reklama výrobcov. Problém je aj s lekármi, ktorí predpisujú neúčinnú obuv svojim pacientom. Je lacná, ale nefunguje. Pozrite si rozhovor a keď potrebujete topánky či tenisky, alebo skutočné barefoty, ktoré vydržia, pozrite na https://epur.sk/ Igor vám dá aj lepšiu cenu. Kupon VYHODNE.Pomôžte svojim nohám. Pošlite každému, kto má vo vašom okolí halux, ostrohu, diabetes alebo robí dlhé prechádzky Ale garantujem, že nájde každý z vás niečo.Som rada, že aj vďaka vám môžem robiť túto prácu a prepájať tak komunitu*********************************************************Ďakujem, že ma podporujete svojimi darmi na HeroHero alebo tu na YouTube. Aj vďaka vám vzniká tento obsah. Chcete ma začať podporovať? Info tu: https://herohero.co/odznova Podpora je možná aj tu na YouTube.. zmysel to má od 5,99€ (50% z vášho predplatného mi zoberie YouTube ako províziu. Tak si to viete spočítať...Hero berie len 12,3%) INFO: Predplatné 2,99 na YT je bez nároku na obsah vopred. Ide len o sympatizovanie, za čo ďakujem... Ak nechcete platiť kartou, možné je podporovať aj cez číslo účtu o.z. : SK45 8330 0000 0022 0165 1060 - názov účtu: Institut Trvaleho Rozvoja 40+ do poznámky uveďte, že ide o DAR ĎAKUJEM a nezabudnite pozrieť info a linky o podujatiach ... ( INFO: Podujatia ❤ - https://www.40plus.sk/podujatia-odznova/ Buďte zdraví Martina Valachová• Web: http://www.40plus.sk • Facebook: http://fb.com/40plus.sk • Instagram: / odznovapodcast

Spolupracovník Andrej Žiarovský a redaktor Lukáš Krivošík diskutujú o geopolitických ohniskách dneška. Ukrajinci zasiahli ciele v Petrohrade v čase, keď sa tam konala prestížna konferencia. Darí sa Kyjevu preberať na bojisku iniciatívu? Volodymyr Zelenskyj poslal Vladimirovi Putinovi list, v ktorom ho vyzval na stretnutie v neutrálnej krajine. Aj ruský prezident vypúšťa vyhlásenia, ktoré naznačujú možnosť skorého ukončenia vojny. Ide o seriózny trend alebo len divadlo pre domáce publikum? Rozoberieme aj dianie na Blízkom východe. Objavili sa informácie o nezhodách medzi americkým prezidentom Donaldom Trumpom a izraelským premiérom Benjaminom Netanjahuom. V Iráne, zdá sa, pozorujeme mocenský vzostup Mohammada Bákera Kálíbáfa. Čo to znamená pre budúcnosť? V závere sa ešte vrátime na Slovensko. Kým časť verejnosti viní bývalú vládu, že za zbrane pre Ukrajinu dostaneme len zlomok očakávanej sumy, druhá časť obviňuje súčasné vedenia ministerstva obrany, že systém protivzdušnej obrany Kub predal pod cenu. Majú tieto dva prípady niečo spoločné?

Pour l'épisode #344 je recevais Julien Briault. On en débrief avec Tugdual.

A Aliança da Redenção (parte 5) - Gabriel Manzoni by IDE

V areáli, ktorý sa nachádza neďaleko Zvolena a patrí súkromnej spoločnosti Robus z Krupiny, nájdete najmä vyradenú vojenskú techniku. Parkujú tam však aj dve plné batérie protivzdušného systému 2K12 Kub. Predseda Demokratov Jaroslav Naď tvrdí, že ide o funkčné stroje a z dostupných zmlúv usudzuje, že mohli byť predané ako šrot a pod svoju cenu. Ide pritom preňho o citlivú tému, keďže od Roberta Kaliňáka aj premiéra stále počúva, ako práve on nechal Slovensko neozbrojené po tom, čo poslal techniku na Ukrajinu. Teraz sa Kaliňák bráni, že to práve za Naďa vznikla dohoda o kuboch. Čo, kto, komu predal, aký problém vznikol a aké sa ponúkajú vysvetlenia? O To sa pýta Nikola Šuliková Bajánová reportéra denníka SME Michala Katušku. Zdroje zvukov: JOJ24, YouTube/Demokrati Odporúčanie Včera som odporúčala dva filmy, jedným z nich bol horor The Backrooms. Najviac sa mi na ňom páčila atmosféra, kulisy a soundtrack. V tom na záver zaznela skladba The Word Becomes Flesh. Ide o track z nového albumu dvojice Boards of Canada, prvého po trinástich rokoch. Pomenovali ho Inferno a dnes je mojím odporúčaním. – Všetky podcasty denníka SME nájdete na⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ sme.sk/podcasty⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ – Odoberajte aj audio verziu denného newslettra⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ SME.sk⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ s najdôležitejšími správami na⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ sme.sk/brifing See omnystudio.com/listener for privacy information.

Hebrejom 12,18-24 18 Nepriblížili ste sa k hmatateľnému a plápolajúcemu ohňu ani k čierňave, k temnote alebo búrke, 19 ani k hlasu poľnice a zvuku slov. Tí, čo ho počuli, prosili, aby im viac neznelo slovo. 20 Nemohli totiž zniesť príkaz: Ak sa čo i len zviera dotkne vrchu, nech je ukameňované. 21 A také hrozné bolo to, čo videli, že Mojžiš povedal: Som vyľakaný a trasiem sa. 22 No vy ste sa priblížili k vrchu Sion a k mestu živého Boha, k nebeskému Jeruzalemu, k desaťtisícom anjelov, k veľkolepej slávnosti, 23 k zhromaždeniu prvorodených, ktorí sú zapísaní v nebi, k Bohu, sudcovi všetkých, k duchom spravodlivých, ktorí už dosiahli dokonalosť, 24 k Ježišovi, prostredníkovi novej zmluvy, ku krvi očistenia, ktorá volá hlasnejšie než krv Ábela. „Game-changer“. Dnes mladí ľudia radi používajú cudzie slová na pomenovanie rôznych vecí, javov, či ľudí. Jedným z takýchto slov je aj slovo „game-changer“. Ide o niečo, čo radikálne mení situáciu. Toto slovo by sa dalo preložiť ako „ten, čo mení pravidlá hry“. V našom dnešnom texte vidíme veľký rozdiel medzi vystrašeným prístupom ľudí k Hospodinovi na vrchu Sinaj a radostným prístupom na vrchu Sion, ktorý tu reprezentuje večný život v Božom kráľovstve. Aký ohromný „game-changer“ je Pán Ježiš! Pred Jeho Príchodom sa Boh zdal byť vzdialený a hrozivý. Samotný Mojžiš bol po návrate zo Sinaja vyľakaný a triasol sa. S Ježišovým príchodom nám však Pán Boh otvára dvere do Svojej prítomnosti, do Svojho nebeského kráľovstva. Skrze krv Pána Ježiša, ktorá nás očisťuje od všetkých našich neprávostí, sa stávame omilostenými Božími deťmi. Pán Ježiš je skutočne Tým, Kto v dejinách ľudstva radikálne mení pravidlá hry. Odovzdaj dnešný deň (i celý svoj život) Tomu, Kto Svojou prítomnosťou všetko mení! Modlitba: Bože, ďakujem Ti za takú veľkú a draho zaplatenú zmenu, čo priniesol Pán Ježiš! Odpusť, že si z nej vyberám len to, čo sa mi páči! Meň moju myseľ, nech Ťa nasledujem až do konca! Amen. Pieseň: ES 456 Autor: Branislav Sadloň Očakávaj Hospodina! Buď silný! Nech je pevné tvoje srdce. Očakávaj Hospodina! Žalm 27,14 Marta povedala Ježišovi: „Pane, keby si bol býval tu, nebol by mi brat zomrel. Ale aj teraz viem, že o čokoľvek by si prosil Boha, Boh Ti to dá.“ Ján 11,21-22 Hebrejom 2,(1-4)5-10 •  Modlíme sa za: Senné (NoS) Otázky na rozjímanie: Ako dnes vnímam rozdiel medzi strachom na vrchu Sinaj a radosťou na vrchu Sion — kde v mojom živote stále pristupujem k Bohu so strachom, namiesto s dôverou v Božiu milosť v Kristovi? Kde v mojom živote potrebujem si uvedomiť, že Ježiš je „game-changer“, ktorý radikálne zmenil pravidlá hry — v akej situácii stále čakám na trest, hoci už mám prístup k očisteniu a zmiereniu skrze Jeho krv? Ako dnes žijem z prístupnosti k nebeskému Jeruzalemu, k desaťtisícom anjelov a k Bohu ako Otcovi — či žijem ako Boží dieťa s istotou, alebo ako otrok so strachom? Aplikácia do života: V tomto týždni si vyhraďte 10 minút denne na čítanie Hebrejom 12,18–24 a modlitbu: „Pán Ježiš, uč ma pristupovať k Tebe s dôverou, nie so strachom.“ Zapíšte si jednu situáciu, kde stále pristupujete k Bohu so strachom (napr. hriech, neistota, vina, odsudzovanie), a jednu modlitbu, kde sa vyznávate, že už máte prístup k očisteniu a milosti. Na konci týždňa si overte, či sa mení váš postoj k Bohu — či ho vnímate viac ako Otca, nie ako Sudcu. Zdieľajte túto skúsenosť s niekým, kto potrebuje povzbudenie v prístupe k Bohu s dôverou. Dnes som vďačný za tieto 3 veci: _________________________________ _________________________________ _________________________________ Viac o vďačnosti, čo to je, prečo je dôležité byť vďačný, ako praktizovať vďačnosť nájdeš na blogu

"J'ai toujours su, quand je veux quelque chose, aller le chercher, mais surtout argumenter" Le D.E.V. de la semaine est Houleymatou Baldé, ex-Tech Lead et fondatrice de Yeeso. Venue en France sans prérequis informatiques, Houleymatou raconte comment elle est devenue tech lead après un parcours semé d'obstacles, entre autodidaxie, doutes techniques, volonté de légitimer sa place, et surtout capacité à provoquer ses propres opportunités. Elle partage sans filtre ce que veut dire assumer sa trajectoire atypique, demander sa reconnaissance au bon moment, et transmettre le leadership aux autres femmes de la tech, via l'association Yeeso qu'elle dirige. Houleymatou insiste sur l'importance des modèles visibles, du mentorat, et de l'écoute des signaux faibles du quotidien. Un épisode concret pour comprendre que prendre le lead, c'est surtout oser demander et assumer sa position, pas simplement enchaîner les certifications.Chapitrages00:00:59 : Un long voyage vers la légitimité00:07:16 : Le parcours d'Houleymatou00:11:26 : Engagement et volonté d'agir00:15:19 : L'importance de la représentativité00:28:37 : Reconnaissance envers les mentors00:28:54 : L'arrivée en entreprise et le décalage00:35:30 : Évolution et apprentissage continu00:39:19 : Devenir Lead Technique00:39:47 : Changement de Carrière00:41:31 : Intégration et Apprentissage00:43:35 : Rôle et Leadership00:46:09 : Apprentissage par Mimétisme00:51:55 : Création de l'Association Yeso01:03:24 : Leadership et Opportunités01:11:33 : Inspiring Future Generations Liens évoqués pendant l'émission Chaine Youtube de Yeeso & IT woman network24h chrono

„Preto nechajme teraz začiatočnícke učenie o Kristovi a povznesme sa k dospelosti. Neklaďme zase znova základy, hovoriac o pokání z mŕtvych skutkov, o viere v Boha,“. List Židom 6:1 Ako otec a starý otec viem z osobnej skúsenosti, že starostlivosť o bábätká dá poriadne zabrať. Napríklad naučiť dieťa jesť si vyžaduje veľa úsilia. Začína sa detskou výživou, čo prináša svoje vlastné jedinečné výzvy. Potom prichádza tuhá strava, ktorú treba nakrájať na malé kúsky vhodné pre dieťa. Samozrejme, dieťa nechce vždy jesť, takže musíš vymýšľať kreatívne spôsoby, ako ho povzbudiť, aby jedlo prijalo. Deti sa musia naučiť jesť, krájať si jedlo a napokon si ho aj pripravovať. To všetko je súčasťou dospievania. Autor Listu Židom túto myšlienku dospievania prenáša do duchovnej roviny. Mnoho ľudí nikdy duchovne nedospelo. Na začiatku sa síce zaviazali Kristovi, no nikdy skutočne nepochopili, čo znamená byť úplne oddaným nasledovníkom Ježiša. Stručne povedané, nereagovali na to, čo Biblia nazýva učeníctvom. Nie je to len otázka ignorovania biblických výziev, ako napríklad: „ale vzrastajte v milosti a poznaní nášho Pána a Spasiteľa Ježiša Krista.“ (2Pt 3:18) Ide aj o premárnenie dôležitých príležitostí a životných skúseností. Spomeň si na všetky kulinárske lahôdky, ktoré si si vychutnal odvtedy, čo si prešiel od detskej výživy k tuhej strave. Ten istý princíp platí aj pre duchovný rast kresťana. Prechod od duchovného mlieka k duchovnému pokrmu, ako ho opisuje List Židom 5:11–14, si vyžaduje úsilie a ochotu prekonať samého seba a vystúpiť zo svojej komfortnej zóny. Odmena však za tú námahu rozhodne stojí. Kresťanský život je viac než len vyslovenie modlitby odovzdania sa Kristovi. Znamená nasledovať Ježiša nielen ako svojho Spasiteľa, ale aj ako svojho Pána. Ak je tvojím jediným zdrojom duchovnej výživy počúvanie kázní iných ľudí, budeš sa duchovne nachádzať v relatívne oslabenom stave. Učenie a kázanie majú svoje miesto, no musíš sa naučiť, ako si, obrazne povedané, nakrájať vlastné jedlo. Musíš sa naučiť duchovne sa nasýtiť. List Židom 6:1 hovorí: „Preto nechajme teraz začiatočnícke učenie o Kristovi a povznesme sa k dospelosti. Neklaďme zase znova základy, hovoriac o pokání z mŕtvych skutkov, o viere v Boha,“. Musíme ako veriaci dospievať a odmietnuť zostať navždy duchovnými bábätkami. Musíme vyrásť a stať sa Božími mužmi a ženami. Otázka na zamyslenie: V ktorých oblastiach potrebuješ duchovne rásť? Greg Laurie

Na ktoré choroby cesnak funguje? A ako ho konzervovať, keď ho potrebujete ako liek.. aby nevymizli liečivé účinky? ❤️Pozrite si aj hodnotné kurzy: https://skola.odznova.sk/ - ❤️Využite zľavy na nákupy: https://40plus.sk/vychytavky Aj na to som sa pýtala v rozhovore. Imi priniesol aj mladý cesnak, ale aj niektoré zakonzervované produkty. Viete, čo je čierny cesnak? A kde nájdete liečivo v cesnaku v mede? Pozrite si celý rozhovor a verím, že vám dá odpovede. Predobjednávky na cesnak vraj môžete zasielať už teraz, lebo čas beží.. povedal Imi. webka hosťa: https://cesnak-slovakia.sk/*********************************************************Ďakujem, že ma podporujete svojimi darmi na HeroHero alebo tu na YouTube. Aj vďaka vám vzniká tento obsah. Chcete ma začať podporovať? Info tu: https://herohero.co/odznova Podpora je možná aj tu na YouTube.. zmysel to má od 5,99€ (50% z vášho predplatného mi zoberie YouTube ako províziu. Tak si to viete spočítať...Hero berie len 12,3%) INFO: Predplatné 2,99 na YT je bez nároku na obsah vopred. Ide len o sympatizovanie, za čo ďakujem... Ak nechcete platiť kartou, možné je podporovať aj cez číslo účtu o.z. : SK45 8330 0000 0022 0165 1060 - názov účtu: Institut Trvaleho Rozvoja 40+ do poznámky uveďte, že ide o DAR ĎAKUJEM a nezabudnite pozrieť info a linky o podujatiach ... ( INFO: Podujatia ❤ - https://www.40plus.sk/podujatia-odznova/ Buďte zdraví Martina Valachová• Web: http://www.40plus.sk • Facebook: http://fb.com/40plus.sk • Instagram: / odznovapodcast

Topics covered in this episode: CVE-2026-48710: A Maintainer's Perspective daily-stars-explorer Markdown to pdf with pandoc and typst postman2pytest Extras Joke Watch on YouTube About the show Brian #1: CVE-2026-48710: A Maintainer's Perspective Marcelo Trylesinski suggested by Lee Luocks Short version: users of Starlette: upgrade to Starlette 1.0.1 security professionals: we can't treat open source projects like corporations This top link is a Starlette security advisory with the title Missing Host header validation poisons request.url.path, bypassing path-based security checks The CVE apparently caused some negative press targeting starlette. However, “the vulnerability came from the application pattern and the deployment, never from something Starlette intended.” A quote from an OSTIF article: “This bug is a classic “responsibility gap” where if this maintainer didn't patch, thousands of exposed projects would have to individually secure their projects. In doing this work, they've voluntarily taken on the responsibility to protect the ecosystem from long-term systemic harm. As with all open source projects, they owed us nothing and could have left this to be everyone else's problem and took the extraordinary steps of helping the ecosystem.” Both X40 D-Sec and Ars Technica expected immediate fixes and responses from Starlette. That's not good. We can do better. Michael #2: daily-stars-explorer Explore the full history of any GitHub repository.

Nesta mensagem, o Pr. Gil Pimentel, com o texto em Marcos, capítulo 16, versículos 5 ao 10, nos traz uma reflexão sobre nesta vida todos iremos errar e pecar, e a ressurreição que nos alcança, nos dando asas.Quando pensamos em uma galeria, imaginamos um lugar onde obras preciosas são expostas para serem admiradas. Em Marcos 16:5-10 encontramos uma verdadeira galeria das asas, onde vemos pessoas que, pela graça de Deus, receberam "asas" para se levantar depois da dor, do fracasso e da desesperança.Na manhã da ressurreição, as mulheres foram ao sepulcro carregando lágrimas, dúvidas e saudades. Elas esperavam encontrar um corpo, mas encontraram uma mensagem de vida. O túmulo estava vazio. Jesus havia ressuscitado!Nesta galeria espiritual, podemos contemplar algumas "asas" que Deus deseja dar aos seus filhos.1. As asas da esperançaAs mulheres chegaram ao sepulcro esperando o pior, mas Deus já havia preparado o melhor.Muitas vezes também caminhamos carregando preocupações, acreditando que determinadas situações não têm mais solução. Porém, a ressurreição nos lembra que Deus continua escrevendo a história quando pensamos que ela terminou.A esperança cristã nasce exatamente onde os recursos humanos acabam.Deus é especialista em transformar túmulos em testemunhos.2. As asas do recomeçoO anjo trouxe uma mensagem especial: "Dizei aos discípulos e a Pedro..."Pedro havia negado Jesus três vezes. Ele carregava a culpa de seu fracasso. No entanto, ao mencionar seu nome individualmente, Deus estava mostrando que ainda havia lugar para ele.As asas do recomeço são dadas àqueles que pensam que perderam sua oportunidade.Quando Deus chama Pedro pelo nome, Ele está dizendo:"Seu erro não é maior do que a Minha graça."3. As asas da missãoAs mulheres não deveriam permanecer apenas contemplando o túmulo vazio. Elas receberam uma tarefa: "Ide e anunciai."Quem experimenta o poder da ressurreição não pode guardar essa notícia apenas para si.Deus nos dá asas para sair da paralisia e voar na direção do propósito.O Evangelho nunca foi uma mensagem para ser armazenada, mas para ser compartilhada.4. As asas da transformaçãoMarcos destaca que Jesus apareceu primeiro a Maria Madalena, aquela que havia sido liberta de sete demônios.Que contraste extraordinário!A mulher que um dia foi marcada por sua escravidão espiritual agora se torna a primeira testemunha da ressurreição.Isso nos ensina que Deus não define as pessoas pelo seu passado, mas pelo que Sua graça pode fazer nelas.As asas da transformação nos levam para além das marcas que carregamos.Conclusão: A galeria das asas em Marcos 16 não apresenta pessoas perfeitas. Ela apresenta mulheres assustadas, um discípulo fracassado e uma mulher que tinha um passado difícil.Mas todos eles foram alcançados pela ressurreição.Hoje, Deus continua expondo em Sua galeria homens e mulheres que receberam:As asas da esperança para vencer o desânimo;As asas do recomeço para superar os fracassos;As asas da missão para viver o propósito;As asas da transformação para testemunhar a graça.O túmulo vazio continua anunciando a mesma verdade: quem encontra o Cristo ressuscitado recebe asas para voar acima das circunstâncias e viver uma nova história.Porque a ressurreição não apenas muda o destino eterno; ela muda a maneira como vivemos hoje.Se esta mensagem edificou a sua vida, curta e compartilhe com mais pessoas.Deus te abençoe!

You wake up, brew the coffee, open GitHub, and there it is. Another pull request on your open source project. Thirteen thousand lines added. No issue filed first. No discussion. Just "here, please review this for me." Over the past year, GitHub activity has spiked roughly twelve times in a few short months, and a huge chunk of that signal is landing on the same small group of maintainers who were already stretched thin. The curl bug bounty got buried under AI-generated noise. Jazzband, the home of Django classics like pip-tools and the Django debug toolbar, hit what its maintainer called an "apocalypse" and started sunsetting. Even CPython just shipped fresh guidelines on AI-assisted contributions this week. So what does all of this actually look like from the receiving end of the pull request? On this episode, Paolo Melchiorre joins us to tell that story from inside the maintainer's chair. Paolo is a director of the Django Software Foundation, an organizer of PyCon Italy, a Django Girls coach, and he has spent the past year carefully collecting examples of how AI is reshaping open source contributions. The good, the bad, and the extra fingers. We dig into his PyCon US talk on AI-assisted contributions and maintainer load, why AI is best understood as an amplifier rather than a new kind of contributor, the wildly different policies across 86 open source foundations, whether projects banning AI today are reacting to last year's models. Episode sponsors AgentField AI Talk Python Courses Links from the show Guest Paolo Melchiorre: github.com DSF: www.djangoproject.com djangonaut-space: djangonaut.space PyCon Italia: 2026.pycon.it uDjango: github.com My PyCon US 2026 post: www.paulox.net AI-Assisted Contributions and Maintainer Load: www.paulox.net Senior Engineer Tries Vibe Coding: www.youtube.com Code Rabbit AI PR Reviews: www.coderabbit.ai GitHub Usage Graphs: github.blog Update on CPython's AI Policies: fosstodon.org High-Quality Chaos from Curl: daniel.haxx.se The Generative AI Policy Landscape in Open Source: redmonk.com Watch this episode on YouTube: youtube.com Episode #550 deep-dive: talkpython.fm/550 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Joe Maionchi (Co-founder & COO) and Rod Christensen (Co-founder & Chief Architect) of RocketRide join the MLOps Community to walk through AIDE — the AI Integrated Development Environment. RocketRide is an open-source AI pipeline platform that lets developers build, debug, and run production-grade agentic AI workflows directly from their IDE, with support for 13+ LLM providers, 8+ vector databases, and full multi-agent orchestration.AI Is Fast. AI Projects Are Slow. Let's Fix That. // MLOps Podcast #378 with JRocketRide's Joe Maionchi (Co-founder & COO) and Rod Christensen (Co-founder & Chief Architect)A huge shout-out to  ⁨RocketRide⁩  for this collaboration!

A Aliança da Redenção (parte 4) - Gabriel Manzoni by IDE

Hosts Brad Causey and Spencer Alessi break down the 2026 Verizon Data Breach Investigations Report, focusing on the findings that actually matter for IT and security teams.The biggest surprise: vulnerability exploitation has overtaken stolen credentials as the top initial access vector, accounting for 31% of attacks, while credential abuse dropped to just 13%. This completely flips the script on years of "identity is the new perimeter" thinking.Topics covered include:Vulnerability explosion and remediation crisis: Why there are too many vulnerabilities and not enough time for patching, with only 26% of CISA KEV vulnerabilities fully remediated (down from 38%)The patching time paradox: Median remediation time increased from 32 days to 43 days despite organizations initially getting faster at patching from 2022-2024Web application sprawl: How the push to cloud and SaaS has created massive attack surfaces organizations don't own and can't patchThe top 4 initial access vectors: Vulnerability exploitation, phishing, credential abuse, and pretextingRansomware economics shifting: 48% of breaches involved ransomware, but 69% of victims didn't pay and median payments dropped to $139,875Mobile phishing success: Mobile-centric phishing had 40% higher success rates than email phishing as users get better at spotting email threatsSocial engineering evolution: The human element appeared in 62% of breaches, with pretexting requiring different countermeasures than traditional phishingShadow AI explosion: 45% of employees are regular AI users on corporate devices (up from 15%), with 67% using non-corporate accountsAI data exfiltration: Shadow AI is now the third most common non-malicious insider risk, with source code being the top data type leakedMCP and IDE extension risks: Real-world examples including PocketOS having their entire production database deleted by Claude connected to a railway CLI MCPBrad and Spencer emphasize that while the threat landscape is shifting dramatically, the fundamentals still matter. Organizations need to get comfortable with not being able to patch everything and focus on what matters most.Blog: https://offsec.blog/Youtube: https://www.youtube.com/@cyberthreatpovTwitter: https://x.com/cyberthreatpovFollow Spencer on social ⬇Spencer's Links: https://spenceralessi.comWork with Us: https://securit360.com | Find vulnerabilities that matter, learn about how we do internal pentesting here.

"La plupart des développeurs ne sont pas des experts en sécurité. On nous demande de développer de plus en plus de choses." Le D.E.V. de la semaine est Tugdual Grall, Copilot Specialist chez GitHub. Dans cet épisode, Tug revient sur la façon dont l'IA et l'automatisation bouleversent notre rapport à la sécurité applicative. Il évoque la nécessité de former tous les développeurs à des réflexes DevSecOps, l'importance de l'automatisation pour rester à jour face à la complexité croissante et la difficulté de déléguer la responsabilité de la sécurité à des outils seuls. Tug partage aussi ses convictions sur la collaboration entre équipes et la sensibilisation progressive, plutôt que la recherche de l'outillage parfait. Un regard concret et sans surpromesse sur les pratiques de sécurité à l'ère de l'IA.Chapitrages00:00:56 : Faire du code fiable, c'est pas tout à fait la même limbonade.00:01:49 : Introduction à DevSecOps00:02:24 : Comprendre DevSecOps00:04:27 : L'importance de la sécurité00:05:28 : Pénétrer dans le monde des tests de sécurité00:07:33 : Sensibilisation à la sécurité pour tous00:08:50 : Outils et pratiques de sécurité00:10:54 : Collaboration et sécurité00:13:23 : L'impact de l'IA sur le développement00:18:16 : Récits de sécurité et vulnérabilités00:20:32 : L'avenir de la sécurité et des responsabilités00:29:38 : Évolution des métiers avec l'IA00:40:25 : L'impact de l'IA sur le travail00:51:18 : Partager et apprendre ensemble

Your documentation has two audiences now - humans reading the rendered HTML, and AI agents trying to make sense of your library. Rich Iannone and Michael Chow from Posit are back on Talk Python with a brand new Python documentation tool called Great Docs that takes both seriously. Rich is the creator of Great Tables, and before that the R package GT, the man has a serious eye for design, and he's pointed that energy at the Python docs ecosystem. We'll talk about how Great Docs spins up a polished site in three commands, why every page ships as Markdown for your favorite LLM, how it leans on Quarto for executable code blocks and tabbed install sections, and where it lands against Sphinx, MkDocs, and Zensical. Plus, you'll meet Tablin. Here we go. Episode sponsors Sentry Error Monitoring, Code talkpython26 Temporal Talk Python Courses Links from the show Guests Michael Chow: github.com Rich lannone: github.com Python Web Security with OWASP Top 10 and Agentic AI Course: talkpython.fm Great Docs: posit-dev.github.io/great-docs Great Tables: posit-dev.github.io GT Episode: talkpython.fm Sphinx: www.sphinx-doc.org mkdocs: www.mkdocs.org Zensical: zensical.org Hugo: gohugo.io Ghost: ghost.org Rs pkgdown: pkgdown.r-lib.org Quarto: quarto.org quickstart: posit-dev.github.io llms.txt file: llmstxt.org llms.txt: talkpython.fm mcp: talkpython.fm cli: talkpython.fm Watch this episode on YouTube: youtube.com Episode #549 deep-dive: talkpython.fm/549 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Topics covered in this episode: Dumb Ways for an Open Source Project to Die How to create a pylock.toml lockfile https://github.com/facebook/Lifeguard Choosing a Python Logging Library in 2026 Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 11am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: Dumb Ways for an Open Source Project to Die Core categories The maintainer left The maintainer is still there Sabotage and capture The release pipeline broke Force majeure The world moved on The project split - Examples Bulma PRs still from 2023, issues and PRs with no maintainer response for years, last release 1.5 years ago diskcache Similar, got hired by OpenAI, crickets after that Brian #2: How to create a pylock.toml lockfile Tim Hopper Tim walks through using uv, pip and pdm to create pylock.toml files. Recommendation: use uv export --format pylock.toml -o pylock.toml He also has How to install from a pylock.toml lockfile with pip but the short version is: use -r because tools treat it like a requirements file Michael #3: https://github.com/facebook/Lifeguard Lifeguard is a static analyzer to detect Lazy Imports incompatibilities and ease the adoption overhead for Lazy Imports in Python. I'm more excited about lazy imports after my Cutting Python Web App Memory Over 31% experience Some Python patterns depend on imports executing immediately. For example: Module-level side effects — a module that registers a handler or modifies global state at import time will behave differently if that import is deferred. The registry pattern — a module that registers itself (e.g., adding to a global dict) when imported will silently fail to register under Lazy Imports. sys.modules manipulation — code that reads or writes sys.modules assumes prior imports have already executed. Metaclasses and __init_subclass__ — class creation side effects may depend on imports being resolved. Project Stage: Beta Lifeguard is in active development. We are aiming to be ready for general use by the Python 3.15 final release. Brian #4: Choosing a Python Logging Library in 2026 Ayooluwa Isaiah " which libraries matter, how they compare, where they overlap with the standard module, and when each one makes sense.” The slant with this article is the need to log json output, which seems reasonable as things like API entry and exit point logging will include json. Covered libraries standard library logging with a hat tip to python-json-logger Same site has a guide to setting up python-json-logger structlog Loguru Logbook picologging Some benchmarks with structlog, stdlib+json, and Loguru, with structlog coming out faster I liked the Loguru example I'm going to have to try @logger.catch and logger.exception() for easily logging exceptions and serialize=True to enable JSON output. Extras Brian: When Women Stopped Coding - Planet Money segment , spotted on BlueSky from Savannah Ostrowski Lean TDD is now leaner Still working on audio version, but some great changes in 0.7.1 version Ch 6, TDD Interpretations, move ATDD and some of BDD to chapter Ch 7, Change name to TDD with Teams: BDD and ATDD Ch 9, Lean TDD, streamline steps and chapter Ch 10, Change name to Lean TDD with Teams: Lean ATDD Ch 11, Lean TDD with AI, Add short discussion about guardrails and security Michael: New course: Python Web Security: OWASP Top 10 with Agentic AI All courses now with Spanish subtitles, see announcement Joke: Stop texting me

Cap

I sit down with Logan Kilpatrick from the Google DeepMind team, live at Google I/O, to unpack everything Google just announced and what it means for founders and builders. We cover Gemini 3.5 Flash, the new Gemini Omni world model, the expanded Antigravity ecosystem, managed agents in the Gemini API, and the native Android app builder inside AI Studio. Logan shares how distillation keeps pushing Pro-level intelligence into Flash, where the real opportunities sit for solo founders, and why the agentic era has finally crossed the chasm from demo to useful. If you have an idea and want to ship something this week, this episode maps the toolkit. Timestamps 00:00 – Intro 00:53 – Gemini 3.5 Flash: The New Workhorse Model 01:49 – How Flash 3.5 Stacks Up Against Sonnet 02:38 – Gemini Omni: A World Model for Any Input and Output 06:18 – Building a Content and Creator Layer on Omni 08:21 – What to look forward to 10:53 – Google Spark and Managed Agents 14:00 – The Agentic Era and Requests for Startups 17:17 – The Antigravity Ecosystem Overhaul 18:51 – AI Studio vs. Antigravity: Vibe Coding vs. Agentic Engineering 21:31 – Native Android Apps Built Inside AI Studio 23:44 – Closing Thoughts Key Points Gemini 3.5 Flash ships as a Sonnet-level workhorse model tuned for long-running agentic tasks, coding, and tool use, available on day one to 900M+ Gemini app users. Gemini Omni is a single model that takes any input and produces any output across video, image, audio, and music, fusing Veo, Nano Banana, Lyria, and TTS into one system. Managed agents in the Gemini API let builders ship agentic products with a single API call, using skills and markdown instead of writing orchestration code. The Antigravity suite now spans an IDE, agent manager, CLI, SDK, and API surface, all sharing the same agent harness that powers Gemini Spark. AI Studio targets vibe coding and now builds native Android apps for free, while Antigravity targets production-quality, million-line-codebase engineering. The cost of intelligence keeps dropping thanks to distillation, opening up smaller markets that previously needed a 40-person team and venture funding to address. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND LOGAN ON SOCIAL X/Twitter: https://x.com/OfficialLoganK Youtube: https://www.youtube.com/@LoganKilpatrickYT LinkedIn: https://www.linkedin.com/in/logankilpatrick/

Take the 2026 AI Engineering Survey and get >$2k in credits and AIE WF tickets!On the product side, everyone is getting Computer - Perplexity, Manus, Cursor, and so on. Meanwhile on the research side, agentic evals like TerminalBench and GDPVal are also assuming computer (Harbor). On both ends, the consolidating LLM OS stack has become a standard toolkit, and Daytona is one of a small set of AI Infra companies that are booming because of it.“The end of localhost” has been Ivan Burazin's obsession for more than a decade.Something that is all too familiar…Long before agents became the default way people talked about software development, Ivan was already chasing the idea that development should not depend on a fragile local machine. CodeAnywhere, one of the first browser-based IDEs, was an early attempt at that future: move the development environment into the cloud, make setup reproducible, and free developers from the endless “works on my machine” tax.The thesis was directionally right, but the market wasn't ready yet.However, agents changed that. They do not care about a laptop, desk setup, or favorite editor. They need a computer they can access through an API: something stateful enough to keep working, fast enough to spin up instantly, flexible enough to resize, isolated enough to be safe, and composable enough to run the messy real-world workflows that real software engineering actually requires.Daytona isn't just selling “sandboxes” in the narrow code-execution sense. It is the latest version of Ivan's original localhost thesis.In this episode, Daytona's CEO joins swyx to explain why AI agents need more than code execution boxes: they need composable computers, stateful sandboxes, instant startup, dynamic resources, and infrastructure that can survive workloads going from zero to 100,000 CPUs.We go deep on the new agent compute market: Daytona's hard pivot from human dev environments to AI sandboxes, the New Year's Eve MVP that customers begged for, why Daytona runs on bare metal with its own scheduler, how one customer runs almost 850,000 sandboxes a day, and why RL/eval workloads went from 0% to roughly 50% of usage in just months. Ivan also explains why agents need Windows and macOS machines, why CLI may matter more than MCP, why Kubernetes is painful for this workload, and why the future AI cloud may look more like Stripe than AWS.We discuss:* How Daytona grew out of CodeAnywhere, Shift, and the “end of localhost” thesis* Why Daytona pivoted from human dev environments to AI sandboxes* Why agents need composable computers instead of disposable code execution boxes* The New Year's Eve MVP that customers chased API keys for* Why Daytona chose bare metal, stateful snapshots, and its own scheduler* How Daytona spins up one sandbox in ~60ms and 50,000 sandboxes in ~75 seconds* Why Daytona's biggest customer runs ~850,000 sandboxes a day* How RL/eval workloads create zero-to-100,000 CPU spikes* Why RL workloads went from 0% to roughly 50% of Daytona usage* Why customers compare Daytona against EKS/GKS and say they're “never going back”* Why every AI agent may need a computer, including Windows and macOS environments* The Apple licensing constraints that make macOS sandboxes hard* Why CLI gives agents more power than MCP* How open source helps agents integrate Daytona* Why agent-generated PRs may break today's CI/CD assumptions* Why AI SaaS companies reselling tokens may face a cold shower* Why the AI cloud may look more like Stripe than AWSIvan Burazin* LinkedIn: https://www.linkedin.com/in/ivanburazin* X: https://x.com/ivanburazinDaytona* Website: https://www.daytona.io* X: https://x.com/daytonaioTimestamps* 00:00:00 Hook* 00:01:12 Introduction* 00:03:15 CodeAnywhere, Shift, and the end of localhost* 00:05:58 What Daytona is: composable computers for AI agents* 00:08:07 The pivot from dev environments to AI sandboxes* 00:10:17 The New Year's Eve MVP and customers begging for API keys* 00:12:56 Bare metal, stateful sandboxes, and Daytona's scheduler* 00:17:28 60ms startup, 50,000 sandboxes, and 850K daily runs* 00:21:53 Spiky RL/eval workloads and the new agent infra problem* 00:28:12 RL workloads, Kubernetes pain, and dynamic resizing* 00:33:31 Why every AI agent needs a computer* 00:38:48 macOS sandboxes and Apple's licensing problem* 00:44:28 Why CLI may matter more than MCP* 00:48:11 Open source, GitHub stars, and agent integration* 00:53:11 Git, CI/CD, and agent collaboration bottlenecks* 00:58:15 Founder life and building a 25-person infra company* 01:02:44 AI SaaS, token resale, and API-first business models* 01:06:10 GPU sandboxes, data centers, and compute growth* 01:09:48 Why the AI cloud may look more like Stripe than AWS* 01:11:26 Closing thoughtsTranscriptIntroduction: Daytona, CodeAnywhere, and the End of LocalhostSwyx [00:00:02]: Okay, we're in the studio with Ivan Burazin, CEO of Daytona. Welcome.Ivan [00:00:07]: Thanks for having me, man.Swyx [00:00:08]: Ivan, you and I go back.Ivan [00:00:10]: Way back.Swyx [00:00:11]: How I don't even know how, you found, did you reach out or, for Shift.Ivan [00:00:17]: I reached out to you. The reason was you - we were just - we were thinking about I was one of the co-founders of CodeAnywhere, the first browser-based IDE, and so we were thinking a long time of, localhost should die. And you had this article.Swyx [00:00:29]: End of localhost.Ivan [00:00:30]: Then I reached out to you because of that, and then we talked, and I was actually at a different job and learning about I was the head of, developer experience, and you were quite well-versed in that, and I actually reached out to you, among other people, how do we go about that? What are the key things and whatnot at this point in time? And you were nice enough to take the call, and I remember I was late on your call with you.Swyx [00:00:51]: I don't remember.Ivan [00:00:52]: I remember because I was with my then I'm thinking of a girlfriend or wife at that point in time, I'm not sure. It's the same person, so that's great, and I was late ‘cause we were, in, Italy on, vacation, and then I was late for something. I felt so bad, and you were so nice to be, good about.Swyx [00:01:10]: The reason I'm nice is because I'm also late to other people, so it's like, who's, who's without sin here, yeah, so I have to, for those who don't know, InfoBip Shift, there's this whole thing that, you did in the past, and, and that was basically one of the inspirations for me starting AI Engineer, which is like, I have to thank you for giving me that push to be like, “Oh, you can, you can build and sell conferences?”Ivan [00:01:34]: I remember you asked you asked me at the beginning to give me advisory shares, and I was so focused on what we were doing, I said no, and I should've took the advisory shares. So I'm sorry, dude. But anyway.Swyx [00:01:43]: We're not, we're not venture backed.Ivan [00:01:44]: No, it doesn't matter.Swyx [00:01:45]: It's Yeah, anyway, so I think what's impressive about you is that CodeAnywhere is the thing that you've been trying to build, and, you kind of put it on hold and then came back after InfoBip. Just give us the story, do you - the story and the origin story, going into Daytona.From CodeAnywhere and Shift to DaytonaIvan [00:02:05]: Sure. Like, really way back, me and my co-founder have been together. I say this, I've said this multiple times, it's like we were married and divorced and married. Some people actually ask me is my co-founder my partner. they thought it literally. It's not literally, but we have done multiple companies together, and to your point, we had this shift where we went from the CodeAnywhere to the conference called Shift, and then back to, Daytona. We originally started stacking servers, doing like virtualization in the early 2000s and, routers and doing basically all these things, at a foundational level, and that was a services company which we sold to focus on what my co-founder actually invented, which was the very first browser-based IDE, right, I say the first. Before us was actually Heroku. They did it for a very short time until they became Heroku. But outside of them, we were the only one, and it was called.Swyx [00:02:55]: There was Cloud9.Ivan [00:02:57]: Cloud9 came out slightly after us. There was Replit, which came out when we stopped doing it, Replit came out, and they have been successful since then, which is great. There was Nitrous.io. There was quite a few that existed at the time, but it was like too early. But the interesting part is that we, at that point in time, because there was no VS Code, there was no Kubernetes, and Docker had just started when we Or I'm not sure if it was even public at that point in time. And so we had to build everything to the whole stack ourselves and that was the key learning that we brought into and that we've been using in Daytona today. So it was super early. There's about 3 million people used CodeAnywhere. It was slightly, it was angel-backed more than venture-backed. We ended up paying everyone back because it didn't have that sort of scale. But, three years ago, we started something similar with Daytona, which is not what we are today, but it was automating dev environments for human engineers, the basically the underlying stack of CodeAnywhere. And then we did a hard pivot last January to sandboxes. And so here we are.Swyx [00:04:01]: Historic pivot, yeah, and, it's one of those things where, I had independently invested in CodeAnywhere, but also in E2B, and then both of you pivoted into the same thing, and I'm like, “F**k.”Ivan [00:04:12]: You invested, you invested in Daytona. You invested in Daytona. But you were the first If we had not got your check, we wouldn't have done it.Swyx [00:04:18]: No way.Ivan [00:04:19]: No, it was like, “We have to get him on board first,” and you were that kicker that we, that got us off the ground.Swyx [00:04:23]: No, because you were putting me on your pitch deck, man. I was like, “Man, this is like a good trip if I don't invest.”Ivan [00:04:29]: That's because it was your quote. It's like we.Swyx [00:04:30]: Yeah. It's the end of localhost.Ivan [00:04:31]: Did a bunch of research about end of localhost and who was interested in that,.Swyx [00:04:34]: No, that's like, I put, I wrote that blog post, and every single company in that field reached out to me, and then every VC who was receiving those pitches then also had to call me and, talk it, talk through it with me.Ivan [00:04:47]: It's finally happening though.Swyx [00:04:48]: It was really super interesting.Ivan [00:04:48]: It's finally happening.Swyx [00:04:49]: It's finally happening.Ivan [00:04:49]: Yeah, it's finally.Swyx [00:04:49]: It's finally happening, with maybe sort of non-human users. Yeah, so what is Daytona today? Let's get like a quick description. I'm wearing the shirt.What Daytona Is Today: Composable Computers for AI AgentsIvan [00:04:58]: You're wearing the shirt. Yes,.Swyx [00:04:59]: It says, I think your branding is very good. Like, it's very consistent. It runs AI code. Like, it cannot be simpler.Ivan [00:05:05]: Exactly, but we're gonna probably have to change that.Swyx [00:05:07]: Oh, s**t.Ivan [00:05:07]: It's also a subset of what we do. Unfortunately, we really love this, Run AI Code is super simple. People interpret it different ways. I think we've given out 5,000, 6,000 of these shirts. People wear them with pride because it doesn't really market about us.Swyx [00:05:21]: Yeah, Daytona's on the back.Ivan [00:05:22]: It markets the back. It markets to the person itself, so I think we did a really good job on that one. But it is also a subset of what we do, because people, when they think about Run AI Code, they just think about these small, let's call it isolates, code execution boxes that, you send some code, you get an output. Whereas what Daytona is today is essentially composable computers for AI agents. It is, the market calls them sandboxes which can be misleading.Swyx [00:05:44]: All these things. All these things on.Ivan [00:05:45]: Yeah, exactly, ‘cause it can be misleading ‘cause people usually think about sandboxes as a demo or a test environment versus a production-grade environment. But what Daytona does, if you think of the laptop that you have in front of you or the computer that's over there, or, my wife is an architect, so she has like a Windows with a 3D graphics card inside to do 3D rendering. Like, as humans, we have different computers or different compositions of computers. And our belief is strongly that agents today and going forward will need all these different compositions of computers to do different types of tasks. And so we offer that basically through an API.Swyx [00:06:19]: Yeah, to give people - I'm trying to sort of front-load all the aha moments or the wow moments so that people can, stay engaged and click like and subscribe. the market is exploding, right? Like, you have been reporting 74% month-on-month growth, and it also, it's just been growing for a while. Like, it's been going like this. And every single - It's not just you guys. It's every single.Ivan [00:06:41]: Everyone, yeah.Swyx [00:06:42]: Sort of, compute provider. I don't know if you agree with me saying compute provider or not.Ivan [00:06:48]: It's fine.Swyx [00:06:48]: Yeah. So like organically PLG-driven growth, but also enterprise is doing super well, I think I wanna rewind to January of last year when you did the pivot. Like, so you obviously called this market early, and you were positioned for it, and you are now one of the market leaders. But what was the insight that made you do the pivot?The Pivot: From Human Dev Environments to Agent SandboxesIvan [00:07:06]: The insight that made us do this pivot is the quarter before that, so end of 2024, when we had - Basically, we did a demo with - I don't I think we discussed this as well, Devin was not public. You actually gave me access to Devin at that time. So Devin.Swyx [00:07:25]: I did?Ivan [00:07:26]: Yeah, you gave me access.Swyx [00:07:26]: I don't think I was supposed.Ivan [00:07:27]: Yeah, exactly.Swyx [00:07:28]: Yeah, I.Ivan [00:07:28]: So it doesn't matter. You.Swyx [00:07:29]: Yeah. I gave like three friends access.Ivan [00:07:31]: Yeah, or it was a call and you showed it to me. It doesn't matter. but OpenDevin was available, which is now called OpenHands. And so we're like, “Oh, this seems to be a thing. This is not public. Let's take our for human automation of dev environments and take, OpenDevin and launch that as a SaaS.” And we did that. Not very many people signed up and used it, but a lot of people reached out that were building agents, and they were like, “Hey, my agent needs a compute sandbox runtime,” whatever you wanna call it. I forgot what it was called at that point. And then we were like, “Oh, amazing. This is a new market. Here is our infrastructure. Here's our product, and go.” And what we found really fast, soon, was that people did not like what we had built. It didn't work. And I remember talking to people at the beginning when we're doing this, the sandbox we're building for agents. People were like, “Oh, why is it different? It's the same thing. We have like EC2, we have VMs, we have all these things.” But we saw that everyone we gave it to, it was like 20, 30 people, they all said, “No.” Like, “This is not what we need. This sort of breaks.” And basically, me and my co-founder not knowing a lot about - ‘cause we're infra people. We're not AI people. So I basically took it upon myself to like watch every single podcast that exists, including all of, all of these and all that, and sort of get up to date, read all the blogs, like get, understand what's going on.Swyx [00:08:45]: Do you wanna shout out who else was useful, just in case people are also looking.Ivan [00:08:49]: Generally we -, I looked at There's a few of podcast, different segments and different types. So there's you guys, No Priors, Bill Gurley's was great while.Swyx [00:09:04]: VG2, yeah.Ivan [00:09:05]: Yeah, while it was around. So there's a few. 20VC is interesting from a different dynamic, and some are different dynamic. But there was, also Red Points.Swyx [00:09:14]: We're not really about the compute market.Ivan [00:09:15]: It was also already - Sorry?Swyx [00:09:16]: You're, you want - You're looking at the agent infra market.Ivan [00:09:19]: I was looking at the agent market and the AI market in general and sort of understanding who are the players, what the perception, and how that goes. And like obviously you complement this with like going to conferences, going to events, going to meetups, reading white papers, like doing all the things that you have to do to understand what's happening. And so when we figured, when we sort of had an idea of what we had to build, literally over the New Year's Eve, literally on New Year's Eve, I half vibe coded the first MVP, first minimal viable product of what Daytona is today. And I went to sleep at like 3:00 AM or something like that. I was doing - I just put my like baby daughter and wife to sleep and, Happy New Year's, and go back to just, doing this. And I sent it to my co-founder, my CTO, and he saw it in the morning. He's like, “This is absolute garbage.” “Do not show this to anybody at all, but the idea is good.” And so he took two weeks, and he rebuilt it.Swyx [00:10:09]: Did it like look like that? Listen, I - It was rough idea.Ivan [00:10:12]: Oh, not even, not even close. Like it was it was way worse. But it was like a very - It was a simplistic view of what it should be. Like, it worked, but it was not ideal. And so he went, we went down the whole, which is his job as CTO, to go, and he came back with this version. We then called all the people that had said like, “This is garbage,” a quarter ago. And we set up these calls, and we gave it to - We just demoed it to everyone. And all the calls went long, every single one. They were 15-minute calls, and they all went to like 25, 30 minutes or whatnot. And everyone said, “We need, we want access.” There was no login, just an API key, ‘cause it was just a beta or an alpha. And they said, “Oh, we want access.” And we're like, “Sure, yeah. Okay, thank you very much.” But after like the next day, if we'd not send it, every single one, like every call that we did, everyone came back, “Where is my API key?” Like everyone wanted it. We're like, “S**t.” Like this is it. Like I've never felt So one, the understanding to your point was like most people thought it was the same infrastructure for humans and agents. We understood a quarter ago it's not. We just didn't know what was the right primitive. And then when we came, and we can talk about what that is, and we gave it to these people, I've never seen, I've never experienced - I've done multiple companies in my life. I've never experienced this, that people literally call you if you do not give them access. Like they want access right now. And so it's like, okay, they don't want this. the thing that they want doesn't seem to exist, or they have not found it, and they really want what we want. And then when we understood that we're onto something, and then when you think about the size of the market, like the market for human engineers and enterprise is a very large market, so think GitLab or whatnot. But the market for every single agent that will exist ever in the future is just like, what is that market? How big is that? And we're like, “We are all in on this.” And so that is where we made sort of the cut between the old product and the new one.Bare Metal, Stateful Sandboxes, and the Lambda + EC2 ModelSwyx [00:12:02]: Yeah. But it wasn't composable at the time?Ivan [00:12:05]: It was very - It was basically just a Linux box that you could change, that you could define number of CPUs, disk, and RAM. Like that is what you could do, but you couldn't have multiple operating systems, you couldn't resize it on the fly, you couldn't add a GPU, you couldn't do like all the things. It was just the, just the first sort of variation of that, yeah.Swyx [00:12:22]: Was it bare metal from the start?Ivan [00:12:24]: It was bare metal from the start. And so the interesting thing that we thought about right away, so our.Swyx [00:12:29]: Which, give people the background, what is the normal path?Ivan [00:12:32]: Yeah, so, basically most providers run this on top of VMs. And also.Swyx [00:12:37]: Firecracker.Ivan [00:12:38]: Yeah, they run on Firecracker and VM. And so we also fire - We can get - We have multiple isolation layers and we can do that. But the common way to do it is that they, one, that the state of the machine, or the hard disk is not part of the sandbox itself. And the other thing is they're not meant to last forever. So most of them are preemptible, like they can There's a time that they can live. And so our thought was when we were going into this is, agents will be like humans in the sense of you don't want your laptop to be shut down until you're done with work. Like, and you want to close the lid and open the lid, it's the same state. So you - Agents would want that, like the pause and come back. They want those two things. But also agents really want speed, right? Can they get it? So when we thought about it's like we need something insanely fast, how to make it fast, how to make it long-running, and stateful. And so those two things, it's like combining a Lambda and an EC2, right? Those two things together. And so we didn't have an idea how others did it, ‘cause we didn't know too that there was a market around this. It was more like, okay, this is what we need, what they need. And we looked at Kubernetes, it wasn't wasn't good enough for that. We looked at Nomad, it didn't enable that. And so our history in rewriting our own scheduler at CodeAnywhere is basically what my CTO came up with. Like, he's like, “Oh, the learnings from there,” and he brought it. And the funny thing is, our third co-founder, when he saw it, he's like, “Dude, what is this? This is like 2008.” Like, we went back in time, and he's like, “Exactly.” And so the reason why Daytona is like super fast, and you see this on benchmarks, is we essentially, we run on bare metal. We have our own scheduler, we use the underlying, disk, CPU, and RAM of the underlying machine, which means your IOPS are insanely fast because there's no, there's no network between an EBS or something like that. But also the snapshot, the point in time, the templates, are also preloaded on the bare metal machines. So when you fire off a sandbox from a template or a snapshot, you're essentially directed to the bare metal machine where that snapshot is based on that NVMe drive, and then it literally just turns on that machine, and it's local. There's no network latency, anything on there. And so that is sort of the specificities that we, when we're thinking from first principles, what a computer would look like for an agent, that is what we came up with, and that's what we created.Benchmarks, 60ms Startup, and 50,000 SandboxesSwyx [00:15:02]: Yeah. I should maybe, I don't know if you endorse this, but there's someone that does compute SDK, you guys do very well on there, with like the TTI, right? I. is this a, is this a is this a relevant benchmark for you guys? I don't know.Ivan [00:15:16]: I don't know, and it changes every day. So today RKL is.Swyx [00:15:18]: I don't know what RKL is. Never heard of it.Ivan [00:15:20]: Yeah. RK, yeah, so it is there.Swyx [00:15:22]: You are, at least a third of the next tier of performance, and then, there's a lot of other better-known names that are very slow to start.Ivan [00:15:31]: Yeah. We've been the number one by far for a long time, and now there's different, there's different definitions also of sandboxes, different isolation patterns, different other things. So RKL runs it literally on the S3, the data, so it's very different, and they spin up a sandbox, spin up a container for that, so it's a different type of thing. So the definition of a sandbox is something that we can all, we all need to get along with. But yeah, we're insanely fast on getting these things, up and running. And so you can see even there that it's a zero point 0.10 to 0.11, so.Swyx [00:16:03]: Close enough. Yeah. what else do you need, right?Ivan [00:16:05]: Yeah. So the benchmarks itself, so, in this, in I don't think the benchmarks equate to market ownership or revenue or anything like that. and I've seen this with multiple benchmarks, not just in sandboxes, but in general benchmarks around.Swyx [00:16:20]: It's table stakes. It's just like.Ivan [00:16:21]: Exactly. But it doesn't hurt.Swyx [00:16:22]: Just roughly check.Ivan [00:16:22]: Like you definitely have to be up there and you have to be competing so that people know that, oh, this is definitely one of the top. Because this is only one dimension of what customers look for. There's other things like how many can you spin up consecutively? There's a feature set, there's support, there's like all different things that people look at, but you definitely have to be there, on the benchmarks.Swyx [00:16:40]: How many people do people spin up consecutively?Ivan [00:16:43]: So we have.Swyx [00:16:43]: Or concurrently, is the Concurrency, right?Ivan [00:16:45]: There's three metrics that we look at. And so one is like time to spin up one, and so our time to spin up one is 60 milliseconds with network latency. So request, spin up, reply, 60, the whole thing, 60 milliseconds. That is one. But if you wanna spin up 50,000 at once, we are now at about 75 seconds. So it takes about 75 seconds to spin up concurrently 50,000. Some others, there's public data around this, like take 2,000 seconds, which is 30 minutes. Like there's different variations of that. And then there is the so it is speed of one, speed of like multiple, and then how many can you consistently have up and running. And so we basically have right now no limit to how much we can add because we basically own our own metal. But the biggest customer of ours does like about 850,000 every single day is sort of where they're, where they're just shy of a million every single day that they're running, we do have a request for half a million concurrent, which is literally half a million CPUs somewhere running. So that's an interesting.Swyx [00:17:44]: They pay by like vCPU seconds.Ivan [00:17:47]: By seconds, yeah.Swyx [00:17:47]: Or whatever. Yeah. Okay, and so and then, and the other thing is, the sleeping and the resuming, ‘cause it's all the stateful resumption of all these things, how, what kind of workload are people putting through this, right? Like how is it Do we measure by gigabytes in memory, gigabytes in storage? I don't In like network attached storage. I, what are the costly ones of, out of all these features?Workload Economics: CPU, RAM, Network, and StorageIvan [00:18:15]: The most expensive thing are CPU.Swyx [00:18:18]: Okay. Yeah, of course.Ivan [00:18:18]: The second one, yeah Then it's RAM, then it's disk. We actually don't charge.Swyx [00:18:22]: Which is snapshotting, right?Ivan [00:18:23]: No, it's actually the, snapshotting's part of it, but basically the size of your hard disk, of your machine. So do you have 10 gigabytes, do you have 20, do you have 50, do you have whatever? And then the transference of that. Right now, currently we don't charge for, network at all at Polychron.Swyx [00:18:37]: Oh, you gotta, yeah, you gotta fix.Ivan [00:18:38]: Yeah. It is very much a it's a larger and larger part of our bill, so we're working around, that part there. Obviously, that is the least, expensive, so the hard disk is the least expensive, so it's basically CPU, RAM, for us network, ‘cause we don't charge the customer, and then hard disk, is how it's split up. But there's also different types of workloads, so we basically split it up into two types of workloads in Daytona. One is what we call background agents or long-running agents. and the other is, basically RLs and evals, which I put sort of together. And so they have very different patterns of usage, and if you look at the usage of a background And I'll just name names of companies, not specifically.Background Agents vs. RL/Evals: Two Usage ShapesSwyx [00:19:21]: Yeah, open, all hands.Ivan [00:19:23]: Yeah. So like a background agent's a Cognition, a Lovable, a like all these things are Harvey. These are all long-running, background agents. And so if you look at their usage patterns, their usage patterns are similar to human, which is like follow the sun. Basically, the usage patterns of that is like noon is probably the highest, and the midnight is the lowest, and then weekends are lower. weekday is higher.Swyx [00:19:42]: Yeah, that's a fun question. How global is it? Is it very US-centric or?Ivan [00:19:46]: The US is a large part, but we have currently, we have Asia, Europe, and the US regions.Swyx [00:19:52]: So it's quite global.Ivan [00:19:53]: Yeah, it's quite global. We have it all over. It's interesting that our I talked to you a bit about this. Our number one city by user.Swyx [00:20:01]: Hmm.Ivan [00:20:02]: Is Singapore.Swyx [00:20:04]: Oh, wow. Amazing.Ivan [00:20:05]: Which is an interesting one, right? Not by revenue, just by just like by individual head count.Swyx [00:20:09]: Really?Ivan [00:20:09]: Just like an interesting thing.Swyx [00:20:10]: Singapore is, Singapore is weirdly high in the adoption charts of AI for the population. It's like an, seven, eight million population. And it's like keeps showing up.Ivan [00:20:20]: No, it's quite interesting. We were quite shocked, and I was like, “Oh, this is interesting.” And also one that's up there.Swyx [00:20:24]: There's a reason I'm doing AI using Singapore. it's because I'm from there.Ivan [00:20:27]: We're there. We're gonna, we're gonna be there as well. and it's interesting that Japan is in the top or like Tokyo's in the top, which is in all the tech cycles it has never been. It has never been, so it's quite interesting that they're.Swyx [00:20:39]: I think the Japanese just love AI. Yeah. It's that, and then it's Brazil. That's it.Ivan [00:20:44]: Brazil has always been in.Swyx [00:20:45]: I think.Ivan [00:20:46]: Even when I look, if you look at like GitHub's data and ask historically with CodeAnywhere, it was always like US, Western Europe, and then you'd have like India, Brazil, China, like that would be there. But like Singapore was not in, specifically Japan was never in sort of that top, that top.Swyx [00:21:01]: Yeah. Weird pockets.Ivan [00:21:01]: Weird. Yeah, so it's very global.Swyx [00:21:02]: Okay, so actually that, but that's helps you to distribute your load through, all time?Ivan [00:21:08]: The interesting thing is like we have those kind of loads, but if you look at the researcher loads, they're quite different. So what they are is like if you give them concurrency of 10,000 or 50,000 or 100,000 CPUs at ARMb, when they fire off a run, it's just 100%. And then it just runs, and then it stops. So it's very, the usage pattern is squares basically, right? And it's also not follow the sun, because people will fire it off at midnight before they go to sleep but then wake up and so it's very unpredictable, so you don't know where that is. So the shapes of the usage are quite different than we have had before. And also what's interesting is when it's sort of a follow the sun, even if you have a high growth company, you can sort of predict your usage patterns and have enough capacity for that, because it's sort of, it grows in a, in a way you can project. When you have companies doing sort of like evals and RL, they're super spiky. So they're gonna come in, it's like, “We're gonna use nothing, then can we have 100,000?” Right? And then go back down. And then 100,000, go back down. So it's very different, right? And.Swyx [00:22:09]: Do you want to lock them into commits so.Ivan [00:22:11]: Yeah, we do.Swyx [00:22:12]: Yeah, okay.Ivan [00:22:12]: We so we have to lock them into some sort of commits to have that capacity, because we have to have, basically we have to have the capacity for peak. Right? And so right now, Daytona's mean utilization is 15%, 1-5.Swyx [00:22:25]: Oh my God.Ivan [00:22:26]: So it's very low.Swyx [00:22:27]: Because it's very spiky.Ivan [00:22:27]: It's very spiky, but we get up to 90%. so we have these things. And so what we're, what we're looking at right now as a company is similar to Cloudflare where you can like geo move things around, but that works really well for basically the background agent where it's follow the sun. But this, it's not. Like it's a very different shape. Obviously with scale you figure these things out, but that's an interesting new problem that we have, as a compute provider in the agent space. And when we were doing the conference recently, and so we talked to like Nikita from Neon and.Swyx [00:22:57]: I should bring it up.Ivan [00:22:58]: Parag from Parallel and whatnot, everyone has the same problem. Whereas the usage is super spiky, and this is something that has not happened before, that you have these types of like it was always, it the amplitudes were not this high, right? So it's quite interesting use case and problem solve.Compute Conference and Spiky Agent InfrastructureSwyx [00:23:12]: Yeah, I don't know if we're gonna bring this up again, but let's just talk about the conference, you had like 1,000 something people at the Warriors game, at the Sorry, where is it? What's.Ivan [00:23:22]: Chase Center.Swyx [00:23:23]: Chase Center.Ivan [00:23:23]: Chase Center.Swyx [00:23:24]: I went. It was, it was very impressive. Obviously, you can, how to throw a conference, what did you learn? you put, you pulled together all these impressive names.Ivan [00:23:33]: What I.Swyx [00:23:34]: What were you looking for?Ivan [00:23:35]: My thesis behind the Compute Conference was let's bring together people that are building infrastructure for AI agents. Because when I think of what we're building, it is the agent is the primary user, what are the ergonomics and usage patterns of agents, and so we can do that. And what I found, this was a theory, it wasn't proven, is that we all have these problems, as I touched onto. And I was, as I was talking on stage, it was like we all have the same underlying infra problems, which is this spiky workloads, unpredictable workloads that we've never had before, in human, compute or human infrastructure. And it's, again, it's the same when I was talking to Parag or when I was talking.Swyx [00:24:20]: Lynn. Nikita.Ivan [00:24:21]: Lynn, Nikita. Lynn especially, I was talking to her the other day as well. Like the It is a very interesting type of problem to solve because I can touch on Cloudflare because there's a lot of like talk about that recently as to how they solve that, which is they have a bunch of geos, and basically, as users work in different places, and depending on your tier, they can move you around the geos. And so that how, that's how they get the higher utilization. But you can sort of predict these, and it's If it's something in You'll rarely get a spike that is 10 orders of magnitude. Like you'll get a like let's say one of your customers has some like an exponential curve. What is that to I'm using Cloudflare as an example. 10%, 20%, whatever it is. I don't, I don't have this data, I'm just assessing. It's surely not 10x, right? It's surely not something there. And so how do you go out and solve this problem? And we're all solving this in different ways. So we have.Swyx [00:25:11]: She also has the same thing.Ivan [00:25:12]: Yeah, I know specifically that like Neon had that issue as well. Like how are we solving these spiky loads and things like that ‘cause we talked about it. And so the interesting thing for me to actually internalize was, yes, everyone that's building for agents first is going through this, and we're all solving similar problems, which is quite.Swyx [00:25:28]: Let me let me double-click on this. Okay. So for example, Neon, I happen to know that they're very sort of S3 oriented, right? so they're just like fully bet on S3. And you get to benefit from S3's distribution and infrastructure. So I would imagine that Neon doesn't have to care, whereas Lynn maybe has to care a bit more because obviously she's doing GPU inference. And, for listeners, we did an episode with her, one and a half years ago. And you have to care. But like, right?Ivan [00:25:54]: Parag cares for sure, and Nikita.Swyx [00:25:58]: And Parag is C of, Parallel.Ivan [00:25:59]: Parallel, yeah.Swyx [00:26:00]: Former CTO of Twitter.Ivan [00:26:01]: Twitter, yeah.Swyx [00:26:02]: They are the search.Ivan [00:26:03]: Yeah, they're search, yeah.Swyx [00:26:03]: I You and I know but the listeners don't know.Ivan [00:26:08]: Yeah, we can put it down in the screen, and so ‘cause we, when we were talking.Swyx [00:26:11]: I'll put it up on the, on the screen.Ivan [00:26:12]: Yeah, right.Swyx [00:26:12]: People can look it up if they need.Ivan [00:26:14]: Look it up. And, yes, but they still have CPU and RAM, allocation that you have to have up and running. And so CPU and RAM, you have to allocate that and have that ready. And so there's basically two ways to do it. One is you either over-provision and you can handle the bursts, or two, you basically have, I don't know if this is a term, just-in-time compute, which is like as your load becomes, as your usage comes in, you can fire off requests for VMs or bare metals at other cloud providers and then get them up and running.Swyx [00:26:43]: This is if you go above 100%, right?Ivan [00:26:45]: Yeah, this is.Swyx [00:26:46]: Like your overflow.Ivan [00:26:46]: If your overflow, like spillage or whatever you do.Swyx [00:26:48]: You probably lose money on it, but it doesn't matter, right?Ivan [00:26:50]: It, not Well, you might, you might not That is a more cost-effective way to do it but it's a slower way to do it. Because basically what you have to do is you have to like queue your requests, spin up these just-in-time compute, get it all ready, provision it, and then get your workload there. And so if the time isn't important that much, that's fine, and you can do that. But if your customer, and especially for, let's say, the RL training runs, the reason why a lot of people come to us is because GPUs are more expensive than CPUs, right? So you want your GPU running at, what, 100% the entire time. And so when you're running runs on CPUs, when the when the CPU cycle is like down and spinning up the next one, you want that to be instantaneous so that your GPU doesn't go down, right? And if you then have to like go out and provision machines, you're essentially telling the GPU that it has to wait, and that's incurring our cost. So there's things that you have to try to solve for there.RL Workloads, Declarative Images, and Kubernetes ReplacementSwyx [00:27:43]: Yeah, let's talk about the different workload, right? You said that, what was it? A few months ago, you had zero RL workload and now it's 50%.Ivan [00:27:52]: It will be this one, 50%, yeah.Swyx [00:27:54]: Let's talk about how different it is, right? Like I imagine, for example, a lot less dynamic code generation of like arbitrary code. Like here, it's probably all the same code. You're just doing parallel runs or something, I don't know.Ivan [00:28:05]: Yeah. So you'll have multiple Depends on the like for each run, you'll have a snapshot. And they, for the most part, they actually do use our declarative image builder, which is like, “Oh, we, the agent wants these dependencies, these env vars.”Swyx [00:28:17]: These ones, yeah.Ivan [00:28:18]: Yeah, the declarative image builder, it.Swyx [00:28:20]: Which is a very modal like thing that they.Ivan [00:28:22]: Yeah. And so we build it on the fly and then we propagate that snapshot, and you can spin up as many sandboxes as you want against that snapshot. And then if you have to do changes, the model can, or like it could be also be automated. It's like, “Oh, now for the next run, we need to install these things or remove these things or whatever to get, a task done,” and then it goes off and runs that. So yes, that is something that it seems that they prefer. The number one reason I found, or should I say, let's take a step back. What we are competing against in that environment is essentially managed Kubernetes. So EKS, GKE, whatever. That is what the vast majority run on. And anyone that has tried Daytona versus GKE, EKS is like, “I'm never going back.” That has always been. There's a few reasons. One is the ergonomics. So if you have, if you're using Kubernetes to spin that up, you have to essentially manage the interface interactions with that. Daytona, although as a compute provider, it's more akin to a Twilio and Stripe from a consumption perspective than it is an AWS. Like you have an API, an SDK, it's quite like easy and seamless to get these things up and running, that's one. The other is the speed to which we spin up, which we mentioned earlier, which is much faster, and the scale to which we can go to. We haven't got into features, but an interesting feature is that it's very hard to OOM, or out of memory, our sandboxes, because we can dynamically on the fly.Swyx [00:29:48]: Resize.Ivan [00:29:49]: Resize, which is like impossible on almost any other thing. There are some technologies that enable you to do that, but it's like a very hard thing. And so we actually saw this when, the Terminal Revenge team is, brought us actually. So thank you, Alex and the team, that brought us into this whole space.Swyx [00:30:05]: It's just very rare that, a framework would just say, “Guys, just use Daytona.”Ivan [00:30:11]: Yeah, I think it says it somewhere. Yeah.Swyx [00:30:13]: Yeah. I was like, “What is this?”Ivan [00:30:15]: There's all, there's multiple there, but they also mention a few other places. and so Daytona specifically-We have, the, just jumping on themes here We, I don't know where it says Data Center.Swyx [00:30:27]: I, there.Ivan [00:30:27]: Doesn't matter.Swyx [00:30:28]: There's a very strong recommendation, which is, very unusual. Which is, it's.Ivan [00:30:33]: We do not pay them for this, just.Swyx [00:30:34]: I know, yeah. They just like you.Ivan [00:30:35]: Yeah, they like us. yeah, and also a thing, so, Data Center has multiple isolation sets underneath. The customer doesn't have to know what they are. But basically we have Docker, which is a container, that's hardened with Sysbox. So it's Docker's, isolation that is a security equivalent to a VM, but it's still a container. And that is the default, and they, especially in these training workloads, really like that as an interface to be able to use just a basic Docker container, and we enable Docker and Docker. Which for these RL runs, if you need to do a Docker compose or Kubernetes, you can spin up a K3S inside of these things, which unlocks a huge amount of workloads that you can do that you cannot do on other providers. So just on that part is much more interesting. And so we went that, through that. We showed them that we could do that, and they enjoyed that quite a bit. They being the general venture people.Swyx [00:31:28]: Those people, yeah.Ivan [00:31:29]: And Harbor people.Swyx [00:31:29]: Harbor people, do are they, are they a company yet?Ivan [00:31:33]: As far, I do not know.Customer Pull, Slack Connect, and the Computer Use BetSwyx [00:31:35]: Okay. All right. Yeah. It's like super obvious that like, there's a lot of excitement and success around these things, okay, so yeah, tell us more, right? Like, this is an exploding workload, Harbor adopted you, which helped speed things along. But what are you learning as this new workload comes online?Ivan [00:31:53]: There's a couple things that we learned, which we chat about in the beginning. We, and this has led our story, as we mentioned, we like talked to a lot of customers along the way, and we add more features and more tool sets as we talk to customers. And it's interesting that And I think it's that the ecosystem is so small and/or the models get smarter, where when we see one user come with a request, we know it goes on a roadmap if like three to five customers come with the same request in that week. It's like very bizarre. It happens so many times, which is.Swyx [00:32:27]: Because they're all friends.Ivan [00:32:28]: Sorry?Swyx [00:32:28]: They all, they're all friends. They're all in the same group chat.Ivan [00:32:30]: Yeah, probably, yeah. ‘Cause and they're like, “Oh, can you do this?” And I'm like, “Okay, this is interesting. We'll put it on a feature request.” And then the next one's like, “Oh, can you do this?” “Okay.” It's all the same, right? It's always the same. And so what we try to do, and I personally try to do, I try to be on as many call, quote-unquote “sales calls” I can. I'm in every Slack channel. We literally have about 1,000 Slack Connect channels, something like that. It's an interesting, there's so many interesting things you find out when you have all the Slack channels. You can also see where people, transfer between companies. You see leave Slack channel, enter Slack channel. It's an interesting thing. Also, just I digress, I feel that Slack Connect is literally LinkedIn what it should be. You have a list.Swyx [00:33:08]: LinkedIn charges you to, use your own connections, but Slack doesn't, right? Slack is like, do it for free. It's more lock-in. It's great.Ivan [00:33:15]: Yeah. It's amazing. Yeah. It's one of the reasons.Swyx [00:33:17]: You're gonna pay Slack for life.Ivan [00:33:18]: Exactly. You're there for life. So that's interesting. And so one of the things, the newer things we were talking about earlier is we made a big bet and put a lot of investment on computer use. that is not seen publicly the light of day. We haven't GA'd that yet, but we have.Swyx [00:33:32]: Is there a thing I can pull up?Ivan [00:33:33]: There is computer use there. It's right up a bit.Swyx [00:33:36]: Oh, yeah. Okay.Ivan [00:33:38]: What we have, what we talked about and what we've seen publicly is there's this theme now about, the human emulator where And Elon from XAI has talked about this publicly, and if you think about the models today, they're actually quite sophisticated and they can do a lot of work, but they still don't have access to all the tools. Like, I'm a strong believer that the most efficient way for an agent to work is essentially headless or through, terminal or whatnot. But if we, if we look at knowledge work in general, there's about 100 million knowledge workers in the US, about a billion in the world, and knowledge workers, and the salaries of them aggregate to 10 trillion in the US 50 trillion worldwide.Swyx [00:34:24]: Wow.Ivan [00:34:25]: Something like that. And if we look at, the five most important sectors of that, so like healthcare and government and financial services and whatnot, that's about 56% of that. So let's say it's about half of that. So in the US it's about 25 trillion, and most of them, most of that work is actually still locked into legacy apps inside of Windows, which is not going anywhere for a very long time. Like, people just won't invest in that. How much of it? our assumption is the following: if, in the RPA market, which is similar market, well, not the same 25% of, these white collar, workers', work is automated. If an agent is more sophisticated, can go through more runs, figure stuff out, let's say it's, 40%, right? And so if you take 40% of that, you get to essentially, $10 trillion a year.Swyx [00:35:17]: That's a TAM.Ivan [00:35:18]: That is a that is a TAM. So that's the TAM of the models, right? That's not our, essentially ours. But you get to that size, and to be able to do that, you essentially have to give agents these computers with the legacy. So computer use, either Mac or Windows or Linux. Linux we also obviously have and others have. But Windows specifically is something very new, and the only option right now is an EC2 with, Windows or on Azure. Both of them take anywhere from three to five minutes to spin up. We've created an actual sandbox, so it's a second instead of milliseconds, but you have, point in time snapshots, you have, forking, you have all the things that you have from a sandbox, but essentially enables you to hopefully unlock all this value. And so that's been our big push and bet, but we've sort of, kept our ear to the ground. What is sort of the next things in the market?RPA Returns: Why Agents Still Need ComputersSwyx [00:36:06]: Yeah, knowledge work, and building, and sort of RPA, the next wave of RPA. I got very excited about RPA kind of during COVID times. The UI path was IPO-ing. And it was, a very hot Isn't it, Eastern European?Ivan [00:36:20]: It is, Romanian.Swyx [00:36:21]: Romanian?Yeah, it might be the only Romanian, big unicorn okay, yeah. This I don't I don't, I don't have like a I think there's, I think there's a stage being set for the resurgence of RPA, ‘cause everyone understands that, yeah, no one wants to deal with these shitty apps and no one's gonna rewrite them. Like, you just have to do, a remote operation and programmatic operation of them.Ivan [00:36:45]: If you wanna unlock it, my own setup was basically the following. So I was doing a board deck recently, last month, whatever, and I'm like, “Okay, let's just, let's just do automated.” So, all our data's in, ClickHouse and PostHog and QuickBooks, where everyone else's is, and I'm basically, connected that all to, my Cloud code, like go off and go Cloud code whatever. Go off and, here's the integrations, go do that. It pulled out the first report, which was great. It connected to Brex and all these things, pulled it, which was great, and then I say, “Okay, now pull out this, and this,” and I kept getting, really well McKinsey-style design reports, but the data said partial data. all the missing data, partial data. Like, it can't access all the things, and I got so frustrated, and so I got, I got, my Mac Mini virtual sandbox with OpenClaw. I gave it its own account in our company, and then I went to all these services and created a read-only account, so literally like an intern in your company. And so I would say, “Now go and do this report,” and it would get the same, or like, “I can't via the MCP or the API or whatever. I can't get all the information.” I'm like, “Go log in.” And it will log into the website, then go in, export the data. It'll export the data and do the thing end to end. So even for things that have today APIs, not all of it is exposed, and I to get value, I get immense value right now, but it has to be a computer usage, unfortunately, and so I spend a bunch of tokens just on that, but I get the job done. And so if even a startup like ours, and using all the hottest tools, still needs a computer agent what hope does, Goldman have to have a headless, right?Swyx [00:38:22]: Yeah, what a - Why isn't Microsoft doing this?Ivan [00:38:27]: I'm pretty sure, Satya had a post yesterday.Swyx [00:38:29]: Oh, okay. I see.Ivan [00:38:29]: Which was like, “Every agent needs a computer.”Swyx [00:38:31]: I see, I see.Ivan [00:38:32]: So they have launched something recently.Swyx [00:38:34]: Yeah, they have Microsoft Power Automate, I'm sure, I'm sure, they're gonna have their version.macOS Sandboxes, Apple Constraints, and the Windows OpportunityIvan [00:38:39]: Version of that, yeah.Swyx [00:38:39]: You're gonna try to do yours, and it - I always know there's always demand for Mac, but I know it's, tricky to host, macOS sandboxes.Ivan [00:38:49]: We will have macOS sandboxes fairly soon. The problem with macOS, OS sandboxes is, I'm deep in this, I don't know how much interesting is.Swyx [00:38:55]: No, it's.Ivan [00:38:56]: MacOS has this problem.Swyx [00:38:57]: It's a licensing thing, right?Ivan [00:38:58]: Licensing thing. So one, you're allowed to run only two parallel VMs per machine, so that's one. Two, you can only license to a different user every 24 hours. So if you come in and theoretically, if I wanna charge you per second and I charge you one second, I have to have it idle for the rest of the day. I can't have anyone else doing that. So the pricing will be different in the sense that I will have to - we would have to charge for 24 hours, and that's not even, that's not even the most difficult thing. But the, thing above that is, from a security perspective, they enable you to do memory snapshot, pause, resume, but only on the same physical drive, physical machine. And so what you can do in, Windows world or Linux world is that I can move in the background, your snapshot from one to the other and manage load, right? Here, if you wanna do that, you essentially have to have your.Swyx [00:39:49]: Yeah, snapshots. Yeah.Ivan [00:39:50]: Your.Swyx [00:39:51]: It's like.Ivan [00:39:51]: Physical machine.Swyx [00:39:52]: You can't break it up.Ivan [00:39:53]: You can't, you can't move things around that, and all of that is, that part is, from a security standpoint, if it is written. Like, I understand the security aspect of that, but it disables you from doing these agentic, like really scalable agentic workloads.Swyx [00:40:08]: You need to do a vibe-coded, clean room implementation on macOS that you can then - That's like Clean OS or something. I don't know.Ivan [00:40:17]: So. We have.Swyx [00:40:18]: ‘cause like Linux was originally like a clean room rewrite of Unix.Ivan [00:40:21]: Okay. Yeah.Swyx [00:40:21]: Or something like that, right? Like same thing to macOS. Someone needs to do it.Ivan [00:40:25]: Someone will do that, and someone will have some long-running agents for a few days to figure this stuff out. But yeah. So definitely we - we're really close to offering something ‘cause people do want it, but the pricing will be different, and the feature set will be sort of stringent.Swyx [00:40:38]: Yeah, nobody's gonna use this. like, the labs, the labs will because they want to automate macOS.Ivan [00:40:42]: They have to do RL. They have to do RL again. But even if you The - So the point is with the RL part, if you, if you do RL on macOS, then the next iteration of the model comes out, it will be able to use these tools significantly. Then you actually need to run those, that somewhere. So you're gonna have to have that, later on. And from, if anyone at Apple is listening, I very much feel that they are shooting themselves in the foot of the scale of the revenue of compute or licensing they could get if they would just enable a concurrency model similar to what you can get on a Windows and a, and Linux.Swyx [00:41:17]: Yeah. Yeah. And I'm sure they've heard this before. They just don't care. Yeah, it's And maybe they will change their mind with the new CEO.Ivan [00:41:24]: Yeah. We'll see.Swyx [00:41:25]: We'll see.Ivan [00:41:25]: High hopes.Swyx [00:41:26]: High hopes.Ivan [00:41:26]: High hopes.Swyx [00:41:27]: Okay. But I, it's very clear the market opportunity is huge in Windows, and you can go for a long time on just Windows, but your customers are gonna want both. and I think, it is interesting to me that, this is the sort of God application of agents, right? Like, I don't It was - How big was OpenClaw for you guys? Like, was it, was there, a significant bump.OpenClaw, Agent Labs, and the B2B2C Sandbox MarketIvan [00:41:54]: Not for us because we.Swyx [00:41:54]: Because you already.Ivan [00:41:55]: We're kind of positioned differently. Whereas although it's completely PLG and we have individual developers that use it, most of the users that use Daytona are sort of a B2B2C. Sort of it's either B2B or B2B2C. So, in the researcher world, it's B2B, so you're selling to, labs and neo labs and things like that. But on the long-running agents, it's mostly, from a scale revenue perspective, it's mostly B2B2C, where you have a app layer agent that uses you at a big scale.Swyx [00:42:26]: Like a Manus. Yeah.Ivan [00:42:28]: Like a Manus Lovable type of thing.Swyx [00:42:31]: Yeah. I think that's the question of, well how, um-Uh, yeah, B2B to C is basically to me what I've been calling an agent lab, which is kind of like you're not in a model lab, but you're making a very good wrapper that is a platform that other people can sign up so they don't have to code those things. Yeah, it sound, it sounds like a much better market than the direct OpenClaw market.Ivan [00:42:56]: I've like - We I've done multiple things. So the CodeAnywhere's part of our career path R in the calendar, was very much an end user developer product. And so that is great. It You can get a lot of developer love, and I feel that we do as a company have a bunch of developer love. But it's a different type, where it's people building these things. Again, it's more akin to a Twilio because you don't really run - As a person, you wouldn't run Twilio. I don't know how many people remember. It was like ask your developer billboard and whatnot. And people really love Twilio, but they only used it inside of like, “Oh, I'm building this app or service for thing.” And so we're very much directly to that. And you also know that I used to work for a competitor for Twilio, so it's kind of ingrained, in my DNA.Swyx [00:43:35]: People don't know InfoBip is that big.Ivan [00:43:38]: Yeah, it's.Swyx [00:43:39]: Because.Ivan [00:43:40]: It's a billion euro.Swyx [00:43:40]: They're all American. They're like, “Whatever's in Europe doesn't matter to me.” But like it's the, it's the same size or bigger? Same size?Ivan [00:43:46]: It's about half the size.Swyx [00:43:47]: Half the size?Ivan [00:43:48]: Yeah, about half the size.Swyx [00:43:48]: It's like, yeah.Ivan [00:43:48]: Still huge. Multiple billions a year. Yes.Swyx [00:43:51]: That's crazy.Ivan [00:43:51]: Exactly, and so that - These are like really interesting and large revenue-generating, very sticky businesses. Whereas when you're selling to the - When your focus is the end developer, it is a very hard sell because they're very price sensitive, very price conscious, very around that. And there's very It's very hard to scale. Your cap is the number of people that are willing to spin up - First of all, wanna spin that up, and then spin up multiple of these. Whereas if you're in the enterprise one, like we know everyone's talking about like how many tokens they're spending, I'm spending. Like a lot of companies today are like, “If this is our company, spend as much as you can.” Like basically that is where we're going. And so if you think about that paradigm, where you're selling to companies that say, “Spend as much as you can to generate, productivity,” versus, “Oh, I'm a single person. I have this much budget, and I'm doing this thing because it's fun or it's helping me out or whatever.” Like it is a different, it's a different go-to-market, I think, strategy.MCP, CLIs, and Sandboxes as the Agent RuntimeSwyx [00:44:50]: Yeah, there's a lot of discussion. I'm just kind of going through like the mental list of things that are in your favor, which is, for example, MCP versus CLI. Like obviously you want CLI. It's been very good for you. I feel like it's maybe a drop in the bucket or maybe it's huge. I'm just checking whether it's like these are big trends.Ivan [00:45:10]: Those things you - work well in our favor, to your point just because every.Swyx [00:45:13]: They're kind of drop in the bucket, right?Ivan [00:45:15]: I think it's like sort of all the things come together. And so there's so many things that impact that. To your point, like OpenClaw wasn't huge for us, but like having the agent SDK, from Anthropic, so or Cloud Claude Code was very interesting. The reason why it was interesting is that a lot of, let's call them app I don't know what to call them, app layer agent companies, essentially they are like, “Oh, I can create this new app, this new agent. All I need, I just use Claude Code, and I throw it into a sandbox, and then I have my interface to the human to that.” And so that enabled so many more companies to actually offer this, and then they would pull on sandbox. So that was, that was interesting. And to your point, like MCP, versus the CLI, the MCP is an interface against an API, whereas the CLI is like you can actually go do things. Like this is it. The difference between integrations and actually running scripts or data or analysis against a thing. So being able to use a CLI very well enables the agent to do more things, and it's because that people will invoke a sandbox, they'll run it in the CLI, and but it'll do anal-analysis on that data and then give you an actual result versus just, pulling data from an API source.Swyx [00:46:29]: Yeah, it's a layer of indirection basically, it's the same thing as agentic search versus RAG, which where you're.Ivan [00:46:34]: Exactly, yeah.Swyx [00:46:34]: Just like you just win whenever people put more agents into their workflow. And so like it doesn't really matter, but I'm just kinda teasing out like what else have people heard about that like it's sort of, “Oh yeah, this is another sandbox use case. Oh yeah, that's another one.” Am I, am I missing any big ones?Ivan [00:46:51]: The thing, the thing that people, which is the computer use stuff, which I think is probably the most interesting one, is, and to your point, we've talked to so many people over the last year. It's like, “Oh, like why do you need a sandbox? Why do you need this? Why this?” And to your point, it's like, “Oh, I need sandbox for this. I need sandbox for that. I need sandbox-” It's like, “Oh, I need it for every single thing.” And so basically what I, what I - and it sounds like a broken record, it's like you use a laptop every single day, right? And you are n of one. It's just you. But now imagine how And by the way, the laptop, the computer PC market, the PC market is about equal to the cloud market in total. So it's about 150, 180 billion a year. Something like that. It's about roughly the three cloud hyperscalers is about equal to like Apple, HP, Lenovo, whatever, It's a little bit less, but it's sort of like that. And now imagine And that's just like, so how big is the addressable market? What, how many people are there in the world now? What's the last data?Swyx [00:47:45]: Let's call it eight billion.Ivan [00:47:46]: Eight billion. And so let's say you can have two computer, like you have one personal and one business, whatever. Like so it's double that, right? and so that's 16 billion, right? How many agents are gonna be running in two years, in 10 years, in 100 years? Like And for every single task, they will need one of these. And so how big is that? That market is essentially quote unquote “infinite”. You will get to the point, and Dylan Patel was at the conference talking about, from SemiAnalysis, that talks usually about GPUs, was also talking about how CPUs will now be a bottleneck because it will be the constraint. You won't be able to grow, or we won't be able to have enough of these because there won't be enough CPUs to basically do.Swyx [00:48:23]: Yeah. Well, I actually had a really good podcast with Doug Oliphant, who, which was his president at SemiAnalysis, where they've basically been like, yeah, it's been a GPU shortage first, but then it's cascaded down to memory and now to CPUs.Ivan [00:48:35]: CPU, yeah.Swyx [00:48:35]: It-What's next? So networking. So, networking actually has been in shortage for a while if you're looking at, just GPU networking. But, yeah, it's really crazy the amount of computer use that's going on, yeah, cool. I, other questions are, just the one very big part is the open sourceness which you didn't have to do, your competitors don't do, like it's not, a lot of people are worried about keeping their projects open source because some competitor can just slot fork it. I don't know if there's any reflections on just being an open source company.Open Source, Trust, and Enterprise ProcurementIvan [00:49:15]: Yeah. There's a bunch. So we the original product that we did was open source.Swyx [00:49:19]: Yeah. CodeAnywhere.Ivan [00:49:20]: So doing that was actually very good for us. There's basically a saying of, What's the saying? Like, companies that are, that are doing really well, measure themselves against, free cashflow, that are kinda okay, it's EBITDA, then, it's, it goes all the way down.Swyx [00:49:36]: The worst is like GitHub stars.Ivan [00:49:37]: GitHub stars. GitHub stars are the worst, yeah. So you go all the way down to GitHub stars. And so our original one was GitHub stars. That's what we talked about, we're at the point we're talking about revenue, so we're we've gone up the stack on that. And so we started.Swyx [00:49:47]: No, profit.Ivan [00:49:48]: Yeah. We haven't, we're, we'll get there. We'll get there. But basically at that point we did stars and GitHub and it was useful, and the original variation that we did, it we split the core into its own repo and it was Apache 2.0, so very, permissive. And then we basically would bundl

JetBrains is positioning itself as the last major independent AI coding-tool vendor in a market increasingly tied to hyperscalers and foundation model labs. Speaking at Google Cloud Next, JetBrains VP of business developmentMikhail Vink argued that competitors such as Microsoft Copilot, Anysphere Cursor, and Windsurfare all tied to either AI labs or cloud providers. By contrast, JetBrains says its independence allows customers to switch freely between models fromOpenAI,Anthropic, andGoogle Cloudwithout being locked into one ecosystem. That flexibility underpins JetBrains' broader AI strategy. Rather than building its own foundation model, the company is focusing on orchestration and governance through JetBrains Central, announced in March as a management layer for AI agents, usage controls, analytics, and consumption-based billing. Vink said the company's profitability, 16 million users, and 300,000 commercial customers from its long-running IDE business have allowed it to remain venture-free and model-neutral. JetBrains argues that as developers increasingly swap between AI models, neutrality may become more valuable than owning the models themselves. Learn more from The New Stack around the latest in AI coding-tools:  JetBrains ‘Agentic' AI Agent Helps Automate Coding Tasks JetBrains: AI agents are about to repeat the cloud ROI crisis  JetBrains names the debt AI agents leave behind Join our community of newsletter subscribers to stay on top of the news and at the top of your game. 

"Peut-être que notre plus-value aujourd'hui, c'est d'être des devs. Et devs, c'est pas que taper du code" Le D.E.V. de la semaine est Antonio Goncalves, Principal Software Engineer chez Microsoft et co-organisateur de Devoxx. Dans cet épisode, on plonge dans la complexification du métier avec l'essor de l'IA et des plateformes cloud comme Microsoft Foundry. Antonio raconte comment les développeurs doivent désormais arbitrer entre des milliers de modèles, tout en gérant les attentes métiers, la sécurité et le coût des tokens. Il partage son regard sur la transformation accélérée des pratiques, entre impact métier, outillage et nouveaux collègues&hellip agents IA compris ! Un échange sans filtre sur une profession qui doit jongler entre vitesse, expertise et humanité.Chapitrages00:00:55 : Introduction à l'IA et son impact00:01:51 : Présentation d'Antonio00:03:41 : Transition vers la génération de code00:04:37 : Intégration de l'IA dans les fonctionnalités00:07:27 : Maturité des clients face à l'IA00:09:53 : Complexité croissante dans le métier00:14:52 : Accélération des tâches et des commits00:16:04 : Évolution des méthodes de travail00:20:32 : La génération sacrifiée00:25:17 : Importance de l'apprentissage sans outils00:28:31 : L'IA comme calculatrice moderne00:33:26 : Comparaison avec les technologies établies00:39:39 : Simplification via les outils modernes00:49:02 : Innovations dans l'aviation et l'ingénierie00:54:58 : Réflexion sur l'évolution du métier00:59:25 : Intégration des tokens dans le travail quotidien01:03:13 : Recommandation de ressources01:04:00 : Conclusion et perspectives d'avenir Liens évoqués pendant l'émission Cours Anthropic sur Skilljar

Na výletnej lodi MV Hondius sa objavilo podozrenie na zriedkavý prenos hantavírusu z človeka na človeka, čo vyvolalo obavy aj množstvo dezinformácií na sociálnych sieťach. Aký nebezpečný je hantavírus v skutočnosti, čo o ňom vieme a prečo odborníci zatiaľ nehovoria o scenári podobnom covidu? Aj o tom diskutovala Veronika Jursová Prachárová so šéfkou Demagóg.sk Veronikou Frankovskou a virológom Borisom Klempom, vedcom pôsobiacim v SAV a na Prírodovedeckej fakulte Univerzity Komenského.V úvodnej rubrike Dezinformačný radar Veronika Frankovská upozornila, že pri príležitosti druhého výročia atentátu na premiéra Roberta Fica sa opäť šíria obvinenia, že útočník bol nejakým spôsobom prepojený na stranu Demokrati. Objavujú sa aj autoritatívne formulované tvrdenia, že takéto prepojenie potvrdil súd. „To však nie je pravda. Naopak, rozsudok Špecializovaného trestného súdu aj rozsudok Najvyššieho súdu potvrdili, že Cintula konal sám, a nespomínali žiadne takéto prepojenia na žiadnych iných aktérov,“ uviedla Frankovská.V kontexte hantavírusu Frankovská upozornila, že na sociálnych sieťach sa objavujú tvrdenia, podľa ktorých hantavírus nie je taký nebezpečný a ide o nástroj, aby opäť vznikla svetová pandémia a niekto nás mohol znovu kontrolovať. „Táto obava, že môže opäť vzniknúť nejaká pandémia, je určite pochopiteľná. Čo už však nie je pravdivé, sú ďalšie spôsoby, akými sa to snažia dokazovať – napríklad tvrdenia, že vírus v skutočnosti unikol z laboratória, alebo že už existujú testovacie centrá vo Švajčiarsku na hantavírus,“ povedala Frankovská. Doplnila, že v Európe ani v Amerike nemáme schválené vakcíny na hantavírus ani takéto testovacie centrá.V druhej časti podcastu vedec Boris Klempa vysvetlil, že hantavírusy sú pomerne veľká skupina vírusov, v rámci ktorej rozlišujeme veľa konkrétnych vírusových druhov. Ide podľa neho typicky o vírusy prenášané hlodavcami. Len niektoré z týchto vírusov, ak sa náhodne dostanú do človeka, vedia spôsobiť závažné ľudské ochorenia.„Pravdepodobnosť, že by hantavírus spôsobil pandémiu, je veľmi nízka. Vo všeobecnosti sa hantavírusy považujú za také, že sa vôbec neprenášajú z človeka na človeka. To sa týka všetkých, ktoré sa nachádzajú v Európe a v Ázii. V podstate jediný hantavírus, pri ktorom bolo jednoznačne zdokumentované, že sa môže prenášať z človeka na človeka, je juhoamerický Andes vírus. A to je presne ten, čo sa zhodou nešťastných náhod ocitol práve na tej výletnej lodi,“ vysvetlil Klempa.Podľa Klempu je Andes vírus jediným hantavírusom, pri ktorom dochádza k šíreniu z človeka na človeka. Zdôraznil však, že aj v tomto prípade je šírenie veľmi málo účinné a vyžaduje si pomerne blízky a dlhodobý kontakt. „Riziko, že by došlo k nekontrolovateľnému šíreniu, je vlastne veľmi nízke,“ dodal.Z doteraz zdokumentovaných prípadov, ktoré boli doposiaľ len v Argentíne a Čile, podľa Klempu jednoznačne vyplýva, že najväčším rizikovým faktorom je zdieľanie spoločnej domácnosti alebo spoločného lôžka.

A Aliança da Redenção (parte 3) - Gabriel Manzoni by IDE

Topics covered in this episode: Using Django Tasks in production Co-authored with Claude? PyPI packages are increasing rapidly httpx2 Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 11am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: Using Django Tasks in production Tim Schilling shares how the Djangonaut Space website has been using Django's new tasks framework and some of the info missing from the official Django docs. Tasks require a third party package, django-tasks-db to actually run the tasks. Article walks through all changes necessary to get an email process running to notify admins of new testimonials. Cool simple example. With the db backend, you can monitor progress of tasks in the admin, to see which tasks are scheduled, completed, or have errors. Some wishes for the community to implement new tutorial in the Django docs Django Debug toolbar panel for tasks test/mock backend Great title for wish list: Thinks I'd like to see, but I'm too lazy to implement myself. Michael #2: Co-authored with Claude? Via Nik T. We don't put “executed on macOS”, “edited with PyCharm”, etc. in our commits. Why Claude? Seems like a growth hack to me, that I don't really care to participate in. Some projects that have formalized their thoughts on this: The Generative AI Policy Landscape in Open Source Adjust to turn off in ~/.claude/settings.json see the docs. { "attribution": { "commit": "", "pr": "" } } Brian #3: PyPI packages are increasing rapidly Artem Golubin There's been an increase of published packages per week on PyPI A pretty big increase in the last handful of months. 30% increase since 2025, clearly due to AI Artem is building hexora, a malicious Python code detector. Cool package too, it can: Audit project dependencies to catch potential supply-chain attacks Detect malicious scripts found on platforms like Pastebin, GitHub, or open directories Analyze IoC files from past security incidents Audit new packages uploaded to PyPi. Artem is using hexora to analyze recently published pypi packages and many are obviously vibecoded and trigger false positives for abuses of eval, exec, and subprocess Side note: I don't think that's necessarily a false positive. Not malicious, but maybe a stupid-code-detector? Lots are LLM related, Lots have bots contributing code Publishing rate is crazy, dozens to hundreds of published versions in a day is a bug, not a feature Brian's proposal, PyPI should limit releases per day for any package to something a sane human would do, even if they make a mistake on a release, to maybe like 2-3, definitely under 10, in a day. And if the repo has obvious agent contributors listed, maybe lower to the limit to 1-2 a day? Honestly, “move fast and break things” doesn't apply to breaking the commons. Michael #4: httpx2 More on the httpx, httpxyz, etc changes: Pydantic people started their own fork, httpx2. Michiel says “while we think httpxyz was definitely needed, we welcome httpx2 and think it should be the ‘blessed' fork.” Kludex, who is among other things maintainer of Starlette, was considering a fork As it stands, httpx2 is lacking the performance improvements they added to httpxyz. But it will not be long before they will add those, too. Also they already made some smart decisions: they are switching from certifi to truststore they are switching to compression.zstd on Python 3.14+, enabling zstd compression by default they merged httpcore and vendored it in their repository Discussion on Hacker News Extras Brian: The Four Horsemen of the LLM Apocalypse - Anarcat Django/JetBrains 2026 developer survey is open Pyrefly 1.0 : “meaning we are confident that Pyrefly is ready for production use.” Michael: Just about ready to release Python Web Security: OWASP Top 10 with Agentic AI course. Be sure to be on the courses newsletter to get notified. Joke: Proud Parents

Cum ne afectează smartphone-urile și social media starea de bine, sănătatea mintală și relațiile? Începem astăzi seria Digital Wellbeing, 6 episoade dedicate acestei teme, susținută de Vodafone.În acest episod introductiv al seriei, Paul Olteanu și Luciana Baicea urmăresc viteza extraordinară de adoptare a smartphone-urilor și rețelelor sociale din 2007 încoace, ne arată ce spun datele globale și europene despre sănătatea mintală a tinerilor după 2010 și explică de ce sistemul nostru nervos nu e proiectat pentru felul în care folosim azi tehnologia.Discuția se sprijină pe cercetarea psihologului Jonathan Haidt (New York University), autorul cărții The Anxious Generation (O generație în pericol), pe studiul ISBRD 2026 realizat de Fundația Vodafone împreună cu Save the Children și Ipsos, plus date de la Eurostat, UNICEF și Organizația Mondială a Sănătății.În acest episod discutăm despre:Adopția smartphone-ului și a social media și de ce perioada 2010–2012 e un punct de cotiturăDatele despre anxietate, depresie, somn și singurătate la adolescențiDe ce designul rețelelor sociale activează aceleași circuite ca jocurile de norocCele patru riscuri fundamentale: atenție fragmentată, dependență, izolare și afectarea somnuluiResurse menționate în conversație:Cartea O generație în pericol (The Anxious Generation) de Jonathan HaidtCartea Dopamine Nation de Anna LembkeStudiul ISBRD 2026 — Fundația Vodafone, Save the Children, Ipsos - ⁠Copilărie Conectată: starea de bine și reziliența digitală a copiilor și tinerilor din Europa⁠Acest episod face parte din seria Digital Wellbeing, susținută de Vodafone și de Fundația Vodafone."(00:00) Intro""(02:30) Structura seriei și conținutul din cele 6 episoade ale ei""(06:46) Geneza: lansarea iPhone în 2007 și adopție globală smartphone""(10:07) De la 5% pe rețele la 85%: adopția social media""(13:04) De la camera frontală la TikTok: nașterea culturii performative""(16:45) Erving Goffman: 'instagramabil' și viața ca performanță socială""(20:50) Date Jonathan Haidt: anxietate +139% și depresie +145% după 2010""(25:41) Argumentul substituirii: restrângerea timpului petrecut cu prietenii""(29:47) Somn sub 7 ore la adolescenți: ce arată cercetarea""(30:54) 'Viața mea se simte fără sens' — colapsul speranței la tineri""(34:01) Studiul ISBRD 2026: bunăstarea digitală a tinerilor europeni""(37:12) 97% folosesc internetul zilnic — dar pentru ce anume?""(40:49) Pentru ce a evoluat sistemul nervos vs. lumea de astăzi""(44:30) Coldplay și ecranul ca fereastră: a trăi vs. a filma momentul""(47:38) Ritmurile biologice și joaca liberă (Gordon Neufeld)""(49:40) Recompensa variabilă și cele 31 de studii interne Meta""(53:07) De ce 'busy' a devenit medalie de onoare și filme pentru double screen""(57:04) Conexiune, autonomie și sens: iluzia competenței prin metrici""(01:02:30) Identitate, ierarhii și comparație: oglinda lui Dunbar vs. milioane de străini""(01:06:34) Întrupare și sincronicitate: ce se pierde în texte și emoji""(01:09:50) Dimensiunea audienței și stabilitatea comunității după Haidt""(01:14:05) Dauna 1 — Fragmentarea atenției: impactul notificării necitite""(01:20:53) Dauna 2 — Dependența și recompensa variabilă""(01:23:40) Anna Lembke și cele patru simptome ale sevrajului""(01:25:39) Dauna 3 — Izolarea socială și conflictul prin mesaje""(01:29:19) Dauna 4 — Lumina albastră, conținutul emoțional și 'revenge scrolling'""(01:31:36) Ce urmează în episoadele 2–6 ale seriei"

In this episode: An IDE written in Rust hits 1.0; more vulnerabilities, this time in TanStack and Next.js; and the AI layoffs continue—we'll discuss whether you should be worried.Timestamps:0:46 - Alternative editor Zed hits 1.010:48 - AI layoffs24:12 - TanStack's CI pipeline was compromised30:01 - Another Next.js vulnerability31:46 - Tailwind 4.3 adds new scrollbar utilities35:03 - Fire Starter: The new install element41:22 - What's making us happyNews:Paige - Alternative editor Zed hits 1.0Jack - Not even TanStack is safe from npm hacks and another Next.js vulnerabilityTJ - Cloudflare lays off 1,100 employees & Cisco lays off 4,000 employeesLightning News: Tailwind 4.3 adds new scrollbar utilitiesFire Starter:What Makes Us Happy this Week:Paige - The Porsche Track ExperienceJack - Porch planets projectTJ - Chilipad mattress topperThanks as always to our sponsor, the Blue Collar Coder channel on YouTube. You can join us in our Discord channel, explore our website and reach us via email, or talk to us on X, Bluesky, or YouTube.Front-end Fire websiteBlue Collar Coder on YouTubeBlue Collar Coder on DiscordReach out via emailTweet at us on X @front_end_fireFollow us on Bluesky @front-end-fire.comSubscribe to our YouTube channel @Front-EndFirePodcast

Pour l'épisode #340 je recevais Nicolas Guillot. On en débrief avec Guillaume.

#350: The bottleneck used to be writing the code. Now it is feeding the agent enough context to write the right code. That is Patrick Debois' argument, and given that Patrick coined the term DevOps, it is worth paying attention when he says the discipline is shifting again. The model does not matter. The IDE does not matter. What matters is whether your team can capture the way you actually work and hand it to an agent that does not know any of it. The promise was that AI would let us ship without writing specs. The reality is the opposite. If you want decent output, you need richer specs, more docs, and a way to feed the agent what is unique about your team and your codebase. Viktor admits he stopped writing specs himself. He talks to the agent until he is satisfied, then says write it down. The work did not go away. It moved. A second agent that validates your work tends to take the original spec too seriously and miss what is not there. The interesting validation is not whether the code matches the spec. It is whether the spec matches reality. Patrick's response is harness engineering -- combining verifier agents with deterministic tooling like linters and tests, and mining conversation logs for the moments a user says this is wrong so the missing context can be saved and reused. Memory, hooks, skills, registries -- all just delivery mechanisms for the same underlying thing. Patrick's number one piece of advice if you are starting today is brutal in its simplicity. When the agent does the wrong thing, write it down in your AGENTS.md or claude.md. Do not just re-prompt and move on. Build the context file. That is the new job. Code moved to context. Context, eventually, moves to knowledge -- the way your organization actually works, captured somewhere an agent can use it. Whoever owns that layer wins. The model does not.   Patrick's contact information: LinkedIn: https://www.linkedin.com/in/patrickdebois/ X: https://x.com/patrickdebois   YouTube channel: https://youtube.com/devopsparadox   Review the podcast on Apple Podcasts: https://www.devopsparadox.com/review-podcast/   Slack: https://www.devopsparadox.com/slack/   Connect with us at: https://www.devopsparadox.com/contact/

"Notre métier est profondément ancré dans une culture de transmission, de personne à personne." Le D.E.V. de la semaine est Julien Landuré, CTO chez TechTown. Organisateur engagé de conférences comme le DevFest Nantes, il nous explique pourquoi la culture tech adore se retrouver en chair et en os, même à l'heure du replay permanent. Julien partage son regard de bâtisseur d'agora moderne, parle modèle économique et inclusivité, et insiste sur l'importance du collectif. On découvre les coulisses de la création d'événements tech et les moteurs humains derrière la scène. Un épisode qui rappelle que la conférence n'est pas une option, mais un pilier du métier.Chapitrages00:01:00 : Introduction à la culture de la conférence00:01:34 : L'importance des rencontres dans la tech00:05:10 : Les opportunités offertes par les événements00:07:21 : L'évolution des meet-ups à Nantes00:07:55 : L'expérience des premiers événements00:10:17 : De l'idée à la réalisation du DevFest00:13:53 : Les défis de l'organisation d'événements00:18:44 : La sélection des speakers00:24:13 : Le rôle des participants dans les conférences00:26:40 : Le modèle économique des événements00:31:32 : Choisir ses sponsors avec soin00:33:59 : Les bénéfices d'organiser des conférences00:39:23 : Le networking : un aspect essentiel00:45:22 : L'impact de l'IA sur l'apprentissage00:48:47 : La place pour de nouvelles conférences00:50:01 : Conseils et recommandations de conférences Liens évoqués pendant l'émission Conference Hall (pour créer son talk et le soumettre partout)AAIF Agentique AI Foundation

What if your database worked more like Git? Every change captured as an immutable event you can replay, instead of a single mutating row that quietly forgets its own history. That's event sourcing, and Chris May is back on Talk Python, fresh off our Datastar panel, to walk us through what it actually looks like in Python. We'll cover the core patterns, the libraries to reach for, when not to use it, and why event sourcing turns out to be a surprisingly good fit for AI-assisted coding. Episode sponsors Sentry Error Monitoring, Code talkpython26 Temporal Talk Python Courses Links from the show Guest Chris May: everydaysuperpowers.dev Intro to event sourcing e-book: everydaysuperpowers.gumroad.com Domain-Driven Design: The Power of CQRS and Event Sourcing: How CQRS/ES Redefine Building Scalable System: ricofritzsche.me DDD: www.amazon.com Understanding Eventsourcing (Martin Dilger): www.amazon.com Event Sourcing Explained using Football Video: www.youtube.com Why I finally embraced event sourcing and why you should too article: everydaysuperpowers.dev valkey: valkey.io diskcache: talkpython.fm eventsourcing package: github.com eventsourcing docs: eventsourcing.readthedocs.io John Bywater: github.com Datastar: data-star.dev Microconf: microconf.com Event Modeling & Event Sourcing Podcast: podcast.eventmodeling.org Python Package Guides for AI Agents: github.com Iodine tablets AI joke: x.com KurrentDb: www.kurrent.io Watch this episode on YouTube: youtube.com Episode #548 deep-dive: talkpython.fm/548 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Topics covered in this episode: httpxyz one month in Learn concurrency - a deep dive into multithreading with Python pip 26.1 - lockfiles and dependency cooldowns Python 3.15 sentinal values from PEP 661 Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 11am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: httpxyz one month in First version of httpxyz contained just the fixes to get zstd working, and the fixes to get the test suite running on python 3.14, some ‘housekeeping' changes related to the renaming End of March: a compatibility shim that allows you to use httpxyz even with third-party packages that import httpx themselves, as long as you import httpxyz first. Importing httpxyz automatically registers it under the httpx name in sys.modules , see https://httpxyz.org/httpx-compatibility/ Fixed a WHOLE bunch of performance related issues by forking httpcore Brian #2: Learn concurrency - a deep dive into multithreading with Python Nikos Vaggalis “Whenever you are trying to speed up code using multiple cores, always ask yourself: “Do these threads need to talk to each other right now?” If the answer is yes, it will be slow. The best parallel code splits a big job into completely isolated chunks, processes them separately, and merges the results at the finish line.” Good overview of thread concurrency with Python and how that's been improved dramatically with free-threaded Python Defines lots of terms you come across, including “embarrassingly parallel multithreading” There's a counter example that's nice Start with a shared resource, a counter, and multiple threads updating it Attempt to fix with threading.Lock(), which fixes it, but slows things down Good explanation of why Proper fix with concurrent.futures and separating the work of different threads so that they can be independent and their results can be combined when they're all finished. Michael #3: pip 26.1 - lockfiles and dependency cooldowns Python 3.9 is no longer supported Experimental: installing from pylock files Dependency cooldowns (see my post about this) Lifting several 2020 resolver limitations Brian #4: Python 3.15 sentinal values from PEP 661 MISSING = sentinel("MISSING") def next_value(default: int | MISSING = MISSING): ... if default is MISSING: ... Take a name str as a constructor parameter Intended to be compared with is operator, similar to None Sentinal objects can be used as a type, also similar to None and can be combined with other types with |. Unlike None, sentinal values are truthy. (Elipses ... are also truthy) This seems like a strange choice. but I guess it must have made sense to someone. It does force you to use is instead of depending on False-ness, so I guess it'll make code using sentinels more readable. Interesting that the PEP was started in 2021, and we're finally getting it this year. Extras Brian: Before GitHub - Armin Ronacher tenacity - cross-platform multi-track audio editor/recorder learned about it from Armin's article Joke: Joke option Make it myself Seems similar to what people think about software now Links httpxyz one month in httpxyz.org/httpx-compatibility Learn concurrency - a deep dive into multithreading with Python pip 26.1 - lockfiles and dependency cooldowns my post about this Python 3.15 sentinal values from PEP 661 Before GitHub tenacity Make it myself

Dnes sa začína súdny proces v kauze Očistec. Ide o kauzu obrovských rozmerov, kde sú pre trestné činy založenia zločineckej skupiny, korupcie či zneužívania právomoci verejného činiteľa obžalovaní aj podpredseda parlamentu za Smer Tibor Gašpar, jeho príbuzný nitriansky oligarcha Norbert Bödör, bývalý špeciálny prokurátor Dušan Kováčik, či bývalé vedenie NAKA za tretej vlády Roberta Fica.Ako vyzeralo vyšetrovanie o aké výpovede a dôkazy sú spísané v 181 stranovej obžalobe? Na čom stavia svoju obranu obhajoba? Ako s tým súvisia aktuálne vyšetrovania Úradu inšpekčnej služby voči bývalým vyšetrovateľom? A ako môže celý súdny proces ovplyvniť najnovšia novela trestného zákona ministra Suska? Braňo Závodský sa rozprával s Xéniou Makarovou z Nadácie Zastavme korupciu.

When OpenAI trained GPT-3, they didn't roll their own orchestration layer. They used Ray, an open source Python framework born out of the same Berkeley research lab lineage that gave us Apache Spark. And here's the twist: Ray was originally built for reinforcement learning research, then quietly faded as RL hit a wall. Until ChatGPT showed up. Suddenly reinforcement learning was back, as the post-training step that turns a raw language model into something genuinely useful. Edward Oakes and Richard Liaw, two founding engineers behind Ray and Anyscale, join me on Talk Python to tell that story. We'll trace Ray from its RISE Lab origins at UC Berkeley to powering some of the largest training runs in the world. We'll talk about what Ray actually is, a distributed execution engine for AI workloads, and how a few lines of Python become work running across hundreds of GPUs. We'll cover Ray Data for multimodal pipelines, the dashboard, the VS Code remote debugger, KubRay for Kubernetes, and where Ray fits alongside Dask, multiprocessing, and asyncio. If you've ever stared at a single-machine Python script and thought, "there has to be a better way to scale this", this one's for you Episode sponsors Sentry Error Monitoring, Code talkpython26 AgentField AI Talk Python Courses Links from the show Guests Richard Liaw: github.com Edward Oakes: github.com Ray: www.ray.io Example code (we used for walk-through): docs.ray.io Getting Started with Ray: docs.ray.io Ray Libraries: docs.ray.io kuberay: github.com Watch this episode on YouTube: youtube.com Episode #547 deep-dive: talkpython.fm/547 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Enrique Ibarra, CIO and Head of Business Transformation at GNP, Mexico's largest insurance company, walks through an enterprise-scale pilot of autonomous software development involving roughly 1,000 internal and external developers. The episode examines how agentic AI changes developers' roles from creators to editors and orchestrators.In CXOTalk episode 918, Ibarra explains why AI co-pilots alone were insufficient to modernize a 20-year-old mainframe system, how GNP evaluated the Blitzy autonomous development platform across four real-world use cases, and how developer roles are shifting from creators to editors and orchestrators. The episode covers legacy modernization, enterprise AI adoption, change management, measurable results, and the two-year roadmap to retool the full engineering organization.YOU'LL DISCOVER✅ The CIO's phased human-in-the-loop playbook: target high-effort, low-risk friction points first (documentation, test suites, version upgrades)✅ Measured outcomes: 5 to 10X engineering velocity, near-100% autonomous completion on language upgrades, roughly 80% on frontend modernization✅ Why GNP's 20-year-old mainframe system forced a modernization decision tied to cost and the coming COBOL talent shortage✅ How the pilot was structured across four use cases: Java 8 to Java 21 migration, Angular frontend upgrade, new feature build, and security vulnerability remediation✅ Why autonomous platforms differ from co-pilots, and when to use each (Blitzy for heavy lifting, IDE-based co-pilots for the final 20%)✅ How to encode technical, security, and architectural guidelines as prompt inputs rather than post-hoc review✅ The change management approach that converted skeptical developers into active users within weeks✅ Strategic payoff: shipping new insurance products in weeks rather than months, and shifting IT from maintaining the business to dictating market paceTIMESTAMPS0:00 Introduction and headline results0:39 Why GNP needed to modernize a 20-year-old mainframe system1:15 From coding co-pilots to an autonomous platform2:36 Designing the four-use-case pilot4:26 Autonomous platforms versus vibe coding5:49 What autonomous development means in practice7:24 Encoding security and governance as prompt inputs8:24 Results: velocity, autonomy rates, and the final 20%10:16 How developer roles and daily work change11:19 Managing developer skepticism and change resistance12:25 Advice for CIOs: the phased human-in-the-loop playbook13:34 Strategic business benefits and first-to-market product launches14:58 Rolling out across seven teams and a two-year horizon16:34 Final advice for engineering leaders getting started

Topics covered in this episode: profiling-explorer Reverting the incremental GC in Python 3.14 and 3.15 VSCode AI Co-author defaults to on, then off django freeze Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 11am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: profiling-explorer Adam Johnson And intro post Python: introducing profiling-explorer “profiling-explorer is a tool for exploring profiling data from Python's built-in profilers, which are stored in pstats files. ” Features Dark mode Click the calls, internal ms, or cumulative ms column headers to sort by that column. Use the search box to filter by filename or function name. Hover by a filename + line number pair to reveal the copy button, which copies the location to your clipboard for faster opening. Click the callers or callees links on the right of a row (not pictured above) to see the callers or callees of that function. Michael #2: Reverting the incremental GC in Python 3.14 and 3.15 Python 3.14 shipped with a new incremental garbage collector, but production reports of severe memory pressure (Neil Schemenauer measured up to 5× peak RSS on pathological cyclic workloads) have pushed the core team and Steering Council to revert it in both 3.14 and 3.15 - returning to the 3.13-era generational GC. This is the second time the inc GC has been pulled back: it was also reverted right before 3.13.0 final, and it shipped in 3.14 without going through the PEP process. The tradeoff is real: Neil's benchmarks showed max GC pause times of 1.3ms with inc GC versus 26ms with the generational one - great for latency-sensitive apps, terrible for memory-constrained ones. Release manager Hugo van Kemenade will ship 3.14.5 early with the revert, and Gregory Smith floated the idea of a 3.14.5rc1 - the first patch-release RC since 3.9.2 back in 2021. Tim Peters spent the thread doing live forensics on Windows, running a toy deque program that should cap at 1GB and watching it balloon to 15.6GB on a 16GB machine - and discovered the gen0 collector effectively never fires under the new scheme. Tim's bigger meta-point: CPython has a chronic shortage of real-world GC benchmarks, pyperformance has "basically no interesting" cyclic workloads, and users almost never share real data - so core devs keep flying blind on changes like this. Django maintainer Adam Johnson published a blog post mid-thread documenting a real memory "leak" in Django's migration system caused by inc GC, with a manual gc.collect() workaround - the listener-facing receipt that this wasn't just theoretical. If the inc GC comes back for 3.16, it'll go through a proper PEP, and the discussion is already shifting toward keeping both collectors available via a startup flag - which Neil and Sergey Miryanov have both prototyped. Brian #3: VSCode AI Co-author defaults to on, then off VSCode merges Enabling ai co author by default - 3 week ago Ton's of “why would you do this” and related comments VSCode merges Change default for git.addAICoAuthor to off - yesterday Take-away, don't rely on default, set addAICoAuthor to off yourself Michael #4: django freeze Convert your dynamic django site to a static one with one line of code. Just run python manage.py generate_static_site :) Features Generate the static version of your Django site, optionally compressed .zip file Generate/download the static site using urls (only superuser and staff) Follow sitemap.xml urls Follow internal links founded in each page Follow redirects Report invalid/broken urls Selectively include/exclude media and static files Custom base url (very useful if the static site will run in a specific folder different by the document-root) Convert urls to relative urls (very useful if the static site will run offline or in an unknown folder different by the document-root) Prevent local directory index Extras Brian: Thinking Less, Trusting More: GenAI's Impacts on Students' Cognitive Habits Michael: Vercel breached, employee to blame Introducing the new Talk Python web player GitHub uptime (a couple of views 1, 2) Joke: Friends in tech

We get real about what AI search changes and what it does not, then map SEO back to fundamentals like attribution, buyer intent, and revenue. We also share how agency teams can use agent workflows and governance to move faster without turning the business into chaos. • Matt's return, agency ownership changes, and why the timing matters • Cameron's path from engineering to SEO through referrals and Google Business Profile wins • AI search as a conversation starter with CEOs while fundamentals stay critical • Why brand traffic and last-click attribution mislead decision makers • Cutting low-value traffic through pruning to drive more calls and leads • Agent harness basics using folders, instructions, APIs, and automation • Getting teams into IDE workflows, avoiding chat-only memory limits, and protecting .env keys • Data privacy for regulated industries, self-hosted models, and AI governance policies Guest Contact Information: Website: www.bidviewmarketing.comLinkedIn: www.linkedin.com/cameron-libuttiMore from EWR and Matthew:Leave us a review wherever you listen: Spotify, Apple Podcasts, or Amazon PodcastFree SEO Consultation: www.ewrdigital.com/discovery-callWith over 5 million downloads, The Best SEO Podcast has been the go-to show for digital marketers, business owners, and entrepreneurs wanting real-world strategies to grow online. Now, host Matthew Bertram — creator of the LLM Visibility Stack™, and Lead Strategist at EWR Digital — takes the conversation beyond traditional SEO into the AI era of discoverability. Each week, Matthew dives into the tactics, frameworks, and insights that matter most in a world where search engines, large language models, and answer engines are reshaping how people find, trust, and choose businesses. From SEO and AI-driven marketing to executive-level growth strategy, you'll hear expert interviews, deep-dive discussions, and actionable strategies to help you stay ahead of the curve. Find more episodes here: youtube.com/@BestSEOPodcastbestseopodcast.combestseopodcast.buzzsprout.comFollow us on:Facebook: @bestseopodcastInstagram: @thebestseopodcastTiktok: @bestseopodcastLinkedIn: @bestseopodcastConnect With Matthew Bertram: Website: www.matthewbertram.comInstagram: @matt_bertram_liveLinkedIn: @mattbertramlivePowered by: ewrdigital.comSupport the show

The cloud is convenient until it isn't. You upload your photos, sync your contacts, click through the cookie banners. Then prices go up again or you read about a family that lost their entire Google account over a medical photo sent to a doctor. At some point, the question shifts from "why would I run this myself?" to "why aren't I?" My guest this week is Alex Kretzschmar, head of DevRel at Tailscale, longtime host of the Self-Hosted podcast, and co-founder of Linuxserver.io. We cover what self-hosting really means in 2026, the apps worth running yourself like Immich and Home Assistant, why Docker Compose ties it all together, and how Tailscale lets you reach any of it from anywhere, without opening a single port. If you've been thinking about pulling your digital life back behind your own walls, this is your roadmap. Episode sponsors Temporal Talk Python Courses Links from the show Guest Alex Kretzschmar: alex.ktz.me Bitflip podcast: bitflip.show Self-Hosted podcast (Alex's previous show): selfhosted.show Perfect Media Server: perfectmediaserver.com KTZ Systems on YouTube: youtube.com/@ktzsystems Linuxserver.io (co-founded by Alex): linuxserver.io "How Tailscale Works" blog post: tailscale.com/blog/how-tailscale-works https://tailscale.com/: tailscale.com Self-hosted apps discussed Awesome Self-Hosted (GitHub list): github.com Immich (Google Photos alternative): immich.app Home Assistant: home-assistant.io Open Home Foundation: openhomefoundation.org Plausible Analytics: plausible.io Umami Analytics: umami.is Python integration for umami: pypi.org Pi-hole: pi-hole.net AdGuard Home: adguard.com NextDNS: nextdns.io Coolify: coolify.io Docker + ufw: docs.docker.com Storage, backup & filesystem OpenZFS: openzfs.org ZFS.rent (offsite ZFS replication): zfs.rent Backblaze: backblaze.com Hetzner Storage Box: hetzner.com DigitalOcean: digitalocean.com Secrets management mentioned OpenBao (open-source Vault fork): openbao.org HashiCorp Vault: hashicorp.com Bitwarden: bitwarden.com 1Password: 1password.com Hardware mentioned Proxmox VE: proxmox.com Minisforum MS01: minisforum.com Zima Board / Zima OS: zimaspace.com Other references Cory Doctorow on "enshittification" (Cory's blog where he coined the term): pluralistic.net Linus Tech Tips' WAN Show (Linus mentioned NAS-building going mainstream): linustechtips.com Watch this episode on YouTube: youtube.com Episode #546 deep-dive: talkpython.fm/546 Episode transcripts: talkpython.fm Theme Song: Developer Rap