Podcasts about GitLab

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This week on The Audit Podcast, Danielle Ritter, VP and Head of Internal Audit at GitLab and former CAE at Instacart, joins the show to share lessons from her leadership journey and practical advice for audit professionals at every stage of their careers.   Drawing from her experience leading audit functions across multiple organizations, Danielle discusses what matters most during a CAE's first 100 days, how to build credibility with stakeholders, and why strong relationships are essential to an effective audit function. She also shares how her team is embracing AI, developing new skills, and preparing for the future of the profession.   2:06 – Using AI in work and everyday life 5:16 – Where CAEs should focus: insights vs. efficiency 6:46 – Day One: listening and learning 10:11 – Navigating the CAE interview process 13:09 – How to define and demonstrate value 16:40 – What information belongs in the boardroom 19:00 – A practical approach to building strong relationships 22:45 – AI and the future of job security 27:55 – Making time for self-directed learning 30:07 – Final thoughts: your career does not define you   Be sure to connect with Danielle on LinkedIn.   Also, be sure to follow us on our social media accounts on LinkedIn, Instagram, and TikTok.   Also be sure to sign up for The Audit Podcast newsletter and to check the full video interview on The Audit Podcast YouTube channel.   This podcast is brought to you by Greenskies Analytics, the services firm that helps auditors leap-frog up the analytics maturity model. Their approach for launching audit analytics programs with a series of proven quick-win analytics will guarantee the results worthy of the analytics hype.    Whether your audit team needs a data strategy, methodology, governance, literacy, or anything else related to audit and analytics, schedule.

Wir sprechen über aktuelle Technikthemen rund um Infrastruktur, Open Source und KI. Ein Schwerpunkt ist Sebastians stark automatisierte Kubernetes-Umgebung auf Talos Linux mit GitOps und KI-Agenten unter menschlicher Kontrolle. Außerdem diskutieren wir Plattformfragen, Sicherheits- und Lieferkettenthemen sowie verschiedene KI-Entwicklungen. Zum Schluss greifen wir noch einige kleinere Themen aus dem Entwickleralltag und Werkzeuge für lokale LLMs auf. Blast from the Past Kubernetes Cluster ist nun live! https://www.siderolabs.com/talos-linux https://github.com/kreativmonkey/homelab-gitops payphonetag Froscon Toter der Woche Aus für De-Mail – warum das @ das eingekringelte e besiegte wero Aus für Ubuntu Pastebin – Abschaltung Ende Juni 2026 feedburner Untoter der Woche Stuxnet's Older Brother Revealed After 21 Years (video) fast16 | Mystery Shadow Brokers Reference Reveals High-Precision Software Sabotage 5 Years Before Stuxnet AI der Woche Continue Y/N Torvalds nennt KI Bug Reports “reine Zeitverschwendung” … aber curl Entwickler “zeigt sich versöhnlich” https://hothardware.com/news/new-ai-cyber-worm-thinks-up-its-own-attacks-to-infect-computers Anthropic: Weltweite Pause bei KI-Entwicklung ‘sinnvoll’ Anthropic Bewertung 965 Millarden rsync drama rsync analyse Google Chrome silently installs a 4 GB AI model on your device EU AI Act: Transparenzpflichten ab August 2026 Jakob gewinnt Gemma4 12B Bonsai 4b News Backblaze has quietly stopped backing up your data Debian must ship reproducible packages Cloudflare kauft Vite: Open Source und herstellerneutral – mit Millionenfonds https://arstechnica.com/security/2026/06/dozens-of-red-hat-packages-backdoored-through-its-offical-npm-channel/ https://www.golem.de/news/nur-ein-client-noetig-http-2-bomb-legt-webserver-in-sekunden-lahm-2606-209396.html Blog Post Themen Was eigentlich wenn kein GitHub? Ghostty Is Leaving GitHub Codeberg Gitlab BitBucket (nein!) Hackergarten 3D-Druck der Woche Bambu Lab: I’m reposting your code & I dare you to sue me. (video) Bambu Lab 3D printers: Never again (video) baltobu Zauberstab zum Bezahlen Weltumwelttag “PET Recycling” Mimimi der Woche modules C++20 tooling Python click Nix & SELinux Nix: cross-compiling Updates sind scheiße! Brother Drucker mit neuem Zertifikat Cosmic Desktop Nix Logo Lesefoo I put a datacenter GPU into my PC searchcode.com's SQLite database is probably 6 terabytes bigger than yours How I run multiple $10K MRR companies on a $20/month tech stack Serving a Website on a Raspberry Pi Zero Running Entirely in RAM NixOS auf Flint 2 You don’t love systemd timers enough! Picks IPv8 is finaly here Internet Protocol Version 8 (IPv8) The Unsolved Mystery of Lorem Ipsum (video) ODROID H5 Mechanical Pencil Umweltkosten durch Vibe Coding: Tool berechnet CO₂-Ausstoß für Claude Code Artikel von Heise taken (again)

In this episode of Elixir Wizards, hosts Charles Suggs and Emma Whamond sit down with Marek Šuppa, creator of the Missing GitHub Status page, a project that reconstructs GitHub's historical uptime data and reveals discrepancies between official status reporting and the platform's actual reliability. Marek tells us about his dev journey from open source contributor at DuckDuckGo to machine learning engineer at Cisco-acquired Slido. Then, we discuss GitHub's evolution from a hosted Git service into a critical developer tool. We cover reliability, transparency, AI-driven platform growth, developer workflows, and the challenges of balancing convenience with resilience. Along the way, we cover alternative platforms, self-hosted solutions, and whether recent outages are changing how developers think about ownership, dependency, and the future of software collaboration. Topics Discussed in this Episode: Why did Mr. Shu create the Missing GitHub Status Page? GitHub's reported uptime versus developer experiences How open source contributions shaped Marek's career The evolution of GitHub from tool to critical infrastructure Centralization risks in modern software development Git's distributed roots and today's platform-centric workflows Developer reactions to GitHub outages Transparency and accountability in status reporting AI's impact on developer platforms and infrastructure demands Microsoft's stewardship of GitHub Forgejo, Codeberg, and alternative Git hosting platforms Self-hosted Git solutions and tradeoffs Network effects and platform lock-in The social side of software collaboration Building resilience into developer workflows What GitHub outages teach us about infrastructure dependency Links Mentioned: The Missing GitHub Status Page https://mrshu.github.io/github-statuses/ Slido https://www.slido.com/ https://duckduckgo.com/ The official GitHub Status Page https://www.githubstatus.com/ Statuspage.iohttps://www.atlassian.com/software/statuspage Zig Leaves GitHub https://ziglang.org/news/migrating-from-github-to-codeberg/ Ghostty Leaves GitHub https://mitchellh.com/writing/ghostty-leaving-github GitLab https://about.gitlab.com/ Codeberg https://codeberg.org/ https://git.kernel.org/ Forgejo Lightweight Self-Hosting https://forgejo.org/ Former GitHub CEO Thomas Dohmke launches Entire https://entire.io/news/former-github-ceo-thomas-dohmke-raises-60-million-seed-round Update on Spain and LALIGA blocks of the internet https://vercel.com/blog/update-on-spain-and-laliga-blocks-of-the-internet

Bom dia Tech! Tudo bem? Meu nome é Arthur Givigir e hoje é quinta-feira, dia 04 de junho de 2026 e trago para vc as principais notícias de tecnologia, vamos lá?Quer patrocinar ou fazer uma parceria com o Bom dia Tech? Mande um e-mail para contato@bomdia.teche vamos conversar!Apoio03:48: Promoções do 6.6 da Amazon - Diversos ProdutosNotícias00:00: ☀️ Bom dia Tech!00:23:

Markets are facing a conundrum of overbought technicals, says Tom White when analyzing the price action on Wall Street. He urges caution for traders in the short term. That's not stopping earnings from muscling strength, seen in Palo Alto Networks' (PANW) beat despite a pullback in shares. Tom also notes GitLab's (GTLB) earnings beat and announcement of job cuts. Macy's (M) posts a strong quarter that adds confidence in the retail sector. ======== Schwab Network ========Empowering every investor and trader, every market day.Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about

George Tsilis discusses Wednesday's top moving stocks right after the opening bell. He highlights GitLab's (GLTB) earnings beat and job cut announcements. George turns to Macy's (M) Ulta Beauty's (ULTA) earnings and what they mean for the retail space. ======== Schwab Network ========Empowering every investor and trader, every market day.Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about

In der heutigen Folge sprechen die Finanzjournalisten Daniel Eckert und Holger Zschäpitz über Infineons historischen Rekord, die Disruptionsangst bei den Börsenbetreibern und warum die Börsenrallye in 2 Wochen abrupt enden könnte. Außerdem geht es um Nvidia, Hewlett Packard Enterprise, Broadcom, Applied Materials, Lumentum, Coherent, Qualcomm, ON Semiconductor, Lattice Semiconductor, Alphabet, Amazon, Microsoft, CoreWeave, Nebius, Salesforce, ServiceNow, Intuit, Workday, The Trade Desk, Palo Alto Networks, GitLab, Ulta Beauty, Infineon, Suss Microtec, Siemens, SAP, Bayer, Deutsche Börse, Cboe Global Markets, CME Group, Nasdaq, CrowdStrike, C3.ai, Five Below, Macy's, Medtronic, Rent the Runway, Inditex, Micron Technology, SK Hynix, AT&S, Ibiden, Unimicron, ING, Spotify, Amundi FTSE All World GDP-Weighted (WKN: ETF345). Wir freuen uns an Feedback über aaa@welt.de. Noch mehr "Alles auf Aktien" findet Ihr bei WELTplus und Apple Podcasts – inklusive aller Artikel der Hosts. Hier bei WELT: https://www.welt.de/podcasts/alles-auf-aktien/plus247399208/Boersen-Podcast-AAA-Bonus-Folgen-Jede-Woche-noch-mehr-Antworten-auf-Eure-Boersen-Fragen.html. Hier könnt ihr den AAA-Newsletter abonnieren: https://www.welt.de/newsletter/article232797673/Alles-auf-Aktien-Der-taegliche-Boersen-Newsletter-fuer-WELTplus-Abonnenten.html Und - ganz neu: AAA gibt es jetzt auch auf Instagram: https://www.instagram.com/alles_auf_aktien/ Disclaimer: Die im Podcast besprochenen Aktien und Fonds stellen keine spezifischen Kauf- oder Anlage-Empfehlungen dar. Die Moderatoren und der Verlag haften nicht für etwaige Verluste, die aufgrund der Umsetzung der Gedanken oder Ideen entstehen. Hörtipps: Für alle, die noch mehr wissen wollen: Holger Zschäpitz können Sie jede Woche im Finanz- und Wirtschaftspodcast "Deffner&Zschäpitz" hören. +++ Werbung +++ Du möchtest mehr über unsere Werbepartner erfahren? Hier findest du alle Infos & Rabatte! https://linktr.ee/alles_auf_aktien Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutz: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html

Investors digest cybersecurity earnings, AI developments and shifting risk appetite. Mandy Xu of Cboe explains how options traders are positioning and where speculative activity is building. Palo Alto Networks headlines earnings. Saket Kalia of Barclays breaks down the results and what they signal for cybersecurity spending, enterprise demand and the broader software landscape. Ulta and GitLab add fresh reads on the consumer and technology spending. A major conversation on AI in healthcare: our Kate Rooney sits down with Microsoft AI CEO Mustafa Suleyman and Mayo Clinic CEO Dr. Gianrico Farrugia to discuss how artificial intelligence is transforming medicine, research and patient care. Sunhaina Sinha of Raymond James discusses the capital raising environment and whether funding conditions are improving for companies and investors. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Today we are talking about AI, How to stay up to date with it, and if it will really take our jobs with guests Angie Byron & Amber Matz. We'll also cover AI Best Practices for Drupal as our module of the week. For show notes visit: https://www.talkingDrupal.com/555 Topics What Is AI Learners Club Amber Defines the Club Origin Story and DrupalCon AI Debate and Community Tensions Issue Queue Conduct and Moderation Thread Tone vs Substance AI Adoption Outside Drupal Conflict Mediation Playbook Maintainer Burnout and Flood Safe Space Learners Club How the Club Started Picking Topics and Demos AI Taking Our Jobs Future of Learners Club Resources Context Control Center AI Learners Club Initiative page Event calendar YouTube Playlist Session Recaps Next session (Claude Design) Slack: #ai-learners Most wanted topics What Angie's working on these days Guests Amber Matz - tugboatqa.com amber-himes-matz Angie Byron - ai_best_practices webchick Hosts Nic Laflin - nLighteneddevelopment.com nicxvan John Picozzi - epam.com johnpicozzi Scott Falconer - managing-ai.com scott-falconer MOTW Correspondent Martin Anderson-Clutz - mandclu.com mandclu Brief description: Do you want to start using AI tools for Drupal development, in the most efficient way possible? There's a composer plugin for that! Module name/project name: AI Best Practices for Drupal Brief history How old: created in Mar 2026 by Angie Byron (webchick), one, of today's guests, a long-time Drupalist, one-time Acquian, and a fellow Canadian Versions available: dev version only, which doesn't seem directly opinionated about what version of Drupal you're using, though it does have minimum versions of PHP and Symfony libraries that suggest Drupal 10 is functionally your minimum Maintainership It is officially seeking co-maintainers Test coverage Documentation - an in-depth README, or you can ask an AI model! (like I did for this segment) 54 open "Work Items" on Gitlab, so lots of active discussion already Module features and usage AI Best Practices for Drupal aims to be the opinionated starter experience for AI-assisted Drupal development You can think of it as a single Composer install that makes any AI coding agent "speak Drupal": following community standards, preferring contrib over custom code, and avoiding framework-naive mistakes. It replaces scattered, tool-specific CLAUDE.md files and Cursor rules that some Drupal developers currently maintain individually, with one canonical, community-governed package that works across Claude Code, Cursor, Copilot, and more. With contributions by a variety of Drupal luminaries including Marcus Johansson, Christoph Briedert, and Scott Falconer, it's the Drupal equivalent of Laravel Boost: stop explaining Drupal to your AI every session and just get writing code. After install or update, it will create an AGENTS.md file from a provided template if there isn't one already, or it will update a specifically marked "ai-best-practices" section of an existing file You will also have a directory of provided skills, and guidance for creating new Drupal agent skills Also included is a set of evals, meant to automatically identify when AI models go off course and provide feedback AI Best Practices for Drupal is meant to provide guidance that will be particularly useful for AI agents, so it's ideal for Drupal developers getting started with AI tools, or for AI developers who want to get started with Drupal

The power of choice is in full effect! How you can leverage GitLab to publish your next Quarto document online, how to bring key R functional paradigms to a Python session, and adding a larger safety net with your unit tests with {mutagen} 0.2.0. Episode Links This week's curator: Jon Carroll - @jonocarroll@fosstodon.org (Mastodon) & @jonocarroll.fosstodon.org.ap.brid.gy (Bluesky) & @carroll_jono (X/Twitter)Deploying Quarto documents with GitLabFunctions over Idioms - Writing R in Python with rfunsmuttest 0.2.0: More Mutators, Better Reporting, and Parallel ExecutionEntire issue available at rweekly.org/2026-W22Supplement ResourcesData Science at the Command Line https://datascienceatthecommandline.com/DevOps for Data Science https://do4ds.com/{pak} System Requirements https://pak.r-lib.org/reference/sysreqs.htmlSupporting the showUse the contact page at https://serve.podhome.fm/custompage/r-weekly-highlights/contact to send us your feedbackR-Weekly Highlights on the Podcastindex.org - You can send a boost into the show directly in the Podcast Index. First, top-up with Alby, and then head over to the R-Weekly Highlights podcast entry on the index.A new way to think about value: https://value4value.infoGet in touch with us on social mediaEric Nantz: @rpodcast@podcastindex.social (Mastodon), @rpodcast.bsky.social (BlueSky) and @theRcast (X/Twitter)Mike Thomas: @mike_thomas@fosstodon.org (Mastodon), @mike-thomas.bsky.social (BlueSky), and @mike_ketchbrook (X/Twitter) Music credits powered by OCRemix Wrestling with Double Bass - Street Fighter II - Malcos - https://ocremix.org/remix/OCR01270A Simple Flip can Change Fate - Final Fantasy VI - Level 99 - https://ocremix.org/remix/OCR02692

Roland and J-M go solo to pull back the curtain on something that's been years in the making: BPM OS, a purpose-built, local-first tool stack designed to help small, talented process and architecture teams stand up a real BPM practice — without the vendor dependency, IT overhead, or 12-month procurement nightmare.In this episode of the podcast we talk about: Most BPM programs fail not because of bad content, but because organizations treat it as a pure IT exercise — buy a platform, check the box, and wonder why nothing sticks.The three pillars every BPM capability needs are content, governance, and adoption — yet most organizations only address the first one.Knowledge rented from consultants or SaaS vendors disappears the moment you stop paying; BPM OS is built on the principle that you own it outright, forever.BPM OS targets three groups: small internal teams doing more with less, consulting organizations that want baked-in methodology for client delivery, and vendors looking to bundle a white-labeled practice layer with their platforms.Groundwork is the brainstorming and planning app — dump ideas onto a canvas, sort them into zones, and shift into structured planning mode with priorities and rough timelines.Playbook is a lightweight wiki for capturing structured knowledge, course profiles, stakeholder analyses, and methodology documentation — with templates so you never start from a blank page.Atlas generates visual subway maps of your learning curriculum or capability landscape, complete with time-sensitive station states, deprecation indicators, and links back to Playbook pages.Outline lets you define the detailed content structure of a course or deliverable in a hierarchical, mind-map-style view — moving from “What do we need to teach?” to "Exactly what are the chapters and items?”Course Flow is a Kanban-based project management tool for developing and iterating on courses, complete with a built-in feedback form, an inbox for triage, and a status dashboard across all active projects.Cadence is a personal (and optionally team) task planner organized by day and category — with recurring daily items, carry-forward of incomplete tasks, and a simple velocity metric to spot overload before it becomes a crisis.The entire stack runs on Node.js, saves files as Markdown and JSON (no database required), plays nicely with Google Drive or OneDrive for backup, and optionally connects to GitHub or GitLab for full version history.Apps interoperate through lightweight linking and import/export — cards from Groundwork flow into Atlas, tasks from CourseFlow export into Cadence, and every Playbook page carries a permanent link that works anywhere in the stack.Find out more and download your free personal copy of Cadence at whatsyourbaseline.com/bpm-os—and check the episode show notes for a PDF overview of all six apps.Reach out by emailing ⁠hello@whatsyourbaseline.com⁠ or subscribe to our newsletter and articles on Substack at whatsyourbaseline.substack.com.

У свіжому дайджесті DOU News обговорюємо реліз в Україні: Мінцифра додала ШІ-асистента в застосунок «Дія». У глобальному тек-секторі черговий парадокс — корпорація Cisco звільняє 4000 співробітників на тлі рекордних прибутків, а GitLab повністю перекроює структуру заради ери ШІ-агентів. Також у випуску нова жорстка reCAPTCHA від Google та свіжа аналітика ринку праці 2026 року. Дивіться ці та інші новини українського та світового тек-сектору. Таймкоди 00:00 Інтро 01:07 Як айтівці шукають роботу в 2026 році 05:55 На скільки зростає зарплата айтівців при зміні роботи 06:54 ШІ-асистента додали у мобільний застосунок «Дія» 08:16 На війні загинув QA-спеціаліст, переможець Премії DOU Геннадій Міщевський 09:07 Головні фічі нової Android 17 12:14 Cisco звільняє 4000 співробітників попри надприбутки 13:44 GitLab проводить масштабну реструктуризацію заради ери ШІ-агентів 17:19 Anthropic повернула OpenClaw та використання сторонніх агентів 20:12 Anthropic знову обійшла OpenAI за кількістю бізнес-клієнтів 22:29 Нова reCAPTCHA від Google блокує доступ до сайтів 24:16 Батьки звинувачують ChatGPT у загибелі сина через погану пораду 26:44 Що рекомендує Женя: статтю про вайб-кодинг та агентну інженерію та канал «AI Engineer»

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

What if faster coding is actually slowing your software delivery down? Most teams are pouring AI into the coding phase, but the real bottleneck is everywhere else.In this episode, Andrew Haschka, Field CTO at GitLab for Asia Pacific and Japan, explains why most AI strategies in software engineering are failing and what it takes to fix them. He introduces the AI paradox: teams invest heavily in AI-assisted coding, yet coding accounts for less than 20% of the software delivery lifecycle, leaving the biggest bottlenecks untouched.Andrew makes the case for intelligent orchestration — moving from isolated AI interactions to governed, end-to-end agentic flows that span planning, coding, testing, security, compliance, and release. He shares how a unified system of record forms the foundation for high-quality AI outcomes, and why fragmented tools and siloed context actively limit what AI can deliver. Drawing on real customer examples — including Ericsson's 50% faster deployments and 130,000 hours saved in six months — he shows what a holistic approach actually looks like in practice.The conversation also covers how tech leads, developers, and junior engineers need to evolve their skills in a world where AI handles routine implementation. Andrew closes with a compelling argument: in the agentic era, governance isn't just a compliance burden, it's the primary source of competitive advantage.Timestamps:(02:30) What Are the Key Responsibilities of a Field CTO at GitLab?(03:26) Why Should Organizations Govern AI Strategy Rather Than Chase the Latest Features?(06:41) Why Is an End-to-End Agentic Flow More Valuable Than Individual AI Tools?(09:39) What Is the AI Paradox and How Does Intelligent Orchestration Solve It?(14:47) How Does Shifting Focus to Requirements Quality Transform Software Delivery Outcomes?(18:19) How Has GitLab Evolved Beyond CI/CD Into a Full End-to-End Delivery Platform?(20:20) What Should Software Teams Prioritize Beyond Coding in the AI Era?(24:14) How Do Organizational Silos Create a Capability Threshold for AI Adoption?(27:49) What Practical Strategies Can Organizations Use to Break Down Internal Silos?(30:58) How Did Ericsson Achieve 50% Faster Deployments and Save 130,000 Hours With GitLab?(33:07) How Should Software Developers Evolve in the Age of AI Agents?(36:26) How Is the Tech Lead Role Evolving in a Hybrid Human-AI Team?(39:22) How Can Junior Developers Keep Up With the Rapid Shift in Industry Expectations?(42:40) Why Do 79% of Singapore DevSecOps Practitioners Believe AI Will Create More Jobs?(45:27) Why Are Companies Reducing Staff Despite the Growing Demand for Software?(48:34) What Are the Most Common Pitfalls When Implementing Agentic Workflows?(52:29) What Practical Steps Should Engineering Leaders Take to Govern AI Responsibly?(55:13) Why Should Engineering Leaders Build an AI Strategy Before Choosing Technology?(57:15) 3 Tech Lead Wisdom_____Andrew Haschka's BioAndrew Haschka serves as Field CTO for Asia Pacific & Japan at GitLab, where he acts as a trusted strategic advisor to enterprise customers and partners navigating complex technology transformation. With over 20 years of experience spanning software delivery, cybersecurity, cloud infrastructure, and organisational transformation, Andrew brings a rare combination of technical depth and executive-level counsel to the organisations he works with.Prior to GitLab, Andrew held senior leadership roles across APAC at Google and VMware, and has led large-scale digital transformation programmes for organisations including Downer, IBM, Jones Lang LaSalle, Thomson Reuters, Optus, and across the Fiji and Pacific Islands.Follow Andrew:LinkedIn – linkedin.com/in/andrewhaschkaLike this episode?Show notes & transcript: techleadjournal.dev/episodes/258.Follow @techleadjournal on LinkedIn, Twitter, and Instagram.Buy me a coffee or become a patron.

Over de ‘tweede act' van GitLab, en malaise bij Meta. Toen Mozes van de berg naar beneden totterde, had hij twee stenen met tien regels bij. Je mag je ouders geen meppen verkopen, bijvoorbeeld, en niet jaloers zijn op een ander. God is tegenwoordig vervangen door Git, en die is wel jaloers op de andere kindjes. Zij zijn namelijk lekker afgeslankt, want ook bedrijven kunnen aan de Ozempic. Eén klein prikje en je bent zo een man of duizend lichter! Welkom in Computer Club, een podcast door Frederik 'Freddy' De Bosschere & Thomas 'Smollie' Smolders. Met dank aan Sebastiaan Van den Branden & Toon De Pauw voor de technische hulp. Wekelijks bespreken we de actualiteit op vlak van technologie en gaan we op zoek naar interessante feiten en innovaties. Af en toe nodigen we zelfs een gast uit. Er zijn ook jingles. Events: https://computerclub.events Forum: https://computerclub.forum Word Vriend van de Show: https://vrienden.computerclub.online Nieuwsbrief: https://nieuwsbrief.computerclub.online Merchandise: https://computerclub.shop

In der heutigen Folge sprechen die Finanzjournalisten Philipp Vetter und Holger Zschäpitz über einen kleinen Realitätscheck an den Börsen, die Orbitpläne von Space X und Google sowie eine veritable Enttäuschung bei der Munich Re. Außerdem geht es um Bayer, Munich Re, Siemens Energy, Thyssenkrupp, Zalando, Under Armour, Hims & Hers Health, ZoomInfo, GitLab, CME Group, Alphabet, Rackspace Technology, AMD, eBay, GameStop, Allianz, Micron, Meta, Tesla, Apple, Qualcomm, Volkswagen, BMW, Mercedes-Benz Group, Airbus, Saudi Aramco, Equinor, ConocoPhillips, AppLovin, Nvidia, Investor AB, Welltower, Altria Group, CNOOC, SAP, Global X China Electric Vehicle and Battery ETF (WKN: A3C5S0), UBS MSCI China A SF UCITS ETF (WKN: A2PRV8), Xtrackers CSI300 Swap UCITS ETF (WKN: DBX0M2), HSBC MSCI China A UCITS ETF (WKN: A2N390), KraneShares CSI China Internet UCITS ETF (WKN: A2PBU9), HSBC Hang Seng Tech UCITS ETF (WKN: A2QHV0), iShares Dow Jones China Offshore 50 ETF (WKN: A0F5UE). Wir freuen uns an Feedback über aaa@welt.de. Noch mehr "Alles auf Aktien" findet Ihr bei WELTplus und Apple Podcasts – inklusive aller Artikel der Hosts. Hier bei WELT: https://www.welt.de/podcasts/alles-auf-aktien/plus247399208/Boersen-Podcast-AAA-Bonus-Folgen-Jede-Woche-noch-mehr-Antworten-auf-Eure-Boersen-Fragen.html. Hier könnt ihr den AAA-Newsletter abonnieren: https://www.welt.de/newsletter/article232797673/Alles-auf-Aktien-Der-taegliche-Boersen-Newsletter-fuer-WELTplus-Abonnenten.html Und - ganz neu: AAA gibt es jetzt auch auf Instagram: https://www.instagram.com/alles_auf_aktien/ Disclaimer: Die im Podcast besprochenen Aktien und Fonds stellen keine spezifischen Kauf- oder Anlage-Empfehlungen dar. Die Moderatoren und der Verlag haften nicht für etwaige Verluste, die aufgrund der Umsetzung der Gedanken oder Ideen entstehen. Hörtipps: Für alle, die noch mehr wissen wollen: Holger Zschäpitz können Sie jede Woche im Finanz- und Wirtschaftspodcast "Deffner&Zschäpitz" hören. +++ Werbung +++ Du möchtest mehr über unsere Werbepartner erfahren? Hier findest du alle Infos & Rabatte! https://linktr.ee/alles_auf_aktien Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutz: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html

This is a recap of the top 10 posts on Hacker News on May 11, 2026. This podcast was generated by wondercraft.ai (00:30): I'm going back to writing code by handOriginal post: https://news.ycombinator.com/item?id=48090029&utm_source=wondercraft_ai(01:57): Postmortem: TanStack npm supply-chain compromiseOriginal post: https://news.ycombinator.com/item?id=48100706&utm_source=wondercraft_ai(03:25): Mythos Finds a Curl VulnerabilityOriginal post: https://news.ycombinator.com/item?id=48091737&utm_source=wondercraft_ai(04:52): Ratty – A terminal emulator with inline 3D graphicsOriginal post: https://news.ycombinator.com/item?id=48093100&utm_source=wondercraft_ai(06:20): Gmail registration now requires scanning a QR code and sending a text messageOriginal post: https://news.ycombinator.com/item?id=48092028&utm_source=wondercraft_ai(07:48): GitLab announces workforce reduction and end of their CREDIT valuesOriginal post: https://news.ycombinator.com/item?id=48100500&utm_source=wondercraft_ai(09:15): Software engineering may no longer be a lifetime careerOriginal post: https://news.ycombinator.com/item?id=48095550&utm_source=wondercraft_ai(10:43): CUDA-oxide: Nvidia's official Rust to CUDA compilerOriginal post: https://news.ycombinator.com/item?id=48096692&utm_source=wondercraft_ai(12:10): The greatest shot in television: James Burke had one chance to nail this scene (2024)Original post: https://news.ycombinator.com/item?id=48090521&utm_source=wondercraft_ai(13:38): If AI writes your code, why use Python?Original post: https://news.ycombinator.com/item?id=48100433&utm_source=wondercraft_aiThis is a third-party project, independent from HN and YC. Text and audio generated using AI, by wondercraft.ai. Create your own studio quality podcast with text as the only input in seconds at app.wondercraft.ai. Issues or feedback? We'd love to hear from you: team@wondercraft.ai

Friday Deployments. Alle reden darüber, viele haben eine starke Meinung dazu und erstaunlich viele Teams haben vor allem eins: Angst. Nicht nur vor Technik, sondern vor kaputten Prozessen, endlosen Freigaben, Rufbereitschaft am Wochenende und der berühmten Frage, wer schuld ist, wenn Production brennt. Aber ist das Problem wirklich der Freitag oder zeigt der Freitag nur schonungslos, wie gut oder wie fragil unsere Software Delivery wirklich ist?In dieser Episode sprechen wir mit Sujeevan, ehemaliger Solutions Architect bei GitLab und Grafana, Podcaster beim Tilpod, DevOps-Autor und Gründer der Friday Deployments GmbH. Gemeinsam schauen wir auf den Mythos Friday Deployment und zerlegen ihn in seine Einzelteile: CI/CD, Staging, Monitoring, Feature Flags, Blue Green und Canary Deployments, Delivery versus Deployment, Blameless Post Mortems, On Call, DevOps-Kultur, Compliance, Banken, Mittelstand und die Frage, warum viele Teams technisch mehr könnten, es kulturell aber trotzdem nicht tun.Dabei wird schnell klar: Wer freitags nicht deployen kann, hat oft kein Freitagsproblem, sondern ein Delivery-Problem, ein Kulturproblem oder ein Vertrauensproblem. Wenn du wissen willst, wie Teams deploybarer, stressfreier und am Ende auch produktiver werden, ist diese Folge für dich.Bonus: Eine Waschmaschine erklärt den Unterschied zwischen Continuous Delivery und Continuous Deployment erstaunlich gut.Unsere aktuellen Werbepartner findest du auf https://engineeringkiosk.dev/partnersDas schnelle Feedback zur Episode:

In Season 15 episode 2, Elixir Wizards Sundi Myint and Charles Suggs chat with Micah Cooper to talk about distributed systems, data replication, and what it actually looks like to build these ideas in Elixir.   Micah shares his journey from Ruby to Elixir and walks us through Visor, a library he's building based on the Viewstamps replication algorithm. Inspired by systems like TigerBeetle, Visor explores how you can replicate state across nodes using GenServers, giving you fault tolerance and recovery without relying entirely on traditional database patterns.   We talk about the difference between distributed systems and data replication, where things tend to get misunderstood, and what changes when you start thinking about state this way. The conversation also touches on event sourcing, tradeoffs in system design, and how Elixir's distributed model makes some of these concepts more approachable than you might expect.   Along the way, we talk about building for curiosity, experimenting with new ideas, and how projects like this push the ecosystem forward.   Topics discussed in this episode: Building Visor and working with the Viewstamps replication model Replicating GenServer state across nodes Distributed systems vs. data replication Lessons from TigerBeetle and financial system design Event sourcing challenges and tradeoffs Rethinking database-first architectures Snapshotting, recovery, and fault tolerance The role of Elixir's distributed model Experimentation, learning, and building for curiosity   Links mentioned: Micah's GitHub https://github.com/mrmicahcooper Micah's GitLab https://gitlab.com/mrmicahcooper The Visor repository: https://gitlab.com/mrmicahcooper/visor Visor Hex Package https://hex.pm/packages/visor Ruby on Rails https://rubyonrails.org/ Phoenix LiveView Framework https://www.phoenixframework.org/ Zig Programming Language https://ziglang.org/ TigerBeetle https://tigerbeetle.com/ TigerBeetle internal docs https://github.com/tigerbeetle/tigerbeetle/tree/main/docs/internals The BEAM https://www.erlang-solutions.com/blog/the-beam-erlangs-virtual-machine/ GenServer https://hexdocs.pm/elixir/GenServer.html Apache Kafka https://github.com/apache/kafka RabbitMQ https://www.rabbitmq.com/ Redpanda https://www.redpanda.com/ SQL https://www.ibm.com/think/topics/structured-query-language Kubernetes https://kubernetes.io/ YAML https://yaml.org/ Nomad Workload Orchestrator https://developer.hashicorp.com/nomad Flutter https://flutter.dev/ Commanded https://hexdocs.pm/commanded/Commanded.html Go Programming Language https://go.dev/ Clojure Programming Language https://clojure.org/ Nebulex https://hexdocs.pm/nebulex/Nebulex.html Mnesia https://www.erlang.org/doc/apps/mnesia/mnesia.html Cachex https://hexdocs.pm/cachex/Cachex.html libgraph https://hexdocs.pm/libgraph/Graph.html Horde https://hexdocs.pm/horde/Horde.Registry.html NocFree split keyboard https://www.nocfree.com/ Micah's LinkedIn https://www.linkedin.com/in/micah-cooper-4a737560/ 

I'm back with my friend and colleague Sabine Hossenfelder for another episode of “What's New in Science”. Spending time with Sabine was a nice chance to step away from my physics lecture series for a bit. I know many of you have been enjoying the lectures, so don't worry, they'll be back soon.In this episode, we covered an incredibly wide range of science topics. Sabine opened with reported claim that the CIA used quantum magnetometry to find the downed pilot in Iran. The report, in the NY Post, looked fishy. We explain why it is. Then I described a new discovery in the physics of material that may solve perhaps the biggest problem in AI now: heat generation in computers. Sabine talked about a new claimed Big Bang Theory that might have some relevance to quantum gravity. Then I countered with a discussion of yet a new result that suggests the standard model of cosmology may have troubles, or that observers are wrong. After that, Sabine introduced a paper describing a possible new way to measure gravitational waves. I think it is a fine piece of work, though it is not clear if it is practical. If it were, then the huge interferometers that are now being used could be replaced by ‘tabletop' detectors. We will see. Finally, I described an amazingly interesting news story that might have implications for the future of medicine. It also demonstrates what one person, with determination and wealth, can do to possibly cure their own maladies. Sid Sijbrandij, a billionaire tech CEO of Gitlab, was diagnosed with inoperable spine cancer, and launched an amazing program of diagnostics, AI data mining, and a group of scientists who developed vaccines specific to his genetic makeup. After implementing all the procedures, he has been cancer free for a year. While this is beyond the reach of people without these resources now, Sid's story demonstrates the potential power of combining AI and genetic medicine in the future.As always, an ad-free video version of this podcast is also available to paid Critical Mass subscribers. Your subscriptions support the non-profit Origins Project Foundation, which produces the podcast. The audio version is available free on the Critical Mass site and on all podcast sites, and the video version will also be available on the Origins Project YouTube. Get full access to Critical Mass at lawrencekrauss.substack.com/subscribe

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Sid Sijbrandij is the co-founder of GitLab, one of the world's largest open-source software companies. But in 2022, his life took a radical turn — he was diagnosed with a rare and aggressive form of cancer.Instead of relying solely on the medical system, Sid took a different approach. He ran every diagnostic imaginable, developed experimental treatments, combined therapies, and ultimately built his own path to survival — even when doctors ran out of options.In this episode, we explore how Sid applied first-principles thinking to medicine, why healthcare systems are fundamentally misaligned with patient incentives, and what the future of personalized treatments could look like. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.infinitacitytimes.com

Et si le code source était le patrimoine le plus précieux de notre époque ? Roberto Di Cosmo explique pourquoi il est vital de préserver tous les logiciels, même les plus insignifiants. Une mission titanesque qui pourrait bien devenir un enjeu stratégique majeur pour nos sociétés.Interview : Roberto Di Cosmo, chercheur en informatique et fondateur de Software HeritagePunchlinesSans code source, on perd le contrôle du numérique.GitHub n'est pas une archive, c'est une plateforme éphémère.On archive tout, même les logiciels inutiles.Quelques pétaoctets suffisent pour préserver toute l'histoire du code.Le code est un enjeu de souveraineté stratégique.Pourquoi archiver tous les codes sources existants ?L'informatique est le fondement de notre société, mais on oublie que tout repose sur des codes sources. Sans ces codes, on perd la maîtrise de ce qu'on utilise au quotidien. On s'est rendu compte que ces codes étaient dispersés sur des plateformes fragiles et parfois éphémères. Certains ont déjà disparu du jour au lendemain. Il n'existait aucune véritable archive, contrairement au web ou aux images. C'est ce constat qui a déclenché notre projet.GitHub ne suffit pas à préserver les logiciels ?Non, absolument pas. GitHub ou GitLab sont des plateformes de collaboration, pas des archives. On peut y supprimer un projet à tout moment, ou une plateforme peut fermer. Cela s'est déjà produit avec des services comme Google Code. Des millions de projets ont disparu. Une archive, au contraire, garantit que ce qui est déposé restera accessible dans le temps.Pourquoi avoir choisi d'archiver absolument tout, même le code inutile ?Parce qu'il est impossible de juger à l'avance ce qui sera important. Un exemple marquant est PHP, qui semblait insignifiant à ses débuts et qui est devenu essentiel pour le web. Le logiciel évolue avec le temps. Ce qui paraît inutile aujourd'hui peut devenir crucial demain. Donc on archive tout, sans filtrer, et on laisse l'histoire faire le tri.Le code devient-il un enjeu stratégique aujourd'hui ?Oui, clairement. Nous dépendons énormément de plateformes étrangères sur lesquelles nous n'avons aucun contrôle. Si l'accès est coupé, toute la chaîne logicielle peut s'arrêter. Software Heritage permet de reconstruire cette continuité en fournissant une copie indépendante. Cela devient un enjeu de souveraineté, pour les entreprises comme pour les États.Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

จะเกิดอะไรขึ้นเมื่อสุดยอดผู้บริหารและวิศวกรระดับโลก ต้องเผชิญกับโรคมะเร็งกระดูกที่ยากจะรักษา แทนที่จะพึ่งพาวิธีการแพทย์แบบดั้งเดิมเพียงอย่างเดียว เขาเลือกมองร่างกายเป็นเหมือนระบบซอฟต์แวร์ที่เกิดข้อผิดพลาด แล้วประยุกต์ใช้แนวคิดการบริหารธุรกิจสตาร์ทอัป ผสานเข้ากับพลังการประมวลผลของ AI อย่าง GPT-4 เพื่อ “แฮ็ก” ระบบชีววิทยาของตัวเองจนเอาชนะความตายได้สำเร็จ เรื่องราวของ Sid Sijbrandij อดีต CEO ของ GitLab ที่เปลี่ยนวิกฤตชีวิตให้เป็นพิมพ์เขียวบทใหม่ของวงการแพทย์เฉพาะบุคคล จะน่าทึ่งขนาดไหน และ AI กำลังจะพลิกโฉมอนาคตของเราไปอย่างไร เลือกฟังกันได้เลยนะครับ อย่าลืมกด Follow ติดตาม PodCast ช่อง Geek Forever's Podcast ของผมกันด้วยนะครับ =========================  สนับสนุนโดย =========================

After watching Project Hail Mary, Cal sees more than a sci-fi story about saving the stars—he sees a blueprint for how humans might survive the age of AI. That insight leads him to a real-life story even more extraordinary. When tech founder Sid Sijbrandij is diagnosed with a rare, aggressive cancer, the traditional medical system eventually runs out of answers. Most people would accept that outcome. Sid does the opposite. He treats his own disease like an open- source problem—gathering data, building a team, and chasing solutions across the globe with the same mindset that helped build GitLab into a billion-dollar company. With the help of AI, Cal translates this complex scientific journey into a human story anyone can follow. One that's filled with pancakes, partnerships, love, and a radical idea: What if the future of survival—against disease, against uncertainty, against AI itself—belongs to those who adapt fastest? This episode is about more than cancer. It's about how humans fight back.

Git nutzen wir jeden Tag. Aber Hand aufs Herz: Wie viel davon verstehen wir wirklich?Hinter commit, push und pull steckt kein bisschen Magie, sondern ein erstaunlich komplexes System aus Objekten, Referenzen, Protokollen und Designentscheidungen, die bis heute die Softwareentwicklung prägen. Und genau da wird es spannend. Denn Git ist 20 Jahre alt, aber alles andere als fertig entwickelt.In dieser Episode sprechen wir mit Patrick Steinhardt, Git Maintainer, Contributor zu libgit2 und Staff Engineer im Git Team bei GitLab. Gemeinsam tauchen wir tief in die Git Internals ein und klären, warum Git sich gegen Subversion durchgesetzt hat, was ein bare Repository auf der Server-Seite eigentlich macht, wie Clone, Fetch und Push wirklich funktionieren und warum große Repositories, Millionen Referenzen, Binärdateien und Git LFS bis heute echte Herausforderungen sind. Außerdem geht es um Reftables, Partial Clones, Large Object Promises, pluggable object databases, Git History, Interactive Rebase und die Frage, was Git 3.0 mit SHA-256, besserer Usability und moderner Architektur verändern könnte.Wenn du Git bisher vor allem als Werkzeug für deinen täglichen Workflow gesehen hast, bekommst du hier einen Blick unter die Haube, der vieles neu sortiert. Vielleicht hörst du diese Folge als Developer:in mit einem leichten Ich benutze Git seit Jahren Gefühl. Vielleicht gehst du raus mit dem Gedanken: Ich kenne bisher gerade mal die Oberfläche. So oder so, diese Episode ist Pflichtprogramm für alle, die Versionskontrolle, Entwickler-Workflows, Open Source und die Zukunft von Git besser verstehen wollen. Bonus: Danach wirkt selbst git rebase plötzlich fast freundlich.Unsere aktuellen Werbepartner findest du auf https://engineeringkiosk.dev/partnersDas schnelle Feedback zur Episode:

This is a recap of the top 10 posts on Hacker News on March 28, 2026. This podcast was generated by wondercraft.ai (00:30): Founder of GitLab battles cancer by founding companiesOriginal post: https://news.ycombinator.com/item?id=47556729&utm_source=wondercraft_ai(01:59): Spanish legislation as a Git repoOriginal post: https://news.ycombinator.com/item?id=47553798&utm_source=wondercraft_ai(03:29): Go hard on agents, not on your filesystemOriginal post: https://news.ycombinator.com/item?id=47550282&utm_source=wondercraft_ai(04:58): AI overly affirms users asking for personal adviceOriginal post: https://news.ycombinator.com/item?id=47554773&utm_source=wondercraft_ai(06:28): I decompiled the White House's new appOriginal post: https://news.ycombinator.com/item?id=47555556&utm_source=wondercraft_ai(07:57): Britain today generating 90%+ of electricity from renewablesOriginal post: https://news.ycombinator.com/item?id=47553484&utm_source=wondercraft_ai(09:27): I Built an Open-World Engine for the N64 [video]Original post: https://news.ycombinator.com/item?id=47553717&utm_source=wondercraft_ai(10:56): CERN uses ultra-compact AI models on FPGAs for real-time LHC data filteringOriginal post: https://news.ycombinator.com/item?id=47552562&utm_source=wondercraft_ai(12:26): Cocoa-Way – Native macOS Wayland compositor for running Linux apps seamlesslyOriginal post: https://news.ycombinator.com/item?id=47553185&utm_source=wondercraft_ai(13:55): AMD's Ryzen 9 9950X3D2 Dual Edition crams 208MB of cache into a single chipOriginal post: https://news.ycombinator.com/item?id=47550878&utm_source=wondercraft_aiThis is a third-party project, independent from HN and YC. Text and audio generated using AI, by wondercraft.ai. Create your own studio quality podcast with text as the only input in seconds at app.wondercraft.ai. Issues or feedback? We'd love to hear from you: team@wondercraft.ai

Décision de justice historique contre les géants des réseaux sociaux. OpenAI se prépare à la Bourse. Anthropic invente l'agent IA télécommandé. Google crée un "compresseur" pour IA afin d'économiser la mémoire informatique. Sony abandonne son projet de voiture. Nouvelle cyberarnaque au deepfake. Une bibliothèque mondiale du logiciel

In der heutigen Folge sprechen die Finanzjournalisten Philipp Vetter und Holger Zschäpitz über Stagflationssignale, crashende Softwareaktien und ein weiterer Großauftrag für Palantir. Außerdem geht es um CF Industries, Mosaic, Archer-Daniels-Midland, Hubspot, UiPath, Atlassian, Zscaler, Snowflake, Gitlab, MongoDB, Salesforce, Datadog, Servicenow, Intuit, Workday, Gartner, Amazon, SAP, Arm, Apple, Samsung, Microsoft, Ionos, Commonwealth Bank of Australia, National Australian Bank, BHP Group, Rio Tinto, Westpac Banking, ANZ Group, Wesfarmers, Xtrackers S&P ASX 200 (WKN: DBX1A2), iShares MSCI Australia (WKN: A0YJ80), Xtrackers II Australia Government Bond ETF (WKN: DBX0GG). Die Infos zum Buch “Project Maven – A Marine Colonel, His Team, and the Dawn of AI Warfare” von Katrina Manson findet ihr hier: https://wwnorton.com/books/9781324123316 Wir freuen uns an Feedback über aaa@welt.de. Noch mehr "Alles auf Aktien" findet Ihr bei WELTplus und Apple Podcasts – inklusive aller Artikel der Hosts. Hier bei WELT: https://www.welt.de/podcasts/alles-auf-aktien/plus247399208/Boersen-Podcast-AAA-Bonus-Folgen-Jede-Woche-noch-mehr-Antworten-auf-Eure-Boersen-Fragen.html. Hier könnt ihr den AAA-Newsletter abonnieren: https://www.welt.de/newsletter/article232797673/Alles-auf-Aktien-Der-taegliche-Boersen-Newsletter-fuer-WELTplus-Abonnenten.html Und - ganz neu: AAA gibt es jetzt auch auf Instagram: https://www.instagram.com/alles_auf_aktien/ Disclaimer: Die im Podcast besprochenen Aktien und Fonds stellen keine spezifischen Kauf- oder Anlage-Empfehlungen dar. Die Moderatoren und der Verlag haften nicht für etwaige Verluste, die aufgrund der Umsetzung der Gedanken oder Ideen entstehen. Hörtipps: Für alle, die noch mehr wissen wollen: Holger Zschäpitz können Sie jede Woche im Finanz- und Wirtschaftspodcast "Deffner&Zschäpitz" hören. +++ Werbung +++ Du möchtest mehr über unsere Werbepartner erfahren? Hier findest du alle Infos & Rabatte! https://linktr.ee/alles_auf_aktien Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutz: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html

In today's hyper-connected world, we have more ways to communicate than ever before — yet meaningful human connection is becoming increasingly rare.In this solo episode, Penny Zenker explores what she calls the growing “connection deficit” and why it is one of the biggest challenges facing leaders and organizations today.Despite constant messaging, video calls, and social media interactions, many teams feel more disconnected than ever. With workplace disengagement reaching record levels, leaders must rethink how they create trust, belonging, and meaningful collaboration.Penny shares practical examples of how organizations like Shopify, Atlassian, and GitLab intentionally design connection into their cultures — and how leaders can do the same.In this episode, you'll learn:• Why we are experiencing a modern connection deficit • How shallow communication is impacting employee engagement and leadership • The key psychological drivers behind real human connection at work • Why trust and vulnerability accelerate execution and collaboration • Simple practices leaders can use to design deeper connections in meetings and teamsAs technology and AI continue to reshape the workplace, the organizations that succeed will be the ones that intentionally cultivate human connection, trust, and purpose.Because in a digital world, connection doesn't happen by accident — it must be designed.

Market update for Wednesday March 4, 2026Check out the Public app for incredible investing tools and to support the show (⁠LINK⁠)Follow us on Instagram (⁠@TheRundownDaily⁠) for bonus content and instant reactions.In today's episode:OpenAI looks toward NATO defense deal Tesla receives robotaxi driven upgrade from Bank of AmericaRoss Stores provides upbeat 2026 outlook after holiday earnings beat Gitlab shares plummet amid sales slowdown amid AI eraFun Fact: Mark Zuckerberg buys the most expensive home in Miami

In this episode of The Cybersecurity Defenders Podcast, we discuss some intel being shared in the LimaCharlie community.GitLab's Threat Intelligence Team published detailed findings on North Korean activity associated with the Contagious Interview campaign and broader IT worker operations.A financially motivated, Russian-speaking threat actor used generative AI tools to compromise more than 600 Fortinet FortiGate firewall instances between January and February, according to Amazon Web Services.Cisco has released emergency patches for a critical zero-day vulnerability in its Catalyst SD-WAN products that has been actively exploited in the wild.Citrini Research presents a forward-looking scenario framed as a June 2028 macro memo describing a “Global Intelligence Crisis” triggered by abundant AI-driven intelligence.Support our show by sharing your favorite episodes with a friend, subscribe, give us a rating or leave a comment on your podcast platform.This podcast is brought to you by LimaCharlie, maker of the SecOps Cloud Platform, infrastructure for SecOps where everything is built API first. Scale with confidence as your business grows. Start today for free at limacharlie.io.

English Edition (ByteSized): In this first episode of the new ByteSized dRTP season, sponsored by the STEP-UP programme from the EPSRC (UK) you'll meet Richard Acton. Richard created a tool to help you keep track of all the steps you should take to make your software shareable and reproducible. With checklists, built right into your GitLab, GitHub repo. Linkshttps://rsspdc.org/ home page for the checklistshttps://rsspdc.gitlab.io/slides/bytesize-workshop_2026-02-26.html#/outline https://gitlab.com/rsspdc/checklists download the checklists MD files from herehttps://www.software.ac.uk/news/software-management-plans Software management plan (SMP) from the Software Sustainability Institutehttps://www.france-grilles.fr/presoft-software-management-plans-model/ another template of a SMP from Teresa Gomez-Diaz (Paris, France) - PRESOFThttps://hal.science/hal-01802565v1 I'd like to thank the STEP-UP project for their support of this podcast. STEP-UP is a collaboration between Imperial College London, King's College London, University College London and the University of Westminster. STEP-UP is funded by the Engineering and Science and Physical Research Council in the UK. Get in touchThank you for listening! Merci de votre écoute! Vielen Dank für´s Zuhören! Contact Details/ Coordonnées / Kontakt: Email mailto:peter@code4thought.org UK RSE Slack (ukrse.slack.com): @code4thought or @piddie Bluesky: https://bsky.app/profile/code4thought.bsky.social LinkedIn: https://www.linkedin.com/in/pweschmidt/ (personal Profile)LinkedIn: https://www.linkedin.com/company/codeforthought/ (Code for Thought Profile) This podcast is licensed under the Creative Commons Licence: https://creativecommons.org/licenses/by-sa/4.0/

(Presented by TLPBLACK: High-fidelity threat intelligence and research tools for modern security teams. From curated Passive DNS and real-time C2 monitoring to actionable IOC feeds and daily malware samples, we help defenders detect, hunt, and disrupt threats faster, with seamless integration into SIEM and SOAR workflows.) Three Buddy Problem - Episode 86: We dig into GitLab's explosive look at North Korea's “Contagious Interview” APT operation, the scale of fake IT worker infiltration, and what it means for companies chasing cheap talent. Plus, a fresh batch of already-exploited Ivanti and Dell zero-days, the return of Apple's shutdown logs, and thoughts on addictive AI coding agents affecting human purpose. Cast: Juan Andres Guerrero-Saade, Ryan Naraine and Costin Raiu.

AGENDA: 04:14 Anthropic's $30B Raise at $380B 06:18 Why SaaS Stocks Keep Getting Crushed 18:15 Wall Street's New Religion: AI Replaces Headcount  22:42 The Bear Case for Shopify: What Could Go Wrong? 31:51 Replit and Lovable are Proof Figma Missed Out: Figma; Buy or Sell?  48:42 Stripe Raises at $140BN: Is Stripe Wildly Overvalued or Adyen Undervalued?  54:36 OpenAI Buys OpenClaw 01:06:28 Thrive's $10B Growth Fund 01:09:10 Arif Janmohamed Leaves Lightspeed for New Firm 01:17:12 Workday's Founder Returns as CEO: Will it Work?  01:20:34 Which Founder Returns Next: HubSpot, Twilio, Gitlab? 01:24:03 Is Monday.com a Screaming Buy? 01:28:25 Jason and Harry Bet $200,000  

Live recording of the fortnightly podcast Design Systems WTF (back for season two!), where Luke Murphy and Michelle Chin attempt to combat all the amazing wtf in design systems. In each episode, they answer a single question around design system troubles with a Q&A from the live audience.Design systems kill creativity, right? We've heard that said so many times. But are we actually taking the time to inject joy into the system itself? Not only considering it as a part of the process for what we include in the system, but also in how we do documentation, release notes, and general communication around the design system? Or controversially... is it even important?Show notesLuke's article on delighting in design systemsSociete Generale release notes articleAaron Walter's Heirarchy of User NeedsThe socks component in Gitlab's Pyjamas design system

AI coding tools are writing more code than ever, but your software isn't shipping any faster. Welcome to the AI Paradox and the solution, intelligent orchestration.Bill Staples, CEO of GitLab, explains why AI-accelerated coding is actually creating massive downstream bottlenecks in code reviews, security checks, and deployment, and why adding more AI tools only makes the problem worse. GitLab's solution: intelligent orchestration across the entire software development lifecycle.You'll discover:✅ The "AI Paradox:" why faster coding isn't translating into faster software delivery✅ How tool fragmentation and context-switching are killing developer productivity✅ Why agents that thrive on context fail when your tools are siloed✅ The "inner loop architecture" that makes AI agents 40% more accurate and 25% faster✅ How GitLab's intelligent orchestration approach combines workflows, context, and guardrails✅ Why mid-level developers are about to become strategic orchestrators (not just coders)✅ The exact metrics CIOs should track, and why "lines of code" is the wrong one✅ First steps: audit, consolidate, and pilot before going all-in on AI⏱️ TIMESTAMPS0:00 The AI Paradox: Why faster coding doesn't mean faster delivery1:10 How tool fragmentation creates developer bottlenecks3:40 Why AI agents make complexity worse (not better)5:12 Solving the AI automation problem: people, process, and technology6:36 Inner loop architecture: co-locating agents and data9:14 Intelligent orchestration: workflows, context, and guardrails10:32 How GitLab's knowledge graph supercharges agent accuracy12:49 Universal guardrails for humans and AI agents13:39 Real-world results: 2-3x more merge requests, pipeline fixes in minutes15:00 Common threads driving customer success16:36 How AI transforms the mid-level developer's role19:06 Advice for CIOs and CTOs putting this into practice20:49 First steps: audit, measure, and pilot22:45 Core metrics to evaluate AI's real value25:02 Wrap-up

AI coding assistants are boosting developer productivity, but most enterprises aren't shipping software any faster. GitLab CEO Bill Staples says the reason is simple: coding was never the main bottleneck. After speaking with more than 60 customers, Staples found that developers spend only 10–20% of their time writing code. The remaining 80–90% is consumed by reviews, CI/CD pipelines, security scans, compliance checks, and deployment—areas that remain largely unautomated. Faster code generation only worsens downstream queues.GitLab's response is its newly GA'ed Duo Agent Platform, designed to automate the full software development lifecycle. The platform introduces “agent flows,” multi-step orchestrations that can take work from issue creation through merge requests, testing, and validation. Staples argues that context is the key differentiator. Unlike standalone coding tools that only see local code, GitLab's all-in-one platform gives agents access to issues, epics, pipeline history, security data, and more through a unified knowledge graph.Staples believes this platform approach, rather than fragmented point solutions, is what will finally unlock enterprise software delivery at scale. Learn more from The New Stack about the latest around GitLab and AI: GitLab Launches Its AI Agent Platform in Public BetaGitLab's Field CTO Predicts: When DevSecOps Meets AIJoin our community of newsletter subscribers to stay on top of the news and at the top of your game. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Microsoft Patches Four Azure Vulnerabilities (three critical) https://msrc.microsoft.com/update-guide/vulnerability Evaluating and mitigating the growing risk of LLM-discovered 0-days https://red.anthropic.com/2026/zero-days/ Gitlab AI Gateway Vulnerability CVE-2026-1868 https://about.gitlab.com/releases/2026/02/06/patch-release-gitlab-ai-gateway-18-8-1-released/

DOGE staff face scrutiny over possible Hatch Act violations. GitLab fixes a serious 2FA bypass. North Korean hackers target macOS developers through Visual Studio Code. Researchers say the VoidLink malware may be largely AI-built. MITRE rolls out a new embedded systems threat matrix. Oracle drops a massive patch update. Minnesota DHS reports a breach affecting 300,000 people. Germany looks to Israel for cyber defense lessons. A major illicit marketplace goes dark. Our guest is Ashley Jess, Senior Intelligence Analyst from Intel 471, with a “crash course” on underground cyber markets. And auditors emerge as an unlikely line of cyber defense. Remember to leave us a 5-star rating and review in your favorite podcast app. Miss an episode? Sign-up for our daily intelligence roundup, Daily Briefing, and you'll never miss a beat. And be sure to follow CyberWire Daily on LinkedIn. CyberWire Guest Today we have Ashley Jess, Senior Intelligence Analyst from Intel 471, sharing a “crash course” on how underground cyber markets and emerging trends. Selected Reading Trump administration concedes DOGE team may have misused Social Security data (POLITICO) GitLab warns of high-severity 2FA bypass, denial-of-service flaws (Bleeping Computer) North Korean Hackers Target macOS Developers via Malicious VS Code Projects (SecurityWeek) Voidlink Linux Malware Was Built Using an AI Agent, Researchers Reveal (Infosecurity Magazine) MITRE Launches New Security Framework for Embedded Systems (SecurityWeek) Oracle's First 2026 CPU Delivers 337 New Security Patches (SecurityWeek) Minnesota Agency Notifies 304,000 of Vendor Breach (GovInfo Security) Germany and Israel Pledge Cybersecurity Alliance (BankInfo Security) $12B Scam Market Tudou Guarantee Shuts Down (GovInfo Security) Research reveals a surprising line of defence against cyber attacks: accountants (The Conversation) Share your feedback. What do you think about CyberWire Daily? Please take a few minutes to share your thoughts with us by completing our brief listener survey. Thank you for helping us continue to improve our show. Want to hear your company in the show? N2K CyberWire helps you reach the industry's most influential leaders and operators, while building visibility, authority, and connectivity across the cybersecurity community. Learn more at sponsor.thecyberwire.com. The CyberWire is a production of N2K Networks, your source for strategic workforce intelligence. © N2K Networks, Inc. Learn more about your ad choices. Visit megaphone.fm/adchoices

Connect to John Gilroy on LinkedIn   https://www.linkedin.com/in/john-gilroy/ Want to listen to other episodes? www.Federaltechpodcast.com Today, we have an experienced tech veteran, Bob Stevens from GitLab, offering insights on how he sees the federal government overcoming three main technology challenges in 2026. Challenge ONE:   Software improvement on scale. Stevens observed that everyone has seen AI's ability to review code. It has passed the basic phase, and now, in 2026, it cannot only review code but also identify security vulnerabilities, ensure compliance, and even generate documentation. This means that older, expensive-to-maintain systems can be transitioned to more flexible, economical cloud models. Challenge TWO:   Going away from reacting. The word "continuous" has been the goal for cyber defenders for the past several years. Fortunately, AI is allowing that noble goal to be put into practice. When applied appropriately, newer technology can achieve lower breach rates and faster threat response times. Challenge THREE:   emergence of a "universal" developer. Traditionally, requirements would be gathered by an intermediary and then translated into instructions for software developers. Stevens shows how newer AI-based approaches can eliminate that intermediary step. In other words, a pilot can precisely describe what they want in an avionics system, and the developers can work from that description. That means solving domain-specific problems with traditional development skills. Ideally, subject matter experts directly translate their knowledge into functional software systems. Some call this the "universal" developer approach. Stevens emphasized the importance of AI, security, and flexibility for future developers. GitLab's DevSecOps platform integrates AI across the entire software development process.

We're joined by Sid Sijbrandij, founder of GitLab who led the all-in-one coding platform all the way to IPO. In late 2022, Sid discovered that he had bone cancer. That started a journey he's been on ever since... a journey that he shares with us in great detail. Along the way, Sid continued founding companies including Kilo Code, an all-in-one agentic engineering platform, which he also tells us all about.

We're joined by Sid Sijbrandij, founder of GitLab who led the all-in-one coding platform all the way to IPO. In late 2022, Sid discovered that he had bone cancer. That started a journey he's been on ever since... a journey that he shares with us in great detail. Along the way, Sid continued founding companies including Kilo Code, an all-in-one agentic engineering platform, which he also tells us all about.

Topics covered in this episode: Has the cost of building software just dropped 90%? More on Deprecation Warnings How FOSS Won and Why It Matters Should I be looking for a GitHub alternative? 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 10am 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. HEADS UP: We are taking next week off, happy holiday everyone. Michael #1: Has the cost of building software just dropped 90%? by Martin Alderson Agentic coding tools are collapsing “implementation time,” so the cost curve of shipping software may be shifting sharply Recent programming advancements haven't been that great of a true benefit: Cloud, TDD, microservices, complex frontends, Kubernetes, etc. Agentic AI's big savings are not just code generation, but coordination overhead reduction (fewer handoffs, fewer meetings, fewer blocks). Thinking, product clarity, and domain decisions stay hard, while typing and scaffolding get cheap. Is it the end of software dev? Not really, see Jevons paradox: when production gets cheaper, total demand can rise rather than spending simply falling. (Historically: the efficiency of coal use led to the increased consumption of coal) Pushes back on “only good for greenfield” by arguing agents also help with legacy code comprehension and bug-fixing. I 100% agree. #Legacy code for the win. Brian #2: More on Deprecation Warnings How are people ignoring them? yep, it's right in the Python docs: -W ignore::DeprecationWarning Don't do that! Perhaps the docs should give the example of emitting them only once -W once::::DeprecationWarning See also -X dev mode , which sets -W default and some other runtime checks Don't use warn, use the @warnings.deprecated decorator instead Thanks John Hagen for pointing this out Emits a warning It's understood by type checkers, so editors visually warn you You can pass in your own custom UserWarning with category mypy also has a command line option and setting for this --enable-error-code deprecated or in [tool.mypy] enable_error_code = ["deprecated"] My recommendation Use @deprecated with your own custom warning and test with pytest -W error Michael #3: How FOSS Won and Why It Matters by Thomas Depierre Companies are not cheap, companies optimize cost control. They do this by making purchasing slow and painful. FOSS is/was a major unlock hack to skip procurement, legal, etc. Example is months to start using a paid “Add to calendar” widget! It “works both ways”: the same bypass lowers the barrier for maintainers too, no need for a legal entity, lawyers, liability insurance, or sales motion. Proposals that “fix FOSS” by reintroducing supply-chain style controls (he name-checks SBOMs and mandated processes) risk being rejected or gamed, because they restore the very friction FOSS sidesteps. Brian #4: Should I be looking for a GitHub alternative? Pricing changes for GitHub Actions The self-hosted runner pricing change caused a kerfuffle. It's has been postponed But… if you were to look around, maybe pay attention to These 4 GitHub alternatives are just as good—or better Codeburg, BitBucket, GitLab, Gitea And a new-ish entry, Tangled Extras Brian: End of year sale for The Complete pytest Course Use code XMAS2025 for 50% off before Dec 31 Writing work on Lean TDD book on hold for holidays Will pick up again in January Michael: PyCharm has better Ruff support now out of the box, via Daniel Molnar This is from the release notes of 2025.3: "PyCharm 2025.3 expands its LSP integration with support for Ruff, ty, Pyright, and Pyrefly.” If you check out the LSP section it will land you on this page and you can go to Ruff. The Ruff doc site was also updated. Previously it was only available external tools and a third party plugin, this feels like a big step. Fun quote I saw on ExTwitter: May your bug tracker be forever empty. Joke: Try/Catch/Stack Overflow Create a super annoying linkedin profile - From Tim Kellogg, submitted by archtoad

Während Dietmar Deffner in Dubai die Sonne genießt, hat sich Holger Zschäpitz das „schwäbische Schlitzohr“ der Tech-Szene ins Studio geholt: Thomas Rappold, Silicon-Valley-Investor und Buchautor, redet Tacheles über den aktuellen KI-Hype und überrascht mit einer gewagten These: Für ihn gehört der Börsenliebling Nvidia 2026 nicht mehr zu den Top-Favoriten. Stattdessen erklärt Rappold, warum Alphabet (Google) für ihn das bessere Investment ist und wieso er jetzt massiv auf verprügelte Software-Aktien wie GitLab oder DocuSign setzt. Außerdem: Warum ein US-Steuergesetz („One Beautiful Bill“) den Tech-Boom 2026 neu entfachen könnte und welche Rolle „langweilige“ Aktien wie Visa oder Siemens Healthineers in seinem Depot spielen. Eine Episode voller konkreter Aktien-Ideen – von der „Everything-App“ für die persönlichen Finanzen bis zum Metaverse-Play Roblox. DEFFNER & ZSCHÄPITZ sind wie das wahre Leben. Wie Optimist und Pessimist. Im wöchentlichen WELT-Podcast diskutieren und streiten die Journalisten Dietmar Deffner und Holger Zschäpitz über die wichtigen Wirtschaftsthemen des Alltags. Schreiben Sie uns an: wirtschaftspodcast@welt.de Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutzerklärung: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html

AI platform selection remains uncertain as frontier models rapidly evolve. Dave Steer, Chief Marketing Officer at Webflow, brings two decades of scaling experience at GitLab, Cloudflare, and other category-defining companies to discuss navigating the current AI landscape. He argues that context-aware platforms built on top of commodity frontier models will determine competitive advantage, with marketing workflow platforms like Webflow positioning to compete against developer-focused tools like GitHub and GitLab.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Darren Murph, a leading voice on distributed work and former leader at GitLab, Zillow, and Andela returned to the show.We dug into the remote first maturity scale, the four-pillar operating model (knowledge, project, self, performance), and how to build an “org brain.”---- Sponsor Links:

B2B tech marketing requires constant adaptation to survive industry disruption. Dave Steer, Chief Marketing Officer at Webflow, brings two decades of scaling experience from GitLab, Cloudflare, and other category-defining companies. He explains why successful marketers treat their strategies like stock portfolios with both long-term anchors and rapid pivots. Steer outlines how experimentation frameworks help teams adapt quickly when market conditions shift unexpectedly.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this week's show Patrick Gray and Adam Boileau discuss the week's cybersecurity news, including: FBI intervenes in Scattered Spider Salesforce leaksite Clop loots Oracle E-Biz deployments Plus so much more data extortion.. At least it's not ransomware … we guess? The US still can't decide who's gonna be in charge of NSA & Cybercom Cambodian scam compounds get sanctioned and $15b in crypto is seized NSO gets sold for pocket-lint-grade money Bugs! Redis CVSS 10, Ivanti, Crowdstrike and… Internet Explorer?! zeroday?! In the wild?!!!? This week's episode is sponsored by Stairwell. Founder Mike Wiacek talks about how Stairwell brings VirusTotal-like visibility to private files, and about integrating the insights that brings into your SOC workflow. This episode is also available on Youtube. Show notes FBI takedown banner appears on BreachForums site as Scattered Spider promotes leak | The Record from Recorded Future News Dozens of Oracle customers impacted by Clop data theft for extortion campaign | CyberScoop Well, Well, Well. It's Another Day. (Oracle E-Business Suite Pre-Auth RCE Chain - CVE-2025-61882) Clop is a Big Fish, But Not Worth Hunting - Risky Business Media ShinyHunters Wage Broad Corporate Extortion Spree – Krebs on Security The company Discord blamed for its recent breach says it wasn't hacked Qantas confirms cybercriminals released stolen customer data | The Record from Recorded Future News Red Hat confirms breach of GitLab instance, which stored company's consulting data | CyberScoop Risky Bulletin: Microsoft revamps Edge's "IE Mode" after zero-day attacks - Risky Business Media Teenagers arrested in England over cyberattack on nursery chain Kido | The Record from Recorded Future News Acting US Cyber Command, NSA chief won't be nominated for the job, sources say | The Record from Recorded Future News Layoffs, reassignments further deplete CISA | Cybersecurity Dive Trump's scandalous directive to AG Pam Bondi reached the public by accident Feds sanction Cambodian conglomerate over cyber scams, seize $15 billion from chairman | The Record from Recorded Future News US Congress committee investigating Musk-owned Starlink over Myanmar scam centres | Myanmar | The Guardian Satellites Are Leaking the World's Secrets: Calls, Texts, Military and Corporate Data | WIRED Netherlands invokes special powers against Chinese-owned semiconductor company Nexperia | The Record from Recorded Future News Spyware maker NSO Group confirms acquisition by US investors | TechCrunch Apple Announces $2 Million Bug Bounty Reward for the Most Dangerous Exploits | WIRED Wiz Finds Critical Redis RCE Vulnerability: CVE‑2025‑49844 | Wiz Blog SonicWall admits attacker accessed all customer firewall configurations stored on cloud portal | CyberScoop SonicWall SSLVPN devices compromised using valid credentials | Cybersecurity Dive Issues Affecting CrowdStrike Falcon Sensor for Windows ZDI Drops 13 Unpatched Ivanti Endpoint Manager Vulnerabilities - SecurityWeek Jaguar Land Rover launches phased restart at factories after cyber-attack | Jaguar Land Rover | The Guardian Windows 10 support ends today — here's who's affected and what you need to do