Podcasts about benchmarks

SpaceX startet mit einem ordentlichen Pop in den Handel. Tausende Mitarbeiter werden zu Millionären, Founders Fund und Andreessen Horowitz vermelden Rekord-Returns. Anthropic launcht Fable 5 und das Mythos-Modell für Testpartner. OpenAI plant laut Wall Street Journal drastische Preissenkungen für den User-Krieg mit Anthropic. China plant $300 Mrd. für nationalen KI-Ausbau über fünf Jahre. Xiaomi MiMo Code schlägt Claude Code in den gängigen Benchmarks. OpenAI übernimmt das Kieler Startup ONA, Mistral kauft das Linzer Emmi AI für eine Industrie-KI-Plattform und verhandelt selbst eine $20-Mrd.-Bewertung. Dario Amodei mit neuem Essay zur AI-Exponential-Politik. Oracle Earnings, Prometheus von Jeff Bezos bei $41 Mrd. Die Trump-Familie hat $2,3 Mrd. mit Krypto eingestrichen. Palantir verliert vor dem Zürcher Handelsgericht gegen die Zeitschrift Republik. Neura Robotics raised $1,4 Mrd. mit Tether als Lead. Landgericht München: Google haftet für seine AI-Overviews.  Unterstütze unseren Podcast und entdecke die Angebote unserer Werbepartner auf ⁠⁠⁠⁠⁠⁠doppelgaenger.io/werbung⁠⁠⁠⁠⁠⁠. Vielen Dank!  Philipp Glöckler und Philipp Klöckner sprechen heute über: (00:00:00) SpaceX-IPO (00:08:04) Mitarbeiter-Millionäre (00:11:51) OpenAI/Anthropic-IPO-Outlook (00:15:31) Elon-Puppe vor der Nasdaq (00:16:13) Anthropic Fable 5 & Mythos 5 (00:19:54) OpenAI Preiskrieg (00:27:27) Token-Wert pro Abo (00:30:30) Messi für ChatGPT (00:34:48) China $300 Mrd. KI-Plan (00:37:31) Xiaomi MiMo Code (00:39:46) OpenAI kauft ONA (00:42:54) Anthropic: AI Exponential Policy (00:46:53) Oracle Earnings (00:48:07) Mistral kauft Emmi AI (00:49:08) Prometheus von Bezos (00:50:48) Trump Phone (00:51:22) Waymo Premier (00:55:40) Google Trade-Worker (00:57:08) Anthropic Claude Corps (00:58:37) Trump-Krypto-Scam (00:59:35) The Platform Group (01:03:48) Palantir vs. Republik (01:05:48) Mistral $20 Mrd. Runde (01:07:07) Neura Robotics Series C (01:10:47) NYT: China und Robotik (01:13:19) Google haftet für AI-Overviews Shownotes SpaceX-IPO zieht $70 Mrd. an Retail-Orders - bloomberg.com Founders Fund + Andreessen: Rekord-Returns aus SpaceX-IPO - bloomberg.com SpaceX Proteste - xcancel.com Anthropic launcht Claude Fable 5 & Mythos 5 - wired.com OpenAI plant drastische Preissenkungen für User-Krieg mit Anthropic - wsj.com Bitte manuell prüfen (petergostev-Post) - xcancel.com SemiAnalysis - xcancel.com China plant $295 Mrd. für nationalen KI-Ausbau - bloomberg.com ONA: Kieler KI-Startup raised - linkedin.com Anthropic: Policy on the AI Exponential - anthropic.com Oracle Q4 Earnings - cnbc.com Mistral übernimmt Emmi AI für Industrie-KI-Plattform - handelsblatt.com Prometheus: Bezos' Industrial-AI-Startup - axios.com Teardown: Trump Phone ist HTC U24 Pro in Gold - de.ifixit.com Waymo launcht Loyalty-Programm mit 10% Cashback - techcrunch.com Google launcht Trade-Worker-Initiative für KI - axios.com Daniela Amodei startet Anthropics Claude Corps - apnews.com Xiaomi MiMo Code schlägt Claude Code bei 200-Step-Tasks - venturebeat.com Trump-Crypto-Playbook: Family wins, Investors don't - reuters.com The Platform Group - manager-magazin.de Einstweilige Verfügung: The Platform Group vs. Manager Magazin - lhr-law.de Palantir - ft.com Mistral verhandelt $20 Mrd. Bewertung - bloomberg.com Bitte manuell prüfen (dreger-Post) - linkedin.com Neura Robotics schließt Rekord-Series-C - neura-robotics.com Chinas Humanoid-Robot-Schub - nytimes.com Deutsches Gericht: Google haftbar für AI-Overviews - thenextweb.com

Thanks to our partners Promotive, WickedFile, Maverick Shop Owners, and OverdryveYour technicians got more productive in 2025. Your labor rate went up. Your parts margins improved. So why is the average shop owner keeping almost exactly the same percentage of every dollar as they did the year before?The answer is hiding in your effective labor rate — and most shop owners haven't looked at it once.In this episode, Hunt Demarest breaks down the headline findings from Paar Melis & Associates' 2026 Auto Shop Benchmark Report — the largest study of its kind, built from more than 200 real shop locations across the country. From average repair order trends to technician productivity, overhead creep, benefits adoption, pay structure breakdowns, shop management software rankings, and the labor rate shame list nobody wants to be on, this is the financial state-of-the-industry episode you didn't know you needed. And it's only Part One.What You'll Learn(00:00) Intro — the 2026 Benchmark Report is live and how to get your free copy(03:16) Who made this report possible — methodology, participation, and what Paar Melis clients get that nobody else does(05:30) How to read benchmark numbers without misleading yourself — context, outliers, and the ARO trap(13:15) Sales are up 10-11% — but how much of that is real production vs. a labor rate increase you already gave yourself?(16:20) Productivity jumped from 47% to 55% — so why didn't net profit follow?(18:30) Effective labor rate: the silent margin killer hiding in plain sight in 2025(27:30) Benefits adoption hits an all-time high: 73% of shops now offer health insurance(29:30) Retirement plans, tool reimbursement, Trump Accounts, and the fringe benefits arms race(30:45) Four-day work weeks and non-cash comp — how shops are winning the talent war without raising base pay(34:30) Good management makes money, not good pay plans(36:30) 83% of shops are doing digital vehicle inspections — Hunt thought it would be closer to 100%(37:30) Shop management software rankings: Tekmetric at 56%, Mitchell likely on the way out, Shopware and Protractor tied for third(40:30) The labor rate shame list — 11% of shops haven't raised their rate in 18 months or moreIf you're ready to stop guessing where your numbers stand, start benchmarking against 200+ real shops across the country, and finally understand why doing more work doesn't always mean making more money — this episode is essential listening.Get the FREE 2026 Auto Shop Benchmark Report: https://hubs.ly/Q04j-grh0Thanks to our partner, PromotivePromotive has over 40 years of recruiting and automotive experience. If you need qualified technicians and service advisors and want to offload the heavy lifting, visit https://gopromotive.com/Thanks to our partner, WickedFileTurn chaos into clarity with WickedFile, the AI for auto repair shops. Transform invoices into insights, protect cash flow, and stop losing parts, cores, or credits to maximize your bottom line. visit https://info.wickedfile.com/Thanks to our partner, Maverick Shop OwnersYou're working on growing a more profitable shop - that's critical. That's exactly what the 24-video Blueprint course by Maverick Shop Owners addresses - customers, sales, profit, people, systems, and freedom. Get free access for our listeners only at https://maverickshopowners.com/blueprintThanks to our partner, OverdryveOverdryve is your AI-powered marketing operating system. It predicts slow weeks before they happen, automatically launches revenue-driving campaigns, tracks ROI down to the dollar, and optimizes performance in real time. Visit https://overdryvemarketing.com/Paar Melis and Associates – Accountants Specializing in Automotive RepairVisit us Online: www.paarmelis.comEmail Hunt: podcast@paarmelis.comText Paar Melis @ 301-307-5413Download a Copy of My Books Here:Beyond the Bays: A Financial Playbook for Auto Repair Shop OwnersWrenches to Write-OffsYour Perfect Shop The Automotive Repair Podcast Network: https://automotiverepairpodcastnetwork.com/Remarkable Results Radio Podcast with Carm Capriotto: Advancing the Aftermarket by Facilitating Wisdom Through Story Telling and Open DiscussionDiagnosing the Aftermarket A to Z with Matt Fanslow: From Diagnostics to Metallica and Mental Health, Matt Fanslow is Lifting the Hood on Life.The Weekly Blitz with Chris Cotton: Weekly Inspiration with Business Coach Chris Cotton from AutoFix - Auto Shop Coaching.Speak Up! Effective Communication with Craig O'Neill: Develop Interpersonal and Professional Communication Skills when Speaking to Audiences of Any Size.Business by the Numbers with Hunt Demarest: Understand the Numbers of Your Business with CPA Hunt Demarest.The Auto Repair Marketing Podcast with Kim and Brian Walker: Marketing Experts Brian & Kim Walker Work with Shop Owners to Take it to the Next Level.

US President Trump said they are negotiating regarding Iran and a victory will happen very soon; he stated they will declare total victory in two weeks; Brent Aug'26 -1.1%Trump was said to have warned Israeli PM Netanyahu that if he turns escalation into war, he will be left alone against Iran. He also told the Israeli PM that if he does not get an Iran deal within a few days, he would lead the strikes on Iran.A top Iranian official casted doubt on a deal being imminently reached between the US and Iran, telling CNN that major roadblocks persist on issues like Iran's nuclear program and uranium enrichment.Pentagon accused several Chinese tech-giants (Alibaba, Baidu, BYD, Tencent) of aiding the Chinese military.APAC stocks traded mixed; European equity futures are indicative of a slightly weaker open.DXY is incrementally lower with G10s broadly firmer, and the Kiwi outperforms.Looking ahead, highlights include German Balance of Trade, Exports, Imports (Apr), Mexican Inflation (May), US ADP Weekly Change, Exports/Imports, Atlanta Fed GDP, Existing Home Sales (May), Wholesale Inventories (Apr), Canadian Exports/Imports (Apr), EIA STEO (Jun), Comments from ECB President Lagarde, Supply from Netherlands, Germany & US.Read the full report covering Equities, Forex, Fixed Income, Commodites and more on Newsquawk

120 Millionen Euro - das ist die neue Bewertung des österreichischen AI-Startups Fonio, das sich in kurzer Zeit zum Marktführer für KI-Telefonie aufgeschwungen hat. Jetzt folgt die neue FInanzierungsrunde, die 14,6 Millionen Euro schwer ist und dazu dient, das Geschäft in Europa und den USA auszubauen.Wie das alles gelaufen ist und was am Plan steht, das verrät uns heute im Podcast CEO und Mitgründer Daniel Keinrath, der Fonio erst 2024 gemeinsam mit Matthias Gruber gründete. Die Themen:

Bryan Anthony Davis discusses his hope for pass catchers in 2026. Check out this and more on his solo show, BAD Language. Steel Curtain Network is courtesy of the Fans First Sports Network. Check out Meinelschmidt Distillery at meineldistillery.com and use the code SCNJUN to save 10% at checkout! Learn more about your ad choices. Visit megaphone.fm/adchoices

Over the weekend, Israel struck Lebanese targets despite US President Trump urging Israeli PM Netanyahu to refrain from strikes. In retaliation, Iran launched missiles at Israel.US President Trump has ordered Israel and Iran to immediately stop shooting. Crude futures jump (Brent Aug'26 +4.1%) following the renewed strikes, weighing on fixed income benchmarks.European bourses slump after renewed Middle East strikes and further tech selloff, while US equity futures rebound from last week's selloffDXY rangebound; antipodeans outperform while USD/JPY slips back below 160.00 handle. Looking ahead, highlights include US NY Fed SCE (Jun), Apple WWDC Keynote (June 8-12).Read the full report covering Equities, Forex, Fixed Income, Commodites and more on Newsquawk

https://novacut.ai/  https://genaimeetup.com/  Anthropic has officially closed a $65 billion Series H at a $965 billion valuation, nearly 2.5x its valuation from just 100 days ago. Meanwhile, funding is flowing across the ecosystem: Frameworks AI at $15B, Baseten at $11B, OpenRouter's $113M Series B, and Cognition AI's $1B Series D. NVIDIA went on an open-source super week with Nemotron 3 Ultra, Cosmos 3, and Nemotron 3.5 ASR. Microsoft dropped 5 new MAI models. Google released Gemma 4 12B, and Anthropic shipped Opus 4.8. On the benchmarks front, DeepSWE crowns GPT-5.5 as the leader in long-horizon coding tasks, while ITBench shows even frontier models struggle with real-world SRE incidents — Claude Opus 4.7 tops out at just 47%. Plus: Cloudflare acquires VoidZero to build the future of AI-native edge development, and Google is paying SpaceX $920M/month for compute. Topics covered: • Anthropic's $65B Series H and path to $1T • Fireworks AI, Baseten, OpenRouter & Cognition funding rounds • Microsoft's 5 new MAI models • NVIDIA's open-source super week (Nemotron, Cosmos 3) • MiniMax M3, Gemma 4 12B, JetBrains Mellum2, Opus 4.8 • DeepSWE benchmark: GPT-5.5 leads long-horizon coding • ITBench: Frontier models under 50% on real SRE tasks • Cloudflare + VoidZero for AI-native edge dev • Google's $920M/month SpaceX compute deal #AI #Anthropic #NVIDIA #OpenAI #AInews #TechNews #LLM     Funding rounds Anthropic formally confirmed the closure of its $65 billion Series H funding round at a post-money valuation of $965 billion. This represents a 2.5-fold increase over its $380 billion Series G valuation from February 2026, adding $585 billion in value in approximately 100 days https://www.anthropic.com/news/series-h  Frameworks AI raising at 15B valuation representing a near fourfold increase from its $4 billion Series C valuation recorded in October 2025 processing 15 trillion tokens daily for major production clients including Cursor, Notion, and Perplexity https://finance.yahoo.com/sectors/technology/articles/fireworks-ai-eyes-15-billion-174609357.html Baseten is raising 1B at 11B valuation annualized revenue, which skyrocketed from $200 million to $600 million over a single quarter https://techstartups.com/2026/05/26/ai-inference-startup-baseten-in-talks-to-raise-1-billion-at-11-billion-valuation/  OpenRouter has secured a $113 million Series B funding OpenRouter has experienced exponential traffic growth, with weekly production throughput expanding fivefold from 5 trillion to 25 trillion tokens over a six-month horizon https://www.businesswire.com/news/home/20260526953416/en/OpenRouter-Raises-%24113-Million-CapitalG-led-Series-B-as-Weekly-Volume-Explodes-to-25T-Tokens  Further up the stack: Cognition AI secured a $1 billion Series D round led by Lux Capital and 8VC https://cognition.ai/blog/series-d   Model Releases MAI models: MAI-Code-1-Flash: A 5-billion active parameter model optimized for ultra-low latency within GitHub Copilot and VS Code. MAI-Image-2.5: A high-fidelity image generation model ranking third on global image evaluation arenas, outperforming competing architectures like Nano Banana Pro. MAI-Transcribe-1.5: A multi-lingual speech processing engine offering fivefold speed improvements across 43 languages. MAI-Voice-2: Natural audio and voice generation across 15 languages, available at a highly competitive price point. Web IQ: A search-grounding API engineered to directly compete with Perplexity. https://microsoft.ai/models/    https://www.peoplematters.in/news/ai-and-emerging-tech/uber-imposes-dollar1500-monthly-ai-spending-limit-on-employees-amid-rising-costs-50073    Nvidia has executed an "Open-Source Super Week," positioning itself as a dominant software and model publisher: Nemotron 3 Ultra (best US open source open weights model but behind china): A massive 550-billion parameter MoE (55 billion active) designed with a 1-million token context window, optimized specifically for high-throughput, cyclical agent loops. It achieved peak throughput rates of 400 tokens per second on day-zero optimized clusters. Cosmos 3: A physical AI world-modeling framework comprising 16-billion Nano and 64-billion Super variants. Built on a Mixture-of-Transformers (MoT) architecture, Cosmos 3 natively binds textual, visual, auditory, and physical kinetic vectors. Nemotron 3.5 ASR: A highly compact 0.6-billion parameter streaming speech recognition model pushing sub-100 millisecond latencies across 40 language locales.   https://www.minimax.io/models/text/m3  MiniMax M3: A 1-million token context model hitting 59.0% on SWE-Bench Pro and 74.2% on MCP Atlas, though noted for high token consumption due to intensive internal self-validation loops.   https://blog.google/innovation-and-ai/technology/developers-tools/introducing-gemma-4-12b/  Gemma 4 12B: Google's Apache 2.0 on-device model, which utilizes an encoder-free architecture that projects vision and audio vectors directly into the text-token space, bypassing separate CLIP-style encoders to minimize local memory footprints. https://www.jetbrains.com/mellum/  JetBrains Mellum2: A compact 12-billion parameter MoE (2.5 billion active) engineered for ultra-low latency routing and retrieval-augmented generation (RAG) sub-agents within developer IDEs. Opus 4.8 https://www.anthropic.com/news/claude-opus-4-8    https://www.cnbc.com/2026/06/05/google-to-pay-spacex-920-million-a-month-for-xai-compute-capacity.html      Benchmarks: https://deepswe.d atacurve.ai/blog https://venturebeat.com/technology/deepswe-blows-up-the-ai-coding-leaderboard-crowns-gpt-5-5-and-finds-claude-opus-exploiting-a-benchmark-loophole (GPT 5.5 the winner in long horizon tasks) a highly complex software engineering benchmark focused on original, long-horizon tasks across five distinct programming languages. Comprising 113 chaotic tasks across 91 live, production-grade repositories, DeepSWE forces agents to generate 5.5 times more code and modify an average of 7 separate files per task compared to standard evaluations. On this challenging leaderboard, GPT-5.5 leads with a score of 70%, establishing a significant 16-percentage-point lead over contemporary alternatives I think older benchmarks where models reach ~90% accuracy can be considered saturated. Few percentage points don't give us any good signal.  https://research.ibm.com/publications/developing-ai-agents-for-it-automation-tasks-with-itbench  ITBench-AA, an evaluation framework focusing on live Kubernetes incident response and Site Reliability Engineering (SRE) operations. Comprising 59 live, containerized SRE incident snapshots, the results are remarkably sobering: every frontier model scored under 50% on successful incident resolution, with Claude Opus 4.7 leading at 47% and GPT-5.5 following closely at 46%.   Edge AI announcements: https://www.cloudflare.com/press/press-releases/2026/cloudflare-acquires-voidzero-to-build-the-future-of-the-ai-native-web/  The consolidation of the AI-native developer stack has reached the runtime virtualization layer. Cloudflare recently completed the acquisition of VoidZero, the development group responsible for Vite, Vitest, Rolldown, and Oxc, backing the transaction with a $1 million open-source ecosystem fund. This acquisition is highly strategic; as autonomous agents write an increasing proportion of production software, local development environments, compilation pipelines, and bundlers must be optimized for execution speeds that match agent speeds. Cloudflare's goal is to construct a localized, full-stack edge playground. In this sandbox, AI agents can generate, test, bundle (utilizing the highly parallelized, Rust-based Oxc and Rolldown engines), and deploy entire web applications end-to-end within milliseconds. This architecture completely bypasses traditional local machine container bottlenecks, enabling high-velocity agent loops to execute in a fully sandboxed, web-scale edge runtime.

Brett Hammer fills in for Ben Criddle and discusses LJ Martin's chances of winning another Big 12 Player of the Year award, the latest AJ Dybantsa news, all of the news and notes out of Cougar Country, and more! The Deseret News' Jay Drew and BYUtv's Jarom Jordan to the program.

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Family matters here. Mish Schneider, chief strategist at MarketGauge.com, discusses market momentum and its effects on commodities, regional banks and more. She also gives an update on the modern “economic family,” a benchmark that helps investors assess market direction. Tune in to learn about the semiconductor industry's continued strength, AI's longevity and why small caps still matter. Learn more about your ad choices. Visit megaphone.fm/adchoices

US President Trump said talks with Iran were continuing at a rapid pace; he thinks he will have an agreement with Iran to extend the ceasefire and reopen the Strait of Hormuz over the next week.Iran's Foreign Ministry said the US bears direct responsibility for violations of the ceasefire with Iran and by Israel in Lebanon, adding that a violation on one front was equal to violations on all fronts.The US is in talks to expand nuclear weapon deployments in Europe, according to the FT.Crude futures gradually pulled back overnight following the prior day's rally; fixed income caught a bid overnight.APAC stocks were mixed following the choppy performance stateside; European equity futures indicate a positive cash market open with Euro Stoxx 50 futures up 0.5%.Looking ahead, highlights include EZ CPI (May), JOLTs Job Openings (Apr), RCM/TIPP Economic Optimism, New Zealand Export/Import Prices (Q1), NBP Policy Announcement (Jun). Speakers include Fed's Kashkari & Hammack, BoE's Bailey & Greene, ECB's Vujcic. Supply from the UK & Germany. Earnings from Dollar General, Palo Alto & ULTA Beauty.Read the full report covering Equities, Forex, Fixed Income, Commodites and more on Newsquawk

Governor Josh Shapiro is pitching details of his plan for managing data center growth,  months after broadly sketching out a strategy in his budget address. Shapiro, who is running for reelection, is calling on state lawmakers to work with his administration to make his proposal into law. It includes a series of benchmarks data center owners would need to meet in order to get tax benefits from the commonwealth.  And a deep dive:Staying with the topic of development – but with a twist...Think about the shingles on your home - are they made of asphalt? Aluminum? Wood? Imagine if those shingles were made of food waste - pineapple peels, egg shells, and shrimp shells. A group of researchers at the University of Pennsylvania are designing building materials that could be healthier for us and the planet. 

Have you seen the new testing tool that claims to give you fully working end-to-end tests in five minutes with zero setup? What are some of the ways AI agents are quietly gaming their own benchmarks, and what does that mean for how you evaluate them? How do you keep test-driven development alive when AI is the one writing the code? Find out in this episode of the TestGuild News Show for the week of June 1st. So, grab your favorite cup of coffee or tea, and let's do this. Time Item URL 0:00 Intro   0:24 Testifly https://testgld.link/Testifly1 1:13 AI False Confident principle https://testgld.link/130UlI0w 2:46 Webinar of the Week https://testgld.link/qG5fosCF 3:38 AI Agent Cheating https://testgld.link/C40pSlfj 4:44 TDD for AI https://testgld.link/wvLSXtmu 6:10 Webwright https://testgld.link/Nc0BkWBu 7:29 AI Quality Manifesto https://testgld.link/SUXMTc4X 8:45 Claude Workflows https://testgld.link/gOp52O6T  

A US Central Command spokesperson said US forces conducted self-defence strikes in southern Iran on Monday, in which US forces hit targets, including missile launch sites and Iranian boats attempting to emplace mines.US Secretary of State Rubio said US strikes on Iran do not preclude a diplomatic deal and that an Iran deal is possible within days.A source familiar with talks between the high-level Iranian delegation and officials in Doha said Qatari mediation has led to an understanding with the US on Tehran's frozen financial assets, according to Al Jazeera.Crude futures partially rebounded off the prior day's lows after slumping nearly 7% on Monday.Asia-Pac stocks were mixed; European equity futures indicate a mildly lower cash market open with Euro Stoxx 50 futures down 0.3%.Looking ahead, highlights include US Chicago Fed National Activity Index (Apr), Dallas Fed Manufacturing Index (May), Consumer Confidence (May), NBH Policy Announcement (May), Supply from Italy & the US.Read the full report covering Equities, Forex, Fixed Income, Commodites and more on Newsquawk

Investidores ignoram nova escalada nos ataques americanos contra alvos iranianos e mantêm foco na diplomacia.

Investidores ignoram nova escalada nos ataques americanos contra alvos iranianos e mantêm foco na diplomacia.

Você sabe quantas vulnerabilidades críticas existem no seu código escondidas? Neste episódio, nossos hosts destrincham o Claude Mythos da Anthropic e como essa ferramenta está revolucionando a descoberta de falhas de segurança em sistemas digitais. Eles analisam desde o Project Glasswing até casos reais de vulnerabilidades encontradas, discutindo o dilema entre automatizar a segurança e os riscos que envolvem essa tecnologia. Dê o play e ouça agora!Assuntos abordados:Projeto Glasswing;Vulnerabilidades automatizadas;Benchmarks técnicos;Custos de segurança;Vazamentos Mythos;Futuro da cibersegurança;Engenharia social.Links importantes:Vagas disponíveisNewsletterDúvidas? Nos mande pelo LinkedinContato:  entrechaves@dtidigital.com.brO Entre Chaves é uma iniciativa da dti digital, uma empresa WPP #inteligenciaartificial

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

Anthropic hat das Compute-Problem gelöst: Mit dem Kauf von SpaceX' Colossus 1 kommen 300 Megawatt Rechenleistung hinzu, die Quotas steigen und das Rate Limiting zur Rush Hour entfällt. Fabian Walther und Ole Wendland ordnen den Deal ein, sprechen über seine unbequemen Begleitumstände und diskutieren, was Andrej Karpathys Wechsel zu Anthropic für den unabhängigen KI-Diskurs bedeutet. Außerdem: Cerebras Systems feiert ein spektakuläres Börsendebüt mit seinem Wafer-Scale-Chip, aktuelle Paper zeigen, dass Agentic Harness Engineering in Benchmarks mehr bringt als ein Modellupgrade, und Codex knackt die ARC-AGI-3-Challenge.

Argus and CME Group discuss the price signals, trading activity and risk tools emerging around higher-GHG ethanol.

5/17/26 Sunday Morning message

You can be fully booked and still feel like the numbers don't add up. The 2026 A&E Benchmark Report from Monograph shows exactly why, and which firms have figured it out.Ashish Desai, CEO of Monograph, joins Mark LePage to walk through the data on what separates high-performing architecture firms from the rest. The gap isn't in design quality or demand. It's in how efficiently firms convert time into revenue, and revenue into cash.What you'll learn:→ Why AI-enabled firms earn $20K more per employee on $5K more in cost→ The three levers every firm leaks value through: utilization, realization, and cash flow→ How top firms hit 100% realization while the average firm loses 4 cents on every billable dollar→ Why billing monthly is the single highest-impact change most firms can make→ How enabling e-payments cuts time to get paid from 6 weeks to 8 daysAshish Desai is CEO of Monograph, the firm management platform used by 2,200+ architecture and engineering firms to win more work, deliver projects profitably, and get paid faster. He previously served as CPO at Monograph and CPO at 99designs.Download the 2026 A&E Benchmark Report at monograph.com/benchmark. Learn more at monograph.com.

On this episode, Amy Kramer, Head of the Go-To-Market Operating Group at Level Equity, shares findings from their 2026 Go-To-Market Insights Report—a benchmark study covering sales efficiency, marketing spend, headcount, compensation and AI adoption across their portfolio companies.Amy and Shiv dig into what the data shows: why SDRs are having to reach out to more prospects to book the same number of meetings, how the best-performing teams are breaking through the noise with smarter targeting and more direct outreach, and why companies are shifting more budget toward brand and top-of-funnel. They also cover the rise of AI visibility as a pipeline driver, how teams are restructuring around rev ops and product marketing, and what the shift in go-to-market rhythm means for how companies hire and retain customers.The information contained in this podcast is not intended to constitute, and should not be construed as, investment advice.

Melissa, Amanda, and Molly take over the OPT studio to share Q1 industry benchmarks, discuss key trends in online sales, and offer actionable advice for OSCs and leaders navigating a lower-volume, higher-quality lead environment.HousekeepingOnline Sales and Marketing Summit - Oct 1-2 - Austin, TX - We encourage OSCs to attend, with new interactive programming planned.TITO ShoutoutMonica Fikany at New Home Inc - Monica had great lead-to-appointment conversions in Q1.Danielle Evans at Bishard Holmes - 38% of Danielle's appointments came from aged leads.Key TakeawaysLead volume is down, but quality is up: The top of the funnel remains constrained, volume hasn't fully bounced back. However, conversion rates are improving, meaning OSCs are doing more with less.Prospecting is the biggest win of Q1: Normally, prospecting dips in Q1 as new leads come in during selling season. This quarter, prospecting stayed consistent and even increased -- a major highlight. The 22% age lead appointment rate is a direct result of sustained prospecting effort.Your CRM is your most valuable asset: Maximize CRM usage by logging detailed notes after every interaction - aged leads hold untapped opportunity, and leadership relies on quality CRM data to make strategic decisions, so consistency matters.Personalization wins appointments: Buyers are on a longer journey right now. Personalizing outreach and follow-up, based on good notes and CRM data, is what sets top OSCs apart.Skills CheckFor Leaders:Stop measuring program success purely on lead volume. Conversion percentages are the more meaningful metric right now. Scorecards should reflect this shift.For OSCs:Be disciplined and consistent with prospecting.Treat every lead like it's gold.Respond to new leads fast, speed to first response beats the competition.Stay process-driven: no lead left behind.

What actually gets a consumer company funded in Europe? Fewer things than most founders think.This is one of the questions the first episode of Consumer Tech Napkin explores, with Andreas Munk Holm joined by Sameer Singh (Partner with Speedinvest's Marketplaces and Consumer team), Susan Lin (Partner and Investor at Felix Capital) and Joe Seager-Dupuy (Director, Investment at True).The conversation covers engagement as the real leading indicator, why a decade of cheap capital let weak products hide behind paid acquisition, what behavioural signals actually move investors and why AI is not the defensibility play most founders assume it is.If you're building consumer, this one's worth your time.Key highlightsEngagement is the strongest signal in consumer software, not monetisationGrowth can hide weak businesses when retention and organic acquisition are missingAI alone is not a moat and thin wrappers are easy to replicateConsumer is underfunded in Europe despite producing many of its biggest outcomesBlitzscaling only works when companies already have defensibilityTimestamps(00:00)⁠ What actually gets a consumer company funded in Europe?⁠(02:40)⁠ Why AI is not a platform shift⁠(04:15)⁠ Thin AI wrappers and defensibility in consumer software⁠(07:30) AI-enabled consumer opportunities in health, therapy and financial services⁠(10:00)⁠ What investors actually look for in consumer startups⁠(11:20)⁠ Why engagement is the strongest signal that something is working⁠(15:10)⁠ Why behaviour matters more than surveys or narratives⁠(19:00)⁠ Why consumer remains underweight in European venture⁠(27:00)⁠ Marginal costs, pricing power and scalable business models⁠(34:30)⁠ Why blitzscaling only works when companies already have a moat⁠(39:00)⁠ Paid acquisition, defensibility and sustainable growth⁠(41:30)⁠ Felix Capital's consumer investing scorecardSubscribe to EUVC, the home of European tech, for more insights: https://www.eu.vc/subscribe

Iran submitted its response to the latest proposal by the US to end the war; state media later reported that the US proposal amounted to Iran surrendering to Trump's excessive demands.US President Trump rejected Iran's response to the peace plan, which he called totally unacceptable.Iran's proposal was said to have stressed the need for the US to pay compensation for war damages and emphasised Iran's sovereignty over the Strait of Hormuz. Brent climbed above the USD 105/bbl, and WTI breached the USD 100/bbl level to the upside. APAC stocks traded mixed; European equity futures indicate a flat cash market open.Looking ahead, highlights include Norwegian Inflation (Apr), US Existing Home Sales, BoC Market Participants Survey. Supply from the US. Earnings from Hims & Hers, Constellation Energy, Circle Internet, Hannover Re & Gea Group.Read the full report covering Equities, Forex, Fixed Income, Commodites and more on Newsquawk

The rapid evolution and practical deployment of advanced AI agents within complex technical and business environments. One key focus is the transformation of IT support services, where automated systems utilize tools like Claude and n8n to reduce ticket volumes and accelerate resolution times through intelligent triaging. Additionally, the texts highlight Anthropic's multi-agent research architecture, which improves performance by delegating tasks to specialized subagents operating in parallel. Significant infrastructure developments are also noted, such as Anthropic's partnership with SpaceX to massively expand the compute capacity required for these resource-intensive workloads. Finally, the collection offers a comparative analysis of frontier models like GPT 5.5 and Claude Opus 4.7, evaluating their specific strengths in coding, long-horizon reasoning, and autonomous tool use. Together, these documents illustrate a shift toward proactive, data-driven AI ecosystems that manage increasingly sophisticated, multi-step operations.

Interview with Michael Gentile, InvestorOur previous interview: https://www.cruxinvestor.com/posts/mining-alpha-with-michael-gentile-40t-debt-negative-real-rates-gold-volatility-9758Recording date: 30th April 2026The junior mining sector is undergoing a fundamental revaluation, evidenced by two landmark acquisitions that have established new pricing benchmarks for quality gold assets. G Mining Ventures acquired G2 Goldfields at approximately $600 per ounce, while Agnico Eagle purchased Rupert Resources at $500-600 per ounce. Both transactions commanded 70% premiums to prevailing market prices, marking a significant departure from the $50-150 per ounce valuations that have persisted despite gold's rise from $1,500 to $4,500.These premium valuations reflect a strategic shift toward infrastructure-adjacent assets that offer reduced capital requirements and faster payback periods. In G Mining's case, the target sits directly adjacent to their operation under construction, potentially creating a combined 500,000-ounce annual production profile while eliminating over $1 billion in duplicate infrastructure costs. At current gold prices and $2,000 all-in sustaining costs, acquiring ounces at $600 where minimal additional capital is required still yields $1,900 per ounce in cash margin.Strategic investor Michael Gentile, co-founder of Bastion Asset Management, has built his investment framework around this infrastructure dynamic. Operating with 30-35 core positions, he allocates initial capital at 1% of portfolio value, targeting 5-20% ownership stakes in post-discovery companies with $30 million market capitalizations. His emphasis on management ownership of 10-30% of shares, proximity to existing infrastructure, and clear pathways to production has produced five to six successful exits over nine years of full-time investing.The investment process emphasizes patience, with typical timelines of 5-10 years from discovery to acquisition or production. Gentile acknowledges that only 20-30% of investments reach full realization, making diversification across minimum 10-15 positions essential. Position sizing scales with performance, with successful investments receiving up to 5% of book capital across multiple financings while underperformers remain capped at initial allocations.The improving financing environment, characterized by tighter pricing terms and major miners' strong balance sheets, supports continued M&A activity and potential sector-wide revaluation as quality near-term assets become increasingly scarce.Sign up for Crux Investor: https://cruxinvestor.com

How much should a market garden bed generate? After analyzing numbers from hundreds of farmers, the range is massive: $300 per bed to $1,500+ from the same bed size and season. This episode breaks down seven per-bed revenue benchmarks by crop, from the $500 baseline that keeps you alive to the $1,500+ hero crops that keep your farm profitable. Click here to watch the full episode on our YouTube Channel.  Subscribe for more content on sustainable farming, market farming tips, and business insights!   Get market farming tools, seeds, and supplies at Modern Grower. Follow Modern Grower:  Instagram  Instagram Listen to other podcasts on the Modern Grower Podcast Network:  Carrot Cashflow  Farm Small Farm Smart  Farm Small Farm Smart Daily  The Growing Microgreens Podcast  The Urban Farmer Podcast  The Rookie Farmer Podcast  In Search of Soil Podcast Check out Diego's books:  Sell Everything You Grow on Amazon   Ready Farmer One on Amazon **** Modern Grower and Diego Footer participate in the Amazon Services LLC. Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to Amazon.com.

Trump has told officials to prepare for an extended blockade of Iran, WSJ; Trump said they are doing very well in the Middle East.An update that lifted energy briefly overnight and while the move pared into the European morning, benchmarks are at fresh highs with WTI peaking just below USD 104/bbl.The fresh energy highs have weighed on fixed, though only modestly pre-FOMC and with brief EGB respite on German state CPIs.USD lifts into the likely final Fed as Chair for Powell, AUD lags post-CPI, EUR briefly hit by German state CPIEnergy advances weigh on equity sentiment, numerous mega-cap earnings ahead, including AMZN, GOOG, META, MSFT & QCOMLooking ahead, highlights include US Durable Goods (Mar), US Housing Starts (Feb/Mar), Wholesale Inventories (Mar), Fed/BoC/BCB Policy Announcements (Apr), Speakers include BoC's Macklem & Fed Chair Powell.Read the full report covering Equities, Forex, Fixed Income, Commodites and more on Newsquawk

AI is now good enough to change how computational biology teams actually work, but most companies are still adopting it like it's 2023. Sonia Timberlake, R&D strategy consultant for Timberlake & Maclsaac Biopharma Consulting, speaks with host Eleanor Howe about what's real: agentic coding, high-throughput data workflows, and the practical limits that still slow teams down. Timberlake digs into benchmarks for capabilities and end-to-end tasks, as well as multimodal chart understanding, source verification, and where human review remains non-negotiable. The conversation also explores beyond AI to what biopharma risks missing, why novel targets still matter, and where investment interest is clustering right now. Plus, tune in to get a preview of Timberlake's workshop at Bio-IT World Conference & Expo in Boston next month! If this helped you think more clearly about AI in drug development and computational biology, subscribe, share the show with a colleague, and leave a review so more builders can find the conversation. Links from this episode:  Workshop: AI Upskilling for Computational Biology Teams Bio-IT World BioTeam Diamond Age Data Science Bio-IT World's Trends from the Trenches podcast delivers your insider's look at the science, technology, and executive trends driving the life sciences through conversations with industry leaders. 

OpenAI Smartphone Rumors, Charter's Stock Plunge, Intel–Tesla Foundry Boost, Direct-to-Device Satellite Benchmarks, Verizon's Q1 Net Adds, and a Socorro AI Data Center DebateThe 6G Podcast hosts discuss rumors that OpenAI may build a smartphone with Qualcomm and MediaTek, potentially launching around 2027 and enabling tighter OS-level AI integration than Android or iOS. They review Q1 telecom earnings, highlighting Charter's nearly 25% stock drop after losing over 100,000 broadband customers and adding fewer mobile lines than expected, sparking M&A speculation including a possible Verizon or T-Mobile bid and a rumored Deutsche Telekom move to fully acquire T-Mobile. They cover Intel's earnings surge and Tesla naming Intel's 14A node for “Terra Fab,” framed as a CHIPS Act-aligned U.S. manufacturing milestone relevant to 6G supply chains. The episode also summarizes a new direct-to-device satellite report showing about 0.5%–1% monthly unique usage across tracked countries, and Verizon's Q1 return to positive postpaid phone net adds, alongside discussion of an AI data center proposal in Socorro, New Mexico and local opposition over power and water concerns.00:00 Welcome to Six G00:21 OpenAI Phone Rumors03:21 AI OS and Ecosystem05:35 Smartphone Market Shakeups06:00 Telecom Earnings Shock07:05 Charter Selloff Fallout08:01 M&A Rumors Heat Up09:48 Cable vs Fiber Reality13:25 Intel and Tesla Surge19:00 Direct to Device Satellites21:27 Satellite Use vs Density23:28 UK Scan Rate Insights24:08 Hajj Network Challenges26:01 Verizon Q1 Turnaround30:19 Fixed Wireless Limits32:31 Socorro Data Center Debate36:47 Data Centers Case by Case40:16 Wrap Up and Subscribe

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*Listen to the Show notes and podcast transcript with this multi-language player. Summary This conversation centers on the believer's journey out of the limitations of the past and into the present reality of life in the Spirit. While past experiences serve as important “benchmarks” that reveal God's faithfulness and establish spiritual foundations, they are not meant to hold us back or define our present walk. Instead, they become reference points that strengthen faith as we continue moving forward. The speakers emphasize that true life is found in the Spirit, not in the soul, flesh, or past experiences. Believers are called to live in the “now” reality of God's kingdom, where everything He has done remains alive and accessible. This journey is described as a return to our origin in God—an awakening to our eternal identity in Christ. Ultimately, the message reveals that we are being drawn upward into deeper realms of the Spirit, not by striving, but by aligning with God and allowing Him to lead. It is a continual progression toward our true home in Him, where we fully realize who we are and where we came from. Show Notes Main Theme: Living in the present reality of the Spirit while moving forward from past experiences into deeper realms of God. A Greater Heritage in GodOur inheritance in the kingdom far surpasses anything the world offers.Living in past failures or experiences limits present spiritual life. The Role of Benchmarks Past experiences serve as spiritual foundations, not destinations.They testify to God's faithfulness and guide future growth.Like climbing anchors, they prevent falling too far back. Moving Forward, Not Backward Spiritual growth creates points of no return.True progress means continuing onward, not revisiting old mindsets. Living in the Spirit vs. the Flesh Identity is rooted in the Spirit, not emotions, memories, or past pain.Focus determines whether the past has power over us. God's Faithfulness Revealed in the Past Looking back properly brings humility and gratitude.It reveals God's guidance and intentional work in our lives. A Journey of Impartation Each step forward brings new revelation and transformation.Believers are continually being drawn into deeper spiritual realms. Entering a New Realm A shift from time-based living to “now” reality in the Spirit.God's works are not past—they are alive and present. Return to Origin in God Believers come from God and are returning to Him.Identity is discovered through revelation of Jesus Christ. Eternal Identity in Christ We are not merely created beings but originate from God in Christ.Our journey is a return to our eternal home. Being Led by the Spirit Spiritual growth is not self-driven but Spirit-led.Alignment with God opens the next level of experience. Quotes “Do you want to live in what was, or in the light God has brought you into?”“Benchmarks are not places to stay—they are foundations to stand on.”“If you fall, you only fall back to the last place you knew God was real.”“We are not living in the realm of the earth—we are living in the realm of the Spirit.”“Everything God has ever done is still alive right now.”“We're not timeline people waiting for something—this is now.”“We came out of God, and we are returning to Him.”“Our identity is revealed as we see Christ.”“We are not doing this—He is calling us up, and we are aligning with Him.” Scriptural References Psalm 126 (1)“We were like those who dream.”Hebrews 7 (3)Melchizedek: “without father, without mother… having neither beginning of days nor end of life”2 Corinthians 5 (17)“Old things have passed away… all things have become new”John 16 (28)“I came forth from the Father… and go to the Father”Ephesians 1 (3)“Blessed us with every spiritual blessing in heavenly places”Ephesians 2 (6)“Seated us together in heavenly places in Christ Jesus”Romans 8 (14)“As many as are led by the Spirit… these are sons of God”Jeremiah 1 (5)implied concept) – Known before formationEcclesiastes 3 (11)Eternity placed in the heart Takeaway The past is not your dwelling place—it is your witness. God uses it to establish truth in you, but your life is meant to be lived in the present reality of the Spirit. As you move forward, aligning with Him, He leads you into deeper realms of understanding, identity, and union with Himself. You are not becoming something new—you are awakening to where you came from and returning to who you've always been in Him.

4/26/26 Sunday Morning message

OpenAI liefert eine Rekordwoche: ChatGPT Images 2 kombiniert Reasoning mit Bildgenerierung – Infografiken, Speisekarten und Comicstrips entstehen per Prompt. GPT 5.5 überholt Claude Opus 4.7 in vielen Benchmarks. SpaceX will Cursor für $60 Mrd. übernehmen, inklusive $10 Mrd. Breakup-Fee – vermutlich um KI-Revenue fürs IPO aufzupolieren. Der SpaceX-IPO-Prospekt taxiert den eigenen Markt auf $28,5 Billion, davon $26,5 Billion für KI. Amazon kauft den Telko-Anbieter Globalstar, Project Houdini beschleunigt modularen Data-Center-Bau. DeepSeek V4 erscheint als stärkstes chinesisches Open-Source-Modell. Anthropic kooperiert mit Freshfields für Legal AI. OpenAI holt Ex-Airbnb-Manager für EMEA. USVC will VC-Investments ab $500 für Kleinanleger öffnen. Polymarket führt Perpetuals ein. Meta, Microsoft und Snap entlassen Tausende. Tesla liefert solide Earnings, aber FSD funktioniert nicht auf Hardware 3 – eine Lüge an Käufer. Meta will Mausbewegungen und Tastaturanschläge der Mitarbeiter für KI-Training erfassen. Samsung-Mitarbeiter streiken. Talon One wird für €750 Mio. an Adyen verkauft. Aleph Alpha wird von Cohere übernommen.  Unterstütze unseren Podcast und entdecke die Angebote unserer Werbepartner auf ⁠⁠⁠⁠⁠⁠doppelgaenger.io/werbung⁠⁠⁠⁠⁠⁠. Vielen Dank!  Philipp Glöckler und Philipp Klöckner sprechen heute über: (00:00:00) ChatGPT Images 2 (00:07:19) GPT 5.5 und Cursor-Übernahme durch SpaceX (00:18:35) SpaceX-IPO-Prospekt: $28,5 Billion TAM (00:24:36) GPT 5.5 überholt Claude Opus 4.7 (00:26:37) OpenAI EMEA-Chef von Airbnb (00:29:09) DeepSeek V4 und China-Industriespionage (00:34:28) Google TPU 8: Training und Inferenz getrennt (00:38:47) Anthropic + Freshfields: Legal AI (00:43:05) OpenAI Super-App, USVC ab $500 (00:51:00) Layoffs: Meta, Microsoft, Snap (00:58:37) Tesla Earnings und FSD-Hardware-Lüge (01:12:34) Earnings: ServiceNow, SAP, Intel, Samsung-Streik (01:19:00) Polymarket: Heizlüfter-Betrug (01:31:18) Talon One: €750 Mio. Exit an Adyen (01:38:50) Aleph Alpha wird von Cohere übernommen Shownotes SpaceX sichert sich Kaufrecht für Cursor - ft.com XAI prüfte Kooperation mit Mistral und Cursor - businessinsider.com SpaceX-IPO: KI als größte Chance im Prospekt - reuters.com SpaceX: KI-Datenzentren im All nicht rentabel - reuters.com OpenAI GPT 5.5 und ChatGPT als Super-App - techcrunch.com OpenAI holt Airbnb-Manager als EMEA-Chef - bloomberg.com Tencent und Alibaba verhandeln DeepSeek-Investment - theinformation.com Weißes Haus wirft China industriellen KI-Diebstahl vor - ft.com Google TPU 8: Eigener Inferenz-Chip - wsj.com Google Cloud: Neue TPU-Chipreihe vorgestellt - bloomberg.com Anthropic und Freshfields: Legal-AI-Deal - ft.com USVC- xcancel.com Meta entlässt 10% für KI-Fokus - cnbc.com Microsoft: Abfindungen für 7% der Belegschaft - wsj.com Microsoft: Abfindungen für 7% der US-Belegschaft - ft.com Tesla Q1 2026 Earnings - wsj.com Tesla: Ärger mit frühen Kunden wegen FSD - marketwatch.com Musk kauft eigene Cybertrucks über Firmen - teslarati.com Air Force kauft Cybertrucks als Schießziele - fortune.com ServiceNow -14%: Iran-Krieg trifft Subscriptions - cnbc.com SAP Q1: Cloud-Revenue +27% - seekingalpha.com Intel-Aktie steigt durch KI-Boom über Dotcom-Niveau - ft.com Samsung: 30.000 streiken für KI-Gewinne - bloomberg.com Polymarket: Heizlüfter manipuliert Wetter-Wette - xcancel.com Polymarket startet gehebelte Perpetuals - cnbc.com Meta trackt Mausbewegungen für KI-Training - reuters.com Meta-Mitarbeiter empört über Überwachung - xcancel.com Angermayer: Enhanced Games als SPAC - xcancel.com FBI ermittelt gegen NYT-Reporterin - nytimes.com Talon One: €750 Mio. Exit an Adyen - manager-magazin.de Personio erstmals profitabel - handelsblatt.com Telekom erwägt volle T-Mobile-Übernahme - bloomberg.com Glöckler und das OMR-Poster - linkedin.com Google investiert bis zu $40 Mrd. in Anthropic - wsj.com Cohere übernimmt Aleph Alpha, Schwarz investiert $600 Mio. - bloomberg.com

Join Simtheory: https://simtheory.aiSo Chris, this week... a LOT has happened. We're back to regular programming (maybe), and back with our average takes. Nothing's changed.GPT-5.5 just dropped today - but you can't even use it in the API. Vaporware? OpenAI is charging MORE than Opus 4.7 and we haven't even tested it yet. Meanwhile Claude Opus 4.7 landed a couple weeks ago and... the vibes are off? Mike's actually going BACK to 4.6. Something's wrong.But the real star: OpenAI Image 2. This thing is genuinely terrifying. We committed what can only be described as "parody fraud" - faking a council letter so realistic Mike's own mother fell for it on a phone call. Then Chris posted a fake development approval with the mayor's real name into a local Facebook group and had to delete it when someone tagged the actual mayor. The forgery capabilities are absolutely unhinged.Also: GLM 5.1 is so good Mike forgot he switched to it. Kimi K 2.6 is criminally underrated. VCs are paying 70% of your real token costs. Consumers pay only 5.5% of actual cost. The everything app war is ON. The SaaS-pocalypse is real. And we made two new diss tracks.Chris made a graffiti sign in LA. It says "This Day in AI." It was the best artwork in the class. That tells you everything.CHAPTERS:0:00 - Intro & We're Back (Don't Over-Commit)1:14 - Overview: Everything That Dropped While We Were Gone2:56 - GPT-5.5: Vaporware? Not Even in the API4:57 - Benchmarks vs Reality: Nobody's Excited About OpenAI Models5:50 - GLM 5.1 & Kimi K 2.6: Secretly Just As Good?8:15 - The Everything App Race & Product Layer War8:56 - Token Economics: You're Only Paying 5.5% of Real Cost13:08 - We Burned $1.5M in Cloud Credits in 2 Months16:13 - "$30/Month Is Too Expensive" (It Actually Costs $700)19:25 - Where Is Google?? TPUs Should Flatten Everyone22:01 - Agentic Tasks Are 10-50x More Expensive Than Chat25:07 - OpenAI Workspace Agents: Glorified Zapier?27:01 - Single Agent vs Multi-Agent: How Do You Actually Work?33:06 - Building Automation Is HARD (Our Support Shame)35:33 - OpenAI Image 2: The Fraud Episode Begins44:16 - FRAUD DEMO: The Fake Council Letter (Mum Falls For It)49:16 - FRAUD DEMO 2: Chris Posts Fake Mayor Letter on Facebook52:17 - Fake Receipts, Bank Statements & Can Forgeries Be Detected?57:25 - Claude Opus 4.7: The Vibes Are Off59:51 - Mythos Preview: "Pics or It Didn't Happen"1:01:56 -

"Somalia closes Bab al-Mandab Strait to Israeli shipping", IRNA reports; "The move comes as a direct response to Israel's recognition of the breakaway region of Somaliland, Yemen Press Agency reported on Wednesday".European bourses are mostly lower; US equity futures also extend lower, TSLA -2.7% post-earnings.USD and NOK outperform, GBP shrugs off political instability as PMIs firm, NZD underperforms.EZ PMIs initially helped fixed income off lows, but an inflationary UK release sparked new lows.Geopolitics keeps crude prices underpinned and metals softer amid a firmer USD.Looking ahead, highlights include Global Flash PMIs (Apr), Mexican Inflation (Apr), Canadian PPI (Mar), US Jobless Claims (Apr/18). Supply from the US. Earnings from Blackstone, Freeport-McMoran, American Airlines, Keurig Dr Pepper, Intel, Lockheed Martin, and SAP.Read the full report covering Equities, Forex, Fixed Income, Commodites and more on Newsquawk

Benchmarking is one of the most powerful—and underused—tools in a brewery. In this episode, we break down how brewery owners and managers can turn complex financial statements into simple, actionable scorecards that drive better decisions.You'll learn how top breweries use key metrics, industry benchmarks, and weekly financial meetings to identify profit leaks early, improve margins, and strengthen cash flow. Instead of waiting for month-end financial reports, breweries can install a simple financial operating system that provides real-time visibility into the numbers that truly matter.Key TakeawaysWhy financial statements alone aren't enoughMonthly reports are often backward-looking and complex. A simple benchmark scorecard provides real-time visibility and early warning signals.The small set of metrics that truly drive brewery profitabilityNumbers like EBITDA, debt service coverage, gross margin, and key cash-flow drivers help determine whether the business model is sustainable.How to build a simple weekly financial scorecardFocus on just 3–5 key metrics per department to track performance, identify gaps, and drive accountability across the team.The Financial Operating System breweries should installThe cycle is simple: set targets → measure performance → identify gaps → take action → report results weekly.How leading breweries use benchmarking to stay aheadTop breweries track margins, cash, sales velocity, and marketing ROI to make faster decisions and protect profitability.ResourcesSign up for the Brewery Profit Brief -  Clear Numbers, Cash Flow Clarity, and One Practical Action to Improve Your Brewery's Profit Get the free mini-course Brewery Key Performance Indicators - scorecards, templates and best practices to improve your most important numbersTake the Brewery Financial Health Check -  A quick self-assessment that shows where your brewery stands on the key drivers of profitabilityReady to transform financial results in your beer business? Learn more about the Beer Business Finance Association, a network of owners and managers working together to build more profitable companies. 

US President Trump said the US have been asked to hold their attack on Iran until such time as its leaders and representatives can come up with a unified proposal.It was reported that Iran received 'some sign' the US is ready to break the blockade, spurring mild risk-on at the time.UKMTO reported two separate incidents near Oman and Iran, with the latter spurring upticks in the crude complex.European bourses opened higher but have since trundled lower, ASM International +8% after a strong Q1 and guidance; US equity futures gain.USD tracks oil prices, NZD repricing continues and Sterling unreactive to mostly in-line inflation data.Fixed income follows energy but is relatively contained thus far, Gilts marginally underperform.Looking ahead, highlights include EZ Consumer Confidence (Apr), CBRT Policy Announcement (Apr). Speakers include ECB's Lagarde & Cipollone. Supply from US. Earnings from Vertiv, Boeing, GE Vernova, AT&T, Tesla, ServiceNow, IBM.Read the full report covering Equities, Forex, Fixed Income, Commodites and more on Newsquawk

Crypto might be the world's best test bed for AI trading — and Virtuals Protocol is running the experiment live. Weekee Tiew, co-founder of Virtuals Protocol, joins us to explain Degen Claw, their AI Council judging system, and why agents will soon replace wallets. We unpack why pure P&L is the wrong benchmark, how the trench agent concept could reshape portfolio management, and what crypto's role is in the future of finance. Enjoy! TIMESTAMPS: (00:00) Introduction (05:29) Nexo Ad (06:03) Interview with WeeKee (09:28) Bot Strategies and Purpose of Agentic Trading (12:16) How the “AI Council” Works (14:39) Nexo Ad (15:33) How Automation Fits into Benchmarks (19:37) Incentives (24:07) What Makes You Bullish on AI Agents and Crypto in Trading? (26:35) LLMs vs Quants (28:53) The Ultimate Bull Case FOLLOW GUEST › Weekee Tiew (Virtuals Protocol) — https://x.com/everythingempty FOLLOW THE SHOW › David — https://x.com/dcanellis › The Breakdown — https://x.com/TheBreakdownBW SPONSORS › NEXO Nexo is the premier digital wealth platform. Receive interest on your crypto, borrow against it without selling, and trade a range of assets. Now available in the U.S with 30 days of exclusive privileges. Get started at http://nexo.com/breakdown Get top market insights and the latest in crypto news. Subscribe to the Blockworks Daily Newsletter: https://blockworks.co/newsletter/ DISCLAIMER As always, remember this podcast is for informational purposes only, and any views expressed by anyone on the show are solely their opinions, not financial advice.

Marcie Borgal Shunk is the founder and president of The Tilt Institute and creator of Leadership Foundations, a high-impact virtual program designed to give law firms essential leadership skills and practical solutions. For nearly three decades, she has worked with more than 3,000 law firm leaders on talent, culture, and leadership, helping dozens of AmLaw firms anticipate and prepare for the future of law. A Harvard graduate, Marcie holds two fellowships, four certifications in culture and coaching, and several board advisory positions. She is a frequent contributor to the American Lawyer, Thomson Reuters, and Bloomberg Law. Sona Spencer is the Chief Legal Talent Officer at Troutman Pepper Locke, where she leads the firm's legal recruiting, professional development, inclusion, and career coaching functions. Drawing from more than 15 years of experience in AmLaw 50 firms, she collaborates closely with firm stakeholders to implement training, compensation frameworks, and inclusion and retention strategies that ensure the firm can attract and retain talent at all levels to exceed client service goals. WHAT'S COVERED IN THIS EPISODE ABOUT THE DEATH OF APPRENTICESHIP IN LAW FIRMS The apprenticeship model built generations of lawyers, and for a long time it worked. Junior associates learned by proximity, absorbing how to think and practice by working alongside more experienced attorneys over the course of years. Hybrid work, lateral mobility, and generational shifts in how people learn have quietly dismantled that model, and many firms are still operating as though it's intact. Addressing the problem requires more than plugging holes. Firms need to rethink how they signal investment in their people, build structured pathways that make expectations explicit, and develop the human and leadership skills that AI cannot replicate. The firms getting this right have moved beyond standalone training programs and created systems where talent can see the path, understand what's expected, and take an active role in their own development. In this episode of The Lawyer's Edge, Elise Holtzman talks with Marcie Borgal Shunk of The Tilt Institute and Sona Spencer of Troutman Pepper Locke about why the apprenticeship model is failing, what the most forward-thinking firms are doing differently, how AI is reshaping the skills lawyers need to develop, and where firm leaders should start if they want to make a real change. 2:38 - The origin of "The Death of Apprenticeship" article 4:08 - Why hybrid work and generational differences are breaking down the model 7:08 - Why what made senior lawyers successful may not work for the next generation 8:07 - Lateral mobility and compensation wars as added pressure on retention 10:45 - Making the business case for talent development 13:27 - Breaking down the true cost of replacing an associate 15:13 - AI and the risk of outsourcing junior associate learning 19:08 - The human skills firms need to be building deliberately 22:13 - Executive presence and how lawyers show up on camera and in rooms 27:07 - Why leaders have to model what they teach 29:34 - How Troutman Pepper Locke's YOUniversity achieved 75% participation in year one 32:02 - Benchmarks, Learning Management System (LMS) integration, and self-directed development paths 34:48 - Takeaways for smaller firms without large Learning & Development resources 38:44 - Starting small with pilots and building intentionally 41:26 - Don't assume your path is everyone's path 43:36 - Clear communication and moments of kindness Mentioned In The Death of Apprenticeship: What it Means for Lawyers and Law Firms Marcie Borgal Shunk on LinkedIn | The Tilt Institute Sona Spencer on LinkedIn | Troutman Pepper Locke The Death of Apprenticeship: Reimagining Law Firm Talent Strategy for a New Era Get connected with the coaching team: hello@thelawyersedge.com The Lawyer's Edge

Anthropic dropped Claude Opus 4.7 with better vision, better coding and… better everything. And, along with OpenAI's new Codex, AI is accelerating ever faster. This week on AI For Humans, Anthropic released Claude Opus 4.7, a major step up from Opus 4.6 with better visual reasoning, improved software coding and even makes presentations for cavemen. Benchmarks put Opus 4.7 between 4.6 and the unreleased Mythos preview, and the new default xhigh reasoning level means more token burn but more reliability on hard problems. The same day, OpenAI updated Codex with better computer use, an integrated browser, and a bunch of new tools.  Then Jensen Huang's epic Dwarkesh Patel interview broke the internet, with Jensen explaining why NVIDIA keeps selling AI chips to China and dropping the instantly iconic "you're not talking to someone who woke up a loser" line.  Plus, Reese Witherspoon is now in on AI, Doug Liman's Killing Satoshi got made for $80M using AI tools (would have cost $300M without them) and we got our first look at AI Val Kilmer. OPUS 4.7 HAS LANDED. CODEX GOT UPGRADED. IT'S ALL HAPPENING Come to our Discord: https://discord.gg/muD2TYgC8f Join our Patreon: https://www.patreon.com/AIForHumansShow AI For Humans Newsletter: https://aiforhumans.beehiiv.com/ Follow us for more on X @AIForHumansShow Join our TikTok @aiforhumansshow To book us for speaking, please visit our website: https://www.aiforhumans.show/ // Show Links // Claude Opus 4.7 Official Blog Post https://www.anthropic.com/news/claude-opus-4-7 Claude Opus 4.7 System Card https://cdn.sanity.io/files/4zrzovbb/website/037f06850df7fbe871e206dad004c3db5fd50340.pdf Opus 4.7 Is Better at Presentations https://x.com/nadzi_mouad/status/2044814009040261336?s=20 A4H for Cavemen by Cavemen https://x.com/gavinpurcell/status/2044822422868865209?s=20 Opus 4.7 Default xhigh Reasoning and Token Burn https://x.com/mattpocockuk/status/2044802839709372798?s=20 Opus 4.7 Has a New Tokenizer and Base Model https://x.com/natolambert/status/2044788470179332533?s=20 OpenAI Codex Update: Codex for Almost Everything https://openai.com/index/codex-for-almost-everything/ Reese Witherspoon Is Now in on AI https://www.hollywoodreporter.com/news/general-news/reese-witherspoon-ai-comments-instagram-reel-book-authors-1236566844/ The Jensen Huang Interview With Dwarkesh Patel https://youtu.be/Hrbq66XqtCo?si=NpEzxTuuXreLiNRs Dwarkesh Pushes Jensen on Selling Chips to China https://x.com/dwarkesh_sp/status/2044483393941848131?s=20 First Look at AI Val Kilmer https://x.com/Variety/status/2044491101990535460?s=20 Killing Satoshi: Doug Liman's $80M AI-Made Movie https://x.com/TheWrap/status/2044414225158635528?s=20  

3. The 21st century saw massive cash infusions creating “ghost cities” and excessive infrastructure. China's cement consumption and loan volume surpassed historic US benchmarks while billionaires like Jack Ma were suppressed. The Belt and Road Initiative then attempted to export this excess capital into international markets. (3)1903

An airhacks.fm conversation with Holly Cummins (@holly_cummins) about: discussion about Quarkus energy efficiency and performance benchmarks, comparing Quarkus throughput and energy consumption to Spring Boot, the Quarkus Benchmarks repository and Spring-Quarkus performance comparison repository on GitHub, three times throughput and half the energy consumption with Quarkus, Quarkus build-time optimization and tree shaking, monomorphic vs megamorphic dispatching in the JVM, removing reflection at build time, the reactive core built on Vert.x enabling blocking APIs with reactive scalability, Quarkus dev experience and fast reload, build duration comparison between Quarkus and Spring Boot, the Writing Greener Java Applications white paper, the Energy Efficiency across Programming Languages study, Java ranking among the most energy-efficient languages, carbon-aware dispatching and Electricity Maps, zombie deployments and kubernetes cluster waste, serverless architecture with Quarkus on AWS Lambda, SnapStart for sub-second cold starts, Provisioned Concurrency cost savings, GraalVM native binaries vs JVM mode in serverless environments, CycloneDX SBOM generation in Quarkus, build-time vs runtime configuration for ISO 27001 security certification, Kruize Autotune for JVM hyperparameter optimization, JVM tuning folk wisdom and the copy-paste typo anecdote, Francesco Nigro's performance optimization work across the stack from assembly to JVM, Jeff Mesnil leading JBoss energy efficiency efforts, cheese fondue recipe, UK chocolate and Cadbury Roses Holly Cummins on twitter: @holly_cummins

Is the secret to slashing your token costs by 65% forcing your LLM to speak like a caveman? This week on the Friday Deploy, Andrew and Ben test out a hilarious new Claude plugin that reduces AI output to primitive shorthand before diving into Anthropic's $100 million push to win the cybersecurity arms race with Project Glasswing. The hosts also unpack the sudden release of four game-changing open-source models—including Gemma 4 and Halo 3—and explain why modern AI benchmarks are proving that humans still have a cognitive edge. Finally, they wrap up by sharing how they deploy custom background agents to hack their way through expo floors at industry conferences.Read the guide: The APEX FrameworkFollow the show:Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts:Follow AndrewFollow BenFollow DanFollow today's stories:Project GlasswingTool School: Benchmarking 101 (How To Read AI Model Report Cards)Four Open Models Just Proved You Can Own Frontier AI at Every ScaleJuliusBrussee/cavemanOFFERSStart Free Trial: Get started with LinearB's AI productivity platform for free.Book a Demo: Learn how you can ship faster, improve DevEx, and lead with confidence in the AI era.LEARN ABOUT LINEARBAI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production.AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance.AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil.MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.

The most efficient Skate Ramp brands earn large amounts of money in small geographies. In this episode I explain how to measure this and why it's so important to set such a high standard for an undercapitalized business early on. You have to listen to learn the benchmark. This is contained in my book, deliberately. Sort of. Your Host: Dr. James F. Richardson of Premium Growth Solutions, LLC www.premiumgrowthsolutions.comPlease send feedback on this or other episodes to: admin@premiumgrowthsolutions.com

A persistent structural challenge highlighted in this episode is the disconnect between technology investment and demonstrable business outcomes, which fuels operational inefficiency and accountability gaps in technology spending. As articulated by technology economist Dr. Howard Rubin, a common industry tendency is to measure IT success based on technology adoption or budget size rather than objective business results. This pattern is not limited to large enterprises but affects small and mid-sized organizations, many of which feel compelled to maintain “current” technology without clear evidence of operational or financial return. Primary evidence centers on the inadequacy of current macroeconomic indicators—such as the Consumer Price Index (CPI) and Gross Domestic Product (GDP)—for assessing technology value and risk in smaller organizations. Dr. Rubin noted that official statistics and classic economic telemetry do not track the true inflation or productivity impact of technology stacks, particularly as hyperscalers invest trillions in infrastructure. The transcript highlights that price increases or capital recovery pressures in services like Microsoft Office or cloud platforms are likely to affect smaller organizations first, exacerbating operational risk and cost unpredictability. Supporting developments include analysis of flawed benchmarking practices, such as using IT spend as a fixed ratio to revenue or operating expense without examining enabling value or efficiency outcomes. Failure to contextualize technology investments can lead to counterproductive decisions, like arbitrary cost-cutting when IT as a percentage of expenses rises, ignoring possible operational savings or revenue lift driven by technology. Dr. Rubin advocates for pattern recognition and bespoke analysis over reliance on aggregated industry numbers, pointing out that mass market vendor investments and macroeconomic policy often obscure direct impacts at the SMB and MSP level. For MSPs and technology decision-makers, the operational implication is a heightened need to create internal technology inflation indices and track category-specific price pressures. Rather than relying on aggregate industry benchmarks or public economic data, service providers should establish tailored metrics to capture their own cost structures, labor pressures, and technology value. The discussion points toward the need for more deliberate accountability and ongoing evaluation—especially given that upstream price increases from hyperscalers and SaaS vendors are set to impact providers and their clients, with limited ability to negotiate at smaller scale.  

AI benchmarks are breaking—saturated, gamed, and increasingly disconnected from real-world performance. This episode explores why that's happening and how new tests like ARC AGI 3 aim to measure actual learning and reasoning instead of memorization. In the headlines: Apple's deeper Gemini plans, a major efficiency breakthrough from Google, and rising political tension around AI infrastructure.Brought to you by:KPMG – Agentic AI is powering a potential $3 trillion productivity shift, and KPMG's new paper, Agentic AI Untangled, gives leaders a clear framework to decide whether to build, buy, or borrow—download it at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.kpmg.us/Navigate⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mercury - Modern banking for business and now personal accounts. Learn more at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://mercury.com/personal-banking⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Recall - The API for meeting recording. Get Get started today with $100 in free credits at ⁠⁠https://www.recall.ai/aidb⁠⁠AIUC-1 - Get your agents certified to communicate trust to enterprise buyers - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.aiuc-1.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Blitzy - Want to accelerate enterprise software development velocity by 5x? ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://blitzy.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AssemblyAI - The best way to build Voice AI apps - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.assemblyai.com/brief⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Robots & Pencils - Cloud-native AI solutions that power results ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://robotsandpencils.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Agent Readiness Audit from Superintelligent - Go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://besuper.ai/ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠to request your company's agent readiness score.The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://pod.link/1680633614⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Our Newsletter is BACK: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://aidailybrief.beehiiv.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Interested in sponsoring the show? sponsors@aidailybrief.ai