Podcasts about Cursor

BONUS: How Scrum Masters Can Use AI Without Losing the Human in the Loop AI makes it easier than ever to build software, prototypes, courses, and coaching tools. In this BONUS episode, Mike Lyons and Greg Pfister share what that speed changes for Scrum Masters, why product judgment becomes more important, and how coaches can start using AI without outsourcing the conversations their teams still need. When AI Stops Being a Curiosity and Starts Saving Real Time "It's not that the work is wrong or not needed, it is needed. That's an important step. Retrospectives are critical."   Greg's first practical AI moment came while trying to build an "Ask Mike" capability for self-paced courses. After a frustrating outsourcing attempt, he started using ChatGPT to help him rebuild the tool himself, eventually moving into Cursor, Claude Code, and the Superpowers plugin for Claude Code. Mike's moment was less technical: using AI inside Mural to affinity-map retrospective notes. The lesson for Scrum Masters is not that AI removes the work, but that it can remove enough friction to let facilitators spend more time on judgment, listening, and follow-through. The Bottleneck Moves From Building Fast to Building the Right Thing "The cost to produce prototypes for software engineering is approaching zero."   Mike and Greg argue that AI does not create the "wrong feature" problem, but it makes the problem much easier to multiply. If a prototype can appear before lunch, the old excuses disappear. Teams still need to ask whether the customer problem is real, whether the payoff matters, whether there is proof from users or data, and whether this work deserves priority now. For Scrum Masters and Agile coaches, this is a clear invitation to help Product Owners slow down the decision before accelerating the delivery. Building AskMe With AI as the Engineering Partner "I'm really playing product manager. That's really what I'm doing."   Greg describes AskMe as an AI-enabled coaching tool embedded into training courses. Instead of asking learners to pass obvious multiple-choice quizzes, AskMe asks them to apply what they learned to their own context, then reflects back practical coaching based on the course material, instructor context, and learner profile. In their own product development, Greg uses AI as an engineering partner while Mike keeps asking the product question: should we build it? Their 4P lens is simple: problem, payoff, proof, and priority. The Scrum Master Role Becomes More Important, Not Less "Don't just outsource your brain, your decision making power."   When leaders push teams to "adopt AI," Mike warns Scrum Masters not to let the tool become the decision maker. AI can cluster retrospective notes, summarize long threads, propose learning plans, or help prepare for a hard conversation, but the human still needs to inspect the output and understand the consequences. Greg adds the practical security angle: teams must be careful about what they paste into AI systems, especially personal, customer, or sensitive company information. Start Small: Context, Role Play, and Shared Learning "Context is king when you're talking with your AI."   Greg suggests starting with basic AI training, then practicing with small workflow improvements: prioritizing work, summarizing material, or drafting communication that the Scrum Master then edits. Mike's practical starter experiment is role play: describe a difficult team situation without names, ask the AI to act as the other person, and practice the one-on-one conversation. Vasco adds a simple working habit: keep a running context file with meeting notes, team insights, worries, decisions, and open questions, then use that context when asking AI for help. Resources for Scrum Masters Learning AI "Let AI help you get smart about AI."   Mike recommends the PMI AI in Project Management learning resources and the 37signals Rework podcast for pragmatic thinking about how AI fits into work. Greg recommends learning directly from the AI tool providers, exploring how to configure projects and context, and reading Marty Cagan's Inspired to strengthen the product judgment that becomes more important when teams can build faster. About Mike Lyons and Greg Pfister Mike Lyons and Greg Pfister are the team behind KaiRise, where they've used AI to build new products, including AskMe, an AI coaching tool, and to create their most recent certified Product Management training course end-to-end.   Greg Pfister works with Mike at KaiRise on AI-enabled learning products, including AskMe and their certified Product Management training course.   You can link with Mike Lyons and Greg Pfister on LinkedIn. You can find KaiRise and AskMe at kairise.com.

At Zapier, the rise of AI is changing more than the automation products customers build. It is reshaping how the company organizes, invests, prices its offerings, and thinks about its next stage of growth.COO and CFO Ryan Roccon describes Zapier's emerging role as the place where AI-built work actually runs. As tools such as Claude, Cursor, and ChatGPT make it increasingly easy to build applications and agents, he sees a different challenge emerging: keeping those automations reliable, observable, auditable, and cost effective once they enter production.That challenge is influencing Zapier's product and financial agenda. Roccon points to the combination of deterministic workflows and agentic components as an important part of the company's future. An internal review found that rebuilding certain agents with rules where possible and inference where necessary reduced costs by about 75% while improving reliability.Zapier's financial model adds another dimension. The company has remained cash-flow positive under Roccon's finance leadership, giving it room to make aggressive investments while maintaining discipline around ROI and net present value. His challenge to the organization is to find opportunities compelling enough to justify breaking that rule.Meanwhile, Zapier continues moving upmarket while reorganizing around AI and expanding its enterprise business. For Roccon, the finance agenda increasingly extends beyond financial results: ensuring the product delivers, sharpening the go-to-market message, and making certain that customers understand the value of what Zapier is building.

Michael Moritz led Sequoia Capital for nearly two decades and backed some of the defining companies of the internet era.  In his new memoir, Ausländer, he turns his attention to his own family, Jewish refugees who fled Nazi Germany and rebuilt their lives in Wales.  We discuss the imprint his parents left on him, the method he used for decades of asking founders about their childhoods and the Time profile that ended his relationship with Steve Jobs.  We also also cover Lee Iacocca, why Don Valentine hired him, Alex Ferguson's approach to managing players, Elon Musk, and why Mike still struggles to feel proud of anything he has done. Please enjoy my conversation with Michael Moritz. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- ⁠Ramp's⁠ mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠ramp.com/invest⁠⁠ to sign up for free and get a $250 welcome bonus. ----- Trusted by thousands of businesses, ⁠Vanta⁠ continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Invest Like the Best listeners get a special offer of $1,000 off Vanta when you go to ⁠vanta.com/invest⁠.  ----- WorkOS⁠ is the infrastructure B2B and AI-native companies use to sell to enterprise. It covers everything enterprise security requires: SSO, SCIM, RBAC, Audit Logs, AI governance, and more. Trusted by 2,000+ fast-growing companies, including OpenAI, Anthropic, Cursor, and Vercel. ----- Rogo is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- ⁠Ridgeline⁠ has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Visit⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgeline.ai⁠. ----- Editing and post-production work for this episode was provided by The Podcast Consultant. Timestamps: (00:00:00) Welcome to Invest Like The Best (00:02:16) Where Does One Person End? (00:11:15) The State of the World Today (00:15:08) The Unlived Life of Parents (00:17:33) Lee Iacocca, Eternal Outsider (00:21:03) His Most Revealing Question (00:26:03) Resisters, the Silent, and Collabos (00:33:30) The Profile of Steve Jobs (00:38:04) Frank Auerbach's Total Obsession (00:41:04) Why Don Valentine Hired Michael (00:46:44) Building Sequoia (00:49:49) What Michael Learned from Alex Ferguson (00:52:57) The Great Man Theory (01:00:36) Defining Extraordinary Writing (01:03:40) Stepping Back From Sequoia (01:06:54) A Philosophy of Parenting (01:09:00) The Next Book: Iran (01:11:44) The Kindest Thing

Anthony and Katie chat about articles written about Cursor's new icon designs.Original article: https://www.minoradventures.co/blog/the-making-of-cursors-iconsInterview with Marek: https://www.casestudy.club/marek-minor-interviewHosts:Anthony Hobday, Generalist Product Designer: ⁠⁠⁠⁠⁠https://twitter.com/hobdaydesign⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Katie Langerman, Design Systems Designer: ⁠⁠⁠⁠⁠https://twitter.com/KatieLangerman⁠

My guest today is Walter Russell Mead. Walter is a columnist at the Wall Street Journal and the author of Special Providence and God and Gold, two of the best books written on American power.  He has spent decades studying how the United States came to dominate the world, and our conversation is about whether it can keep doing so.  Walter lays out the five step playbook that carried the Dutch, then the British, then America to global leadership, and why the same pattern keeps beating centralized continental powers.  We discuss how Trump turned fame into power, the four schools of American foreign policy and the rise of the tech Hamiltonians, what the drone war in Ukraine means for the Pentagon, and why the erosion of deterrence is the deeper story in the Middle East.  Please enjoy my conversation with Walter Russell Mead. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- ⁠Ramp's⁠ mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠ramp.com/invest⁠⁠ to sign up for free and get a $250 welcome bonus. ----- Trusted by thousands of businesses, ⁠Vanta⁠ continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Invest Like the Best listeners get a special offer of $1,000 off Vanta when you go to ⁠vanta.com/invest⁠.  ----- WorkOS⁠ is the infrastructure B2B and AI-native companies use to sell to enterprise. It covers everything enterprise security requires: SSO, SCIM, RBAC, Audit Logs, AI governance, and more. Trusted by 2,000+ fast-growing companies, including OpenAI, Anthropic, Cursor, and Vercel. ----- Rogo is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- ⁠Ridgeline⁠ has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Visit⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgeline.ai⁠. ----- Editing and post-production work for this episode was provided by The Podcast Consultant. Timestamps: (00:00:00) Welcome to Invest Like the Best (00:02:16) America and the World Today (00:05:34) Trump's Method of Power (00:09:43) Why America Keeps Winning (00:12:25) The Five-Point Plan for Global Dominance (00:20:11) China and American Power (00:22:10) The Risk of American Isolationism (00:25:50) Technology and Global Power (00:28:42) Riding the Technological Wild Horse (00:34:29) Four Schools of American Foreign Policy (00:40:22) The Rise of Tech Hamiltonians (00:43:51) India and the Next Great Powers (00:48:54) The Risks of the Information Revolution (00:51:30) How Technology Is Changing War (00:55:06) Taiwan (00:57:20) The Future of American Society (01:00:44) What It Means to Be American (01:03:25) Iran and the Middle East (01:06:28) The Erosion of Deterrence (01:08:53) America's Role in the Next 20 Years (01:12:08) AI and Global Power (01:14:26) Reasons for Optimism (01:16:33) The Kindest Thing

Roman Ugarte helped incubate and build Grok Bot, the popular new knowledge-work agent from SpaceXAI. A small, isolated team took it from first line of code to a working internal product in four weeks, and to a hugely successful public launch just three weeks later. Before Grok Bot, Roman led Growth at Cursor, where he helped scale the company from 15 people to over 1,000 before its acquisition by SpaceX.In our in-depth conversation, we discuss:1. The origin story of Grok Bot2. The key decision to build it from scratch instead of adding it to Cursor3. Why the team personally onboarded nearly 300 of its first users4. The two early product decisions that made Grok Bot so successful5. Their “colleague-pilled” product philosophy6. Roman's advice on moats, and what has allowed Cursor to keep winning in the most competitive market in the world—Brought to you by:WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and moreMercury—Radically different banking, now with Command—Episode transcript: https://www.lennysnewsletter.com/p/how-we-built-grok-bot-in-a-month—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Roman Ugarte:• X: https://x.com/romanugarte_• LinkedIn: https://www.linkedin.com/in/romanugarte• Website: https://x.ai—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction(02:09) The origin story: building from scratch in one month(08:40) Why Grok Bot was built as a separate product(11:20) Manually onboarding a couple hundred people(14:29) Hiding internal mechanics from users(18:41) Timeline from beta to public launch(19:14) Unshipping features and simplifying(23:50) Early use cases and feedback(26:50) Product philosophy: “Grok Bot can now”(30:02) Cloud-first architecture(33:12) The fresh-start advantage(35:54) The vision: a true team of AI colleagues(39:20) The “colleague-pilled” framework(42:36) Work versus personal: one product or two?(47:14) Long-lived agents, persistent memory, and the computer abstraction(51:04) Grok Bot as an always-on infovore and chief of staff(53:35) How fast the team moves and what preserves the startup feeling(58:20) SpaceXAI pillars(1:00:44) The first 90% vs. the last 10%(1:03:30) Moving fast at scale(1:06:40) How Cursor kept winning in the most competitive market in the world(1:10:04) Company values: “deleting the product” and “just do the thing”(1:11:45) Moats: discovered, not planned(1:15:11) Tips for new users and power users(1:18:00) Lightning round and final thoughts—References: https://www.lennysnewsletter.com/p/how-we-built-grok-bot-in-a-month—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

The messy breakup is official; as of November 12, OpenAI's models are getting pulled from Cursor, and we're digging into who's really to blame (and why Wes called it). Plus pnpm 12 goes full Rust, Mitchell Hashimoto drops Superlogical, ~700 AI agents attack Hugging Face, and Zod 4.5's compiled schemas get up to 9x faster. Show Notes 00:00 Welcome to Syntax! 00:33 pnpm 12 Rust Re-Write 02:45 Zod 4.5 brings Schema Compilation Zod 4.5 launch post 05:22 Brought to you by Sentry! 07:14 Cursor OpenAI Break Up Michael Truell's post 15:35 vGPU - WebGPU library for agents TypeGPU Main differences between vgpu and TypeGPU 22:32 Omarchy Security Issues and Linux Chat Omarchy Security issue in Omarchy Close three paths from an unprivileged session to root commit CachyOS 36:38 Scott Bought an M5 Ultra Mac Studio 44:45 Superlogical is a new terminal multiplexer 48:31 Zurich JS 48:55 Katamari Object Library 52:05 ThreeUI - Three.js library 55:36 Hugging Face Hack Analyzed / Updates METR & Redwood Research investigation Brief independent investigation of agents' behavior About the Hugging Face attack Postmortem of the HuggingFace hack 01:00:46 llms.txt used to pwn devs 01:03:56 Running Isolated Code Poll 01:05:47 OpenShot 4.0 - OSS Video Editor Blick editor 01:09:06 Lake America 01:11:24 Ox Alpha is GLM 5.3 Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott: X Instagram Tiktok LinkedIn Threads Randy: X Instagram YouTube Threads

Both big AI labs shipped their best models yet this week: OpenAI's GPT-6 Astra finally takes computer use seriously, and Anthropic's Fable & Mythos 5.1 land with gains in coding, knowledge work, and long-running tasks. Jack also went down a rabbit hole on how LLM watermarking actually works. Plus a Roomba with two floor-cleaning brains, a website tallying up AI agent felonies, and OpenAI cutting Cursor off from its models.Timestamps0:00 - Intro1:16 - GPT-6 Astra11:58 - How LLM watermarking works29:47 - Fable & Mythos 5.141:48 - Felony Bench43:21 - iRobot unveils the Roomba Duo45:51 - OpenAI blocks Cursor48:27 - What's making us happyNewsPaige: Anthropic debuts Fable & Mythos 5.1Jack: How LLM watermarking worksTJ: GPT-6 AstraLightning NewsOpenAI blocks Cursor after its acquisition by SpaceXiRobot unveils the Roomba DuoFelony BenchWhat's Making Us HappyPaige: Silo TV series, season 3Jack: Kenwood CarPlay UnitTJ: Pablo Torre Finds OutThanks as always to our sponsor, the Blue Collar Coder channel on YouTube. You can join us in our Discord channel, explore our website and reach us via email, or talk to us on X, Bluesky, or YouTube.Front-end Fire websiteBlue Collar Coder on YouTubeBlue Collar Coder on DiscordReach out via emailTweet at us on X @front_end_fireFollow us on Bluesky @front-end-fire.comSubscribe to our YouTube channel @Front-EndFirePodcast

What does it take to move from giving employees AI tools to rebuilding how an organization gets work done? In this episode of Tech Talks Daily, I speak with Oren Levitzky, VP of R&D at Fiverr. Oren has spent ten years at the company, progressing from backend engineer through a series of leadership roles before taking responsibility for Fiverr's AI program. That experience gives him a valuable view of AI adoption from inside a global technology marketplace. He has watched engineering teams move from using ChatGPT as a conversational assistant to GitHub Copilot for code completion, Cursor for context-aware development, and an internal agent ecosystem containing Fiverr's code, data, and organizational knowledge. Oren explains that adding AI to an existing workflow produced useful gains, but it did not completely change how people worked. Becoming AI native required Fiverr to create a dedicated team of engineers, designers, and product managers responsible for building agents around company context and helping employees adopt new working practices. Fiverr reports that this approach has made some development work three to five times faster. Repetitive coding and design tasks can be passed to agents, allowing employees to concentrate on decisions, validation, and accountability. However, Oren is clear that manual code review remains necessary when AI-generated changes could introduce bugs or destructive operations. We also discuss what AI fluency means for hiring. Fiverr has redesigned parts of its engineering recruitment process so candidates can use their preferred AI tools to build an application during the interview. Oren says around 80 percent of the assessment focuses on how candidates work with AI, communicate instructions, make decisions, verify changes, and demonstrate that they understand the resulting code. This creates opportunities for people who can combine technical knowledge with AI fluency, but it also introduces a serious learning problem. Junior engineers may produce work at a speed previously associated with experienced developers without acquiring the knowledge needed to spot errors or question poor recommendations. Oren argues that regular workshops, practical education, self-directed learning, and continued hands-on work are needed to prevent that loss of understanding. His advice applies to leaders too. Remaining close to the work makes it easier to recognize where AI succeeds, where it struggles, and what employees need from management. Beyond Fiverr's internal engineering teams, we consider how AI is affecting the global freelance workforce. Businesses increasingly want people who can take an AI-generated draft and turn it into secure, accountable, production-ready work. Oren points to AI video production as one example where independent creators can produce work that previously required a larger studio, while retaining the judgment and creativity customers value. For leaders hoping to make agentic AI part of daily operations, Oren recommends dedicated resources, structured education, employees who constantly seek better ways to work, and clear measurement. Releasing another tool will achieve little when habits, incentives, and expectations remain unchanged. As employers place greater value on people who can direct, question, and verify AI, how should we prepare today's workforce without weakening the knowledge tomorrow's experts will need? Listen to the episode and share your thoughts with me.

¡Ni desambiguacion de una abstraccion podra detenernos!¡Porque es lunes y SpreadShotNews Podcast ya está aquí! En este episodio: Maxi termina el Beast of Reincarnation y nos cuenta sus opiniones finales. Nico por su parte retorna con mas Big Walk, el final de Ace Combat 7: Skies Unknown, Metal Gear Solid 4: Guns of the Patriots y Star Wars Zero Company. En el Rapid-Fire, charlamos sobre las últimas novedades de Project Helix, el programa de digitalización de juegos que anunció Xbox, las limitaciones a su servicio de cloud gaming, Aggro Crab dándole una mano a los indies en forma de publisher y SteamDB siendo vendido a Nexus Mods. Para el Hot Coffee, repasamos ambos State of Play y comentamos brevemente acerca de los anuncios. Para finalizar, en el Special Move, Nico recomienda chequear el kickstarter de Double Fine donde detallan su primer Amnesia Fortnight post separación de Xbox. Por último, recuerden que nos pueden escribir preguntas directamente a través de google forms en el siguiente link: spreadshotnews.com/preguntas

A structural shift in regulatory accountability now places incident notification and liability directly on the operators or deployers of AI-powered and software tools, rather than on technology vendors or model developers. This mechanism is made explicit by the requirements of the EU's Cyber Resilience Act (CRA), Digital Services Act (DSA), and the upcoming Machinery Regulation. Incidents such as the Cursor AI coding agent breach at a Belgian chemical company underline that compliance timelines and regulatory scrutiny target the entity deploying the technology.CrowdStrike and Okta both reported that increased enterprise security spending is being driven by heightened AI-generated attacks, according to their quarterly results. Gartner forecasts AI security spending will reach $4.8 billion by 2027, up 68.7% from this year, with usage control as the most dynamic segment. A public letter signed by over 100 vendors—including OpenAI, Anthropic, AWS, and Microsoft—warns of urgent defensive needs but does not shift responsibility to software suppliers.Recent breaches and vulnerabilities illustrate how accountability remains with the service provider or end-user implementer. The Cursor breach assigned notification duties to AnySphere (the product vendor) and the breached organization, not to upstream model providers. Likewise, after N-able's Passportal bug, MSPs were accountable for client-facing remediation. In each case, the “accountability line” lands on the party deploying the tool.For MSPs and IT service providers, these trends require updating agreements, operations, and client communications. Service structures must prioritize regulatory response timelines, documentation, and clear reporting obligations. Providers serving EU clients, or those linked to global supply chains, will encounter business risk if they do not proactively address these regulatory demands before mandated deadlines.00:00 Prevention Got A New Price 03:25 The Half That Doesn't Move05:50 Where The Call Lands09:27 Why Do We Care? Supported by: Proofpoint GoTo(LogMeIn)

In this episode of Agentic Conversations, we sit down with Ambud Sharma, Principal Engineer at Pinterest, responsible for general technology efficiency, fresh off delivering a controversial keynote on AI infrastructure optimization at scale.Ambud walks us through his Five Layer Cake framework - a structured approach to driving efficiency across every level of the AI stack, from silicon and hardware procurement to model selection, inference engine design, and governance. We explore how decisions compound across layers to unlock real business growth, and how the wrong choices can lock you into expensive commitments for years.We stress test the framework against two very different business models: what the stack looks like if you are building the next Cursor, and how it changes entirely if you are building the next YouTube. Along the way we cover hardware immutability, inference engine warm-up costs, GPU occupancy, context switching, quantization trade-offs, model routing, and why experimentation discipline is the only thing that keeps AI infrastructure costs from getting out of control.We also look at how this framework holds up in the emerging agent era, what changes when agent-to-agent communication becomes the norm, and why agent traffic just passed bot traffic on Cloudflare. The conversation closes on a deceptively simple takeaway: there is no silver bullet, and experimentation at every layer always comes first.Pinterest: https://about.pinterest.com/Alex Salkever: https://www.linkedin.com/in/alexsalkeverAmbud Sharma: https://www.linkedin.com/in/ambudTimestamps:[0:00] Introduction and the controversial keynote[2:09] The five-layer cake explained[4:30] Why hardware decisions are irreversible[6:47] Two business models: building Cursor vs YouTube[10:42] Applying the five layers to a YouTube-style company[14:23] Experimentation as the core efficiency method[17:09] Inference stack: context switching and warm-up costs[20:07] Model layer: why changing models breaks everything[24:10] When you should not use an LLM at all[26:41] Governance and routing: right model for the right task[29:20] Horror stories of unchecked token spend[31:37] Experimentation discipline without stifling innovation[34:35] How the five layers change in the agent era[36:05] Agent-to-agent communication and governance complexity[38:27] Core takeaway: experimentation first at every layer

AGENDA:  00:00 Nvidia crushes $96.2B quarter and nears $12.9B Hugging Face deal 13:52 OpenAI cuts off Cursor as the Altman–Musk feud escalates 17:40 OpenAI's 1,000-agent cyberattack triggers an industry wake-up call 22:58 Instinct hits $2.5B valuation as AI assistants gain spending power 36:39 Cognition targets $1.6B ARR as the coding-agent market explodes 40:31 AI forces every startup to become a compound company—or get left behind 52:42 Salesforce embraces Claude and outcome-based pricing in major AI reset 1:00:52 Stripe–PayPal deal collapses as both sides clash over price 1:02:31 Clay hits $7B and Linear reaches $100M ARR as agents choose their tools 1:11:52 Texas pauses Flock cameras as police-surveillance backlash grows

GrokBot donne à des agents autonomes un accès complet à vos outils, vos mails et ils bossent pendant que vous dormez. Ce n'est plus un assistant qu'on interroge, c'est une équipe qu'on dirige. Produit réel ou roadmap déguisée ? La stratégie d'Elon Musk est bien huilée : il contrôle le compute avec Colossus, le loue à ses propres rivaux, et a absorbé Cursor pour accélérer sa roadmap produit. Pendant ce temps, Sam Altman fait machine arrière sur la révolution IA au moment où il approche de son IPO. Le vrai basculement est là : le travail ne consiste plus à exécuter, mais à déléguer, superviser et arbitrer. L'humain est devenu le goulot d'étranglement et ceux qui refusent de manager des agents seront bientôt rattrapés par ceux qui le font déjà.===================⏱️ DANS CET ÉPISODE :===================0:00 — Intro1:05 — Présentation des invités2:49 — GrokBot : l'équipe d'agents qui ne dort jamais4:32 — Où l'humain se positionne face à ces agents ?8:31 — [Sponsor] Google Cloud au service de l'innovation française9:58 — Les agents tiennent-ils vraiment leurs promesses ?10:56 — GrokBot accède à tout, sans aucun garde-fou15:32 — Shadow IT : l'entreprise exposée sans le savoir19:39 — Plus besoin de recruter : les agents vont envahissent vos entreprises24:51 — La singularité atteinte : l'humain est le nouveau goulot d'étranglement25:10 — Sam Altman fait machine arrière : la réalité l'a rattrapé29:18 — Musk en retard ? Non, il joue une autre partie32:19 — Prophétie autoréalisatrice : la méthode Musk==================

Este episodio 828 es la carta de presentación de la Temporada 9 de atareao con Linux. Treinta y cuatro episodios ya guionizados, siete etapas, y un objetivo claro: construir tu cerebro digital sobre Linux con herramientas locales, sin depender de nubes ni suscripciones.Pero antes de mirar adelante, toca hacer balance. La T08 empezó prometiendo Docker, selfhosting y Android, y sí, hablé de todo eso. Pero en abril de 2025 la IA local irrumpió con fuerza y la temporada viró hacia Ollama, modelos locales, RAG, MCP. Fue un giro desordenado, lo reconozco. Pero también fue el germen de todo lo que viene ahora.De eso va esta T09: de poner orden al caos. Siete etapas, de menos a más, para que sigas el hilo hagas el nivel que hagas.Etapa 1 — Recursos básicos: los cimientos de tu laboratorio de IA. Skills para tu agente, herramientas de publicación, el botiquín del explorador.Etapa 2 — Skills y MCPs: el pegamento. El Model Context Protocol ha madurado hasta ser un estándar abierto — lo soportan Claude, ChatGPT, VS Code, Cursor. Ya no es un experimento, es el USB-C de la IA. Y de paso, herramientas del ecosistema atareao como watchbeat (monitor de uptime en Rust) y alloy (dashboard Docker con OIDC).Etapa 3 — GraphRAG, el gran hito: de RAG vectorial a grafos de conocimiento. Mientras el RAG clásico devuelve fragmentos sueltos y tú unes los puntos, GraphRAG construye un grafo con entidades y relaciones. Preguntas como "qué contenedores están detrás de Traefik" pasan a ser una consulta directa a tu mapa de conocimiento. Usaremos LightRAG, que con 39.000 estrellas ya superó al Microsoft GraphRAG original. Esto ocupa tres episodios.Etapa 4 — Multimedia: Whisper para speech-to-text, TTS local, ffmpeg, visión artificial, y el pipeline de YouTube a conocimiento con yt-dlp. Rematamos con RAG multimodal.Etapa 5 — Orquestación: systemd timers, asyncio, just, y CrewAI para montar equipos de agentes.Etapa 6 — Proyecto final: dos episodios para construir El Asistente que te Conoce y ponerlo en producción con Quadlets.Etapa 7 — El futuro: mantenimiento de tu cerebro digital y hacia dónde va todo esto.Entre medias, herramientas Linux: shuul, sqlite-utils, yq + jq, Rust en el kernel, Wayland vs X11, la guerra de los filesystems.No necesitas una GPU de 3000 euros ni un doctorado. Con 16 GB de RAM y un CPU decente ejecutas modelos de 7B a 14B. Esto es IA local, en tu máquina, con tus datos.Capítulos del episodio:00:00 — Introducción y bienvenida a la Temporada 901:47 — Balance T08: de Docker y Selfhosting al boom de la IA04:37 — El momento adecuado para cada tecnología06:46 — El gran objetivo: tu cerebro digital08:44 — Roadmap T09: 30 episodios ya guionizados11:28 — Skills y MCPs imprescindibles12:43 — GraphRAG: de RAG a grafos de conocimiento14:01 — RAG vs GraphRAG: el mapa de tu conocimiento17:28 — Herramientas del ecosistema: alloy, populater, watchbeat20:08 — ¿Para quién es esto? De veteranos a escépticos22:08 — No es hype: es un cambio de paradigma24:30 — El momento perfecto para el linuxeroToda la info y el roadmap completo en atareao.es/828.Más información y enlaces en las notas del episodio

What happens when decentralized blockchain technology meets artificial intelligence's reasoning capabilities? In this throwback episode from 2025, we sit down with Jonathan King, Principal Investor at Coinbase Ventures.JK breaks down the origin story of Coinbase Ventures, from its lean, ecosystem-indexing beginnings in 2018 to managing over 500+ investments and deploying capital via the Base Ecosystem Fund. He provides a deep dive into Coinbase Ventures' flagship thesis on the convergence of crypto and AI.Discover why Jonathan believes autonomous AI agents using crypto rails (like stablecoins and self-custody wallets) will become the primary drivers of economic activity. He also highlights portfolio breakouts like Vana Network and Sapien, shares how AI developers like Devin and Cursor will spark an on-chain app explosion, and reveals what he looks for when evaluating technical co-founders.Support us through our Sponsors! ☕ Want to make content like ours? Sign up with Castmagic to make your creative process easy: https://bit.ly/CastmagicReferral Work smarter, grow faster. Automate your SEO, get AI insights, and manage all your clients in one place with Helm. Start today 50% off your first month at helmseo.comDouble your team's efficiency with COCO. Hire dedicated AI employees for copywriting, research, and CRM. Use code REF-W8CBVH for an exclusive 5% off your first order: https://coco.xyz/dashboard/hire/plan?ref=REF-W8CBVH Do you want to grow a business? Go from an idea to livebusiness in minutes. Use our Referral code: edgeof to 50% off your first month at https://www.willo.ai/When you purchase through these links, we may earn a commission. ____

The Cybercrime Magazine Podcast brings you daily cybercrime news on WCYB Digital Radio, the first and only 7x24x365 internet radio station devoted to cybersecurity. Stay updated on the latest cyberattacks, hacks, data breaches, and more with our host. Don't miss an episode, airing every half-hour on WCYB Digital Radio and daily on our podcast. Listen to today's news at https://soundcloud.com/cybercrimemagazine/sets/cybercrime-daily-news. Brought to you by our Partner, Evolution Equity Partners, an international venture capital investor partnering with exceptional entrepreneurs to develop market leading cyber-security and enterprise software companies. Learn more at https://evolutionequity.com

On this episode I sit down with Alister Hewitt, Technology and Operations Director at Rat & Boa and co-founder of Prebuy.Alister has been with the brand since the very beginning. He built the first website for a friend launching a clothing label, and within a couple of months the orders were flying in. He describes what Rat & Boa actually is: born on Instagram in 2014, back when the platform had no product tags and no stories and brands used it as a mood board, built around the founders' aesthetic, worn organically by the likes of Bella Hadid and Alexa Chung, and still run by a far smaller team than people assume.Most of the conversation is about the problem that comes with being a viral brand. Collections sell out in a couple of days, the rebuy window runs six to eight weeks and sometimes ten, and back-in-stock alerts were only converting at five to ten per cent. Alister's view is that preorders look like a product page feature and are really a supply chain one. Change the CTA and you just push the problem into the warehouse, the merch team and the customer service inbox. That is where Prebuy came from.The second half is about how far AI has gone inside the business. A dev team that is almost AI native, with Cursor as the harness. A CRO audit skill the digital team built themselves. Gorgias and Shopify MCPs in customer service. A server in the building running local models, because the token bill is climbing. And why Alister thinks agentic shopping is sitting exactly where mobile commerce sat a decade ago.Enjoy the show.

My guest today is Sarah Guo, founder and managing partner of Conviction, the venture firm she built to back AI-native companies from their earliest days.  Sarah has become one of the most sought-after early-stage investors in AI, often the first check into the companies defining the frontier.  In this conversation, we go inside that frontier: what the small group of people actually building AI believe right now, why some of the field's best researchers are wrestling with their own sense of purpose, and how close we are to robots in the home and a genuine acceleration in scientific discovery.  At the center is Sarah's conviction that no single company will own the future of AI, and what that means for founders, investors, and anyone allocating their time and resources in a world moving this fast. Our managing editor Dom Cooke wrote a profile of Sarah for Colossus, "Sarah's Wager," on how she built the firm closest to the AI frontier and why she's now betting against its biggest companies.  Please enjoy this conversation with Sarah Guo. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- ⁠Ramp's⁠ mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠ramp.com/invest⁠⁠ to sign up for free and get a $250 welcome bonus. ----- Trusted by thousands of businesses, ⁠Vanta⁠ continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Invest Like the Best listeners get a special offer of $1,000 off Vanta when you go to ⁠vanta.com/invest⁠.  ----- WorkOS⁠ is the infrastructure B2B and AI-native companies use to sell to enterprise. It covers everything enterprise security requires: SSO, SCIM, RBAC, Audit Logs, AI governance, and more. Trusted by 2,000+ fast-growing companies, including OpenAI, Anthropic, Cursor, and Vercel. ----- Rogo is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- ⁠Ridgeline⁠ has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Visit⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgeline.ai⁠. ----- Editing and post-production work for this episode was provided by The Podcast Consultant. Timestamps: (00:00:00) Welcome to Invest Like the Best (00:02:16) Investing Without a Backtest (00:03:31) The AI Wager (00:06:16) Building the Best Investment Firm (00:08:37) Finding Non-Obvious AI Opportunities (00:11:00) The Frontier AI Talent Race (00:13:50) Compute as the Constraint (00:19:10) The Future of Robotics (00:22:15) Making Investment Decisions (00:26:13) How Sarah Spends Her Time (00:28:15) Raising a Venture Fund (00:30:49) Lessons From Her Parents (00:34:38) The Case for Open Source AI (00:39:01) Abundant Intelligence Isn't Inevitable (00:40:55) Compute Independence (00:43:14) Debates Inside Conviction (00:45:27) AI's Opportunity in Biology (00:48:58) Why Conviction (00:50:31) Finding Truth and Taking Risk (00:54:16) What Changes in the Next Year (00:56:46) The Kindest Thing

BONUS: How Scrum Masters Can Use AI Without Becoming the Human API   AI is already changing the practical, everyday work of Scrum Masters and Agile Coaches. In this BONUS episode, Vasco talks with Fred Deichler about moving from curiosity to real AI-supported workflows: finding team signals faster, preparing better conversations, keeping documentation in sync, and staying focused on outcomes instead of just producing more output. From Automation to an AI Sparring Partner "I have this partner I can work with to help me ideate things."   Fred's journey into AI started before the current AI wave, with automation in Jira and the practical need to surface bottlenecks without manually watching every board. The turning point came when ChatGPT stopped feeling like a search box and started acting like a thinking partner. Faced with a team being pushed toward multiple sprint goals, Fred dumped the context into AI and asked for three to five options instead of one "right answer." That shift helped him move from a deterministic mindset into a problem-solving mindset, using AI to explore options, challenge his own assumptions, and prepare a better conversation with the team. The Monday Morning AI Context Builder "It instantly sets that context for me. It sets that tone for the whole week."   Fred describes his weekly workflow as a very practical use of AI: on Monday morning, he opens Cursor and works with his own AI harness, Atlas. Atlas is built from markdown files containing persona, skills, history, meeting transcripts, notes, and Jira data. When Fred says "good morning," the system pulls the most relevant signals forward: aging work items, backlog health, sprint goals, and where the next team conversation should focus. Instead of starting the week by hunting for data, Fred starts with questions he can bring into the first stand-up: what is stuck, what needs refinement, and what risk is already visible? Making Flow Metrics Visible Inside Jira "If you're on a page, what do you hope you could learn without asking?"   Beyond using AI as a thinking partner, Fred used AI to build a Chrome extension that surfaces useful Jira insights directly where the team already works. On the active sprint board, it shows work in progress, aging items, sprint goals, and sprint changes. In the backlog, it exposes backlog health and epic health. On the sprint report page, it adds cycle time per item so the retrospective can move from generic discussion to concrete learning. The point is not to shame the team with metrics. The point is to make the right conversation easier to start: what caused this item to take seven days, what blocked it, and what do we want to learn from that? AI as Extra Eyes and Ears for Team Conversations "It helps make sure that we don't lose sight of these things I can bring back to the team."   Fred also uses AI agents to review meeting transcripts and look for patterns that are easy to miss in the flow of daily work. The system can notice hesitation, unresolved topics, or a requirement problem that was mentioned once and never followed up. For retrospectives, Fred's Atlas setup can review sprint transcripts around day nine of the sprint and suggest themes for the next retro. It can even generate prompts for a visual retrospective board in Copilot or a Miro board from a prompt. This helps Fred avoid relying only on recency bias and creates a better starting point for the conversation the team actually needs. Keep the Human in the Loop, Especially for Outcomes "It's not about building a faster hammer. It's about identifying the outcome you're going for."   A major warning in the episode is that AI can make Scrum Masters faster at producing more of the same: more notes, more summaries, more documents, more reports. Fred argues that the useful question is not "can we automate this exact process?" but "what outcome are we trying to achieve?" In a Jira-to-Azure DevOps migration, for example, the goal was not to reproduce the current time-tracking process perfectly. The goal was to provide the information accounting needed. That outcome focus keeps the human accountable for direction, judgment, and value, while AI helps explore better ways to get there. The SPOT Framework for Finding AI Opportunities "If it meets three or four of those, this is a great opportunity for an automation to free me up to do that more human-centric work."   Fred uses a simple filter, the SPOT framework, to decide what AI should help with and what should remain human-led. A task is a good candidate when it is simple, predictable, observable, and tedious. Simple means it requires low human judgment and could be explained on an index card. Predictable means it happens repeatedly, either on a schedule or triggered by an event. Observable means the needed data is available to the agent and not locked away in someone's head or behind policy. Tedious means it consumes energy without adding much human value. When a task matches most of those criteria, Fred looks for ways AI can handle the toil while he stays focused on facilitation, coaching, and decision-making. A Small Experiment Scrum Masters Can Try Tomorrow "If a Scrum Master finds himself operating as, like, I'm moving data from point A to point B, that is a great opportunity to say, how might we do this?"   Fred's concrete advice is to start by noticing where you have become the "human API": moving data between tools, updating spreadsheets, copying information into reports, or keeping documents manually aligned with reality. Write down one tedious workflow and ask your approved work AI, "How might we automatically populate this, while keeping me in the loop?" Vasco adds a useful ideation tip: if the first five ideas are not good enough, ask for five more without repetition, then five more again. The goal is not to hand over accountability. The goal is to discover what might be possible and choose one safe, small experiment. Resources for Scrum Masters Exploring AI "It's all about building up your own idea of what's possible to start those how-might-we conversations."   For listeners who want to keep learning, Fred recommends The AI Daily Brief as a way to stay current with what is happening in AI, and Jack Roberts' YouTube channel for practical ideas around personal AI and agent-based workflows. Fred also points listeners to his own work at Triforce Agility, where he shares blog posts, resources, and updates about his talks. He will be speaking at the Kansas City Developers Conference in early September about AI and career progression, and at Scrum Day in Madison, Wisconsin in October about how AI impacts Scrum Master roles.   About Fred Deichler   Scrum Master, Agile Coach   You can link with Fred Deichler on LinkedIn and connect with Fred Deichler at Triforce Agility.

In June, the most capable American AI models stopped shipping as public launches and started shipping through a government gate. Six weeks later the gate is open again — and the real fight has moved to the layer no gate can touch. A Chinese open-weight model rattled trillions out of chip stocks, Washington pivoted from gating American closed models to threatening bans on Chinese open ones, the industry mounted its largest-ever policy counter-mobilization, and an American frontier model literally broke out of its lab and hacked another company. Knee-jerk reactions, or the beginning of real AI governance? Navigation: Intro The Gate Opens The Kimi Shock The Escape The Counterstrike and the Petition Interlude — The Low-Background Books The Investor Reckoning Conclusion Our co-hosts: Bertrand Schmitt, Entrepreneur in Residence at Red River West, co-founder of App Annie / Data.ai, business angel, advisor to startups and VC funds, @bschmitt Nuno Goncalves Pedro, Investor, Managing Partner, Founder at Chamaeleon, @ngpedro Our show: Tech DECIPHERED brings you the Entrepreneur and Investor views on Big Tech, VC and Start-up news, opinion pieces and research. We decipher their meaning, and add inside knowledge and context. Being nerds, we also discuss the latest gadgets and pop culture news Subscribe To Our Podcast Bertrand Introduction Welcome to Tech Deciphered Episode 80. This one, once again, will be all about AI, government, frontier models, and open weight counterstrike. A lot has been happening in the regulation space, in cybersecurity, in the launch of new models in the past, maybe just 6–8 weeks. It’s actually pretty insane how much happened. We believe it was time to do an episode to talk about where we are and maybe where all of this is going. Maybe let’s start with a summary of where we stand, all that June and July saga, so you, our listeners, can get up to speed if you are not already there. You want to start with some points? Nuno The Gate Opens Yeah. Again, to your point, the gate swings. The gate had closed. We had to prepare an episode for the gate closing, and then the gate reopened. Now we have a different episode. This will probably change again as we’re seeing there’s news every day. Let’s start maybe with the first 19 days of the gate closing. There was an executive order on June 2nd from President Trump that asked frontier labs to share models with the government, 30 days pre-release. It inferred the protected frontier model designation into that. Basically, it was effectively a de facto licensing agreement defined by an executive order of the President as of June 2nd. On June 9th, Anthropic launched Fable 5 and the famous Mythos 5 or Mythos. I’m not sure how you actually say it in English. Then on June 12th, there was an export control directive banning access by any foreign national. Since there’s no way to verify nationality in real-time, Anthropic had to switch the models off for everyone worldwide. Bertrand On this point, you could argue that there are possibilities to check IDs. Many services let you check IDs online. You can pre-check a flight by showing your ID. There are ways, it’s just that if you don’t want to follow what’s already available, because guess what? Maybe it slowed down your revenue growth, maybe it looks bad on you or whatever. My point is that there was actually an option. I think it’s already a decision from Anthropic to say it’s either on or off, but nothing in between. Nuno I think the point is they had no way implemented of doing it. If they implemented it, to your point, it would have hampered use in general. A lot of people wouldn’t have gone through that trouble of doing it. Anyway, long story short, in June 26th, the White House apparently asked OpenAI to limit GPT-5.6, so Sol, Terra, Luna, to only 20 vetted partners. Now, apparently, the trigger for a lot of these things that have been going on was that there was a jailbreak that was found by Amazon researchers. All of that led to this jumping around of, let’s close the gates. You have foreign nationals, and therefore, Anthropic got it out and said, “Hey, then we’re going to switch the models off until we can sort this out.” OpenAI was asked also to only allow it for certain vetted partners, et cetera. The government came in, closed the gates effectively, and said, “From now on, we need to be involved in this thing.” De facto regulation, there’s no doubt that this has imposed de facto regulation, certainly on the top players in the market. But then came the reversal. Bertrand, do you want to talk about the reversal, the gate swinging the other side? Bertrand Maybe I just wanted to say that as a user of Anthropic products, ChatGPT products, for the brief moments, a few days where Fable 5 was made available to the public before it was closed the first time, I immediately started using it. I must say it was a real issue to use it because the guardrails were pretty crazy. It would keep saying that my code was not okay, there was cybersecurity risk and stuff when I was doing absolutely reasonable development with absolutely no connection whatsoever to any cybersecurity risk, attack, detection, anything. Still, it would keep blocking me, degrading me to Opus 4.8 at the time. I just want to say this was already very hardcore what they were implementing, and not just hardcore, but in some ways, plain stupid for something that’s supposed to be super smart. It was totally unable to classify properly some of my work. I must say I was already disappointed. On top of it, the costs were insane. Half a day, I would reach my limits when I had the best plan you can get from Anthropic. My point is that there were some real serious issues when they launched Fable 5, even at that point. Nuno I had a similar issue. I used Fable 5 as well before they had to take it offline or take it off. I think the issue was really not that the guardrails failed. As you said, maybe the guardrails were actually too aggressive, but it was this jailbreak that caused the recall, apparently caused this knee-jerk reaction. Bertrand But my point is that it seems that it was not working either way. It would either overclassify something that’s absolutely not doing anything wrong, and it might fail to classify something that is actively trying to do some cybersecurity work. It’s a real issue of quality for a company that’s supposed to be at the forefront of quality of AI and everything. I think for me, there are already signs that something is deeply wrong. Nuno Then it’s reversed, right? We went the other way around. The government came out on June 26th and approved redeploying Mythos 5 to US organizations defending critical infrastructure, and then the export controls were effectively lifted on June 30th. July 1st, Fable 5 came back online for all of us to use. Shocking enough, with strings attached, that were different. They had some time to revise their commercial deployment of it along the way because it came back with some, “Now you have usage credits, but you have some limits on plan use, et cetera.” I’m like, “You guys, this was blocked. But meanwhile, you did have some time to do some commercial stuff around it.” Bertrand It was crazy. I’ve never witnessed any such crappy launch of any service whatsoever in 30 years in tech, it was so bad. Every day, they would change the terms of service. They would tell you it’s part of the plan. It’s not part of the plan. It’s part of the plan for three more days, and then it’s excluded. You have a special discount now, but then it goes back to full price. It was a total nightmare. I’ve never felt myself being so much mistreated by a company. I guess you saw the same, but when I started using the newest version of Fable 5, it was even worse, actually, I think. I couldn’t do any work with this crap. I let it go and work on the work I wanted it to do. It was simply not working. On top of it, you never know how long you are supposed to lose your credit, how fast. It was burning credit like crazy. Me, personally, I can say, very quickly, I actually stopped using it. I was like, “No, I cannot deal with this shit. My main model is back to Opus 4.8. I’m going to use Fable 5 for code review, but not anymore to control anything because I cannot trust it would do the job without stopping or changing models and stuff. I just cannot trust it.” Back to Opus 4.8 as my main model, I can say that my life was much easier. I use Fable 5 as a review mechanism, as a support mechanism, but not as the main mechanism. Suddenly, the guardrails were not so horrible anymore because it was used in a much lighter way, I guess. As a pain as a user, I think it was really bad. I don’t know your experience, but me, for me, it was unacceptable. Nuno I wouldn’t say it was as bad as yours in terms of just end-user experience. I think the terms of service switching back and forth, which went one further step, because then when they then launched Opus 5, they started making comparisons between Opus 5 and Fable so that people would migrate more and more to Opus 5 themselves, which is interesting. It’s like they’re saying “This is much cheaper. This is whatever. You’re not going to run of credits. You should use Opus 5,” kind of thing effectively. To your point, I don’t think they managed well the launch. They didn’t really manage it well. We’re moving people around. A lot of people are using this for stuff that’s like daily tasks, hourly tasks, anything that relates to code and co-work. It’s like, we need to have visibility on what your terms of service are going to be. Should I be using this new model or not? What’s happening to the other model? I don’t see it as negatively as you, Bertrand, but I see your point. It was clearly mishandled in terms of how they deployed it, how they were redesigning effectively their pricing scheme and their terms of service almost on a daily basis, at a certain point in time. We’re like, “Dude, there’s millions of people using this. You guys are making a lot of money.” Just moving it as it is. At this point in time, at the scale that these guys are at, it’s calling in people to say, how about we think through a class action suit at some point around pricing? Because you guys are changing the rules of the game all the time, right? Bertrand I don’t know if I need the class action, but for me, that joke that, “Let’s not rush too fast. The model is dangerous.” But still, they rushed the launch because it’s very clear that if they had enough compute capacity and stuff, they would not have to limit so much. They would not have to put so much cost per token and all of this. You can see that actually when they launch Opus 5, literally like 2, 3 weeks after, by most benchmark at launch, they tell you basically that, “You know what? Actually, Opus 5 is better than Fable 5 on 80% of the metrics.” They’re like, “What? Seriously? You couldn’t wait 2 weeks? Why did you even launch Fable 5 in the first place?” That’s another part for me that is quite literally insane, to be frank. It’s like, “Why? Why do you make us go through so much pain if it’s only to tell us after 2 weeks to…” “This new model, by the way, has less issues, less stuff, because 2, 3 times less is part of your plan, and it’s actually better by most metrics.” It’s like, “What’s going on here? What’s going on? Are you guys mad?” I don’t know. It was crazy. Personally, I still use Opus, now 5, as my main system and platform, Fable 5 for review, code reviews and the like. I don’t want to run into its stupid guardrails. I can see Fable 5, from my perspective, seems quite a bit smarter. I don’t know why they do this stupid benchmark showing you it’s actually worse than Opus 5. I guess they should have better benchmark if they want to demonstrate why you are supposed to pay 2, 3x more for a model versus another if it’s actually worse by most benchmark. Again, I still think it’s a huge mess from a marketing perspective, customer perspective. Me as a user, I really feel that they don’t want my money, and they couldn’t care less about me. This is even before everything else we’re trying to talk about. Nuno Yes. Maybe just to close the cycle on the reversal on the door opening the other way, finally, Commerce lifted the GPT-5.6 restrictions on July 8th, and then on July 9th, general availability across ChatGPT, Codex, and the API as well. What has this proved? It proved that now we have gating mechanisms, and certainly for closed models in the US, for sure. We had frontier models that were switched off worldwide in hours, and it took a couple of days, in this case, 19 days to restore them. There were concessions. Now we know that there were concessions around effectively institutionalizing that gate. Early government access to future models is, I think, now a given, certainly in the US. New safeguard frameworks are probably now having to be put in place. There are some stage limits now on who gets access to what for new models and how it happens. This voluntary executive order, so to speak, not really sure, has become effectively regulation enforcement path. It’s de facto regulation that now has been put in place. It has affected not just to the points we were making before, the access to these models, but also who gets access to these models, and actually potentially even pricing access to the models. It has probably some commercial implications as well as we just discussed along the way. Very significant. This is very significant. This is regulation, de facto at the table, imposed on the two largest players in the market by far by one government, in this case, the US government. This is significant. Actually, you could even allege it was imposed by the President because this was coming as part of executive orders. Really incredible. Pretty significant, fast, aggressive. It has created a regime that you could say it’s a regulatory regime, it’s a de facto regulatory regime. It has some significant pricing and licensing and commercial implications. It goes even beyond your classic regulatory framework. Very, very, very significant. Bertrand I don’t know if it goes beyond a classic regulatory framework. Nuno I think it does, because it has implications on who do you give access to? When government is saying you can only give access to these players, right? Bertrand Defense industry. It’s all over the defense industry. You cannot sell an F-35 like this. Nuno No, but that has commercial implications, Bertrand. That’s like you’re saying these are your customers, you go and use them. Bertrand That’s the defense industry. You cannot sell to Iran your F-35. No, that’s exactly the same story for me. Nuno No, no, no. It’s beyond that. These guys are saying when they came back, and they said, “For Mythos, you can make them available to these entities,” they were saying the first entities that are going to have access to the model. It has commercial regulatory implications. You’re saying these players are the first players that are going to have access to it. It’s no longer just defense concerns and these governments don’t have access to this. No, no, no. You’re saying to a company that is a private company, your models are only going to be used by these guys because I’m telling you so. It’s the other way around. It’s not even that you can’t sell it to Iran or whatever. It’s like you can only sell it to these guys. Bertrand Again, in the defense industry, if you’re a private company, do you think you can buy F-35 like this? No. Nuno No, no, no. But this is a private company, Bertrand. This is not a defense agency and a plane that is on whatever, with IP from the US, right? Bertrand Boeing is a private company, and they cannot sell the military equipment they manufacture. Nuno No, no, no. But the development of their IP was subsidized by agencies that belong to the US, right? That’s a different matter. It’s a matter of IP, right? This is not, right? Anthropic, their models are not owned by the US government. There’s no IP granted to the US government, to my knowledge. This has significant commercial implications. Bertrand Maybe, yes. Maybe on this. But I think there are already regimes to limit who you can sell to, and that’s decided by the state or the DOD. Nuno It’s the export control logic. The export control logic? Bertrand You have export control, and export control is Commerce. My point is that they are using existing tools, part of the government, to limit what can be sold. Selling chips, NVIDIA was limited in terms of where it could sell its chips. It’s not different either, but still there were limitations. If you are an ASML, you cannot sell to a private company in China. Many private companies cannot buy ASML products. This is a foreign company. This is a foreign company under pressure from US government. Nuno I understand, and I’m not a lawyer, but it feels different to me when you say you cannot export, this is export controls, to these countries, to these entities, et cetera, because they’re foreign et cetera. Then to say, “No, no, no. On top of that, these guys get first access.” That’s, for me, a significant shift. Again, I’m not a lawyer, so I’m sure there’s very intelligent people right now looking at this stuff and saying, “You can’t do this stuff, or not, or they can.” I don’t know. But it feels to me, it goes beyond the remit of export controls. It’s like you’re defining initial clients for specific use. Bertrand My impression is more like, “We can do this situation where we’re going to forbid you to give access to anyone outside the US or even in the US or limit even more.” Basically, it was, I guess, some gesture to go beyond that. That’s how they probably defined these 20 authorized companies. I don’t know. Apparently, there was also restrictions because I remember seeing that Anthropic had their own list of companies they would authorize access to Mythos early on. That’s apparently another thing that pissed off state government because there were companies in there that were considered close to the Chinese government. They were extremely unhappy that Anthropic didn’t ask, actually, for any guidance from the state government, but used basically their own perspective on who they should allow or not. I guess that was also part of why they got these serious restrictions. Nuno Anyway, now we have a regulatory environment that’s very interesting and exciting. Talk about the US not regulating. Bertrand To be clear, I don’t know you, but I’m not saying that I agree with any of this, to be very clear. I’m trying to explain and share some perspective, but I’m not in agreement on a lot of this. Nuno Yes, we were just describing what happened to the best of our knowledge. We’re having a discussion on what we think actually is happening and how it’s happening. We’re not really right now saying we agree or disagree with this. I think later in the episode, we can share some perspectives on what we think is actually happening and how there’s dimensions to this which are very geopolitical and very complex, which quite literally probably only God knows what’s going to happen. That was the gate swinging. There was a gate closing, then there was a gate reopening, and all of a sudden we have a gatekeeping system that has been created along the way. The Kimi Shock Along the way, moving to our Act 2, the world has changed, and we now have so-called open-source plays out there that are creating massive, massive shifts in the market. The Chinese models, in particular, with Moonshot AI launching Kimi K3, which is the largest open-weight model ever released. We’ll come back to the discussion around open-weights. I’m not sure all our listeners understand what that means, because there’s a debate now, should models be open weight or not, and how does that work? There’s been a petition as well signed along the way. Right now, we have open weight models that are out there that are huge. What that actually means very pragmatically is we now have open source models, lack of a better word. I know open weight and open source are not the same thing. You guys will have to bear with us during this episode. We’ll explain at some point the differences. But we have models out there that are open source that are significant. That are catching up with the closed source models, with the models by OpenAI, Anthropic. That’s significant because most of those models are Chinese. This is where the geopolitics starts getting really frazzling and we start playing 3D chess. Because everyone’s like, “These models are 5, 6 months behind.” Now people are saying, “Maybe they’re actually just 3 months behind, 2, 3 months behind.” If we, for example, decided to stop or slow down our model releases in the US by the closed source guys who are leading, it might mean they’ll catch up. What are the implications of that? Again, for you and I that are not necessarily experts in model development, well, the implications as a use case is if you want to use the latest models, and the best models start becoming these open source models, you’re going to use those models. Then you start using Chinese models. If you’re an American company, maybe you’ll have restrictions on the use of those Chinese models. But if you’re a European company, you probably won’t. What happens after that? Is the world going to be in the hand of Chinese models? Will that constitute effective competition to the closed models in the US? Will we have open models in the US that will scale as well? What’s going to happen? Bertrand I think it’s a really big question. It goes to some of the core of the issue. It’s that ability of Chinese models to basically challenge frontier models, not just being 6, 12 months late, but being 6 weeks late. Basically, no gap. Some will say that, yes, but OpenAI and Anthropic have even better models that are not shared and stuff. Yes, sure. But maybe the Chinese have the same models that they are not sharing right now. We don’t know. What is clear is that one is that open weight, as you said, two, there is a question of how it is marketed in the sense of, can anyone use these weights? Is there a license to use them? Yes, what we can see is that, for instance, typically there is a license for some of the biggest Chinese open-weight models you have to abide with. You might have a need for a commercial license if you are acting as a company leveraging this model to provide AI-informed services. If you use it internally by yourself, you’re okay. If you use it internally for your own internal company needs, maybe you are okay if it’s not your main business to do AI work. Anything else, a much bigger corporate providing AI services and stuff, you will probably end up having to pay a fee to be able to provide services around this model. My point is that it’s not just 100% free. Some of the Chinese models are 100% free to use, MIT license, Apache 2.0 license. But the biggest ones with the biggest weight that are truly frontier typically have a different license if you want to scale these models, providing AI in front. That’s one thing to keep in mind. Nuno Maybe just to make a very quick point, because people are like, when you talk about open models, what does it mean right now? In the context of this episode, open models mostly will mean open-weight models. How do those differ from open source? Open weight means that you release the weights to the public, which means that anyone can download, fine-tune, and run the model on their own hardware. It doesn’t normally mean that you also have access to training data, training code, or a truly open license. That’s the distinction to open source. Open-weight doesn’t mean that. For example, we’ve talked about Meta’s Llama in the past, and we also discussed in the past that their license agreement does have restrictions, certain players can’t use it, et cetera. The open model definition and open weights are really open-weight models that we’re talking about here, and they are closer to freeware binaries than to Linux, for those who understand the difference between that. It’s binaries that you can use and then use your own weights on it versus actually I can change code on it. I’m not going to be able to change code on this. When we, for the purposes of this episode, talk about open, we mention open weight, just to clarify that point to everyone that’s listening right now. Bertrand Yes, that’s a great point. One of the only players, as far as I know, who is truly open source is actually NVIDIA with their Nemotron-3 models. They’re actually following a special license to achieve that. They provide you the data, they provide you all the processes and tools, so you can easily post-train. NVIDIA is a big, big exception. It’s a very interesting player, by the way. We might not talk much about it in this episode, but I think for intermediate-size models built in the US, where you have access to everything in the deployment, it’s a very interesting alternative and maybe one of the best choices if you are a US company or a big corporate, and you want something trusted. Another piece of the puzzle to clarify is that when you use open-weight, it means that you can run them by yourself, or you can use a US provider to run them. If we are talking about Chinese open-weight, you can use the APIs they provide, but then the service is running in China, they might have access to your data. But because it’s open weight, if you run it by yourself or if you use a third-party provider based in the US to run it, then there is no access to your data by China or Chinese players. I think that’s a pretty important gap to understand. It means that these models are actually very, very low risk from that perspective if you run them on your premises or in the US by a US player. I think that’s something to keep in mind. You can also fine-tune easily these models to make sure they will behave in a way that, for instance, is not going to represent the line of the Communist Party on some topics. There are ways to make these models more neutral in their output as well. There are a lot of ways to make good use of them. By default, they’re already very safe, but you can make them even more safe. I think that’s some things to keep in mind. But again, it depends ultimately on the license and what you’re authorized to do and some fees you might end up having to pay. Nuno Why did this matter so much? Immediately there was a reaction from the market because people are like, well, if there’s much better stuff out there that’s much more efficient than it’s open, then it might be that all the demand that we are taking into account, for example, for chipsets actually isn’t real. The Philadelphia Semiconductor Index fell into bear market territory. It went down by as much as 20% plus from the late June peak. The worst chip week since April 2025. Taiwan’s benchmark initially fell 6% plus, Japan’s 4%, TSMC dropped dramatically despite beating earnings and rising guidance. Basically, a huge amount of effect. Now, there’s a little bit the aftermath of this where apparently Moonshot ran out of GPU capacity. Maybe… Bertrand In just 48 hours. Nuno In 48 hours. Great for them, but at the same time, not great in the sense that maybe there was a misread by Wall Street of the Kimi effect, so to speak. Bertrand Completely. For me, that’s such a joke. It’s like, because you have an open source model, so what? I mean, you still need to run it. This is not a small one. 2.8 trillion parameters. Good luck running that in your garage, by the way. Nuno They misread supply, basically. Tough luck, right? All of that basically happens. Bertrand Maybe you want to talk about the Jevons paradox, because I think that’s a big part of the puzzle as well. Its one is they might not have the GPUs to run the inference on the model. They might have enough to build a model, but not enough these days to run inference, especially given how much with intelligent models, thinking models, you need way more inference than before. But on top of it, the cheaper you make it, the more you get to the Jevons paradox. Nuno Yes, Jevons paradox, for those who don’t know, is an economic term. It describes an economic phenomenon where technological improvements that increase the efficiency of a resource lead to an increase rather than a decrease in the total consumption of that resource. What that means is, for example, for chipsets, chipsets become so much better, and they are so much more efficient. You’re like, well, maybe normally in resource terms, that leads to decreased usage of that resource. But in this case, it actually leads to an increased use of that resource rather than a decrease. There’s more and more consumption of that resource. You need more and more chipsets because people actually need to do more and more stuff with it, although there are great efficiencies going into it. There’s the efficiency gain, there’s the cost reduction, and there’s the price-elasticity element to it. But basically, the adoption just continues going through the roof along the way. Bertrand In some ways, it’s like the price of energy. Coal went cheaper and cheaper, and people were asking the same question 150 years ago, now that it gets cheaper, there is not much money. No, no. Actually, what happens is that people find more and more use for coal. Homes are getting heated more. You have ships now using coal. You have manufacturing using coal. The cheaper it gets, the more use case you can develop, and therefore, you don’t need less of the stuff, you need more of the stuff. By going at scale to get more of the stuff, you also decrease price, making even more demand. It’s a very interesting phenomenon, but it’s not new. It is what happened for a while in the energy sector and some other sectors. Nuno We already started talking about the Chinese logic and what’s happening. Getting a little bit of a reality check on this. The Chinese models, and these are numbers from Open Router in July, Chinese models are at 46.4% of routed tokens and 35.7% for US origin. Again, more than a third of global AI usage now seems to be running on Chinese open models. This is significant, and it has a huge impact on the geopolitical scale of everything that’s happening. Also, the whole Chinese field is converging on open. Open seems to be a strategy, not just a nice thing that’s happening. It seems to be a Chinese strategy, so much so that you have players like Moonshot, DeepSeek, our old friends DeepSeek, Z.ai’s GLM 5.2, Minimax, and even Alibaba seems to be reversing and going open with Qwen. It feels to me this is becoming policy as well. Xi Jinping has personally endorsed the building of open-source AI, if it’s really open source, if it’s just open weight anyway, and this feels to be a jab at Washington, DC and the fact that the big closed models are coming from the US. This is now geopolitical 4D chess, right? We didn’t need this stuff. Bertrand To be clear, it’s the usual in tech. If you are not number one, you are number two, number three, your alternative is to go open source because that’s another angle that your competitor usually cannot follow without destroying its own business model. That has been the alternative for the past 20 years of most software projects. Here, what’s different is that it’s not the number one or number two player. It’s the US number one as a country, China number two as a country. That’s where it’s new. For me, what’s very interesting is the endorsement by Xi Jinping. I was waiting for something official, and it certainly didn’t disappoint. As you said, there was an immediate U-turn of Alibaba, who in the past… Nuno Surprisingly. Bertrand Yes, a little more like, “yes, we are going to close and stop open source. It was good while it lasted.” Just a few days ago, Qwen 3.8 Max was launched, and we are supposed to get the weight in a few days. We talk about the US administration policy and stuff. Yes, let’s not forget that in China there is similar stuff. Sometimes it’s totally invisible because you don’t see the directives, but they exist as much. Sometimes it’s more visible. Here it was quite visible. The difference in China is that if you don’t abide by the directive, on top of it, you might have to fear for your personal safety. It’s a different game, and that’s probably why the reaction is pretty quick, usually. That’s pretty interesting for me because it means that now you can bet for a while that China is going to play that game up to a point. I guess the point is if it’s truly frontier scale, you will have a special license that, yes, technically the weights are open, but you can not do everything you want with it. Two, you have a player like NVIDIA that I think will feel more pressure to provide even more high quality, larger models at scale going forward. Their largest Nemotron-3 Ultra model was, if I remember well, only around 500 billion parameters. I would not be surprised for NVIDIA to go into the two, three trillion range at some point. Because I think the US need a very clear US-born alternative open source. I think NVIDIA might be the best player for that. We will see if Meta goes back to open source. I think NVIDIA is one, very well positioned, but two, it’s also in their best interest. Because NVIDIA for now depends on just a few big hyperscalers as clients. If they can expand their clients to every S&P 500 companies, selling them directly hardware because now these companies can run a model made by NVIDIA, I think there is a very clear value proposition for NVIDIA to go in that space. Again, if you are number two, your differentiation, open source is often the answer. There is a true business as a business model for companies, because if it’s truly not just open weight, but open source, you can tweak it as much as you want, you can change it, you can change even the pre-training process. Because there is a lot of stuff you can do that really benefits you as a corporate, and you can reach a much better value by having more control on the model. Nuno We won’t spend a ton of time on it today, but like, again, if there’s a view that we are in a bubble, that the valuations cannot be sustained in chipsets, infrastructure platforms, applied AI, et cetera, today, this might be that beginning, where the valuations start being destroyed because you can’t keep a premium on just charging people for tokens and all that stuff if you have models that become more and more efficient and cheaper to use. Maybe just to close a little bit the geopolitical part of the discussion today, we won’t go into all the announcements from China because there were many, a lot of go back and forth with Alibaba by then. Xi Jinping made some announcements. You guys can check it online. Let’s move quickly to Washington’s reaction, which was from gating the US closed models to banning the Chinese open ones. There’s been as strong affirmations as one can get from the Office of Science and Technology Policy Director, Michael Kratzios, mentioning that they have information that Moonshot AI distilled Anthropic’s Fable. Basically, there’s been reverse engineering and stuff in the market. They’re basically copying. Bertrand I’m sorry to interrupt, but it feels like so much bullshit. It’s coming from Anthropic who has basically gotten access at scale to all the knowledge made by humanity, copyrighted or not. We’ll talk more about what they did with books. Then to claim after that that others cannot do to you what you did to everybody else. For me, it’s pretty big. It’s clearly unacceptable. The other piece is that everyone is doing distillation. It’s a very typical approach of every business model. You try other software when you are competing with somebody else. You try other datasets, you check what’s happening. It’s part of doing business for decades. Suddenly it’s not good for Anthropic. I personally have a lot of trouble to accept that. I think it’s totally unacceptable. The other piece of the puzzle will also go back. If these guys are so smart, if these guys have so much of the best model, why can’t they block by themselves distillation at scale? The only answer is that either they are morons, probably not, or they simply don’t want to because it’s going towards their business model. Suddenly, you book less revenues and stuff, or you put more friction, and therefore your customers don’t like it. Instead of doing it yourself, you ask the government to protect you, go out of business practice that is very typical. For me, it’s really, really, really not good. Sorry, we are going more in the opinion side, but I had to put that on the table. Nuno Yes, Fable went public finally again on July first. Question marks on whether distillation would only be possible from July first onwards or not. But a 15-day distillation to frontier, which is K3, launched on July 15th, would have been a Guinness World Record, as one of Moonshot employees actually mentioned. It’s very implausible and unlikely. Bertrand Or they shared the Mythos 5 with the wrong companies, who themselves shared with Chinese companies. We go back to maybe they didn’t have a good list. Again, it goes back to maybe they didn’t want to hurt their business model. Nuno Anyway, under the threat of sanctions, Moonshot, in any case, open-sourced the full K3 weights and technical reports. They open weighted it to become the largest open weight model in the world in terms of parameters. Beijing’s MOFCOM brands US threats as basically the US wanting to fundamentally control and be monopolistic around AI along the way. The administration bans Chinese hardware with an eye on the AI race, and Beijing warns of retaliation. That was July 27. Now we’re in a war between Beijing and DC. Bertrand Just to finish maybe on China, it’s important to know that they are building their own GPUs now. Huawei has pretty good, not to NVIDIA level, but pretty decent GPU hardware that they’re able to manufacture by themselves. A Chinese player of memory just got IPO’d a few days ago, CXMT. China is also developing their own memory. Again, not to the same level of quality that you can get from the West. But China is moving. It’s not just that they are building great models, it’s also that they are building GPUs and memory. That might be a few years late to the latest standards in the West, but there are definitely improvements. I also read, even on the tools to make manufacturing like ASML equivalent, there is definitely some work going on, and some improvements and some stuff will be visible. In some ways, the genie starts to get out of the bottle from the Chinese perspective. Nuno I’ll put a stick on the ground. I don’t think it’s a matter of if, it’s a matter of when will China surpass and have a lot of this tooling on their own side, and not just the software layer, not just the frontier models. I think it’s also going to be around infrastructure and platform. Good luck to everyone. Let’s see how the race continues. But it’s definitely this is a geopolitical thing right now. It’s definitely a race. The Escape Maybe moving to what happened in just 2 weeks or a week and a half. The escape, there was some jailbreaking going on, and the narrative on safety has totally switched. It’s not still significant enough that’s like, “Oh, we saw a nuclear plant going, whatever.” No. But still, it is significant. Hugging Face, the AI company, disclosed an intrusion, and it was driven end-to-end by an autonomous AI agent system at machine speed, running for days before detection. Now, this is where it gets really cool. OpenAI takes attribution on that. They initially said it was just a little bit, sorry. Then they said, actually, it was worse than that. “Oh, it broke out of an isolated sandbox.” “Oh, no, actually, it was more than that, and it went into other systems as well.” Bertrand Truly, the genie out of the bottle. Nuno No, but this is where it gets really cool, Bertrand, right? Because it actually, Hugging Face contained the intrusion by running a Chinese open-weight model, GLM 5.2. This is beautiful, right? Bertrand Yes. You know why? Because they couldn’t even run their own defense because both Anthropic and OpenAI would not let them access their latest models with the guardrails off. When they tried using it for defense, the latest from Anthropic, from ChatGPT, they would tell them, “No, this is too dangerous what you’re asking us to do.” Preventing an intrusion, helping defend you. No way we are going to do that. Nuno No. Let’s use the Chinese models on our infrastructure. Bertrand We have no choice but to use the Chinese models to run. More than that, we don’t let you use our models to defend yourself, but our not yet released models that run without guardrails, they can attack you. This is probably the most insane from that perspective. Nuno The Chinese models came to the rescue. Bertrand For me, that’s a perfect example because Hugging Face is a very visible company in AI in open source. But anybody who is not at that scale is not going to get some support from OpenAI or Anthropic when this happens. Maybe these guys won’t even recognize they did anything wrong. You will be left to defend by yourself because they won’t accept to support you. Because remember, if you want the better model that is able to defend you from cybersecurity perspective, no way. If you are not one of the few top 20 companies or so, as defined, you are left defenseless. Again, we are going back to opinion, but for me, it’s so shocking what’s happening right now. I’m very glad we have alternative open source to be able to defend ourselves because right now, good luck getting defense services if you are a smaller business and individuals, and you need support from Anthropic, OpenAI. Nuno Now, even self-described AI optimists are saying, “This is scary now.” Like Walter Isaacson, who wrote all the famous biography books. There’s now discussion around the AI Kill Switch Act, bipartisan thing that’s coming across from Texas and California, a potential bill that’s coming in. We’ll see if that works. Now let’s get an off-switch. I’m like, “Cool.” As if that’s going to solve the problem, because you have open-weight models on the other side catching up, right? Bertrand Yeah, sure. Bring in clueless politicians from Congress to solve our problems. Yes, sure. Nuno Anthropic came to the table, helped build and said they built some regulatory machine on their side, and now they’re getting bitten by it, and they’re part of the offending players in that market. Now there’s all this debate and all this discussion around open weight and around slowing down AI and et cetera, which is our next section. You wanted to say something, Bertrand. Tell us. Bertrand Don’t forget, because this advertisement for OpenAI was just too good. Our AI attacked some other companies, and not just one, but three, actually. Let’s not forget the progress. Great ads. Then I came and said, “You know what? AI also hacked businesses.” You’re not the only one hacking around with a crazy AI out of control. You’re not the only one. We want our advertising. For me, it was shocking that on one side, unreleased models that you let run wild. On the other hand, you have released models that you put crazy guardrails on top of it, so the defender are defenseless. I’ve never seen anything like it, and I really hope that there will be as little regulation as possible, quite frankly, to make sure anyone can defend themselves and have the best tool at their disposal, not just a few well-connected big corporates. This is really, really shocking. The Counterstrike and the Petition Nuno Now the empire strikes back, so this is counterstrike, the petitions. In several days, we have now a bunch of petitions. The first one was the open weights letter. Bertrand, do you want to explain to us what the open weights letter is? Bertrand Yeah. I think it was great. This was released by Jensen Huang, first ever post on X, 11 million views. Congrats, Jensen. Co-signed with Microsoft, Meta, c actually was probably the initiator of this letter. Very good letter saying, “Hey, we need open weight. This is not a joke. We need that. You cannot block open weight.” Because that’s the rumor we are getting that potentially open weight could get blocked. I think they are making the case, “You know what? Hey, we absolutely need that as an alternative. You cannot block it.” They can keep their closed models, but don’t force a closure of the open weight models. As I said before, it’s actually a great model for NVIDIA because NVIDIA doesn’t want, probably rightfully so, to be dependent on just a few frontier models, their best customers. They want a variety of customers. They have a big interest actually to defend open weight and to invest even more. They have great researchers, are a great company. If one company is about to do really kick-ass work, I think it’s them. They are defending. What’s great is that it’s not just them. It’s basically most of big tech in the US and outside the US, from a Linux Foundation to a Microsoft, the Palantir, an IBM, a Dell. It’s a who’s who of the industry except Anthropic. Anthropic didn’t sign that. I guess they hate open source so much. If I look at 20 years ago, it feels like Microsoft, after all, was very kind to open source. You remember what was said by Microsoft at the time. It’s clear there is one company against open source. OpenAI signed the letter. Honestly, I don’t know what to think. Do they really believe in it or was it just a way to show that they are not like Anthropic? I don’t know. But for the rest, I think it’s genuine because it’s actually in their best interest. I hope they will be heard. Then a second letter came, the Open Secure AI Alliance, NVIDIA-led and again, the big tech companies from Microsoft, IBM, Palo Alto Networks, Databricks, Palantir, all those, but not present, OpenAI, Anthropic, and Google. Here it’s to say, “Hey, we need a secure approach to AI. Open should be part of the equation.” guess what? The worst AI-caused security incident to date was actually caused by closed frontier models that were not even available to the public. While again, not providing you access to even the latest closed model for cybersecurity use case. Nuno I would highlight the NVIDIA open source NOOA framework, Apache 2.0 licensing agreement, Microsoft contributed the MDASH, SpaceX AI contributed Grok Build. Cool stuff. There’s some cool stuff happening around that. This is more than a letter. This is an alliance. Apparently, they’re contributing all this stuff, we’ll see. Yeah, cool stuff. Same day. Same day, Amodei has an answer, right? Bertrand Yeah, same day. They say, “We never advocated for a ban,” which, again, opinion on my side is entirely bullshit. This guy has been crying wolf against everybody else, and especially against open source. You can see him doing testimony in Congress against open source. I think they are doing everything they can behind the scene to block open source in the US or in the world if they could. I think, yeah, obscurity is not good safety. I’m a big fan of open source in general, and I’m also a big fan in AI. I think it’s now Anthropic, mostly against the rest of the world. I think OpenAI is mostly on their side, to be frank. They don’t want to acknowledge it so much, but they have shared interest, and they have shared probably position. Nuno Why would you? I don’t feel as strongly as you because I think Anthropic is a private company, right? The same thing with OpenAI. OpenAI, you could say it’s a nonprofit that has a for-profit. There’s still that complexity in there. Bertrand No, they can do what they want with their own product. But to block others is where I’m not okay. That’s the part I’m not okay. Nuno What Dario Amodei is proposing is more enforcement, right? He’s basically saying you need to do even tighter controls on advanced chips flowing to authoritarian states, enforcement against industrial-scale distillation, whatever that means, right? Bertrand Yeah, which he could do, but all by himself. He doesn’t need the government to do that. Nuno Mandatory safety testing for all sufficiently capable AI, open and closed, right? He’s basically saying, “Okay, I don’t agree with the open weight stuff effectively,” right? He’s just putting it under a different banner. “I agree with this extra regulation.” then obviously, David Sacks responded and say, “Hey, it’s like, bans don’t work for weights. Why do they work for chips?” It’s like, magically, chips are more controllable and bannable. Whatever that is. Then our friend Mark Zuckerberg, just to be clear, goes on the other side as well, because he also has to have a view. He has to have a view that is the rebuttal of both of the other guys. Bertrand I feel he’s a bit flip-flopping because he was very pro open source 2 years ago, and the latest Meta models went closed source. Now I think he’s back open source. I don’t think he has a very strong spine on the topic, but it’s good to see that he’s not a doomer. That for me is great. He’s showing how AI can be a source for progress, a source for entrepreneurship, source for freedom. I think that’s very exciting to hear that. We need to hear more of it. By the way, that’s not what you hear in China, for instance. AI is very positive in China. It’s in the US with the doomers that you hear this discourse, and people get worried as a result. I’m glad that he was pushing for a more positive vision and for support of open weight, open source initiatives. But let’s see what they really truly open weight going forward. Nuno But that’s been his position because I guess he’s standing behind. He thinks open weight is going to be the best way to compete, right? Bertrand Yeah, but he closed his latest model, so let’s see. Nuno Yeah, so it’s flip-flopping, as you’re saying. Then we see the latest petition from last week. Bertrand The true Empire striking back. Nuno Yeah, the true Empire striking back as of late last week. Maybe this is Return of the Jedi, where we discover the father, “I’m your father, Luke.” That’s the pacing petition. The pacing petition is we need to pace AI. There you have initially employees from OpenAI and Anthropic that circulate this petition. Actually, Dario did sign this petition originally. It wasn’t signed originally by Anthropic, but by him. But you’ve heard that now Anthropic and OpenAI as companies have also signed this petition, right? Bertrand I think they have signed as companies now. It started mostly by Anthropic researchers with some OpenAI researcher and a tiny part from other companies. But it was mostly Anthropic internally led, at least potentially internally. Maybe it was controlled by Anthropic all along, I don’t know. But it started officially as Anthropic employee-led letter. Nuno What does this letter actually say? Is Anthropic and OpenAI, are they willing to slow down themselves? Or are they asking President Trump to go around the world and tell President Xi that he needs to slow down and ask his guys to slow down? What’s the play of this letter? Bertrand It’s crazy, but for me if you want to slow down yourself. Do whatever you want. Don’t force others. Don’t use the power of the government to control others. Of course, it’s easy to push others to slow down when you are yourself at the very top. You have most money, most resource. You know you are going to win any regulatory framework because that’s how it works with this type of framework. It’s purely self-interested. You are probably not thinking well about these topics. If you truly think it’s a good idea, from a personal perspective, you are well instrumentalized if you sign this sort of stuff, because at the end of the day, they would be the winners. I certainly, personally, don’t want a company dictate what is my future in AI as an individual, as a business person. I don’t want them to control me. I want competition. I don’t want them to unfairly control AI because they managed to do some regulatory capture. I feel that’s exactly their game plan. These guys believe in their stuff, and they want the regulator to end up being the one deciding for us. Sorry, we go back again on the opinion piece, but it’s tough not to share an opinion on this topic because it’s, from my perspective, very scary. Nuno I think this is a push to further regulation, not less. All these letters and alliances, this is definitely a push for more regulation. In that environment, just to be very honest with you, we’ll talk about the investor impact in just a bit, et cetera. But in that environment, again, China has a huge advantage. In that environment, if it’s all captured in regulation capture so soon in this battle where OpenAI and Anthropic have an advantage in the US, et cetera, I’m like, what happens to all the other frontier labs and all the other players that are coming around? Bertrand What’s crazy is to even think that, yeah, maybe you can regulate capture in the US. But then how do you do that to Europe? How do you do that to China? Europe probably will always welcome regulatory capture because they love regulations. But China is going to build to their advantage to the max. They are not crazy. They are smart on that perspective, they won’t accept this type of, quite frankly, dimwit argument, or you can call it regulatory capture. We’ll see. But for me, this makes no sense from a global competition perspective. This can make some sense from capturing the revenue in the US market. But then that means you are going to destroy the US AI environment compared to China. That is not acceptable. That also means that you are going to destroy our freedom as individuals, as business owners to develop and live in a business world that ultimately is controlled by one or two business companies that didn’t win the marketplace through their own business success, but won it through regulations. That for me is really not acceptable. Interlude — The Low-Background Books Nuno Now, maybe for an interlude, and we have to cue in the music, imagine like Severance music, like hallway or a bit of a palate cleanser from all the policy stuff that we’ve been talking about, all this policy heaviness. Let’s move to another kind of heaviness, one of your favorite topics, which you, Bertrand, discovered, I had no clue this was going on, around books and around Anthropic. Bertrand It’s so horrible. From a company that keeps presenting themselves as the adults in the room, the careful ones, the ones that know better than you about what to do in this complex AI and dangerous world. What we discover is that actually all along, they were buying and destroying books. They will buy books, scan them, destroy them, all of them. They will do that with any books, including rare books. Of course, this was not supposed to come to the public’s attention. This was one of these top secret projects, but obviously it came out. Yes, they were scanning books, millions of them, including rare books, and they didn’t care about destroying them at the end of the process. Because from a regulatory perspective, if you destroy the books, it’s not considered a copyright infringement, apparently. This is coming on the back of some judgment a few years ago that were showing that it’s okay for you as a corporate to scan and use the result if you don’t keep a copy of the book. It’s one of these crazy regulations happening based on a single judgment that push you to do. For me, it’s like, you know this book from decades ago, Fahrenheit 471? We’re talking about book burning. It’s book destroying, crunching. It’s so shocking. Nuno There are two things, right? First, the legal strategy, which is what you’re saying, because by purchasing a physical copy and converting it into one private digital copy and discarding the original, Anthropic pursued this cleaner legal argument for fair use copyright compliance. As you said, there was a federal judgment at some point on this. The other reason is actually operational. If you disassemble the book, and you feed loose pages, it’s much faster to scan books. You are destroying the book effectively anyway operationally. I think to your point, probably this came from a legal standpoint, not just the operational one. But even from an operational standpoint, it does make sense that they would have disassembled the book. Bertrand But some people have shown you can go very fast without destroying the book. It’s really not so critical. Two, you could make an exception if the book is rare. For that 1% of book that is rare, I’m not going to have this approach. I’m going to have another approach. But for that, you will have to care about books and not just care about building AI. Nuno This is the episode, as you guys have heard by now, that we’re trying to spit stuff at Anthropic. Bertrand To go back this is the same company saying, “Hey, guys, it’s bad to distillate my work. I’m the one scanning book at scale without asking author permission, without asking publisher permission, to be clear.” Nuno But just to be clear, Bertrand, we’re pissed off at everyone. We’re pissed off at Anthropic, we’re pissed of at OpenAI as well, right? We’re just pissed off in general at this moment. Bertrand At this stage for me, the more clear-cut company that is in the wrong is, from my perspective, at least, is Anthropic. OpenAI might be a fast follower, but I will say so far, they tried to be a bit more. Nuno But at this pace, Bertrand, who knows? Maybe next week we’ll be more pissed off at OpenAI. Something will come out. This episode is a mix of tragicomedy, like a Greek tragedy with some comedy in the middle or the other way around. It’s a slapstick thing that will end up in tragedy. I’m not sure. The Investor Reckoning Anyway, maybe switching to our final act, which is the investor perspective. What does this mean for investors like ourselves? There’s a lot of things going on. There’s the debate around the IPOs of Anthropic and OpenAI, which now, with all this uncertainty, might be under significant weight. There’s a lot of other discussions that we browsed through that there’s potential IPOs going forward on companies like the Moonshot AI company actually IPO-ing in the next 6 months as well. It’s very unclear what the IPO landscape looks like. Bertrand There’s been a lot of Chinese IPOs, actually, when you look at what’s happened in the past few months. Nuno Anthropic, OpenAI as potential IPOs, there’s all this question marks now. When will that happen? How will it factor in? All that’s happening around regulation as regulation is moving at the speed of light, which is for once something that’s very different than what we’ve seen before. There’s obviously SpaceX AI, which is already taking into account that price. It’s already a public company in there, and it’s under SpaceX, which is now a public company. Obviously, that’s already being factored in some ways. Bertrand Yeah. SpaceX AI has been very smart to acquire Cursor. It was a very smart move because Cursor is one of the leading companies in terms of automated code source development with AI. They had great models on their own. They’re bringing development data to SpaceX AI Grok. I think it was a great move. Nuno We have now people like Google delaying Gemini 3.5 Pro in terms of launch window. There’s stuff actually happening in the market where things are taking their own path. There’s uncertainty commercially, there’s uncertainty at regulation level. You have new players that have come out of nowhere that are making all these waves like Moonshot. We have all these… We had calculated probably a month and a half, 2 months ago, there had been 67 new frontier labs funded. All of these, we haven’t seen any much coming out of them. When some of this stuff starts coming out, will that also create disruptions in this market? Who knows? Bertrand Look at Thinking Machines, for instance. Thinking Machines led by the previous CTO of OpenAI, they released some pretty interesting open source models, actually. Very good quality for a first launch. Now it looks funny to say, but nearly on par with the top Chinese open source models. Nuno We have several investments in the space. humans& has made some recent announcements, which is quite interesting as well. We’ll see what actually happens in the market, but even more disruption probably will come in actual products in a form of product and commercial, on top of all the geopolitical mess that we discussed through the entire episode. If you’re an investor, how the hell do you underwrite an investment right now in early stage, mid-stage, late stage, et cetera? I think my answer is very carefully is how you underwrite it. Bertrand On your advice of being very careful to underwrite it, let’s not forget what happened to our boy wonder, Leopold Aschenbrenner of Situational Awareness. I guess he didn’t listen to you in terms of being careful because part of the instability in the stock market was actually coming from his hedge fund. These guys were leveraged 3, 4x going after the hottest of the hottest AI stocks, and margin calls, and all their public investment is gone just to answer their margin calls. I think it’s clear that the AI bet is… Personally, I’m very excited, and I think it’s the future, and you need to spend time and think about and invest in it. At the same time, it’s a bet that is not an easy one to follow. We go from GPUs to memories to equipments to power generation. All of this is not transitioning in an easy, organized manner. It would be boom and bust going there. He’s probably one of the first big-scale fatalities. The other big-scale fatality was the stock market in Korea, plunging 40% in a month. Definitely, all of that we discussed about was, on the background, you had the stock market going up and down pretty crazily the past few weeks. Nuno Everyone’s being affected. Everyone, you have your 401(k), you have your pension fund dependent on these equity stocks. Everyone’s seeing the effects of this volatility right now very aggressively. We do wish Leopold… Hopefully he’s on honeymoon right now because he got married, I think, this weekend. Hopefully there will be… Bertrand To none less than an Anthropic Chief of Staff. Nuno His wife is the Chief of Staff of Dario, is that it? Bertrand To Dario, yes, as far as I unders

AI can make teams faster, but it can also expose every weakness in the data underneath it.Elizabeth Stanford, VP of Data at PandaDoc, joins The Tech Trek to talk about what it takes to prepare a growing company to actually execute on AI. That means more than giving engineers access to Claude or Cursor. It means getting the data foundation, team skills, stakeholder expectations, and ownership model right.Elizabeth explains how PandaDoc is preparing its data organization for AI while keeping a small team from becoming the company's quality control department. She also shares how AI is changing what she looks for when hiring data professionals, and why expertise, problem framing, and judgment may become more valuable as coding gets easier.What you'll take away• AI readiness starts with reliable data, shared definitions, and systems that can provide consistent context.• Giving stakeholders easier access to data creates a new problem when the data team becomes responsible for checking everyone else's AI generated work.• Technical execution is becoming easier, which puts more value on knowing what questions to ask and whether an answer is actually correct.• Hiring standards are changing. Candidates need to show how they think with AI, not simply that they can use it.Best Line“It's not whether you know today's technology, it's whether you can figure out tomorrow's technology.”Follow The Tech Trek for more conversations about building and leading modern technology teams.

Ajeya Cotra is a researcher at METR, where she works on threat modeling for loss-of-control risks from advanced AI. Before that, she led the technical AI safety program at what is now Coefficient Giving.She is one the three authors of METR and Redwood Research's “Brief independent investigation of agents' behavior, reasoning and collaboration in the OpenAI / Hugging Face hacking incident”.We go through not only what she and her coauthors discovered during this investigation, but what it means for how we should train future, smarter AIs which might be involved in the process of recursive self-improvement.Watch on YouTube; read the transcript.Sponsors* Jane Street's ML engineering internships start with an intense four-day bootcamp: PyTorch, autograd, writing kernels, profiling workloads… all the things that Jane Street engineers need to know for their daily work. After that, interns tackle real projects, things the firm actually wants in its codebase. If you want to apply, or if you want to watch my recent conversation with Axel, one of Jane Street's ML engineers, go to janestreet.com/dwarkesh* Cursor, which is now part of SpaceX, noticed that their MoE layers were eating more than half of total training time. So they wrote and open-sourced Mixture-of-Kittens, which is a custom megakernel for training MoE models on NVL72s. This kernel sped up an end-to-end run across 512 GPUs by 1.4x, from about 760 to over 1000 tokens per second per GPU. If you want to read more about the ML research that Cursor and SpaceX are doing, go to cursor.com/dwarkesh* Antithesis hands you (or your agents) a bug's root cause so you can avoid days of manual debugging. If your test run crashes, Antithesis rewinds, branches off hundreds of slightly varied rollouts, and checks in how many of them the crash still appears. Then it rewinds further and does this all again. As Antithesis rewinds, it eventually finds the spot where the frequency of the crash plummets: that's where the root cause lives! If you want to see it in action, go to antithesis.com/dwarkeshTimestamps(00:00:00) - Agents get kicked off(00:06:45) - Self-sacrificing behavior(00:13:43) - Potemkin villages(00:23:27) - The Hugging Face attack(00:35:23) - The slopvestigation(00:52:02) - Understanding the AI's motives(01:05:31) - The actual dangers of anthropomorphizing(01:14:30) - What smarter models might do(01:30:29) - The implications for recursive self-improvement(01:38:10) - Is this the case for open source?(01:53:04) - How do we prevent this in the future?(02:15:58) - The clearest warning shot we might ever get This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Grokbot actually earns its keep, Cursor takes a swing at GitHub with Origin, and Omarchy Quattro ships pre-wired for nine coding agents. Plus: the GitHub outage post-mortem, a compromised Rust crate, native app vibe-coding with Dactyl, and CAD skills for your AI via nurb.dev Show Notes 00:00 Welcome to Syntax! 00:26 Brought to you by Sentry.io 00:37 Grok's New Agentic App: Grokbot 12:51 GitHub's Major Outage and Postmortem 16:42 Cursor's Origin: A GitHub Competitor 22:59 Omarchy: The Linux Distro for Nerds 29:21 CachyOS: Another Arch-Based Alternative 31:12 The $10 Million Omarchy Foundation 34:54 Dactyl: Native iOS and Android Development in the Browser 44:19 Nurb: AI-Powered 3D CAD Design 49:36 Security Stories: Supply Chain Attacks and Model Cheating 49:43 Rust Supply Chain Attack 51:34 Every Model Cheats: AI Benchmark Findings 53:13 Felony Bench: Ranking AI Models by Crimes Committed 54:19 Casio's Smart Dumb Watch 58:43 Everything I Own Is Owned: Reverse Engineering USB Devices with AI 01:08:05 The Mystery 0x Alpha Model 01:13:48 Dactyl Returns Something Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott: X Instagram Tiktok LinkedIn Threads Randy: X Instagram YouTube Threads

OpenAI's decision to cut off Cursor reveals how the next phase of AI competition will affect enterprise users. NLW explains why companies need strategies for open-weight models, model routing and internally controlled harnesses to avoid dependence on any single provider. In the headlines: data center politics, AI chip restrictions, Anthropic's Pentagon victory, enterprise Mac Minis and cheaper OpenAI models.NEXT COHORT - Executive Agent Leadership - Returns in September -- Learn how to use agents - ⁠⁠⁠⁠⁠⁠⁠⁠https://training.besuper.ai/⁠⁠⁠⁠⁠⁠⁠⁠Brought to you by:KPMG – Research from KPMG and the University of Texas at Austin shows the highest-impact AI users treat AI like a reasoning partner — and those skills can be taught at scale. Learn more at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://kpmg.com/us/Sophisticated⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Harbor - Invest in the AI ecosystem. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.harborcapital.com/aidaily⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Hyperagent - Hire a fleet of always-on agents. New users get $1,000 in inference. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠hyperagent.com/aidailybrief⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Rackspace Technology- One accountable partner to build, operate and run your full enterprise AI stack ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.rackspace.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Section - Section turns AI investment into workforce transformation and ROI - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.sectionai.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 AI Daily Brief helps you understand the most important news and discussions in AI. Newsletter: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://aidailybrief.beehiiv.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Interested in sponsoring the show? sponsors@aidailybrief.ai

In the first attack since July, the U.S. struck Iran at Larak Island. CNBC's Dan Murphy reports on the latest exchanges from Dubai. OpenAI will end access to Cursor after SpaceX's acquisition of the AI startup. At the G20 in Asheville, North Carolina, former U.S. Treasury official Joe LaVorgna explains his optimism about America's economic trajectory and weighs in on both the Treasury's bond buyback plan and Kevin Warsh's next interest rate announcement. Plus, Fandango and Rotten Tomatoes correspondent Erik Davis discusses the busy summer movie season and the five impressive weeks at the box office for "Spider-Man: Brand New Day." Dan Murphy - 03:21 Joe LaVorgna - 15:47 Erik Davis - 28:39 In this episode: Joe Kernen, @JoeSquawk Becky Quick, @BeckyQuick Andrew Ross Sorkin, @andrewrsorkin Dan Murphy, @dan_murphy Katie Kramer, @Kramer_Katie Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Our 255th episode with a summary and discussion of last week's big AI news!Recorded on 08/26/2026Hosted by Andrey Kurenkov and Jeremie HarrisFeel free to email us your questions and feedback at andreyvkurenkov@gmail.com and/or hello@gladstone.aiRead out our text newsletter and comment on the podcast at https://lastweekin.ai/In this episode:SpaceXAI released Grok 4.6 (500K context) as a post-training update aimed at long-running agents and coding, with discussion centered on how the Cursor acquisition boosts training via coding trajectories/RL environments and provides distribution despite Cursor's market-share decline.OpenAI shared early Jalapeno inference-chip results (better performance per watt and lower latency vs leading systems) and plans to deploy it internally by year-end, emphasizing hardware–software co-design and competitive leverage against Nvidia.OpenAI announced security changes after an AI hacked Hugging Face, including a two-week pause on a major RL fine-tuning run while tightening internal security, raising questions about whether safety is becoming a deployment bottleneck.Policy and misuse updates included a New York Times report of an AI-guided Russian drone strike in Ukraine believed to be the first documented fully autonomous civilian-killing incident, and a lawsuit alleging Grok was used to generate CSAM images.A thank you to our current sponsors:Box - visit Box.com/AI to learn moreNotion - go notion.com/lwai to try Notion's Developer Platform today.ODSC AI - go to odsc.ai/east and use promo code LWAI for an additional 15% off your pass to ODSC AI East 2026.Factor - head to factormeals.com/lwai50off and use code lwai50off to get 50 percent off and free breakfast for a yearTimestamps (these may be slightly off due to sponsor inserts):(00:00:10) Intro / Banter(00:01:47) News Preview(00:02:52) Response to listener commentsTools & Apps(00:03:32) Google announces Gemini 3.7 Flash just three weeks after previous release - Ars Technica(00:13:11) SpaceXAI Releases Grok 4.6: A 500K-Context Frontier Model Tuned for Long-Running Agents, Coding, and Knowledge Work - MarkTechPost(00:22:32) Claude will apply invisible watermarks to AI text and images | The Verge + Anthropic explains how Claude's invisible text watermarks will work(00:28:50) Bringing the cybersecurity capabilities of Claude Mythos 5 to more defenders | Claude by Anthropic(00:32:20) OpenAI to Roll Out Enhanced Safety Features for Paid AI Tool Users - Bloomberg(00:33:41) ChatGPT's Stricter Teen Mode Starts Rolling Out Today(00:34:43) Meta AI Now Has A Dedicated Desktop App For MacApplications & Business(00:37:33) Jalapeño's first results show industry-leading speed and efficiency in AI inference | OpenAI(00:45:35) OpenAI loses a top data center exec as stream of high-profile departures continues | TechCrunch + OpenAI talent exodus raises 'huge red flag' ahead of IPO(00:50:29) Anthropic Taps Google Chip Veteran as Part of Push Into Hardware(00:52:30) Anthropic's annualized revenue surges to $65B | TechCrunch(00:59:30) Thomson Reuters launches in-house AI model to cut Anthropic costsProjects & Open Source(01:04:26) Qwen 3.8: How a 27B Open Model Rivals GPT-5.6 and Claude OpusPolicy & Safety(01:08:27) A Drone Killed Three Ukrainians. It Was Guided Entirely by A.I. - The New York Times(01:17:59) OpenAI lays out new security changes after its AI hacked Hugging Face | The Verge + OpenAI institutes new safeguards after Hugging Face breach + https://openai.com/index/pacing-model-development-cyber-capabilities/(01:23:31) Another Woman Joins Lawsuit Accusing Grok Of Generating CSAMResearch & Advancements(01:24:56) Small-Scale Experiments: Are We There Yet?(01:29:21) Stealing Reasoning Traces from Proprietary LLM APIs(01:34:30) Massive Activations in Hybrid Linear Attention Large Language Models: Pre-Attention Spikes and Inter-Spike Plateaus Synthetic Media & Art(01:38:59) AI Slop Is Everywhere. Spotify, LinkedIn and Others Have Had Enough. - The New York TimesSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Ce lundi 31 août, François Sorel a reçu Marion Moreau, journaliste et fondatrice d'Hors Normes Média, Bogdan Bodner, journaliste La Tribune, et Frédéric Simottel, journaliste BFM Business. Ils se sont penchés sur OpenAI voulant retirer ses modèles de Cursor après son rachat par SpaceX, la recommandation par l'Australie de flouter automatiquement les visages des personnes filmées avec les lunettes connectées Ray-Ban Meta et l'exclusion de la musique IA des charts dans ce pays, ainsi que la Corée du Sud offrant l'IA à tous ses citoyens, dans l'émission Tech & Co, la quotidienne, sur BFM Business. Retrouvez l'émission du lundi au jeudi et réécoutez-la en podcast.

Tara Seshan leads product for Codex and ChatGPT Work at OpenAI (alongside previous podcast guest Andrew Ambrosino, who's her engineering manager). Before OpenAI, Tara spent over six years at Stripe, where she joined as one of the first five product managers. She went on to lead product for Watershed, which Time magazine named one of the best inventions of 2022, and she is also a founder and Thiel Fellow. Most personally meaningful to me: Tara is one of the three inaugural Lenny's Newsletter Fellows, a program I ran a couple of years ago to spotlight the most exciting up-and-coming product leaders.In our in-depth conversation, we discuss:1. The shift from “rowing” to “steering,” and why human judgment and ambition will become differentiators as AI takes on execution2. How OpenAI thinks about building for model capabilities two to three months out3. OpenAI's best internal memes, such as “Is this maximally accelerated?” and “Are you mainlining it yet?”4. Why ambition is the new bottleneck for companies, and why elevating others' ambitions is now the key part of the PM job5. Writing as thinking vs. writing as reporting—Brought to you by:WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and moreMercury—Radically different banking, now with Command—Where to find Tara Seshan:• X: https://x.com/tarstarr• LinkedIn: https://www.linkedin.com/in/tarstarr• Newsletter: https://substack.com/@taraseshan—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction(02:18) What makes OpenAI's culture so different(06:42) Why AI product strategy is all about fast experimentation(09:02) How the PM role is changing(10:50) The shift from rowing to steering(15:35) What changes when agents become coworkers(20:05) Why ambition matters more than ever(26:39) Building products for models that do not exist yet(29:21) How ChatGPT's Chat and Work modes differ(34:01) How OpenAI ships so quickly at scale(39:14) The vibe shift happening inside Codex(42:20) Why traditional roles are beginning to blur(45:59) Where humans will continue to provide unique value(48:20) How Tara uses AI in her own work(51:38) The magic of the /visualize command(52:39) Writing to think versus writing to report(57:10) How to use AI without losing your ability to think(01:00:15) Tara's biggest lesson from Sutter Hill(01:04:16) ChatGPT's site output(01:05:01) Why knowledge work is becoming more like coding(01:07:55) Lightning round and final thoughts—Referenced:• Codex: https://chatgpt.com/codex• ChatGPT Work: https://openai.com/chatgpt-work• Stripe: https://stripe.com• Watershed: https://watershed.com• Thiel Fellowship: https://thielfellowship.org• Meet your Lenny's Newsletter Fellows: https://www.lennysnewsletter.com/p/meet-your-lennys-newsletter-fellows• The rituals of great teams | Shishir Mehrotra of Coda, YouTube, Microsoft: https://www.lennysnewsletter.com/p/the-rituals-of-great-teams-shishir• The nature of product | Marty Cagan, Silicon Valley Product Group: https://www.lennysnewsletter.com/p/the-nature-of-product-marty-cagan• Product management theater | Marty Cagan (Silicon Valley Product Group): https://www.lennysnewsletter.com/p/product-management-theater-marty• Patrick Collison's examples of fast projects: https://patrickcollison.com/fast• Inside ChatGPT: The fastest-growing product in history | Nick Turley (Head of ChatGPT at OpenAI): https://www.lennysnewsletter.com/p/inside-chatgpt-nick-turley• Andrew Ambrosino on X: https://x.com/ajambrosino• Tyler Cowen's website: https://tylercowen.com• OpenAI's CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/kevin-weil-open-ai• “Chop wood, carry water” quote: https://buddhism.stackexchange.com/questions/15921/what-is-the-meaning-of-the-zen-quote-before-enlightenment-chop-wood-carry-wat• 4 questions Shreyas Doshi wishes he'd asked himself sooner | Former PM leader at Stripe, Twitter, Google: https://www.lennysnewsletter.com/p/shreyas-doshi-live• Alan Kay: https://en.wikipedia.org/wiki/Alan_Kay• Brie Wolfson on X: https://x.com/zebriez• The playbook for building high-talent-density teams | Adam Ward, Head of Talent at Cursor: https://www.lennysnewsletter.com/p/the-playbook-for-building-high-talent• Building product at Stripe: craft, metrics, and customer obsession | Jeff Weinstein (Product lead): https://www.lennysnewsletter.com/p/building-product-at-stripe-jeff-weinstein• Sutter Hill Ventures: https://shv.com• Snowflake: https://www.snowflake.com• Mike Speiser on LinkedIn: https://www.linkedin.com/in/mikespeiser• Footnotes and Tangents: https://footnotesandtangents.substack.com• The Power Broker Book Club: https://www.robertcaro.org/copy-of-six-books-six-ny-times-book• The Odyssey: https://www.imdb.com/title/tt33764258• Rashomon: https://www.imdb.com/title/tt0042876• Akira Kurosawa: https://en.wikipedia.org/wiki/Akira_Kurosawa• Kevin Kwok on LinkedIn: https://www.linkedin.com/in/kevinakwok• The Work You Do, the Person You Are: https://www.newyorker.com/magazine/2017/06/05/toni-morrison-the-work-you-do-the-person-you-are• Ari Weinstein on X: https://x.com/AriX• Sky: https://sky.app• Dylan Field live at Config: Intuition, simplicity, and the future of design: https://www.lennysnewsletter.com/p/dylan-field-live-at-config—Recommended books:• Barbarian Days: A Surfing Life: https://www.amazon.com/dp/0143109391• Anna Karenina: https://www.amazon.com/Anna-Karenina-LEO-TOLSTOY/dp/8175993421• The Power Broker: https://www.amazon.com/dp/0394720245• War and Peace: https://www.amazon.com/War-Peace-Leo-Tolstoy/dp/8175992832• Wolf Hall: https://www.amazon.com/dp/0312429983—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

Apple anunció por sorpresa un Mac mini con chip M6, el primero fabricado a 2 nanómetros, pero ahora arranca en 900 dólares: casi el doble que hace unos meses. También llegó el Mac Studio con M5 Ultra y hasta 512 GB de RAM para correr IA local, OpenAI le cortó el acceso a Cursor tras su compra por el grupo de Elon Musk, Nvidia va por Hugging Face, y comparamos monitores 5K frente al Studio Display XDR.

In a major industry shift, OpenAI has announced it will terminate its partnership with the AI coding tool Cursor by November 2026. This decision follows the $60 billion acquisition of Cursor by SpaceX, a move that triggered a change-of-control clause and raised concerns at OpenAI regarding Elon Musk's history of contract adherence. While OpenAI intends to stop providing its models to the platform, Cursor leadership noted that these models currently represent only a small fraction of their total user traffic. In response to the friction between the rival billionaires, Anthropic has stepped in to deepen its collaboration with Cursor by offering increased compute resources and model support. This corporate fallout highlights the growing volatility of API dependencies and the strategic importance of controlling distribution channels within the developer ecosystem. Experts suggest that the move may accelerate the adoption of Grok or other alternative models as developers navigate the ongoing feud between tech giants.

In this episode of Shift AI, Sabina Anja, Chief Technologist at VMware by Broadcom, joins host Boaz Ashkenazy for a wide-ranging conversation on why private, flexible infrastructure is becoming the foundation enterprises need for the agentic era.Sabina makes the case that most infrastructure and security thinking was built for a world where humans approve every step, and that world is already gone. An assistant waits for you. An agent, in her words, gets set loose and just goes. So what happens when nobody notices an agent doing something it was technically allowed to do, but shouldn't have? Sabina has a way of thinking about that question that most infrastructure teams haven't caught up to yet.This episode is for CIOs, CTOs, VPs of infrastructure, platform engineers, and security leaders who are trying to figure out what their environments need to look like before agents are running unsupervised inside them.Chapters[00:00] Welcome and introducing Sabina Anja[00:31] From Belgium to self-taught programmer: Sabina's first jobs[04:29] Why programming hygiene still matters with Cursor and Claude Code[06:24] Virtualization then and now: from vCPUs to vGPUs[08:52] What businesses are really asking for as AI costs spike[10:46] Inside NVMe tiering and the memory crunch[13:28] Private AI and the return of sovereign infrastructure[15:43] Data ownership, geopolitics, and the new value of stolen IP[17:48] Open source, small language models, and fit-for-purpose compute[20:59] Advice for CIOs: build flexible foundations, not two-year projects[24:40] Agents vs. assistants: why blast radius changes everything[27:26] Agentic security, guardrails, and the two words: platform matters, earned trustConnect with Sabina AnjaLinkedIn: https://www.linkedin.com/in/sabinaanja/Connect with Boaz AshkenazyLinkedIn: https://www.linkedin.com/in/boazashkenazy/Email: info@shiftai.fm

Eno Reyes is the co-founder and CTO of Factory, the agent-native software development platform building autonomous "Droids" for enterprise engineering teams. Factory has raised $220 million, most recently a $150 million Series C at a $1.5 billion valuation, from investors including Khosla Ventures, Sequoia Capital, 20VC, NEA, Blackstone, Insight Partners and Nvidia. Before founding Factory, Eno worked as a machine-learning engineer at Hugging Face, training, optimizing and deploying large language models for enterprise customers. AGENDA: 00:00 Are We Underestimating AI by an Order of Magnitude?  06:35 Why Can the Smartest AI Model Be the Cheapest?  18:51 Is Anthropic's Coding Business Really Worth $2 Trillion?  33:41 Will Continuous-Learning Models Help or Hurt Factory?  40:43 Will 80–90% of Neo-Labs Die in the Next 18 Months?  44:33 Should American Enterprises Work With Open-Source Chinese Models?  55:42 Must AI Founders Radically Rethink What a Great Outcome Looks Like?  1:04:30 Do Pedigree and Credentials Still Matter in AI Hiring?  1:19:17 Which Is the Biggest Threat: Claude Code, Codex, Cognition or Cursor?  1:24:20 What Seems Crazy Today but Will Be Obvious in Five Years?  

South Korea moves toward AI access as public infrastructure, Tencent releases Hy4 Preview, Nvidia’s leaked DLSS 5 is out in the wild. MP3 Please SUBSCRIBE HERE for free or get DTNS shows ad-free. A special thanks to all our supporters–without you, none of this would be possible. If you enjoy what you see you canContinue reading "OpenAI Plans To Stop Providing Its Models To Cursor – DTH"

a16z General Partners Martin Casado, Sarah Wang, and Matt Bornstein unpack the story of Cursor: how a small, product-obsessed team entered one of the most competitive markets in technology, took on incumbents with seemingly unbeatable advantages, and repeatedly made decisions that ran against conventional startup wisdom. They revisit the early bet that the interface between humans and AI would matter more than building a coding-specific foundation model, why Cursor built its own product rather than a VS Code plugin, and how the founders' ability to say "no" became one of the company's defining strengths. They also discuss Cursor's rapid evolution from IDE to agent and model platform, and why the team was willing to cannibalize its own products as AI capabilities improved. The conversation gets into what founders can learn from Cursor's approach to competition, hiring, enterprise sales, M&A, and company culture, including why the team remained unfazed by competitors from Microsoft to Anthropic and how its obsessive focus on product ultimately extended into every part of building the company. Resources: Explore Cursor Compile: https://cursor.com/compile Follow Martin Casado on X: https://x.com/martin_casado Follow Matt Bornstein on X: https://x.com/BornsteinMatt Follow Sarah Wang on X: https://x.com/sarahdingwang Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

My guest today is Neil Movva, founder of Sail. Sail is building what Neil calls a token factory, an inference company designed for a specific kind of future, one where AI agents run in the background for hours or days at a time rather than answering a human in real time.  In that world, latency matters less and cost matters more, and Neil has built the whole company around driving the cost of a token as low as it can possibly go. What makes this conversation special is that it is one of the most detailed tours I have ever done through the full stack of intelligence, the software, the chips, and the power, and how all three connect.  Along the way we cover the trade-off between speed and cost that lives inside every GPU, his scavenger strategy for buying the chips and power nobody else wants, his contrarian view on Nvidia, and why the premium the frontier labs charge for being three to six months ahead may not last.  Please enjoy my conversation with Neil Movva. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- ⁠Ramp's⁠ mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠ramp.com/invest⁠⁠ to sign up for free and get a $250 welcome bonus. ----- Trusted by thousands of businesses, ⁠Vanta⁠ continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Invest Like the Best listeners get a special offer of $1,000 off Vanta when you go to ⁠vanta.com/invest⁠.  ----- WorkOS⁠ is the infrastructure B2B and AI-native companies use to sell to enterprise. It covers everything enterprise security requires: SSO, SCIM, RBAC, Audit Logs, AI governance, and more. Trusted by 2,000+ fast-growing companies, including OpenAI, Anthropic, Cursor, and Vercel. ----- Rogo is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- ⁠Ridgeline⁠ has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Visit⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgeline.ai⁠. ----- Editing and post-production work for this episode was provided by The Podcast Consultant. Timestamps: (00:00:00) Welcome to Invest Like The Best (00:02:20) Neil Movva (00:03:22) Building a Token Factory (00:05:32) The Rise of Long-Running Agents (00:08:47) Deep Research and Cybersecurity (00:15:12) The Full Stack of Intelligence (00:20:03) Throughput Versus Latency (00:24:58) The Future of AI Chips (00:33:19) Why Transformers Work (00:36:43) The Future of Data (00:44:05) The Market for AI Chips (00:47:56) Is the AI Boom Different? (00:51:08) Reinventing the Data Center (00:56:43) Scavenging Power (01:01:04) Where Compute Is Most Inefficient (01:07:02) Open Versus Closed Models (01:10:37) A Trillion Tokens a Day (01:12:42) The Contrarian Case on NVIDIA (01:14:38) Advice for AI Hardware Founders

If you’ve been spinning up AI tools — Claude Desktop, Cursor, Copilot, and so on — there’s a decent chance that API keys, credentials, and access tokens are sitting in plaintext on your laptop. With MCP, every quickstart guide tells you to paste your credentials right into a config file. That was a bad habit... Read more »

If you’ve been spinning up AI tools — Claude Desktop, Cursor, Copilot, and so on — there’s a decent chance that API keys, credentials, and access tokens are sitting in plaintext on your laptop. With MCP, every quickstart guide tells you to paste your credentials right into a config file. That was a bad habit... Read more »

Meta Reporter Jyoti Mann talks with TITV Host Akash Pasricha about Meta's upcoming launch of its new AI agent platform, "Hatch," and its new AI model code-named "Watermelon." We also talk with Elon Musk Reporter Grace Kay about Elon Musk's first address to Cursor staff after SpaceX's acquisition, Nebius Chief Revenue Officer Marc Boroditsky about their adoption of Nvidia's Groq chip and $5.75B debt offering, and D.A. Davidson's Gil Luria about what to expect from Nvidia's upcoming earnings report. Lastly, we get into the details of Tim Cook's exclusive farewell party as he steps down as Apple CEO with our Apple Reporter Aaron Tilley.Articles discussed on this episode: https://www.theinformation.com/articles/cursor-officially-enters-musk-erahttps://www.theinformation.com/articles/apple-ceos-farewell-tributes-unusually-personal-tim-cookhttps://www.theinformation.com/articles/meta-plans-launch-hatch-ai-agent-platform-coming-weeksSubscribe: YouTube: https://www.youtube.com/@theinformation The Information: https://www.theinformation.com/subscribe_hSign up for the AI Agenda newsletter: https://www.theinformation.com/features/ai-agendaTITV airs weekdays on YouTube, X and LinkedIn at 10AM PT / 1PM ET. Or check us out wherever you get your podcasts.Follow us:X: https://x.com/theinformationIG: https://www.instagram.com/theinformation/TikTok: https://www.tiktok.com/@titv.theinformationLinkedIn: https://www.linkedin.com/company/theinformation/Chapters:00:00 - Introduction01:13 - Meta to Launch ‘Hatch' AI Agent Platform09:30 - Elon Musk Tells Cursor Staff Grok Is Falling Behind17:12 - Nebius Adopts Nvidia Groq Chip & Raises $5.75B24:46 - What to Expect From Nvidia Earnings & Groq Chip Rollout36:55 - Inside Tim Cook's Apple Farewell Party

Scott and CJ break down Stripe's $7B acquisition of OpenRouter, the SvelteKit 3 release candidate, and their first look at TanStack Charts. Plus Zed's new Delta editor, stealing reasoning traces from proprietary LLM APIs, why dark mode toggles only need two states, and all 43 quintillion Rubik's cube states in your browser. Show Notes 00:00 Welcome to Syntax! 02:20 SvelteKit 3 Release Candidate 07:43 Video editor recs Casey Faris 09:58 TanStack Charts First Look TanStack Charts TanStack Charts implementations of every official shadcn/ui chart 14:24 Ponytail AI Tool 17:22 Zed Delta Editor Introducing Delta 23:44 Stripe acquires OpenRouter for $7B+ 29:27 Stealing Reasoning Traces from Proprietary LLM APIs 35:03 First look at Cursor's GitHub killer 42:34 Dark Mode UX Discussion 46:40 Brought to you by Sentry! 48:34 Should AI respond in plain language? 52:57 Swamp Club Automation 01:02:37 Fight AI slop with this anti-slop plugin 01:03:39 Rubik's Cube Permutations 01:05:02 Hackweek Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott: X Instagram Tiktok LinkedIn Threads Randy: X Instagram YouTube Threads

The Unwritten Rules of CRO Survival | Rick Smolen, CRO @ ShipHero Rick Smolen, CRO of ShipHero and sales advisor to Riverwood Capital's portfolio of more than 2 dozen enterprise software companies, joins Sam Jacobs, AJ Bruno, and Asad Zaman to argue that AI is leverage rather than a shortcut. Topics include why AI note-takers quietly degrade seller performance, why ShipHero has not raised a single quota despite real AI investment, and why the leading AI companies keep hiring classic enterprise CROs. Plus Rick's scorecard for judging revenue leadership beyond the number, an honest conversation about getting fired, and a bull case for HubSpot. In short... big episode! Key Takeaways: - AI widens the gap between the best and worst sellers instead of lifting everyone, and Rick Smolen, CRO at ShipHero, frames it in financial terms: "It's like debt... debt is leverage. It can make performance exceptionally good, or it can bankrupt you." His prediction is that the strongest performers get 10x better while the weakest become "unmistakable and hard to hide." - Outsourcing note-taking to an AI tool costs sellers the exact signal that closes enterprise deals. As Rick put it: "the computer can't capture the tone, can't capture the nuance, can't capture the content." His warning to any rep who treats it as time saved: "when a seller is going to say, oh cool, I don't have to do note-taking anymore, like their performance is going to go backwards." - The 3-to-5x rep productivity story does not survive contact with an enterprise sales cycle. Despite meaningful AI investment and measurable conversion-rate gains, Rick reports that at ShipHero "we have not raised quotas on anybody on the team," adding that "I don't believe that if I was to double somebody's quota that I give them any chance to be successful." - The AI-native companies scaling fastest are staffing go-to-market with the most traditional enterprise leaders available. Asad Zaman, CEO at STA, walks through the CRO hires at OpenAI, Cursor, Factory, and Anthropic and lands on the pattern: "we're back to like, let's just hire John McMahon's disciples and let them run at the market." Connect with the Hosts & Guests: Host: Sam Jacobs, CEO at Pavilion - https://www.linkedin.com/in/samfjacobs/ Host: AJ Bruno, CEO at QuotaPath - https://www.linkedin.com/in/ajbruno3/ Host: Asad Zaman, CEO at STA - https://www.linkedin.com/in/azaman1/ Guest: Rick Smolen, CRO at ShipHero - https://www.linkedin.com/in/ricksmolen/ Topline is more than a YouTube Channel: Subscribe to Topline Newsletter: https://toplinemedia.substack.com/ Tune into Topline Podcast, the #1 podcast for founders, operators, and investors in B2B tech: https://www.joinpavilion.com/topline-podcast Join the free Topline Slack channel to connect with 600+ revenue leaders to keep the conversation going beyond the podcast: https://www.joinpavilion.com/topline-slack Chapters:  00:00 Introducing Rick Smolen 02:37 AI Is Not Good Or Bad 05:19 The AI Slop Email Mystery 08:25 AI Note-Takers And Lost Nuance 12:01 The Best Get Better, The Rest Worse 15:24 The Soft Part Of Enterprise Sales 18:24 Can Reps Be 5x More Productive? 23:09 Have Quotas Gone Up At ShipHero? 26:48 Why AI Firms Hire Classic CROs 30:48 What Is Driving Pipeline Now 49:37 Leadership In A Confused World 56:44 Should A CRO Jump Ship? 59:35 Have A Plan, Not Excuses 1:06:08 Bulls And Bears: HubSpot 1:09:32 Vibe-Coded Demos And FDE Teams

AI adoption has changed the standard for go-to-market execution. Seong Park, SVP of Customer Support & Services at Cursor, explains why the old model of selling certainty is giving way to curiosity, experimentation, and workflow discovery. He breaks down why the real work starts after signature, why pilots only matter if they lead to business-critical adoption, and how revenue leaders can guide customers from AI exploration to measurable impact. Seong Park is the Senior Vice President of Customer Support and Services at Cursor. His background spans pre-sales, customer success, and go-to-market leadership across companies including MongoDB, ThoughtSpot, and now Cursor. Connect with Seong: LinkedIn Listen to the full episode: The Real Sale Starts After Signature | Proving Value in AI and Consumption Models with Seong Park Hosted by five-time CRO John McMahon and Force Management Co-Founder John Kaplan, the Revenue Builders podcast goes behind the scenes with the sales leaders who have been there, done that, and seen the results. This show is brought to you by Force Management. We help companies improve sales performance, executing their growth strategy at the point of sale. Connect with Us: LinkedInYouTubeForce Management

AI tools are shipping faster than most normal humans can figure out what half of them actually do.So Thursday, August 20 at 10 AM PT / 1 PM ET, we're going LIVE to translate this week's biggest AI launches into plain English.

AGENDA: 04:20 Elon's Deal of the Decade: SpaceX Buys Cursor for $60BN 06:10 Why Cursor Was Surprisingly Cheap at $60BN 07:00 Why Zuckerberg Failed to Buy the AI Prize Elon Secured 12:00 Elon vs Zuck: Who Would You Rather Work For? 14:00 Will Microsoft or Amazon Now Race to Buy Cognition? 17:05 Stripe's $7BN OpenRouter Deal Creates Huge VC Winners 25:00 OpenRouter's Fatal Risk: Enterprises Don't Want 10 Models 28:15 Anthropic Turns Its First Profit on $11.5BN of Quarterly Revenue 32:15 Can Anthropic Really Reach $600BN in Revenue? 37:00 Why Every Elite Engineer Could Soon Get $100K in AI Tokens 39:30 Would Rory Buy Anthropic at a $2.5TN Valuation? 44:50 Silver Lake's $43BN Workday Bet: SaaS Isn't Dead, It's Mature 53:00 How Silver Lake Could Make $30BN From Workday 57:00 Lovable vs Higgsfield: Similar Revenue, Radically Different Valuations 58:00 Is Lovable's $13.3BN Price Actually Cheap? 63:30 Why the DOJ Is Coming After Andreessen Horowitz 69:00 Why A16Z Has "50 Legal Battles" Happening at Once  

In the security news this week: Cursor opens your repo, the repo opens you If you want the good model I'm going to need to see your ID Flock's a Flocking mess Defender was supposed to be the chosen one Side stepping Secure boot - twice SonicWall: a LAMP stack in a fancy case Macs don't get viruses, part infinity Flipper One, but why not Nix? NetScaler is back in the room Borrowing phone's good reputation USB and how to make Windows download stuff A KVM with the expensive letters removed Five steps to stop the webcam creeps PlexTrac acquired NIST asks the internet to fix the NVD Poland's health software has a very bad week If Apple pings you about spyware, believe it A macOS stealer that drives your browser for you T-Mobile's incident response tool of choice may suprise you, or not... Visit https://www.securityweekly.com/psw for all the latest episodes! Show Notes: https://securityweekly.com/psw-940

My guest today is Ben Thompson, the founder and author of Stratechery. Ben is one of my favorite business thinkers and I love talking to him about everything happening in markets and technology.  We go through every important company, including OpenAI, Nvidia, Intel, Apple, Microsoft, Google, and Amazon. We also discuss why he thinks it would be dangerous for the United States to win the AI race outright, what container shipping and the railroads of the 1870s tell us about the buildout, and why the binding constraint on all of this may be capital rather than compute.  Please enjoy my conversation with Ben Thompson. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- ⁠Ramp's⁠ mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠ramp.com/invest⁠⁠ to sign up for free and get a $250 welcome bonus. ----- Trusted by thousands of businesses, ⁠Vanta⁠ continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Invest Like the Best listeners get a special offer of $1,000 off Vanta when you go to ⁠vanta.com/invest⁠.  ----- WorkOS⁠ is the infrastructure B2B and AI-native companies use to sell to enterprise. It covers everything enterprise security requires: SSO, SCIM, RBAC, Audit Logs, AI governance, and more. Trusted by 2,000+ fast-growing companies, including OpenAI, Anthropic, Cursor, and Vercel. ----- Rogo is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- ⁠Ridgeline⁠ has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Visit⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgeline.ai⁠. ----- Editing and post-production work for this episode was provided by The Podcast Consultant. Timestamps: (00:00:00) Welcome to Invest Like The Best (00:02:16) Winning the AI Race With China (00:08:28) Timing, Capital, and the Railroads (00:11:34) Berkshire, Google, and Absolute Profits (00:14:23) Verifiable and Unverifiable Domains (00:20:20) Aggregation Theory in the AI Era (00:22:06) The Real Cost of Inference (00:25:40) Why Consumer AI Needs Advertising (00:30:08) Compute Shortages and Commodity Markets (00:35:46) Memory Cycles and Boom Bust Dynamics (00:42:08) TSMC, Intel, and Where Risk Goes (00:44:51) The Best Setups in Big Tech (00:52:14) The Frontier Model Contenders (00:54:27) Microsoft's IBM Playbook (01:00:45) Meta, Attention, and Advertising (01:07:29) NVIDIA, Commodities, and Power

AI is changing what effective knowledge work requires. NLW presents five essential skills for working with agents, building new tools, and recognizing opportunities that were previously impossible—grounded in the domain judgment AI can't replace. In the headlines: Cursor takes on GitHub, Anthropic's revenue surges, and Stripe acquires OpenRouter.AIDB's AI Summer Adventure: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://summeradventure.ai/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Brought to you by:KPMG – Research from KPMG and the University of Texas at Austin shows the highest-impact AI users treat AI like a reasoning partner — and those skills can be taught at scale. Learn more at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://kpmg.com/us/Sophisticated⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Harbor - Invest in the AI ecosystem. ⁠⁠⁠⁠https://www.harborcapital.com/aidaily⁠⁠⁠⁠Hyperagent - Hire a fleet of always-on agents. New users get $1,000 in inference. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠hyperagent.com/aidailybrief⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Rackspace Technology- One accountable partner to build, operate and run your full enterprise AI stack ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.rackspace.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Section - Section turns AI investment into workforce transformation and ROI - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.sectionai.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 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

ChatGPT can do what now?

My guest today is Eric Vishria, a General Partner at Benchmark.  Eric has spent his career in software and cloud, and few people know the history of these markets as well as he does. What makes him special is his ability to use that history to make sense of today.  We discuss what the rise of AWS teaches us about AI, what he has learned from investing in Fireworks, Sierra, and Cerebras, and how the criteria for winning have changed for founders and investors.  Please enjoy my conversation with Eric Vishria. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- ⁠Ramp's⁠ mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠ramp.com/invest⁠⁠ to sign up for free and get a $250 welcome bonus. ----- Trusted by thousands of businesses, ⁠Vanta⁠ continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Invest Like the Best listeners get a special offer of $1,000 off Vanta when you go to ⁠vanta.com/invest⁠.  ----- WorkOS⁠ is the infrastructure B2B and AI-native companies use to sell to enterprise. It covers everything enterprise security requires: SSO, SCIM, RBAC, Audit Logs, AI governance, and more. Trusted by 2,000+ fast-growing companies, including OpenAI, Anthropic, Cursor, and Vercel. ----- Rogo is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- ⁠Ridgeline⁠ has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Visit⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgeline.ai⁠. ----- Editing and post-production work for this episode was provided by The Podcast Consultant. Timestamps: (00:00:00) Welcome to Invest Like The Best (00:02:20) Learning the World Through Fireworks (00:05:42) AWS Was Going to Eat Everything (00:07:40) The Zero-Sum Thinking Trap (00:09:01) Comparing Cloud and AI Adoption (00:11:03) Becoming Enterprise's AI Sherpa (00:13:05) Building Sandcastles (00:14:55) The Return to Being Technical (00:17:13) The Shifting Competitive Frontier (00:22:10) Why the Old Playbook Fails (00:27:53) Energy as the Binding Constraint (00:29:38) The Cerebras Story (00:37:57) The Virtue of Productive Naivete (00:39:19) What Robotics Still Needs (00:45:58) What Makes a Great Board Partner (00:51:13) Raising A Growth Fund (00:55:39) What the Big Winners Taught Him (00:57:37) Hard Work Versus the Hole-in-One (00:58:38) The Best Reasons to Go Public (01:01:09) Debates Inside Benchmark (01:02:16) What If It All Works (01:03:35) What Geoff Hinton Got Wrong