Podcasts about Databricks

Plus: Invictus Growth Partners to acquire Informed.IQ, an AI-based fraud detection company. And PayPal applies to establish its own bank. Julie Chang hosts. Learn more about your ad choices. Visit megaphone.fm/adchoices

Bob Elliott of Unlimited joins the show to break down the market backdrop as investors weigh growth, risk, and positioning, before Leslie Picker reports on what could be the biggest IPO of 2025 with Medline set to price. Databricks CEO Ali Ghodsi discusses his company's latest valuation and what it signals for private AI companies. Collapsing oil prices and unusual Venezuelan shipping activity with Bill Perkins of Skylar Capital. Julia Boorstin explains Instagram's push onto the TV screen. Eric Mandl of Guggenheim on the outlook for tech M&A and what deals could define the next phase for the sector. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

David George is a General Partner at Andreessen Horowitz, where he leads the firm's Growth investing team. His team has backed many of the defining companies of this era, including Databricks, Figma, Stripe, SpaceX, Anduril, and OpenAI, and is now investing behind a new generation of AI startups like Cursor, Harvey, and Abridge. AGENDA: 03:05 – Why Everyone is Wrong: Mega Funds Does Not Reduce Returns 10:40 – Is Public Market Capital Actually Cheaper Than Private Capital? 18:55 – The Biggest Advantage of Staying Private for Longer 23:30 – The #1 Investing Rule for a16z: Always Invest in the Founder's Strength of Strengths 31:20 – Why Fear of Theoretical Competition Makes Investors Miss Great Companies 35:10 – Does Revenue Matter as Much in a World of AI? 44:10 – Does Kingmaking Still Exist in Venture Capital Today? 49:20 – Do Margins Matter Less Than Ever in an AI-First World? 53:50 – My Biggest Miss: Anthropic and What I Learn From it?  56:30 – Has OpenAI Won Consumer AI? Will Anthropic Win Enterprise? 59:45 – The Most Controversial Decision in Andreessen Horowitz History 1:01:30 – Why Did You Invest $300M into Adam Neumann and Flow?    

What does it actually take to move machine learning from experiments into production reliably, responsibly, and at scale?In this episode of Alexa's Input (AI), Alexa talks with Maria Vechtomova, co-founder of Marvelous MLOps and an O'Reilly author-in-progress on MLOps with Databricks. Maria shares how her background in data science led her into MLOps, and why most teams struggle not because of tools, but because of missing processes, traceability, and shared understanding across teams.Alexa and Maria dive into what separates good MLOps from fragile deployments, why shipping notebooks as “production” creates long-term pain, and how traceability across code, data, and environment forms the foundation for reliable ML systems. They also explore how LLM applications are reshaping MLOps tooling, and where the biggest skill gaps still exist between platform, data, and AI engineers.A must-listen for anyone building, operating, or scaling machine learning systems and for teams trying to make MLOps less magical and more marvelous.Learn more about Marvelous MLOps and Maria's work below.LinksWatch: ⁠⁠https://www.youtube.com/@alexa_griffith⁠⁠Read: ⁠⁠⁠⁠https://alexasinput.substack.com/⁠⁠⁠⁠Listen: https://creators.spotify.com/pod/profile/alexagriffith/More: ⁠⁠https://linktr.ee/alexagriffith⁠⁠Website: ⁠⁠https://alexagriffith.com/⁠⁠LinkedIn: ⁠⁠https://www.linkedin.com/in/alexa-griffith/⁠⁠Find out more about the guest at:LinkedIn: https://www.linkedin.com/in/maria-vechtomova/TakeawaysMaria started as a data analyst and transitioned into MLOps.She emphasizes the importance of tracking data, code, and environment in MLOps.MLOps is a practice to bring machine learning models to production reliably.Good deployment processes require modular code and proper tracking.MLOps differs from DevOps due to the complexities of data and model drift.Education is crucial for bridging gaps between teams in AI.Small steps can lead to better MLOps practices.Scaling MLOps requires understanding the unique data of different brands.The rise of LLMs is changing the MLOps landscape.Effective teaching methods involve step-by-step guidance.Chapters00:00 Introduction to MLOps and Maria's Journey02:11 Maria's Path to MLOps and Knowledge Sharing04:41 The Importance of MLOps in AI Deployments10:12 Defining MLOps and Its Challenges11:38 MLOps vs. DevOps: Key Differences13:00 Overcoming Stagnation in MLOps16:04 Small Steps Towards Better MLOps Practices19:29 Scaling MLOps in Large Organizations21:58 The Impact of LLMs on MLOps23:58 The Shift from Traditional ML to AI Applications26:51 Evolving Roles in AI Engineering28:33 Databricks: A Comprehensive AI Platform31:45 Future of AI Platforms and Regulations34:26 Bridging Skill Gaps in AI Teams38:42 The Importance of Context in AI Development40:40 Foundational Skills for MLOps Professionals45:43 Integrating Personal Passions with Professional Growth47:30 Building Impactful AI Communities

Is AI finally ready to do your job — better, faster, and cheaper?In this week's Leveraging AI news recap, host Isar Meitis unpacks a flurry of groundbreaking developments in the world of artificial intelligence — from the release of GPT-5.2 to jaw-dropping advances in recursive self-improving AI (yes, it's as intense as it sounds).Whether you lead a business, a team, or just need to stay ahead of the AI curve — this episode is your executive summary for everything that matters (and nothing that doesn't).We'll also dig into the billion-dollar OpenAI–Disney partnership, how real users are actually leveraging AI in the wild, and why the Fed is finally admitting AI is changing the job market.In this session, you'll discover:The GPT-5.2 release: performance benchmarks and real-world capabilitiesIs GPT-5.2 better than humans at actual work? (71% of the time, yes)Why OpenAI's new “not-an-ad” ad rollout caused a user revoltOpenAI x Disney: Why $1B is being bet on AI-generated Mickey Mouse contentGPT-5.2's weak spots and where Claude Opus still dominatesWhat Recursive Self-Improving AI means (and why Eric Schmidt is nervous)AI designing its own hardware: A startup that could rewrite Moore's LawNew usage data from OpenRouter, Microsoft, SAP & Perplexity – how people actually use AI Why prompt length is exploding (and what that means for your business)AI agents in browsers: the productivity revolution or a security nightmare?Databricks proves AI sucks at raw documents (and how to fix it)The psychological bias against AI-created work — it's realClaude's new Slack integration: is this the dev team you didn't hire?Apple's AI brain drain & why it mattersGartner says: Block AI browsers (for now)AI and unemployment: The Fed finally connects the dotsWant to future-proof your team's AI skills? Isar's AI Business Transformation Course launches again in January — a proven, real-world guide to using AI across content, research, operations, and strategy.

AGENDA: 03:46 SpaceX's $800 Billion Valuation: A Deep Dive 09:18 IPO Market Predictions for 2026 18:18 Netflix's Bold Move: Acquiring Warner Brothers 27:43 Tiger's New Fund Strategy 33:02 Databricks' Head of AI $500 Million Seed Round 36:38 Harvey Raises $160M at an $8BN Valuation 48:22 Will LLMs Kill the App Layer 01:02:02 Google's AI Capabilities 01:06:58 Chinese Open Source Models in US Startups 01:08:57 Airwallex Raises $330M at an $8BN Valuation 01:23:50 Prediction Markets and Insider Trading  

Tiger's last fund did well with investments in OpenAI, Waymo and Databricks. But it warns investors that AI valuations are already 'elevated.' Skild AI is developing a hardware-agnostic foundation model for robots that can be customized for various uses. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Naveen Rao is cofounder and CEO of Unconventional AI, an AI chip startup building analog computing systems designed specifically for intelligence. Previously, Naveen led AI at Databricks and founded two successful companies: Mosaic (cloud computing) and Nervana (AI accelerators, acquired by Intel). In this episode, a16z's Matt Bornstein sits down with Naveen at NeurIPS to discuss why 80 years of digital computing may be the wrong substrate for AI, how the brain runs on 20 watts while data centers consume 4% of the US energy grid, the physics of causality and what it might mean for AGI, and why now is the moment to take this unconventional bet. Stay Updated:If you enjoyed this episode, please be sure to like, subscribe, and share with your friends.Follow Naveen on X: https://x.com/NaveenGRaoFollow Matt on X: https://x.com/BornsteinMattFollow a16z on X: https://twitter.com/a16zFollow a16z on LinkedIn:https://www.linkedin.com/company/a16zFollow the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXFollow the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Please 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 http://a16z.com/disclosures. Stay Updated:Find 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.

On this episode of The Six Five Pod, hosts Patrick Moorhead and Daniel Newman discuss the latest tech news stories that made headlines. This week's handpicked topics include:  The Decode US, Saudi tout new business deals at investment forum https://www.reuters.com/world/middle-east/saudi-crown-prince-seeks-burnish-image-with-corporate-americas-top-executives-2025-11-19/ AMD, Cisco, and HUMAIN to form joint venture to deliver world-leading AI infrastructure https://newsroom.cisco.com/c/r/newsroom/en/us/a/y2025/m11/amd-cisco-and-humain-to-form-joint-venture-to-deliver-world-leading-ai-infrastructure.html Adobe, Qualcomm partner with Humain on generative AI for Middle East https://www.reuters.com/world/middle-east/adobe-qualcomm-partner-with-humain-generative-ai-middle-east-2025-11-19/ Qualcomm to open engineering hub in Saudi Arabia, part of a series of AI deals in kingdom https://finance.yahoo.com/news/qualcomm-to-open-engineering-hub-in-saudi-arabia-part-of-a-series-of-ai-deals-in-kingdom-180008935.html Elon Musk's xAI will be first customer for Nvidia-backed data center in Saudi Arabia https://www.cnbc.com/2025/11/19/musks-xai-will-be-customer-for-nvidia-data-center-in-saudi-arabia.html Microsoft, Nvidia to invest in Anthropic as Claude maker commits $30 billion to Azure https://finance.yahoo.com/news/anthropic-commits-30-billion-microsoft-150718625.html https://blogs.nvidia.com/blog/microsoft-nvidia-anthropic-announce-partnership/ https://x.com/danielnewmanUV/status/1990802932602999149 https://x.com/danielnewmanUV/status/1990822426884682020 https://x.com/danielnewmanUV/status/1990865570242187267 Microsoft Ignite - Announcements https://azure.microsoft.com/en-us/blog/azure-at-microsoft-ignite-2025-all-the-intelligent-cloud-news-explained/ https://x.com/PatrickMoorhead/status/1990845768178282745 https://x.com/PatrickMoorhead/status/1990859751006351461 https://x.com/PatrickMoorhead/status/1990861596558774469 https://x.com/danielnewmanUV/status/1990848107223933309?s=20 Google Gemini 3 Launch https://blog.google/products/gemini/gemini-3/ https://x.com/danielnewmanUV/status/1990875878549512251 https://x.com/PatrickMoorhead/status/1991150119891223015 Yann LeCun Leaving Meta https://www.businessinsider.com/meta-ai-yann-lecun-llm-world-model-intelligence-criticism-2025-11  Pat & Dan interview with Yann LeCun at last year's Davos: https://youtu.be/0gmDufvWlWE  Cloudflare resolves outage that caused widespread internet disruptions, taking down X, ChatGPT for some users https://www.yahoo.com/news/article/cloudflare-resolves-outage-that-caused-widespread-internet-disruptions-taking-down-x-chatgpt-for-some-users-141316666.html OpenText World 2025 - Recap https://x.com/PatrickMoorhead/status/1990806348393554203 https://x.com/danielnewmanUV/status/1990805006661136469 Supercompute 2025 - Recap https://x.com/danielnewmanUV/status/1991231108646678537?s=20 The Flip: Can Google unseat OpenAI as the new benchmark of AI? (The Flip) Bulls & Bears Delayed September report shows U.S. added 119,000 jobs, more than expected; unemployment rate at 4.4% https://www.cnbc.com/2025/11/20/jobs-report-september-2025.html Fed minutes show divide over October rate cut and cast doubt about December https://www.cnbc.com/2025/11/19/fed-minutes-october-2025.html Lenovo Earnings https://news.lenovo.com/pressroom/press-releases/q2-fy-2025-26/ NVIDIA Earnings https://www.cnn.com/2025/11/19/tech/nvidia-earnings-ai-bubble-fears https://x.com/danielnewmanUV/status/1990526850171613211 https://x.com/danielnewmanUV/status/1990538832295702574 https://x.com/danielnewmanUV/status/1991156846900515130 https://x.com/PatrickMoorhead/status/1991544029675135247?s=20 https://x.com/PatrickMoorhead/status/1991540564794220778?s=20 Amazon Raises $15 Billion in First US Bond Sale in Three Years https://finance.yahoo.com/news/amazon-kicks-off-first-us-132051192.html Databricks in talk to raise at $130B valuation https://techcrunch.com/2025/11/18/databricks-reportedly-in-talks-to-raise-funding-at-a-130b-valuation/  

AGENDA: 04:20 Thrive and OpenAI Partnership  07:14 Databricks Raising $5BN at $134BN Valuation: Cheap or Not? 17:39 Eventbrite Acquired by Bending Spoons for $500M 21:39 Pagerduty's $1BN Market Cap, Just 2x Revenue 26:59 The TAM Trap: Why SaaS Is Like Japan 37:42 Lessons from Companies Hitting $100M ARR 44:57 The Future of Labour Markets is F****** 52:10 The Importance of Compounding in Investments 56:45 The Relevance Game in Venture Capital 01:05:01 Supabase at $5BN or Lovable at $6BN: Which One?  

Varun Puri, CEO and cofounder of Yoodli, joins the show to talk about using AI role play to transform how people practice for high stakes conversations, from sales calls to job interviews to tough manager chats. He breaks down how Yoodli went from a consumer public speaking tool to a serious enterprise platform used by teams at Google, Snowflake, Databricks, and more, all while staying anchored in one mission, helping humans communicate with confidence. We dig into product led growth, honest feedback loops, and why real human communication will matter even more as AI makes information instant.Key takeaways• Why Yoodli started with public speaking anxiety and grew into an AI role play simulator for any important conversation, not just conference talks or pitch decks• How watching real user behavior inside companies like Google pulled the team into enterprise without abandoning their consumer product• A simple approach to product feedback, talk to end users constantly, then prioritize changes by business impact, renewal risk, and how many people benefit• What it really takes to move from consumer to enterprise, new roles, new processes, and a very different mindset around reliability, security, and expectations• Why Varun draws clear ethical lines, using AI to coach and prepare people, not to replace human judgment in hiring, promotion, or high trust decisionsTimestamped highlights[00:35] What Yoodli actually does today, from solo practice to training sales and go to market teams inside large enterprises[01:43] The original vision, helping people who are scared of public speaking, and the insight that interviews, sales calls, and manager talks are all just role plays[03:37] How the team listens to end users, the channels they rely on, and why the consumer product is still their testing ground for new ideas and experiments[05:20] Following users into the enterprise, why it was an addition and not a full pivot, and how product led growth inside companies like Google works in practice[07:42] The early shock of selling to enterprises, learning about new roles, SLAs, InfoSec, and bringing in leaders from Tableau and Salesforce to build a real B2B engine[11:10] Two paths for AI in sales, tools that try to replace humans versus tools that make humans better, and why Varun has drawn a hard line on what Yoodli will not do[15:26] A future where information is commoditized and instant, and why communication and presence become the real edge for top performers in that world[20:48] Designing for trust and adoption, how Yoodli keeps practice private by default, when data is shared, and why control has to sit with the end userA line worth saving“In a world where AI makes everyone smarter and faster, the thing that will be at the biggest premium is how you communicate as a human with other humans.”Practical ideas you can use• Keep a consumer like surface in your product so you can experiment faster than your enterprise roadmap would ever allow• Treat feedback from large customers like a queue you rank by renewal risk, strategic value, and number of users helped, not as a list you must clear• Look for product led growth signals inside your user base, if thousands of people in one company are using you, someone there probably wants a team level solution• Draw explicit boundaries for your AI product, write down what you will not automate, so you can build trust with users and buyers over the long termCall to actionIf you care about the future of sales, interviewing, and communication in an AI rich world, this conversation is worth a listen. Follow the show, leave a quick rating, and share this episode with a founder, product leader, or sales leader who is thinking about AI in their workflow. And if you want feedback on your own speaking, check out what Varun and his team are building at Yoodli.

Send us a textInvest in pre-IPO stocks with AG Dillon & Co. Contact aaron.dillon@agdillon.com to learn more. Financial advisors only. www.agdillon.com00:06 - Databricks $134B Primary at 32x 2025E Sales02:20 - Revolut $75B Tender (+56% vs Aug 2025)04:30 - Physical Intelligence (Pi) $5B Primary (+>2.5x in

My guest today is David George. David is a General Partner at Andreessen Horowitz, where he leads the firm's growth investing business. His team has backed many of the defining companies of this era – including Databricks, Figma, Stripe, SpaceX, Anduril, and OpenAI – and is now investing behind a new generation of AI startups like Cursor, Harvey, and Abridge. This conversation is a detailed look at how David built and runs the a16z growth practice. He shares how he recruits and builds his team a “Yankees-level” culture, how his team makes investment decisions without traditional committees, and how they work with founders years before investing to win the most competitive deals. Much of our conversation centers on AI and how his team is investing across the stack, from foundational models to applications. David draws parallels to past platform shifts – from SaaS to mobile – and explains why he believes this period will produce some of the largest companies ever built. David also outlines the models that guide his approach – why markets often misprice consistent growth, what makes “pull” businesses so powerful, and why most great tech markets end up winner-take-all. David reflects on what he's learned from studying exceptional founders and why he's drawn to a particular type, the “technical terminator.” Please enjoy my conversation with David George. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠.⁠⁠⁠⁠⁠⁠⁠⁠ ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ramp⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. 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. ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ridgeline⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. 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. Head to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgelineapps.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to learn more about the platform. ----- This episode is brought to you by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AlphaSense⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. AlphaSense has completely transformed the research process with cutting-edge AI technology and a vast collection of top-tier, reliable business content. Invest Like the Best listeners can get a free trial now at⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Alpha-Sense.com/Invest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and experience firsthand how AlphaSense and Tegus help you make smarter decisions faster. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Show Notes: (00:00:00) Welcome to Invest Like The Best (00:04:00) Meet David George (00:03:04) Understanding the Impact of AI on Consumers and Enterprises (00:05:56) Monetizing AI: What is AI's Business Model (00:11:04) Investing in Robotics and American Dynamism (00:13:31) Lessons from Investing in Waymo (00:15:55) Investment Philosophy and Strategy (00:17:15) Investing in Technical Terminators (00:20:18) Market Leaders Capture All of the Value Creation (00:24:56) The Maturation of VC and Competitive Landscape (00:28:18) What a16z Does to Win Deals (00:33:06) David's Daily Routine: Meetings Structure and Blocking Time to Think (00:36:34) Why David Invests: Curiosity and Competition (00:40:12) The Unique Culture at Andreessen Horowitz (00:42:46) The Perfect Conditions for Growth Investing (00:47:04) Push v. Pull Businesses (00:49:19) The Three Metrics a16z Uses to Evaluate AI Companies (00:52:15) Unique Products and Unique Distribution (00:54:55) Tradeoffs of the a16z Firm Structure (00:59:04) a16z's Semi-Algorithmic Approach to Selling (01:00:54) Three Ways Startups can Beat Incumbents in AI (01:03:44) The Kindest Thing

The Department of Heath and Human Services has been leaning into the use of artificial intelligence to drive better health outcomes for the American public, highlighted by the rollout of ChatGPT across the agency early this fall. In particular, the Centers for Disease Control and Prevention has been a leader in generative AI adoption since 2023. And Travis Hoppe, CDC's chief AI officer, believes AI innovation can continue to move the needle on public health operations. Hoppe joined me recently onstage at FedTalks to share the latest on CDC's AI journey, how the Trump administration's AI Action Plan is guiding the agency's implementation and what's next. The National Nuclear Security Administration is looking for information on potential AI uses for its mission, following an executive order to establish an integrated AI platform that will fuel scientific discovery. In a request for information posted to SAM.gov on Monday, the Department of Energy subcomponent that oversees the nation's nuclear stockpile said it's exploring the use of the budding technology, and specifically requested information about its use in classified environments, best practices for data curation, and how to approach developing and enhancing AI models, among other things. The request comes just a week after the Trump administration launched the “Genesis Mission,” aimed at scientific discovery through AI. That effort will not only create an AI platform for such discovery, but it will also depend on the country's existing research and development infrastructure, including DOE and its national labs. To further the Genesis program, NNSA said it's proactively exploring the use of AI for its “critical operations to accelerate nuclear weapons development timelines, ensuring our deterrent remains responsive, effective, and state-of-the-art against evolving global threats.” Software company SAP inked a new agreement with the General Services Administration to offer federal agencies access to its services at significantly discounted rates, deepening its longstanding partnership with the federal government. The GSA announced the OneGov deal Tuesday, stating that the agreement offers up to 80 percent discounts on SAP's database, cloud, and analytics services. The agency estimated this will lead to $165 million in savings for federal agencies. Specifically, agencies will be able to access products related to SAP's database and data management services with an 80 percent discount. SAP's cloud services, including SAP Business Technology Platform, SAP Analytics Cloud and HR Payroll, will be offered at a 35 percent discount, GSA said. Also in this episode: Databricks VP of Public Sector Todd Schroeder joins SNG host Wyatt Kash in a sponsored podcast discussion on why agencies are prioritizing the use of AI that works across existing data environments, saving time and infrastructure costs. This segment was sponsored by Databricks. The Daily Scoop Podcast is available every Monday-Friday afternoon. If you want to hear more of the latest from Washington, subscribe to The Daily Scoop Podcast  on Apple Podcasts, Soundcloud, Spotify and YouTube.

In this episode of the Technology & Security podcast, host Dr. Miah Hammond-Errey is joined by Kate Carruthers. Kate is currently the head of data analytics and AI at the Australian Institute of Company Directors. She shares her journey from defending Westfield against state and non-state cyber attacks to leading UNSW's enterprise data, AI, and cybersecurity efforts, including delivering the university's first production AI system in 2019 and re-architecting its cloud data platform for AI and ML. She notes boardrooms are evolving from basic cyber literacy to probing AI risks like models, data, and risk registers.  Carruthers outlines some real-world examples, such as UNSW's enterprise AI program, including a machine learning model that predicted which students were likely to fail a course, with 95%+ accuracy, so the university could design careful, humane intervention protocols to reduce self-harm risk. She argues that while frontier models like OpenAI and Gemini have a place, their compute costs, water intensity and general-purpose design make them poorly suited to some business problems, and that the future lies in smaller, industry-specific models trained on highly relevant data. The conversation covers the rise of agentic AI coding tools, the risk of deskilling junior developers, and the need for diverse, product-focused teams to translate technical systems into workable human processes.​ On security, she prioritizes CIA triad integrity over confidentiality, warning of data alterations in cars, medical devices, and government systems via poisoning or underinvestment in encryption. Carruthers urges Australian AI sovereignty—opting for open-source like Databricks over proprietary stacks—amid US-China model contrasts and outage risks from providers like AWS or CrowdStrike. Throughout, she encourages leaders not just to read about AI but to use multiple systems themselves, understand their limitations as probabilistic tools in deterministic business environments, and ground every deployment in clearly defined problems, ethics, and user needs.​

The 5 things you need to know before the stock market opens today: President Trump says he's made his choice for next chair of the Federal Reserve, Disney had brought in more than $500 million globally on the “Zootopia 2” box office, South Korean police are investigating a data breach at e-commerce site Coupang, data analytics firm Databricks is in talks to raise $5 billion at a valuation topping $134 billion, and UnitedHealth Group will reportedly sell off its last South American business. Squawk Box is hosted by Joe Kernen, Becky Quick and Andrew Ross Sorkin.  Follow Squawk Pod for the best moments, interviews and analysis from our TV show in an audio-first format. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this special Cloud Wars report, Bob Evans sits down with Michael Ameling, President and Chief Product Officer of SAP Business Technology Platform, for a deep dive into how SAP is helping customers navigate the fast-moving AI Era. Ameling and Evans discuss how SAP's Business Data Cloud, partnerships with Snowflake and Databricks, HANA Cloud innovations, and new AI-powered tools and agents are helping SAP evolve from an applications powerhouse into a data-and-AI-driven business platform for the next generation.SAP's AI Data FutureThe Big Themes:SAP HANA Cloud Becomes an AI-Optimized Database: SAP HANA Cloud is evolving into “the database AI was looking for." As a multi-model system supporting spatial, graph, vector, and document storage, HANA Cloud enables AI workloads to run more efficiently and contextually. Recent additions, like vector engines and Knowledge Graph capabilities, give customers powerful tools for retrieval-augmented generation (RAG), contextual reasoning, and advanced analytics.Developers Are 'The AI Revolution': Developers aren't observing the AI Revolution, they are the revolution. With modern AI tools, developers can innovate faster, solve bigger problems, and directly influence business outcomes. SAP is investing heavily in meeting developers where they are by enhancing IDEs, building business-aware development tools, and providing context-rich assets such as APIs, business objects, and process insights. AI acts as a teammate, not a replacement.SAP: An Applications and a Data Company: SAP must be both an applications and a data company. Customer value emerges when applications, data, and AI converge seamlessly. SAP's decades of industry expertise give it unparalleled business context, which becomes even more powerful when embedded into AI agents and data platforms. With more than 34,000 SAP HANA Cloud customers and rapidly expanding AI adoption, SAP is positioning itself as the platform where business process knowledge meets modern AI capability.The Big Quote: " . . what we need to understand that AI is our teammate. It's like asking your best friend who has a lot of knowledge, but you can ask multiple friends at the same time. Not everything is always right, but you can ask questions, you can continuously improve. If we understand that pattern, we understand that AI helps us to solve much bigger problems as a developer, and then, of course, having much more impact on real business."More from Michael Ameling and SAP:Connect with Michael Ameling on LinkedIn, or get more insights from SAP TechEd.  Visit Cloud Wars for more.

Todd Schroeder of Databricks explains how AI and recent tech innovations enable federal agencies to bring AI to widely distributed data, instead of moving data to applications, reducing costs, improving security and accelerating decision making.

In Conversation with Patricia Ferreiro on In Your Shoes Podcast about Philosophy of languages, Large language models, future of intelligence and how to be effective in the age of information abundance.Patricia is the founder and CEO of Luar Labs based out of Zurich, Switzerland. Prior to this, she had technical and strategy roles at Microsoft, DataBricks and IBM. At Luar Labs, she trains executives in AI literacy and critical thinking or the digital age, cultivating resilient mental models for a meaningful collaboration with present and future technologies. Connect with Patricia : https://www.linkedin.com/in/patriciaferreiro/

Proof of concepts were once the hallmark of innovation. Today, they are the bottleneck. The most successful technology partnerships are moving beyond pilots and into production, building together, scaling together, and differentiating together.  In this episode of the Zinnov podcast, Jason McIntyre, VP, Consulting & SI Program - Scale Ecosystem, Databricks, joins Rajat Kohli, Partner at Zinnov, for an unfiltered conversation on the future of ecosystems in the age of data and AI.  From the evolution of system integrators into solution creators to why co-development will define the next decade of alliances, Jason shares what it takes to build partnerships that go beyond enablement and marketing. He explains how differentiation, industry depth, and partner mentality can turn collaboration into a true competitive edge.  Tune in now.       

Welcome to a Special Episode of AI Unraveled: The Cost of Data Gravity: Solving the Hybrid AI Deployment Nightmare.We are tackling the silent budget killer in enterprise AI: Data Gravity. You have petabytes of proprietary data—the "mass" that attracts apps and services—but moving it to the cloud for inference is becoming a financial and regulatory nightmare. We break down why the cloud-first strategy is failing for heavy data, the hidden tax of egress fees, and the new architectural playbook for 2025.Source: https://www.linkedin.com/pulse/cost-data-gravity-solving-hybrid-ai-deployment-nightmare-djamgatech-ic42cStrategic Pillars & Topics

Send us a textInvest in pre-IPO stocks with AG Dillon & Co. Contact aaron.dillon@agdillon.com to learn more. Financial advisors only. www.agdillon.com00:00 - Intro00:08 - Anthropic Mega-Scale Infra + $350B Valuation Surge01:44 - xAI $15B Raise at $230B Valuation02:45 - xAI Saudi Arabia 500MW Data Center03:57 - xAI Grok 5 to be Released in Q1 202604:42 - Databricks $130B+ Valuation in Discussion05:55 - Ramp Hyper-Growth to $32B Valuation06:47 - Kraken $800M Raise at $20B Valuation07:51 - Kalshi $1B Raise at $11B Valuation08:54 - Faire Employee Tender at $5.2B09:42 - Apptronik $5B Raise for Humanoid Robots10:44 - Tenstorrent $800M Raise at $3.2B Valuation11:45 - Function Health $298M Raise at $2.5B Valuation12:55 - Suno $250M Series C at $2.45B Valuation13:51 - Bezos Returns as Co-CEO of Prometheus14:42 - Thinking Machines to Raise $5B15:27 - Lambda raised $1.5B + Multibillion Microsoft Deal16:31 - Blue Origin's New Glenn 9x4 Super-Heavy Rocket17:29 - Starlink's New $40 Plan + 10,000 Satellites18:15 - Starlink Wins Emirates Airlines Fleet Deal19:10 - Target to join OpenAI ChatGPT Shopping + Enterprise Rollout20:01 - Perplexity Comet AI Browser Launch

In today's Tech3 from Moneycontrol, we break down the government's big labour code update that mandates IT salaries be paid by the 7th of every month. We also dive into the blockbuster year for VCs with Rs 15,000 crore in IPO exits, Meesho's $5.9 billion listing plans, and an exclusive with Uniphore CEO Umesh Sachdev on why AI rivals NVIDIA, AMD, Snowflake and Databricks invested together. Plus, Groww's first results post-IPO reveal profit up but revenue dipping.

In this CRO Spotlight episode, host Warren Zenna sits down with Steven Birdsall, CRO at Alteryx, to unpack a sweeping leadership transition and how a newly formed C‑suite aligned on product and go‑to‑market. Steven shares how a product‑centric CEO and a servant‑leader CRO combine to create clarity of mandate, performance culture, and human‑first execution across sales, CS, partners, and solutions engineering.The conversation dives deep into Alteryx's evolution from workflows feeding BI to becoming the governed “canvas” for AI and agent use cases. Steven explains how business users can blend structured and unstructured data, enforce governance and access controls, and then safely bring LLMs into the same environment—pushing compute down to cloud data platforms like BigQuery, Databricks, and Snowflake.For CROs, Steven details practical AI operationalization: SDR personalization at scale, three‑dimensional agents trained on company knowledge, and revenue insights built directly on internal data. He outlines how to raise sales efficiency without scaling opex linearly, and why fast experimentation with new AI tools is now core to modern GTM orchestration.Steven closes with hiring and leadership principles for today's CRO: prioritize grit, perseverance, and customer centricity over pedigree; remove roadblocks for the field; and mentor generously. He shares how to balance data‑driven rigor with empathy, build alignment with marketing regardless of reporting lines, and stay entrepreneurial—even inside a large, complex organization.

What happened with Cloudflare this morning. Grok's new model wants to be creative. Catching you up on the bloodbath in crypto if you were unaware. Databricks is 12 years old but it seems to be one of the big AI winners. And debt continues to pile in to the AI buildout. A massive Cloudflare outage brought down X, ChatGPT, and even Downdetector (The Verge) Grok 4.1 has arrived — and it's bringing the fight to ChatGPT with these new features (Tom's Guide) Crypto market sheds $1.2tn as traders shun speculative assets (Financial Times) Google boss says trillion-dollar AI investment boom has 'elements of irrationality' (BBC) Amazon Raises $15 Billion in First US Bond Sale in Three Years (Bloomberg) Databricks in Talks to Raise Capital at a Valuation Above $130 Billion (The Information) Roblox will require age estimation to chat starting next year (The Verge) Learn more about your ad choices. Visit megaphone.fm/adchoices

In today's episode, I'm talking with Andrew Wilhelms, VP of Talent Management at Databricks and a seasoned leader with a wealth of experience from organizations like Twilio and Tesla. In t his conversation, we explore the evolving world of talent development and break down the difference between building individual capabilities and managing organizational systems, and why understanding both is crucial in today's dynamic business landscape.Andrew also shares insights from his unique journey, including how his philosophy background shaped his approach to leadership, what he believes actually transforms good teams into high-performing ones, and why the next wave of talent will require us all—no matter our title—to start thinking (and leading) like executives. They also dig into the impact of AI on both work and leadership, the importance of designing a positive employee experience, and practical ways to move beyond “knowing” to actually “doing” when it comes to developing great leaders.Key Notes and topics we cover in this episode:The Nature of LeadershipPreparing Future LeadersChallenges in Corporate LeadershipTalent Management vs. Talent DevelopmentThe Next Paradigm Shift in Talent: AIAI and Tools in Talent DevelopmentThe “Brickster Experience” at DatabricksPsychological Safety and Growth MindsetManager and Leadership Development ModelsCareer Development PhilosophyLessons Learned & ReflectionsTalent Development TrendsRecommended ResourcesCareer Advice for Talent ProfessionalsThis episode is also sponsored by LearnIt, which is offering a FREE trial of their TeamPass membership for you and up to 20 team members of your team. Check it out here.Connect with Andy here: Website | LinkedInConnect with Andrew Wilhelms here: LinkedInOrder my new book, Own Your Brand, Own Your Career on AmazonAnd my first book, Own Your Career Own Your Life, is on Amazon as well.

S&P futures are down (0.3%) and pointing to a slightly lower open today. Asian equities ended Tuesday trading broadly lower, with the Nikkei leading the declines, down over (3%), followed by the Greater China markets. Markets saw steep losses in large-cap tech and semiconductors ahead of NVIDIA's earnings on Wednesday. Concerns are mounting over high valuations in AI-related stocks, a key driver of this year's market rally. European markets are also sliding now, with the STOXX 600 down (1.2%). Companies Mentioned: NVIDIA, Axalta Coating Systems, Databricks

In this special episode of Cloud Wars Live, Bob Evans speaks with Chad Wahlquist, Architect at Palantir, about the company's explosive Q3 growth and the accelerating adoption of its AI Platform (AIP). They explore how AIP serves as an operating system for the enterprise, enabling customers to achieve global optimization, faster ROI, and model flexibility. Wahlquist also talks about Palantir's open, interoperable architecture and its commitment to delivering value at speed, especially for customers in high-stakes, high-pressure environments.Operate Smarter, Not SlowerThe Big Themes:Speed to Value: Many companies still operate under the assumption that meaningful transformation requires multi‑year timelines (two to three years, sometimes more). Palantir is pushing the idea that you must deliver value in months, three to six months, rather than years. This shift is critical because when business markets move fast, and when competitive advantage erodes quickly, speed becomes a differentiator. If you wait for years, you may miss the window or be out‑paced.Interoperability and Ecosystem Integration: The platform isn't trying to lock you into a “box” you must keep your data in; it instead emphasizes plug‑in interoperability with systems you already have. Wahlquist mentions connectors, SDKs, APIs, and plug‑ins to partners like Snowflake, Databricks, SAP, NVIDIA. The concept: if you already have investment in some systems, don't throw them away; just connect them. This increases the speed to value and reduces friction.Ambition, Willingness to Operate in Crisis: Wahlquist points out they often engage with customers who are under pressure. These customers need value now, not two or three years out. Situations like supply chain disruption, plant outages, labor issues, etc., are real. This situational urgency forces companies to adopt architectures and partners that can deliver now. The takeaway: It's not enough to believe you'll transform in the future; transformation architecture must be built for today's fires.The Big Quote: “Our goal is really: how do we scale our customers and the outcomes they're delivering — not just the number of customers?"More from Chad and Palantir:Follow Chad on LinkedIn or get an overview of Palantir's Q3 in its letter to shareholders. Visit Cloud Wars for more.

Wisdom AI sells to enterprise data teams, empowering them to deploy AI data analysts that automate analytics functions traditionally handled by human analysts. As a former Rubrik co-founder and Google search ranking engineer, Soham identified the analytics problem firsthand while scaling Rubrik from intuition-driven to data-driven operations. In this episode of Category Visionaries, Soham shares how four Rubrik alumni are building a category-defining solution in the data analytics space, the tactical insights from targeting mid-market accounts to optimize deal velocity and onboarding experience, and how AI buying committees shifted from experimental budgets in 2024 to gatekeepers requiring departmental champions in 2025. Topics Discussed: Leveraging mid-market focus to compress sales cycles while refining onboarding as core product differentiation The transition from gut-based decisions to data-driven operations and why analytics remains unsolved Taming LLMs for precision and explainability requirements in enterprise analytics contexts Strategic navigation of the data ecosystem following the FiveTran-DBT merger and positioning against Snowflake, Databricks, and cloud providers Overlaying product-led trial motions on enterprise sales to maintain momentum during extended procurement cycles AI committee evolution from 2024's experimental phase to 2025's security-focused consolidation mandate Pursuing 10x productivity gains versus incremental improvement in established analytics markets GTM Lessons For B2B Founders: Use mid-market to build onboarding velocity as moat: Rubrik deliberately targeted mid-market accounts despite being an enterprise product that closed eight-figure deals. This served two strategic purposes: compressed sales cycles enabled faster learning loops, and the necessity of quick onboarding forced the team to build exceptional admin experiences that became their primary differentiation. For B2B founders, mid-market isn't just easier logos—it's a forcing function for product refinement that creates competitive advantages when moving upmarket. Find problems through operational scar tissue, not market research: Wisdom AI originated when Soham tried moonlighting as engineering's data analyst during Rubrik's scaling phase and discovered he couldn't do it effectively. This wasn't a customer interview insight—it was firsthand recognition that even sophisticated technical leaders with dedicated focus couldn't wrangle data for operational decisions. The problem proved ubiquitous across every business leader optimizing top line, bottom line, and operations. B2B founders building for enterprises should prioritize pain points they've personally hit in operational contexts where existing solutions demonstrably failed them. Engineer time-to-value in minutes for PLG overlay on enterprise sales: Wisdom AI's experiential quality—users get excited when they try it, not when they see slides—creates PLG opportunity despite enterprise positioning. The critical difference: sales-led motions tolerate weeks to first value and build confidence through process, but self-serve requires hook-to-value in minutes with zero support. Soham's insight is using PLG not for credit card swipes but to maintain champion enthusiasm during lengthy procurement processes. B2B founders should architect trial experiences that deliver standalone value pre-data connection, creating internal advocates who sustain momentum through AI committee reviews. Treat ecosystem navigation as first-class GTM workstream: Wisdom AI's success depends on partnership execution with Snowflake, Databricks, and cloud providers—all potential competitors with their own AI initiatives. The FiveTran-DBT merger created immediate dynamic shifts requiring repositioning. Rather than viewing partnerships as business development, Soham frames ecosystem navigation as core GTM infrastructure requiring dedicated strategy and repeatable playbooks. B2B founders in platform-adjacent spaces should staff for partnership complexity early, recognizing that integration points and co-selling motions often determine market access more than direct sales capacity. Architect for AI committee gatekeepers with departmental executive sponsorship: The market fundamentally shifted from mid-2024's "experimental AI budgets, try everything" to 2025's centralized AI committees focused on security, tool consolidation, and preventing organizational wild west scenarios. Soham's tactical response: secure champions owning specific important departments who can navigate approval hierarchies while trial experiences maintain grassroots excitement. The implication for B2B AI founders—assumption of longer cycles, security scrutiny as table stakes, and explicit strategies for climbing from individual enthusiast to organizational deployment become non-negotiable enterprise sales requirements. // Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

Unlocking Healthcare Data: Expert Insights from Jason Bryll of Parable AssociatesIn this episode, host Josh Elledge interviews Jason Bryll, Founder and CEO of Parable Associates, a company helping healthcare organizations harness their data for growth, efficiency, and better patient outcomes. Jason discusses how healthcare's complex data systems—spanning patients, payers, and providers—can be transformed into powerful strategic assets. The conversation explores modern data infrastructure, AI adoption, and how healthcare leaders can turn information into action.Turning Healthcare Data into a Strategic AdvantageJason explains that healthcare organizations deal with some of the most fragmented and regulated data ecosystems of any industry. With multiple payment sources, strict HIPAA compliance, and disconnected systems, many practices struggle to translate data into actionable insights. Through Parable Associates, Jason helps clients design robust, scalable data infrastructures that unify information from EHRs, practice management tools, and claims systems to create real-time visibility into operations.He highlights how modern tools like Microsoft Fabric, Databricks, and Snowflake are transforming how providers process and analyze information. By automating data pipelines, implementing AI-driven analytics, and empowering teams with dashboards, healthcare organizations can reduce claim denials, improve revenue cycles, and accelerate cash flow. Jason emphasizes that true transformation begins with data governance—ensuring clean, accessible, and secure data before layering on advanced analytics.Ultimately, Parable's approach is rooted in measurable ROI. From reducing days sales outstanding (DSO) to uncovering revenue bottlenecks, their systems deliver tangible results. Jason advises healthcare executives to start with a specific business problem—such as cash flow or patient scheduling—and build data strategies around it. “Better reporting is like giving staff a utility belt,” he says. “It equips them to solve problems faster and with more confidence.”About Jason BryllJason Bryll is the Founder and CEO of Parable Associates, where he helps large healthcare organizations transform fragmented data into operational insights. With deep experience in analytics, systems design, and healthcare finance, Jason has worked with providers nationwide to improve data quality, cash flow, and performance through tailored, scalable solutions.About Parable AssociatesParable Associates specializes in healthcare analytics and data engineering, helping medical groups, hospitals, and specialty providers build scalable data ecosystems. The firm designs client-owned systems that unify data across clinical, operational, and financial functions, delivering clear insights and measurable ROI. Learn more at parableassociates.com.Links Mentioned in This EpisodeParable AssociatesConnect with Jason Bryll on LinkedInKey Episode HighlightsWhy healthcare data is uniquely complex and siloedHow to build scalable, secure data infrastructureUsing analytics to improve cash flow and reduce claim delaysPractical applications of AI and modern BI platformsHow Parable Associates delivers measurable ROI through dataActionable advice for healthcare leaders and data teamsConclusionJason Bryll's insights...

When “Normal” Doesn't Work: Rethinking Data and the Role of the SOC AnalystMonzy Merza, Co-Founder and CEO of Crogl, joins Sean Martin and Marco Ciappelli to discuss how cybersecurity teams can finally move beyond the treadmill of normalization, alert fatigue, and brittle playbooks that keep analysts from doing what they signed up to do—find and stop bad actors.Merza draws from his experience across research, security operations, and leadership roles at Splunk, Databricks, and one of the world's largest banks. His message is clear: the industry's long-standing approach of forcing all data into one format before analysis has reached its limit. Organizations are spending millions trying to normalize data that constantly changes, and analysts are paying the price—buried under alerts they can't meaningfully investigate.The conversation highlights the human side of this issue. Analysts often join the field to protect their organizations, but instead find themselves working on repetitive tickets with little context, limited feedback loops, and an impossible expectation to know everything—from email headers to endpoint logs. They are firefighters answering endless 911 calls, most of which turn out to be false alarms.Crogl's approach replaces that normalization-first mindset with an analyst-first model. By operating directly on data where it lives—without requiring migration or schema alignment—it allows every analyst to investigate deeper, faster, and more consistently. Each action taken by one team member becomes shared knowledge for the next, creating an adaptive, AI-driven system that evolves with the organization.For CISOs, this means measurable consistency, auditability, and trust in outcomes. For analysts, it means rediscovering purpose—focusing on meaningful investigations instead of administrative noise.The result is a more capable, connected SOC where AI augments human reasoning rather than replacing it. As Merza puts it, the new normal is no normalization—just real work, done better.Watch the full interview and product demo: https://youtu.be/7C4zOvF9sdkLearn more about CROGL: https://itspm.ag/crogl-103909Note: This story contains promotional content. Learn more.GUESTMonzy Merza, Founder and CEO of CROGL | On LinkedIn: https://www.linkedin.com/in/monzymerza/RESOURCESLearn more and catch more stories from CROGL: https://www.itspmagazine.com/directory/croglBrand Spotlight: The Schema Strikes Back: Killing the Normalization Tax on the SOC: https://brand-stories-podcast.simplecast.com/episodes/the-schema-strikes-back-killing-the-normalization-tax-on-the-soc-a-corgl-spotlight-brand-story-conversation-with-cory-wallace [Video: https://youtu.be/Kx2JEE_tYq0]Are you interested in telling your story?▶︎ Full Length Brand Story: https://www.studioc60.com/content-creation#full▶︎ Spotlight Brand Story: https://www.studioc60.com/content-creation#spotlight Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Informed buyers believe they don't need sellers - and in many cases, they're right. In this episode, Sarah Branfman, Global VP of ISV Sales & GTM at Databricks, explains how buying behavior has fundamentally shifted, why traditional selling fails in complex B2B sales, and what elite sellers must do to create value buyers can't get on their own. Explore more insights: www.globalperformancegroup.com Timestamps: 00:00 – “We don't need a rep anymore.” The hard truth 02:45 – From ballerina to VP: Sarah's nonlinear career path 06:18 – The rise of the informed buyer in complex B2B sales 09:40 – How modern buyers want to buy (and why sellers resist it) 12:52 – Comfort-zone selling and losing deals you could have won 18:10 – Value-based selling, decision-making psychology, and the cost of inaction 20:55 – Ruthless qualification vs. the hope-based pipeline 26:30 – Discovery never ends: re-qualifying through the buying journey 29:02 – Provocative questioning and generating unconsidered needs 33:40 – The 3 traits of elite sellers: drive, curiosity, coachability Modern selling isn't about pressure — it's about enabling informed decision-making through sharper sales discovery, stronger sales enablement, and real business insight. In this episode, Harry Kendlbacher sits down with Sarah, to explore the mindsets and behaviors top sellers use to stay relevant and win in today's complex B2B landscape. You'll learn: – Why buyers feel they don't need sellers – How to win them back with insight-driven conversations – How elite sellers qualify and re-qualify throughout the buying journey – How decision-making psychology and cost of inaction shape urgency Key Takeaways: • Buyers aren't distrustful — they're independent. Sellers must add value beyond what buyers can research or ask AI. • In complex B2B sales, discovery and qualification never end — every new stakeholder resets the process. • The cost of inaction is often a stronger driver of urgency than ROI. • Value-based selling works only when sellers provoke new insights buyers haven't considered. • Elite sellers share three traits: relentless drive, deep curiosity, and coachability. About Guest: Sarah Branfman is the Global VP of ISV Sales & Go-To-Market at Databricks, where she leads strategic partnerships with the world's leading software and data companies. With deep experience in hyper-growth environments like MongoDB and Databricks, Sarah brings a modern, practical perspective on selling to the informed buyer in complex B2B environments. Connect with Sarah on LinkedIn: https://www.linkedin.com/in/sarahbranfman/ If this episode sparked new thinking, share it with your team. Subscribe for weekly insights on modern selling, leadership, and performance. Explore more at www.globalperformancegroup.com

Marc Barnes believes that AI chatbots are evil, and that having a faux conversation with AI chatbots is wrong. Joseph Hobbs, Senior Solution Architect at Databricks, disagrees. In this podcast, they discuss the nature of conversation, how AI imitates conversation, and the Catholic response to AI Chatbots.

Soham Mazumdar, CEO and Co-Founder of WisdomAI, discusses how organizations can break free from the "drowning in data but starving for insights" paradox that plagues modern enterprises. We explore his journey from Google's TeraGoogle project to co-founding and scaling Rubrik through its $5.6 billion IPO, and why he left that success to build an agentic AI approach to Business Intelligence (BI) that transforms how businesses extract value from their data investments.SHOW: 971SHOW TRANSCRIPT: The Cloudcast #963 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" SPONSORS:[Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcastSHOW NOTES:WisdomAI websiteTopic 1 - Welcome to the show, Soham. We overlapped briefly at Rubrik. Give everyone a quick introduction and tell everyone a bit about your time at Google prior to RubrikTopic 2 - You helped scale Rubrik from inception to a $5.6 billion IPO in 2024. What was the "aha moment" that made you leave that success to tackle the enterprise data analytics problem with WisdomAI?Topic 3 - Let's define the core problem. Organizations invest heavily in modern data platforms - Snowflake, Databricks, etc. - but there is the term "drowning in data but starving for insights." What's broken in the traditional BI stack that prevents business users from getting answers?Topic 4 - How do agentic AI and BI fit together? WisdomAI introduces the concept of "Knowledge Fabric" and agentic data insights. Break this down for us - how does this fundamentally differ from traditional dashboards and BI tools?Topic 5 - One of the biggest challenges with GenAI in enterprise settings is hallucination. You've emphasized that WisdomAI separates GenAI from answer generation. How does your approach tackle this critical trust issue?Topic 6 - Let's talk about data integration complexity. Your platform works with both structured and unstructured data - Snowflake, BigQuery, Redshift, but also Excel, PDFs, PowerPoints. How do you handle this "dirty" data reality that most enterprises face?Topic 6a - With so much data, how do most organizations get started? What's a typical use case for adoption?Topic 7 - If anyone is interested, what's the best way to get started?FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

Dhanji R. Prasanna is the chief technology officer at Block (formerly Square), where he's managed more than 4,000 engineers over the past two years. Under his leadership, Block has become one of the most AI-native large companies in the world. Before becoming CTO, Dhanji wrote an “AI manifesto” to CEO Jack Dorsey that sparked a company-wide transformation (and his promotion to CTO).We discuss:1. How Block's internal open-source agent, called Goose, is saving employees 8 to 10 hours weekly2. How the company measures AI productivity gains across technical and non-technical teams3. Which teams are benefiting most from AI (it's not engineering)4. The boring organizational change that boosted productivity even more than AI tools5. Why code quality has almost nothing to do with product success6. How to drive AI adoption throughout an organization (hint: leadership needs to use the tools daily)7. Lessons from building Google Wave, Google+, and other failed products—Brought to you by:Sinch—Build messaging, email, and calling into your product: https://sinch.com/lennyFigma Make—A prompt-to-code tool for making ideas real: https://www.figma.com/lenny/Persona—A global leader in digital identity verification: https://withpersona.com/lenny—Where to find Dhanji R. Prasanna:• LinkedIn: https://www.linkedin.com/in/dhanji/—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 to Dhanji(05:26) The AI manifesto: convincing Jack Dorsey(07:33) Transforming into a more AI-native company(12:05) How engineering teams work differently today(15:24) Goose: Block's open-source AI agent(20:18) Measuring AI productivity gains across teams(21:38) What Goose is and how it works(32:15) The future of AI in engineering and productivity(37:42) The importance of human taste(40:10) Building vs. buying software(44:08) How AI is changing hiring and team structure(53:45) The importance of using AI tools yourself before deploying them(55:13) How Goose helped solve a personal problem with receipts(58:01) What makes Goose unique(59:57) What Dhanji wishes he knew before becoming CTO(01:01:49) Counterintuitive lessons in product development(01:04:56) Why controlled chaos can be good for engineering teams(01:08:07) Core leadership lessons(01:13:36) Failure corner(01:15:50) Lightning round and final thoughts—Referenced:• Jack Dorsey on X: https://x.com/jack• Block: https://block.xyz/• Square: https://squareup.com/• Cash App: https://cash.app/• What is Conway's Law?: https://www.microsoft.com/en-us/microsoft-365-life-hacks/organization/what-is-conways-law#• Goose: https://github.com/block/goose• Gosling: https://github.com/block/goose-mobile• Salesforce: https://www.salesforce.com/• Snowflake: https://www.snowflake.com/• Claude: https://claude.ai/• Anthropic co-founder on quitting OpenAI, AGI predictions, $100M talent wars, 20% unemployment, and the nightmare scenarios keeping him up at night | Ben Mann: https://www.lennysnewsletter.com/p/anthropic-co-founder-benjamin-mann• OpenAI: https://openai.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• Llama: https://www.llama.com/• Cursor: https://cursor.com/• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• Top Gun: https://www.imdb.com/title/tt0092099/• Lenny's vibe-coded Lovable app: https://gdoc-images-grab.lovable.app/• Afterpay: https://github.com/afterpay• Bitkey: https://bitkey.world/• Proto: https://github.com/proto-at-block• Brad Axen on LinkedIn: https://www.linkedin.com/in/bradleyaxen/• Databricks: https://www.databricks.com/• Carl Sagan's quote: https://www.goodreads.com/quotes/32952-if-you-wish-to-make-an-apple-pie-from-scratch• Google Wave: https://en.wikipedia.org/wiki/Google_Wave• Google Video: https://en.wikipedia.org/wiki/Google_Video• Secret: https://en.wikipedia.org/wiki/Secret_(app)• Alien Earth on FX: https://www.fxnetworks.com/shows/alien-earth• Slow Horses on AppleTV+: https://tv.apple.com/us/show/slow-horses/umc.cmc.2szz3fdt71tl1ulnbp8utgq5o• Fargo TV series on Prime Video: https://www.amazon.com/Fargo-Season-1/dp/B09QGRGH6M• Steam Deck OLED display: https://www.steamdeck.com/en/oled• Doc Brown: https://backtothefuture.fandom.com/wiki/Emmett_Brown—Recommended books:• The Master and Margarita: https://www.amazon.com/Master-Margarita-Mikhail-Bulgakov/dp/0802130119• Tennyson Poems: https://www.amazon.com/Tennyson-Poems-Everymans-Library-Pocket/dp/1400041872/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.My biggest takeaways from this conversation: To hear more, visit www.lennysnewsletter.com

In this episode of Real Talk with Anant Veeravalli, the discussion revolves around the evolving data landscape and the necessity for strategic partnerships to achieve holistic measurement. The team unpacks the importance of ethical data sourcing, privacy compliance, and the utilization of clean room environments like Snowflake and Databricks to bridge data gaps. Enabling secure and scalable data connectivity and facilitating real-time data sharing is key for brands to derive meaningful intelligence, including predictive modeling and AI-driven insights. This episode is essential listening for anyone focused on governance, security, and future-proofing data systems.Thanks for listening! Follow us on Twitter and Instagram or find us on Facebook.

Disciplined, purpose-driven innovation, anchored in governance, data, and the human experience, beats shiny-object hype.In this mega-episode, Lisa Fry, Chief Strategy & Innovation Officer at SCP Health, discusses “purposeful innovation” that reduces clinician burden and elevates patient experience: ED-volume prediction to align coverage, early pilots of ambient scribing, and patient-preferred models like hospital-at-home. She explains the guardrails, an enterprise architecture review board, commitments to core platforms, and stage-gated pilots with predefined success metrics, to avoid the “tyranny of the urgent” and scale only what works. Nancye Feistritzer, DNP, RN—VP, Center for Care Delivery & Innovation at Emory Healthcare, talks about how bold initiatives, including the Apple hospital work and implementing Epic on Apple devices, succeed only when they explicitly align with an organization's strategy, mission, and values. Nick Yaitsky, Board Member for TAG Digital Health, urges outcome-first AI roadmaps: accept that healthcare data is imperfect, mitigate bias by fine-tuning models to local populations and even individual patients, and build trust in the same way we came to trust GPS, through consistent, measurable results and governance. Olga Ryzhikova, Founding Partner at Kepler Team, tackles adoption by starting integration where clinicians work (SMART on FHIR/SSO), designing modern user experiences, and favoring ambient, low-click workflows so tools remain in use. Ron Strachan, Global Healthcare CIO Advisor, addresses rural access, noting that resilient, low-bandwidth virtual care and platform economies can “meet patients where they are.” His own brain-tumor journey underscores how imaging precision and reliable infrastructure can change outcomes. Finally, Wes Whitaker, AVP of Growth Strategy & Data Analytics, shows population health at scale: unifying EHR, eligibility, claims, and ADT into a modern cloud/Databricks stack, then applying predictive models to anticipate ER visits, target outreach, drive attribution, and prove ROI, while tightening security with role-based access. Together, their message is clear: govern hard, integrate early, pilot fast, measure relentlessly, and scale empathetically. Tune in and learn how to innovate with rigor, scale with empathy, and deliver measurable value!ResourcesConnect with Lisa Fry on LinkedIn here.Follow SCP Health on LinkedIn here and visit their website here.Follow and connect with Nancye Feistritzer on LinkedIn.Learn more about Emory Healthcare on LinkedIn and their website.Connect with and follow Nick Yaitsky on LinkedIn.Discover more about the TAG Digital Health Society on LinkedIn and explore their website.Follow and connect with Olga Ryzhikova on LinkedIn.Learn more about the Kepler Team on their LinkedIn and explore their website.Connect with Ron Strachan on LinkedIn here.Explore Zoom's website and learn more about them on their LinkedIn.Follow and connect with Wes Whitaker on LinkedIn.Discover more about Premise Health on their LinkedIn and visit their website.

Monzy Merza (@monzymerza, CEO/Founder @Crogl) talks about build a next-generation Enterprise SOC by leveraging AI to stay ahead of Cybersecurity threats.SHOW: 969SHOW TRANSCRIPT: The Cloudcast #969 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwNEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS" SPONSORS:[Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcastSHOW NOTES:Crogl websiteTechCrunch articleForbes ArticleIntellyx ArticleLast WatchDog ArticleTopic 1 - Welcome to the show, Monzy. Give everyone a brief introduction and tell us about your unique journey from government research to Splunk to Databricks to founding Crogl.Topic 2 - Let's start with the current state of cybersecurity and AI. We're seeing headlines about AI being the top cybersecurity concern for 2025, even overtaking ransomware. From your perspective, what's driving this shift and why should organizations be paying attention to the intersection of cybersecurity and AI?Topic 3 - You've described Crogl as an "Iron Man suit" for security analysts. That's a compelling metaphor. Can you break down what you mean by that and how your approach differs from the traditional "reduce alerts" mentality that most vendors have been pushing?Topic 4 - Let's talk about your "knowledge engine" and what you call an “AI for the Enterprise SOC”. You're using compound AI systems with LLMs, smaller models, and knowledge graphs. This sounds quite different from vendors who are just "bolting on" LLMs to existing tools. Walk us through this architectural decision and why it matters.Topic 5 - The cybersecurity industry is experiencing massive alert fatigue - 4,500 alerts per day, with analysts only able to investigate 8-25 of them. Your philosophy is "every alert should be analyzed" rather than filtering them out. That seems counterintuitive to what the market has been doing. How does your autonomous investigation approach actually work in practice?Topic 6 - Where do you see this evolution heading, and what are the implications for SOC teams and security practitioners? Are we heading toward fully autonomous SOCs?FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodI

Gorkem Yurtseven is the co-founder and CEO of fal, the generative media platform powering the next wave of image, video, and audio applications. In less than two years, fal has scaled from $2M to over $100M in ARR, serving over 2 million developers and more than 300 enterprises, including Adobe, Canva, and Shopify. In this conversation, Gorkem shares the inside story of fal's pivot into explosive growth, the technical and cultural philosophies driving its success, and his predictions for the future of AI-generated media. In today's episode, we discuss: How fal pivoted from data infrastructure to generative inference fal's explosive year and how they scaled Why "generative media" is a greenfield new market fal's unique hiring philosophy and lean

In this episode we are discussing the groundbreaking partnership between SAP Business Data Cloud and SAP Databricks. We discuss how SAP BTP is driving AI-first enterprise transformation through seamless SAP Datasphere integration, zero-copy data sharing, and advanced AI/ML workflows. Also, how Business Data Fabric and SAP Business AI are enabling future-ready enterprise IT, making it easier than ever to turn enterprise data into real business value. From hands-on use cases like cash flow forecasting, margin analysis, and attrition analysis to practical tips for engineers and data scientists, you'll get a front-row seat to digital transformation outcomes that matter.

In this episode we are discussing the groundbreaking partnership between SAP Business Data Cloud and SAP Databricks. We discuss how SAP BTP is driving AI-first enterprise transformation through seamless SAP Datasphere integration, zero-copy data sharing, and advanced AI/ML workflows. Also, hear how Business Data Fabric and SAP Business AI are enabling future-ready enterprise IT, making it easier than ever to turn enterprise data into real business value. From hands-on use cases like cash flow forecasting, margin analysis, and attrition analysis to practical tips for engineers and data scientists, you'll get a front-row seat to digital transformation outcomes that matter.

Reed Smith's Jason Garcia, Gerard Donovan, and Tyler Thompson are joined by Databricks' Suchismita Pahi and Christina Farhat for a spirited discussion exploring one of the most urgent debates of our era: Should AI be regulated now, or are we moving too fast? Settle in and listen to a dynamic conversation that delves into the complex relationship between innovation and regulation in the world of artificial intelligence.

Ben Horowitz founded Loudcloud in the middle of the dot-com bust and sold it for $1.6 billion, then led Andreessen Horowitz from its founding to $46 billion in committed capital. Ali Ghodsi co-founded Databricks, stepped in as CEO during a crisis, and led it to a valuation of over $100 billion.In this episode of “Boss Talk”, Ben and Ali join a16z General Partners Sarah Wang and Erik Torenberg to share founder war stories, how to hire and make deals, how to keep culture intense without burning employees out, and why founders should raise their ambitions even higher. ResourcesFollow Ali on X: https://x.com/alighodsiLearn more about Databricks: https://www.databricks.com/Follow Ben on X: https://x.com/bhorowitzFollow Sarah on X: https://x.com/sarahdingwangFollow Erik on X: https://x.com/eriktorenberg Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Resources:Find a16z on X: https://x.com/a16zSubscribe to a16z on Substack: https://a16z.substack.com/Find a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenberg Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast 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.

Chris Degnan is the former Chief Revenue Officer at Snowflake, where he was instrumental in scaling the company from less than $1M in ARR to over $3B in annual revenue. He joined as the first sales hires and built Snowflake's go-to-market engine from scratch, growing the team from to more than 6,000 globally. Under his leadership, Snowflake became one of the fastest-growing enterprise software companies in history, achieving a record-breaking IPO in 2020. AGENDA: 04:34 How to Build a Sales Team from Scratch 07:49 How to Hire and Evaluate Sales Leaders 15:23 Four Big Lessons Scaling Snowflake to $3BN ARR 31:30 Comparing Snowflake and Databricks: What Databricks Did Better? 35:26 How to Manage Sales Team Morale in Competitive Markets 43:53 Why Customer Success is BS and What To Do With It 48:31 How Every Sales Leader Needs to Change in An AI World 49:37 Biggest Reflections on Sales Leadership 54:38 Quick Fire Questions and Final Thoughts   20Sales: Scaling Snowflake from $0-$3BN in ARR | Snowflake vs Databricks: My Biggest Lessons | Why Customer Success is BS and What Replaces It with Chris Chris Degnan

Mal Vivek, founder and CEO of Zeb, discusses the rapid growth of her firm, which has become a leader in digital and AI transformation. Zeb has established itself as one of the fastest-growing AWS Premier Tier and Databricks partners, primarily by addressing the challenges small and medium businesses face in implementing AI solutions. Vivek emphasizes the importance of understanding each client's unique business model and tailoring AI solutions to meet their specific needs, rather than offering a one-size-fits-all approach.Vivek highlights the significant shift in lead generation strategies among their clients, who are increasingly utilizing AI to create more targeted and high-quality leads. This change reflects a broader trend where businesses are moving away from traditional lead lists and instead developing custom AI systems that align with their ideal customer profiles. Additionally, she notes the importance of training and upskilling employees through AI, enabling them to access vast amounts of knowledge quickly and efficiently.The conversation also touches on the concept of an "AI-first strategy," which varies in definition across different organizations. For Zeb, this strategy involves identifying repetitive tasks that can be enhanced through AI while ensuring that the human touch remains integral to the customer experience. Vivek stresses the need for restraint in digital transformation, arguing that not every process should be automated, especially when personal interaction is a key component of a business's success.Finally, Vivek discusses the evolving business models driven by AI, including a shift towards value-based pricing. She explains how Zeb structures its pricing around measurable outcomes and mutual agreements on success metrics, ensuring that both the firm and its clients benefit from the results achieved. This approach not only fosters accountability but also aligns the interests of Zeb with those of its customers, ultimately driving better business outcomes. All our Sponsors: https://businessof.tech/sponsors/ Do you want the show on your podcast app or the written versions of the stories? Subscribe to the Business of Tech: https://www.businessof.tech/subscribe/Looking for a link from the stories? The entire script of the show, with links to articles, are posted in each story on https://www.businessof.tech/ Support the show on Patreon: https://patreon.com/mspradio/ Want to be a guest on Business of Tech: Daily 10-Minute IT Services Insights? Send Dave Sobel a message on PodMatch, here: https://www.podmatch.com/hostdetailpreview/businessoftech Want our stuff? Cool Merch? Wear “Why Do We Care?” - Visit https://mspradio.myspreadshop.com Follow us on:LinkedIn: https://www.linkedin.com/company/28908079/YouTube: https://youtube.com/mspradio/Facebook: https://www.facebook.com/mspradionews/Instagram: https://www.instagram.com/mspradio/TikTok: https://www.tiktok.com/@businessoftechBluesky: https://bsky.app/profile/businessof.tech Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Send us a textThe enterprise software ecosystem continues to evolve rapidly as vendors double down on AI, automation, and data-driven orchestration across business functions. Nintex unveiled new generative AI capabilities to enhance business automation, while Circana introduced its Liquid Supply Chain solution to drive agility and responsiveness in complex networks. CloudBolt extended its optimization capabilities to Kubernetes through the acquisition of StormForge, signaling a stronger focus on cloud efficiency. Kinaxis partnered with Databricks to accelerate AI-powered supply chain orchestration and also announced a collaboration with Infor, further expanding its ecosystem reach. Rootstock's Spring '25 release reimagined the modern ERP experience for manufacturers, and Tempo launched a Strategic Portfolio Management platform to strengthen business alignment. Meanwhile, Tricentis rolled out new testing innovations in its spring update, Velixo secured Series A funding from Elephant to fuel growth, and FloQast introduced auditable AI agents to help finance teams bridge the growing talent gap—illustrating how innovation is reshaping every layer of the enterprise stack.In today's episode, we invited a panel of industry analysts for a live discussion on LinkedIn to analyze current enterprise software stories. We covered many grounds including the direction and roadmaps of each enterprise software vendors. Finally, we analyzed future trends and how they might shape the enterprise software industry.Background Soundtrack: Away From You – Mauro SommFor more information on growth strategies for SMBs using ERP and digital transformation, visit our community at wbs. rocks or elevatiq.com. To ensure that you never miss an episode of the WBS podcast, subscribe on your favorite podcasting platform. 

Join Accenture's Chief AI Officer Lan Guan and Naveen Rao, Former VP of AI at Databricks, for an open and engaging conversation about the realities of scaling AI within large organizations. Hear about Databricks journey from pioneering the first AI chip company to shaping AI strategy and discover the technical hurdles and organizational complexities involved in deploying AI at scale.

Plus: OpenAI and Databricks strike a $100 million deal to sell AI agents. U.S. senators send letters to big tech companies demanding information on H-1B visa usage. Nvidia-backed AI startup Nscale raises $1.1 billion for data-center rollout. Zoe Kuhlkin hosts. Learn more about your ad choices. Visit megaphone.fm/adchoices

In this conversation from Lenny's Podcast, Ben Horowitz joins Lenny to discuss the psychological muscle every founder needs, why hesitation can be fatal for CEOs, when it's time to replace a founder, and how to normalize failure while building confidence. They also explore the Databricks founding story, investing in Adam Neumann after WeWork, whether AI is in a bubble, where the real opportunities lie, and Ben's work with the Paid in Full Foundation supporting hip-hop pioneers. The result is a candid look at leadership, product management, and what it takes to build enduring companies. Timecodes: 00:00 Introduction 00:22 The Psychology of Leadership & Decision-Making02:41 Leadership lessons from Shaka Senghor07.56 Struggle, Pain, and Growth as a CEO 10:15 Running toward fear and why hesitation kills companies19:35 Who shouldn't start a company22:36 The Databricks story: thinking bigger24:54 Managerial leverage and CEO psychology28:06 When founders should be replaced as CEOs31:20 Normalizing failure for CEOs37:57 Counterintuitive lessons about building companies42:31 “Good Product Manager/Bad Product Manager”48:21 Product managers as leaders51:16 Why a16z invested in Adam Neumann after WeWork56:23 Is AI in a bubble?01:02:43 The biggest opportunities in AI01:12:51 Why U.S. leadership in AI matters01:18:53 The Paid in Full Foundation for hip-hop pioneers01:23:18 Lightning round: book recommendations, products, and life mottos Resources: Find Ben on X: https://x.com/bhorowitzFind Ben on LinkedIn: https://www.linkedin.com/in/behorowitz/Watch more of Lenny's Podcast: https://www.youtube.com/@LennysPodcastCheck out Lenny's newsletter here: https://www.lennysnewsletter.com Stay Updated: Find a16z on X: https://x.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX?si=3E8B3qT9TyiwAHJ7JnaKbgListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://twitter.com/eriktorenbergPlease 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.

Ben Horowitz is the co-founder of Andreessen Horowitz, Silicon Valley's largest and most influential venture capital firm, with over $46B in committed capital across multiple funds. He took Loudcloud public with just $2 million in revenue (dubbed “the IPO from hell”), sold it for $1.6 billion, and has backed companies from Facebook to Stripe to Airbnb to OpenAI to Databricks (now worth more than $100 billion). His management philosophy—forged through near-death experiences and refined through coaching hundreds of CEOs—contradicts most conventional startup wisdom.In our conversation, Ben shares:1. Why “founder mode” is half right and half dangerously wrong2. The story behind “Good Product Manager/Bad Product Manager” and why it went viral despite being written in anger3. Where the biggest AI startup opportunities remain4. Why you need to run toward fear, never away5. The one trait that predicts that a founder will fail as CEO6. Inside Paid in Full, Ben's nonprofit awarding pensions to pioneering hip-hop artists—Brought to you by:DX—The developer intelligence platform designed by leading researchers: http://getdx.com/lennyBasecamp—The famously straightforward project management system from 37signals: https://www.basecamp.com/lennyMiro—A collaborative visual platform where your best work comes to life: https://miro.com/lenny—Transcript: https://www.lennysnewsletter.com/p/46b-of-hard-truths-from-ben-horowitz—My biggest takeaways (for paid newsletter subscribers): ⁠https://www.lennysnewsletter.com/i/172439345/my-biggest-takeaways-from-this-conversation—Where to find Ben Horowitz:• X: https://x.com/bhorowitz• LinkedIn: https://www.linkedin.com/in/behorowitz/• Website: https://benhorowitz.com/• Andreessen Horowitz's website: https://a16z.com/—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 to Ben Horowitz(04:09) Important leadership lessons from Shaka Senghor(10:15) Running toward fear and why hesitation kills companies(19:35) Who shouldn't start a company(22:36) The Databricks story: thinking bigger(24:54) Managerial leverage and CEO psychology(28:06) When founders should be replaced as CEOs(31:20) Normalizing failure for CEOs(37:57) Counterintuitive lessons about building companies(42:31) “Good Product Manager/Bad Product Manager”(48:21) Product managers as leaders(51:16) Why a16z invested in Adam Neumann after WeWork(56:23) Is AI in a bubble?(01:02:43) The biggest opportunities in AI(01:12:51) Why U.S. leadership in AI matters(01:18:53) The Paid in Full Foundation for hip-hop pioneers(01:23:18) Lightning round: book recommendations, products, and life mottos—References: https://www.lennysnewsletter.com/p/46b-of-hard-truths-from-ben-horowitz—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