Podcasts about Databricks

Meet Venkata Ramana Reddy Bussu—a Senior Cloud Solutions Engineer & SAP Architect whose fingerprints are on some of the world's most complex enterprise transformations ☁️

How are product leaders building game-changing platforms in the age of AI? In this episode of the CPO Rising Series hosted by Products That Count Resident CPO Renee Niemi, Databricks Senior Vice President of Product Management David Meyer will be speaking on building transformative product strategies in the data and AI landscape. Meyer shares insider insights from Databricks' journey, revealing how product leaders can create innovative platforms that reshape entire industries while staying true to a long-term vision.

In the latest episode ofThe New Stack Agents, Naveen Rao, VP of AI at Databricks and a former neuroscientist, reflects on the evolution of AI, neural networks, and the energy constraints that define both biological and artificial intelligence. Rao, who once built circuit systems as a child and later studied the brain's 20-watt efficiency at Duke and Brown, argues that current AI development—relying on massive energy-intensive data centers—is unsustainable. He believes true intelligence should emerge from low-power, efficient systems, more aligned with biological computing.Rao warns that the industry is headed toward “model collapse,” where large language models (LLMs) begin training on AI-generated content instead of real-world data, leading to compounding inaccuracies and hallucinations. He stresses the importance of grounding AI in reality and moving beyond brute-force scaling. Rao sees intelligence not just as a function of computing power, but as a distributed, observational system—“life is a learning machine,” he says—hinting at a need to fundamentally rethink how we build AI.Learn more from The New Stack about the latest insights about the evolution of AI and neural networks: The 50-Year Story of the Rise, Fall, and Rebirth of Neural NetworksThe Evolution of the AI Stack: From Foundation to AgentsJoin our community of newsletter subscribers to stay on top of the news and at the top of your game. 

What if AI made switching platforms effortless—and what would that mean for SaaS? This week on Topline, Sam Jacobs, Asad Zaman, and AJ Bruno unpack the latest headlines around Databricks, Snowflake, and Ramp to explore whether AI is truly shifting the foundations of enterprise software. They debate the reality behind “vibe coding,” question whether AI is actually boosting productivity (or just slowing us down), and discuss why so much of today's AGI conversation feels overhyped. Plus: the rise of nano agents, the illusion of developer efficiency, and what jobs might look like in 2030.   Thanks for tuning in! New episodes of Topline drop every Sunday and Thursday.   Don't miss GTM2025 — the only B2B tech conference exclusively for GTM executives. Elevate your 2026 strategy and join us from September 23 to 25 in Washington, D.C. Use code TOPLINE for 10% off your GA ticket.   Stay ahead with the latest industry developments and emerging go-to-market trends with Topline Newsletter by Asad Zaman. Subscribe today.   Tune in to The Revenue Leadership Podcast every Wednesday, where host Kyle Norton talks with real revenue operators and dives deep into what it takes to succeed as a modern revenue leader.   You're invited! Join the free Topline Slack channel to connect with 600+ revenue leaders, share insights, and keep the conversation going beyond the podcast!   This episode is sponsored by UserEvidence. Want to know what actually moves the needle on trust? Download The Evidence Gap, a data-backed report on the customer proof that drives real results. Get it now at userevidence.com/evidence.   Key Chapters: (00:00) - Welcome and Introductions  (02:00) - The Retreat Recap and Business Decisions  (04:30) - The Vanishing Switching Costs in SaaS and Cloud  (07:00) - Skepticism Around Kubernetes and Cloud Portability  (09:00) - Middle Market and SMB: Where AI-Enabled Switching Gains Traction  (12:00) - The Paradox of Switching Costs and Enterprise Inertia  (15:00) - The Ramp Phenomenon: Outpacing Incumbents with AI-Driven Finance  (18:00) - Future of Finance Teams: Human + AI Agents Collaboration  (22:00) - The Challenge of AI Hallucinations and Model Reliability  (26:00) - The Reality Check: AI Tools Slowing Developers Down  (29:30) - The Evolving Role of QA: More Fun or More Tedious?  (34:30) - Vibe Coding: Promise, Reality, and Use Case Limitations  (38:30) - Centralized AI Agents vs. Specialized Nano Agents  (42:30) - Envisioning 2030 Businesses: AI's True Impact Unfolds  (45:30) - Defining General and Super Intelligence: Myth vs. Reality  (50:30) - The AI Singularity and Moral Frameworks: Can Machines Learn Ethics?  (54:30) - The Grains of Sand, Rubik's Cube Permutations, and AI Complexity  (57:30) - Lighthearted Hot Takes: WNBA Enjoyment & Infinity Skepticism  (59:00) - Shoutouts to Masterminds, Meals, and Podcasts  (01:02:30) - Parting Thoughts on AI Adoption and CTAs for Listeners

In today's episode of Tech Talks Daily, I sat down with Andy Bell, Head of Data Product Management at Precisely, to explore a challenge that many organizations continue to underestimate: the role of data integrity in AI strategies. With only 12 percent of businesses expressing confidence in the quality of their AI data, it's clear that the rush to implement AI is often outpacing the readiness of the data that supports it. Andy and I unpack what happens when enterprises leap into generative or agentic AI without addressing foundational data issues. From hallucinations to bias to unreliable outputs, the risks are significant. As we discussed, these risks don't just impact models — they erode trust with customers and complicate accountability, especially in regulated industries where traceability is non-negotiable. We then explored the power of third-party data enrichment and how it can offer much-needed context that internal datasets often lack. Andy shared real-world examples, including how a major delivery company saved 65 million dollars by optimizing address accuracy and how San Bernardino County used Precisely's wildfire risk models to improve emergency planning. These aren't abstract use cases — they show measurable business value. Andy also introduced the Precisely Data Link program, a solution designed to make it easier to connect, manage, and query multiple third-party datasets. With persistent IDs and flexible delivery methods through APIs, managed services, and platforms like Snowflake and Databricks, Precisely is helping organizations speed up time to value while reducing integration headaches. Looking ahead, Andy shared how Precisely is building AI capabilities that allow users to query third-party data using natural language. This shift aims to make complex data interactions more intuitive and accessible to business users who may not be data engineers. If data is the fuel for AI, then the quality and context of that data will define the road ahead. Is your organization doing enough to ensure its data can be trusted by the AI it deploys?

Daliana's newsletter on how to find your edge in the AI age and live events: https://dalianaliu.kit.com/e0dcfc214bDaliana interviewed her friend of 10 years, Mike Lo, on how he went from a physics PhD to Sales Engineer at Databricks, and fun stories of their friendship in LA.Mike Lo's Linkedin: https://www.linkedin.com/in/hellomikelo/

Ron Gabrisko is the Chief Revenue Officer at Databricks, where he joined in 2016. Under his leadership, Databricks has scaled from $0 to over $4BN in annual revenue. He has grown the sales team from 0 to over 1,000 globally, leading expansion into enterprise, government, and international markets. Ron previously held senior sales roles at Cloudera and IBM, bringing deep experience in data and AI infrastructure. His tenure at Databricks has been defined by hypergrowth, multi-product adoption, and world-class GTM execution. Agenda for Today: 00:04 – The Databricks Origin Story: Ali, Ben Horowitz & 7 PhDs 00:08 – Ali vs JPMorgan: Turning Down $10M to Stay Cloud-First 00:13 – Prospecting Day: How Ron Scaled the GTM Culture 00:16 – Why Databricks' Pricing Model Was Its Secret Weapon 00:19 – Enterprise vs SMB: The Risky Bet That Paid Off 00:23 – From $2M to $13M ARR: How Ron Built the First Sales Engine 00:29 – Can AI Replace Salespeople? Ron's Brutally Honest Take 00:36 – How to Get Your First Million-Dollar Rep (and Keep Them) 00:42 – The Culture Secret Behind Scaling to 5,000 Sales Reps 00:45 – Why Databricks Waited Until $500M ARR to Go International 00:52 – What Makes a Great Sales Meeting? Ron's Gold Standard 00:58 – The Snowflake Wars: Why Ron Says Databricks Is 5 Years Ahead  

Bret Taylor's legendary career includes being CTO of Meta, co-CEO of Salesforce, chairman of the board at OpenAI (yes, during that drama), co-creating both Google Maps and the Like button, and founding three companies. Today he's the founder and CEO of Sierra, an AI agent company transforming customer service. He's one of the few people I've met who's been wildly successful at every level—from engineer to C-suite executive to founder—and across almost every discipline, including PM, engineer, CTO, COO, CPO, CEO, and board member.In this conversation, you'll learn:1. The brutal product review that nearly ended his Google career—and how that failure led to creating Google Maps2. The question Sheryl Sandberg taught him to ask every morning (“What's the most impactful thing I can do today?”) that transformed how he approached every role3. The three AI market segments that matter4. Why AI agents will replace SaaS products5. His framework for knowing whose advice to actually listen to—and how that came in handy during the OpenAI board drama6. The counterintuitive go-to-market strategy most AI startups get wrong7. Sierra's outcome-based pricing model that's transforming how enterprise software is sold (and why every SaaS company should adopt it)8. What he's teaching his kids about AI that every parent should know—Brought to you by:CodeRabbit—Cut code review time and bugs in half. Instantly: https://coderabbit.link/lennyBasecamp—The famously straightforward project management system from 37signals: https://www.basecamp.com/lennyVanta—Automate compliance. Simplify security: https://vanta.com/lenny—Where to find Bret Taylor:• X: https://x.com/btaylor• LinkedIn: https://www.linkedin.com/in/brettaylor/—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 Bret Taylor(04:10) Bret's early career and first major mistake(08:24) The birth of Google Maps(11:57) Lessons from FriendFeed and the importance of honest feedback(31:30) The future of coding and AI's role(45:26) Preparing the next generation for an AI-driven world(48:46) AI in education(52:05) Business strategies in the AI market(01:04:38) Outcome-based pricing in AI(01:09:15) Productivity gains and AI(01:17:35) Go-to-market strategies for AI products(01:21:49) Lightning round and final thoughts—Referenced:• Marissa Mayer on LinkedIn: https://www.linkedin.com/in/marissamayer/• “Lazy Sunday”—SNL: https://www.youtube.com/watch?v=sRhTeaa_B98• Quip: https://quip.com/• Sierra: https://sierra.ai/• FriendFeed: https://en.wikipedia.org/wiki/FriendFeed• Sheryl Sandberg on LinkedIn: https://www.linkedin.com/in/sheryl-sandberg-5126652/• Jim Norris on LinkedIn: https://www.linkedin.com/in/halfspin/• Paul Buchheit on X: https://x.com/paultoo• Sanjeev Singh on LinkedIn: https://www.linkedin.com/in/sanjeev-singh-20a1b72/• Barack Obama: https://www.obamalibrary.gov/obamas/president-barack-obama• Oprah Winfrey: https://en.wikipedia.org/wiki/Oprah_Winfrey• Ashton Kutcher: https://en.wikipedia.org/wiki/Ashton_Kutcher• PayPal Mafia: https://en.wikipedia.org/wiki/PayPal_Mafia• Sam Altman on X: https://x.com/sama• Warren Buffett on X: https://x.com/warrenbuffett• Unix: https://en.wikipedia.org/wiki/Unix• Fortran: https://en.wikipedia.org/wiki/Fortran• C: https://en.wikipedia.org/wiki/C_(programming_language)• Python: https://www.python.org/• Perl: https://www.perl.org/• Rust: https://www.rust-lang.org/• Eleven Labs: https://elevenlabs.io/• The exact AI playbook (using MCPs, custom GPTs, Granola) that saved ElevenLabs $100k+ and helps them ship daily | Luke Harries (Head of Growth): https://www.lennysnewsletter.com/p/the-ai-marketing-stack• Confluent: https://www.confluent.io/• Databricks: https://www.databricks.com/• Snowflake: https://www.snowflake.com• Harvey: https://www.harvey.ai/• Behind the founder: Marc Benioff: https://www.lennysnewsletter.com/p/behind-the-founder-marc-benioff• Larry Summers's website: https://larrysummers.com/• AutoCAD: https://www.autodesk.com/products/autocad/overview• Revit: https://www.autodesk.com/products/revit/• The art and science of pricing | Madhavan Ramanujam (Monetizing Innovation, Simon-Kucher): https://www.amazon.com/Monetizing-Innovation-Companies-Design-Product/dp/1119240867• Pricing your AI product: Lessons from 400+ companies and 50 unicorns | Madhavan Ramanujam: https://lenny.substack.com/p/pricing-and-scaling-your-ai-product-madhavan-ramanujam• Cursor: https://cursor.com/• CodeX: https://openai.com/codex/• Claude Code: https://www.anthropic.com/claude-code• 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• DirecTV: https://www.directv.com/• SiriusXM: https://www.siriusxm.com/• Wayfair: https://www.wayfair.com/• Akai: https://www.akaipro.com/• Chubbies Shorts: https://www.chubbiesshorts.com/• Weight Watchers: https://www.weightwatchers.com/• CLEAR: https://www.clearme.com/• Stripe: https://stripe.com/• Building product at Stripe: craft, metrics, and customer obsession | Jeff Weinstein (Product lead): https://www.lennysnewsletter.com/p/building-product-at-stripe-jeff-weinstein• Twilio: https://www.twilio.com/• ServiceNow: https://www.servicenow.com/• Adobe: https://www.adobe.com/• Jobs to be done: https://jobs-to-be-done.com/jobs-to-be-done-a-framework-for-customer-needs-c883cbf61c90• The ultimate guide to JTBD | Bob Moesta (co-creator of the framework): https://www.lennysnewsletter.com/p/the-ultimate-guide-to-jtbd-bob-moesta• Inception: https://www.imdb.com/title/tt1375666/• Alan Kay's quote: https://www.brainyquote.com/quotes/alan_kay_100831• Jobs at Sierra: https://sierra.ai/careers—Recommended books:• Monetizing Innovation: How Smart Companies Design the Product Around the Price: https://www.amazon.com/Monetizing-Innovation-Companies-Design-Product/dp/1119240867• Competing Against Luck: The Story of Innovation and Customer Choice: https://www.amazon.com/Competing-Against-Luck-Innovation-Customer/dp/0062435612• Endurance: Shackleton's Incredible Voyage: https://www.amazon.com/Endurance-Shackletons-Incredible-Alfred-Lansing/dp/0465062881—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

Join this episode of DM Radio as host Eric Kavanagh speaks with Steve Sobel of Databricks and Anmol Madan of RadiantGraph. Discover how data and AI are driving a long-overdue transformation in the U.S. healthcare system, a sector that accounts for nearly 20% of the GDP. Learn how modern data architectures, real-time analytics, and AI-driven personalization are enabling healthcare organizations to deliver more efficient, empathetic, and effective care. From breaking down data silos to engaging patients in smarter, more meaningful ways, the guests reveal how the right technology can radically improve outcomes for both providers and patients.

What's up everyone, today we have the pleasure of sitting down with István Mészáros, Founder and CEO of Mitzu.io. (00:00) - Intro (01:00) - In This Episode (03:39) - How Warehouse Native Analytics Works (06:54) - BI vs Analytics vs Measurement vs Attribution (09:26) - Merging Web and Product Analytics With a Zero-Copy Architecture (14:53) - Feature or New Category? What Warehouse Native Really Means For Marketers (23:23) - How Decoupling Storage and Compute Lowers Analytics Costs (29:11) - How Composable CDPs Work with Lean Data Teams (34:32) - How Seat-Based Pricing Works in Warehouse Native Analytics (40:00) - What a Data Warehouse Does That Your CRM Never Will (42:12) - How AI-Assisted SQL Generation Works Without Breaking Trust (50:55) - How Warehouse Native Analytics Works (52:58) - How To Navigate Founder Burnout While Raising Kids Summary: István built a warehouse-native analytics layer that lets teams define metrics once, query them directly, and skip the messy syncs across five tools trying to guess what “active user” means. Instead of fighting over numbers, teams walk through SQL together, clean up logic, and move faster. One customer dropped their bill from $500K to $1K just by switching to seat-based pricing. István shares how AI helps, but only if you still understand the data underneath. This conversation shows what happens when marketing, product, and data finally work off the same source without second-guessing every report.About IstvánIstvan is the Founder and CEO of Mitzu.io, a warehouse-native product analytics platform built for modern data stacks like Snowflake, Databricks, BigQuery, Redshift, Athena, Postgres, Clickhouse, and Trino. Before launching Mitzu.io in 2023, he spent over a decade leading high-scale data engineering efforts at companies like Shapr3D and Skyscanner. At Shapr3D, he defined the long-term data strategy and built self-serve analytics infrastructure. At Skyscanner, he progressed from building backend systems serving millions of users to leading data engineering and analytics teams. Earlier in his career, he developed real-time diagnostic and control systems for the Large Hadron Collider at CERN. How Warehouse Native Analytics WorksMarketing tools like Mixpanel, Amplitude, and GA4 create their own versions of your customer. Each one captures data slightly differently, labels users in its own format, and forces you to guess how their identity stitching works. The warehouse-native model removes this overhead by putting all customer data into a central location before anything else happens. That means your data warehouse becomes the only source of truth, not just another system to reconcile.István explained the difference in blunt terms. “The data you're using is owned by you,” he said. That includes behavioral events, transactional logs, support tickets, email interactions, and product usage data. When everything lands in one place first (BigQuery, Redshift, Snowflake, Databricks) you get to define the logic. No more retrofitting vendor tools to work with messy exports or waiting for their UI to catch up with your question.In smaller teams, especially B2C startups, the benefits hit early. Without a shared warehouse, you get five tools trying to guess what an active user means. With a warehouse-native setup, you define that metric once and reuse it everywhere. You can query it in SQL, schedule your campaigns off it, and sync it with downstream tools like Customer.io or Braze. That way you can work faster, align across functions, and stop arguing about whose numbers are right.“You do most of the work in the warehouse for all the things you want to do in marketing,” István said. “That includes measurement, attribution, segmentation, everything starts from that central point.”Centralizing your stack also changes how your data team operates. Instead of reacting to reporting issues or chasing down inconsistent UTM strings, they build shared models the whole org can trust. Marketing ops gets reliable metrics, product teams get context, and leadership gets reports that actually match what customers are doing. Nobody wins when your attribution logic lives in a fragile dashboard that breaks every other week.Key takeaway: Warehouse native analytics gives you full control over customer data by letting you define core metrics once in your warehouse and reuse them everywhere else. That way you can avoid double-counting, reduce tool drift, and build a stable foundation that aligns marketing, product, and data teams. Store first, define once, activate wherever you want.BI vs Analytics vs Measurement vs AttributionBusiness intelligence means static dashboards. Not flexible. Not exploratory. Just there, like laminated truth. István described it as the place where the data expert's word becomes law. The dashboards are already built, the metrics are already defined, and any changes require a help ticket. BI exists to make sure everyone sees the same numbers, even if nobody knows exactly how they were calculated.Analytics lives one level below that, and it behaves very differently. It is messy, curious, and closer to the raw data. Analytics splits into two tracks: the version done by data professionals who build robust models with SQL and dbt, and the version done by non-technical teams poking around in self-serve tools. Those non-technical users rarely want to define warehouse logic from scratch. They want fast answers from big datasets without calling in reinforcements.“We used to call what we did self-service BI, because the word analytics didn't resonate,” István said. “But everyone was using it for product and marketing analytics. So we changed the copy.”The difference between analytics and BI has nothing to do with what the tool looks like. It has everything to do with who gets to use it and how. If only one person controls the dashboard, that is BI. If your whole team can dig into campaign performance, break down cohorts, and explore feature usage trends without waiting for data engineering, that is analytics. Attribution, ML, and forecasting live on top of both layers. They depend on the raw data underneath, and they are only useful if the definitions below them hold up.Language often lags behind how tools are actually used. István saw this firsthand. The product stayed the same, but the positioning changed. People used Mitzu for product analytics and marketing performance, so that became the headline. Not because it was a trend, but because that is what users were doing anyway.Key takeaway: BI centralizes truth through fixed dashboards, while analytics creates motion by giving more people access to raw data. When teams treat BI as the source of agreement and analytics as the source of discovery, they stop fighting over metrics and start asking better questions. That way you can maintain trusted dashboards for executive reporting and still empower teams to explore data without filing tickets or waiting days for answers.Merging Web and Product Analytics With a Zero-Copy ArchitectureMost teams trying to replace GA4 end up layering more tools onto the same mess. They drop in Amplitude or Mixpanel for product analytics, keep something else for marketing attribution, and sync everything into a CDP that now needs babysitting. Eventually, they start building one-off pipelines just to feed the same events into six different systems, all chasing slightly different answers to the same question.István sees this fragmentation as a byproduct of treating product and marketing analytics as separate functions. In categorie...

Episode 729: Sam Parr ( https://x.com/theSamParr ) talks to Zapier founder Wade Foster ( https://x.com/wadefoster ) about how to build AI Agents. — Show Notes: (0:00) Intro (5:57) DEMO: Instant Dossier (10:49) Model Context Protocol (19:30) DEMO: Read Strategy memos like a Harvard MBA (29:13) DEMO: Inbox Zero Agent (36:00) Getting your team to use AI (40:00) DEMO: Employee fraud detector — Links: • Zapier - zapier.com • Claude - Claude.ai • Glean - https://www.glean.com/ • Databricks - https://www.databricks.com/ • Superwhisper - https://superwhisper.com/ • Wisprflow - https://wisprflow.ai/ • N8n - https://n8n.io/ — Check Out Shaan's Stuff: • Shaan's weekly email - https://www.shaanpuri.com • Visit https://www.somewhere.com/mfm to hire worldwide talent like Shaan and get $500 off for being an MFM listener. Hire developers, assistants, marketing pros, sales teams and more for 80% less than US equivalents. • Mercury - Need a bank for your company? Go check out Mercury (mercury.com). Shaan uses it for all of his companies! Mercury is a financial technology company, not an FDIC-insured bank. Banking services provided by Choice Financial Group, Column, N.A., and Evolve Bank & Trust, Members FDIC — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth • Sam's List - http://samslist.co/ My First Million is a HubSpot Original Podcast // Brought to you by HubSpot Media // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano

A new AI coding challenge has revealed its first winner — and set a new bar for AI-powered software engineers.  On Wednesday at 5pm PST, the nonprofit Laude Institute announced the first winner of the K Prize, a multi-round AI coding challenge launched by Databricks and Perplexity co-founder Andy Konwinski. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Dans cet épisode du Big Data Hebdo, Vincent Heuschling et Quentin Ambard reviennent sur le Data and AI Summit 2025 de Databricks.En autres on parle de :L'acquisition de Néon pour avoir une BDD au dessus du LakehouseLakeflow Designer pour avoir une approche low-codeL'intégration de l'IADatabricks One pour rendre l'interface plus accessibleLes améliorations du moteur SQL de DatabricksAgent Bricks qui simplifie le développement d'agents AI.La data-gouvernance avec Unity Catalog.Le Vector Search au dessus du lakehouseLes inevitables troll envers Snowflake

Ankur Goyal is the founder and CEO of Braintrust, an end-to-end platform for building AI apps. Before that, he founded Impira, a data management platform that was acquired by Figma, where he went on to lead the AI team. Ankur kickstarted his career when he dropped out of college to join the founding team at SingleStore (formerly MemSQL), a formative experience that shaped his views on building for high-bar users. In today's episode, we discuss: • Ankur's early lessons on quality from MemSQL • How frustration with evals at Figma led to Braintrust • Why they delayed go-to-market (on purpose) • How to find product-market fit in a new market • Why building great software comes from a place of “paranoia” • And much more… Referenced: • Airtable: https://www.airtable.com/ • Adam Prout: https://www.linkedin.com/in/adam-prout-0b347630/ • Braintrust: https://braintrust.dev • Brian Helmig: https://www.linkedin.com/in/bryanhelmig/ • Coda: https://coda.io/ • Databricks: https://www.databricks.com/ • David Kossnick: https://www.linkedin.com/in/davidkossnick/ • Figma: https://www.figma.com/ • Goldman Sachs: https://www.goldmansachs.com/ • Kris Rasmussen: https://www.linkedin.com/in/kristopherrasmussen/ • Manu Goyal: https://www.linkedin.com/in/mngyl/ • MemSQL: https://www.singlestore.com/ (now SingleStore) • Nikita Shamgunov: https://www.linkedin.com/in/nikitashamgunov/ • OpenAI: https://openai.com/ • Snowflake: https://www.snowflake.com/ • Zapier: https://zapier.com/ Where to find Ankur: • LinkedIn: https://www.linkedin.com/in/ankrgyl/ • Twitter/X: https://x.com/ankrgyl Where to find Brett: • LinkedIn: https://www.linkedin.com/in/brett-berson-9986094/ • Twitter/X: https://twitter.com/brettberson Where to find First Round Capital: • Website: https://firstround.com/ • First Round Review: https://review.firstround.com/ • Twitter/X: https://twitter.com/firstround • YouTube: https://www.youtube.com/@FirstRoundCapital • This podcast on all platforms: https://review.firstround.com/podcast Timestamps (02:02) Dropping out of college to join MemSQL (02:24) Key lessons from MemSQL (05:54) How to build quality software (08:51) The trick to recruiting well (12:03) Founding Impira and selling to Figma (19:45) How Braintrust was born (25:33) Why good founders are paranoid (28:08) How to recognize a real market opportunity (33:37) The biggest mistake at Impira (35:15) Inside Braintrust's first six months (40:57) How AI is reshaping Braintrust's future (42:32) The evolution of their prompt playground (46:53) Fighting to stay mission-driven (52:45) Make big bets, with extreme clarity (57:00) The cultural choices that shaped Braintrust (58:49) Hiring mistakes they won't repeat (1:03:07) What PMF really looks like

Dans cet épisode, PPC nous embarque dans les coulisses du RAISE Summit 2025, un rendez-vous d'exception au Carrousel du Louvre, où l'intelligence artificielle s'est imposée pendant 2 jours. Pas de slides sur scène, mais des idées fortes et des visions tranchées.PPC a assisté à une table ronde passionnante avec des figures de proue de la tech :Olivier Pomel, CEO de Datadog,Naveen Rao, VP AI chez Databricks,Ross Mason, fondateur de MuleSoft,Andrey Khusid, CEO de Miro,Modérée par Mark Minevich de Mayfield.Ce qui en ressort ? L'entreprise IA n'est pas une simple mise à jour logicielle, c'est un changement de paradigme. On parle de confiance, de vitesse, de culture, et surtout d'un futur où les généralistes augmentés pourraient bien prendre le pouvoir.Dans cet épisode, PPC nous partage ses réflexions, ses doutes, et 4 extraits clés de cette conférence pour mieux comprendre la transition en cours. On y parle rythme d'adoption, résistance au changement, transformation des rôles et nouveaux rapports au travail.Bonne écoute !Pour suivre les actualités de ce podcast, abonnez-vous gratuitement à la newsletter écrite avec amour et garantie sans spam https://bonjourppc.substack.com Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

Stop deliberating and start driving real value from Generative AI. In this must-watch AWS Executive Insights episode, AWS Director of Technology Shaown Nandi and Databricks VP Jeff Traylor cut through the AI hype to reveal practical strategies for achieving tangible AI ROI. Drawing from his experience at both AWS and Databricks, Traylor shares an insider's playbook for successful AI implementation, from building high-performing AI talent to measuring the business impact of AI. Whether you're just starting your AI journey or looking to scale existing initiatives, this candid conversation provides the framework you need to move beyond analysis paralysis and drive meaningful outcomes. Learn how leading organizations are balancing innovation with risk management to unlock AI's transformative potential.

Today's guest is Ari Kaplan, Head of Evangelism at Databricks. Founded in 2013, Databricks democratizes insights to everyone in an organization. Their Data Intelligence Platform provides a unified foundation for all data and governance, combined with AI models tuned to an organization's unique characteristics. Now, anyone in an organization can benefit from automation and natural language to discover and use data like experts, and technical teams can easily build and deploy secure data and AI apps and products.Ari is a leading AI and data influencer and was named one of DataIQ's Top 20 AI Influencers in America in 2024. He created and led the Chicago Cubs' analytics team, inspired Moneyball and held leadership roles at Databricks, IBM and Nielsen. A Caltech Alumni of the Decade, he's authored five best-selling books and consulted for Fortune 500s. Ari also led the Raoul Wallenberg investigation and has been profiled by CNN, Time and the History Channel for his pioneering work in analytics and AI.In this episode, Ari talks about:0:00 His journey from sports fan to analytics pioneer transforming the industry5:54 How the Moneyball legacy fuels his ever-evolving tech innovation journey9:00 Being the Databricks evangelist to inspire global AI innovation11:45 How Databricks uses AI internally, inspires careful customer innovation15:38 Driving unstoppable global growth momentum through their passionate community19:10 His passion for using data science to free wrongly imprisoned, missing people22:01 His optimistic vision for AI's rapidly transformative future25:31 How AI shifted from skepticism to an essential productivity tool rapidlyTo find out more about all the great work happening at Databricks, check out the website www.databricks.com 

Get up to speed on the world’s most exciting AI news with your hosts, Artie Intel and Micheline Learning, two AI reporters dedicated to bringing you the latest breakthroughs and trends. In this episode, discover how ChatGPT-powered Barbies are transforming playtime, why FreedomGPT is making waves as an uncensored, privacy-first AI tool, and how Tanka’s long-term memory is revolutionizing workplace communication. Plus, hear about Amazon’s milestone of deploying its one millionth robot and the AI innovations powering its logistics. Whether you’re an AI enthusiast, tech professional, or just curious about how artificial intelligence is reshaping everyday life, this episode has insights and stories you won’t want to miss. Discover How the Databricks Data Intelligence Platform Empowers Your Data and AI Tasks. Get the Free eBook to Explore How to Unify Your Data and AI Seamlessly with Databricks.

Send us a textThe Compound is a go to source of financial news and insights for me on a weekly basis. What Are Your Thoughts on Tuesdays, Animal Spirits on Wednesdays, and The Compound and Friends on Friday. Incredible insights from Josh, Michael, and Ben Carlson. I highly recommend a Youtube subscribe at https://www.youtube.com/@TheCompoundNews . In this discussion…The IPO market has reopened with strong momentum, marked by blockbuster debuts from companies like CoreWeave and Circle. Circle benefited from perfect timing and favorable regulatory signals. Concerns remain over IPO pricing inefficiencies, especially when stocks surge post-IPO, raising questions about value left on the table. Several private companies - such as Safe Superintelligence, SpaceX, OpenAI, Stripe, Databricks, Anthropic, and Anduril - are generating strong pre-IPO interest. Debt financing is a growing trend among capital-intensive AI and chip firms, offering a non-dilutive alternative to equity. Meta is aggressively acquiring top AI talent, signaling intense competition. Emerging companies like Harvey (AI for law firms), Groq (AI chips), and Clue (context-aware AI assistant) highlight the sector's evolution into apps, platforms, and infrastructure layers. Despite the IPO window being open, many companies opt to stay private due to robust, orderly secondary markets providing liquidity without public scrutiny.

Welcome to episode 308 of The Cloud Pod – where the forecast is always cloudy! Justin and Matt are on hand and ready to bring you an action packed episode. Unfortunately, this one is also lullaby free. Apologies. This week we're talking about Databricks and Lakebridge, Cedar Analysis, Amazon Q, Google's little hiccup, and updates to SQL – plus so much more! Thanks for joining us.  Titles we almost went with this week: KV Phone Home: When Your Key-Value Store Goes AWOL When Your Coreless Service Finds Its Core Problem Oracle’s Vanity Fair: Pretty URLs for Pretty Penny From Warehouse to Lakehouse: Your Free Ticket to Cloud Town 1⃣Databricks Uno: Because One is the Loneliest Number Free as in Beer, Smart as in Data Science Cedar Analysis: Because Your Authorization Policies Wood Never Lie Cedar Analysis: Teaching Old Policies New Proofs Amazon Q Finally Learns to Talk to Other Apps Tomorrow: Visual Studio’s Predictive Edit Revolution The Ghost of Edits Future: AI Haunts Your Code Before You Write It IAM What IAM: Google’s Identity Crisis Breaks the Internet Permission Denied: The Day Google Forgot Who Everyone Was 403 Forbidden: When Google’s Bouncer Called in Sick AWS Brings the Heat to Fusion Research Larry’s Cloud Nine: Oracle Stock Soars on Forecast Raise OCI You Later: Oracle Bets Big on Cloud Growth Oracle’s Crystal Ball Shows 40% Cloud Growth Ahead Meta Scales Up Its AI Ambitions with $14 Billion Investment From FAIR to Scale: Meta’s $14 Billion AI Makeover Congratulations Databricks one, you are now the new low code solution.  AWS burns power to figure out how power works AI Is Going Great – Or How ML Makes Money  02:12 Zuckerberg makes Meta’s biggest bet on AI, $14 billion Scale AI deal Meta is finalizing a $14 billion investment for a 49% stake in Scale AI, with CEO Alexandr Wang joining to lead a new AI research lab at Meta.  This follows similar moves by Google and Microsoft acquiring AI talent through investments rather than direct acquisitions to avoid regulatory scrutiny. Scale AI specializes in data labeling and annotation services critical for training AI models, serving major clients including OpenAI, Google, Microsoft, and Meta.  The company’s expertise covers approximately 70% of all AI models being built, providing Meta with valuable intelligence on competitor approaches to model development. The deal reflects Meta’s struggles with its Llama AI models, particularly the underwhelming reception of Llama 4 and delays in releasing the more powerful “Behemoth” model due to concerns about competitiveness with OpenAI and

Databricks, Inc. est une société mondiale de données, d'analyse et d'intelligence artificielle, fondée en 2013 par les créateurs originaux d'Apache Spark. Mention légales : Vos données de connexion, dont votre adresse IP, sont traités par Radio Classique, responsable de traitement, sur la base de son intérêt légitime, par l'intermédiaire de son sous-traitant Ausha, à des fins de réalisation de statistiques agréées et de lutte contre la fraude. Ces données sont supprimées en temps réel pour la finalité statistique et sous cinq mois à compter de la collecte à des fins de lutte contre la fraude. Pour plus d'informations sur les traitements réalisés par Radio Classique et exercer vos droits, consultez notre Politique de confidentialité.Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

Send us a textExplore the forefront of AI innovation in this engaging episode of Exchanges, Hitachi Solutions' podcast dedicated to transformative technology insights. Host Matt Volke chats with Michael Popp, Principal Data Architect, about the groundbreaking Agent Bricks, unveiled at the Databricks Data and AI Summit. Join us as we dive into how Agent Bricks democratizes AI applications, broadens use cases, and simplifies agent creation for enterprises.Why should you listen?Discover how Agent Bricks empowers non-technical users to develop AI agents without coding, streamlining processes and boosting efficiency.Gain insights from a data architecture expert on Databricks' latest offerings such as LakeFlow and Lakebase, crafted to enhance data orchestration and management.Learn how Agent Bricks can accelerate AI adoption, helping businesses achieve higher levels of data maturity faster than ever before.Get a behind-the-scenes look at what these technological advancements mean for the future of AI in business operations.Listen now to uncover expert perspectives and strategic insights that are shaping the next generation of AI technology.global.hitachi-solutions.com

Andy Konwinski is pledging $100 million of his own money for a new kind of institute to fund researchers. It's already backed Ion Stoica's new lab. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Organisations often find themselves trapped in an infinite loop. Typically hailed as an "infinity loop" or "patching loop,” it's differentiated by a continuous cycle of fixing problems, patching, and redoing data pipelines just to maintain operations.“It's a trap that many financial institutions, banks, insurance companies, and more fall into. This loop or this cycle is a process of focusing on fixing problems, patching,” describes Errol Rodericks.In this episode of the Don't Panic It's Just Data podcast, Errol Rodericks, Product & Solutions Marketing and Sales Enablement Specialist at Denodo, discusses the challenges faced by financial services in steering the infinity loop of reactive data management. He emphasises the importance of breaking free from this cycle to achieve real innovation and success in AI-led initiatives. The conversation explores the significance of AI-ready data, the journey from bronze to gold data products, and how Denodo helps bridge the last-mile gap in data management. The Cost of Poor Data"The cost of poor data isn't just bad decisions. It's the decisions you never knew you could make. You never get around to that."This statement sets the stage for the podcast. It captures the profound effect of being stuck in a reactive data mode and how organisations can overcome it. Rodericks believes that financial services are entirely missing out on strategic opportunities that could redefine their market position.While many financial institutions have invested heavily in centralised lakehouse architectures like Snowflake or Databricks. These alone are not enough. They often struggle to deliver the trusted, real-time insights that Gen AI and business teams require. Missed Opportunities to Measurable OutcomesIt becomes more challenging for financial institutions to deliver adequate Gen AI real-time data insights when dealing with the "missing mile" of data. Approximately 30 per cent of crucial data is often overlooked or inaccessible. To overcome the Gen AI challenges, Denodo facilitates logical data management. The firm provides direct access to live, relevant, and governed data when it's needed. It becomes critical for achieving measurable outcomes with AI-led initiatives.For Chief Financial Officers (CFOs), Rodericks offered a succinct but powerful message – "Modern finance isn't about reports... It's about your ability to predict, to personalise, and to prevent – the three Ps."TakeawaysThe infinity loop is a trap for financial institutions.Reactive data handling leads to missed insights and customer churn.Breaking out of the infinity loop is essential for innovation.AI projects often fail due to unreliable data inputs.AI-ready data must be trusted, timely, contextual, and reusable.The journey from bronze to gold data products is strategic.Ownership of data products is crucial for success.Timeliness of data is critical in financial services.Denodo provides real-time access to data without copying it.Modern finance focuses on prediction, personalisation, and prevention.Chapters00:00 Understanding the Infinity Loop in Financial Services04:23 Breaking Free from the Infinity Loop06:03 The Cost of Firefighting Mode09:14 The Importance of AI-Ready Data19:42 The Journey from Bronze to Gold Data Products22:53 Bridging the Last Mile Gap27:06 Real-World Examples of

My guest today is Ion Stoica, professor of computer science at UC Berkeley and the co-founder of Conviva, Databricks, and Anyscale. Over the last two decades, Ion's research labs - the AMP Lab, the RISE Lab, and now the Sky Computing Lab - have seeded a generation of category-defining companies. Ion has the unique ability to turn non-consensus ideas into durable businesses. He applied machine learning to video optimization with Conviva before AI became mainstream. He scaled Apache Spark into a $60B platform with Databricks. And now, with Anyscale, he's betting on Ray as the foundation for distributed AI workloads. In this episode, we dig into both sides of Ion's work: how to build world-class research labs, and how to turn research into real companies. His clarity of thought makes the future feel legible, and his track record suggests he's very often right. Hope you enjoy the conversation! Chapters: 00:00 The Spark thesis: win the ecosystem first, monetize later 01:00 Intro: From lab to company - Ion's repeatable playbook 03:00 Did you always plan to become a founder, or did it just happen? 05:23 Let's start with Spark - how did the project come about? 13:04 What were the most important early decisions at Databricks? 23:49 You were the first CEO - what did you have to learn (or unlearn)? 30:01 How was building Anyscale different from building Databricks? 33:53 What's obvious to you about the future of AI that others miss? 37:31 Why AI works so well for code 41:00 The thesis behind OPAQUE Systems 44:06 Future infra will be heterogeneous, distributed, and vertically integrated 49:03 China's edge: faster diffusion from lab to market 53:19 Platform companies still work, but only with the right investors 55:57 What role did the Databricks Unit (DBU) play in value capture? 58:02 AI progress is plateauing, but adoption is just beginning

Each time I compile and curate the Database Weekly newsletter, I find lots of Fabric content from the various sources I watch to compose the newsletter. Since I primarily deal with the Microsoft Data Platform stack, this makes sense. Most of the things I am interested in are related to Microsoft, and as a result, I tend to use sources that also use SQL Server, Power BI, Fabric, and related technologies. I do look for other related data items, but I am heavily MSSQL focused. Recently, I stumbled on a piece that contains Fabric Alternatives in AWS, GCP, and OCI. It covers some of the options on these cloud platforms at a very high level. A product name and short description, but it shows there are other choices. I found it interesting that Databricks is mentioned, but not Snowflake. I'm not sure why that is, as Databricks is on Azure (and other platforms) as is Snowflake, but perhaps the author doesn't consider Snowflake a peer? That seems strange. Read the rest of The Data Warehousing Choice

In ERP news this week, Oracle announced fiscal 2025 Q4 and full-year 2025 results. Next, Salesforce unveiled the Summer '25 release, a comprehensive update designed to help businesses boost efficiency by integrating intelligent AI agents alongside human employees. Finally, Qlik announced a series of new capabilities for customers of Databricks, the Data and AI company, built on Databricks Data Intelligence Platform.Connect with us!https://www.erpadvisorsgroup.com866-499-8550LinkedIn:https://www.linkedin.com/company/erp-advisors-groupTwitter:https://twitter.com/erpadvisorsgrpFacebook:https://www.facebook.com/erpadvisorsInstagram:https://www.instagram.com/erpadvisorsgroupPinterest:https://www.pinterest.com/erpadvisorsgroupMedium:https://medium.com/@erpadvisorsgroup

Any modern enterprise generates reams of data, which can be difficult to correctly store, process, and use without the right approach.This has become even more important in the face of AI. Before any leader can begin implementing AI across their workflow, they must first ensure they've prepared data at the right scale – and across its entire lifecycle.Data integration, in which data from across a business is combined into a single stream, can be a huge help here. But where do you start with this? And where do open data formats fit into this mix?In this episode, in association with Informatica, Jane and Rory are joined by Eric Ho, senior director product management at Informatica, to discuss data integration at scale and explore the evolution of open table formats for modern data architectures and data warehousing.Read more:Structured vs unstructured data managementOnly a handful of generative AI projects make it into production – here's whyA quarter of firms still don't have a formal data strategy – and it's hampering AI adoptionWhat is Delta Lake in Databricks?Why your business needs data protection policies

Welcome back to SED News, a podcast series from Software Engineering Daily where hosts Gregor Vand and Sean Falconer break down the latest stories in software engineering, Silicon Valley, and wider tech world. In this episode, Gregor and Sean unpack what's going with Deel and Rippling, explore why Databricks and Snowflake are making big bets The post SED News: Corporate Spies, Postgres, and the Weird Life of Devs Right Now appeared first on Software Engineering Daily.

Ion Stoica helped define the modern data stack. Now he's coming for AI evaluation. From co-founding Databricks and Anyscale to launching LMArena, Ion has shaped the infrastructure underlying some of the biggest shifts in computing. In this conversation, he unpacks what most people get wrong about model evaluation, the infrastructure challenges ahead for agents and heterogeneous compute, and why he believes the U.S. is structurally disadvantaged in open-source AI compared to China. (0:00) Intro(0:49) Launching a New Startup: LMArena(1:01) The Origin of the Vicuna Model(1:54) Challenges in Model Evaluation(6:33) Becoming a Company(7:47) Expanding Evaluation Capabilities(13:48) The Importance of Human-Based Evaluations(18:56) Open Source vs. Proprietary Models(23:05) Infrastructure and Collaboration Challenges(28:22) China's Strategic Advantages in Technology(29:54) Opportunities in AI Infrastructure(31:50) Challenges in AI Model Optimization(35:49) The Role of Data in AI Enterprises(39:31) Reflections on AI Progress and Predictions(50:40) Quickfire With your co-hosts: @jacobeffron - Partner at Redpoint, Former PM Flatiron Health @patrickachase - Partner at Redpoint, Former ML Engineer LinkedIn @ericabrescia - Former COO Github, Founder Bitnami (acq'd by VMWare) @jordan_segall - Partner at Redpoint

Welcome back to SED News, a podcast series from Software Engineering Daily where hosts Gregor Vand and Sean Falconer break down the latest stories in software engineering, Silicon Valley, and wider tech world. In this episode, Gregor and Sean unpack what's going with Deel and Rippling, explore why Databricks and Snowflake are making big bets The post SED News: Corporate Spies, Postgres, and the Weird Life of Devs Right Now appeared first on Software Engineering Daily.

Chris Degnan is one of the most legendary CROs of this generation. He joined Snowflake as employee #13 and the 1st sales hire. He scaled the sales org from 0 to over $3B in ARR, spanned four CEOs, and retired as CRO after 11 years. In his first podcast post-retirement, Chris opened his CRO playbook, from early enablement to hiring rigor and fending off threats from competitors. He also reflects on lessons from working with leaders like Frank Slootman, John McMahon, and Sridhar Ramaswamy. If you're a founder or running sales at a startup, this one is for you. (00:00) Introduction to Chris's Journey at Snowflake (01:47) Navigating Leadership Changes (04:39) The Importance of Sales Methodology and Enablement (10:22) Near-Death Experiences and Company Resilience (13:39) Building a Strong Sales Organization (27:25) Hiring and Scaling the Sales Team (34:52) Board Dynamics and Mentorship (44:29) The Influence of John McMahon (46:22) Leadership Styles and Intuition (46:56) Launching Snowflake Japan (49:39) Learning from Leaders (55:10) The Importance of Competitive Moats (59:12) Snowflake vs. Databricks (01:07:45) Public vs. Private Markets (01:14:03) Sales and Marketing Synergy (01:26:17) Final Thoughts and Future Plans Executive Producer: Rashad Assir Producer: Leah Clapper Mixing and editing: Justin Hrabovsky Check out Unsupervised Learning, Redpoint's AI Podcast: https://www.youtube.com/@UCUl-s_Vp-Kkk_XVyDylNwLA

Send us a text00:00 - Intro00:51 - Scale AI gets $14.3B from Meta, hits $29B valuation02:03 - Starlink doubles subs to 6M, adds 100K in Africa03:22 - SpaceX expands Starship launch capacity in Florida04:08 - Databricks adds Google Gemini, hits $72.8B valuation05:09 - Perplexity partners with Nvidia, eyes $14B raise06:08 - Glean raises $150M at $7.2B valuation07:13 - Mistral hits $6B valuation, expands sovereign AI reach08:32 - Gecko Robotics doubles to $1.25B valuation09:28 - Bullish files confidentially for US IPO

Today's show: Alex moderates a TWIST VC Roundtable with Jason, Paige Doherty (Behind Genius), and Altimeter's Megan Reynolds about the state of early-stage venture capital. They break down the rise of secondary markets as a key liquidity path for VCs, analyze the resurgence in M&A activity from major players like Meta, Databricks, and OpenAI, and question whether inflated ARR figures from YC startups are distorting valuations. Jason shares his year-zero investment thesis and offers tactical advice on secondary structuring and identifying high-quality revenue. Whether you're raising, investing, or building, this episode delivers essential insights into the evolving early-stage landscape.Timestamps:(0:00) Episode Teaser(1:28) Meet our panelists!(2:37) Will secondaries replace traditional M&A?(10:10) LinkedIn Ads - Get a $100 LinkedIn ad credit at http://www.linkedin.com/thisweekinstartups(14:28) Has M&A actually bounced back?(20:06) Pilot - Visit https://www.pilot.com/twist and get $1,200 off your first year.(25:35) Secondary market advice, just for founders(30:10) Retool - Visit https://www.retool.com/twist and try it out today.(32:49) Why is it so hard for emerging managers to raise funds?(38:28) Seed funds: the math is not mathing(52:07) Why early investors become “collateral damage”(56:31) The importance of revenue quality in early-stage startups(1:06:43) Quick Fire Question Round!Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpLinks from episode:Altimeter: https://www.altimeter.com/homeBehind Genius: https://www.behindgeniusventures.com/Follow Meghan:X: https://x.com/MeghanKReynoldsLinkedIn: https://www.linkedin.com/in/meghankreynolds/Follow Paige:X: https://x.com/paigefinnnLinkedIn: https://www.linkedin.com/in/paigedoherty/Follow Alex:X: https://x.com/alexLinkedIn: ⁠https://www.linkedin.com/in/alexwilhelmFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisThank you to our partners:(10:10) LinkedIn Ads - Get a $100 LinkedIn ad credit at http://www.linkedin.com/thisweekinstartups(20:06) Pilot - Visit https://www.pilot.com/twist and get $1,200 off your first year.(30:10) Retool - Visit https://www.retool.com/twist and try it out today.Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarlandCheck out Jason's suite of newsletters: https://substack.com/@calacanisFollow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: https://twistartups.substack.comSubscribe to the Founder University Podcast: https://www.youtube.com/@founderuniversity1916

This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today's innovative AI tech companies who upgraded to OCI…and saved.   Try OCI for free at http://oracle.com/eyeonai   What if you could fine-tune an AI model without any labeled data—and still outperform traditional training methods?   In this episode of Eye on AI, we sit down with Jonathan Frankle, Chief Scientist at Databricks and co-founder of MosaicML, to explore TAO (Test-time Adaptive Optimization)—Databricks' breakthrough tuning method that's transforming how enterprises build and scale large language models (LLMs).   Jonathan explains how TAO uses reinforcement learning and synthetic data to train models without the need for expensive, time-consuming annotation. We dive into how TAO compares to supervised fine-tuning, why Databricks built their own reward model (DBRM), and how this system allows for continual improvement, lower inference costs, and faster enterprise AI deployment.   Whether you're an AI researcher, enterprise leader, or someone curious about the future of model customization, this episode will change how you think about training and deploying AI.   Explore the latest breakthroughs in data and AI from Databricks: https://www.databricks.com/events/dataaisummit-2025-announcements Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI  

Live from the Databricks Data + AI Summit at the Moscone Center, this DMRadio episode kicks off with a high-energy segment featuring Ari Kaplan and a deep dive into the risks of handing proprietary data to public LLMs. The conversation explores safer alternatives like Retrieval-Augmented Generation (RAG) and the power of enterprise knowledge graphs to fuel private, secure AI solutions. Then we shift gears with Mark Stevens of Row 64, discussing the critical need for real-time data visualization—especially in telco, cybersecurity, and smart city planning. From massive-scale data ingestion to digital twins, this episode brings you the pulse of what's next in AI and data strategy.

Tricks to Fine Tuning // MLOps Podcast #318 with Prithviraj Ammanabrolu, Research Scientist at Databricks. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractPrithviraj Ammanabrolu drops by to break down Tao fine-tuning—a clever way to train models without labeled data. Using reinforcement learning and synthetic data, Tao teaches models to evaluate and improve themselves. Raj explains how this works, where it shines (think small models punching above their weight), and why it could be a game-changer for efficient deployment.// BioRaj is an Assistant Professor of Computer Science at the University of California, San Diego, leading the PEARLS Lab in the Department of Computer Science and Engineering (CSE). He is also a Research Scientist at Mosaic AI, Databricks, where his team is actively recruiting research scientists and engineers with expertise in reinforcement learning and distributed systems.Previously, he was part of the Mosaic team at the Allen Institute for AI. He earned his PhD in Computer Science from the School of Interactive Computing at Georgia Tech, advised by Professor Mark Riedl in the Entertainment Intelligence Lab.// Related LinksWebsite: https://www.databricks.com/~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our Slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Raj on LinkedIn: /rajammanabroluTimestamps:[00:00] Raj's preferred coffee[00:36] Takeaways[01:02] Tao Naming Decision[04:19] No Labels Machine Learning[08:09] Tao and TAO breakdown[13:20] Reward Model Fine-Tuning[18:15] Training vs Inference Compute[22:32] Retraining and Model Drift[29:06] Prompt Tuning vs Fine-Tuning[34:32] Small Model Optimization Strategies[37:10] Small Model Potential[43:08] Fine-tuning Model Differences[46:02] Mistral Model Freedom[53:46] Wrap up

Alex Merced talks about the annoucement at Snowflake and Databricks respective conferences in particular when it comes to the lakehouse. Follow Alex: https://www.alexmerced.com/data

What's holding back enterprise adoption of blockchain?In this episode, Sergio from Sonar X joins Sam to explain why the missing piece is data infrastructure. Drawing from experience at Bloomberg and AWS (where he led Amazon Managed Blockchain), Sergio breaks down why most blockchain systems are broken at the data layer—and how Sonar X is building a scalable, multi-chain backend to fix it.From audit-grade historical data to real-time indexing across 30+ chains, Sonar X is laying the foundation for Web3's next growth wave.Key Timestamps[00:00:00] Introduction: Sergio's background and what Sonar X is solving.[00:01:30] Growing up as a fixer: From Italian banking to Bloomberg and AWS.[00:04:00] Falling in love with blockchain: MIT program and lightbulb moment.[00:05:30] The problem: Enterprise-grade infrastructure for blockchain data doesn't exist.[00:07:00] What Sonar X does: Reliable, multi-chain data infra for coverage, quality, and access.[00:09:00] Use cases: From DeFi indexes to forensics, custody, fund admin, and compliance.[00:12:00] The architecture: How Sonar X solves the CAP theorem limitations of blockchain.[00:15:00] Data standardization: Making 30+ chains interoperable via common schemas.[00:17:30] Indexing like Bloomberg: Creating a “market data” layer for all chains.[00:19:00] Data delivery: Snowflake, Databricks, CSV exports, and multi-cloud support.[00:20:00] Business model: Simple annual chain-based subscriptions, no usage limits.[00:22:00] Custom support: Engineering advisory to reduce compute costs for clients.[00:23:00] Challenges ahead: Scaling to meet 1M+ TPS chains and occasional-use customers.[00:25:00] Traditional finance: How blockchain will upgrade, not replace, infrastructure like DTCC or SWIFT.[00:27:00] Blockchain = the ultimate value exchange machine.[00:28:00] Data scale: Every new asset, chain, or protocol creates exponential complexity.[00:30:00] Final ask: Keep investing in product, preparing for GenAI, and expanding chain support.[00:33:00] The future: RWA tokenization, AI agents, and why reliable data will be the cornerstone.Connecthttps://www.sonarx.com/https://www.linkedin.com/company/sonarxhttps://x.com/sonarx_hqhttps://www.linkedin.com/in/sergiocapannaDisclaimerNothing mentioned in this podcast is investment advice and please do your own research. Finally, it would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend.Be a guest on the podcast or contact us - https://www.web3pod.xyz/

In this episode, I reconnect with my old friend Joe Saul-Sehy from The Stacking Benjamins podcast to talk about creating your own life curriculum — because when you do, you may no longer be beholden to anyone. With AI eliminating jobs and making the path to financial independence even tougher, I wanted to sit down with another creator who forged his own way—building a business and income stream through podcasting. I firmly believe everyone should build an online brand and develop a side hustle. The era of job security, pensions, and abundant opportunities is fading. You—and your children—need to learn how to create your own income streams. Check out Joe's work at: https://joesaulsehy.com https://www.stackingbenjamins.com Subscribe To Financial Samurai Join 60,000+ others and subscribe to the free weekly Financial Samurai newsletter. My goal is to help you achieve financial freedom sooner, rather than later. Financial Samurai started in July 2009 and is the leading independently-owned personal finance site today.  This episode is sponsored by Fundrise Venture, an innovative venture capital product that invests in private AI companies like OpenAI, Anthropic, Anduril, Databricks, and more. The minimum investment to start is only $10, and I personally have invested over $185,000 in Fundrise Venture so far.   

Hiring only senior engineers might feel like a smart move, but is it breaking game development? In this episode, Ben sits down with Carly Taylor (an engineer and data scientist formerly on Call of Duty, now at Databricks) to tackle one of the most pressing and misunderstood issues in game development today: the crumbling pipeline of engineering talent. They dive deep into the tragedy of the commons happening across studios, where short-term thinking and overreliance on senior talent are putting the future of game engineering at risk. Carly sheds light on the danger of under-investing in junior talent, the mentorship void left behind by remote work, and the role AI is really playing (hint: it's not what vendors are promising). Whether you're leading a studio, managing engineers, or trying to break into games yourself, this episode is a wake-up call. You'll Hear: -Why the next generation of engineers is not being mentored -How studios are draining the senior talent pool -The real technical challenges of using AI in games -Why hiring only senior devs doesn't produce better games -What juniors bring to the table (and why companies should listen) -How remote work disrupted knowledge transfer and how to rebuild it -Why game dev is still one of the most passionate industries in tech Connect with Carly Taylor: - Website: https://www.rebeldatascience.com/ - Substack: https://carlytaylor.substack.com/ - LinkedIn: https://www.linkedin.com/in/carly-taylor - Databricks: https://www.databricks.com/dataaisummit/speaker/carly-taylor Join the Building Better Games Community: - BBG Discord: https://discord.gg/ySCPS5aMcQ - Level Up Your Production Skills: https://www.buildingbettergames.gg/succeeding-in-game-production - Subscribe to the BBG newsletter: https://www.buildingbettergames.gg/newsletter Connect with Us: - LinkedIn: https://www.linkedin.com/in/benjamin-carcich - Website: https://www.buildingbettergames.gg - Facebook: https://www.facebook.com/bbg.valarininc - YouTube: https://www.youtube.com/@BuildingBetterGames

AI's increasing presence in the legal field is raising significant concerns, particularly regarding the accuracy of information generated by these systems. Judges have reported a notable rise in AI-generated inaccuracies, with 23 instances of fake legal citations identified since May 1st. Legal data analyst Damien Chartland has documented 120 cases where courts recognized AI's hallucinations, which include fabricated legal quotes and non-existent authorities. This trend indicates a shift in responsibility, as lawyers are now accountable for these errors, contrasting with previous instances where self-represented individuals were primarily at fault. The implications are serious, with courts imposing fines exceeding $10,000 for AI misuse.The impact of automation extends beyond the legal sector, as a recent report highlights the potential for AI to exacerbate the gender employment gap. In high-income countries, the risk of women facing job automation has risen to 9.6%, while the risk for men is significantly lower at 3.5%. Jobs traditionally held by women, such as administrative roles, are particularly vulnerable to automation. Experts warn that without substantial changes in the labor market, women may face increased challenges in securing stable employment, as their work often shifts toward household tasks rather than formal employment.In the tech industry, Databricks has revealed that 80% of new databases created on their NEON platform were generated by AI agents, showcasing the growing influence of non-developers in coding. This trend emphasizes the need for companies to adapt to remain competitive, focusing on optimizing products for visibility to large language models. Meanwhile, Zoom's CEO has begun using an AI avatar for quarterly earnings calls, raising questions about authenticity and trust in corporate communication. The use of AI avatars could level the playing field for small business leaders but also introduces risks such as impersonation and misuse.Finally, Qualcomm has challenged Apple's claims regarding the performance of its in-house C1 modem, asserting that it falls short compared to Qualcomm's existing technology. A study found that Android devices powered by Qualcomm outperformed the iPhone 16e in both download and upload speeds, particularly in urban environments. Despite these challenges, Apple aims for full-stack control over its technology, and while the initial performance may not meet expectations, the company is known for its ability to iterate and improve rapidly. This ongoing competition highlights the dynamic nature of the tech industry and the importance of innovation.  Four things to know today  00:00 The Hidden Costs of AI: Legal Fines, Workforce Disruption, and the Rise of Unchecked Automation in the Enterprise05:51 New AI Integrations From OpenAI, Salesforce, and GoTo Push Deeper Into MSP Value Chain—Control or Be Commoditized09:01 From Efficiency to Deception? Zoom's AI Avatar Sparks Questions About Corporate Authenticity and Accountability10:49 Apple's DIY Modem Underperforms Qualcomm—But Version One Shows the Game Plan Is in Motion  Supported by:https://www.huntress.com/mspradio/https://cometbackup.com/?utm_source=mspradio&utm_medium=podcast&utm_campaign=sponsorship 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

In this episode, Yext CEO Michael Walrath joins Sam, Asad, and AJ to talk about what comes after Google. With over two decades of experience leading and investing in internet businesses—including Right Media and Moat—Michael unpacks how AI is reshaping the way we search, discover, and interact with information online.He explains why the old rules of SEO no longer apply, how structured data and digital presence are becoming mission-critical, and what brands need to do now to stay visible in an AI-first world. Michael also shares candid insights on running a public company through market whiplash, how he thinks about signal vs. noise when allocating capital, and why he's choosing profitability over prediction.Thanks for tuning in!Join the revenue leaders redefining growth at Pavilion's CRO Summit 2025, which will be held on June 3rd at the Denver Art Museum. Register today.Join the free Topline Slack channel to connect with 600+ revenue leaders, share insights, and keep the conversation going beyond the podcast!Subscribe to the Topline Newsletter to get the latest industry developments and emerging go-to-market trends delivered to your inbox every Thursday.Tune into The Revenue Leadership Podcast with Kyle Norton every Wednesday. Kyle dives deep into the strategies and tactics that drive success for revenue leaders like Jason Lemkins of SaaStr, Stevie Case of Vanta, and Ron Gabrisko of Databricks.

Krithika Shankarraman was the first marketing hire at OpenAI and Stripe and led marketing at Retool. At OpenAI, she established marketing foundations for ChatGPT for consumers and enterprises, as well as their developer API platform. While at Stripe, she spent over eight years building and scaling their marketing function from scratch. An engineer turned marketer, Krithika brings a uniquely analytical approach to marketing. She currently serves as Entrepreneur in Residence at Thrive Capital, where she helps portfolio companies on all things marketing.What you will learn:1. Why do most marketing playbooks often fail, and what's a better way?2. Which marketing lever should I pull first?3. Why is trying to be better than competitors usually a losing strategy?4. How do I craft positioning that actually converts?5. What makes messaging stick with developers, enterprises, and consumers?6. What pricing experiments actually move revenue?7. What is working at OpenAI really like?8. Why does consistency and quality matter more than speed?—Brought to you by:Eppo — Run reliable, impactful experimentsAirtable ProductCentral—Launch to new heights with a unified system for product developmentLinkedIn Ads—Reach professionals and drive results for your business—Where to find Krithika Shankarraman:• X: https://x.com/krithix• LinkedIn: https://www.linkedin.com/in/krithix/• Website: https://krithix.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 Krithika(04:22) Early marketing lessons from OpenAI(11:17) Diagnosing marketing needs(15:06) The DATE framework and why being cheaper is a race to the bottom(17:11) Marketing strategies at Retool(22:29) Insights from marketing at Stripe(32:33) The importance of consistent marketing communication(39:55) Criteria for hiring a marketing expert(41:43) “Capital M” vs. “lowercase m” marketing(43:05) ChatGPT vs. Claude: market dominance(45:31) The future of AI and its societal impact(47:09) Work-life balance(48:41) Transitioning to Thrive(52:35) Career advice for marketers(55:00) The importance of taste and creativity in the AI era(01:00:04) AI product pricing(01:03:21) AI tools in marketing(01:05:17) Failure corner(01:08:46) Lightning round and final thoughts—Referenced:• OpenAI: https://openai.com/• Stripe: https://stripe.com/• Retool: https://retool.com/• Dropbox: https://www.dropbox.com/• Sam Altman talks about his business model: https://www.youtube.com/watch?v=pLnyjxgFxew• The art and science of pricing | Madhavan Ramanujam (Monetizing Innovation, Simon-Kucher): https://www.lennysnewsletter.com/p/the-art-and-science-of-pricing-madhavan• Pricing your SaaS product: https://www.lennysnewsletter.com/p/saas-pricing-strategy• Netflix: https://www.netflix.com/• Stripe Connect: https://stripe.com/connect• John Collison on X: https://x.com/collision• Patrick Collison on X: https://x.com/patrickc• Cristina Cordova on LinkedIn: https://www.linkedin.com/in/cristinajcordova/• Hackpad: https://en.wikipedia.org/wiki/Hackpad• Building Wiz: the fastest-growing startup in history | Raaz Herzberg (CMO and VP Product Strategy): https://www.lennysnewsletter.com/p/building-wiz-raaz-herzberg• Wiz: https://www.wiz.io/• Thrive Capital: https://thrivecap.com/• Brian Chesky's new playbook: https://www.lennysnewsletter.com/p/brian-cheskys-contrarian-approach• Claude: https://claude.ai/new• ChatGPT: https://chatgpt.com/• Lessons from scaling Stripe | Claire Hughes Johnson (former COO of Stripe): https://www.lennysnewsletter.com/p/lessons-from-scaling-stripe-tactics• Databricks: https://www.databricks.com/• Everyone's an engineer now: Inside v0's mission to create a hundred million builders | Guillermo Rauch (founder and CEO of Vercel, creators of v0 and Next.js): https://www.lennysnewsletter.com/p/everyones-an-engineer-now-guillermo-rauch• Tobi Lütke's leadership playbook: Playing infinite games, operating from first principles, and maximizing human potential (founder and CEO of Shopify): https://www.lennysnewsletter.com/p/tobi-lutkes-leadership-playbook• 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• April Dunford on product positioning, segmentation, and optimizing your sales process: https://www.lennysnewsletter.com/p/april-dunford-on-product-positioning• A step-by-step guide to crafting a sales pitch that wins | April Dunford (author of Obviously Awesome and Sales Pitch): https://www.lennysnewsletter.com/p/a-step-by-step-guide-to-crafting• Severance on AppleTV+: https://tv.apple.com/us/show/severance/• Granola: https://www.granola.ai/• Some people think AI writing has a tell—the em dash. Writers disagree: https://www.washingtonpost.com/technology/2025/04/09/ai-em-dash-writing-punctuation-chatgpt/—Recommended books:• Obviously Awesome: How to Nail Product Positioning So Customers Get It, Buy It, Love It: https://www.amazon.com/Obviously-Awesome-Product-Positioning-Customers/dp/1999023005• Circe: https://www.amazon.com/Circe-Madeline-Miller/dp/0316556327/—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. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.lennysnewsletter.com/subscribe

Excited is overused This week, we recap Microsoft Build, Google I/O, and Java turning 30. Plus, more Vegemite talk and a discussion on whether tech presenters really need to tell us they're “excited.” Watch the YouTube Live Recording of Episode (https://www.youtube.com/live/4ar2nzlx3gw?si=pee9R6HbHN06etA2) 520 (https://www.youtube.com/live/4ar2nzlx3gw?si=pee9R6HbHN06etA2) Runner-up Titles We all need choices Vegans are against everything The problem is you shouldn't be watching keynotes You're giving the black box too much responsibility What are you going to do? Some more stuff they announced that I don't want They're excited about that Hopefully people are excited about that I'm happy for you I want to like it Nerd famous Can you just fix calendaring? It's too much I'm not going back to Java Rundown Will Matt try marmalade with his Vegemite for the full PBJ analogue. (https://bsky.app/profile/thescarletmanuka.bsky.social/post/3lpdioobdek27) MSFT Build Microsoft Build 2025: news and announcements from the developer conference (https://www.theverge.com/news/669382/microsoft-build-2025-news-ai-agents) Microsoft announces over 50 AI tools to build the ‘agentic web' at Build 2025 (https://venturebeat.com/ai/microsoft-announces-over-50-ai-tools-to-build-the-agentic-web-at-build-2025/) Findings from Microsoft's 3-week study on Copilot use (https://newsletter.getdx.com/p/microsoft-3-week-study-on-copilot-impact) Microsoft open sources Windows Subsystem for Linux (https://www.theregister.com/2025/05/19/microsoft_wsl_open_source/) Google I/O Everything announced at the Google I/O 2025 keynote (https://www.engadget.com/ai/everything-announced-at-the-google-io-2025-keynote-171514495.html?guccounter=1&guce_referrer=aHR0cHM6Ly9uZXdzLmdvb2dsZS5jb20v&guce_referrer_sig=AQAAAIewjPeuiVydyPgPtFxJyD7lYSE7rAY-BFM7JxN5AHvJvH_NrHmCURfrSuBK4HmB700OTDoGERdfPyB77mCb8_225GPcoppCXG4dl_bgGOA9j4E5Fprl_nUD__-69yEG5-W7vmXISAdJC2kBU3MSZErnX1TuyR1_gKfb5Hx_OdRs) Android XR is getting stylish partners in Warby Parker and Gentle Monster (https://www.theverge.com/google-io/670013/android-xr-warby-parker-gentle-monster-smart-glassesi-io-2025) Jules - An Asynchronous Coding Agent (https://jules.google/) Google Embraces MCP (https://thenewstack.io/google-embraces-mcp/?link_source=ta_bluesky_link&taid=682cf46509703200019ca4f3&utm_campaign=trueanthem&utm_medium=social&utm_source=bluesky) iOS 19 Will Let Developers Use Apple's AI Models in Their Apps (https://www.macrumors.com/2025/05/20/ios-19-apple-ai-models-developers/) NEW Claude MCP AI Super Agents (https://x.com/juliangoldieseo/status/1924148362653348232?s=46&t=zgzybiDdIcGuQ_7WuoOX0A) AWS Launches Its Take on an Open Source AI Agents SDK (https://thenewstack.io/aws-launches-its-take-on-an-open-source-ai-agents-sdk/) Java at 30: The Genius Behind the Code That Changed Tech (https://thenewstack.io/java-at-30-the-genius-behind-the-code-that-changed-tech/) Relevant to your Interests If AI is so good at coding … where are the open source contributions? (https://pivot-to-ai.com/2025/05/13/if-ai-is-so-good-at-coding-where-are-the-open-source-contributions/) Y Combinator says Google is a ‘monopolist' that has ‘stunted' the startup ecosystem (https://techcrunch.com/2025/05/13/y-combinator-says-google-is-a-monopolist-that-has-stunted-the-startup-ecosystem) Coinbase says customers' personal information stolen in data breach (https://techcrunch.com/2025/05/15/coinbase-says-customers-personal-information-stolen-in-data-breach/) DataBricks interview about Neon (https://www.axios.com/newsletters/axios-pro-rata-a6f0b4f0-fe7f-412f-bf4b-5978de02d604.html?chunk=1&utm_term=emshare#story1) OpenAI launches Codex, an AI coding agent, in ChatGPT (https://techcrunch.com/2025/05/16/openai-launches-codex-an-ai-coding-agent-in-chatgpt/) CarPlay Ultra, the next generation of CarPlay, begins rolling out today (https://www.apple.com/newsroom/2025/05/carplay-ultra-the-next-generation-of-carplay-begins-rolling-out-today/) Meta argues enshittification isn't real in bid to toss FTC monopoly case (https://arstechnica.com/tech-policy/2025/05/meta-says-no-proof-of-monopoly-power-wants-ftc-case-dismissed-mid-trial/) When Open Source Isn't: How OpenRewrite Lost Its Way (https://medium.com/@jonathan.leitschuh/when-open-source-isnt-how-openrewrite-lost-its-way-642053be287d) Wiz 2.0? Cyera's meteoric $6B valuation is turning heads across the cyber world | CTech (https://www.calcalistech.com/ctechnews/article/shavjm2g2) Steve Langasek, One of Ubuntu Linux's Leading Lights, Has Died (https://thenewstack.io/steve-langasek-one-of-ubuntu-linuxs-leading-lights-has-died/) Python: The Documentary [OFFICIAL TRAILER] (https://www.youtube.com/watch?v=pqBqdNIPrbo) Spain Orders Airbnb to Take Down 66,000 Rental Listings (https://www.nytimes.com/2025/05/19/business/airbnb-listings-spain.html) Detecting malicious Unicode (https://daniel.haxx.se/blog/2025/05/16/detecting-malicious-unicode/) Former Apple Design Guru Jony Ive to Take Expansive Role at OpenAI (https://www.wsj.com/tech/ai/former-apple-design-guru-jony-ive-to-take-expansive-role-at-openai-5787f7da) Apple's Worldwide Developers Conference kicks off June 9 (https://www.apple.com/newsroom/2025/05/apples-worldwide-developers-conference-kicks-off-june-9/) Valkey Turns One: How the Community Fork Left Redis in the Dust - Momento (https://www.gomomento.com/blog/valkey-turns-one-how-the-community-fork-left-redis-in-the-dust/?ck_subscriber_id=512834888&utm_source=convertkit&utm_medium=email&utm_campaign=[Last%20Week%20in%20AWS]:%20Transform%20Away,%20as%20AWS%20Reverses%20Course%20-%2017665354) Nonsense Max (@StreamOnMax) on X (https://x.com/StreamOnMax/status/1922781490473034153) Uber to introduce fixed-route shuttles in major US cities designed for commuters (https://techcrunch.com/2025/05/14/uber-to-introduce-fixed-route-shuttles-in-major-us-cities-other-ways-to-save/) Conferences POST/CON 25 (https://postcon.postman.com/2025/), June 3-4, Los Angeles, CA, Brandon representing SDT. Register here for free pass (https://fnf.dev/43irTu1) using code BRANDON (https://fnf.dev/43irTu1) (limited to first 20 People) Contract-Driven Development: Unite Your Teams and Accelerate Delivery (https://postcon.postman.com/2025/session/3022520/contract-driven-development-unite-your-teams-and-accelerate-delivery%20%20%20%20%20%208:33) by Chris Chandler SREDay Cologne, June 12th, 2025 (https://sreday.com/2025-cologne-q2/#tickets) - Coté speaking, discount: CLG10, 10% off. SDT News & Community Join our Slack community (https://softwaredefinedtalk.slack.com/join/shared_invite/zt-1hn55iv5d-UTfN7mVX1D9D5ExRt3ZJYQ#/shared-invite/email) Email the show: questions@softwaredefinedtalk.com (mailto:questions@softwaredefinedtalk.com) Free stickers: Email your address to stickers@softwaredefinedtalk.com (mailto:stickers@softwaredefinedtalk.com) Follow us on social media: Twitter (https://twitter.com/softwaredeftalk), Threads (https://www.threads.net/@softwaredefinedtalk), Mastodon (https://hachyderm.io/@softwaredefinedtalk), LinkedIn (https://www.linkedin.com/company/software-defined-talk/), BlueSky (https://bsky.app/profile/softwaredefinedtalk.com) Watch us on: Twitch (https://www.twitch.tv/sdtpodcast), YouTube (https://www.youtube.com/channel/UCi3OJPV6h9tp-hbsGBLGsDQ/featured), Instagram (https://www.instagram.com/softwaredefinedtalk/), TikTok (https://www.tiktok.com/@softwaredefinedtalk) Book offer: Use code SDT for $20 off "Digital WTF" by Coté (https://leanpub.com/digitalwtf/c/sdt) Sponsor the show (https://www.softwaredefinedtalk.com/ads): ads@softwaredefinedtalk.com (mailto:ads@softwaredefinedtalk.com) Recommendations Brandon: MurderBot (https://www.google.com/aclk?sa=L&ai=DChcSEwi286yM0KiNAxUELNQBHStVDhgYABABGgJvYQ&co=1&gclid=Cj0KCQjwxJvBBhDuARIsAGUgNfjytNAoEF2oBZYZixtUoB15h1o0UU1SJRQp-A-GFE_i0FGLHOE5wY8aAoFzEALw_wcB&cce=1&sig=AOD64_3mm-tO-giOK7S1lj45fNCC7pw-6w&q&adurl&ved=2ahUKEwiFq6eM0KiNAxXI4ckDHc0cBAMQ0Qx6BAg9EAE)

Gopal Krishnamurthy is the founder and CEO of Lumel, which has a suite of products focused on enterprise performance management (EPM). Their apps allow users to plan, report, and analyze data using the modern native app framework vs. traditional SaaS on top of modern cloud data platforms such as Microsoft Fabric, Snowflake, Databricks, and others. Lumel's products provide a full stack of integrated Planning, BI & data apps on the customers' data platforms. He grew his enterprise services company, Visual BI, to over 200 employees and sold that company to Atos in 2021, as he described in his first Practical Founders podcast interview in 2023. Gopal self-funded Lumel with a VC-sized investment and has grown it to over 300 employees in four years. Lumel is already at a revenue run rate of over $12M ARR and is growing fast. Lumel is building its apps using modern cloud data platforms, not siloed SaaS databases, allowing it to manage real-time data across applications. This bold new vision and architecture for enterprise software apps align with modern data approaches supporting AI, creating a billion-dollar opportunity for Lumel in the future. In this episode, Gopal also discusses: The challenge of transitioning from custom services to a no-touch product-led approach selling to enterprises Why VCs wouldn't understand their technology bet and why their patience is paying off What it's like to grow a fast-growth and innovative technology company as a bootstrapper Quote from Gopal Krishnamurthy, founder and CEO of Lumel “The main thing is it's a big market. It's not like we are just trying to get our first $10 million revenue. We have done that with Lumel already. We are looking at how we can get to a billion-dollar ARR business. That's the big, bold vision. We have invested tens of millions already, and we are almost profitable. “We think we can absolutely create a billion-dollar business based on our customer feedback and traction from 3,000 customers. So, it's not a question of product market fit. We worked with hundreds of our enterprise customers and perfected our data app products. “The other thing is that our products can work for smaller and medium-sized businesses because of our architecture and approach. It's completely horizontal: it works for all industries and all customers of all sizes.” Links Gopal Krishnamurthy on LinkedIn Lumel on LinkedIn Lumel website Power BI website The Practical Founders Podcast Tune into the Practical Founders Podcast for weekly in-depth interviews with founders who have built valuable software companies without big funding. Subscribe to the Practical Founders Podcast using your favorite podcast app or view on our YouTube channel. Get the weekly Practical Founders newsletter and podcast updates at practicalfounders.com.

Sam Jacobs, AJ Bruno, and Asad Zaman confront the emotional weight and operational strain of leading through sustained GTM volatility. They reflect on the mental health toll of missed quarters, the pressure to perform under investor scrutiny, and the fine line between perseverance and sunk-cost thinking. The trio explores how founders can navigate uncertain markets with clear contingency planning, why Pavilion is betting big on small peer groups to improve retention, and what the recent wave of strategic M&A reveals about the shifting tech landscape.Thanks for tuning in!Join the revenue leaders redefining growth at Pavilion's CRO Summit 2025, which will be held on June 3rd at the Denver Art Museum. Register today.Join the free Topline Slack channel to connect with 600+ revenue leaders, share insights, and keep the conversation going beyond the podcast!Subscribe to the Topline Newsletter to get the latest industry developments and emerging go-to-market trends delivered to your inbox every Thursday.Tune into The Revenue Leadership Podcast with Kyle Norton every Wednesday. Kyle dives deep into the strategies and tactics that drive success for revenue leaders like Jason Lemkins of SaaStr, Stevie Case of Vanta, and Ron Gabrisko of Databricks.Key Moments:(00:00) Introduction and Reflections on Past Guests(02:59) The Impact of AI on Education(05:56) Market Pulse Check and Economic Outlook(08:58) Navigating Challenges as Founders(11:55) Mental Health and Resilience in Business(15:04) Investor Pressures and Market Dynamics(17:48) The Importance of Adaptability in Entrepreneurship(20:59) Learning from Failure and Moving Forward(33:53) Revenue Growth and Business Optionality(34:56) Leadership Accountability and Personal Growth(36:24) Compassionate Leadership in Business(38:01) Optimism vs. Realism in Business(39:31) Market Trends and Business Strategy(42:04) Building Community and Crafting Business Assets(43:41) Market Dependency and Business Performance(46:47) The Importance of Team Building(47:15) M&A Activity and Market Dynamics

Databricks just snatched up another AI company. This week, data analytics giant announced a $1 billion acquisition of Neon, a startup building an open-source alternative to AWS Aurora Postgres. It's the latest in a spree of high-profile buys, joining MosaicML and Tabular, as Databricks positions itself as the place to build, deploy, and scale AI-native applications.  Today, on TechCrunch's Equity podcast, hosts Kirsten Korosec, Max Zeff, and Anthony Ha unpack the Databricks–Neon deal, where Neon's serverless Postgres tech fits into the larger vision, and whether $1 billion still counts as “a lot of money” these days (spoiler: Kirsten and Anthony are on the fence). Listen to the full episode to hear about: Chime's long-awaited IPO plans and what the neobank's S-1 did (and didn't) reveal. AWS entering a ‘strategic partnership' that could shake up cloud infrastructure, especially as the Middle East ramps up its AI ambitions The return of the web series. Yes, really. Short-form scripted content is back, and investors are placing big bets on nostalgic trend Equity will be back next week, so don't miss it! Equity is TechCrunch's flagship podcast, produced by Theresa Loconsolo, and posts every Wednesday and Friday.  Subscribe to us on Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod. For the full episode transcript, for those who prefer reading over listening, check out our full archive of episodes here. Credits: Equity is produced by Theresa Loconsolo with editing by Kell. We'd also like to thank TechCrunch's audience development team. Thank you so much for listening, and we'll talk to you next time. Learn more about your ad choices. Visit megaphone.fm/adchoices

Today's show: Chime is finally going public with strong financials and a shot at matching its $25B 2021 valuation, signaling real momentum in the IPO market. Databricks just made a $1B bet on agentic AI by acquiring Neon, a Postgres-as-a-service startup riding the new database wave. Then, Dave Rubin joins to share how he built and sold Locals, his uncancellable creator platform, all while navigating the intense media landscape.Timestamps:(0:00) Episode Teaser(1:14) Jason and Alex open the show(1:42) Why Chime's IPO is such a promising sign(7:22) Chime's financials and valuation(10:12) Squarespace - Use offer code TWIST to save 10% off your first purchase of a website or domain at https://www.Squarespace.com/TWIST(12:17) So why did Databricks buy Neon?(13:22) Where is the AI Integration Desktop App?(17:29) Jason's plan to bring Americans back to the movies(20:10) Northwest Registered Agent. Form your entire business identity in just 10 clicks and 10 minutes. Get more privacy, more options, and more done—visit northwestregisteredagent.com/twist today!(21:58) Make movies All-you-can-eat!(26:26) Special Guest: Dave Rubin(30:39) Lemon.io - Get 15% off your first 4 weeks of developer time at https://Lemon.io/twist(31:41) Why Dave Rubin goes phone free for weeks at a time(45:24) Why Identity politics is killing business and sports(49:23) Can Locals reinvent subscription models?Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpLinks from episode:Rubin Report on Locals: https://rubinreport.locals.com/Follow Dave:X: https://x.com/RubinReportYouTube: https://www.youtube.com/channel/UCJdKr0Bgd_5saZYqLCa9mngFollow Lon:X: https://x.com/lonsFollow Alex:X: https://x.com/alexLinkedIn: ⁠https://www.linkedin.com/in/alexwilhelmFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisThank you to our partners:(10:12) Squarespace - Use offer code TWIST to save 10% off your first purchase of a website or domain at https://www.Squarespace.com/TWIST(20:10) Northwest Registered Agent. Form your entire business identity in just 10 clicks and 10 minutes. Get more privacy, more options, and more done—visit northwestregisteredagent.com/twist today!(30:39) Lemon.io - Get 15% off your first 4 weeks of developer time at https://Lemon.io/twistGreat TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarlandCheck out Jason's suite of newsletters: https://substack.com/@calacanisFollow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: https://twistartups.substack.comSubscribe to the Founder University Podcast: https://www.youtube.com/@founderuniversity1916

As AI reshapes the retail advertising landscape, are you leveraging it as a competitive advantage, or are you at risk of being left behind in a data-driven world? Today, we're joined by Uldis Baumerts, Chief Operating Officer of Bryj Technologies, a leader in driving AI-powered innovations for the retail industry. Uldis has extensive experience in transforming the way businesses approach advertising and customer engagement, making him the perfect guest to discuss the transformational role of AI in retail advertising and the future of marketing technology. We're going to be talking about Bryj's recent report, The 2025 Ultimate Guide to AI in Advertising and Retail Marketing, and more Uldis Baumerts, COO at Bryj Technologies, Inc. With over 15 years of experience leading AI-powered product development, large-scale e-commerce platforms, and global IT operations, I specialize in turning strategic vision into innovative, scalable solutions. My leadership is defined by a data-driven approach, technical proficiency, and a track record of delivering measurable business results in fast-paced, high-growth environments. AI & Technology Leadership As COO of Bryj Technologies, I lead cross-functional teams in driving the company's AI-powered mobile engagement platform. I spearheaded the launch of ChatROI, a solution that delivers 15-30% performance uplift for customers and reduces campaign creation time by up to 10-15x. By integrating large language models (LLMs) and Databricks-powered analytics, I ensure our solutions remain at the forefront of innovation, driving both product differentiation and customer success. Key Achievements: Over 15 years of experience in tech leadership, product innovation, and IT operations. Led the growth of a tech organization from 25 to 500+ professionals, with 300% revenue growth over 4 years. Delivered 350+ enterprise e-commerce projects across 23 countries. Launched an AI-powered solution that drove 15-30% performance improvements and 10-15x faster campaign creation for clients. Improved operational efficiency by 20% through agile transformations and scalable delivery frameworks. I am passionate about using AI and emerging technologies to drive innovation, unlock new growth opportunities, and create lasting business impact. If your organization seeks a leader with a proven ability to scale operations, execute complex projects, and deliver cutting-edge solutions, I'm ready to lead the charge. RESOURCES Bryj: https://www.bryj.ai Bryj: AI in Retail Marketing Guide: https://www.bryj.ai/unlock-the-potential-of-ai-in-retail-marketing-with-a-step-by-step-guide/ Catch the future of e-commerce at eTail Boston, August 11-14, 2025. Register now: https://bit.ly/etailboston and use code PARTNER20 for 20% off for retailers and brands Don't Miss MAICON 2025, October 14-16 in Cleveland - the event bringing together the brights minds and leading voices in AI. Use Code AGILE150 for $150 off registration. Go here to register: https://bit.ly/agile150 Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstrom Don't miss a thing: get the latest episodes, sign up for our newsletter and more: https://www.theagilebrand.show Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://www.teksystems.com/versionnextnow The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company