Podcasts about Databricks

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

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

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

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

In this episode, Lois Houston and Nikita Abraham dive into key components of Oracle GoldenGate 23ai with expert insights from Nick Wagner, Senior Director of Product Management.   They break down the Distribution Service, explaining how it moves trail files between environments, replaces the classic extract pump, and ensures secure data transfer. Nick also introduces Target Initiated Paths, a method for connecting less secure environments to more secure ones, and discusses how the Receiver Service simplifies monitoring and management. The episode wraps up with a look into Initial Load, covering different methods for syncing source and target databases without downtime.   Oracle GoldenGate 23ai: Fundamentals: https://mylearn.oracle.com/ou/course/oracle-goldengate-23ai-fundamentals/145884/237273 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. ----------------------------------------------------------------- Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:25 Nikita: Welcome to the Oracle University Podcast! I'm Nikita Abraham, Team Lead of Editorial Services with Oracle University, and with me is Lois Houston, Director of Innovation Programs.  Lois: Hey there! Last week, we spoke about the Extract process and today we're going to spend time discussing the Distribution Path, Target Initiated Path, Receiver Server, and Initial Load. These are all critical components of the GoldenGate architecture, and understanding how they work together is essential for successful data replication. 00:58 Nikita: To help us navigate these topics, we've got Nick Wagner joining us again. Nick is a Senior Director of Product Management for Oracle GoldenGate. Hi Nick! Thanks for being with us today. To kick things off, can you tell us what the distribution service is and how it works? Nick: A distribution path is used when we need to send trail files between two different GoldenGate environments. The distribution service replaces the extract pump that was used in GoldenGate classic architecture. And so the distribution service will send the trail files as they're being created to that receiver service and it will write the trail files over on the target system. The distribution service works in a kind of a streaming fashion, so it's constantly pulling the trail files that the extract is creating to see if there's any new data. As soon as it sees new data, it'll packet it up and send it across the network to the receiver service. It can use a couple of different methods to do this. The most secure and recommended method is using a WebSocket secure connection or WSS. If you're going between a microservices and a classic architecture, you can actually tell the distribution service to send it using the classic architecture method. In that case, it's the OGG option when you're configuring the distribution service. There's also some unsecured methods that would send the trail files in plain text. The receiver service is then responsible for taking that data and rewriting it into the trail file on the target site. 02:23 Lois: Nick, what are some of the key features and responsibilities of the distribution service? Nick: It's responsible for command deployment. So any time that you're going to actually make a command to the distribution service, it gets handled there directly. It can handle multiple commands concurrently. It's going to dispatch trail files to one or more receiver servers so you can actually have a single distribution path, send trail files to multiple targets. It can provide some lightweight filtering so you can decide which tables get sent to the target system. And it also is integrated in with our data streams, our pub and subscribe model that we've added in GoldenGate 23ai. 03:01 Lois: Interesting. And are there any protocols to remember when using the distribution service? Nick: We always recommend a secure WebSocket. You also have proxy support for use within cloud environments. And then if you're going to a classic architecture GoldenGate, you would use the Oracle GoldenGate protocol. So in order to communicate with the distribution service and send it commands, you can communicate directly from any web browser, client software-- installation is not required-- or you can also do it through the admin client if necessary, but you can do it directly through browsers. 03:33 Nikita: Ok, let's move on to the target initiated path. Nick, what is it and what does it do essentially? Nick: This is used when you're communicating from a less secure environment to a more secure environment. Often, this requires going through some sort of DMZ. In these situations, a connection cannot be established from the less secure environment into the more secure environment. It actually needs to be established from the more secure environment out. And so if we need to replicate data into a more secure environment, we need to actually have the target GoldenGate environment initiate that connection so that it can be established.  And that's what a target-initiated path does. 04:12 Lois: And how do you set it up? Nick: It's pretty straightforward to set up. You actually don't even need to worry about it on the source side. You actually set it up and configure it from the target. The receiver service is responsible for receiving the trail file data and writing it to the local trail file. In this situation, we have a target-initiated path created. And so that receiver service is going to write the trail files locally and the replicat is going to apply that data into that target system. 04:37 Nikita: I also want to ask you about the Receiver service. What is it really? Nick: Receiver service is pretty straightforward. It's a centrally controlled service. It allows you to view the status of your distribution path and replaces target side collectors that were available in the classic architecture of GoldenGate. You can also get statistics about the receiver service directly from the web UI.  You can get detailed information about these paths by going into the receiver service and identifying information like network details, transfer protocols, how many bytes it's received, how many bytes it's sent out. If you need to issue commands from the admin client to the receiver service, you can use the info command to get details about it. Info all will tell you everything that's running. And you can see that your receiver service is up and running. 05:28 Are you working towards an Oracle Certification this year? Join us at one of our certification prep live events in the Oracle University Learning Community. Get insider tips from seasoned experts and learn from others who have already taken their certifications. Go to community.oracle.com/ou to jump-start your journey towards certification today! 05:53 Nikita: Welcome back. In the last section of today's episode, we'll cover what Initial Load is. Nick, can you break down the basics for us? Nick: So, the initial load is really used when you need to synchronize the source and target systems. Because GoldenGate is designed for 24/7 environments, we need to be able to do that initial load without taking downtime on the source. And so all the methods that we talk about do not require any downtime for that source database. 06:18 Lois: How do you do the initial load? Nick: So there's a couple of different ways to do the initial load. And it really depends on what your topology is. If I'm doing like-to-like replication in a homogeneous environment, we'll say Oracle-to-Oracle, the best options are to use something that's integrated with GoldenGate, some sort of precise instantiation method that does not require HandleCollisions. That's something like a database backup and restoring it to a specific SDN or CSN value using a Database Snapshot. Or in some cases, we can use Oracle Data Pump integration with GoldenGate. There are some less precise instantiation options, which do require HandleCollisions. We also have dissimilar initial load methods. And this is typically when you're going between heterogeneous environments. When my source and target databases don't match and there isn't any kind of fast unload or fast load utility that I could use between those two databases. In almost all cases, this does require HandleCollisions to be used. 07:16 Nikita: Got it. So, with so many options available, are there any advantages to using GoldenGate's own initial load method?  Nick: While some databases do have very good fast load and unload utilities, there are some advantages to using GoldenGate's own initial load method. One, it supports heterogeneous replication environments. So if I'm going from Postgres to Oracle, it'll do all the data type transformation, character set transformation for me. It doesn't require any downtime, if certain conditions are met.  It actually performs transformation as the data is loaded, too, as well as filtering. And so any transformation that you would be doing in your normal transaction log replication or CDC replication can also go through the same transformation for the initial load process. GoldenGate's initial load process does read directly from the source tables. And it fetches the data in arrays. It also uses parallel processing to speed up the replication. It does also handle activity on the source tables during the initial load process, so you do not need to worry about quiescing that source database. And a lot of the initial load methods directly built into GoldenGate support distributed application analytics targets, including things like Databricks, Snowflake, BigQuery. 08:28 Lois: And what about its limitations? Or to put it differently, when should users consider using different methods? Nick: So the first thing to consider is system proximity. We want to make sure that the two systems we're working with are close together. Or if not, how are we going to send the data across? One thing to keep in mind, when we do the initial load, the source database is not quiesced. So if it takes an hour to do the initial load or 10 hours, it really doesn't matter to GoldenGate. So that's something to keep in mind. Even though we talk about performance of this, the performance really isn't as critical as one might suspect. So the important thing about data system proximity is the proximity to the extract and replicat processes that are going to be pulling the data out and pushing it across. And then how much data is generated? Are we talking about a database that's just a couple of gigabytes? Or are we talking about a database that's hundreds of terabytes? Do we want to consider outage time? Would it be faster to take a little bit of outage and use some other method to move the data across? What kind of outage or downtime windows do we have for these environments? And then another consideration is disk space. As we're pulling the data out of that source database, we need to have somewhere to store it. And if we don't have enough disk space, we need to run to temporary space or to use multiple external drives to be able to support it. So these are all different considerations. 09:50 Nikita: I think we can wind up our episode with that. Thanks, Nick, for giving us your insights.  Lois: If you'd like to learn more about the topics we covered today, head over to mylearn.oracle.com and check out the Oracle GoldenGate 23ai: Fundamentals course. Nikita: In our next episode, Nick will take us through the Replicat process. Until then, this is Nikita Abraham… Lois: And, Lois Houston signing off! 10:14 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

This episode unpacks what this deal means for the future of data and AI. This podcast looks at the synergy between Neon's innovations and Databricks' goals. Learn how Neon's technology fits into Databricks' larger platform strategy.Try AI Box: ⁠⁠https://AIBox.ai/⁠⁠AI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustle/about

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/

Hear why industry insiders are calling this a game-changing acquisition. This podcast looks at the synergy between Neon's innovations and Databricks' goals. We break down how this move reshapes the market for AI-ready data platforms.Try AI Box: ⁠⁠https://AIBox.ai/⁠⁠AI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustle/about

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.   

A valeparaibense Nara fez colégio técnico industrial e, logo em seguida, engatou a formação em engenharia de materiais, o que incluiu projetos de iniciação científica.Com um doutorado, mestrado e pós-doutorado no currículo, não demorou para ela passar a ser encontrada no LinkedIn com ofertas para o exterior. Graças a algumas passagens pelos EUA, Chile, França e Canadá durante a pós-graduação e, a Nara foi galgando oportunidades até surgir a chance de trabalhar em Denver, cidade que ela já havia conhecido e pela qual ela já havia se apaixonado.Neste episódio, a Nara detalha sua trajetória entre a academia e a indústria, e comenta o que existe de legal para fazer na terra dos Rockies que não são Rookies.Fabrício Carraro, o seu viajante poliglotaNara Guimarães, Engenheira de Dados em Denver, Estados UnidosLinks:Medium da NaraConheça a Formação Engenharia de dados com Databricks da Alura e aprenda a realizar a análise exploratória de conjuntos de dados, criar modelos de machine learning e processar grandes volumes de dados.TechGuide.sh, um mapeamento das principais tecnologias demandadas pelo mercado para diferentes carreiras, com nossas sugestões e opiniões.#7DaysOfCode: Coloque em prática os seus conhecimentos de programação em desafios diários e gratuitos. Acesse https://7daysofcode.io/Ouvintes do podcast Dev Sem Fronteiras têm 10% de desconto em todos os planos da Alura Língua. Basta ir a https://www.aluralingua.com.br/promocao/devsemfronteiras/e começar a aprender inglês e espanhol hoje mesmo! Produção e conteúdo:Alura Língua Cursos online de Idiomas – https://www.aluralingua.com.br/Alura Cursos online de Tecnologia – https://www.alura.com.br/Edição e sonorização: Rede Gigahertz de Podcasts

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

In this first part of Microsoft Build special, the trio dive into the announcements that matter and a few side notes from the conference: yes, there was more than just tech making noise this year. Starting with Windows AI Foundry and the new Model Concept Protocol. and exploring updates to Microsoft 365 Copilot, including tuning and multi-agent orchestration.Fabric gets its share of love too, with the CLI hitting GA, updates like shortcut transformations and SPN support, and a quick take on Fabric Data Agents. As the last bit they cover what's new in Azure AI Foundry, from local options to Databricks connector.Show notes Hosted on Acast. See acast.com/privacy for more information.

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

We break down how this move reshapes the market for AI-ready data platforms. Understand the strategic vision that drove Databricks to acquire Neon. This podcast looks at the synergy between Neon's innovations and Databricks' goals.Try AI Box: ⁠⁠https://AIBox.ai/⁠⁠AI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustle/about

Learn how Neon's technology fits into Databricks' larger platform strategy. We explore Databricks' $1B acquisition of the AI database startup Neon. We analyze the competitive landscape in AI data platforms post-acquisition.Try AI Box: ⁠⁠https://AIBox.ai/⁠⁠AI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustle/about

This episode unpacks what this deal means for the future of data and AI. Learn how Neon's technology fits into Databricks' larger platform strategy. Understand the strategic vision that drove Databricks to acquire Neon.Try AI Box: ⁠⁠https://AIBox.ai/⁠⁠AI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustle/about

We break down how this move reshapes the market for AI-ready data platforms. Understand the strategic vision that drove Databricks to acquire Neon. Discover how Databricks is expanding its footprint in the AI infrastructure space.Try AI Box: ⁠⁠https://AIBox.ai/⁠⁠AI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustle/about

Installing Oracle GoldenGate 23ai is more than just running a setup file—it's about preparing your system for efficient, reliable data replication. In this episode, Lois Houston and Nikita welcome back Nick Wagner to break down system requirements, storage considerations, and best practices for installing GoldenGate.   You'll learn how to optimize disk space, manage trail files, and configure network settings to ensure a smooth installation.   Oracle GoldenGate 23ai: Fundamentals: https://mylearn.oracle.com/ou/course/oracle-goldengate-23ai-fundamentals/145884/237273 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   -------------------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:25 Nikita: Hello and welcome to Oracle University Podcast! I'm Nikita Abraham, Team Lead of Editorial Services with Oracle University, and I'm joined by Lois Houston, Director of Innovation Programs.  Lois: Hi there! Last week, we took a close look at the security strategies of Oracle GoldenGate 23ai. In this episode, we'll discuss all aspects of installing GoldenGate. 00:48 Nikita: That's right, Lois. And back with us today is Nick Wagner, Senior Director of Product Management for GoldenGate at Oracle. Hi Nick! I'm going to get straight into it. What are the system requirements for a typical GoldenGate installation? Nick: As far as system requirements, we're going to split that into two sections. We've got an operating system requirements and a storage requirements. So with memory and disk, and I know that this isn't the answer you want, but the answer is that it varies. With GoldenGate, the amount of CPU usage that is required depends on the number of extracts and replicats. It also depends on the number of threads that you're going to be using for those replicats. Same thing with RAM and disk usage. That's going to vary on the transaction sizes and the number of long running transactions. 01:35 Lois: And how does the recovery process in GoldenGate impact system resources?  Nick: You've got two things that help the extract recovery. You've got the bonded recovery that will store transactions over a certain length of time to disk. It also has a cache manager setting that determines what gets written to disk as part of open transactions. It's not just the simple answer as, oh, it needs this much space. GoldenGate also needs to store trail files for the data that it's moving across. So if there's network latency, or if you expect a certain network outage, or you have certain SLAs for the target database that may not be met, you need to make sure that GoldenGate has enough room to store its trail files as it's writing them. The good news about all this is that you can track it. You can use parameters to set them. And we do have some metrics that we'll provide to you on how to size these environments. So a couple of things on the disk usage. The actual installation of GoldenGate is about 1 to 1.5 gig in size, depending on which version of GoldenGate you're going to be using and what database. The trail files themselves, they default to 500 megabytes apiece. A lot of customers keep them on disk longer than they're necessary, and so there's all sorts of purging options available in GoldenGate. But you can set up purge rules to say, hey, I want to get rid of my trail files as soon as they're not needed anymore. But you can also say, you know what? I want to keep my trail files around for x number of days, even if they're not needed. That way they can be rebuilt. I can restore from any previous point in time. 03:15 Nikita: Let's talk a bit more about trail files. How do these files grow and what settings can users adjust to manage their storage efficiently? Nick: The trail files grow at about 30% to 35% of the generated redo log data. So if I'm generating 100 gigabytes of redo an hour, then you can expect the trail files to be anywhere from 30 to 35 gigabytes an hour of generated data. And this is if you're replicating everything. Again, GoldenGate's got so many different options. There's so many different ways to use it. In some cases, if you're going to a distributed applications and analytics environment, like a Databricks or a Snowflake, you might want to write more information to the trail file than what's necessary. Maybe I want additional information, such as when this change happened, who the user was that made that change. I can add specific token data. You can also tell GoldenGate to log additional records or additional columns to the trail file that may not have been changed. So I can always say, hey, GoldenGate, replicate and store the entire before and after image of every single row change to your trail file, even if those columns didn't change. And so there's a lot of different ways to do it there. But generally speaking, the default settings, you're looking at about 30% to 35% of the generated redo log value. System swap can fill up quickly. You do want this as a dedicated disk as well. System swap is often used for just handling of the changes, as GoldenGate flushes data from memory down to disk. These are controlled by a couple of parameters. So because GoldenGate is only writing committed activity to the trail file, the log reader inside the database is actually giving GoldenGate not only committed activity but uncommitted activity, too. And this is so it can stay very high speed and very low latency. 05:17 Lois: So, what are the parameters? Nick: There's a cache manager overall feature, and there's a cache directory. That directory controls where that data is actually stored, so you can specify the location of the uncommitted transactions. You can also specify the cache size. And there's not only memory settings here, but there's also disk settings. So you can say, hey, once a cache size exceeds a certain memory usage, then start flushing to disk, which is going to be slower. This is for systems that maybe have less memory but more high-speed disk. You can optimize these parameters as necessary. 05:53 Nikita: And how does GoldenGate adjust these parameters? Nick: For most environments, you're just going to leave them alone. They're automatically configured to look at the system memory available on that system and not use it all. And then as soon as necessary, it'll overflow to disk. There's also intelligent settings built within these parameters and within the cache manager itself that if it starts seeing a lull in activity or your traditional OLTP type responses to actually free up the memory that it has allocated. Or if it starts seeing more activity around data warehousing type things where you're doing large transactions, it'll actually hold on to memory a little bit longer. So it kinda learns as it goes through your environment and starts replicating data. 06:37 Lois: Is there anything else you think we should talk about before we move on to installing GoldenGate?  Nick: There's a couple additional things you need to think of with the network as well. So when you're deploying GoldenGate, you definitely want it to use the fastest network.  GoldenGate can also use a reverse proxy, especially important with microservices. Reverse proxy, typically we recommend Nginx. And it allows you to access any of the GoldenGate microservices using a single port.  GoldenGate also needs either host names or IP addresses to do its communication and to ensure the system is available. It does a lot of communication through TCP and IP as well as WSS. And then it also handles firewalls. So you want to make sure that the firewalls are open for ingress and egress for GoldenGate, too. There's a couple of different privileges that GoldenGate needs when you go to install it. You'll want to make sure that GoldenGate has the ability to write to the home where you're installing it. That's kind of obvious, but we need to say it anyways. There's a utility called oggca.sh. That's the GoldenGate Configuration Assistant that allows you to set up your first deployments and manage additional deployments. That needs permissions to write to the directories where you're going to be creating the new deployments. The extract process needs connection and permissions to read the transaction logs or backups. This is not important for Oracle, but for non-Oracle it is. And then we also recommend a dedicated database user for the extract and replicat connections. 08:15 Are you keen to stay ahead in today's fast-paced world? We've got your back! Each quarter, Oracle rolls out game-changing updates to its Fusion Cloud Applications. And to make sure you're always in the know, we offer New Features courses that give you an insider's look at all of the latest advancements. Don't miss out! Head over to mylearn.oracle.com to get started. 08:41 Nikita: Welcome back! So Nick, how do we get started with the installation?  Nick: So when we go to the install, the first thing you're going to do is go ahead and go to Oracle's website and download the software. Because of the way that GoldenGate works, there's only a couple moving parts. You saw the microservices. There's five or six of them. You have your extract, your replicat, your distribution service, trail files. There's not a lot of moving components. So if something does go wrong, usually it affects multiple customers. And so it's very important that when you go to install GoldenGate, you're using the most recent bundle patch. And you can find this within My Oracle Support. It's not always available directly from OTN or from the Oracle e-delivery website. You can still get them there, but we really want people going to My Oracle Support to download the most recent version. There's a couple of environment variables and certificates that you'll set up as well. And then you'll run the Configuration Assistant to create your deployments.  09:44 Lois: Thanks, Nick, for taking us though the installation of GoldenGate. Because these are highly UI-driven topics, we recommend that you take a deep dive into the GoldenGate 23ai Fundamentals course, available on mylearn.oracle.com. Nikita: In our next episode, we'll talk about the Extract process. Until then, this is Nikita Abraham… Lois: And Lois Houston signing off! 10:08 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

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.

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

Send us a textWhat a power couple! I am extremely grateful for this conversation with Miri and Rob and for them opening up about their gutsy moves, career trajectories, life-changing marathon experiences, their relationship, and how they seek to continue making an impact. Miri Buckland is co-founder and co-CEO of Zeen, a design tool for tastemakers. A serial consumer technology entrepreneur, Miri previously scaled Landing, Gen Z's Pinterest, to over 1.2M global users, raising $9M in venture funding and earning recognition from Apple, TechCrunch, and Forbes 30 under 30. Miri holds an MBA from Stanford GSB, lives in New York, and ran her first marathon last year (thanks to Pursuit of Performance training camp).  Links:Zeen: https://info.myzeen.app/Miri IG: https://www.instagram.com/miribucklandZeen IG: https://www.instagram.com/myzeenappRob Dalto is the Co-Founder and President of Bronx Burners, a Bronx-based 501(c)(3) organization creating community and opportunity through sport. Rob has 15 years of experience working in enterprise tech companies like AWS and Databricks. He leverages his tech experience to share his passion for health tech, fitness, and inclusion with his 100k social community, documenting his journey through 30+ marathons across the world. Rob holds an MBA from NYU Stern and aspires to be as fast as Miri one day. Rob IG: https://www.instagram.com/pursuitofperformance__?igsh=d3RwYzY5dHZ5d3k5Burners: www.bronxburnersrc.orgSupport the show Come say hi! Instagram: https://www.instagram.com/itsclaudiaramirez/Email: hello@theclaudiaramirez.com Can't wait to see you in one of my courses/programs! I believe in you

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.

The Big Themes:SAP's Flywheel Strategy: SAP introduced a compelling flywheel model that integrates applications, data, and AI to drive enterprise momentum. The idea is that integrated applications generate structured data, which then feeds a robust AI layer. As these layers build on one another, they create a self-reinforcing cycle of productivity, insight, and innovation—a flywheel effect. Unlike Microsoft and ServiceNow, which predict the collapse of applications in favor of agents, SAP asserts that AI agents will enhance, not replace, applications.The Business Data Cloud and Databricks Partnership: A highlight of the event was SAP's Business Data Cloud (BDC), launched in partnership with Databricks. This foundational layer brings together internal SAP data and external sources like Moody's or climate models, enabling richer decision-making. SAP showcased real-world use cases, such as tariff fluctuation impact analysis across supply chains, to demonstrate the power of combining enterprise and contextual data.Prompt Optimizer and the End of Prompt Engineering: SAP's introduction of a “Prompt Optimizer” signals a shift in the AI interface landscape. Instead of manual prompt engineering, users will soon rely on AI to manage and optimize prompts across multiple large language models (LLMs), including ChatGPT, Claude, Gemini, and Perplexity. CTO Philipp Herzig even declared we're at “the beginning of the end” of prompt engineering.The Big Quote: "[Customers are] not ready to deploy AI and have that completely eliminate the need for apps. The data is just not there. So, maybe five years from now, let's see what progress we've made. But what's in the here and now is that customers are looking for applications."

Are you struggling to eliminate friction as data regulations heighten? Noah Levine and Adrian Bolosan join the conversation to discuss cost-efficient innovations in data modernization. Learn from Databricks experts about the zero data movement and the future of walled gardens. Thanks for listening! Follow us on Twitter and Instagram or find us on Facebook.

SuperAnnotate is revolutionizing how companies manage their AI training data with a comprehensive infrastructure platform. Having raised over $53 million in funding, SuperAnnotate has evolved from a specialized algorithm for autonomous vehicles to a centralized data hub that enables enterprises to collaborate with multiple service providers and internal teams. In this episode of Category Visionaries, we spoke with Vahan Petrosyan, CEO and Co-Founder of SuperAnnotate, who shared his journey from PhD student to tech founder and unpacked his vision for creating what he describes as "a database for training data" - similar to Databricks but specialized for AI training data. Topics Discussed: SuperAnnotate's evolution from algorithm to comprehensive data labeling infrastructure The journey from academic research to founding a tech startup How an early contract with an autonomous driving company validated their solution The strategic pivot from competing with service providers to creating a collaborative ecosystem The transformation of their go-to-market strategy to create stickier enterprise relationships SuperAnnotate's focus on building a centralized training data platform for enterprise AI The importance of automation and "SuperAnnotate agents" for AI data operations How customizability has enabled SuperAnnotate to support diverse generative AI use cases GTM Lessons For B2B Founders: Recognize when to stop competing and start collaborating: Vahan's most important go-to-market decision was shifting from competing with service providers to creating an infrastructure that enables collaboration. "That's one of the mindset shifts... we are trying to build an ecosystem with our partners, not really trying to compete with them," he explains. B2B founders should consider whether creating an ecosystem platform might be more valuable than directly competing in fragmented service markets. Solution engineers are crucial for enterprise AI sales: Vahan emphasized that "solution engineering is super important because as you're touching enterprise AI, your solution engineers are more or less the core part of your team." Without proper technical enablement, enterprise customers won't be able to implement complex AI solutions. B2B founders selling sophisticated technology should invest heavily in solution engineering capabilities. Build for adaptability in rapidly evolving markets: SuperAnnotate achieved 3x growth by making their platform "fully customizable to any use case." Vahan noted, "If tomorrow there will be a new agentic workflow, then we'll be able to support it." Rather than offering point solutions, B2B founders in emerging technology spaces should build adaptable platforms that can evolve with changing market needs. Passive fundraising often yields better results than active campaigns: Vahan shared a counterintuitive fundraising insight: "Whenever I was actively fundraising, I was doing something wrong." His most successful raises came from casual coffees with investors who approached him, not from pitching dozens of VCs. B2B founders might benefit from focusing on building relationships and demonstrating value rather than running intensive fundraising campaigns. Enterprise AI is a long-term bet: Looking 3-5 years ahead, Vahan sees enterprise AI as the major opportunity. "Companies have datasets sitting in silos, but that dataset is gold," he explains. The ability to "transform that dataset to training data in a fast and accurate manner will define your moat moving forward." B2B founders should consider how their solutions can help enterprises unlock value from proprietary data.   //   Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe.  www.GlobalTalent.co  

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

This week, we discuss Zenoss finally getting acquired, Databricks buying Neon, and the debut of WizOS. Plus, updates on OpenAI, Google, Apple—and hot takes on Marmite, Vegemite, and Emacs. Watch the YouTube Live Recording of Episode (https://www.youtube.com/live/gtm8WopIaOM?si=NsjyGL8As3sTLg7P) 519 (https://www.youtube.com/live/gtm8WopIaOM?si=NsjyGL8As3sTLg7P) Runner-up Titles Vegemite is still bad You're probably eating it It's a bold statement This episode's all about us Pendantic is my jam They tell you they're making “calculated bets” Rupert SlackGPT No one knows anything, do everything Rundown Marmite Rice Cakes (https://groceries.morrisons.com/products/marmite-rice-cakes/109658607) M&A Virtana Acquires Zenoss to Deliver the Industry's Deepest and Broadest Observability Platform (https://www.virtana.com/press-release/virtana-acquires-zenoss-to-deliver-the-industrys-deepest-and-broadest-observability-platform/) Databricks Agrees to Acquire Neon to Deliver Serverless Postgres for Developers + AI Agents - Databricks (https://www.databricks.com/company/newsroom/press-releases/databricks-agrees-acquire-neon-help-developers-deliver-ai-systems) Introducing WizOS: Securing Wiz from the ground up with hardened, near-zero-CVE container base images. (https://www.wiz.io/blog/introducing-wizos-hardened-near-zero-cve-base-images) Checking on OpenAI Evolving OpenAI's structure (https://openai.com/index/evolving-our-structure/) OpenAI caves to pressure, keeps nonprofit in charge (https://www.theregister.com/2025/05/05/openai_keep_nonprofit_in_charge/) OpenAI Hires Instacart C.E.O. to Run Business and Operations (https://www.nytimes.com/2025/05/08/technology/openai-fidji-simo.html) OpenAI Reaches Agreement to Buy Startup Windsurf for $3 Billion (https://www.bloomberg.com/news/articles/2025-05-06/openai-reaches-agreement-to-buy-startup-windsurf-for-3-billion) Anysphere, which makes Cursor, has reportedly raised $900M at $9B valuation (https://techcrunch.com/2025/05/04/cursor-is-reportedly-raising-funds-at-9-billion-valuation-from-thrive-a16z-and-accel/) Checking in on Google Google Search traffic decline is inevitable, execs say (https://searchengineland.com/google-search-traffic-decline-inevitable-455345) Google tests replacing 'I'm Feeling Lucky' with 'AI Mode' (https://techcrunch.com/2025/05/13/google-tests-replacing-im-feeling-lucky-with-ai-mode/) Checking on Apple Apple To Appeal Judge's Scathing New Ruling In Epic Games Antitrust Case, Says CEO Tim Cook (https://deadline.com/2025/05/apple-to-appeal-ruling-in-epic-games-fortnite-antitrust-case-1236383340/) Eddy Cue is fighting to save Apple's $20 billion paycheck from Google (https://www.theverge.com/policy/662974/google-search-remedies-trial-eddy-cue-apple-deal-ai) PayPal Brings Contactless Payments to German iPhones Under New EU Rule (https://www.macrumors.com/2025/05/13/paypal-contactless-payments-germany/) emacs — Matt Gemmell (https://mattgemmell.scot/emacs/) Relevant to your Interests New Netflix UI (https://about.netflix.com/en/news/unveiling-our-innovative-new-tv-experience) VMware perpetual license holders receive cease-and-desist letters from Broadcom (https://arstechnica.com/gadgets/2025/05/broadcom-sends-cease-and-desist-letters-to-subscription-less-vmware-users/) The EC2 Pricing Form is 284 MB JSON File? (https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonEC2/current/ap-southeast-2/index.json) Has DOGE missed its opportunity? (https://www.nextgov.com/ideas/2025/05/has-doge-missed-its-opportunity/405125/) Thanks to DOGE, Gumroad's founder has a second job with the VA (https://www.fastcompany.com/91330297/doge-sahil-lavignia-gumroad) Microsoft employees are banned from using DeepSeek app, president says (https://techcrunch.com/2025/05/08/microsoft-employees-are-banned-from-using-deepseek-app-president-says/) AI Is Like a Crappy Consultant (https://lukekanies.com/writing/ai-is-like-a-crappy-consultant/) You can now submit your claims for Apple's $95 million Siri spying settlement (https://www.theverge.com/news/663166/apple-siri-audio-recording-lawsuit-payout-applications) Microsoft laying off about 6,000 people, or 3% of its workforce (https://www.cnbc.com/2025/05/13/microsoft-is-cutting-3percent-of-workers-across-the-software-company.html) The Case for Open AI Tooling: Why Developers Need Sovereignty in the AI Era (https://thenewstack.io/the-case-for-open-ai-tooling-why-developers-need-sovereignty-in-the-ai-era/) DeepSeek's ‘Tech Madman' Founder Is Threatening US Dominance in AI Race (https://www.bloomberg.com/news/features/2025-05-13/deepseek-races-after-chatgpt-as-china-s-ai-industry-soars) Microsoft laying off about 6,000 people, or 3% of its workforce (https://www.cnbc.com/2025/05/13/microsoft-is-cutting-3percent-of-workers-across-the-software-company.html) GM unveils new 'groundbreaking' EV battery tech, aims to be first to market (https://www.cnbc.com/2025/05/13/gm-new-ev-battery-tech.html) Exclusive: Slate Auto has already racked up more than 100,000 refundable reservations (https://techcrunch.com/2025/05/12/slate-auto-crosses-100000-refundable-reservations-in-two-weeks) Nonsense Meet Vulcan, the first Amazon robot with a sense of touch (https://www.cnbc.com/video/2025/05/07/meet-vulcan-the-first-amazon-robot-with-a-sense-of-touch.html) Fyre Festival's embattled founder is selling the brand: 'It's time to pass the torch' (https://www.npr.org/2025/04/24/nx-s1-5374909/fyre-festival-for-salrl-billy-mcfarland) Conferences NDC Oslo (https://ndcoslo.com/), May 21st-23th, Coté speaking. 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: Sinners (https://www.rottentomatoes.com/m/sinners_2025) Matt: Devs (https://www.imdb.com/title/tt8134186/) — first recommended by Brandon on episode 223 (https://www.softwaredefinedtalk.com/223) Photo Credits Header (https://unsplash.com/s/photos/Vegemite?license=free&orientation=landscape)

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

When Sam Jacobs founded Pavilion, formerly Revenue Collective, he set out to build a private community for operators in a startup world that traditionally celebrated only founders and operators. But after the community grew rapidly, now totaling 10,000+ members, questions arose about whether the once-exclusive membership had become too open. In this special Topline Spotlight episode, Sam joins co-hosts AJ Bruno and Asad Zaman to discuss how rapid expansion diluted the community's focus, what it took to course-correct, and why building something great takes time—and restraint.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!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(00:42) Business Challenge of the Last 24 Months(01:29) What Is Pavilion?(02:43) Launching Pavilion Gold(04:01) Why the Community Scaled So Quickly(06:51) LinkedIn and Slack as Growth Drivers(07:02) Shifting Culture of Openness Among GTM Leaders(08:04) The Consequences of Losing Focus(10:54) The Biggest Mistake: Removing the Qualification Barrier(11:32) The Challenge of Reversing Course(13:46) Continued Opportunity for Operator Advocacy(15:00) Solving the Challenge: Long-Term Vision(15:54) Building a 3-Year Vision for Pavilion(16:08) Importance of Patience in Building Exclusive Communities

In this conversation, Jaeden discusses the recent acquisition of the database startup Neon by Databricks for $1 billion. He highlights the innovative features of Neon, which focuses on AI-driven database management, and contrasts it with Databricks' growth strategy.Try AI Box: ⁠⁠https://AIBox.ai/⁠⁠AI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustle/aboutTakeawaysDatabricks acquired Neon for $1 billion, focusing on AI-driven databases.AI Box offers a platform for accessing multiple AI models.Neon allows developers to clone databases and scale resources automatically.80% of databases on Neon are created by AI agents.Databricks has raised $19 billion, enabling significant acquisitions.Neon provides an open-source alternative to AWS's Aurora Postgres.The acquisition aligns with Databricks' push into AI technology.Databricks has a history of making multi-billion dollar acquisitions.The growth of Neon showcases the potential of AI in database management.The conversation emphasizes the importance of innovation in tech acquisitions.

Databricks CEO talks with Deirdre Bosa about the company's $1B deal to acquire cloud-based database software vendor Neon, and the rapidly evolving AI landscape. Plus, we walk through what to watch in AI Infrastructure Coreweave's first quarterly report since its March IPO. 

MLOps with Databricks // MLOps Podcast #314 with Maria Vechtomova, MLOps Tech Lead | Founder at Ahold Delhaize | Marvelous MLOps.Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractThe world of MLOps is very complex as there is an endless amount of tools serving its purpose, and it is very hard to get your head around it. Instead of combining various tools and managing them, it may make sense to opt for a platform instead. Databricks is a leading platform for MLOps. In this discussion, I will explain why it is the case, and walk you through Databricks MLOps features.// BioMaria is an MLOps Tech lead with over 10 years of experience in Data and AI.For the last 8 years, Maria has focused on MLOps and helped to establish MLOps best practices at large corporations.Together with her colleague, she co-founded Marvelous MLOps to share knowledge on MLOps via training, social media posts, and blogs.// Related LinksWebsite: marvelousmlops.ioMLOps Course discount code: MLOPS100 for the podcast listeners - https://maven.com/marvelousmlops/mlops-with-databricks?promoCode=MLOPS100~~~~~~~~ ✌️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 Maria on LinkedIn: /maria-vechtomovaTimestamps:[00:00] Maria's preferred coffee[00:42] Takeaways[02:48] Why Databricks for MLOps[09:56] Platform Adoption vs Procurement Pain[12:56] Databricks Best Practices[16:57] Feature Store Overview[22:00] Managed system trade-offs[29:15] Databricks Developments and Trends[44:31] Insider Info and Summit[45:47] Data Ownership Pros and Cons[48:08] Data Contracts and Challenges[51:25] MLOps Databricks Book Guide[52:19] Wrap up

Sid Kumar, Area Vice President of Go-to-Market Strategy and Planning at Databricks, joins the ZoomInfo Labs Podcast to break down the modern GTM org. From building global sales systems to operationalizing AI across workflows Sid brings lots to learn from.We dive into lessons Sid has carried from HubSpot, AWS, and CA Technologies, why a connected GTM is the future, and how to treat go-to-market like a product that's always evolving.In this episode, you'll learn:Why GTM should be treated like a product—not a processHow to scale go-to-market systems globally without losing local nuanceThe right way to experiment with AI across sales, marketing, and CSHow GTM architects can unify data, workflows, and outcomesFor more from ZI Labs, visit ⁠www.zoominfo.com/labs⁠ Ben on LinkedIn - www.linkedin.com/in/bensalzman Millie on LinkedIn - www.linkedin.com/in/milliebeetham

In this episode, Sam, AJ, and Asad are joined by Guy Rubin to dive deep into the critical insights from Ebsta's latest sales benchmarking report. Their report uncovers what separates high-performing sales organizations from the rest. They take a sobering look at current quota attainment trends and why most teams continue to fall short of targets. They also explore how leadership decisions create ripple effects across sales performance, examining the structural and cultural factors driving results. This episode delivers actionable takeaways for sales leaders looking to improve quota attainment, optimize their tech stack, and build more resilient teams in an increasingly complex selling environment.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(03:00) Sales Quota Attainment and Market Dynamics(06:00) The Role of Leadership in Sales Success(08:49) Data-Driven Sales Strategies(11:58) The Challenge of Sales Performance(15:03) The Future of Sales Talent and AI's Impact(17:54) Concentration of Talent in Sales Organizations(22:49) The Concentration of Talent in Organizations(23:41) Data-Driven Insights for Sales Success(25:50) The Role of AI in Sales(26:41) The Myth of the A Player(28:49) The Importance of Consistency in Sales Processes(30:01) The Shift to Full Cycle Sales(32:21) Customer Relationship Management in Sales(34:41) The Impact of Leadership on Sales Performance(37:53) Navigating Volatility in Sales(40:54) Building a Data-Driven Sales Organization(48:05) Pop Culture References and Team Dynamics(49:14) Market Dynamics and Leadership Changes(50:44) Founder Friendliness and CEO Replacement(54:14) The Role of Founders vs. Non-Founder CEOs(01:00:20) Community and Personal Growth(01:01:30) Inspiring Media Ventures and Closing Thoughts

When Rick Smolen stepped into the CRO role at ShipHero, he wasn't just inheriting a sales team—he was taking on the entire customer lifecycle. From marketing to partnerships to customer success, Rick had to quickly learn how to lead teams in functions he'd never directly owned before. In this episode, he shares what that transition was really like, the mistakes he made early on, and how curiosity became his most powerful leadership tool.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!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(01:10) Overview of ShipHero and its services(03:15) Rick's career Journey(06:37) Challenges of transitioning to CRO(09:36) Curiosity and leadership dynamics(14:27) Building a leadership team and embracing failure(18:12) Evaluating leadership success(22:59) Key takeaways and book recommendations

InfluxDB just dropped its biggest update ever — InfluxDB 3.0 — and in this episode, we go deep with the team behind the world's most popular open-source time series database. You'll hear the inside story of how InfluxDB grew from 3,000 users in 2015 to over 1.3 million today, and why the company decided to rewrite its entire architecture from scratch in Rust, ditching Go and moving to object storage on S3.We break down the real technical challenges that forced this radical shift: the “cardinality problem” that choked performance, the pain of linking compute and storage, and why their custom query language (Flux) failed to catch on, leading to a humbling embrace of SQL as the industry standard. You'll learn how InfluxDB is positioning itself in a world dominated by Databricks and Snowflake, and the hard lessons learned about monetization when 1.3 million users only yield 2,600 paying customers.InfluxDataWebsite - https://www.influxdata.comX/Twitter - https://twitter.com/InfluxDBEvan KaplanLinkedIn - https://www.linkedin.com/in/kaplanevanX/Twitter - https://x.com/evankaplanFIRSTMARKWebsite - https://firstmark.comX/Twitter - https://twitter.com/FirstMarkCapMatt Turck (Managing Director)LinkedIn - https://www.linkedin.com/in/turck/X/Twitter - https://twitter.com/mattturckFoursquare: Website - https://foursquare.comX/Twitter - https://x.com/Foursquare IG - instagram.com/foursquare (00:00) Intro (02:22) The InfluxDB origin story and why time series matters (06:59) The cardinality crisis and why Influx rebuilt in Rust (09:26) Why SQL won (and Flux lost) (16:34) Why UnfluxData bets on FDAP (22:51) IoT, Tesla Powerwalls, and real-time control systems (27:54) Competing with Databricks, Snowflake, and the “lakehouse” world (31:50) Open Source lessons, monetization, & what's next

In this episode, we're joined by Gaurav Agarwal, COO of ClickUp, who's led the company's explosive growth to over 10 million users while slashing CAC by 3X and achieving profitability. Gaurav dives into why ClickUp's hybrid motion is crushing it and how to align both for compounding returns, how they reduced CAC by ruthlessly optimizing spend and embracing incrementality over attribution, how to build teams that thrive under high accountability, and more.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 to Gaurav Agarwal and ClickUp(02:54) Gaurav's Journey from Banking to Startups(06:04) Growth Strategies and Challenges at ClickUp(14:54) Branding vs. Performance Marketing in SaaS(21:54) Navigating Brand Marketing and Measurement(24:44) The Importance of Self-Awareness in Leadership(27:39) The Role of Pain in Leadership and Growth(35:57) The Dichotomy of Being Liked vs. Respected(40:39) Building Resilient Teams Through Real Challenges(51:14) The Dynamics of PLG and SLG(52:37) Fragmentation in Go-to-Market Strategies(56:42) The Role of Marketing in Revenue Generation(01:00:45) Influences and Inspirations in Business

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