Podcasts about power bi

For years, Rob had a pretty good system. When a new technology showed up, he didn't immediately declare it the next big thing. He wanted to understand why it mattered first. Sometimes that meant jumping in early, like he did with Power BI. Other times, it meant waiting until the signal was stronger than the hype.   AI was different.   It was the first technology that made Rob question whether his usual approach was enough.   That's where Fair Game begins.   In this special episode, Rob shares the foreword from the audiobook, along with his introduction to Eddie, the AI collaborator that helped shape the book from first draft to finished manuscript. More importantly, he tells the story behind the story. How someone who never considered himself an AI evangelist ended up writing a book about it, why fear became an unexpectedly good teacher, and why he came away convinced that AI success has far less to do with the models themselves than most people think. If you've been hearing Rob talk about Fair Game over the past several months, this is your first chance to hear how it all comes together. It's not Chapter One. It's the reason there had to be a Chapter One.   Also in this episode: Fair Game Preorders

Mike & Tommy dive into self-service analytics with AI, exploring how tools like Claude are changing the way business users interact with data — and whether speed and access come at the cost of trust and governance.They break down what semantic models need to look like when chat is the primary interface, who owns accountability when AI gives a wrong answer, and what practical guardrails BI teams should put in place before scaling AI-assisted analytics.Read more: https://claude.com/blog/how-anthropic-enables-self-service-data-analytics-with-claudeGet in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Lynn Gravley, the newly appointed chairman of the Transportation Intermediaries Association (TIA) and founder of NT Logistics, joins us to break down the real side of the freight industry! Lynn shares his journey from being a broke, freshly minted college graduate to building a thriving managed transportation business. He dives into how managing full networks differs from traditional freight brokerage, the massive role of data analytics and Power BI dashboards, and why aligning with the TIA is a game-changer for building authority. If you are ready to stop fighting fires and start optimizing your logistics network, tune in now!   Connect with Lynn Website: https://www.ntlogistics.com/ / https://www.tianet.org/  LinkedIn: https://www.linkedin.com/in/lynn-gravley/  

2026 ist für uns ein ganz besonderes Jahr.

Mike & Tommy tackle the growing tension between individual and team-owned Microsoft Fabric Agent Skills, exploring how BI teams should organize, govern, and promote skills without killing innovation or creating shadow BI.They break down the full skill lifecycle — from personal experiments to certified team assets — and land on practical governance guardrails that are lightweight enough to actually stick.Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

In today's Cloud Wars Minute, I break down how DynaTech Systems enabled Solmax to turn operational complexity into global efficiency with D365, Power BI, and Microsoft Fabric. Highlights 00:03 — Today I want to take a bit of a dive into a specific case study: the story about the impact of digital transformation enabled by one company on the business outcomes of another. I love having the opportunity to explore stories like this because, as important as it is to discuss the technology itself, how it's implemented and what that implementation can lead to is just as critical. 00:41 — Solmax is a leading geosynthetics manufacturer focused on civil and environmental infrastructure, operating across four continents through 32 legal entities. This broad reach, although great from a growth perspective, was creating challenges such as data silos, inconsistent processes, and a lack of standardized reporting, which affected financial and operational insights. 01:08 — Beyond this, manual processes led to inefficiencies. Complex sales price calculations hindered productivity, and reliance on outdated Microsoft systems resulted in slower Power BI report refresh times. To address these challenges, Solmax had a core goal: the One Organization, One Data, One Reporting initiative. 01:52 — DynaTech has a number of solutions it will tailor to suit the outcomes of an individual client. In the case of Solmax, the company opted for its finance optimization solution. After process consulting, DynaTech enabled a greenfield implementation of D365 Finance and Supply Chain Management with unified processes across 32 entities. 03:17 — Beyond this, unified real-time dashboards enhanced global reporting, supported faster decision-making, and improved the company's audit readiness. Solmax was able to reduce freight costs, accelerate delivery cycles, improve truck utilization, minimize penalties, and shorten accounts payable and receivable processing times. Less manual intervention meant fewer errors. Visit Cloud Wars for more.

Mike & Tommy tackle whether Power BI developers are quietly becoming professional QA testers in the age of Microsoft MCP, weighing in on what separates a true senior developer from a junior when AI writes the first draft.They explore how the developer role is shifting, who owns accountability when AI-generated measures ship broken, and what skills still matter when the tool can do the typing.More on Microsoft MCP for Power BI: https://claude.com/blog/how-anthropic-enables-self-service-data-analytics-with-claudeGet in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Lien pour le Lucanet Connect : https://www.lucanet.com/fr/lucanet-connect-2026/?utm_source=businesspartner&utm_medium=podcast&utm_campaign=FR_FR_ALL_N_ALL_NA_REGISTER_ICP_INTEREST_LNCONNECT_FIELD&utm_content=&utm_term=Dans les conversations sur le choix d'un outil EPM, les questions concrètes restent souvent sans réponse directe. Combien ça coûte vraiment ? Combien de temps dure le projet ? Est-ce qu'on sera autonome à la sortie ? Lucanet est un éditeur allemand créé en 1999, leader européen de l'EPM, adossé à un fonds de private equity depuis 2022, avec un chiffre d'affaires d'environ 200 millions d'euros et un tiers de ses effectifs dédiés à la R&D. Sa cible principale est le mid-market : des structures entre 150 et 200 millions d'euros jusqu'à plus d'un milliard, tous secteurs confondus à l'exception du bancaire.Sur le plan opérationnel, Yassir donne des chiffres précis. Le tarif d'entrée pour la consolidation et le reporting se situe autour de 25 000 euros par an, pour une vingtaine d'entités et une dizaine d'utilisateurs. L'implémentation repose sur des ateliers de co-construction espacés sur environ trois mois, avec une quinzaine de jours de consulting pour les structures jusqu'à 200 millions d'euros, et une vingtaine à vingt-cinq jours pour les groupes d'un milliard et plus. L'objectif à la sortie de projet est l'autonomie totale, grâce à un paramétrage no-code.L'épisode aborde aussi les points de friction. L'outil ne dispose pas de module de dataviz natif : les clients exportent leurs données vers Power BI, Tableau ou Qlik. Yassir le reconnaît et précise que ce point est dans la roadmap pour 2026. Le deuxième inconvénient, qu'il défend autant qu'il le reconnaît, c'est le cadre imposé par le standard : une direction financière qui veut construire quelque chose sur mesure devra en accepter les limites ou en assumer le surcoût.Pour un DAF en phase de sélection d'un outil EPM, cet épisode fournit les éléments de calibrage qui manquent souvent dans les fiches produit ou les argumentaires commerciaux.Je m'appelle Jonathan Plateau. Je suis passé par EY, Valeo et Safran et j'essaye d'engager des échanges et des réflexions sur nos métiers de la finance.Ma mission : vous offrir une expérience éducative, divertissante et parfois surprenante.Ce podcast est fait pour les directeurs financiers (DAF, CFO), les contrôleurs de gestion, qu'ils soient juniors ou confirmés, et qui souhaitent profiter des échanges entre pairs pour enrichir leur pratique de la finance au quotidien et tendre vers le business partner.Joignez-vous à notre communauté passionnée qui explore chaque facette du contrôle de gestion et du business partner.N'oubliez pas que la finance, c'est aussi une question de mindset !N'hésitez pas à partager vos interrogations sur nos discussions ou sur le podcast. Vous pouvez me contacter sur LinkedIn directement.https://www.linkedin.com/in/jonathan-plateau-1980b610/Vous aimerez cette émission si vous aimez aussi :Coonter (Les Geeks des chiffres) • CFO Radio • Une Cession Presque Parfaite • Voie des comptables • Parlons Cash • Le nerf de la guerre • Feedback by la fée • Radio KPMGHébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

Minal Bhatnagar is a technology professional with over 19 years of experience in the IT industry. She remains as curious today as when she started her career—always willing to explore new technologies, experiment, and learn by doing. Her extensive experience allows her to not only innovate confidently but also ensure that challenges are resolved before they become problems.She is passionate about Azure, Data, and Artificial Intelligence technologies, and enjoys leveraging AI-assisted tools to accelerate work, enhance delivery, drive meaningful impact, and bring innovation into everyday processes.Beyond her professional life, Minal enjoys experimenting in the kitchen, organising her home with the precision of a cloud migration project, and exploring health and Ayurveda. She particularly enjoys learning about wellness practices—often convincing herself that her tea selections are part of a carefully crafted strategic plan.

Mike & Tommy dive into RayFin, Microsoft's new AI-first product for building, deploying, and governing agents inside Microsoft Fabric, exploring whether this is a true shift in how BI teams work or just another layer of hype on day one.They break down what RayFin actually changes for semantic models, reports, and pipelines, tackle the real governance risks when AI can build and deploy at platform speed, and land on the practical first steps a Fabric team should take before turning it loose in their tenant.https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Introducing-Rayfin-A-new-AI-first-way-to-build-deploy-and-govern/ba-p/5191676https://azure.microsoft.com/en-us/blog/microsoft-build-2026-building-agentic-apps-with-microsoft-fabric-and-microsoft-databases/Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

- My favorite feature in Acumatica is the ability to connect directly to the data in a Generic Inquiry over OData - It's my favorite feature because both Microsoft Excel and Power BI understand OData so you can design reports that are refreshable at the click of a button instead of having to Export to Excel every time you want new data - But OData can time out on large datasets - That time out problem could be solved with a differential refresh on OData, but I've never figured out how - Kaden thinks he has a way to do it so let's find out

Mike & Tommy dive into Microsoft Build 2026, breaking down what the "agentic apps" announcement actually means for Power BI and Fabric teams—and whether this is a real architecture shift or just rebranded copilots.They weigh in on how Fabric Data Factory orchestration, Microsoft Databases, and Agent Skills change the day-to-day for BI developers and data engineers, and what governance guardrails teams need before anything touches production data.https://azure.microsoft.com/en-us/blog/microsoft-build-2026-building-agentic-apps-with-microsoft-fabric-and-microsoft-databases/https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Orchestration-in-Fabric-Data-Factory-Build-2026-recap/ba-p/5185775Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Mike & Tommy dive into CI/CD automation with agents in Microsoft Fabric, exploring how agentic workflows are reshaping deployment pipelines, whether AI-driven deployments introduce more speed or more risk, and what guardrails teams need before letting agents touch production workspaces.https://github.com/microsoft/fabric-task-flowshttps://learn.microsoft.com/en-us/fabric/cicd/deployment-pipelines/get-started-with-deployment-pipelines?tabs=from-fabric%2Cnew-uihttps://learn.microsoft.com/en-us/fabric/cicd/variable-library/get-started-variable-libraries?tabs=home-pagehttps://github.com/mattpocock/skills/blob/main/skills/productivity/handoff/SKILL.mdGet in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Alejandro Cabrera Muñoz, co-founder and CEO of Green Eagle Solutions, returns to discuss automating 70 GW of renewable assets and why operators are self-operating their fleets. Reach out to sales@greeneaglesolutions.com to learn more! Sign up now for Uptime Tech News, our weekly newsletter on all things wind technology. This episode is sponsored by Weather Guard Lightning Tech. Learn more about Weather Guard’s StrikeTape Wind Turbine LPS retrofit. Follow the show on YouTube, Linkedin and visit Weather Guard on the web. And subscribe to Rosemary’s “Engineering with Rosie” YouTube channel here. Have a question we can answer on the show? Email us! Welcome to Uptime Spotlight, shining light on wind energy’s brightest innovators. This is the progress powering tomorrow Allen Hall: Alejandro, welcome back to the program.  Alejandro Cabrera Muños: Thank you so much, Allen. It’s a pleasure to be here.  Allen Hall: Well, so last time we talked, you had so much happening at Green Eagle, and it is, uh, amazing to watch the progress there. You’ve been around for quite a while now. You started, what, in 2011 working on SCADA systems. Uh, uh, there’s been a lot of evolution since then. Walk me through, like, the process where you thought, “Hey, there’s a business here.”  Alejandro Cabrera Muños: Of course. Uh, we actually started officially back in 2012. It’s been a, quite a, of a long journey to, to get here. Uh, yeah, we started, uh, back, back then. We say it’s a whole new world, right? If we look backwards, like, almost 15 years. Makes me, makes me feel, like, extremely [00:01:00] old. Uh, but ne- nevertheless, um, yeah, back then we were trying to, to cover, like, a lot of issues that were based on OEM SCADAs, which by the way, we still are dealing with. But, but that, that was starting point. It was, um- It was, uh, based on understanding that the, the renewable energy industry is so complex. Every wind farm, every solar plant has different issues, different systems. Even, even the same models from the same manufacturer sometimes have complete different systems, which complicates everything. So it was very exciting to, to start our careers in a, in an industry where nothing is standard and where everyone is looking for something that is standard. So that’s, that’s where we fit in. Um, yeah, and in these years, we, we started basically creating the f- the foundations, uh, uh, on top of, uh, SCADA systems. [00:02:00] But as soon as we had that, those foundations, we realized that this sector is not gonna evolve, uh, it’s gonna cope up with the complexity, uh, of the technical complexity, market volatility, regulatory compliance. That’s not gonna be solved by just having more SCADAs. So we created a layer of automation in place, which is basically what we’ve been, um, evolving in the last 10 years now, um, with the, with the mindset and with the goal that every wind turbine should be running autonomously without having to have people behind it, uh, supervising and taking control of it. Allen Hall: Yeah, and that’s a great founding idea, but that has grown from an idea to you’re automating, what, 40 gigawatts of renewable assets right now?  Alejandro Cabrera Muños: Oh, we’re actually now connected to over 70 gigawatts.  Allen Hall: That’s amazing. Alejandro, that’s incredible.  Alejandro Cabrera Muños: And all of them are different.  Allen Hall: Sure. So that, that’s a combination– 70 gigawatts is a combination of wind and solar and anything else? Alejandro Cabrera Muños: Yes. [00:03:00] Well, actually, one of the, one of the main, um, needs that we try to cover from day one is to be able to connect to all, um, asset classes. So we understand that, um, the challenge of operating a large portfolio for our customers, um, can only be solved if we have the ability to connect to all type of asset classes. So we can have to connect to wind turbines, inverters, trackers, substations, um, energy meters, you name it. You– we have to connect to every single asset class, um, because what’s important is how you manage that data on top of that and how you react on the anomalies.  Allen Hall: Right. Because I think a lot of operators are now considering taking your model, the Green Eagle model of s-self-operating, but they need that help, they need that insight into the operation of a solar farm or a wind farm or, or any of those assets, renewable assets, ensure those inverter-driven assets. You’re, you’re seeing– I, I think we’re seeing the same thing, which is a lot of operators decide to [00:04:00] leave full service agreements globally, and what do you think is driving that now? Uh, is it a financial decision? Is it a performance decision, or is it both?  Alejandro Cabrera Muños: I think there are many factors, but I think the main driver is the financial aspects of it. I think when you, when you delegate the operations to a third-party, uh, entity They are gonna optimize their services to whatever service level agreement or availability they are committed to. And for that reason, you’re never gonna get– effectively, you’re never gonna get the extra mile. You’re never gonna get any extra from there. Um, and that’s okay when the market is– has great conditions and everything w- is going well. But we are seeing how in the last years we have, uh, a lot of market volatility, negative pricing. Everything is becoming more and more complex, so many projects are actually under stake financially. And I think that’s, um, that’s pressuring everyone to look for opportunities to squeeze their assets a little bit more or a little bit better, I would say.[00:05:00] Um, and part of that is to take operations in-house so you at least you have the opportunity to, to do, um, a better job, uh, let’s say.  Allen Hall: Yeah, and part of what we’re seeing is, at least in the United States and, and globally now, I think it’s, there’s more action globally than there has been on mergers and acquisitions. So an operator that has historically had a particular OEM in wind, you know, say it’s Vestas or Siemens or GE, whoever, Nordex, it could be any of them. Uh, when they acquire another competitor or another farm, they’re bringing in a f- a wind turbine they probably don’t know much about. And, and that’s a huge problem. And, and there’s not a lot of resources for them to grab hold of. Uh, that’s one of the marketplaces you’re trying to fill right now, right?  Alejandro Cabrera Muños: Of course. Uh, as I mentioned before, if something describes our sector is that nothing is standard, despite everyone is seeking standardization of everything, right? Uh, but nothing is standard for, [00:06:00] for– and that, that’s the reality. So the first thing when, when you have a portfolio and you are incorporating new assets into it, you need, um, a solution that is able to connect to all type of assets, right? Um, w-we call our solution a three-in-one solution because first of all, it acts as a second level SCADA, so you can connect everything there, uh, everything there, and you have access to all the data across all your assets. Then we have the SCADA automation layer, and then we have the data analysis layer on top of that. Okay. But let’s focus on the operations, which was, uh, your question, right? So you have a new bunch of assets. Sometimes you don’t have any documentation whatsoever, but these are Gamesas, Nordex, a bunch of them from different years. Um, the first thing that we provide is a second level SCADA, so you can connect to all of those. But We have, uh, something that we believe is very unique. So what we provide to our [00:07:00] customers is ability to automate all these assets autonomously. And what that gives you, it’s, um, set of data that can be analyzed, and we can learn from what’s working, what’s not working, beyond what the manufacturer’s gonna tell you to do, right? So we have thousands of General Electric turbines connected to our software, for instance. Um, we know what works, what doesn’t works, uh, what are the faults that can be resetted remotely, what are the ones that are not, what is the success ratio of those resets, ’cause that’s a metric that nobody else has unless you have automation in place. Uh, but we can actually understand, is it working? Is it not working? Is it creating fatigue for no reason to these turbines? So what– we have all this, this, uh, un- this knowledge and this, um, knowhow, uh, for all these models. Um- I believe one of the main, um, value that we provide to our customers is, is not only the, the solution itself, but it’s also the [00:08:00] ability to be somehow prescriptive. It’s, it’s not that we’re gonna know more about how to operate the assets than our customers, but, uh, we have a sense of what’s the benchmark, right? So I, I– And that benchmark is very, very useful for them as well.  Allen Hall: So th- that’s part of getting to scale, and 70 gigawatts is a, a lot of scale, where you have seen a number of turbines in different places operating in different environments and performing at different levels. That’s unique, right? That gives you insight into really what’s happening to a turbine or a solar asset globally and also locally. For a lot of operators that just happen to acquire or, or, or take on a- an older wind farm, uh, they tend to get stuck, right? They, they, they, they don’t tend to be able to, to find their way through those little nuances. That’s a huge financial impact to them eventually, right?  Alejandro Cabrera Muños: It is. And I, and I believe that for many years this was something that in a way got, um– [00:09:00] didn’t get a lot of visibility. I think people were not fully aware of how much revenue, how much production they were losing just because they were not operating their assets at the best capacity. Um, now we have the data to prove what, what better can look like. W- uh, we have data to prove that if you follow the OEM’s, uh, protocols, you may be creating fatigue for no reason. Um, and there are improv- there are ways to improve that thing. So I think it’s, um– We are, we are opening the door for a new, complete new way to operate your, your portfolio and get more benefit from it. Allen Hall: I think that’s a very interesting aspect of the sort of the structural aspects of how a, a wind turbine performs, and a lot of that is driven by software. And you, you realize if you’re paying close attention to the OEMs that some of the software updates are not necessarily performance enhancements. They’re more of protecting the turbine because they realize they may have a problem. So it may be a slight derate, it may be a, a different sort of power curve that happens. [00:10:00] But a lot of operators don’t really sense that that is happening up close because they’re not into the details of that. That’s where Green Eagle separates itself. You are into all those details. And do you have a lot of operators just reach out for help immediately saying, “Hey, I have this Siemens Gamesa or Gamesa wind farm,” think about an older wind farm, a Gamesa wind farm Help. Just please help. Uh, whatever you can do, just show us you can do it. Do you, do you start to run a little test campaign on that site, or do you, or do you go pull back from the 70 gigawatts and 15 years of history to, to show this is what you can do with that particular asset to, to get them involved in a thinking about the problem a little bit differently? Alejandro Cabrera Muños: Well, I wish, I wish it was that way. Um, but what, what– It, it was that transparent, but what happens is that we’re working with the largest, uh, some of the largest utilities and IPPs in the world. So what happens is that they, they will never come to us saying, [00:11:00] “We don’t know how to operate this turbine,” or, “We don’t have enough information.” Um, the way they ask for it is like, “Are you compatible with this?” And, “Do you know… Do you have some protocols? Do you know the standard protocols to run these turbines?” Um, and that’s the way we, we start the conversation, and then they, uh, they, they get confident that we can actually help them with that. We only know about how, how much or how little they know about a specific model once we start working with them. And it’s not all or nothing. I- Ev-Even the largest manufacturer, e-even the largest utilities, their portfolio is constantly evolving. They’re incorporating new sites almost every month. So there’s always one site that they don’t, they don’t have expertise in the, in the house, so it’s, it’s normal. Like, basically not many people have expertise in some of the models from old Nordex or Gamesas or you name it. It, it’s impossible basically to have to understand all models in the world. So I think we [00:12:00] have the, the data, the benchmarks, and experience, and on top of that, the of course, the, the tools, so you can actually operate better those, those assets.  Allen Hall: So the name of your system is called ARSOS, A-R-S-O-S, and for anybody listening to this podcast, you can just Google it, and it’s gonna take you to Green Eagle. What is that product? How would, how would you define or describe that product?  Alejandro Cabrera Muños: Well, ARSOS is a suite. Um, what– The way I like to think about it is a, is a three-in-one solution, right? So it’s first of all, it acts, it, it, it fits in between the SCADA world and the REMs, uh, the REMs, uh, solutions. Okay? And they’re complete different worlds even though you see dashboards and they look the same thing. But SCADAs must be, um, must be able to be installed on premises. They require OT enterprise cybersecurity level. They can be, they should be installed on air-gapped infrastructure, so no access to internet whatsoever. [00:13:00]Um, and that they tend to be extremely complex to configure and, and, uh, adapt to every, uh, every different site. So that’s one world. Um, on the other hand, we have the, the REM solutions that are like more like a SaaS platform, like a Power- it could be Power BI, it could be like the, the normal use cases that you need it. You need something, some tools to create the reports at the end of the month to understand the performance of your assets, right? So you have these two, two worlds. So what we are proposing here is a solution that has been built for the past 15 years, but it fits right in the middle. So it covers Almost everything that you need from a SCADA and second level SCADA solution. It puts automation in place, and then it also gives you all the data so you can consume it in the best way, uh, possible, which by the way, now with, uh, artificial intelligence, it’s incredible what you can do with it. So this is basically what we have built, um, right [00:14:00] now. And the main differentiation here is that since we are in the middle, we are trying to solve all this complexity from a SCADA world with a product that is already pre-configured. So you can basically connect to your sites in a completely easy way, um, doing clicks and not a lot of complexity because it’s already pre-made for your needs. Um, because of that, the time to market is extremely much, uh, faster compared to a SCADA solution, so you can have a solution in thing, in hours and not in months. It’s, it’s not a project anymore, right? Which is, which it sounds like normal when you, when you talk about applications, it sounds like a normal thing to do, that you have a, a system running in hours or minutes. But when you’re talking about SCADAs, that’s like sci- uh, sci-fiction, right? Um, that’s what we’re bringing to, into, onto the table. It’s, it’s, uh, something that you can connect to all your assets in a seamless way, painless, and, uh, and, uh, off the [00:15:00] shelf.  Allen Hall: Well, that’s a very interesting way of framing, uh, the product because, uh, you do see both ends of the spectrum here, where y- there’s a number of companies that are offering a c- completely SaaS product, which is a very pretty dashboard, and it still relies on a human to watch this dashboard and, and to make sense of it, and it provides some insight. And then you get to the other side, which is almost a completely mechanical system, where it’s just SCADA data and, and you’re just picking up data for datas, uh, to have, basically. So you, you f- you sort of find that middle ground. The, the, the amount of software and technology that it’s in that space, though, must be huge, and what is the effect of AI bring to you? Does that help you more with just on the, on the, on the model side or just the, the statistical analysis of all the data that you have access to now?  Alejandro Cabrera Muños: Let me make a, um, clarification. Because since, uh, we are, we are providing automation [00:16:00] in a world that is mission critical, right? So there’s no, a lot of, there’s no room for creativity or probabilistic approach. It all has to be the deterministic, right? Uh, so when we talk about automation, we’ve always been focused on deterministic automation, so rule-based, uh, automation, and that’s what we have implemented on top of the level of the SCADAs, right? So that’s, that’s the part where you know how to deal with an asset. You have the protocols. You want to understand how they work, but you want to have certainty of what happens if the turbine is on fault and the fault is related to the gearbox temperature and so on. So you wanna make sure that there’s a reset automatically executed only if the temperature of the gearbox is under X threshold. So this very deterministic approach. Uh, but we have, uh, something, um, very unique when we go on the, on the other side, when we go on the side of the REMs. Because we not only have the data of, of the assets, we [00:17:00] not only have statuses, performance, availability, uh, production. We also have the data of how these assets, assets have been operated, right? So we know how much fatigue they have received, how they’ve been operated, um, have they received curtailments or not? How many curtailments? What were the reasons? So we can actually have a 360, uh, degree of all the data, including all the control, not only how they’re performing, but also how we are operating those assets. And we believe that this is very unique because only if you have all these 360 data, then you can actually enhance what you have on top of that. And that is where AI come, comes in, right? So AI, AI is great in, um, helping our customers in doing root cause analysis, um, dealing with anomalies are not well, um, uh, procedure. Uh, there’s no course of action that is clear, that you don’t know. It’s, they’re not like too [00:18:00] frequent to, to have one. Uh, mixing different type of data. Like I mentioned before, you have, uh, market data, you have curtailments, you have, uh, commands to stop or start a turbine. You have a lot of information there, and you can put all together. Uh, also along with the CMMS information. Um- Lastly, they get– they can pull that together to do whatever they need, right? Uh, they can build with AI. You, you can now do your own dashboards. You can create your own APMs if you wanted to. Um, and I like to think about it, like, with these new tools that you can create disposable dashboards. And, uh, the concept is that it doesn’t matter how many different dashboards you have in an APM, but tomorrow you have a, a specific case. And I think it’s amazing that now with AI and the right, uh, data structure, you can now create a dashboard, and maybe it’s just for one use case, you know? And you just build it today, look at the data. You have [00:19:00] a, um, a case study, and that’s it. May– you never use it that again. The trick for being able to, to, to create this ecosystem where you analyze the data in a completely different way is that we have been working on how to structure the data so the AI is gonna be able to understand the data itself. So once that, that layer is structured in the right way, then you can actually create your own APMs or your own dashboards as you need to.  Allen Hall: That’s fascinating. So instead of just thinking of a turbine or a, a solar field as a asset where you’re trying to maximize performance necessarily, you’re looking at it from the marketplace, the, the, uh, the shutdowns, all the, the things that are contr- overriding the performance and trying to optimize performance in this market environment, which may be very turbulent, and I think for a lot of wind operators is very turbulent, uh, at, at the minute just [00:20:00] because of the nature of the electricity grid. So you’re, you’re then thinking about Having an AI tool to help you do investigative work on the particulars, not just the global data set of how this turbine globally operates, but the specifics, that’s fascinating because that allows you then to treat each turbine as its own separate power plant, in a sense, but also to, to think about lifetime issues and how to maintain that piece of equipment in a much more efficient way. That’s remarkable.  Alejandro Cabrera Muños: And you have the– With AI, you also have the capabilities to automate all these type of analysis. So once you have a specific, uh, case to be analyzed, then you can automate that case to be analyzed in a daily basis, in a weekly basis. But that’s, uh, that, that’s, uh, that’s, uh, the world that we are moving to. Allen Hall: So a lot of what’s happening at Green Eagle at the moment is being automated and, and making it easy for, for customers to get [00:21:00]onboarded to the RSO system. What does that look like today? Uh, how do, how do I get onboarded? I have an asset of I got 1,000 turbines and a couple of solar fields. What does it look like to get me started in the RSO system with Green Eagle? Alejandro Cabrera Muños: Well, if you’re using our cloud, it’s, it’s gonna be a process of If you have a, a portfolio of 500 gigawatts, you can connect to our, to our cloud in a matter of like one month to two months So that’s something that you can do by yourself. So, um, you can create the assets, you can create the connectivity. The connectivity is done through IP filtering or VPN tunnels. All that is from the, from the dashboards, from, from the cloud. Um, then you can, based on the model directory, you can choose which is the, the assets that you want to connect to and through what channels, whether you have Modbus, OPC, and so on. Um, but that’s a- as complex as, as it gets. Really? It’s n- it’s not easy either, because [00:22:00] you need to understand what is a Modbus, what is a OPC, but that’s what it is. It, it’s not a matter of, like, installing something on site and doing tons of, uh, complex, uh, um, configurations. You don’t need, uh, SCADA engineers to be, like, building these dashboards tailor-made for your sites and, and all that is, is something from the past in o- in our opinion. Allen Hall: So you’re not on the telephone, or you’re not on a, a online chat with the Green Eagle team, because it’s, it’s, it’s– you’ve, you’ve done enough capacity now that you’ve automated this.  Alejandro Cabrera Muños: You don’t have to.  Allen Hall: That’s amazing, because I think that’s the first worry for any operator that is gonna make that leap saying, “Hey, I need a little bit of help with this wind farm or this solar site,” is that, “Oh, I gotta be on the phone. I gotta– There’s a lot of im- of onboarding that has to happen,” and you’ve eliminated that.  Alejandro Cabrera Muños: Well, first, w- I, I totally understand this hesitation. Um, many of our customers are living in, in the, in the SCADA world, right? Uh, and which w- it was probably once a pain [00:23:00] to be configured to begin with, and I think half the sector is traumatized by these processes. So I, I tot- I totally understand that that pain is, is still there, right? I understand that. But what we’re trying to do is to, to move forward and say like, “Yeah, that, that’s gone. That was the past. Now we have a different way to do it.” And if you have, uh, either new assets that you need to connect or you even consider, like, moving to something more modern, something with more capabilities, something that comes with automation in place, uh, well, we have a solution that is painless. Allen Hall: Can I discuss, or can we go back and forth about the, the use of inverter-based resources, the solar and the wind sites, in terms of the, the move from grid following to grid forming and stabilizing the grid? I think there’s gonna be a lot of changes in the way that we operate these assets over the next year. Mostly, uh, I see action in the United States from the Iberian blackout about a year ago. They’re changing the thought process of how they want to run the grid so that the wind [00:24:00] and solar can keep the grid operating. Is– Are you involved in, are you involved in that aspect of how you operate those assets and how those inverters perform and, and configuring them to, to do more of the, of the grid forming and keeping the grid stable? Alejandro Cabrera Muños: I believe, to be honest, this is more related to power plant controllers and hybrid plants. So we have, we have made several projects with, um- With a mix, uh, of, uh, wind, solar, um, and storage. And wh- but what we’re doing here, uh, to be completely honest, we are not involved in the power plant controllers. Uh, we believe that that’s an electrical device and has, uh, uh, particularities that are out of us- our scope. But what we do is to, again, we connect to all asset classes, right? So we also w- connect to the PPCs, and we can monitor the PPC, the performance of the PPC, and we integrate that into everything else, right? So [00:25:00] that’s, for us, that’s another asset that we are connecting to, and that it make– it completes the view of, um, of sites that are now, like, almost like mini portfolios at, at the same place, right? ‘Cause you have, uh, different technologies, service stations. You have so many things that you need to orchestrate as well. So we’re, we’re w- moving into, into that area as well, uh, f- with the same concepts.  Allen Hall: B- so in a, in a sense, you’re able to monitor the health or status of the grid. Because you’re connected to so many of these assets, you have a pretty good understanding of how the grid is doing at any particular moment then. Alejandro Cabrera Muños: That’s right, yeah, especially in, in Spain, of course, ’cause we’re connected to, um, over 25 gigawatts at the, uh, at, in Spain, so.  Allen Hall: Alejandro, that’s amazing.  Alejandro Cabrera Muños: Over 25 gigawatts at the, uh, at, in Spain. So, so that’s s- it’s almost a third of the, of the installed capacity in Spain.  Allen Hall: Is there a movement in Spain to, to use technology like yours [00:26:00] to better monitor, regulate, control the, uh, wind and solar assets so- such that they stay engaged when, when the, the grid starts to, to vary a little bit? Has anybody asked you to, to be involved with that? Because it seems like you’re the right– you’re in the right place at the right time.  Alejandro Cabrera Muños: The challenge of all these grid codes, uh, in, in most of cases is just that There are tons of curtailments that are coming from many different reasons, technical restrictions, market, uh, dispatch, um, other type of compliance. Um, the, the first challenge is to just execute on them, right? So they’re coming, you need to apply on the, on the sites. Um, that was the first, the first phase. But now that we have so many gigawatts connected, and that we’re also participating in balance mechanis- balance mechanisms and ancillary services, what we are seeing is that depending on how your assets perform and how quickly they are in regulating, um, you are gonna [00:27:00] have penalties or more, uh, profitability in the participation of the markets. So that’s, that’s extremely important as well ’cause it’s, it’s quite difficult to, to measure. But we have all the– Since everything is automated, you can always track, and you can statistically understand which of the sites are performing better or worse, in what cases, and therefore you have opportunities to improve the regulation and get more revenue from it. Allen Hall: Okay. So Green Eagle then is, because of the scale that it has at the minute, can look at the grid and is involved in, in the, the grid requirements, so to speak, of, of, uh, curtailments and what assets are operating when, and also the voltage control aspects and frequency control, which is the other part of it. You, because you’re, because you have so many assets in Spain and globally, you, it’s amazing the number of assets you have. You, you then can actually, one, see health of the grid, two, [00:28:00] provide insights to operators on what that looks like. I mean, real time you could, you can do that. And then are, are, are the regulators then coming to, to you asking advice on how these assets should perform? Because it does seem like you would be a tremendous resource on how the grid is actually doing on a larger scale from a renewables standpoint.  Alejandro Cabrera Muños: Yeah. Well, fortunately, the, the regulator has its own also, uh, system, so it’s, uh, redundant, right? So as far as we, we are working to, to have, uh, the best system in the world, but, but it will be a lot of, uh, responsibility for us to just have the whole grid depending on us. That would be a lot of weight. Uh, but in a, in a way, in, in a, in a way, it already depends on us, uh, effectively. So, so the pressure is, is there. We have, we have talked to them, um, since we have so many customers, um, in the, in the– at this level, uh, we have to be very quick in implementing new grid codes and new [00:29:00] regulatory, uh, compliance issues and, and so on. So that’s, that’s, um… It’s a challenge, but at the same time, it’s, it’s very exciting that we are always ahead in, in this regard.  Allen Hall: Right. If, if I was an operator and I had Green Eagle as one of my, uh, helpers in a sense, uh, assistants in a sense, that helps with the, the grid code i-in terms of, one, understanding it, and two, being able to implement the changes that are coming down all the time. You have a resource there that understands it from a larger perspective because you see it from multiple operators in multiple places trying to do the same thing. That’s a huge advantage instead of you trying to na-navigate or try to understand all those grid code changes and why they’re happening and what it means to you and how do you operate your assets. So you can provide a little bit of guidance there for the operators.  Alejandro Cabrera Muños: Of, of course. Um, uh, the main, the main value proposition that we can have here for anyone that wants to participate or be part of the Spanish market is that we already have all this figured out. So if you wanna start from the scratch [00:30:00] with, uh, with a SCADA, industrial SCADA, well, let’s, let’s go with, let’s go with that. You’re gonna be probably traumatized in the future, right? Uh, but with us you have an off-the-shelf product that is already compliance. It, uh, h- we have already set, uh, the system certified by the TSO in Spain. So we have already gone through this process so many times, and it’s off the shelf, so you don’t have to worry about any of this. And on top of that, you have the Peace of mind that if tomorrow there’s gonna be a, a, a new change in the, in the, in a new grid code, well, which most likely is gonna happen, um, soon, uh, we have to, we have to do it. Because we have already, uh, a lot of customers that, that, that need it. So for us, it’s actually also, uh, strategic to, to be ahead and be fast in implementing these grid codes. Allen Hall: That’s amazing. That’s such a huge resource for Spain and the rest of the world. Yeah, that’s amazing. Well, I, I know people who are listening to this podcast right now are thinking, “Okay, I haven’t heard of Green [00:31:00]Eagle, but now I’m interested, and I need to f- find out more.” How do they contact you? Where do they go first? What’s the best first step?  Alejandro Cabrera Muños: Well, they can connect, uh, directly to me through LinkedIn, or they can just write to sales@greeneaglesolutions.com.  Allen Hall: Great, yeah, and Alejandro’s available on LinkedIn, so you can f- find him there. And we’ll put his contact information in the show notes to, so you have quick access. Alejandro, you gotta come back more often because the, the things that you’re doing with Green Eagle are amazing, and, uh, the, the scale is incredible. Congratulations on that. Uh, and, and I, I, I need you to come back and tell us what the next generation looks like because I know when you guys get ahold of AI and start thinking through some of these real challenging problems, Green Eagle will have solutions. So you’re welcome back anytime.  Alejandro Cabrera Muños: Super exciting to come back, uh, when you invite me. Thank you so [00:32:00] much.

We've informally heard that Satya is a listener to LS for a couple years now, but it was still absolutely surreal to meet him and do a live pod at Build, together with our friends at No Priors, the leading VC AI Podcast that we also greatly admire!We covered the MAI model technical takeaways on yesterday's AINews, so I will focus our recap of Satya's main messages around three elements:* Satya's adaptation of the Bill Gates Line for positioning Microsoft as the Frontier Intelligence Platform — customers must gain much more value from the Microsoft ecosystem than Microsoft itself, by building on multi-model harnesses like OpenClaw and Scout, drawing on the full enterprise context exposed by context layers like Work IQ (heavily dogfooded by his C-suite), and building up private evals and traces as a new form of Token IP* AI ROI: On one hand, enterprises are having difficult conversations around Tokenmaxxing and Layoffs, and on the other hand, there are serious re-evaluations of the End of SaaS since the Build vs Buy equation has changed so much. Our previous SemiAnalysis guest had… interesting comments on Microsoft's position on this as the ur-SaaS titan, and Satya had great answers* Making the Impossible Possible: Kevin Scott's inspiring framing around what the most ambitious version of applying AI and technology at large to business and social problems, like education and social impact.Enjoy!Full VideoTranscriptVoiceover: Welcome swyx, Sarah Guo, Elad Gil,, and Chairman and Chief Executive Officer of Microsoft, Satya NadellaSarah Guo: Welcome to a crossover episode of No Priors and Lane Space with Satya Nadella. Um, congratulations on an amazing build. No, thank you so much, and it's great to be with both of you. I listen to both of you or b- both the podcasts all the time. It's great to be on it.Thank you so much. [00:01:00] So you're just talking about, um, these amazing, uh, announcements from across the Microsoft estate all morning for, I think, three hours. What is the, uh, what's the most important reflection or takeaway you have?AI as an Ecosystem PlatformSarah Guo: I, I'd say there are, uh, perhaps the, the biggest one for me is let's sort of conceptualize this more as an ecosystem play as opposed to a single model or even a single platform, right?Satya Nadella: I mean, you know, whatever I... At least for me, having grown up at Microsoft, having seen, whatever, four major platform shifts, uh, I sort of fall into that, um, uh, camp where a platform is defined by fundamentally its ability to create more value about the platform versus what's captured in the platform. And so if you, you view what's happening right now, I think this morning's keynote was how can any company, whether it's an AI native company or a traditional enterprise company, participate as a first-class participant where they can point to AI they created, [00:02:00] right?It's not that they don't use other people's AI. Of course they will. But to me, what's the path? What's the recipe? How do I do it? What does a stack look like? What does the tooling look like? What is valuable? How do you do that? That's it. That's sort of our job to do. Yeah. Ecosystem strategy is, uh, very complicated, right?Sarah Guo: Because you end up building certain components, partnering for certain components, supporting them. You just announced this big suite of models. Like, tell us a little bit about the, uh, training strategy for Microsoft now. Yeah.MAI Models & Training StrategySarah Guo: So, so the thing that we wanted to do with the MAI models was to build, and as Mustafa talked about, first of all, a great lineage, right?Satya Nadella: Starting with pre-training, uh, with very good data quality, uh, doing all the ablations, making sure because in, in some sense it's becoming even harder to build a clean lineage model just because there's so much stuff out there, uh, that you truly need to ablate out to be able to have a fantastic [00:03:00] pre-trained model.In fact, that's one of the challenges of a lot of the open weight models is they look great on one benchmark or two, but they're not great on practice. So that's why, in fact, even in the RFDEs are, they, they are pretty gone really excited about these MAI models because how the heck can a small five B model hill climb?Uh, and it goes back a little bit to what I think is ultimately the key thing to do, which is try to pursue finding that cognitive core. Uh, so to me, starting with a clean lineage- Then creating that ability for companies to be able to use this, right? Not just as a generalist, but to create their own specialist by building this hill climbing scaffold around it, right?So it's not just the model, but you have a hill climb scaffold around it, then you will start building your RLE. You will start collecting the traces. Most importantly, you'll have private evals because we know all the evals out there are good, interesting, [00:04:00] but they're not really that critical- They're work, yeahSwyx: at this point because they all can be maxed. And so the point is each company will have its own private eval. And so that end-to-end platform story around our models is sort of, uh, what I think is interesting. And then the one other thing, Sarah, since you brought that up, is I do feel there's a new frontier.Satya Nadella: Like people talk about the frontier and are you operating at the frontier. Um, interestingly enough, if you add a little temporality to it, you can use, let's say, in, in, in fact, the, the Lando Lakes demo we showed was pretty cool. We used, whatever, GPT-55, right? Then you collected a bunch of traces, and then you took a 5B reasoning model and achieved higher.Sarah Guo: Uh, so that is another aspect of what it means to appear... uh, you know, operate at the frontier Yeah. I, I think, uh, I first of all have to congratulate you on basically building a frontier neo lab inside of Microsoft in two years. Um, I'm wondering, you know, you have all this AI strategy that you're rolling out.Lessons from Two Years of AI DevelopmentSwyx: I'm wondering, what do you know now that you wish you would tell yourself two years ago where- or two or [00:05:00] three years ago? Three years for the Jensen partnership, two years for, uh, MEI. Yeah, I mean, I think the, the thing when, that I reflect quite a bit, right, which is sort of obviously I got into all this when I got excited by the, the scaling laws paper and, you know, when, you know, even the OpenAI partnership came about when those folks said, “Hey, we're gonna really throw a lot of computer transformers.”Satya Nadella: Uh, and they've helped. I- the thing that I always look back and say, “Wow, these things, uh, do have capability that they're climbing up.” W- I mean, this, you know, this crude way of saying it is intelligence is log of compute kind of works. Now what I think we underestimated perhaps is the real-world complexity of deploying these so that they actually deliver the value in the real world, right?So the outcomes as measured by any benchmark is interestingly important, but the true eval is when people out there are able to do unique things that they only can value, and it's very [00:06:00] measurable, right? That I wish we had sort of even, like, had more in our consciousness, right? Which is as an industry.Sarah Guo: Because right now I think when people say, “Wow, I don't want a token max,” it's an artifact of us not having thought ourselves as an industry that we are using tokens to create value every step of the way. So I think that's kind of what I wish we had gotten there, but I'm glad we are here.Real-World Value & Use CasesSarah Guo: What are some of the use cases that you've seen that have created the most value for your customers?Because I know that people talk a lot about code, and I think it's pretty clear that that's something that's having very large scale impact. Are there other areas that you find in common that your customers are really benefiting from? Yeah. I think, yeah, to your point, obviously coding is now got... But it's interesting, by the way, Elijah, to even talk about the coding, right?Satya Nadella: Which is coding has worked so well that we now have to rebuild the IDE, right? I mean, it's kind of nuts to see what we sh- launched is like, oh my God, I have these hundred agent sessions. I... The cognitive load it transfers back to me as a human is so [00:07:00] excessive that now I need a new UI. Uh, oh, by the way, I, like the, the chat as the only artifact was also impossible, so that's why we need a canvas.So it's kind of interesting for all the things about where is software needed or where is UI needed, uh, you kind of need that even for code, right? In a fully agentic world. But that said, one of the things that we are starting to see, we started seeing with co-work, but even some of the work we, we showed with auto com- uh, um, autopilot Right on what you see with claws is a good one because if you sort of think about a lot of human capital is doing the glue work, right?If you now can augment that with tokens/agents that are long-running, durable, right, then your ability to scale even what is still judgment and glue work gets amplified like coding does. Uh, so you can... Like, I'm positive that six months from now we'll all be saying, “Oh, wow,” like, all through ni- the night there was a bunch of stuff that [00:08:00] all these autopilots that I have working on my behalf with my delegated authority, so to speak, right?I can... Sort of given even my identity, did a bunch of work, then of course I'll need my new ADE to say, “Well, what did you do?” Like, I might... “Did I do this work?” And so on. So I think that that's where compressing of workflows, uh, completing of tasks, uh, that's where I think a lot of the value gets created. I think you raised a really interesting point, which is there's the actual agent that's doing the code, and then there's a harness around it, and that's the environment, that's the context, that's everything you're setting up as a developer around actually a coding agent.The Harness Concept for Enterprise AISarah Guo: What is the harness for the enterprise? Is there an equivalent concept for broader productivity work, or how do you think about that concept sort of generalized? That's right. So, so in some sense you kind of want the harness to define the models, the, the data, uh, and the tools, and so that you have a loop across those three.Satya Nadella: And so what we are trying to, first of all, make sure is each of our products that we build, right, whether it's GitHub Copilot or the security copi- the, the [00:09:00] stuff we showed with MDASH or even the discovery for science, it doesn't matter, all of them are multi-model harnesses, um, with tools access so that you can do this progressive, uh, disclosure of tools even so that they're token efficient.Uh, and then you're feeding it with very rich context because that's sort of the other hard lesson we have learned in the last two years is, oh my God, the amount of work you need to do to prep the context layer, uh, such that your plan can execute in the most efficient way is where the magic is. So we have, in our case, we have the GitHub harness, which essentially we're using across all our products.It's available in Foundry, and we are open, like you can use your Llama harness, whatever. Or you can use the, um, uh, you know, any open harness or any harness of yours and train with your tools and multiple models and your context. And so that's the pitch. Because right now a lot of dialogue is, um, “Hey, if I train the harness plus tools and the model together, you get [00:10:00] evals.”Elad Gil: And what we are proving out is... And the best example of that is what we did with MDASH, right? Because when it launched, uh, it found bugs or vulnerabilities that were not found by Mythos Uh, and so there is existence proof, I would claim, that you can have a multimodal harness, uh, that can in fact be more, uh, performant in the real world So a premise behind the, uh, training at the independent frontier labs is really, you know, we're gonna have these models, and we'll have an API business, and we'll support enterprises and startups.Sarah Guo: ButPlatform Strategy & Developer EcosystemSarah Guo: a first-party product, be it productivity or code or search, drives the majority of revenue. That's a different value equation than you're describing, I think, with the Microsoft ecosystem. Uh, if, if that's the case, tell me if it's the case, uh, ‘cause obviously you have first-party products and you have enablement products.Satya Nadella: Um, what is the role of the develop- Like what is gonna be hard and the set of skills and the value capture the developer has in that world? Yeah. So I think that there's always [00:11:00] gonna be the case that someone who is super successful in- as a platform builder can also have first-party products. It was true with Windows.It is true, uh, with, uh, the, the SaaS side and the cloud side as well with us and others and so on. But the thing that is, is it should not be a limiter to other people achieving that same success, right? That I think is the core difference, which is the, the network effects this time around, around intelligence are such because they learn from data, and not really lots of data.It's just a few samples that you have to see to understand what's novel about something. So that's why the game becomes how to protect. So that's why I would say every company, having private evals may be the biggest IP, right? Think about it, like what's that private eval that you can then use even a frontier model to hill climb on and not leak the traces may be one of the biggest [00:12:00] drivers, uh, of IP.Like, so in other words, another te- acid test is you have an eval that's private. You're using, uh, a g- a Model A. Can you switch it to Model B and e- you know, climb up? If you can, then you're in control. If you can't, you're not in control, and that's where even the harness decision becomes super important, right?swyx So therefore, having an open harness, letting all models come in, having your evals, your context, your tools help you hill climb, I think is the skills that an AI native startup needs, a SaaS company needs, or every enterprise needs. Yeah, I think in, in a very real way you are ... Microsoft historically is an operating systems company and th- then become a cloud company.Maybe like the third act is that you're a harness or evals company. Whatever w- ... whatever the, the sort of conglomerate of concepts that you wanna put together. Um, and, and I think like enabling every company to have like frontier intelligence or what- what- Yeah ... I forget the, the [00:13:00] exact term that you used, um, is the, is the mission, right?Satya Nadella: That's it. Like that is, that is the platform promise, that you build with us, you will get your intelligence, uh, for your data. That's it. That ... To, to me, that is the ... Like if there was one tagline, uh, for this entire developer conference is- Can everybody operate at the frontier with their frontier intelligence, right?To me, that is so important because otherwise it, I, I don't know how you achieve stable equilibrium, right? Which is how do I then go and say, “Well, my company is gonna have a terminal value because I now know how to continuously compound-” Yeah ... on top of what's a platform that gets better,” right? So when, like Windows obviously came out, Adobe built, Autodesk built, uh, or even like take what Jensen said.We built DX and he built, you know, CUDA on top of it. Um, right? I mean, I always say to Jensen, “God, I got the short end of that,” right? “I wish, uh, we had recognized it.” But nevertheless, but that, that idea that you can build a platform layer [00:14:00] that someone else can then extend out, um, and build their own intelligence layer in this case, I think is everything, right?Without it, why have a developer conference? I can just come and have you all sort of just worship at the altar of one model. Yeah. But that's not a developer conference. Uh,IP, Evals & Company Valueswyx: backstage we, we had a discussion about what is IP or what is the, the value in a company. It used to be the length of, uh, human experience at a company, and now it's this other thing which is the evals, the, uh, experience in sort of applying agents to the company. Can you... I just want you to like flesh that out a bit more ‘cause- Yeah ... it was very insightful.Satya Nadella: It's a great way to frame it, right? Because yeah, at the end of the day, every company is gonna have both the human capital that is still gonna be super valuable, uh, because humans, uh, and their ability to find the gaps that exist at all times is going to be the way we all will create value, right?I mean, so I'm definitely in the camp that this is going to be about expressing new forms of human agency and ambition even as token capital goes up, right? So let's say a cor- any corporation [00:15:00] has lots of tokens and lot of human capital. The question is how do you compound the two? So if you have a... Like if you take in Teams I have a bunch of agents doing work and a bunch of humans doing work, and the traces between those, that is really important context of how that enterprise is creating value.Then that goes back to train not a generalist model, but to train the company veteran agent, uh, right? That is super valuable again, right? Which is when a company goes says, “It should in fact go onto the balance sheet,” is how I think about it, right? That's so... In fact, there may be... Like human capital was never possible to go put on a balance sheet, uh, because you didn't know how to capture the tacit knowledge.swyx: Whereas now I think you can with the agents that have learned through the h- through, through time, through all the traces. Uh, so that's what at least we think will happen. I, I think the SEC is gonna have to have accounting standards- ... for token, uh, expertise Uh, y- y- you're talking about the equilibrium [00:16:00] state, um, and a stable equilibrium where companies have this compounding value and can see terminal value for themselves.Future of SaaS & Business ModelsSarah Guo: Another challenge to, you know, the considered equilibrium of, okay, there are applications and workflows that are sort of common to a vertical or a horizontal. Um, and this was, like, the generation of SaaS companies and, you know, Microsoft has lots of SaaS properties as well. And then there are things that are very specific to every enterprise that they're differentiated against.Elad Gil: Um, I'm sure you have heard much and participate in much of the debate about the end of software because all these workflows are, are cheap to generate now. Um, do you think the equilibrium looks different between what agents get built- Yeah ... in enterprises versus in their vendors in the future? Yeah. So I think what's happening there is, see, we, we had a particular way we captured, um, I would say workflow in apps, right?Satya Nadella: Because we built a, a data model, right? We schematized some part of some business process. Mm-hmm. We then built a bunch of business logic. Yep. And then we put a bunch of UI [00:17:00] on top of it, right? So that's kind of what every SaaS company- And a little configuration. For, like, 20, 20 years that was the plan.Right, that- Yeah ... and that was it. So interestingly enough, now you kind of get to re-litigate that vertical stacking, right? So I still think, for example, that data model that you built underneath every SaaS application is super good, right? Like, why reinvent it? Like, I, I, my general ledger better be a general ledger.I don't need new schema creation. No. Uh, in fact, that entity relationship, uh, is actually pretty good, robust thing that I want to feed. And you want it to be stable. That's right. Yeah. Then same thing with business logic, right? If, if you look at, uh... We have this product called Power BI, right? It is like dashboards galore people created.The beauty underneath that dashboard is a very rich semantic model, right? Someone took the pain to create a dashboard and do all the measures, and you want that. That's business logic, right? I want that to be available to me. So I think the [00:18:00] challenge of the SaaS business model is we packaged one way. We now have to learn how to unbundle these things and rebundle in new ways and discover new business models, right?I mean, if you look at it, d- what's happening today with Microsoft 365 is a great example, right? We have this thing called Work IQ. In fact, like, what we are realizing is, oh my God, like, you know, if you look at... In fact, there's a pa- historical parallel too, right? We sold first Exchange and SharePoint and, uh, you know, before Teams, we had a thing called Lync Server and what have you, and we thought, “Oh, that's all gonna move to the cloud.”But little did we realize that, um, the number of people who will use servers in the cloud is 10X, 100X, right? Because people were not buying servers, they were just buying a subscription. Mm-hmm. The same thing is now happening with M365 because with Work IQ, we have exposed what is perhaps the most important database in a company that never got used as a database because it was only captive to our apps.Mm-hmm. Right? It, it was all email operated on it, Teams operated [00:19:00] on it, Word, Excel, PowerPoint, SharePoint. But now, like this is one of the coo- coolest things I get to do with Work IQ. I go to a GitHub repo and I say, “Hey, I attended a bunch of design meetings last week related to this repo. Can you capture all that and tell me what changes I should make?”I mean, think about that, right? It literally can go look at all those transcripts, come back with a plan to change a code base, right? Previously, you could never have thought of using M365 for something like that. So the value creation opportunity now in the agent world is in fact 10X more, but it does require us to have...Sarah Guo: For example, there's going to be usage around M365, right? Which is going to be perhaps more than even the e- end users and we have to even re-architect. Like, in fact, like what I use to serve an inbox or a mailbox cannot be used to serve an agent. Uh, and so that's sort of what we are doing.Pricing Models: Per-User, Consumption & OutcomesSarah Guo: I don't believe in, like, permanent business models for any of these domains, but in the [00:20:00] near term, do you have a prediction between, uh, you know, outcomes-based pricing, token-based pricing?Elad Gil: Enterprise bundles Yeah. The way I- I think about this is always we've had... Like, let's even take the per-user pricing. Mm-hmm. The per-user pricing is really an artifact of someone creating a budget needing certainty, right? Because it's the most important thing. Like, somebody wants a budget- Mm-hmm ... they need a per user.Satya Nadella: And, and per user is just a set of entitlements to usage, right? That's kind of what it is. And so the way is, if the first bundling will be take some usage, bundle it into per user stacks and, you know, then sell subscriptions. So subscriptions I think are gonna be there, per user is gonna be there. Then the next big thing will be consumption.So people will say, “I want consumption.” And it's also possible that people will say, “I don't even want to pay for any of the subscriptions or the consumption's outcome.” Mm. But remember, most people love outcomes until they have an outcome, because once you have an outcome, it's like giving away royalty, [00:21:00] right?Mm. I mean, like I, I've talked to customers who love, you know, outcome-based pricing, and I say, “I'm all in,” until they, “Oh my God,” like, “what are you talking about? You're sharing in my outcome? No, no, no. I want you to go back to per-user pricing, and I want you to consumption price,” right? So I think that debate will go on.Uh, but and all, all, all of these business models have a particular time and a place versus one to rule them all. And if anything, if you're a SaaS vendor or you're a platform vendor, having that flexibility... And quite frankly, we face this with GitHub, right? We just recently announced a per-user pricing on GitHub because little, you know, we- GitHub Copilot was constructed at a per-user level before we understood even, uh, the intensity of usage of agents, right?It was an interactive way for a developer to use code complete, maybe tasks. It was not like, oh, I launched 10,000, you know, agents that are going on all day, right? So that is what the adjustment is about. So now that we really want, there will [00:22:00] always be a per user, but there will have to be a consumption meter.Durability of SaaS & Build vs BuySarah Guo: How do you think about the durability of SaaS more generally? One thing I've observed is in a lot of enterprises internally, there will be teams that almost have agent euphoria. They're so excited about the explosion of things they can build that they're trying to rebuild a lot of applications or going to their SaaS vendors and saying, “We're not gonna work with you anymore,” or, “We're considering an internal project.”And it seems like in six to nine months, maybe some of those people will come back and say, “Actually, we, we can't rebuild everything.” How do you think about what's durable in this world and what isn't? Yeah, it's a... It... I think we have to go through one full budget cycle on this to really see the, um- Uh, the sort of the emergence of the equilibrium, because at the end of the day, there's marginal cost to even generating the app, right?Elad Gil: In, in fact, there can be even a, a simple way to say it, like if you should always acquire something if the marginal cost of building and maintaining, uh, something on your own is higher. Uh, right? That should be like it's a quantifiable- Yeah. Right? A quantifiable thing. And [00:23:00] the maintenance part is important, right?Even, like you got to remember like, hey, you know, all the security stuff that now AI will find, you better fix them too fast. Uh, of course, there's a coding agent to help you with, but then that burns tokens, right? So whose responsibility is it? It's kind of like a, a cycle that you've got to think through.And I think we have gone through the excitement that I can generate a lot of software. I think the next thing would be what software do I really want to generate? Mm-hmm. What software do I want to use from others? How do I compose these two into some agentic workflow that I have agency over, right?Sarah Guo: Because I think there'll be very little tolerance for anybody who's inflexible, uh, at the vendor level. Uh, but at the same time, I think that anyone who has got that flexibility shows up, delivers the value, will be back at again, right? We're selling software, uh, but with just different business models, in fact Uh, speaking about building software, um, one of my favorite moments from, I think, a previous build maybe one or two years ago was they had a b- they, they...Swyx: There was a section of you building your [00:24:00] own software. I'm curious if you're building anything now. Yeah. So I, I think the... You know, first of all, let's face it, right? Building software has made it possible for even the incompetence of a CEO of a company- ... like ours, uh, you can build, so thank God. But that said, I, I, I, I do feel that, you know, something like, um, GitHub Copilot to me, and especially the new Sessions app or the new app, has just made it so much more possible for you to have agency over artifacts that you felt you couldn't touch before, right?Satya Nadella: So to, for me as a CEO, even to go to a code base, uh, to be able to learn about it, like I remember joining Microsoft long back, you know, first and then you say, man, everybody had to go in and look at, you know, whatever, Cutler's, Malik, or what have you to learn how to do good C, uh, C++ code. Um, so now that ability to be more full stack up and down is so good, but that doesn't mean every one of us should be doing the same thing.The question is: [00:25:00] how do you then have the ability to inspect things, learn things, see things, um, I think is just so much more. And so to me, what I'm building a lot of is these long-running Foundry agents. Uh, right? So there's autopilots. So the easiest thing is, to me, I think I just built one, uh, even last week, where the idea was, hey, can I have an agent that is continuously monitoring essentially my own chief of staff autopilot, right?We're gonna have that obviously in, uh, Scout. That's what, uh, uh, we showed. But it is so easy and trivial to build. I took Work IQ. I said, “Take Work IQ, go, uh, and build a Foundry long-running agent.” Uh, store all the memory in, um, uh, using Ray Fin, right? Basically at my backend as a service. And lo and behold, it built it, and not only built it, I could say publish to Teams, and it published the damn thing to Teams.Sarah Guo: So the ability, uh, to have a, you know, some end-to-end project like this complete is just pretty [00:26:00] miraculous. How do you think, uh,Future Engineering RolesSarah Guo: that impacts the different types of engineering roles that exist in the future? Because right now I think there's, you know, a dozen different types of engineers that you can be, from QA, front end, et cetera.You know, there's a big swath. I've heard some people argue that in four or five years we'll basically end up with four engineering roles. It'll be people who are managing agents, it'll be four deployed engineers or FDEs, it'll be security engineers, and then people working on large scale infrastructure for a small number of services, and then everything else just collapses into the agentic world.Satya Nadella: Yeah, I- Do you think that's a correct view of the world? Yeah, I mean, I think, I think we'll have to experiment our way through it. But what you said is what... There are some very at scale things. At LinkedIn, they did structurally change- Mm-hmm ... uh, and it, you know, basically built up a new discipline called full stack builder, right?So they went and said, “Hey, let's bring, uh, people from design and product management, front end engineering, all put them together.” Uh, but also have an edge, right? It's not like the design person still doesn't have the design edge, or the front end [00:27:00] person doesn't have the front end edge, but you can give yourself bigger scope in roles so that you're not confined to one role.Um, and then r- equally, infrastructure has become very critical, right? So in other words, like, I mean, RLEs, I mean, one thing we've realized is even for the Excel team, for example. Mm-hmm. Building the RLE in which a reward can be learned is actually one of the hardest sort of infrastructure problems.Mm-hmm. Uh, and so you kind of need even new talent, right? Distributed systems people even in what was considered an end user app team, uh, because it's a different skill set. So yes, infrastructure, science is the other one, obviously. Um, so I think we'll see how these evolve, right? Where's the s- real... I mean, always the world will have a bunch of specialists.Okay. Um, you know, I think the generalist role is going to be the most exciting, right? Because the leverage of a generalist- Mm-hmm ... um, is where we are going to see the maximum returns, right? When, when you said, “Hey, are you coding?” I'm now a gen- Like, what... I've basically translated [00:28:00] knowledge work Right?Which I did, where I created a Word document or a spreadsheet, or even, uh... And now I can build an app, right? It's in the same sentence. Uh, right? That idea that, “Oh, wow, my generalist skills have gotten higher leverage,” I think is what we're gonna see across the board. Music to the ears of CEOs and VCs that are, like, a little dangerous and a lot of- Golden age for idea peopleSarah Guo: idea people. Yeah. Uh- With a lot of agency. I- if you take that idea of personal agency and you just zoom it out to the organizational context, um, uh, my partner Mike Renall, who, uh, actually started his career at Microsoft, just wrote an essay where one of the big takeaways is i- it's an age where you can be much more ambitious, and you need to be, given the pace of the environment and how quickly, actually, users and companies are open to adopting new technologies.Satya Nadella: Um, how do you think about... I, I feel silly asking this of somebody running a, you know, trillion-dollar-plus company already, butAmbition & Making the Impossible PossibleSatya Nadella: how do you think about how Microsoft can be more ambitious now? It's a great question. Um, I [00:29:00] think, um- I think the, the thing in these type of transitions is to have a conceptual model of how work can change to go after outcomes that you could hardly imagine previously, right?In fact, Kevin Scott has this nice line, right, which is, um, when you can make the impossible... Like, when you're making hard things easier, that's sort of one point of leverage. But true ambition is about making the impossible possible. So now the thing that is missing a little bit in all of our organizations is what is that new conceptual model of what can we build?What was impossible and what can we build? And I'll give you one example of this, right, which is I take great inspiration from sort of the people who were managing the Azure net- network. And they came to the... This was from even last year. You know, we were scaling. You saw that I, I [00:30:00] talked about sort of how we built in the last 15 months more Azure capacity than we built in the first 15 years.I mean, it's crazy. Wild. Yeah. Right? It's pretty wild. And it's the same team. So they saw that and they said, “Bob, this just ain't gonna work if we don't reconceptualize our work.” So they built... Essentially they said, “Our job is not to do Azure networking. Our job is to build the agentic system does, that, that does Azure networking,” right?These are the folks managing the 500-plus fiber operators managing the VAN, right, all over. And fiber operations ultimately is a physical operation. Things get cut, things get, uh, you know, have to be repaired. You know, we have fancy words called DevOps and so on. Basically, emails are coming in and you gotta go respond to them, take care of it.So they built this agentic system. They even have a character for it. It's called Miles, and it sort of does all this stuff, right? They started sort of screaming for more tokens and so on. And so they were saying, “Look, uh, we don't need a headcount. We need tokens in order to be able to [00:31:00] manage, uh, our operation.”That reconceptualization- Mm-hmm ... of what their work is, right? They, they basically took their work and made it meta, right? That meta work is now their new work. Mm-hmm. Right? In the ‘80s, if somebody had come to us and said, “4 billion people are gonna get up in the morning and start typing,” my model would've been, we need 4 billion typists?But we're not doing typing, we're doing knowledge work. So that, to me, I think is it, right, which is whether it's Microsoft or whether it's any organization, is to give ourselves permission to do new types of metacognition, meta work, using these new tools to change the outputs that matter, uh, and then really make the impossible possible.Sarah Guo: So completing that dot or the, the connective tissue across those, I think, is where a lot of the enterprise value will get created.Data Center Build-Out & Community ImpactSarah Guo: Should we talk about data centers? Yeah, please ask. Oh, okay. Well, uh, uh, w- we-- this leads nicely into the data center build-up. I always think, I- I just-- I'm just impressed at the sheer scale of the [00:32:00] build-out from Microsoft, but also everyone else, that this is redefining what it means to be a hyperscaler.And I just feel like that, that, that is at unprecedented scale on finances, uh, on the way you run the company, but also the communities that are, that are impacted. Um, yeah, just talk a bit more about what you're seeing on the ground, like when you visit your- Yeah, I think there are two aspects of it.Satya Nadella: Obviously, the, the build-out is, uh, extraordinary. Um, you know, nothing like this has happened, and it's great to be, uh, one of the participants in it. Uh, but you brought up the other part, right? I think at this point it's clear that unless we as an industry, uh, are very principled about ensuring that the benefits of all the stuff we're talking about are felt in real ways, uh, at the community level, right?Because this is not just a, a campaign, um, right? It has to be real, where people are saying, “Look, this is not ch- changing the prices on energy for me.” In fact, if anything, it's bringing down prices because long term there's going to be a better [00:33:00] grid, there is going to be more energy. Water consumption is, in fact, not sort of, uh...In fact, water is being replenished, right? You gotta really, you know, educate folks on truly what's happening, the cl- uh, the closed loop systems we are building. We have to invest in the training, the jobs, the tax base. In fact, the least talked about stuff is the amount of jobs that get created during construction, after construction.What's the tax base that's there in the community? And, and all this has to be real. Um, and, and if that is the case, then we will have permission. If it is not, we won't have permission. It's as simple as that, right? Which is, uh, we, we... I think we have to take it as an industry pretty seriously. Uh, I think it's good for communities to be skeptical, ask the hard questions, for us to do the hard work, earn that.Um, but at the end of the day, if there's-- if we can really be the produ-- Wait. I've always felt like in human history, if you use a lot of energy but also create a lot of value for society- The story has been fantastic. If you don't [00:34:00] do that, it's not been that great. And this time around, I'm a firm believer that ultimately if you do have a token economy that drives productivity, that drives economic growth, that drives broad spread, um, you know, participation, better health outcomes, um, then I think we'll be in a great place.Sarah Guo: Uh, and that's at least what we all have to be focused on. Yeah. It, it makes me think actually that with all these initiatives that you're doing, might be e- easier to see ROI in the communities first before in enterprise. Yeah. I, I mean, I think both sides. Yeah. In fact, it comes back together. It has to be the people in the communities are going to be employed, are going to be participants, uh, in the real economy, right?Satya Nadella: That's I think the question is. Like, if we- if the broad economy is doing well and the communities are doing well, the dots get connected. It's sort of the market forces are such that we will connect the dots. And that I think is it. Like, you ought to be able to see the evidence. You can't be about o- any one company, uh, but it has to be broad economic growth and broad [00:35:00] ec- you know, community permission.Elad Gil: Yeah. I guess I wanna talk aboutSocietal Impact & Optimism About AIElad Gil: what you're most optimistic about currently or what have you most updated your personal models on regarding societal impact of AI? So you're saying what's the, the, the- What have you updated most on in terms of societal impact of AI? Yeah. I think the, um, the p- the most, um- Critical thing is the first question we even started with, which is we need to tell the story and make it real that everybody has a real shot to participate as a first-class participant in this new economy.Satya Nadella: Right? That's kind of, I think we- in the next 12 months, 18 months, we need a way for people to say, “Oh, wow, I get it.” Right? There's going to be tremendous capability, tremendous amount of infrastructure, but I can see what is going to happen, whether it's the benefits like health outcomes or my ability to create a startup or my ability to run my [00:36:00] local sort of, uh, store more efficiently.It's just happening, and I see that, uh, benefit myself, right? That to me, you know, earning that permission in a path-dependent way, we can't wait. See, the one thing, Eli, that I've now learned is I think the world is gonna be very skeptical of tech and tech companies that say, “Trust us, we've got it. The g- future is gonna be glorious.”Sarah Guo: Uh, you kind of have to deliver tangible benefits. Um, and quite frankly, politicians winning elections, uh, because they have advocated for that. That will be at least my adjustment because without it, um, thinking that somehow... Because it's too important this time around. It's too much of the economy for it not to be the case So one very simple framework I have for, you know, what are, what is gonna be the broad benefit of AI, um, beyond the communities just working in technology, are, are sort of wealth creation- Yepit's [00:37:00] gonna happen in a ton of different companies, startups and large companies. Then you have healthcare. Uh, you, you had amazing demos today. There are companies like Open Evidence. I think that is happening. Um,Education & Future of LearningSarah Guo: education seems like another one that's an- Yep ... obvious good where we haven't seen as much impact as I'd expect.Swyx: Do you have a hypothesis on why that might be, or if it'll come? Yeah, I mean, I think this is where, again, how we think about education, how... You know, recently I met with, uh, the founders of Alpha School and learnt a lot about what they were going and going about, and it's fascinating to listen, uh, to how to even rethink- MmSatya Nadella: uh, what does education really look like. Because I think it's actually very important. Mm. Uh, and I'm not saying anything traditionally being done is less important, right? I was even looking at the, uh... It's fascinating to see. I, I, I forget the which Stanford class it was, uh, the, the Asian guidelines for CS something.Mm. Uh, because you still need people to learn. Uh, like it was an interesting AI class that they were making sure people were learning how to apply softmax appropriately versus saying, “Hey, fix my training run.” Mm-hmm. Uh, so I think learning concepts is important. It's going to [00:38:00] be, uh, critical. But the way we create the incentives, what are the credentials, how we value those credentials, what is the employment opportunity for those credentials?So I think that there's a complete change that has to happen, uh, given the way to get to information, way to educate yourself, way to continuously keep yourself updated has changed so much. So I think interestingly enough, maybe the next big startup and success story could be someone who builds a new university, um, or a new, um, pedagogy even of how to get someone to go through a curriculum and find economic opportunity, uh, that's highly valuable.Well, that has felt, uh, perhaps impossible for a long time, but it's a great note to end on and something that might be possible. It's still possible. Yeah. Thank you, Satya. Thank you so much. Thank you. Yeah. I appreciate it. Thank you all. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.latent.space/subscribe

Mike & Tommy dive into Claude Design meets Power BI Embedded, exploring whether AI-generated UX is a shortcut or a quality risk, how semantic models stay the source of truth when LLMs scaffold embedded apps, and what guardrails belong on every AI-assisted analytics project.https://www.reddit.com/r/PowerBI/comments/1sy5kue/claude_design_meets_power_bi_embedded/Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Vom Monatsbericht zur Echtzeitsteuerung – das klingt einfach, stellt Unternehmen in der Praxis aber vor erhebliche Herausforderungen. Daten in Echtzeit erfassen, aufbereiten und für Entscheidungen nutzbar machen erfordert mehr als Technologie: Es braucht neue Organisationsstrukturen, integrierte BI-Plattformen und eine veränderte Unternehmenskultur. Die neue Ausgabe 3/2026 der Fachzeitschrift Controlling zeigt: Von der Reporting Factory über Matrixproduktionssysteme bis zu Digitalen Zwillingen – Echtzeitsteuerung ist ein Gesamtpaket aus Technologie, Organisation und Kultur. Im Performance Manager Podcast spricht Peter Bluhm mit Prof. Dr. Burkhard Pedell, Inhaber des Lehrstuhls für Controlling an der Universität Stuttgart und Mitherausgeber der Fachzeitschrift Controlling: Warum reichen Technologie und Organisation allein nicht aus – und welche drei Hebel müssen gemeinsam angepackt werden? Wie verkürzt eine zentrale Reporting Factory die Analyselatenz – und welche Rolle spielen Power BI und Robotic Process Automation dabei konkret?  Wie verändern Digitale Zwillinge das Controlling grundlegend – und welche Kompetenzen müssen Controller jetzt aufbauen? 

We'll tell you what's new, again. Microsoft 365 Copilot Chat. That's right. Simplified. Faster. More under the more menu. Less colour. Save your Teams Events as templates and get a glimpse of the new Events app. Take a look at the Planner Agent from Copilot, now GA. This and more... 0:00 Introduction 2:39 Microsoft 365 Copilot: Planner agent general availability - MC1323264 8:08 Power BI integration with Microsoft 365 Copilot - MC1323266 13:17 Save your event as template to reuse event configurations - MC1324279 17:59 PowerPoint Live adds the ability to reload updated presentations during meetings - MC1324281 20:48 Microsoft 365 Copilot app: Simplified, chat-centered experience - MC1325422 28:06 (Updated) New entry points for "Create pages with AI in SharePoint" - MC1324284

Mike & Tommy tackle Microsoft Fabric hints to work faster, exploring whether teams are wasting time due to self-inflicted bad workflows, poor reuse, and confusing busy work with shipping value. They break down which repeatable tasks should be standardized first, when "just build it" becomes technical debt, and what practical Fabric habits listeners can adopt this week to stop the waste and start delivering faster.Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Heads up — this is Part 2 of Jamie's conversation with Jaclyn Taylor If you haven't heard Part 1 yet, go back and start there. It sets up everything we unpack today. Most healthcare teams are working hard. They're just not working together. And the patient is the one absorbing the cost. In this second half of the conversation, Jamie and Jaclyn move from the why into the how. What does it actually look like when a provider stops responding to today's schedule and starts managing an entire patient panel? How do you turn a community health worker, a pharmacist, a PT, and a social worker into one coordinated team instead of four parallel ones? And what's the difference between data that produces reports and data that produces decisions? You'll hear: Why "frequent touches" only work when they're connected — and how fragmented touches still land patients back in the hospital The quarterback model — what it actually means for a provider to own a patient's trajectory, not just their visit The shift from seeing patients to managing a population — and why most providers were never taught how Why we don't have a resource problem in healthcare — we have an orchestration opportunity How to use technology and data without drowning in either What "showing up" really means inside a system that isn't perfect yet This is the episode for anyone trying to lead change from inside a system that's still catching up. Press play. www.YourHealth.Org

Mike & Tommy explore agentic skill and report design, diving into the "Five Minutes to Wow" framework and whether AI agents accelerate great design or amplify bad habits. They confront questions about who owns design decisions when the AI makes the call, how to balance speed with craftsmanship, and what guardrails prevent self-service clutter—ultimately wrapping up with practical takeaways for anyone opening Power BI Desktop tomorrow.https://data-goblins.com/power-bi/five-minutes-to-wowhttps://community.fabric.microsoft.com/t5/Power-BI-Updates-Blog/Power-BI-May-2026-Feature-Summary/ba-p/5182174https://community.fabric.microsoft.com/t5/Power-BI-Updates-Blog/New-Power-Query-experience-in-Power-BI-Desktop-Preview/ba-p/5181129Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Le commissaire aux comptes est souvent vu comme celui qui vient demander des factures, refaire des contrôles et ajouter de la contrainte.Mais est-ce vraiment ça, l'audit ?Dans cet épisode des Geeks des Chiffres, je reçois Victor Laschon, expert-comptable, commissaire aux comptes et cofondateur de DataYoyo.Après près de 10 ans chez KPMG, Victor a cofondé DataYoyo avec une idée simple : aider les auditeurs à mieux exploiter la donnée pour arrêter de passer leur temps sur la formalisation et revenir au cœur du métier.Dans cet épisode, on reprend l'audit depuis la base :À quoi sert vraiment un commissaire aux comptesPourquoi l'audit légal est souvent mal compris par les dirigeantsComment se construit une mission d'audit : acceptation, indépendance, approche par les risques, seuils, certificationPourquoi auditer une maison de champagne, une usine ou une société cotée ne demande pas la même lectureCe que le rehaussement des seuils a changé pour la professionComment la donnée, le FEC, la DSN, Power BI et l'IA peuvent transformer le métierPourquoi il vaut mieux demander 10 factures pertinentes que 40 factures prises au hasardComment repérer des écritures atypiques : créances clients extournées en dettes fournisseurs, provisions, mouvements étrangesPourquoi l'automatisation ne remplace pas l'auditeur, mais peut remplacer ce qui l'empêche de réfléchirLe vrai sujet des juniors : progresser, poser les bonnes questions, comprendre les comptes au lieu de remplir des fichiersPourquoi Victor pense que l'audit reste un métier d'avenir pour ceux qui entrent dedans avec le bon prismeLe message de l'épisode est clair.La data et l'IA ne doivent pas enlever de la valeur au métier.Elles doivent lui en redonner.LinkedIn de Victor : https://www.linkedin.com/in/victor-laschon/Site DataYoyo : https://datayoyo.frCode Promo YT1 : - 10% sur toute la plateforme Les Geeks des Chiffres.--------Bienvenue sur le podcast n°1 de la filière comptable et financière ! + 850 000 écoutes.Je suis Nicolas Piatkowski, cofondateur de l'école en ligne Les Geeks des Chiffres, qui a formé plus de 14 000 étudiants au DCG & DSCG : https://www.lesgeeksdeschiffres.comChaque semaine, des pros du chiffre me partagent leur parcours, leurs réussites (et galères !), leurs conseils, et t'aident à décrypter un secteur en pleine mutation.Que tu sois en DCG, DSCG, alternance, BTS ou un professionnel aguerri… Tu trouveras ici des interviews inspirantes, des retours d'expérience concrets, des insights métier et des clés pour te démarquer dès tes premières expériences.Bonne écoute… et c'est partiiiiii !  »Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

Mike & Tommy dive into whether agentic tooling should be driving your Knowledge Center, exploring if docs, support, and governance content can—or should—be fully automated by AI, and what that means for the future relevance of your CoE.Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Help us become the #1 Data Podcast by leaving a rating & review! We are 67 reviews away! The odds are stacked against you for remote data jobs. I show you how to flip them in your favor.

Send us Fan MailLeadership in healthcare simulation doesn't always come with a title or a roadmap. One day you're an educator or clinician, and the next day you're responsible for staffing, budgets, accreditation prep, outcomes, and the long list of “Can you also…?” requests that land on a simulation program. We sit down with two leaders who have lived that reality and built thriving programs anyway: Dawn Swiderski, Associate Vice President of Simulation Services at the Carolina Simulation Center at Atrium Health (now Advocate Health), and Cheryl Camacho, Director of Simulation and Outreach at Nationwide Children's Hospital.We dig into the shift from the SSH Directors Section to the Simulation Program Leadership Section and why that change is more than a rebrand. It's a move toward inclusion for people leading without the “director” label, whether you're new to simulation, stepping into management unexpectedly, or guiding a program through influence instead of authority. Dawn and Cheryl share how they listen to member feedback and turn it into practical support that actually matches what leaders need in the moment.You'll also get a clear tour of what's available through SimConnect: quarterly webinars, section meetings, and the highly popular couch conversations where members bring burning questions like simulation ROI, accreditation, costing models, policies, staffing allocation, and how to prove value with metrics and KPIs (including examples like Power BI). We talk about the underused SimConnect library filled with templates, forms, job descriptions, and recorded sessions that help you move faster, especially if you're tired of reinventing the wheel.If you lead any part of clinical simulation education, patient safety simulation, or simulation operations, this one is built for you. Subscribe, share it with a simulation colleague, and leave a review with the leadership topic you want tackled next.Innovative SimSolutions.Your turnkey solution provider for medical simulation programs, sim centers & faculty design.

Most marketing teams hand sales a stack of brochures and never hear back. In this episode of Content to Close, Nat Norris, VP of Marketing and Customer Success at Model 1 Commercial Vehicles, breaks down how his team gets out of the trophy case of unused white papers and into the rooms where deals are won and lost. Nat walks through how he embeds marketers inside the company's three sales segments (public, commercial, and retail), why he forces his team into weekly quote review and deal loss meetings, and the data hygiene work he had to do in Power BI before any of it could function. He also shares the FAB framework (Features, Advantages, Benefits) he carried over from his catalog days, with a simple rule: push the benefit, self-serve the feature. And he closes with the two governors he uses to decide when there's enough data to act: the 80/20 rule and the "front page of the newspaper" worst-case test. If you've ever wondered how to turn marketing collateral into something sales actually uses, this one's for you.About NatNat Norris is the VP of Marketing and Customer Success at Model 1 Commercial Vehicles, a nationwide commercial dealership selling work trucks, cargo vans, school buses, and shuttle buses. Based in Indianapolis, Nat has spent about 17 years in B2B marketing for equipment, with stops in e-commerce and large holding-company environments before landing at a single-family-owned business. His group leads marketing, customer experience, product information, customer care feedback, and inside sales lead qualification. Nat is a self-described data and dot-connecting nerd whose old product-management instincts shape how he thinks about content, storytelling, and what salespeople actually need in the field.Show Notes- Connect with Nat on LinkedIn: https://www.linkedin.com/in/natnorris/Text us what you think about this episode!

Mike & Tommy explore the importance of agentic skills for the Fabric developer, weighing whether Skills are a productivity breakthrough or another governance risk, and discussing how to build, version, and share Skills without sacrificing engineering discipline.https://github.com/mattpocock/skills/blob/main/skills/productivity/grill-me/SKILL.mdhttps://community.fabric.microsoft.com/t5/Power-BI-Updates-Blog/Semantic-model-settings-pane-Preview/ba-p/5177694https://community.fabric.microsoft.com/t5/Power-BI-Updates-Blog/Execute-DAX-Queries-REST-API-Preview/ba-p/5177697Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Mike & Tommy dive into Databricks Genie and the growing hype around data agents, exploring whether the real challenge is natural language chat or the semantic layer underneath—and what Power BI teams must fix before any AI agent can deliver trusted, governed answers at scale.https://www.advancinganalytics.co.uk/blog/genie-is-a-semantic-layer-problem-not-a-chat-problem-1https://community.fabric.microsoft.com/t5/Fabric-Updates-Blogs/OneLake-catalog-is-now-natively-available-in-Foundry-Generally/ba-p/5178376https://community.fabric.microsoft.com/t5/Fabric-Updates-Blogs/Direct-Lake-on-SQL-with-Fabric-Data-Warehouse/ba-p/5177641https://community.fabric.microsoft.com/t5/Power-BI-Updates-Blog/Modern-Visual-Tooltips-in-Power-BI-Generally-Available/ba-p/5173946Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Mike & Tommy weigh in on whether bookmarks in Power BI are still worth the maintenance burden, exploring how field parameters, slicers, and modern features have changed the game, and when you should still reach for bookmarks versus simplifying your data model instead.https://tabulareditor.com/blog/ai-readiness-and-best-practices-for-semantic-models-a-comprehensive-guidehttps://community.fabric.microsoft.com/t5/Fabric-Updates-Blogs/OneLake-catalog-is-now-natively-available-in-Foundry-Generally/ba-p/5178376Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Help us become the #1 Data Podcast by leaving a rating & review! We are 67 reviews away! I made a tool that turns your GitHub projects into a real portfolio. Here's what it looks like in action.BUILD YOUR OWN PORTFOLIO: https://dcj.app/mydatafolio-0QqsQr

This is episode 326, recorded on May 7th, 2026, where John and Jason break down the Power BI & Fabric April 2026 Feature Summaries — DAX user-defined functions are here in preview, Direct Lake is flexing new modeling muscles, the Dataflows Gen1 community drama has a plot twist, Fabric Data Warehouse finally gets true transactional DDL, and VS Code integration in Fabric notebooks keeps leveling up. It's the April feature summary double-header. For show notes please visit www.bifocal.show

In this episode we dive into performance reviews.The ChallengeYou're a senior scheduler running three data center schedules for one client. Your manager calls a quarterly performance review. You're great in P6, you hit your reports, and you assume the conversation will write itself. It won't. In this episode, I play the manager and Greg Lawton plays the senior scheduler to show what most schedulers get wrong in that room and how to turn the review into your next promotion.Continue LearningCheck out our book The Critical Path Career: How to Advance in Construction Planning and SchedulingSubscribe to the Beyond Deadlines Email NewsletterSubscribe to the ⁠⁠⁠⁠Beyond Deadlines⁠⁠⁠⁠ Linkedin Newsletter⁠⁠Check Out Our YouTube Channel⁠⁠.ConnectFollow ⁠⁠⁠Micah⁠⁠⁠, ⁠⁠⁠Greg⁠⁠⁠, and ⁠⁠Beyond Deadlines⁠⁠ on LinkedIn.Beyond DeadlineIt's time to raise your career to new heights with Beyond Deadlines, the ultimate destination for construction planners and schedulers. Our podcast is designed to be your go-to guide whether you're starting out in this dynamic field, transitioning from another sector, or you're a seasoned professional. Through our cutting-edge content, practical advice, and innovative tools, we help you succeed in today's fast-evolving construction planning and scheduling landscape without relying on expensive certifications and traditional educational paths. Join us on Beyond Deadlines, where we empower you to shape the future of construction planning and scheduling, making it more efficient, effective, and accessible than ever before.About MicahMicah, the CEO of Movar US is an Intel and Google alumnus, champions next-gen planning and scheduling at both tech giants. Co-founder of Google's Computer Vision in Construction Team, he's saved projects millions via tech advancements. He writes two construction planning and scheduling newsletters and mentors the next generation of construction planners. He holds a Master of Science in Project Management, Saint Mary's University of Minnesota.About GregGreg, an Astrophysicist turned project guru, managed £100M+ defense programs at BAE Systems (UK) and advised on international strategy. Now CEO at ⁠⁠Nodes and Links⁠⁠, he's revolutionizing projects with pioneering AI Project Controls in Construction. Experience groundbreaking strategies with Greg's expertise.Topics We Coverchange management, communication, construction planning, construction, construction scheduling, creating teams, critical path method, cpm, culture, KPI, microsoft project, milestone tracking, oracle, p6, project planning, planning, planning engineer, pmp, portfolio management, predictability, presenting, primavera p6, project acceleration, project budgeting, project controls, project management, project planning, program management, resource allocation, risk management, schedule acceleration, scheduling, scope management, task sequencing, construction, construction reporting, prefabrication, preconstruction, modular construction, modularization, automation, Power BI, dashboard, metrics, process improvement, reporting, schedule consultancy, planning consultancy, material management

On this episode of The Association Podcast, we welcome Lacey Pope, MBA, CAE, Customer Success Manager at Web Scribble, to discuss her career journey in associations and her transition to the industry partner side. Lacey shares how she entered the association world through temp work, earned her CAE, and later drove process improvements at the Oncology Nursing Society that increased live support and boosted customer satisfaction by nearly 10%. She reflects on leading membership technology modernization at Shriners International—including AI translation tools, a new LMS, project management platform, and Power BI reporting—work that earned her recognition at the AWTC Awards. The conversation also explores hiring in the age of AI, daily AI use in customer success, and how associations can build stronger workforce development pipelines beyond a basic job board. 00:00 Welcome and Introductions 00:36 Rapid Fire Questions 02:17 Lacey Association Journey 03:26 Process Improvement Wins 04:55 Career Pivot and Web Scribble 07:22 Awards and Title Tradeoffs 09:32 Vendor Side and Member Value 12:05 Meet Mabel Topic Wheel 13:23 Hiring in the Age of AI 17:44 Daily AI and Policies 20:01 Using AI On The Side 20:51 Five-Year Career Pivot 22:17 Recruited To WebScribble 23:00 Industry Credibility Matters 24:58 Networking And Job Boards 27:02 Daily Wins And Parenting 28:21 AWTC Recognition And Belonging 30:52 Recognition And Community Growth 33:24 Customer Success Trends 34:51 Advice For Student Pipelines 36:42 What WebScribble Does 38:32 Final Thanks And Wrap

Get featured on the show by leaving us a Voice Mail: https://bit.ly/MIPVM  This episode explores how Microsoft Planner is evolving into a practical, AI-assisted project management tool for modern teams. Cindy Lewis explains how Planner fits into daily work through Microsoft Teams, how AI agents support planning, reporting, and risk assessment, and why small usability improvements matter. The discussion also covers Copilot, Dataverse, Power BI, and the shift from automation to agent-style AI that actively helps manage work. 

Mike & Tommy dive into Building Agentic Tools for Microsoft Fabric With Alex Powers, exploring Microsoft's Alex Powers' new tool 'Taskflow Assistant' for Microsoft Fabric and how AI is transforming the way professionals work with Fabric workflows, discussing whether we're helping users master the platform or avoid learning it altogether.https://github.com/microsoft/fabric-task-flowshttps://community.fabric.microsoft.com/t5/Fabric-Updates-Blogs/Discover-items-across-workspaces-with-the-OneLake-Catalog-Search/ba-p/5176768https://community.fabric.microsoft.com/t5/Fabric-Updates-Blogs/Pipelines-are-evolving-beyond-ETL/ba-p/5177527Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Help us become the #1 Data Podcast by leaving a rating & review! We are 67 reviews away! Skills aren't enough to land a data job. Here's what Graham was missing and how we fixed it live.

Treasury teams are being asked to move quickly to digitalize, with AI only adding to the pace as the number of tools, use cases and ideas keeps expanding. The challenge for many NeuGroup members is figuring out where to start and what will actually make a difference. In this episode, Dan Morrison, Global Treasury Digital and Performance Manager at SLB, formerly Schlumberger, joins NeuGroup's Justin Jones to discuss how treasury teams can make AI useful without getting overwhelmed. For Mr. Morrison, the future of treasury starts with consolidating information in tools like SAP Central Finance, a system that consolidates financial data from multiple enterprise resource planning (ERP) systems into a single platform. From there, the focus shifts to how the data is used.Across SLB, teams have built dashboards in Microsoft's Power BI, often referred to internally as PBIs, to visualize cash positions, exposures and other key metrics. Some are highly effective, but they are not always consistent across regions. Part of his role is identifying what works, standardizing it and scaling it, so treasury teams are working from the same data and definitions.As more processes become automated, Mr. Morrison emphasizes the need for clear ownership. That includes using frameworks like RACI (responsible, accountable, consulted and informed) to define who owns data, who validates it and how issues are escalated. Structure becomes more important as AI is layered in. If the data is inconsistent or ownership is unclear, the tools will only amplify the problem.Listen to the full episode for Mr. Morrison's insights on how AI is reshaping treasury, where to focus now and how teams can keep pace.

Rob was supposed to be finishing his book. Last chapter. Two days past deadline. Freedom was right there. Instead, he hit pause and recorded this. Because something from a few weeks ago wouldn't leave him alone. A Microsoft exec had dropped "Microsoft IQ" into a conversation weeks ago. At the time, it didn't fully land. Not unusual. There's been a steady firehose of new terms, new features, new promises. Most of them sound important. Not all of them are. Then he got deep into the data chapter. The one where you have to stop talking about what AI could do and deal with what it takes to make it work in a real company. And that's where this thing stopped sounding like a label and started looking like a plan. AI looks great right up until you ask it to do something that depends on your business. Your definitions. Your documents. Your people. That's where things usually start to wobble. Not because the model isn't capable, but because it doesn't have the context to land the answer. What Microsoft is doing with IQ is trying to meet that problem head on. ·       Fabric IQ is the structured side. Semantic models doing what they've always done, but now under a lot more pressure. ·       Foundry IQ is all the documents and content you forgot you had. ·       Work IQ is the human layer. Who's involved. Who needs to know. What you meant when you said "that thing." And yeah… if you've been doing Power BI the right way, this is where it gets interesting. Because those semantic models everyone else treated like optional homework? That's now the thing everything else leans on. We're not saying this episode is the key to your AI implementation, but it will make it clear why some of this is working and some of it isn't.

Watch on YouTube: https://youtu.be/2aPU-4PUXNk  Clarity, resilience, and a commitment to building the right systems can transform how an organization operates and grows. In this episode of Stories from the River, Charlie Malouf welcomes Lee Vang, Senior Business Intelligence Developer, to reflect on his journey at Broad River Retail and the pivotal role he played in rebuilding the company's business intelligence foundation. Joining during a time of significant transition, Lee shares how he stepped into a near non-existent BI environment and took on the challenge of creating the infrastructure needed to support leaders and Memory Makers with accurate, actionable data. Lee discusses the evolution of data-driven decision making across the organization, including the development of foundational tools like the HFC KPI and Truth Report, and the integration of modern platforms such as ThoughtSpot and Power BI. He highlights the importance of data integrity, system alignment, and making insights accessible across all levels of the business. Visit https://www.storiesfromtheriver.com for more episodes.    Broad River Retail brought this show to you. Visit https://BroadRiverRetail.com    Follow us on LinkedIn: https://www.linkedin.com/company/broad-river-retail 

This is episode 325, recorded April 17th, 2026, where John and Jason dig into the Real-Time Intelligence section of the Microsoft Fabric March 2026 Feature Summary covering topics such as Business Events, DeltaFlow for CDC, real-time processing with Spark notebooks, and some welcome quality-of-life updates across Event House and workspace monitoring. For show notes please visit www.bifocal.show

Mike and Tommy review the most underrated Fabric features based on buzz and client usageGet in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

This week on Explicit Measures, we tackle a critical "last mile" problem in Business Intelligence: how do you add narrative context to Power BI reports when the storytellers aren't Power BI users? Our listener has built monthly snapshot reports delivered to multiple business units, but marketing leads need to annotate these reports with context before they reach their final audience. We explore the gap between data delivery and storytelling, challenge assumptions about tool selection, and discuss practical patterns for integrating qualitative commentary with quantitative metrics—without breaking your data governance or forcing non-technical users into unfamiliar platforms.Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Mike & Tommy tackle the overfed golden dataset problem—when a single "source of truth" becomes a 100-table, 400-measure monster that takes four minutes to open. They explore why teams fall into the trap of cramming everything into one model, how fear of discrepant numbers drives over-centralization, and what it takes to split a bloated semantic model without breaking executive trust or reverting to data chaos.Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Mike & Tommy weigh in on whether Databricks and Microsoft Fabric are converging into direct competitors, exploring how Databricks' push into BI with Genie and AI capabilities is closing the gap on Power BI's presentation layer. They question whether "end-to-end" platforms are the future or just feature bloat, discuss where semantic models should live in a modern data stack, and help teams decide when to bet on one platform versus embracing the dual-stack reality.Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

This is episode 324, recorded on April 17th, 2026, where John and Jason continue through the Microsoft Fabric March 2026 Feature Summary — the Data Science & AI rebrand with Fabric Data Agents reaching GA, AutoML going GA, multimodal support for AI functions, the Data Warehouse section covering Fabric Data Warehouse recovery, Activator support, T-SQL AI functions, ANY_VALUE aggregate, Custom SQL Pools, SQL audit logs GA, outbound access protection, and the big one — the Database Hub, Fabric's new unified control plane for databases across edge, on-prem, cloud and Fabric. For show notes please visit www.bifocal.show

Mike & Tommy dive into improving AI skills for Fabric developers, exploring whether to start with prompt engineering or semantic modeling fundamentals, how to build real agents without organizational buy-in, and when AI tools actually add value beyond well-built reports. They tackle the tension between learning cutting-edge capabilities and mastering core BI craft, offering a practical 90-day roadmap for developers stuck in slow-adoption environments.Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Mike & Tommy dive into Joachim's repo-based golden semantic model architecture, exploring whether AI-assisted development is making the classic thin-report pattern obsolete and how upcoming MCP servers for report modeling might reshape architectural decisions. They weigh the trade-offs between file-based AI edits and application-layer safety, discuss when splitting reports makes sense, and tackle the question of whether Power BI developers are becoming software engineers by another name.Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

This is episode 323, recorded on April 16th, 2026, where John and Jason dig into part one of the Microsoft Fabric March 2026 Feature Summary — including the GA of OneLake Catalog Govern for admins, the OneLake Catalog Search API as an MCP tool, workspace tags going GA, DLP policies extending to structured data in OneLake, branched workspace with Git integration and selective branching, the new connection reference variable type, Fabric CLI v1.5 with one-command deployments, the Fabric Remote MCP server, OneLake File Explorer reaching GA, and the preview of Fabric Runtime 2.0 with Spark 4 and Delta Lake 4. For show notes please visit www.bifocal.show

Matt James, EVP, CFO & Chief Acquisition Officer at Oakbridge Insurance Roll-up platforms that skipped real integration are getting exposed when they go to market. Buyers want proof of organic growth, clean data, and a platform that actually functions as one. A lot of processes are breaking down because those proof points aren't there. Matt James co-founded Oakbridge Insurance in 2020 and has since closed 60+ acquisitions, integrating 100% from day of close. This conversation covers how he built that system, what went wrong with billion-dollar competitors, and what he would fix first if he walked into a revenue-aggregating roll-up right now.  What You'll Learn Why multiple arbitrage is gone, and what buyers are scrutinizing instead How Oakbridge evaluates cultural fit before any financial criteria What a failed billion-dollar roll-up sale process looks like from the inside Building integration continuity from LOI through 90 days post-close How distributed equity drives buy-in across an acquired organization  If you're evaluating targets and want to know if they're integration-ready pre-LOI, the Intelligence Hub can help you score cultural fit, data readiness, and technology maturity. Join the professional membership at  mascience.com/membership. ____________________ This episode is sponsored by DealRoom DealRoom's State of M&A Report gives you data to back up your M&A priorities. The State of M&A Report reveals the gap between what teams think matters and where the real bottlenecks are. Download it now to get expert insights: https://hubs.ly/Q03ZxRvD0 ____________________ Episode Chapters [00:03:00]  Introduction & Matt's Background [00:05:00] How Buyer Diligence Has Shifted [00:06:00] Organic vs. Inorganic Growth and Why It Matters [00:11:00] The Four-Criteria Deal Evaluation Framework [00:14:00] Validating Cultural Fit Before LOI [00:17:00] Deal Structure: Equity, Earnouts, and Alignment [00:20:00] What Billion-Dollar Platforms Got Wrong [00:26:00]Building the Integration System at Oakbridge [00:31:00] Bridging Diligence and Integration [00:38:00] Data Infrastructure: Databricks, Power BI, and Why It's Worth It [00:45:00] Building Proprietary Deal Flow [00:52:00] First Moves When Integration Is Broken