Raw Data with Rob Collie

P3 Adaptive

Raw Data with Rob Collie breaks down the complex world of AI into practical actions for modern business leaders. With co-host Justin Mannhardt and expert guests, the show uses real stories to deliver clarity and confidence to turn your data into real business value. Catering especially to mid-market leaders who know their size isn't a limitation but a competitive advantage, Raw Data cuts through the hype with straight talk from people who've actually built, deployed, and lived with these systems in high-stakes environments. Whether you're a business leader drowning in AI noise or a data practitioner ready to get off the starting line, you'll get accessible breakdowns of technology that drives actual impact, confidence-building roadmaps for modernizing data analytics, and practical wins you can apply immediately. This isn't theoretical frameworks or jargon wallpaper; it's honest guidance from leaders who've been in your shoes and figured out what actually works, so you can too.

  1. -18 h

    Knowledge Is Having Its Data Moment

    For years, businesses learned that having data and being able to use it are two very different things. We cleaned it, structured it, modeled it, argued about which version was the truth, and built entire careers around making messy information useful. Now AI is creating the same problem all over again. Except this time, it's knowledge. In this episode, Rob explains why everything we learned from the data era is suddenly relevant again. Companies are sitting on enormous amounts of knowledge scattered across documents, conversations, systems, processes, and people's heads. AI can consume more of it than ever before, but that doesn't magically make it organized, trustworthy, or useful. Which means a lot of those supposedly "old" data skills are about to look awfully cutting edge again. Rob also introduces The Goldilocks Altitude, his new Substack for ideas that live somewhere between the 30,000 foot AI think piece and the technical weeds. This episode features one of the first: "Everything We Did for Data, We Now Need to Do for Knowledge." Listen now, then head over to The Goldilocks Altitude. If knowledge is having its data moment, there's going to be plenty to talk about. Also in this episode: The Goldilocks Altitude

  2. 18 août

    What is "Botsitting?" (plus: Data Agents Continue to Blow Our Minds)

    There's a new word for what your team is doing with the AI you bought them. You're not going to love it. "Botsitting." Babysitting, but for bots. Journalists are suddenly all over it, and not one of the AI people Rob asked had ever heard of it. New name, familiar burn. Turns out mandating AI usage is a great way to pay good money for software that makes everybody slower. Then the flip side. Rob's spent years telling anyone who'd sit still that conversational data changes how we work. A recent experiment made him realize he'd been underselling his own argument. So one half of AI is wearing people out, and the other half is hooking people who never cared about data in their lives. We're still early, folks. And apparently, we're going to need some new vocabulary. Listen to the latest episode of Raw Data. Turns out AI gets a lot more interesting once you see what people actually do with it.

  3. 12 août

    Power BI Veterans React to the Fair Game AI Book

    For most of tech history, the new thing belonged to the new people. Then AI showed up and ruined a perfectly good pattern. Because the smartest model on the planet can know darn near everything and still have no idea how your company works. It doesn't know which rules matter, which ones everyone ignores, why that ugly spreadsheet still exists, or that the "temporary" workaround from 2019 is now apparently infrastructure. Jon Perl, Tim Rodman, and Trent McKinster join Rob for a conversation about Fair Game that pretty quickly becomes a conversation about who has the upper hand here. And it might just be the crafters. The people who spent years poking at problems, pulling things apart, building better ways to do the work, and collecting the kind of business context you can't download with a model. From there, things get wonderfully nerdy. Custom AI. Semantic models getting their long overdue victory lap. Whether SaaS is about to get picked apart one annoying subscription at a time. And the possibility that we've been thinking about the AI skills gap completely backwards. Maybe experience isn't the thing AI replaces. Maybe it's the thing AI has been waiting for.

  4. 4 août

    The Crafter's Edge with Pedro Rossello

    There have always been people who can't help themselves. Give them a clunky process, a messy spreadsheet, or a problem nobody owns, and they're already halfway to building something better. Rob calls them crafters. They were valuable before AI. They're becoming indispensable because AI rewards exactly the way they've always worked. While everyone else is trying to "become AI native," crafters are doing something much less glamorous. They're making one workflow better. Then another. Pedro Rossello from Aderant is one of those people. Along with Rob and P3's own David "Oz" Osorio, he makes the case that the biggest AI wins don't come from chasing the newest thing. They come from solving real business problems with better tools and better judgment. The funny thing is, those wins don't always look like AI success stories. They look like fewer headaches, smarter decisions, and work that simply gets done better than it did last week. That's the crafter's edge. It isn't flashy. It isn't loud. But it's probably what separates the companies still talking about AI from the ones already putting it to work.

  5. 14 juil.

    Everyone's Priority. Nobody's Job

    AI headlines have already moved on to the deep end. Most businesses haven't. Every week brings another headline about what's next for AI. Build your own model. Train your own LLM. Customize everything. It's exciting, unless you're one of the thousands of companies still trying to answer a much simpler question: where does AI actually fit into the work we do every day? Here's the thing. AI has become everyone's priority and almost nobody's job. Leadership knows it matters but the real work still lives inside thousands of everyday workflows, where tribal knowledge, context, and experience drive the decisions. That's the gap, and it's a very different problem than the one the headlines are chasing. That's the conversation Rob and Justin have this week. Sparked by Satya Nadella's comment that every company should eventually have its own LLM, they make the case that the industry is getting ahead of itself. As Rob puts it, "Everyone's sitting poolside and Satya's talking about the deep end." Most organizations don't need a custom model. They need AI that understands their business, their data, and their workflows. That's where the biggest wins are happening today, and it's exactly where companies should be focused before they start worrying about building their own LLM. If AI has started to feel like an arms race you somehow missed, this episode is a welcome reminder that the biggest opportunities are still waiting in the shallow end.

  6. 30 juin

    The End of All You Can Eat AI

    For about two years, we've all been reaching for the biggest hammer on the wall because someone else was paying for the nails. If you were on a subscription, you grabbed the biggest, baddest model on the menu and used the crap out of it. Two hundred dollars a month for work that would have cost thousands on the meter. It rounded to free. Then a new model showed up for roughly fifteen minutes. It wasn't covered by anyone's subscription. It was priced by the token. And Rob immediately saw something much bigger than a product launch. The migration everyone assumed would be painful, moving millions of people away from all you can eat subscriptions, suddenly had a simple answer. Just make the newest, smartest model a premium experience. Checkmate. The buffet doesn't disappear. You just have to decide whether the lobster is worth paying for. Justin made the exact mistake he told himself he wouldn't make. He tried it anyway. He handed the model a sprawling request to audit an entire codebase and walked away. It came back with nearly twenty legitimate findings, from accessibility improvements to a legal disclosure that referred to the company as a corporation instead of an LLC. More importantly, it handled a level of independent work he wouldn't have trusted another model to do. His reaction afterward said everything: "I wish I hadn't tried it." Because once you've seen what the next generation can do, you can't unsee it. But if using it costs six or seven thousand dollars a month for one developer, "always use the best model" stops being a habit and starts becoming a business decision. Whether you're building with AI every day or just trying to make sense of where it's all headed, this conversation is a good reminder that the technology isn't the only thing changing. The business model is too. Give it a listen and see where Rob and Justin think it all leads.

  7. 23 juin

    Waiting Worked...Until AI

    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

  8. 16 juin

    Why Bigger AI Isn't Always Better

    Microsoft just unveiled a monster of a machine built for local AI. More memory. More horsepower. More everything. Which led Rob and Justin to a question that has almost nothing to do with the hardware. Are we already using more AI than the job actually requires? This conversation starts with Microsoft's latest announcement but quickly turns into something much bigger. When do you actually need a frontier model? When is a smaller model just as good? And what happens when companies stop optimizing for the smartest AI and start optimizing for the right AI? It's a familiar pattern. New technology shows up, everyone assumes bigger is better, and eventually we learn that the best solution isn't the most powerful one. It's the one that's powerful enough. AI may be reaching that point faster than anyone expected. Along the way, Rob and Justin dig into the economics of tokens, why developers should think differently than everyday AI users, and why Microsoft's latest hardware announcement feels like it's missing a piece of the story. They don't pretend to have all the answers. Instead, they do what this podcast does best: pull on an interesting thread until a much better conversation emerges. If your first instinct has been to reach for the biggest model every time, this episode might convince you that the future belongs to the people who know when not to.

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Raw Data with Rob Collie breaks down the complex world of AI into practical actions for modern business leaders. With co-host Justin Mannhardt and expert guests, the show uses real stories to deliver clarity and confidence to turn your data into real business value. Catering especially to mid-market leaders who know their size isn't a limitation but a competitive advantage, Raw Data cuts through the hype with straight talk from people who've actually built, deployed, and lived with these systems in high-stakes environments. Whether you're a business leader drowning in AI noise or a data practitioner ready to get off the starting line, you'll get accessible breakdowns of technology that drives actual impact, confidence-building roadmaps for modernizing data analytics, and practical wins you can apply immediately. This isn't theoretical frameworks or jargon wallpaper; it's honest guidance from leaders who've been in your shoes and figured out what actually works, so you can too.

Informations

  • Création
    P3 Adaptive
  • Années d’activité
    2020 - 2026
  • Épisodes
    242
  • Classification
    Contenu explicite
  • Site web de l’émission
    Raw Data with Rob Collie

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