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.

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Tuesday · 35 min
AI and the Rule Nobody Wrote
Rob has a lot of Claude folders now. One knows the book. Another knows the company planning. Others have picked up meeting notes, briefing docs, LinkedIn ideas, strategy work, and whatever else was useful enough to save at the time. None of this felt like a problem while it was happening. Quite the opposite. The whole setup was working well enough that Rob kept giving it more to know. Then one of those markdown files started telling him what he was and wasn't supposed to do. Rob and Justin follow that thread into a much bigger problem than one weird sentence in one weird folder. Once AI starts carrying knowledge from one place to another, remembering things, connecting things, and helping everybody work faster, a few very old problems start wandering back into the room wearing new clothes. The BI crowd may recognize them. Rob certainly did. And one of his solutions will be immediately familiar to anyone who has ever opened a Power BI model, looked at the relationships it helpfully created for them, and started deleting.
September 15 · 25 min
Your Favorite AI Has a Moat Problem
For a minute there, it looked like the AI wars would come down to who built the smartest model. Rob's not buying that anymore. Take Claude. Rob's increasingly convinced that what makes Anthropic so sticky isn't Claude itself. It's Claude Code. It's Cowork. It's the software wrapped around the model that makes the whole thing so ridiculously useful. Great news for Anthropic, except for one tiny problem: software can be copied. And when the models themselves are interchangeable enough to live in a dropdown menu, you have to start wondering what any of these companies really have that somebody else can't recreate. That question leads straight to Microsoft, which may be holding a much better hand than it gets credit for. Everyone else is trying to worm their way into your email, your files, your chats, and the rest of your working life. Microsoft is already sitting inside the castle. From there, Rob and Justin talk through the increasingly strange economics of all this, whether actual humans using your product become the moat that matters, and finally, the proposed fix for our data center problem that involves launching the data centers into space. Give it a listen for Rob's take on that one, starting with the minor inconvenience of physics.
September 1 · 22 min
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
August 18 · 38 min
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.
August 12 · 1 hr 24 min
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.
August 4 · 1 hr 24 min
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.
July 14 · 32 min
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.
June 30 · 24 min
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.
June 23 · 15 min
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
June 16 · 29 min
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.
June 9 · 35 min
What Happens After the AI Works?
For the past few years, the conversation around AI has focused on the technology. Which model is best. Which tools to use. How fast everything is changing. But once you start building with it, a different challenge emerges. The technology is often the easy part. The hard part is everything else. The definitions that don't match. The documentation nobody trusts. The tribal knowledge living in someone's head. The processes that work only because a few key people know how to navigate around the mess. Business intelligence exposed some of these problems years ago. AI is exposing even more of them. For years, the people who cared about semantic models were mostly talking to each other. Everyone else had a simpler view: the dashboards worked, the BI nerds were overcomplicating things, and if a slightly different version of yesterday's question showed up, someone could always write more SQL. That worked well enough until AI agents became the ones asking the questions. Agents don't wait two weeks for a developer. They improvise. And the improvisation is different every time. That's the moment the semantic model stopped being a nice-to-have and started looking a lot more like a requirement. Every data quality problem that used to come home to roost the first time you built a dashboard is back, only now the list is longer. AI cares about policies, institutional knowledge, organizational context, and all the things that used to live quietly in people's heads. The one-version-of-the-truth problem just got a much bigger job description. Along the way, Rob and Justin compare notes from the front lines of building with AI, from multi-agent systems and knowledge management to the unexpected ways these tools behave once they leave the lab and meet real organizations. There's a book update in here too. Fair Game is officially available for pre-order, and Rob shares why the independent bookstore route matters more than most people realize. If you've been wondering what happens after the AI works, this episode is a pretty good place to start. Also in this episode: Pre-order Fair Game: Customizing AI to Your Business Is Easier Than You Think Fortune: Big Tech is laying off developers. My company just hired its first. We're both right about AI (By Rob Collie)
June 2 · 6 min
Absences, KPI Updates, Book Title and Pre-Order Bundle Reveal
If you've listened to the podcast over the past several months, you've probably heard Rob mention "the book" a few times. Well, it's finally done. In this solo episode, Rob reveals the title, shares the story behind it, and talks about the question that sent him down the AI rabbit hole in the first place: what does this technology actually mean for normal businesses? Not Silicon Valley. Not billion dollar tech companies. The rest of us. What he found was both simpler and more surprising than expected. The farther he got from the headlines and hot takes, the clearer it became that AI isn't some magical new category of technology. It's a lot closer to the data, software, and business problems companies have been wrestling with for years. Which raises an interesting question: if AI is more approachable than most people think, why are so many organizations still standing on the sidelines waiting for someone else to go first? As it turns out, that question became a book. And this episode is the story of how it got there. Also in this episode: Pre-order Fair Game: Customizing AI to Your Business Is Easier Than You Think Fortune: Big Tech is laying off developers. My company just hired its first. We're both right about AI (By Rob Collie)
May 5 · 19 min
It's Time to Start Looking Into Microsoft IQ
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.
April 28 · 56 min
Cowork Builds Apps Now, and 'Acquired Skills Will Appear Here' w/ Garett Medlin
Garett Medlin just got the official title for the job he was already doing: AI Practice Lead at P3. He's also the person responsible for Rob trying Cowork in the first place, despite Rob's very reasonable question: "Why the hell would I want Cowork if I already have Claude Code?" Then Rob accidentally proved Garett right. He made an offhand comment about needing a better way to track feedback on book graphics. Nothing dramatic. Just the kind of annoying little process problem everyone complains about and nobody fixes. Two days later, there was a Slack bot reminding him to review images, a web app with approve buttons, surrounding context from the manuscript, and a clean way to send feedback without creating a Slack archaeology project. Built by a non developer. In Cowork. Which makes Microsoft's Copilot Cowork story… awkward. Garett came with the field report. Yes, it can make PowerPoints. Yes, it talks to OneDrive. No, it doesn't have memory. No, it doesn't have custom instructions. No, it doesn't have projects. The section where those capabilities are supposed to live is called "Acquired Skills," and it currently says they will appear here. Which is a choice. At the same time, companies are getting top down mandates to spend $20 million a year on AI with absolutely no idea what they're supposed to spend it on. IT gets handed the problem, Copilot gets treated like the answer, and somebody nearby is always trying to sell a very expensive fear of the tools that already work. This episode is really about that gap. Between what's shipping and what's still "coming soon." Between the people waiting for enterprise permission and the people already building useful things on a Tuesday afternoon. Turns out, the scariest part of AI might be realizing the non developers got there first.
April 21 · 30 min
AI "versus" the Medical Establishment, Rob's Sith Name, and the Death of Social Media?
Rob didn't go looking for a fight with the medical system. He just showed up with receipts. Claude had already mapped the symptoms, suggested the tests, and summarized the situation better than any portal ever would. And instead of pushing back, the doctor basically said, "Yeah, this all checks out," added a few things, and moved on. No drama. No turf war. Just a quiet moment where you realize… the system didn't break. It just got leapfrogged. The next morning, sitting in an Uber on the way to the fasting lab, Rob had AI log into his medical portal, pull down test results, interpret them, suggest next steps, and tee up additional tests before the lab even opened. That's not "AI as a helper." That's AI running point. And when it catches an error in the doctor's AI-generated notes and fixes it by talking to their system directly… yeah. That's the moment. You don't unsee that. Which is great… until you zoom out. Because the same thing that lets you bulldoze friction in healthcare also bulldozes friction everywhere else. Social media. Identity. Trust. If AI can operate the interface better than you can, the whole idea of "who's actually doing what" starts to get fuzzy real fast. There's a version of this where everything gets more efficient. There's another version where everything gets a little… fake. This episode walks through both. It's worth knowing which one you're already in.
April 14 · 28 min
Book PR, Fourth-and-One, the AI Knowledge Cliff, and LinkedIn WTF Moments
Something shifted this year and you can see it in the reactions. Not to the technology. To people talking about it. Rob shared a screenshot on LinkedIn. CFO. Friday night. Using CoWork in real time. The kind of moment where you have to stop yourself because you won't sleep otherwise. And that's what set someone off. Not hype. Not a prediction. Just… "this is happening." Apparently that's enough now. Rob calls it the knowledge cliff. AI knows three things. What's in the training. What it can pull from the web. And everything that only exists in your world. The first two feel almost the same. The third is where things break. That's where most of the frustration lives. If you haven't crossed that line yet, AI feels inconsistent. Impressive one minute, useless the next. If you have, it starts to look a lot more like real work getting done. You can see it in companies already changing how they plan and operate. You can see it in schools trying to figure out how to respond. And you can definitely see it in the comments, where people react to the exact same example like they're living in two different worlds. You can't really be smug about it. But the people who've crossed the cliff aren't waiting for consensus. They weren't a year ago either. This episode won't tell you what to think about AI but it will make it a lot harder to ignore what's already happening.
April 8 · 46 min
How Claude Cowork is Helping a College Senior Boil the Job-Hunting Ocean
The job hunt is a numbers game. The problem is, the numbers are brutal. Hundreds of applicants per role. Ghosted applications. "Entry level" jobs asking for experience no one at 22 could possibly have. In this episode, Rob brings on his daughter Ella, a college senior in the middle of it, and hands her something different. Not advice. Not a better resume template. A coworker that doesn't get tired, doesn't lose track, and doesn't stop digging. Within 48 hours, she's using Claude Cowork to search across sources, filter for real roles, verify listings, organize everything into a system, and adjust the criteria on the fly when the market doesn't cooperate. It's messy. It's imperfect. And it's wildly more effective than doing it alone. Watching it happen in real time makes one thing pretty obvious. This isn't about AI helping you think. It's about AI helping you work. One person scrolling and hoping. One person running a system that never stops. Listen to this episode to decide which side of that you want to be on.
March 31 · 30 min
More Cowork Love, "Data Gene" Gets a Rebrand, Tiny Bottle, and the End of Wordpress
The work feels different now. You can hear it in this one. Something that used to feel like overhead suddenly starts pulling its weight. Not a demo. Not something you have to babysit. It's actually doing useful work while you're still figuring out what you want. That's a weird moment the first time you see it. And then it stops being weird and just becomes the new normal. It shows up in a few places here. Cowork starts earning its keep. The "data gene" gets reworked into something that fits where things are going. And there's a moment that might make you a little uncomfortable if you've spent years leaning on tools like WordPress to get things out the door. Because the gap those tools were filling is getting smaller. Fast. The people who like to build and adjust as they go feel that immediately. They don't want to wait around for results. Now they don't have to. And then there's the other camp. The folks who checked this out once, decided it wasn't that impressive, and moved on. Still pretty confident the whole thing is overblown. You can feel that tension in this episode. And it matters. Because a year ago this would've sounded like a stretch. It doesn't anymore.
March 24 · 43 min
Knowitall Doctors, Mac Keyboards, More Love for CoWork, and Maybe it was the Models After All
Most AI still lives in the "that's pretty cool" category. It answers questions, writes a decent paragraph, maybe even points you in the right direction. And then you still have to go do the work. That line is starting to move. Not in theory. In real, hands on, open the file and keep going kind of ways. We're talking about outputs that don't fall apart the second you touch them. Work that shows up structured, editable, and worth building on. That's a very different experience than what most people think of when they hear "AI." Some of this stuff still feels like a demo. You try it, you nod, and then you go back to doing things the old way. Other parts are starting to feel different. You give it something real and it gives you something back you can use without starting over. That's the shift. And once you see it, it's hard to unsee. Listen to the episode and decide where AI in your business is still a demo and where it's finally ready to pull its weight.
March 17 · 43 min
Why CoPilot Cowork is a Big Deal
Most people think they've already experienced AI. They've asked a chatbot a question, had it summarize something, maybe even draft an email. That version is useful, but it isn't the one that actually changes how work gets done. The real shift starts when AI stops talking about work and starts participating in it. That's the moment Rob ran into while experimenting with Cowork tools, and it was convincing enough to push him into changes he hasn't made since the DOS era. Microsoft just announced Copilot Cowork, and Rob thinks it could turn out to be the most significant AI product Microsoft has shipped so far. Not because of a flashy feature list, but because of where it lives. When something like this can operate across the Microsoft 365 environment where work already happens, it suddenly has real context. Files in OneDrive. Documents in SharePoint. Conversations in Teams. Meetings in Outlook. At that point the tool isn't sitting off to the side anymore. It's working inside the same ecosystem your team already runs on. Most of the working world is still standing on the quiet side of an inflection point they don't fully see yet. Once tools like this start showing up inside the systems companies already use every day, things will move quickly. In this episode Rob and Justin unpack why this moment matters, why Copilot Cowork could change how people experience AI at work, and what it means for the people and organizations paying attention right now. If that includes you, this is the one to listen to.

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