Podcast
Raw Data with Rob Collie
Hosted by P3 Adaptive · EN
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.
30episodes
Episodes
Newest firstAll episodes
It's Time to Start Looking Into Microsoft IQ
3w ago00:19:33Tap to summarizeRob 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.
Transcribe →Cowork Builds Apps Now, and 'Acquired Skills Will Appear Here' w/ Garett Medlin
4w ago00:56:10Tap to summarizeGarett 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.
Transcribe →AI "versus" the Medical Establishment, Rob's Sith Name, and the Death of Social Media?
Apr 2100:30:02Tap to summarizeRob 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.
Transcribe →Book PR, Fourth-and-One, the AI Knowledge Cliff, and LinkedIn WTF Moments
Apr 1400:28:06Tap to summarizeSomething 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.
Transcribe →How Claude Cowork is Helping a College Senior Boil the Job-Hunting Ocean
Apr 800:46:53Tap to summarizeThe 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.
Transcribe →More Cowork Love, "Data Gene" Gets a Rebrand, Tiny Bottle, and the End of Wordpress
Mar 3100:30:56Tap to summarizeThe 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.
Transcribe →Knowitall Doctors, Mac Keyboards, More Love for CoWork, and Maybe it was the Models After All
Mar 2400:43:00Tap to summarizeMost 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.
Transcribe →Why CoPilot Cowork is a Big Deal
Mar 1700:43:57Tap to summarizeMost 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.
Transcribe →Career Growth Curves and the Data Gene as the Answer to Everything
Mar 1000:29:14Tap to summarizeEvery once in a while a new tool shows up that bends the career curve for a certain kind of person. Not everyone. Just the people with that itch to poke at systems until they finally give up their secrets. The same instinct that used to turn someone into the unofficial Excel wizard in the office is now colliding with AI development tools that can help you build real software. If you have the data gene, this moment feels a little like someone just handed you a much bigger toolbox. It has a lot in common with what happened when Power BI first showed up. For years the people who understood the business problems best were stuck with tools that could only go so far. Power BI suddenly bridged that gap. Now AI assisted development is doing something similar across the rest of the tech stack. The distance between I know what the answer should be and I can build the thing that proves it is shrinking fast. Of course, building something is not the same thing as building a company. Rob and Justin get into that too. AI can help you spin up software faster than ever, but the hard parts of business still live somewhere else. Vision. Distribution. Understanding the real problem well enough to solve it in a way that people care about. The tools are getting easier. The thinking still matters. Also in this Episode: The Lion King Lyrics Revealed
Transcribe →Who's the AI Stakeholder: Leaders or Employees?
Mar 300:22:49Tap to summarizeRob and Justin had a plan. Scale Justin's brain across the entire P3 consulting team. Build an AI agent that bottled up his frameworks, his instincts, the way he navigates AI conversations with clients. In theory, everyone gets smarter overnight. It was a solid idea. The tech worked. The knowledge base was deep. The guardrails were tight. And almost nobody used it. Not because it was broken. Because the team wasn't waking up thinking, "Man, if only I could channel Justin right now." That wasn't the fire in front of them. So instead of feeling like leverage, the agent felt like homework. And that's the punchline. You can build something powerful and still miss the mark. No one was losing sleep over not having this tool. No one's bonus depended on it. So it drifted. Not rejected. Just... optional. That's a brutal place for a "strategic initiative" to land. The fix isn't a better tool. It's sequencing. Define the services, train the team, build the human infrastructure that makes the tool land on a surface that's ready for it. Every AI project that has worked traces back to the builder being a direct stakeholder. Not adjacent to the problem. In it. Proximity to the pain is doing a lot of work that no amount of clever architecture can replace. When leaders are the ones excited about AI and employees are the ones expected to use it, you've got a stakeholder mismatch. And that mismatch is quietly killing more AI initiatives than any technical failure ever will. If you're planning a rollout, or already wondering why yours isn't sticking, this episode is for you. Be sure to subscribe on your favorite podcast platform for new content delivered directly to your inbox.
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