Seven years is a long time to live with something you know needs fixing. Especially when fixing it means spending a small fortune and hoping you'll like the result. Then something changed. Rob has a million dollar story to tell: p3ada.pt/7years

A project can be perfectly on track and still be headed in the wrong direction. That’s why “working backward from the answer” matters a whole lot more than it sounds like it should. Especially with AI. 🔗p3ada.pt/build-backwards

Rob’s AI found a rule. Tiny problem: nobody wrote it. It had started as something much smaller, somewhere else, and somehow arrived in a new place with a promotion nobody approved. New Episode:🔗p3ada.pt/ai-rule

You know your technology is becoming a commodity when it’s a dropdown. Opus? Sonnet? Pick one. And that got Rob thinking. If the LLM is swappable and the really useful software built around it can be copied, where exactly is the moat? 🔗p3ada.pt/AI_Moat

AI can read everything your company knows. Excellent. Is everything your company knows organized, accurate, current, consistent, and understandable? Ah. Data people, you know where this is going. Listen now: p3ada.pt/data_moment

“Botsitting” sounds made up. Rob thought so too. Then multiple journalists wanted to interview him about it. That’ll get your attention. Turns out, the ridiculous name describes something pretty interesting. 🔗 p3ada.pt/botsitting

Power BI found the people who see a new tool and immediately wonder what else it can do. AI just found them again. John Perl, Tim Rodman, and Trent McKinster join Rob to compare notes on Fair Game and a much bigger toolbox. Listen now: p3ada.pt/power_bi_veterans

There have always been crafters. AI didn't create them. It just made everyone else notice. 🎙️ The Crafter's Edge, with Pedro Rossello 🔗p3ada.pt/crafters_edge

"Everyone's sitting poolside and Satya's talking about the deep end." That might be the best description we've heard of where the AI conversation is today. This week's episode asks a simple question: Should businesses spend more time in the shallow end? 🔗p3ada.pt/everybodys_priority

For the last two years, AI has been an all-you-can-eat buffet. The next phase may be choosing what's actually worth ordering. That's this week's conversation on Raw Data by P3. p3ada.pt/ai_buffet

AI has a funny way of making old problems look brand new. Data quality. Business context. Tribal knowledge. Those weren't AI problems yesterday, and they aren't AI problems today. AI just has a way of exposing them faster. 🔗p3ada.pt/waiting_worked

We've spent two years asking: "How smart is this AI?" We're about to start asking a much better question. "How much AI does this job actually need?" 🔗p3ada.pt/better_ai

For years, semantic models were something BI people cared about. Everyone else just wanted the dashboard to work. Now AI shows up, starts asking questions, and suddenly all those semantic model conversations aren't optional anymore. Funny how that works. 🔗p3ada.pt/after_ai

The "How Long Has Rob Been Sick?" KPI has officially retired. The "How Many Pages Has Rob Written?" KPI has retired too. Which means there's finally a book title to reveal, a pre-order bundle to announce, and a few stories to tell along the way. 🔗p3ada.pt/book-title

What AI in Power BI is NOT: a shinier search bar dashboard summaries in plain English yet another productivity demo What P3AI IS: A BI interface that keeps up with how people actually think, question, and explore. 🔗p3ada.pt/ai_power_bi #PowerBI #AI #BusinessIntelligence

For years, semantic models were treated like backend plumbing. Necessary. Kinda boring. Definitely not the star of the show. Now AI shows up and people are suddenly realizing those models might be the only reason any of this works at scale. 🔗p3ada.pt/microsoft-iq

Leadership keeps saying the same thing: spend more on AI. No target. No use case. Just go do something. Meanwhile, the real wins are coming from people fixing the annoying Tuesday afternoon problems nobody else touched. 🔗p3ada.pt/cowork-apps

This episode isn’t really about healthcare. It’s about what happens when AI stops waiting for systems to cooperate. And just goes around them. 🔗p3ada.pt/ai-vs-med

Same example. Completely different reactions. One person sees real work getting done. Another thinks it’s overhyped nonsense. They’re not arguing about the same thing. They’re operating with different context. 🎧p3ada.pt/ai_cliff

This starts as a job hunt story. It doesn’t stay one. Because once the system is in place, the use case stops mattering. Search Filter Verify Track Adjust And that pattern is everywhere. This is the shift from "help me think" to "handle the busy work." 🔗p3ada.pt/ai-coworker