We talk about folders all day, but the folders are FOR something. I want to know what... 🎖️Bonus points: comment with the single most painful manual process in your industry. The best comp entries come from exactly those answers.

@Curtis Hays just dropped the capstone on a series I've been watching build in real time — and it's the one I'd send you to if you're tired of AI advice that sounds right and moves nothing. THE MIRROR AND THE WINDOW. The whole essay hangs on one distinction Curtis borrowed from Tom Nixon and then stress-tested against years of client work: most of us treat the Why like a mirror. Sit down, look inward, write what you see, call it true. It reads fine. It never shapes a decision. Tom's move is the window. Go to the people who buy. Listen to what they say about themselves. Find the reason they already had — don't invent one in a conference room. Curtis makes the AI parallel land hard. The default posture — "you are a helpful assistant" — is the same mistake rebuilt. Declared, not excavated. Instructions, not scars. A system that performs confidence without having earned it. The line that stuck with me: "AI did not generate it. AI revealed it." That's the through-line of everything Curtis has been working out loud in David's Corner. Not magic. Not infrastructure theater. A system for protecting and scaling judgment — built from real client work, real corrections, real belief layers that took months before the fifteen-minute setup felt easy. He didn't phone this in. Seven essays. One arc. From perception gap to worldview engineering to outsourcing the typing while keeping the thinking — and now Solve for Why. Archaeologists, not architects. I gave Curtis the section to work it out loud. He did the work. If you haven't read the series yet, start here: 👉 David's Corner → Curtis Hays — Systems Worth Amplifying (https://www.skool.com/cliefnotes/classroom/c7f102c7?md=dba87827cdff47449034a8368d492e48) Read them in order. The intro maps the whole thread. The Mirror and the Window is the payoff — but you'll feel it more if you've walked the path. And if you've already built something that started in the community and ended up as doctrine — drop what you're working on below. Curtis surfaced his in the open. That's how this place actually works.

Just published this video to spur attention. Let me know what you think: https://www.linkedin.com/feed/update/urn:li:activity:7473413393870315521/ Bas and other are sharing great posts about their work too: https://www.linkedin.com/posts/basiliso-rosario_giving-an-ai-a-hippocampus-taught-me-one-ugcPost-7472517062230360066-tqbH/?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAXIIh8Bzf2hpuF8Jy5odtYEA0fEhnxykyg Awesome stuff that Bas is showing the world!

Everyone's stacking AI experts into "councils" right now. Here's what nobody mentions: most of them produce blander advice than a single good prompt. I've been building multi-agent systems for a while, and the council pattern is seductive. Load six marketing legends, let them debate, synthesize the genius. Three things I learned the hard way: 1. Councils regress to the mean. Put Cialdini, Godin, and Vaynerchuk in a room and "synthesize" their answers and you get generic marketing advice wearing three nametags. The fix isn't a better synthesizer. Stop resolving the disagreement. Let the tension stand and make one agent own the call. 2. The debate is where your budget dies. Distilling a book into a tight skill file is cheap. Having agents argue in real time is not. If "minimal tokens" is your pitch, the preprocessing is doing the work and the roundtable is the luxury. 3. It doesn't make the model smarter. Cold Claude already does a soft version of all of this. What the structure buys you is named, sharp, predictable behavior. Say that honestly — the moment you claim it makes the AI "smarter," you've oversold it. None of this means don't build councils. It means build them with your eyes open. The real test for any council: do your experts actually disagree, or do they just agree in different vocabulary? If it's the second, you built one expert and gave it six hats. (Riffing off the systems thread from @Curtis Hays that @David Vogel highlighted for us and the 'systems' build — good work worth pressure-testing.)

Sometimes you just have to stop talking, take action, and prove what is possible. Tonight, I’m sitting with my laptop finishing up a PowerPoint presentation. Tomorrow, I am hosting a Global Copilot Cowork Workshop for colleagues across multiple departments and countries. Looking back, things have moved at absolute lightning speed. The Timeline - March: I started experimenting with Claude Code and joined this amazing community shortly after. - May 4th: I had a high-level meeting with our global Head of AI. He gave me the green light to use Copilot Cowork since Claude Code isn't corporate-approved yet. - Today: I'm teaching others how to do what I just did. In just a short month and a half, I’ve built several custom skills focused entirely on our hardest finance bottlenecks. And the timing couldn't have been better. The Ultimate Test: A Compressed Month-End We were recently acquired, which meant our standard 6-day month-end closing window was aggressively cut down to just 4 days. Normally, this would mean pure panic and stress. We had never missed a deadline, but we always had to fight for it. During the May closing, I put my new Copilot skills to work. The result? It went so smoothly that on day 4, my boss literally looked at me and asked: "Did we forget something?" Normally, she works grueling hours, staying up late to log back on after putting her kids to bed. Not this time. I only had to work a truly long day on Day 1. Day 2 was slightly extended, and Days 3 and 4 were completely normal, quiet, peaceful workdays. We smashed a compressed timeline with zero stress. Tomorrow's Mission: Giving Back Tomorrow, I'm stepping up to the whiteboard. I'm running a workshop to show people what this tech can actually do. We are going to build a "light" finance skill together from scratch. The core lesson is simple but powerful: How to feed raw data into an AI agent and get a perfectly formatted, HQ-compliant report out the other side. What the Future Holds