I rebuilt my site today with the focus on folders over agents. It's geared toward providing the workflows for businesses. Not sure if this is allowed here, but I'm sharing anyway. Take it down if it breaks any rules. So many great minds here, so I thought it was worth risking criticism or advice on how to improve. Perhaps it will give you ideas for your own site. Check it out: optimarketai.com

🎟️ PRIZE: FREE SEAT IN THE LYCEUM 🎟️ Pick your cohort. Technical, Business, or Creator. Your call. ---- 🇬🇧 We're back. Good morning from London. 👋 Thanks for the patience last week. Jake and I needed a few days to breathe before London Tech Week kicked off, and you all responded with nothing but support. We don't take that for granted. Now let's get back to building. ---- 📋 THE CHALLENGE Build a folder-based AI operator that handles ONE operational workflow end-to-end. You pick the workflow. This week's deliverable is one operator folder that someone could drop into a Claude project and use to handle a real business workflow without babysitting. ---- 🎯 PICK YOUR WORKFLOW The workflow is yours. Pick something specific. Pick something you'd actually use. A few sparks to get you thinking: - 🎫 Customer support triage (which tier handles this ticket?) - ✅ Content review and approval - 📨 Lead intake and qualification - 💸 Refund request handler - 🤝 Partnership pitch evaluator - 🎙️ Podcast guest pitch sorter - 💼 Freelance project intake - 📄 Resume screen for one specific role - 📅 Meeting request triage (book, decline, delegate) The more specific, the better. "Customer support" is too broad. "Refund request triage for an ecommerce store doing under 200 orders per month" is right. 📎 If you want a fully written client brief as a reference, the attached PDF walks through one example. Don't build the example. Use it as a template for how to think about scoping your own operator. ---- 🗂️ THE METHODOLOGY If this is your first comp, welcome. Here's what you need to know: This week (and every week) you're learning interpretable context methodology. Folders as architecture. Each file does one job well. Your operator is a folder with five things: - 📄 identity.md (who the operator is and what workflow they own) - 📐 rules.md (the decision logic: criteria, edge cases, escalation rules) - 💬 examples.md (decisions in action, including at least one edge case) - 📚 reference/ (checklists, templates, rubrics) - 📖 README.md (how to use it)

Had a call today with researchers from Stanford's Autonomous Agents Lab. They're studying AI adoption at marketing agencies. Found me via Google. I asked them how much research they did on me first, none; they were embarrassed to say they just filled out my contact form. I warned them it might not be the conversation they expect. At the end, they said I was the most advanced agency owner they'd spoken with. They'd never heard of ICM. These are smart people doing real research. They've talked to a lot of agencies. And the most common thing they see is: people using ChatGPT chat, maybe dabbling with agents, struggling to get them to do things reliably end-to-end. You all know what I've been running for the past 2 months and I showed them. Then the researchers showed me their own tool — an autonomous browser agent that can log into Google Ads and act. I told them: I don't write to external platforms without a human reviewing it first. That's a policy, not a technical limitation. My clients' $20K/month runs through my judgment, not an AI's. Human in the LOOP! Their reaction: "that makes sense." But they were clearly used to hearing "I'm trying to get the AI to do more." I'm not. I'm trying to get the AI to help me reason better. That's a different goal. My takeaway: if you're in this group and you're here honestly learning, you're way ahead, don't stop! Keep building! Ronnie Coleman once said: "Everybody wants to be a bodybuilder, but nobody wants to lift no heavy-ass weights."

I forced a Why once. It didn't work, and it took me about a decade to understand why. I'd seen Simon Sinek's "Start With Why" talk when it came out, the Golden Circle, Why-How-What. That's not my idea. It's his. And it's a good one, which is exactly why we grabbed it. This was back at an agency I worked at, and we used Why-How-What as a culture thing. We sat down to declare our Why because it sounded good, because it was the kind of thing a sharp agency was supposed to have. We were copying what other agencies were doing. We weren't that mature at the time and thought we could just invent these things. So we did. We wrote one down. It read fine. It moved nothing. Then I left, went into the consulting world, and Why-How-What went dormant for me. I didn't think about it for years. It wasn't until about ten years later that it came back through Tom. When Tom started doing brand work for our clients, he kept saying two things. The first: "You are what your customer says you are." The second, the one that actually reordered how I think about this: "I want to find out for myself, from the customer." That's when it clicked. Not because the framework was new. I'd had the framework for a decade. It clicked because Tom wasn't declaring anything. He was going to look. The mistake I made at the agency was treating the Why like a mirror. Sit down, look inward, write what you see, call it true. What you get is a reflection of what you already assumed about yourself, dressed up well enough to sound like a discovery. What Tom does is turn the mirror into a window. He says it plainly: "If it sounds to me like you're looking in the mirror, turn that mirror into a window and look through it and see the customer or the user or the audience on the other side and talk to them about them." He doesn't ask the brand what it believes. He goes to the people who buy and finds out what they already know. The Why was never inside us waiting to be phrased correctly. It was on the other side of the glass the whole time, in the customer's own words, and the work was going to find it instead of inventing it. Tom puts the reason bluntly: "Few people care about you when they're reading or consuming or viewing or deciding and shopping. They care about themselves."

This is a little bit of a rant cause I can’t post these thoughts anywhere else. At least, I’m not ready to get publicly crucified yet, so… I cannot talk to almost anyone I know about ai. They have no idea what’s going on, or about the kind of stuff we do. It’s all doom and gloom. There is something that really bugs me about it, beyond the naivety and half-glass-full mentality. It’s that... gatekeeping does nothing for humanity and is a selfish mentality at its core. So ai has access to lots of data, and artists data. So what? If you’re really good, it doesn’t matter. Great products, great services, great talent all have one thing in common which makes them in-demand. They’re great. And greatness is witnessed by all the people who consume their work. There’s no gatekeeping because it’s literally on display. From Harry Potter to Michael Jordon, Disney to Taylor Swift, Steve Jobs to Crayola Crayons. If no one is trying to copy you, then your work isn’t loud enough. Either because it’s not good enough (yet), or because you’re hiding it away from the world out of fear. In any case, their success came from being great, NOT from gatekeeping information or their talents and trying to sell them to the highest bidder. Bringing it full circle… Nobody lost money cause I finally had a tool that could do work for me for free. Rather, everyone in my companies will literally make more money because of massively efficient operations. It also means we’ll be able to afford remarkable talent with the extra profits we bring in due to that efficiency. I’m SO glad I have more options to take care of the people I bring into my sphere. One last thought… a little side quest here.. Whenever I ask people about why it isn’t a good thing that robots will be able to farm all the organic food we need at extremely low costs to produce compared to what we have now, no one has a good answer. I used to be of the mindset that really rich people should use their money to fix problems like world hunger. Then I actually looked at the challenge of getting the recipients to use money the way it’s intended, and started crunching numbers to see how long they could solve it for. Full stop, it doesn’t work. Because complex problems require complex solutions. A billion dollars solves world hunger for how long… a day? A week? A month? And then what?