My brother spent his career trying to see threats coming before they happened. He was a Marine first. Then a sheriff in Orange County. His specialty was counterterrorism. Somewhere in there, he got close with two guys named Patrick Van Horne and Jason Riley, who wrote a book called Left of Bang. The idea comes from combat — the "bang" is the moment it goes off. Everything before that is "left of bang." Most training teaches you what to do after the bang. Left of bang teaches you to read the signals before it — the small things that don't add up, the cluster of cues that tell you it's coming. My brother taught it to his deputies. The point was never to react faster. It was to see it coming early enough that you didn't have to. A lot of you have seen my ICM now, the place where my entire business lives. Client files, notes, the running log of who's doing what. And I keep noticing that the way I've built it, I only find out something's broken after it's already broken. A client folder is missing something it should have had — and I find out when I go looking for it and it's not there. A log gets so long and cluttered it stops being useful — and I find out when I can't find anything in it. Things pile up in the inbox that should've been filed weeks ago — and I find out when I finally look. Every one of those is a small bang. And every one of them had a left side. There were signs before it broke. I just built a system that waits for the break instead of watching for the signs. So I've been sketching the opposite. Something that checks the system's health on purpose — walks through and asks "what's missing that should be here? what's grown too big? what slipped?" — and tells me while it's still small. Four cluttered entries, not forty. A folder missing one piece, not a client meeting where I realize the whole thing was never set up. Here's where I'm stuck, and I'd genuinely like the room's read: Is this worth building — or is it overengineering? Is "check the health of your own system before it breaks" a real discipline, or does it just become another thing you build, run twice, and never look at again?

🎟️ PRIZE: FREE SEAT IN THE LYCEUM 🎟️ Pick your cohort. Technical, Business, or Creator. Your call. ---- 🇺🇸 Quick note first. This post is going up Today because we took Memorial Day off yesterday. To keep things fair, you've got until Sunday May 31st at 12:00 PM EST to submit. Same week of build time, just shifted. ---- 📋 THE CHALLENGE Build a folder-based AI researcher for a specific topic or industry. You pick the domain. This week's deliverable is one researcher folder that someone could drop into a Claude project and use as their personal research partner for whatever domain you've built it for. ---- 🎯 PICK YOUR DOMAIN The domain is yours. Pick something specific. Pick something you'd actually use. A few sparks to get you thinking: - 🏦 M&A activity in one industry (fintech, healthcare, defense) - ⚖️ Court cases in one area of law (employment, IP, immigration) - 🧬 Scientific research on one health condition or treatment - 🏘️ Real estate market dynamics in one city or asset class - 🥊 Competitive intelligence for one product category - 📜 Historical research on one period, place, or movement - 📚 Academic literature in one specific subfield - 📋 Regulatory developments in one sector - 📰 Journalism research on one beat (climate tech, AI policy, biotech funding) The more specific, the better. "Research assistant" is too broad. "M&A research analyst for early-stage fintech deals in the US and Europe" is right. ---- 🗂️ 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 researcher is a folder with five things: - 📄 identity.md (who the researcher is, what domain they cover) - 📐 rules.md (how they research) - 💬 examples.md (what good looks like) - 📚 reference/ (frameworks, source lists, key concepts) - 📖 README.md (how to use it)

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. 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 crunching numbers to see how long they could solve it for, and full stop, it doesn’t work. Complex problems require complex solutions. A billion dollars solves world hunger for how long… a day? A week? A month? And then what?

Come chat about your goals for this week! Update: seems like there is an appetite for this so this will officially be Sunday Coffee #1! New reset every Sunday for the week ahead. Thought it would be fun to start a new series where we can all chat about our goals for the upcoming week. Leave a comment below: - What you’re working on - Something you hope to ship - Blockers you’re running into at the moment - Where you’re looking for help currently - Anything else you’d like to share Let’s use this as a chat room to discuss current freeform topics. Network with fellow members and maybe link up for projects. Do you think this is a good idea to have weekly? Would you like a space to come discuss your current work? Leave a like and enter your vote in the poll. If there seems to be enough interest I’ll make a new thread every Sunday. ☕️

Most people are using AI like a slot machine. Pull the lever, hope for a payout, blame the model when it's generic. The makers I respect run a workshop instead. They've stopped asking AI for things and started telling it what they're building. Three moves: 1. Outcomes, not prompts. A prompt is a wish. A brief is a contract. When AI gets it wrong, your brief was ambiguous. 2. Context is king. Models are interchangeable. Context is yours. A bad prompt with the right context beats a great prompt with none. 3. Train your taste. AI gives you 90% in 10% of the time. Spend the 90% you got back on the trim pass. Your taste is the bottleneck now. Full deep-dive: aris-space.com/stop-prompting-start-defining-outcomes // A<3