The Hopium Lab is an idea factory. A place where problems get interrogated until they break, patterns get found where nobody else is looking, and systems get built for real, deep, long-term value, not the low-hanging fruit that makes a nice slide deck.
Whether you're a company trying to solve something real with technology, or an individual trying to turn what you know into something that earns, this is the place problems come to become products.
We don't build AI wrappers. We don't sell you a dev shop with a fancy pitch. We sit in the mess with you, question everything, find what everyone else missed, and build the thing that actually works.
Deep expertise across AI, data, systems thinking, and product management, applied across industries where most consultants wouldn't know where to start. Three years building complex AI systems before it was fashionable. A career's worth of patterns from sectors that never usually talk to each other. That cross-domain wiring is the whole point.
A living map of every capability, product, internal agent, domain, and sector, and how they connect. Tap any node. Search the brain. Drag the time slider. This is the cross-domain wiring made visual.
The patterns you find working across this many sectors are the ones nobody else in the room has seen. That's not accidental. That's the point.
Each one born from The Hopium Lab, from a problem, a gap, an obsession, or a market nobody was serving properly. This is what it looks like when one person operates a multi-product lab.
We don't ship AI agents that drift. We built the memory layer that keeps them honest, the assistant that runs the ops, the autonomous agents that find revenue, the auditor that catches the bugs, the financial OS that runs the holding company. Used internally to run a multi-product lab from one brain. Some of it is open source.
┌─ skyMem ─────────────────┐ │ 13-LAYER COGNITION STACK │ │ ▓▓▓▓▓▓▓▓▓▓▓▓▓ provenance │ │ ▓▓▓▓▓▓▓▓▓▓▓░░ trajectory │ │ ▓▓▓▓▓▓▓▓░░░░░ persona │ │ ▓▓▓▓▓▓░░░░░░░ graph │ └──────────────────────────┘
The same stack that ships our products ships yours. Selected client builds, the ones we're allowed to show. Day-rate consulting, fixed-fee builds, or full product partnerships. If it fits, we ship it.
The Lab notebook. Last few weeks of motion, products, infrastructure, milestones. Updated by hand because automation is for things that don't deserve thought.
Not a blog. The system designs, theses, and cross-sector patterns that usually stay on the whiteboard. Raw thinking, shared before it's polished.
Because the streak certifies attendance, not understanding. The habit engine is the best thing Duolingo has and it is pointed at the wrong measurement. The fix is not to demand harder answers, it is to build a supported progression where the scaffold fades and the tick is earned for learning rather than completion.
Read →The most common way people try to build a report generator is to pour every source into one model and ask for the answer. Over enough sectors and steps it drifts, invents figures, and cannot tell you why. The fix is not a bigger model. It is an architecture.
Read →Project H measures continuously and rigorously, and guarantees by construction that no number it computes ever reaches a human surface. Here is the architecture that makes that possible, and why nearly every decision follows from that one inversion.
Read →People keep asking me what the AI system of the future looks like. Here is mine, drawn out in full. Seven layers, two feedback loops, and one property almost nobody designs for: it gets cheaper every time it runs.
Read →Most people selling this put the price behind a form. The form exists so a salesperson can find out what you can afford before telling you what it costs.
I don't have a salesperson. So the prices are on the page. Fixed fee, fixed date, and what's excluded written down where you can hold me to it.
Ninety minutes on your idea, then one written page telling you whether it is real and what the first buildable piece is.
What's in it →Two days, one written page, one straight answer on whether you actually have a problem.
What's in it →Seventeen categories, a one-word verdict on page one, and the first fixes arrive as pull requests, not as a list for somebody else to implement.
What's in it →Fifteen days to find out, capability by capability, whether you have an AI system or a demo with a try/except around it.
What's in it →The record-keeping architecture your legal team needs in order to make the claim, ending with a verifier your auditor can run against an export, with no access to me and no access to you.
What's in it →Good. Those are our favourite projects. The ones that look impossible from the outside. The ones where the answer is in a layer nobody's dug to yet. Bring it. We've heard “unrealistic” before. We've also seen what happens next.
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