archive
Everything I make
This is where I keep the thinking I've done in public — research teardowns and the things I'm building. Most of it started as me trying to understand a system well enough to act on it, then deciding the reasoning was worth keeping. Browse it all, or filter down to what you came for.
Metsu — The Living Cognitive Distillation Engine
Everyone is racing to give AI memory of your facts and preferences. I'm building the layer underneath. Metsu is a model of how you actually think, reason, decide, and make meaning, grounded in validated psychology and cited to your own words. It ports into any AI to make it yours, and you can read it to understand yourself. The personalization everyone wants, with the depth nobody else has.
Read ↦Catalyst Radar: Real-Time Market-Event Detection Engine
The whole Catalyst Radar project in one place: a Python engine that scans 163 perpetual markets every five minutes, ranks the unusual movers, classifies each catalyst with Claude, and fires a deterministic alert. Then I backtested 482 of its live alerts and the honest answer came back: the edge dies after the first hour. So I don't trade it by hand. The engine ships, the research ships, and the backtest that killed the trade thesis ships too. The thinking is the artifact.
Read ↦Palantir Foundry: Incident Triage Agent
Built this to impress Palantir before an interview, straight up. One session inside Foundry, their actual platform, and I shipped a full incident triage agent end to end: live data, an ontology, an AIP agent that reasons over runbooks, and a governed action behind a human approval gate. The fun part was just playing in their software, watching the data pipelines line up and the object state flip in real time while I watched. Same shape as the agent I shipped at Walmart, this time on their governance primitives.
Read ↦Fixxr Competitive Teardown: AI Car Repair in a Startup Graveyard
A venture-grade competitive teardown of Fixxr, an AI car-repair startup I was weighing joining. The due diligence I'd want before betting my time on a team: where the category's graveyard is, what the real differentiated wedge is, and whether the traction holds up.
Read ↦FDD Update Engine: AI + Deterministic Drafting for Franchise Disclosure Documents
Found a document nobody automates: the franchise disclosure document every franchisor has to refile every year, by hand, by lawyers. I built a demo to test it, and building it changed the whole idea. Attorneys don't draft 23 items from a blank page. They put last year's filing next to this year's and fix what moved. So that's the product now: upload the old FDD, drop in the new inputs, get a tracked-changes diff a lawyer can finalize. The actual workflow, not a text generator.
Read ↦Reverse Samwer Screen: 16 Foreign-Proven App Opportunities With US Whitespace
Here's the cheat code: find the apps already winning in other countries that nobody has built for the US yet. That's structural arbitrage, not guessing. I screened for sixteen foreign-proven opportunities sitting on open US whitespace, then broke down what actually makes each one transplantable.
Read ↦Catalyst Radar: A Quant Backtest of 482 Live Breakout Alerts
An adversarial study of 482 live alerts the engine actually fired. I graded all of them: conditional win rates, feature interactions, regime analysis, exit timing, plus an $8 Grok experiment to test whether the LLM layer predicts anything. The honest result: the only robust edge is a two-variable filter, the biggest lever is an exit rule and not an entry, and the LLM's direction call adds nothing measurable.
Read ↦Venture Assessment: AI for Regulated-Document Compliance
Before betting on a wedge, I wanted to know which one was actually better. So I put two against each other. FDD, the legal side, where every franchisor refiles a 23-item disclosure by hand every single year. Versus defense compliance documents, where my clearance gives me an angle. This is that assessment: market, tech, and regulatory risk on both, and why I led with FDD.
Read ↦OVERPOWER: A Browser Open-World Sandbox
A browser open-world superhero sandbox: procedural city, switchable powers, crowd NPCs, buildings you can level. No external assets, all of it generated in code. And it was one-shotted, a single prompt to Claude's Fable model. The experiment was simple: how far can one prompt take a whole open-world game? This far.
View on GitHub ↗Feasibility: An AI Agent for Remote Fleet Control Without a Unified API
Early thinking on future robotics and an AI fleet controller: could an autonomous agent run a heterogeneous hardware fleet with no unified API? The feasibility study that seeded the idea of an autonomous remote AI agent.
Read ↦Unsolved Problems for an Autonomous Remote AI Agent: Consumer Devices & Automotive
Where could an autonomous AI agent actually take over your devices and your car? I went looking for the real gaps, the control locked behind apps and proprietary billing that nobody has cracked. Then I sorted them: which are real, which are unsolved, and which are actually worth building.
Read ↦Catalyst Detection Engine v2: Peer Review & Architecture Spec
An adversarial peer review of my own detection architecture, measured directly against v1: what the first version left on the table, the assumptions the empirical record contradicts, and the v2 spec that fixes them.
Read ↦Catalyst Radar v1: Architecture Optimization Brief
My first hard pass at fixing the Catalyst Radar architecture. The v1 spec had three structural flaws: uniform polling, one LLM call per ticker, and a ranking that leaned on a lagging number. So I redesigned the loop, the prefilter, and the scoring to fix signal-to-noise and keep the cost near zero.
Read ↦MCP-to-Open-RMF: The Robotics Infrastructure Gap
The original research on the robotics-fleet problem: bridging MCP to Open-RMF so an AI agent could orchestrate a heterogeneous robot fleet. An honest read on the whitespace — and why the timing matters more than the opportunity.
Read ↦Every Data Vector for Predicting Music Virality
Investigating whether music virality has an objective, mathematical basis — cataloguing every data vector that might predict whether a track breaks out, and how much real signal each one carries.
Read ↦Multi-Timeframe Execution Engine: A Complete Architecture
Early architecture research, before I built Catalyst Radar. A single perp account can't hold opposing positions at once, so every multi-timeframe system has to solve the net-position problem first. This is the spec where I worked that out: three layers, 15M, 1H, 4H, on BTC-PERP, reconciled into one net position. The thinking that fed the build.
Read ↦PropJigs: API-First Wholesale Real-Estate Marketplace
My first real build. An API-first wholesale real-estate marketplace: it turns off-market contracts into AI deal briefs, hides the full address until a buyer makes a verified commit, and tracks intent and reputation in a graph. First time I took a niche all the way to a shipped product.
View on GitHub ↗Nothing in this category yet.