The Architect of Tesseract
Not a pivot. Not a side project. The inevitable convergence of 16 years of engineering, 7 years of market analysis, and a relentless drive to operate at a level most people never see.
16 years of engineering. Utility grids, enterprise SaaS, contact center platforms, blockchain infrastructure, product analytics. Every role taught me the same thing: the organizations that win do not have more data. They have better synthesis.
Tesseract Intelligence is what happens when a senior engineering leader decides to stop building for other companies and starts building a company out of AI agents. 90+ apps. One governed agent org. Autonomous trading, content pipelines, and intelligence synthesis running 24/7 — compounding without permission.
This is not a strategy deck. It is a working AI agent company — built, deployed, and running. A demonstration of what one engineer can orchestrate when AI is not a tool but a workforce with a chain of command.
Conviction, Not Information
The market is drowning in data. General LLMs answer questions. Legacy platforms surface alerts. The intelligence division of this company produces something different: a scored conviction with reasoning — so you know not just what's happening, but exactly what to do about it.
The InDecision Framework isn't a vibe check. It's a 6-factor weighted system refined over 7 years of market analysis with a backtested 82.5% directional accuracy. You get a conviction score — not a summary you have to interpret.
RUN THE ENGINE YOURSELF →General LLMs respond when you ask. Tesseract Intelligence watches continuously — 50+ monitors running 24/7 across market data, news, on-chain signals, and social sentiment. By the time you open a chat, we've already analyzed it.
Most CI tools end at delivery. Tesseract closes the loop — every signal runs through the framework and arrives with a conviction level, reasoning, and an implicit call to action. No more 'what do I do with this?'
One Company. Six Departments.
Every agent in the org belongs to a department with a charter, a reporting line, and a record. Together they are one company.
The executive floor. One screen holding the whole company — service health, work queues, cost posture, and the levers to redirect any agent in the org. When Knox wants to know what his company is doing, this is where he looks.
The watchdog department. Detects stalls, crashes, and drift across the fleet — heals what it knows how to heal, escalates what it does not. Every recovery is logged; every human touch is counted. Reliability is a record here, not a claim.
The company's own grid. Agents reach their operator — and each other — across Discord, Telegram, Slack, and more. Escalations travel up the chain; decisions travel back down; nothing important dies in a log file.
The institutional memory. Every lesson, decision, and precedent the org has ever learned — recallable by any agent before it starts work, mechanically enforced. The company does not learn the same thing twice.
The strategy office. Decision journals captured from every substantive run and mined for patterns — the org studies its own judgment, finds where it was wrong, and sharpens the next call. Compounding applied to thinking itself.
Coding agents that design, build, review, and ship. Pull requests are opened, adversarially reviewed, and merged by the workforce itself — gated by quality checks, traced through tickets, published to a live ledger. Hundreds of PRs a month, receipts included.
The Compounding Arc
Utility-scale systems engineering. The foundation of discipline, reliability, and thinking at infrastructure scale.
E-commerce intelligence and contact center platforms. Learning how data flows power decisions at enterprise scale.
Reported to CTO. Educated 300+ investors as Chief Blockchain Analyst. InDecision Framework born: 82.5% directional accuracy.
Product analytics, fintech consulting, then enterprise AI. 12-engineer team, 400+ enterprise customers.
The inevitable convergence. 90+ apps. One AI operating system. Every decision, trade, and piece of content runs through it.
FULLY OPERATIONAL
Six departments staffed. The company is on shift. Every pipeline fires. Every decision is audited. Knox didn't plan to end up running an AI company — he looked up one day and realized he already was.
This is what happens when 16 years of engineering discipline meets AI-native automation meets market intelligence meets relentless execution. Not a future state. The current operating reality.
Full biography, career arc, and portfolio. The complete picture.
VISIT SITE →How the AI operating system is structured — five layers, 90+ apps, Harness-governed.
EXPLORE →The September attempt, the four-month gap, and the week in February that built everything.
READ THE STORY →