Adam R. Cagle
AI Systems

AI Systems.

A collection of production products, public betas, open-source systems, and research prototypes built across Claude Projects, GPT Projects, and Anthropic API deployments. The work spans brand voice, campaign production, market intelligence, agent-commerce architecture, governed marketing workflows, and geospatial research. Every system keeps a human in control of the decisions that matter.

// Skills & Guardrails

I’ve got skills.

Skill files and Markdown guardrails steer frontier models to reliable output and automate work at scale, from copywriting to proposals. Touch a name to scatter it. Four I share the most.

Brand Voice · Copy System

Sunset Marquis Copy System

The operating voice for Sunset Marquis. Speaker, pillars, banned moves, fact rules, and channel guidance that keep AI-drafted copy on brand and accurate. The same system behind the hotel’s campaigns.

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Operating System · Company Build

AIC · The AI Corporation

A playbook for building an AI-native company. MTP constitution, agent fleet, workflow interfaces, live dashboards, governance, and unit economics, from idea to operating model.

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Proposals · Fundraising

The Grant Application Builder

A disciplined system for fundable proposals. Funder fit, evidence labels on every claim, reconciled budgets, portal-ready answers, and a human review gate. Never fabricate, never submit.

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Production · Ship Discipline

Finisher

Turns a working prototype into a launchable product. A 13-layer readiness scorecard, P0/P1/P2 triage, security gates, and a hard definition of done. A working demo is not a finished product.

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// The Applications

Systems that run.

Production products, public betas, open-source systems, and research prototypes. Systems built to run, expose their rules, and keep high-risk capabilities gated.

01 · Guided Interactive Demo · Governed AI

Website Content Migration Accelerator

Website Content Migration Accelerator workflow graph with guided narration
3Sample workflows with guided voice-over narration
40Executing nodes in the governed workflow
45Evidence and review-state connections
0Automatic public writes
The System
Each record moves through deterministic intake, extraction, retrieval, disposition, ambiguity analysis, independent verification, authority gates, human review, and final audit output.
The Guided Experience
Choose from three sample workflows. A polished voice-over explains every decision, safeguard, model handoff, and human checkpoint while the record moves through the live 3D graph.
Human Authority
Models recommend and verify. Deterministic controls validate the evidence. Humans retain authority over every consequential decision.
n8nMulti-ModelEvidence IDsHuman ReviewGrok Voice
02 · Production · WordPress SEO · ChatGPT App
Singularity SEO dashboard
2Control surfaces: WordPress dashboard + ChatGPT app
4Operating stages: audit, field study, AIO build, tracking
GSCSearch Console: clicks, impressions, CTR, position
LiveRank feed: found, pending, improvement states
Google Analytics Certification 2026 badge Google Analytics Certification (2026)GA4 reporting, conversion measurement, attribution, and SEO/AIO progress tracking.
Problem
Small teams need SEO that works for classic search and AI answer systems, but the work fragments across plugins, keyword tools, spreadsheets, dashboards, and someone guessing what to change next.
System
Singularity SEO turns ChatGPT into the control room for a connected WordPress site: managed pages, rendered metadata, technical health, GSC visibility, and live rank checks. ChatGPT audits the site, studies competitors, and builds page-level SEO and AIO recommendations.
Workflow
Connect WordPress, verify the site, run a read-only baseline, then review competitors, choose keyword lanes, produce one governed full-site proposal, apply approved updates, and preserve rollback-ready change IDs.
Outcome
SEO becomes an operating loop instead of a plugin screen: audit, compete, optimize for search and AI answers, measure the result, then improve again.
03 · Free Beta · Agent-Native Marketplace

Agent Exchange

Agent Exchange live marketplace API dashboard
Problem
An agent marketplace needs identity, policy, reputation, dispute handling, and explicit limits before money or fulfillment enters the loop.
System
Verified agents can publish permitted inventory, search listings, negotiate offers, record trade outcomes, and build reputation through a machine-readable API.
Architecture
Node.js, JSON and MCP interfaces, Ed25519 authentication, idempotent trade states, offer negotiation, rate limits, moderation controls, and an admin audit surface.
Current Status
Free beta is live. Payment processing, custody, and smart-contract escrow remain deliberately disabled behind feature gates.
Free BetaOpen SourceEd25519Payments Gated

Designed and built by Adam R. Cagle as a public systems, policy, and agent-commerce architecture sample.

// Systems & Agents

Built with intent.

I design, direct, and ship AI systems across production, open source, and research. Each is built around explicit rules, bounded authority, and human control over the decisions that matter.

04 · Production · Brand Voice · RAG

Agency689 Writing Systems

½×Production time per campaign cycle
3+Viable first drafts per run
3/wkSunset Marquis runs in active cycles
3Active client brands in production
Problem
Agency work creates constant demand for strong first drafts across email, banners, ad creative, landing pages, and social, with zero tolerance for voice drift. Generic AI output is the enemy.
System
Brand context files, RAG-retrieved voice samples, SKILL.md governance, and persona specs are assembled before any draft. The system produces multiple drafts, routes them through a standards AI for voice and quality, then to a human for approval via Telegram. Nothing ships without sign-off.
RAGSKILL.mdTelegramStandards AI
05 · Open Source · Architecture Sample

VRT2 · CLAW

VRT2 CLAW dashboard
27Data streams ingested daily
23Active hypotheses across 6 tiers
5Verification states per signal change
20%Drawdown fires a system-wide kill-switch
System
Node.js + SQLite backbone. Claude Haiku handles routine daily reviews; Claude Sonnet handles advanced analysis. Ingests Finnhub, EDGAR, earnings transcripts, analyst revisions, and macro feeds daily, synthesized into structured intelligence briefs.
Discipline
Every signal moves UNVERIFIED → SYNTAX_OK → SQL_VERIFIED → RUNTIME_VERIFIED → PRODUCTION_VERIFIED. New signals run at 0.50× weight until proven; sub-55% hit rates auto-deactivate; a 20% drawdown fires the kill-switch. Nothing trades automatically.
Node.js + SQLiteKill-switchMIT Open Source
GitHub
06 · Open Source · Governed Book Marketing

BookLite

BookLite dashboard
6Channels: Reddit, X, FB, IG, Goodreads, KDP
1Claude brain: book, author voice, strategy unified
Selectable autonomyAutonomous or human-approved workflows
MITFork it, adapt it, ship it
System
A single Claude brain reads book metadata and generates platform-specific copy for all six channels in one run. OAuth2 and OAuth 1.0a handle auth server-side. KDP ranking data feeds back in via Rainforest API for attribution learning.
What it is
The open-source Lite release of the internal Agentic689 book and music marketing system. One book, one author voice, one Claude brain, six platforms. The Lite release strips to the essentials so the architecture is readable.
GitHub
07 · Proof of Concept · AI Gold Prospectivity

AuScan

AuScan dashboard
72%HIGH-confidence score validated vs USGS MRDS
5Sensors: ESRI, EMIT, Landsat, ASTER, Sentinel-2
10World-class gold deposits as training fingerprints
5×5Max search grid across 100-mile radius
System
AuScan trains Claude Vision on the spectral and structural signatures of ten world-class gold deposits: Witwatersrand, Carlin Trend, Kalgoorlie, and others. Multi-sensor data is assembled into terrain fingerprints for each deposit.
Validation
In testing it scored a HIGH-confidence hit at Oregon’s Pueblo Mining District, a documented former gold producer, cross-referenced against the USGS Mineral Resources Data System.
GitHub
// AI Learning

Donkey on the Edge.

What happens when you point these models at something genuinely hard and learn by making them make it. Case in point.

F = ma → Quantum Gravity
Donkey curriculum map
18Days from Newtonian mechanics to the frontier
38Reference documents written from scratch
5New results across 3 theorems in Paper I
1Integer-valued exponent gap nobody has explained
On April 23, 2026 I asked Claude where to start with quantum mechanics. No physics degree behind the question. The conversation ran in one unbroken thread from Newtonian mechanics to the frontier. By May 11 it had produced a paper, “Complexity-Sensitive Complementarity in Non-Isometric Holographic Codes,” headed for the arXiv.
// Supporting Systems

Other systems.

Marketing Automation

Book & Music Marketing

The production-scale predecessor to BookLite: multiple titles, multi-artist configurations, and cross-platform attribution at scale.

Identity Systems

Persona Governance

Validated persona scaffolding that holds an agent’s voice and authority bounds across runs.

Correlation Engine

COOK · Anomaly Correlation

Multi-asset anomaly correlation across markets, surfacing what moves together and why.

Site · Shipped by Agent

Agentic689 Site

The studio’s own website, built and shipped by an agent.

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