Portfolio

Case Studies

Deep-dive breakdowns of real projects - architecture decisions, metrics, and lessons learned. Not mock-ups. Production code.

Browse the project portfolio

Case Study 01

Fernhill Community PWA

A full-featured community platform - real-time messaging, event management, privacy protection - built solo across 16 active build days of AI-assisted engineering.

Next.js 16 React 19 Supabase PostgreSQL Capacitor 7 Stripe Connect Row-Level Security E2E Encryption PWA

Community Needed Enterprise Features on a Startup Budget

A community organization needed a full-featured platform with real-time messaging, event management, member directories, and privacy protection. Traditional development estimates ranged from $381K to $736K with 12-18 month timelines.

Agentic Engineer + AI Paradigm

Solo developer leveraging AI-assisted development - not "vibe coding," but a disciplined engineering process where a human architect directs AI tools to produce production-grade output. Every line reviewed. Every pattern intentional.

72,738
Lines of Production Code
320
TypeScript Files
104
React Components
87
Database Tables
183
Passing Tests
16
Active Build Days
  • End-to-end encrypted direct messaging (Web Crypto RSA-OAEP key exchange)
  • Stripe Connect payouts for event fees and membership (Express accounts)
  • Cross-platform delivery via a Capacitor 7 native shell over the Next.js web app
  • Real-time updates via Supabase subscriptions across 87 Postgres tables
  • Row-level security enforced on every table; STRIDE threat model
  • WCAG 2.1 AA accessibility; PWA with offline support and push notifications
95% Cost reduction - $20,235 actual vs $381K-$736K traditional estimate
18-36× Return on investment compared to conventional development
~96% Time reduction - 16 active build days vs a 12-18 month traditional timeline
Why This Matters

Proves the Agentic Engineer + AI model is viable for enterprise-grade applications. This isn't a toy demo - it's ~73K lines of production code across 87 tables, with end-to-end encryption, row-level security, Stripe Connect payouts, and a STRIDE threat model.

Case Study 02

Vet-Rate.org - On-Device AI for Veterans

Browser-based AI that helps veterans navigate VA disability claims — zero server-side data collection, wrapped in a dual-LLM injection defense, a tamper-evident audit log, and a red-team CI gate. Your data never leaves your device.

React Vite WebLLM Wllama RAG Dual-LLM Defense Red-Team CI Web Crypto PWA

Sensitive Data Can't Leave the Device

Veterans need help navigating complex VA disability claims - understanding regulations, rating criteria, and documentation requirements. But personal health information and service records are extremely sensitive. Sending that data to a cloud API is a non-starter.

AI That Runs Entirely in the Browser

Instead of calling OpenAI or any external API, the entire AI pipeline runs in the user's browser. LLM inference, RAG retrieval, voice processing, and OCR - all on-device. Zero network calls for personal data. Ever.

React / Vite PWA WebLLM (WebGPU) Wllama (WASM) HF Transformers.js RAG Pipeline Voice Orchestration Tesseract OCR
803
Passing Tests (46 files)
7
Red-Team Attack Classes
41
Free Veteran Tools
100%
On-Device Inference

Treating the LLM Itself as an Attack Surface

On-device inference removes the server, but an LLM that reads VA regulations, scanned paperwork, and retrieved documents is still exposed to prompt injection. The defense is built like a real trust boundary:

  • Dual-LLM split defense — a privileged controller orchestrates, while untrusted content is processed by a quarantined worker that never sees privileged actions (dualLLM.js)
  • PII spotlighting & scrubbing — untrusted text is delimited and obfuscated PII is scrubbed before it reaches the model (piiScrubber.js), and URLs are stripped from output before any external send (sanitize.js)
  • Hash-chained, tamper-evident audit log — each AI interaction is appended with sha256(prevHash ‖ entry); a single changed byte breaks the chain. It stores SHA-256 digests, never raw prompts or PII — and it's honestly tamper-evident, not tamper-proof (no signing key)
  • Red-team CI gate — every build replays a corpus spanning 7 attack classes (direct & indirect injection, exfiltration, URL bait, schema hijack, PII traps, and mixed) against the defenses
  • STRIDE threat model + OWASP LLM Top 10 mapping; NIST SSDF v1.1 and OWASP ASVS L1 aligned informally (no formal attestation claimed)
  • On-device LLM inference (WebLLM / Wllama) — no API calls, no data exfiltration
  • RAG pipeline over 38 CFR Parts 3 & 4, validated against the eCFR
  • Voice input/output and document OCR for scanning VA paperwork
  • 41 free claim tools (C-File analyzer, nexus builder, C&P prep, buddy statements)
  • Optional BYOK Google Gemini for users who want it — local-first by default
  • 803 passing tests across 46 files; 6-job CI (quality, test, build, e2e, red-team, security) + CodeQL
Zero Personal data sent to any server — privacy by architecture, not policy
7-class Prompt-injection red-team gate on every CI build
~41% Line coverage today — stated honestly, still climbing
Why This Matters

Most "AI" apps just call OpenAI. Vet-Rate runs the entire inference pipeline on the user's device and treats the model as an attack surface — a dual-LLM boundary, a tamper-evident audit chain, and a red-team gate are rare even in funded products. The numbers are stated honestly: ~41% line coverage and a mobile-hardening sprint still in progress. A VA API integration reached OAuth sandbox success (PKCE) but ships flag-disabled pending re-credentialing, so no veteran data ever touches it.

Case Study 03

Compliance-as-Code - 10-Framework Cross-Mapping

Codified compliance that maps controls across 10 regulatory frameworks, generates OSCAL, and automates evidence collection.

NIST OSCAL MCP Server VS Code Extension CMMC SOC 2 HIPAA GDPR

Compliance Framework Overload

Organizations subject to multiple regulatory frameworks (SOC 2, HIPAA, GDPR, PCI DSS, etc.) face massive redundancy. The same control - "encrypt data at rest" - appears in different language across every framework. Teams waste months re-documenting the same controls.

Codify Everything. Map Once. Export Anywhere.

Treat compliance like code: version-controlled, testable, and machine-readable. Map controls across all 10 frameworks to identify overlaps, generate NIST OSCAL catalogs for interoperability, and provide developer tools for inline compliance checking.

10
Regulatory Frameworks
214
Mapped Controls
7
MCP Tools
31
Compliance Templates
  • 10 regulatory frameworks cross-mapped with shared controls identified
  • NIST OSCAL export for GRC tool interoperability
  • AI-assisted compliance review (offline + Claude API)
  • VS Code extension with IntelliSense for control IDs
  • MCP server for AI assistant integration
  • Automated evidence collection and gap analysis
10→1 Unified control mapping eliminates redundant documentation
OSCAL Machine-readable output interoperable with SIEM and GRC platforms
Why This Matters

Most compliance tools handle 1-2 frameworks. This maps 10 simultaneously with NIST OSCAL output - the standard the federal government is converging on. Plus developer tools that put compliance in the IDE, not a spreadsheet.

Case Study 04

AetherMyst - Enterprise-Scale Game Engine

A production-quality RPG in Unreal Engine 5.7 with professional C++ architecture, 17 modules, and custom MCP automation.

Unreal Engine 5.7 C++ GAS 17 Modules MCP Automation Gameplay Debugger

Proving Systems-Level Engineering Depth

Web portfolios are common. Proving you can architect large-scale C++ systems with real-time constraints, memory management, and modular plugin architecture? That requires building something substantial.

Full UE5 Game with Enterprise Patterns

Build a complete RPG with the Gameplay Ability System, modular architecture (17 separate modules), automated testing, and custom MCP integration for AI-assisted game development.

362
C++ Source Files
42,727
Lines of C++
17
Modules
23
Subsystems
369+
MCP Commands
78+
Automation Tests
  • GAS-based combat: combo, block, dodge, magic, ranged, melee
  • 78+ automation tests for regression safety
  • Save/load system with serialization
  • Object pooling for performance optimization
  • Custom gameplay debugger for runtime inspection
  • 68 native gameplay tags for clean event routing
0.28s Clean PIE (Play-In-Editor) boot time
27s Incremental build time - fast iteration on 42K+ lines
17 Independent modules - clean separation, no spaghetti
Why This Matters

Shows depth beyond web development - full systems programming with enterprise patterns. GAS mastery, modular C++ architecture, automated testing, and custom tooling for AI-assisted game development.

Case Study 05

Structured For Growth - The Meta-Portfolio

A portfolio site that IS the portfolio - every best practice it advertises is demonstrable in its own codebase.

Vite Express CI/CD CodeQL SAST OWASP ZAP SBOM Zero Trust FedRAMP

Practice What You Preach

Most portfolio sites claim expertise in security, accessibility, and compliance - but their own codebase doesn't demonstrate any of it. If you're selling best practices, your portfolio should be the proof.

Recursive Portfolio Architecture

The site itself demonstrates everything it advertises. Compliance engine? Built in. WCAG accessibility? Tested and validated. Security headers? A+ rated. CI/CD pipeline? 4-stage with SAST, DAST, and SBOM generation.

12
Compliance Frameworks
651+
Mapped Controls
554
Passing Tests
55
Test Files
5-Phase
Deploy Pipeline
A+
Security Headers
  • 12 compliance frameworks with 651+ controls codified
  • 554 passing tests across 55 test files (unit, integration, E2E, accessibility)
  • 5-phase deploy pipeline: Fix → Validate → Prepare → Build → Ship
  • 4-stage CI/CD: CI → CodeQL SAST → OWASP ZAP DAST → Release with SBOM
  • VPAT (Voluntary Product Accessibility Template) generation
  • AI guardrails with prompt injection defense
  • PIV/CAC authentication flow for federal clients
  • WCAG 2.2 accessibility throughout
A+ Security headers rating - CSP, HSTS, and full header hardening
WCAG 2.2 Accessible - keyboard navigation, screen reader support, color contrast
Recursive The portfolio demonstrates exactly what it sells - zero gap between claims and implementation
Why This Matters

Recursive portfolio - the site demonstrates exactly what it sells. When a client asks "can you do compliance?" the answer is "you're looking at it." No gap between marketing claims and technical reality.

Case Study 06

Battle Buddy Club

World-class veteran connection platform connecting all branches of service.

Next.js 16.1.6 TypeScript Prisma Tailwind CSS Auth.js Pusher (WebSockets) Resend UploadThing Web Push

Veterans Need Real Connection, Not Another Directory

Veteran isolation is a crisis. Existing platforms offer directories and forums, but nothing that creates genuine, real-time connection with Battle Buddy matching, mutual aid, and community support — the kind of platform that usually requires a team of 5-10 engineers.

Full Social Network Architecture, Solo Build

Build a complete social platform with real-time messaging, push notifications, image processing, OAuth with military verification, and content moderation — all as a single developer leveraging AI-assisted engineering.

79
Source Files
Real-Time
WebSocket Backbone
Multi-Tier
Verification System
Full Stack
Social Platform
  • Battle Buddy matching by branch, era, location, and interests
  • Groups & communities with real-time messaging
  • WebSocket-powered live updates, typing indicators, online presence
  • VSO Finder for veteran service organizations
  • Mutual aid system (request/offer help: transportation, housing, food, employment)
  • Crisis Support with 24/7 Veterans Crisis Line integration
  • OAuth + ID.me military verification
  • Image uploads with automatic optimization
  • Push notifications (browser) + HTML email notifications
  • Admin dashboard with content moderation and audit logs
Full Social Complete social network — not a CRUD app, not a directory
Real-Time WebSocket messaging, typing indicators, presence — live interaction
Solo Build The kind of system that usually takes a team of 5-10 engineers
Why This Matters

Full social platform — not a CRUD app. Real-time messaging, push notifications, image processing, OAuth, content moderation. The kind of system that usually takes a team of 5-10.

Case Study 07

CanSo Music

Direct-to-fan music platform. Artists own their data. 100% revenue to artists.

Next.js 16.1.6 Prisma 7.3.0 Stripe Connect Cloudflare R2 Tailwind CSS v4 Shadcn/UI Resend Playwright NextAuth v5

Music Platforms Take Too Much, Give Too Little

Artists lose 15-30% of revenue to platforms. Distribution is locked behind gatekeepers. DDEX compliance is a nightmare. Musicians need a platform where they own their data and keep 100% of their revenue.

Vertical SaaS — Payment to Distribution in One Platform

Build a vertically integrated music platform: Stripe Connect for split payments, Cloudflare R2 for zero-egress content delivery, DDEX for industry-standard distribution, and Playwright for end-to-end quality assurance.

685
Source Files
DDEX
Industry-Standard Export
100%
Revenue to Artists
E2E
Playwright Testing
  • DDEX industry-standard music distribution export
  • Stripe Connect split payments & subscriptions
  • Cloudflare R2 storage (S3-compatible, zero egress costs)
  • Artist dashboard & analytics
  • Fan storefronts with custom theming
  • Album/track management with metadata
  • Playwright E2E testing
685 Files Full vertical SaaS platform — payment, delivery, metadata, distribution
DDEX Industry-standard XML export for major distributor compatibility
Bandcamp-Scale A vertical SaaS platform that could compete with established players
Why This Matters

Music industry tech is notoriously complex — DDEX XML, royalty splits, content delivery at scale. This isn't just a web app, it's a vertical SaaS platform that could compete with Bandcamp.

Case Study 08

Patriot Ledger (Tax-Ronomicon)

Client-side tax preparation for service-disabled veteran business owners — dual-algorithm validation, IRS-citation traceability, and AES-256 in the browser.

Next.js TypeScript AES-256 Encryption SHA-256 Integrity Zero-Trust Browser

Tax Software You Can't Trust

Tax preparation software handles the most sensitive financial data imaginable, yet most tools send everything to a server, use single-algorithm calculations, and offer zero legal traceability. Service-disabled veteran business owners face unique tax complexities that generic software handles poorly.

Client-Side Only, Dual-Algorithm Verification

All data stays in the browser, encrypted with AES-256. Every calculation is verified by two independent algorithms that must agree before any number is accepted. Every field is mapped to specific IRS legal citations for full traceability.

61
TypeScript source files
172/194
tests passing
12
double-blind validators
Zero
Server-Side Data
  • Double-Blind Calculation Validation — two independent algorithms, locks on discrepancy
  • Legal Citation Layer — every field mapped to specific IRS codes (26 USC, IRS Publications)
  • SHA-256 cryptographic integrity for tamper detection
  • All data stays in browser (AES-256 encrypted, zero-trust architecture)
  • Federal calculators — Form 1040, Schedule C, SE tax, Section 179 / MACRS depreciation, QBI (federal totals and depreciation modules are in active stabilization — see test status below)
  • Oregon / Portland-Multnomah state calculators — in progress; their test suites currently fail and are being resolved
  • Auto-generated project health dashboard (tests, architecture checks) via the CTK toolchain
172/194 Tests passing across 18 files; 22 still failing in the state-tax, depreciation, and Form 1040 total-tax modules (in progress)
Double-Blind Two independent algorithms must agree before a number is accepted
Zero Trust All data encrypted client-side — nothing ever touches a server
Why This Matters

The architecture treats correctness as a first-class concern: a double-blind validation layer where two independent algorithms must agree before any number is accepted, every supported field traced to an IRS citation, and all data encrypted in the browser. It's a work in progress — the federal core validates, while the state and depreciation calculators are still being stabilized — but the design shows how high-assurance tax logic can run entirely client-side.

Case Study 09

Client Management System

Encrypted client management platform with appointment scheduling, intake workflows, and zero-trust data isolation for service-based businesses.

Express Node.js AES-256 Encryption JWT Auth RBAC REST API CI/CD

Service Businesses Need Secure Client Data Handling

Service-based businesses — wellness practitioners, consultants, therapists, coaches — collect sensitive client information: health histories, contact details, session notes, and payment data. Off-the-shelf booking platforms store this data on third-party servers with opaque security practices. HIPAA-grade data isolation shouldn't require enterprise budgets.

Encrypt Everything. Own Your Data.

Build a self-hosted client management platform where all personally identifiable information (PII) is encrypted at rest with AES-256. Role-based access control ensures staff see only what they need. Appointment scheduling, intake forms, session tracking, and client communications — all in one system with full audit logging.

AES-256
PII Encryption at Rest
22
Passing Tests
RBAC
Role-Based Access
Zero Trust
Architecture Pattern
  • AES-256 encryption for all client PII at rest
  • Appointment scheduling with availability management and reminders
  • Digital intake forms with encrypted submission storage
  • Session notes and treatment tracking with provider-only access
  • Role-based access control (admin, provider, front desk)
  • JWT authentication with refresh token rotation
  • Full audit logging for compliance traceability
  • RESTful API designed for future frontend integrations
HIPAA-Grade AES-256 encryption and RBAC meet healthcare-level data protection requirements
Self-Hosted No third-party data storage — the business owns its data completely
Audit-Ready Full logging trail satisfies regulatory review and insurance requirements
Why This Matters

Most small-business booking platforms treat security as an afterthought. This system applies enterprise-grade encryption and access control to a domain that desperately needs it — protecting real client data with the same rigor used in federal systems.

Case Study 10

Firearm Safety Team

Full-stack class-management CMS for a Portland community safety-education service — digital waivers, multi-provider payments, and an admin calendar dashboard.

Next.js 16 React 19 TypeScript Tailwind CSS 4 Prisma ORM Stripe Square PayPal NextAuth.js Leaflet

Community Safety Education Needs Professional Infrastructure

Running a firearm familiarization service for marginalized communities requires professional class management, secure registration, payment processing, and scheduling — but off-the-shelf solutions don't serve the mission.

Purpose-Built CMS with Full Business Logic

Build a complete content management system with public-facing class listings, student registration with waiver agreements, Stripe payment processing, admin dashboard with calendar view, and email notifications — all optimized for the specific needs of a community-focused training organization.

43
Database Models
109
API Endpoints
103
Page Routes
561
Passing Tests
  • Student registration with digital waiver agreements
  • Multi-provider payments — Stripe, Square, and PayPal behind an ADR-defined payment source-of-truth, plus gift cards and a merch store
  • Admin dashboard — class management, calendar view, orders, and a system health panel
  • Distributed rate limiting, feature flags, and webhook event-status tracking
  • Interactive range-location map (Leaflet)
  • Email notifications via Nodemailer; NextAuth.js + bcrypt authentication
  • STRIDE threat model and 13 ADRs documenting the key architecture decisions
561 Tests All passing across 57 files, with enforced coverage gates — 90% lines, 85% functions, 80% branches
Multi-Provider Stripe, Square, and PayPal behind one ADR-defined payment source-of-truth
13 ADRs + STRIDE Architecture decisions and a threat model documented in-repo
Why This Matters

The oath I swore never came with an expiration date. This platform turns community safety education into a professional operation — class management, multi-provider payments, scheduling, and student tracking — built with the same engineering rigor as the enterprise projects: 561 passing tests behind enforced coverage gates, 13 ADRs, and a STRIDE threat model. It's honestly versioned at v0.1.0 — admin MFA and a handful of hardening items are still on the roadmap.

Case Study 11

Project Prism

Zero-knowledge LGBTQIA+ safety app with Signal Protocol encryption, resource mapping, and panic mode. AGPL-3.0 open source.

React 18 TypeScript Django 4.2 PostgreSQL + PostGIS Signal Protocol TweetNaCl Docker Leaflet

Safety Apps Must Be Trustworthy — Zero Knowledge Required

LGBTQIA+ individuals need safety resources, community connection, and secure communication — but existing platforms collect data that could be weaponized. A safety app that stores your data in plaintext isn't a safety app.

Zero-Knowledge Architecture with Signal Protocol

Build a full-stack safety platform where the server can never read user content. End-to-end encryption via Signal Protocol, anonymous community boards, geospatial resource mapping with PostGIS, and emergency features including panic mode with shake-to-hide and duress PINs.

120+
Source Files
19+
Verified Orgs
19
Tribe Categories
Zero
Server-Readable PII
  • Resource map with 19+ verified organizations (HRC, Trevor Project, PFLAG, etc.)
  • End-to-end encrypted messaging via Signal Protocol
  • Tribes — anonymous community boards across 19 categories
  • Mutual aid network for requesting and offering support
  • Queer Cache — location-based encrypted messages
  • Panic mode with shake-to-hide and duress PINs
  • Community Bridge — transparent bug tracking
  • Admin moderation system with trust levels
  • React Native mobile app
Zero Knowledge Server never sees plaintext — Signal Protocol E2EE throughout
Open Source AGPL-3.0 — community can audit, fork, and deploy independently
Full Stack React frontend, Django backend, PostGIS, Docker — production-ready
Why This Matters

Safety technology for marginalized communities must be trustworthy by design, not by promise. Zero-knowledge architecture means even a compromised server reveals nothing. Signal Protocol encryption, panic modes, and anonymous boards — built for people whose safety depends on privacy.

Case Study 12

Midnight Agentic

A local-first MCP swarm — an architect → programmer → executor pipeline backed by 94 specialized agents and 674 MCP tools, running fully air-gapped.

Python 3.11+ LangChain MCP Server Docker LM Studio Multi-GPU

Cloud AI Is a Leash — Local LLMs Need Orchestration

Running AI locally preserves privacy and control, but individual models can't handle complex multi-step workflows. You need parallel agents with different specializations working together — an architect, a programmer, and an executor — without sending a single byte to the cloud.

Swarm Architecture with Specialized Agents

The core is a spec → code → execution pipeline where the Architect defines requirements, the Programmer implements them, and the Executor runs and validates the output — each on its own local LLM endpoint with a custom system prompt. That pipeline grew into a registry of 94 specialized agent modules exposing 674 MCP tools (code, media, data, DevOps, and GPU), all served from a local MCP server with no cloud calls.

94
Specialized Agents
674
MCP Tools
264
Passing Tests
100%
Local Inference
  • 94 specialized agent modules exposing 674 MCP tools from one local server
  • Architect → Programmer → Executor spec-to-execution pipeline
  • GPU task router scheduling work across 4 local GPUs (~64GB VRAM, PCIe-aware)
  • 6-job DevSecOps CI — lint, Snyk SCA + Code, tests, container scan, SBOM
  • Snyk SCA clean (0 vulnerable dependencies across 12); MCP server over HTTP/SSE
  • Docker containerization; extensible — add agents without changing the core
Air-Gapped Complete AI development pipeline with zero internet requirement
Extensible Add agents, change models, reconfigure — YAML-driven flexibility
Privacy-First Your code never leaves your machine — no telemetry, no cloud calls
Why This Matters

The agentic paradigm is the future of software development, but it doesn't have to mean surrendering your code to cloud providers. Midnight Agentic proves you can run a full multi-agent development pipeline locally — your models, your data, your control. The security posture is stated honestly: Snyk SCA is clean, while Snyk Code surfaces 259 findings — mostly expected command-injection and path-traversal signals from MCP tools that wrap local CLIs, documented in a triage doc with a per-deployment risk model rather than buried.

Case Study 13

TIP Toolkit

Technology Intelligence Platform — 404 curated sources across 21 domain profiles, trust scoring, hybrid BM25 + dense retrieval, and a multi-provider AI synthesis agent.

Python 3.11+ Flask Hybrid RAG (BM25 + dense) sentence-transformers AI Agent Trust Scoring

Information Overload Requires Intelligence, Not Just Aggregation

Tech professionals need to stay current across multiple domains — AI, cybersecurity, full-stack development — but RSS feeds are noise without curation. You need trust scoring, bias detection, and relevance filtering to separate signal from noise.

Curated Intelligence Pipeline with Hybrid Retrieval

Build a multi-source pipeline that scores every source on a 0-100 trust scale with bias indicators, then ranks content for relevance against one of 21 domain profiles (agentic AI, cybersecurity, MLOps/LLMOps, clean architecture, and more). Retrieval is hybrid: a BM25 lexical index and a dense sentence-transformers index are merged via reciprocal rank fusion, so results aren't dependent on either exact keywords or embedding quality alone. A pluggable multi-provider AI agent (OpenAI + Anthropic, with per-model cost tracking) synthesizes the ranked set into a searchable knowledge base.

404
Curated Sources
101
Passing Tests (17 files)
32
REST Endpoints
21
Relevance Profiles
  • 404 curated RSS/TLDR sources (Stratechery, MIT Tech Review, Krebs, etc.)
  • Trust scoring (0-100) with Platinum/Gold/Silver/Bronze tiers + per-source bias indicators
  • Hybrid retrieval: BM25 lexical index + dense sentence-transformers, fused with reciprocal rank fusion
  • 21 domain relevance profiles (agentic AI, cybersecurity, MLOps/LLMOps, clean architecture, …)
  • Pluggable multi-provider AI agent (OpenAI + Anthropic) with per-model cost tracking
  • Flask dashboard + REST API across 32 endpoints; CSV / Markdown export
  • 8-job CI (lint, type-check, tests, pip-audit, Bandit SAST, gitleaks, CodeQL, zizmor) + SECURITY.md threat model
  • 101 passing tests across 17 files
Signal from Noise Trust scoring and bias indicators cut through information overload
Domain-Aware Multi-profile relevance scoring for different professional contexts
Actionable Knowledge base synthesis — not just feeds, but intelligence
Why This Matters

Staying current in tech isn't about reading more — it's about reading smarter. TIP Toolkit applies intelligence-analysis techniques to tech news: trust scoring, bias detection, hybrid retrieval, and AI synthesis — turning 404 sources into actionable intelligence. It's deliberately local-first and single-user (no auth, no hosted multi-tenant surface), and the numbers are stated honestly: 101 tests currently cover ~27% of lines, and several CI scanners (pip-audit, Bandit, CodeQL) run in report-only mode while coverage and ADRs are still being backfilled — disclosed rather than rounded up.

Case Study 14

Online Security Recon

Security reconnaissance and privacy audit dashboard — tools catalog, pipeline configuration, and scan automation.

React 19 TypeScript Vite 6 Tailwind CSS 3 React Router 7 PWA

Security Professionals Need Unified Reconnaissance Tools

Security reconnaissance involves dozens of specialized tools, each with its own interface and output format. Professionals need a unified dashboard that catalogs tools, configures pipelines, runs audits, and presents findings — without juggling terminal windows.

Unified Security Dashboard with Pipeline Orchestration

Build a multi-page PWA that serves as command central for security operations — tools catalog with categorized listings, configurable recon pipelines, privacy audit workflows, agent architecture visualization, and an extensible scanner dashboard.

11
Dashboard Pages
PWA
Offline-Ready
Zero
Required Env Vars
React 19
Latest Stack
  • Dashboard overview with security posture summary
  • Tools catalog with categorized security/recon tools
  • Recon pipeline configuration and execution
  • Privacy audit assessment workflows
  • Agent architecture visualization
  • Security recommendations engine
  • Scanner dashboard with scan history
  • Offline-capable PWA — works without internet
Unified One dashboard for all security reconnaissance operations
Extensible Zero required environment variables — plug in your tools as needed
Modern React 19, TypeScript, Vite 6 — cutting-edge developer experience
Why This Matters

Security professionals shouldn't have to context-switch between a dozen terminal windows. Online Security Recon brings tool cataloging, pipeline orchestration, and audit reporting into a single, offline-capable dashboard.

Case Study 15

Five-Minute MBA

A microlearning EdTech platform that delivers occupation-specific business curriculum in five-minute lessons — 500+ curricula and 23,000+ lessons served from one Next.js codebase, with a cost-aware four-tier AI model router.

Next.js 16 React 19 Supabase TypeScript (strict) AI Model Router next-intl Stripe WebLLM Vitest + Playwright

Role-Specific Skills, Not Generic MBA Theory

Workers across every occupation sector need short, job-relevant continuing education — but most business and professional-development content is generic, long-form, and not mapped to a specific role or its regulatory context. A line cook, a paralegal, and a wind-turbine technician do not need the same lesson, and none of them has an hour to spare.

One Micro-Curriculum Per Occupation, Generated and Served at Scale

Each occupation gets a "kit" — a structured curriculum of roughly five-minute lessons with quizzes, branching scenario exercises, and spaced repetition. AI handles generation and runtime tutoring, but every call passes through a cost-aware router that maps the task to the cheapest viable model. One codebase serves consumer, high-school, university, and enterprise (SSO/seat-based) audiences across twenty languages.

501
Occupation Curricula (kit manifests)
23,473
Micro-Lessons (MDX)
20
Locales
14
CI Workflows
  • Four-tier model router (on-device Llama → Haiku → Sonnet → Opus) selects the cheapest model that can handle each task to control token cost
  • 23,000+ MDX lessons across 501 occupation kits, validated in CI
  • Internationalized to 20 locales from a single codebase via next-intl
  • 58 versioned Supabase migrations through enterprise seats, org subscriptions, and SSO
  • Spaced-repetition scheduling (FSRS / SM-2) and branching scenario assessments
  • Stripe / PayPal / Square payments; SCORM 1.2 and LTI export for institutions
  • Documented lethal-trifecta security audit and 14 CI workflows (AI-eval gate, Lighthouse, gitleaks, SBOM) plus 224 automated tests
501 kits One micro-curriculum per occupation, 23K+ lessons validated in the build pipeline
4-tier Per-task model routing — from on-device Llama up to Opus — to keep AI spend proportional to difficulty
20 langs Full internationalization across 20 locales from one Next.js codebase
Why This Matters

This is enterprise EdTech, a consumer product, and applied AI economics in one system — content at a scale (23K+ lessons) that only holds together because generation, validation, and cost control are engineered into the pipeline rather than bolted on.

In the interest of honesty: accreditation is in preparation (the IACET checklist is roughly 90% complete, targeting Q3 2026) with five further bodies planned — no body has accredited the program yet. The codebase is private, so this is a documented case study rather than a live link.

Case Study 16

History GPS

A dependency-free 3D globe that maps nearly 6,000 historical sites across 100,000 years of human history — with looted-artifact provenance arcs and a measured four-phase data-merge pipeline behind the dataset.

Vanilla JavaScript globe.gl Three.js Node.js Pipeline Vitest HTML5 / CSS3

History Is Hard to See in Space and Time Together

Historical data is scattered and rarely visualized spatially and temporally at once. It is even harder to see the displacement of looted cultural artifacts — the path from where an object originated to the museum that holds it today. History GPS makes both legible on a single interactive globe.

A Zero-Build Globe Over a Disciplined Data Pipeline

The front end is intentionally dependency-free: plain HTML, CSS, and JavaScript render a globe.gl / Three.js globe with no bundler and no framework. Behind it, a four-phase Node pipeline (validate → merge → verify → report) consolidates roughly 160 regional batch files into one canonical dataset, dedupes records, enforces ID uniqueness, and emits a machine-readable report. A dual-range slider filters by year; an arc toggle draws origin-to-museum provenance arcs for looted items.

5,968
Historical Sites
100K
Years of Timeline
20
Site Categories
1.26s
Data-Merge Pipeline
  • Interactive 3D globe (globe.gl / Three.js) with zero build step and no framework
  • Dual-range timeline slider spanning 100,000 BCE to the present
  • Looted-artifact provenance arcs drawn from an object's origin to its current museum
  • Four-phase merge pipeline that consolidates ~160 regional batch files in a measured 1.26 seconds
  • Canonical dataset with deduplicated, ID-unique records across 20 site categories
  • 119 Vitest tests covering data integrity, filtering, coordinates, and globe logic
Zero deps Vanilla HTML/CSS/JS — no framework, no bundler, nothing to ship but the static files
1.26s Measured end-to-end merge of ~160 batch files into one deduplicated dataset
0 dup IDs ID-uniqueness enforced and verified across the canonical site catalog
Why This Matters

The visible product is a globe; the real work is data engineering — turning scattered regional sources into one verified, queryable dataset, and giving contested cultural heritage a spatial story it usually lacks.

In the interest of honesty: this is currently a local prototype — a hosted demo and screenshots are the next step before it can be called live. Provenance and repatriation status are drawn from source records and, for contested objects, should be read as point-in-time rather than settled.

Case Study 17

ORC — Cognitive Prompt Router

A VS Code extension that scores each prompt's cognitive load and routes it to the cheapest viable model and effort level — FrugalGPT cascade, Haiku compression, and prompt caching applied to everyday AI coding spend.

TypeScript VS Code Extension API Anthropic SDK FrugalGPT Cascade Prompt Caching Vitest Semgrep SAST

Every Prompt Pays Top-Tier Prices

AI coding spend balloons when every prompt — trivial or complex — hits a top-tier model at full token price. Developers have no easy way to match task difficulty to model cost, or to apply 2026 cost-optimization patterns (caching, compression, cascading) automatically inside the editor.

Score the Prompt, Then Route It

ORC intercepts the prompt before it reaches the model. It scores cognitive load on a 1–10 scale — using a fast rule-based heuristic or a roughly $0.001 Haiku classifier — maps the score to one of five routing tiers, and picks the cheapest viable model and effort level, surfacing an Approve / Override / Escalate / Downgrade decision. On top of routing it layers prompt caching, Haiku-based context compression, and a FrugalGPT quality cascade that only escalates to pricier models when cheap output fails a quality check.

5
Routing Tiers
154
Passing Tests
9
Model Registry Entries
3-tier
Quality Cascade
  • Five-tier cognitive router (minimal → extreme) mapping load score to model and effort
  • FrugalGPT-style three-tier quality cascade (heuristic → structural → Haiku LLM) that escalates only on failure
  • Haiku-based context compression to shrink prompts before the expensive call
  • Prompt caching with ephemeral cache_control breakpoints on stable context
  • Real Anthropic SDK integration with streaming execution
  • Local Semgrep SAST with five custom rules plus documented prompt-injection hardening
~90% Projected input-cost reduction from prompt-cache reads — derived from Anthropic's published pricing, not a measured end-to-end benchmark
5-tier Cognitive load scored 1–10 and routed to the cheapest viable model and effort level
154 tests Routing, cascade, compression, and caching logic covered by 154 passing tests
Why This Matters

Most "use a cheaper model" advice stops at a suggestion. ORC turns AI economics into engineering — load scoring, cascading, caching, and compression wired into the editor so cost control happens by default, not by discipline.

In the interest of honesty: the cost-reduction figures (up to ~90% from cache reads, ~65% from compression) are projected from published pricing, not measured benchmarks. The model registry intentionally includes registry-ready placeholder IDs for models that are not yet released — only the Haiku entry maps to a currently-shipping model. This is a working v0.1.0 prototype, not yet published to the Marketplace.

Use Cases

From Idea to Full-Stack Web Presence

How SFG's integrated knowledge — compliance, AI, accessibility, security, MBAi methodology, and engineering discipline — transforms concepts into production systems. Every use case below is grounded in a real project.

Privacy-First AI Applications

Scenario: An organization handles sensitive user data (health records, financial info, PII) but wants to leverage AI for analysis, guidance, or decision support — without sending data to cloud APIs.

Solution Approach: Deploy on-device AI using WebLLM (WebGPU) and Wllama (WASM) for browser-based LLM inference. Pair with a RAG pipeline over domain-specific regulations or knowledge bases. Voice I/O and OCR for accessibility. Zero network calls for personal data.

SFG Capabilities Applied:

  • On-device LLM inference and RAG pipeline architecture
  • Zero Trust data architecture — no server-side collection
  • PWA for offline-first operation
  • WCAG 2.2 AA accessibility (voice, keyboard, screen reader)
  • Compliance with HIPAA/NIST data handling requirements
Proven By

Vet-Rate.org — runs the entire AI inference pipeline in the browser with zero data exfiltration. If it works for veteran health data, it works for any sensitive domain.

Rapid Enterprise Platform Development

Scenario: A community, nonprofit, or startup needs a full-featured platform — messaging, events, member management, privacy protection — but has a startup budget and a tight timeline.

Solution Approach: Agentic Engineer + AI paradigm: human architect directing AI tools to produce production-grade code at 18-36x traditional ROI. End-to-end encryption, row-level security, real-time subscriptions, WCAG accessibility — shipped in days, not months.

SFG Capabilities Applied:

  • AI-assisted development methodology (not "vibe coding" — reviewed, intentional)
  • Full-stack architecture: Next.js, Supabase, PostgreSQL, TypeScript
  • End-to-end encryption and 233+ RLS policies for data isolation
  • PWA with offline support and push notifications
  • MBAi Sustainable Balanced Scorecard for measuring ROI across financial, social, and environmental axes
Proven By

Fernhill Community PWA — 72,738 lines of production code across 87 Postgres tables and 16 active build days. Enterprise features on a startup budget.

Multi-Framework Compliance Automation

Scenario: A defense contractor, SaaS company, or healthcare organization is subject to multiple compliance frameworks (NIST 800-171, CMMC, SOC 2, HIPAA, GDPR, PCI DSS) and drowning in redundant documentation.

Solution Approach: Codify all compliance requirements as version-controlled, machine-readable data. Cross-map controls across frameworks to eliminate redundancy. Generate OSCAL catalogs for GRC tool interoperability. Provide developer tools (MCP server, VS Code extension) for inline compliance checking.

SFG Capabilities Applied:

  • 12-framework cross-mapping engine with 651+ controls
  • NIST OSCAL export for SIEM/GRC platform integration
  • MCP server (7 tools) for AI assistant integration
  • VS Code extension with IntelliSense for control IDs
  • AI-assisted gap analysis and evidence collection
  • Engineering Commandment X: "Enforce Standards Programmatically"
Proven By

Compliance-as-Code — 10 frameworks mapped simultaneously. Most compliance tools handle 1-2. Plus developer tools that put compliance in the IDE, not a spreadsheet.

Large-Scale Systems Engineering

Scenario: A project requires deep systems programming — real-time constraints, memory management, modular architecture, and automated testing at scale — beyond typical web application complexity.

Solution Approach: Apply enterprise software patterns (modular architecture, subsystem decomposition, automated testing) to systems-level code. Use the Gameplay Ability System pattern for complex state machines. Build custom MCP tooling for AI-assisted development at scale.

SFG Capabilities Applied:

  • C++ systems programming with modular plugin architecture
  • MCP automation (369+ commands) for AI-assisted development
  • Automated testing suites for regression safety
  • Performance optimization (object pooling, fast iteration)
  • Engineering Commandment I: "Write Tests First" — applied to systems code
Proven By

AetherMyst — 362 C++ source files, 42,727 lines, 17 modules, 78+ automation tests. Enterprise software patterns applied to game engine development.

Recursive Portfolio & Meta-Demonstration

Scenario: A business needs its web presence to not just claim expertise but demonstrate it — compliance, accessibility, security, performance, and AI integration all provable in the codebase itself.

Solution Approach: Build the site as a living demonstration. The compliance engine runs on the site. The WCAG accessibility is tested and validated. Security headers are A+ rated. The CI/CD pipeline includes SAST, DAST, and SBOM generation. The AI assistant uses both server inference and on-device WebLLM.

SFG Capabilities Applied:

  • 12 compliance frameworks codified in the site's own codebase
  • 4-stage CI/CD pipeline (CI → CodeQL SAST → OWASP ZAP DAST → Release with SBOM)
  • Dual-tier AI assistant (server API + WebLLM local inference)
  • WCAG 2.2 AA accessibility with DHS Trusted Tester v5.1 methodology
  • 6-gate preflight system enforcing all 10 Engineering Commandments
  • A+ security headers (Helmet.js, CSP, HSTS)
Proven By

Structured For Growth (this site) — when a client asks "can you do compliance?" the answer is "you're looking at it." Zero gap between marketing claims and technical reality.

Veteran & Mission-Driven Social Platforms

Scenario: A veteran service organization, community group, or mission-driven nonprofit needs a full social platform — matching, real-time messaging, mutual aid, crisis support — not just a directory or forum.

Solution Approach: Build a complete social network with WebSocket-powered real-time messaging, intelligent matching algorithms, push notifications, OAuth with identity verification, and admin moderation tools. Crisis support integration for high-risk communities.

SFG Capabilities Applied:

  • Full social network architecture (messaging, presence, notifications)
  • Matching algorithms (by branch, era, location, interests)
  • Crisis support integration (Veterans Crisis Line)
  • Identity verification (ID.me, OAuth)
  • Content moderation and admin audit logs
  • MBAi Servant Leadership coaching framework applied to platform design
Proven By

Battle Buddy Club — full social network for veterans. Real-time messaging, matching, mutual aid, crisis support. The kind of system that usually takes a team of 5-10 engineers — built solo.

Vertical SaaS & Industry-Specific Platforms

Scenario: An industry (music, legal, medical, trades) needs a domain-specific platform with industry-standard integrations, split payments, content delivery at scale, and compliance with sector-specific regulations.

Solution Approach: Build a vertically integrated SaaS platform with industry-standard data formats (DDEX, HL7, ACORD), split payment processing (Stripe Connect), zero-egress CDN (Cloudflare R2), and end-to-end testing (Playwright). The platform model, not a service agency.

SFG Capabilities Applied:

  • Industry-standard format integration (DDEX, OSCAL, XML schemas)
  • Payment platform architecture (Stripe Connect, split payments, subscriptions)
  • CDN and content delivery (Cloudflare R2, S3-compatible)
  • E2E testing with Playwright
  • MBAi Triple Bottom Line P&L — financial sustainability with social mission
Proven By

CanSo Music — 685-file vertical SaaS music platform. DDEX distribution, Stripe Connect payments, 100% revenue to artists. Bandcamp-scale, built by one developer.

Financial-Grade Secure Web Applications

Scenario: A financial tool, tax preparation system, or calculator handles extremely sensitive data and requires legal-grade correctness guarantees — where a miscalculation has real consequences.

Solution Approach: Client-side-only architecture with AES-256 encryption. Double-blind calculation validation (two independent algorithms must agree). Legal citation mapping for regulatory traceability. Cryptographic integrity verification (SHA-256) for tamper detection.

SFG Capabilities Applied:

  • Double-blind calculation validation — two independent algorithms must agree
  • AES-256 encryption + SHA-256 integrity hashing
  • Legal citation layer mapped to specific regulatory codes
  • Zero-trust browser architecture — no server-side data
  • Engineering Commandment III: "Security Is Not Optional"
Proven By

Patriot Ledger — client-side tax preparation. Double-blind validation, AES-256, legal citation mapping to IRS codes. 172 of 194 tests passing, zero server-side data storage.

Encrypted Client & Practice Management

Scenario: A wellness practice, consulting firm, law office, or therapy practice needs client management — appointments, intake forms, session notes, billing — with genuine data protection, not a SaaS platform that stores client data on someone else's server.

Solution Approach: Self-hosted Express/Node.js platform with AES-256 encryption for all PII at rest. Role-based access control (admin, provider, front desk). JWT authentication with token rotation. Full audit logging for regulatory compliance. RESTful API for future integrations.

SFG Capabilities Applied:

  • AES-256 encryption at rest for all client PII
  • Role-based access control (RBAC) with principle of least privilege
  • JWT auth with refresh token rotation
  • Audit logging for HIPAA/regulatory traceability
  • Compliance-as-Code patterns applied to healthcare/service data
  • Engineering Commandment II: "Automate Everything Repetitive" — scheduling, reminders, intake workflows
Proven By

Client Management System — encrypted client management for service businesses. AES-256, RBAC, audit logging. Enterprise security applied to small-business needs.

What Ties Every Use Case Together

Regardless of domain, every SFG project shares a common engineering DNA:

10
Engineering Commandments
12
Compliance Frameworks
WCAG 2.2
Accessibility Floor
MBAi
Business Methodology
  • Security by Default — AES-256, Zero Trust, CSP, HSTS on every project. Not bolted on after launch.
  • Accessibility First — WCAG 2.2 AA, Section 508, DHS Trusted Tester v5.1. Keyboard, screen reader, and voice support.
  • Compliance Built In — NIST, CMMC, FedRAMP, OSCAL baked into the development lifecycle, not a post-hoc audit.
  • AI-Augmented Development — MCP servers, agentic workflows, on-device inference integrated into the engineering process.
  • MBAi Methodology — Triple Bottom Line accounting, Servant Leadership, Sustainable Balanced Scorecard applied to every engagement.
  • Preflight Quality Gates — 6-gate system (Format → Lint → Tests → Docs → LLM Context → Audit) runs before every deploy.
  • 4-Stage CI/CD — CI → CodeQL SAST → OWASP ZAP DAST → Release with SBOM. Every commit scanned.

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