AI Search Engine Optimization
48-Hour Diagnostic
The Architectural Challenge: Traditional SEO agencies optimize for 2012 Google bots. When enterprise buyers query ChatGPT, Perplexity, or Claude for vendor recommendations, un-optimized brands are completely invisible.
llms.txt Endpoint
200 OK // 48KB Synthesized
JSON-LD Knowledge Graph
52 Disambiguated Entities
Citation Consensus
Rank #1 Cited Vendor
- Deploy machine-readable
llms.txt & llms-full.txt context endpoints.
- Engineer deep nested Schema.org JSON-LD knowledge graphs & entity disambiguation.
- Establish cross-platform web consensus across registries & technical hubs.
- Systematically displace competitor citations in ChatGPT Search and Google AI Overviews.
llms.txt Standard
JSON-LD Graphs
ChatGPT Search
Perplexity Pro
Vector Context
Speed & Performance Engineering
48-Hour Staging Sprint
The Architectural Challenge: Interaction to Next Paint (INP > 200ms) and Cumulative Layout Shifts trigger silent mobile ranking demotions and cause 30–50% checkout drop-offs.
Interaction to Next Paint
380ms < 76ms (79% faster)
Cumulative Layout Shift
0.342 0.000 CLS (Zero Shift)
Production Risk
Zero Downtime Staging Clone
- Isolated clean-room staging clone diagnosis eliminating all production risk.
- Purge delay-JS cloaking plugins that mask real user performance penalties.
- Deterministic elimination of layout shifts to 0.000 CLS via CSS containment.
- Main-thread JavaScript unbundling for INP < 100ms on mobile devices.
INP < 100ms
0.000 CLS
LCP < 1.2s
Clean-Room Staging
CrUX Aligned
Modern Web Platforms
Bespoke Architecture
The Architectural Challenge: Sluggish corporate websites built on bloated WordPress themes or unoptimized React SPA bundles that churn high-value enterprise prospects.
Time to First Byte
< 180ms Global Edge TTFB
Client JS Bundle
< 38KB Initial Hydration
Lighthouse Benchmark
100 / 100 / 100 / 100
- Production Next.js 14/15 App Router engineering with React Server Components (RSC).
- Strict TypeScript typings, zero-hydration layout shifts, and sub-500ms initial loads.
- Headless content layer integration with Supabase, PostgreSQL, or edge KV stores.
- Automated CI/CD performance regression gates preventing future code degradation.
Next.js 15
React 19 RSC
Strict TypeScript
Edge Runtime
Supabase KV
Engineering Leadership & Rescue
3–5x Velocity
The Architectural Challenge: Scaleups trapped in low-velocity offshore cycles where every feature release introduces 3 new regression bugs, costing founders months of progress.
Code Stewardship
100% Principal Systems Architect
Sprint Velocity
3.8x Delivery Speedup
Total Cost (TCO)
~42% TCO Reduction
- Direct senior architect stewardship: zero junior developers, zero management overhead.
- Emergency triage and cleanup of spaghetti codebases, orphaned packages, and security holes.
- Refactoring legacy technical debt into clean, testable, modular micro-architectures.
- Time-zone aligned asynchronous updates and direct Slack collaboration channels.
Principal Engineer
Codebase Audit
Security Hardening
TCO Reduction
Zero Bloat
Internal Tools & Labs
Manifest V3 Certified
The Architectural Challenge: High-friction internal operations, compliance auditing, and data extraction bottlenecks that commercial off-the-shelf SaaS tools cannot handle.
Data Privacy
Zero External Leak // Isolated
Storage Latency
< 4ms chrome.storage.local
Production Creds
Published Store Authors (Fogo)
- Architecting private Manifest V3 browser extensions with zero external data leaks.
- Offline-first local caching using
chrome.storage.local for zero latency.
- DOM scrapers, automated compliance radars, and real-time publisher audit tools.
- Published creators of flagship extensions on the official Chrome Web Store (Fogo, AffiScope).
Manifest V3
Chrome Web Store
DOM Automation
Offline-First
TypeScript SDK
Backend & Infrastructure
Enterprise SLA
The Architectural Challenge: Backend APIs and database schemas buckling under traffic spikes, slow transactional queries, and rigid legacy ERP approval workflows.
FastAPI Middleware
< 12ms P99 Latency
Database Tuning
PostgreSQL Connection Pooling
Enterprise ERP
PeopleSoft AWE & CI Stabilized
- High-speed asynchronous API middleware engineering with Python and FastAPI.
- Docker containerization, microservice isolation, and zero-downtime deployment pipelines.
- PostgreSQL schema indexing, connection pooling, and heavy-duty query tuning.
- Oracle PeopleSoft ERP performance tuning and automated Approval Workflow Engine (AWE) setup.
FastAPI
PostgreSQL
Docker
Oracle PeopleSoft
AWE Automation