Technical Portfolio

Challenge

Built first-of-its-kind system enabling autonomous AI agents to maintain indefinite context and coordinate complex workflows across sessions.

Solution

• Architected 12-agent system using Model Context Protocol (MCP) servers
• Designed persistent memory infrastructure storing 148+ conversations (16.8M+ characters)
• Built real-time communication platform with artifact storage and version control
• Implemented cross-instance memory sharing enabling true AI continuity

Results

• Autonomous agents coordinate multi-day projects without context loss
• Workflow efficiency increased 10x vs sequential single-agent approach
• Novel architecture enabling unprecedented AI collaboration patterns
• Foundation for future multi-agent product development

Challenge

Trained RL agent to learn optimal market execution strategies on top of validated trading signals, achieving institutional-grade performance through principle-based training.

Solution

• Designed 8-phase training pipeline: market structure → extensions → entry timing → position sizing
• Implemented principle-based reward function (optimizing for correctness, not human approval)
• Built hierarchical cascade: Sector Wy (weekly) → Daily Wy → Hourly Wy coordination
• Validated through 6,479+ documented backtests establishing empirical baseline

Results

• 77% win rate achieved in out-of-sample testing (2023-2026)
• 81% average return across 69-symbol universe
• Novel architecture: RL learns execution on pre-trained market understanding
• Outperforms traditional algorithmic approaches by teaching principles, not patterns

Challenge

Built AI agent that identifies opportunities, crafts personalized outreach, qualifies responses, and routes qualified leads automatically — operating as autonomous business development representative.

Solution

• Designed dual-mode operation: consulting client acquisition + employment opportunity identification
• Implemented personalization engine analyzing target profiles and crafting custom messaging
• Built qualification logic filtering responses and routing only high-quality leads
• Integrated with davidvigil.ai for interactive lead nurturing via AI chat

Results

• Automated business development enabling focus on high-value activities
• Personalized outreach at scale (hundreds of targets, individually customized)
• Qualification pipeline ensuring only serious inquiries reach human attention
• Adaptable architecture: pivot from employment → pure client acquisition as business evolves

Challenge

Designed multi-tenant SaaS platform for algorithmic traders, measuring exact slippage between signal generation and broker execution, with real-time analytics and automated risk controls across multiple customer accounts.

Solution

• Architected multi-tenant SaaS infrastructure with isolated customer environments
• Built webhook → broker API → analytics pipeline with sub-50ms latency per tenant
• Implemented tenant-specific slippage measurement and performance tracking
• Designed circuit breaker system with automatic halt on customer-defined drawdown limits
• Created prop-firm fanning capability (1 signal → 20 accounts simultaneously per customer)

Results

• Multi-tenant architecture enabling scalable SaaS business model
• Transparent performance metrics: "The only platform showing truth about your algorithm"
• Real-time slippage tracking enabling customer strategy optimization
• Automated risk management preventing catastrophic losses across all tenant accounts
• Scalable infrastructure supporting institutional-grade execution for multiple customers

Challenge

Built production iOS application for peptide protocol tracking in single development session, demonstrating rapid AI-assisted development capabilities.

Solution

• Designed and implemented using Claude Code for accelerated development
• Built dosing schedule management with compound tracking
• Implemented local data persistence using Core Data
• Created intuitive SwiftUI interface for protocol management

Results

• Concept to working prototype in <8 hours (single development session)
• Production-ready iOS application deployed to TestFlight
• Demonstrates AI-assisted development velocity
• Proof-of-concept for rapid mobile application development

Challenge

Built database system managing 200K+ SKUs for discount grocery operations, enabling data-driven procurement and dynamic pricing across massive product catalog.

Solution

• Designed Knack.com database architecture for procurement optimization
• Implemented dynamic pricing system for discount inventory (returns, close-outs, liquidations)
• Created data-driven decision framework across 200K+ product variations
• Reduced inventory processing time by 300% through automation

Results

• Procurement decisions optimized through real-time data analysis
• Competitive pricing advantage competitors couldn't replicate
• 300% improvement in inventory processing efficiency
• Scaled two businesses to $6.45M combined revenue using this system

Challenge

Developed algorithmic trading indicators published on TrendSpider marketplace, generating recurring revenue through tiered SaaS model.

Solution

• Implemented ES5-compliant JavaScript for platform compatibility
• Ported TrendSpider PivotPro algorithm to Python with exact parity
• Built proprietary TTZ (Time-to-Zero) forecasting system
• Designed PEEP methodology (Entry/Stop/Target management)
• Validated through 6,479+ backtests across multiple symbols and timeframes

Results

• $4K-100K+ combined ARR across tiered pricing ($3.99-99.99/month)
• Forecast-first design predicting inflection points vs reacting to them
• Empirical validation methodology establishing competitive advantage
• 16+ products successfully published and generating revenue