From Marine Corps to AI Founder: An Unconventional Tech Journey

Posted on Sep 18, 2025

Sometimes the most unconventional paths lead to the most innovative destinations. This is the story of how 20+ years in operations management and hospitality became the foundation for building AI diagnostic platforms that process millions of data points.

The Foundation: Military Discipline Meets Business Operations

My journey into AI development didn’t start with computer science classes or coding bootcamps. It began at The Citadel in Charleston, SC, where I earned my Bachelor of Science in Business Administration while serving as a United States Marine Corps Reservist.

The military instilled something invaluable: systematic thinking under pressure. When you’re responsible for mission-critical operations, you learn to break down complex problems into manageable components, execute with precision, and adapt when circumstances change.

These skills would prove more transferable to software development than I initially realized.

The Hospitality Crucible: Learning Operations at Scale

After graduation in 2003, I dove into restaurant management—an industry that taught me more about real-world operations than any business school could.

Bonefish Grill: The Management Laboratory (2005-2015)

Starting as a Manager in Training in Gainesville, FL, I worked my way up through multiple locations:

  • Saint Simons Island, GA - Manager
  • Jacksonville Beach, FL - Manager
  • Mandeville, LA & Knoxville, TN - Managing Partner

The breakthrough came as Managing Partner, where I was responsible for complete P&L management. For three consecutive years, I increased sales, profits, and traffic while maintaining guest satisfaction scores above corporate expectations.

Key lesson learned: Data-driven decision making scales operations.

I was selected as 1 of only 8 restaurants nationwide for corporate menu testing—a recognition that came from consistently demonstrating operational excellence through metrics and systematic process improvement.

The Operations Playbook That Would Shape AI Development

During my hospitality years, I developed what I now call “Speed Operations”—a methodology focused on:

Rapid Problem Identification

  • Real-time data monitoring (sales, inventory, customer feedback)
  • Pattern recognition in operational metrics
  • Quick pivots based on performance data

Systematic Process Improvement

  • Breaking complex workflows into optimizable components
  • A/B testing different approaches
  • Standardizing successful processes for replication

Team Development at Scale

  • Developing hourly employees into management positions
  • Creating talent pipelines for sustainable growth
  • Building systems that function independently of individual contributors

These principles would later become the foundation of my “Speed DevOps” methodology in AI development.

The Logistics Bridge: Understanding Complex Systems

In 2020, I transitioned to logistics, becoming a CDL Class A flatbed OTR driver with TMC Transportation, then launching Longshore Logistics LLC as an owner-operator.

This wasn’t a step backward—it was strategic research.

Logistics Insights That Inform AI Architecture

Route Optimization & Delivery Coordination

  • Reduced delivery times through strategic planning
  • Algorithm-thinking applied to real-world constraints
  • Understanding the complexity of multi-variable optimization

Fleet Management

  • Preventive maintenance schedules increasing vehicle uptime by 20%
  • Data-driven maintenance predictions
  • System reliability through proactive monitoring

Performance Metrics

  • Maintained 100% DOT compliance rate
  • Achieved 98% customer retention
  • 10% reduction in operating costs through efficiency improvements

The logistics experience taught me how complex systems interact, how small optimizations compound into significant improvements, and how data-driven decisions create measurable business value.

The AI Transition: Applying Operations Expertise to Technology

In 2023, I founded Intent Solutions Inc., applying two decades of operational experience to AI development.

DiagnosticPro.io: Operations Thinking Applied to AI

The breakthrough project was DiagnosticPro.io—an AI-powered diagnostic platform that now processes vehicle diagnostics at $29.99 per analysis.

The operations background was crucial:

Data Pipeline Architecture (254 BigQuery Tables)

  • Applied supply chain thinking to data flow
  • Created systematic ingestion processes for 500K+ records
  • Built redundancy and monitoring like restaurant inventory systems

Multi-Source Integration

  • YouTube, Reddit, and GitHub APIs feeding the platform
  • Treated each data source like a vendor relationship
  • Applied procurement principles to API management

Quality Control Systems

  • Restaurant food safety protocols adapted to data validation
  • Systematic testing procedures before production deployment
  • Error handling based on hospitality service recovery methods

The “Speed DevOps” Methodology

My unique approach combines military precision, restaurant operational speed, and logistics optimization:

Concept to Production: 48-72 Hours

Phase 1: Rapid Assessment (4-8 hours)

  • Business requirements analysis using restaurant P&L thinking
  • Technical architecture planning with logistics optimization principles
  • Resource allocation based on military mission planning

Phase 2: Systematic Development (24-48 hours)

  • Modular development approach from restaurant station management
  • Continuous testing like food quality control
  • Real-time monitoring implementation

Phase 3: Deployment & Optimization (12-24 hours)

  • Staged rollout procedures from restaurant new menu launches
  • Performance monitoring using fleet management principles
  • Rapid iteration based on operational feedback

The Technology Stack: Operations-Informed Choices

My tech stack choices reflect operational thinking:

Backend: Python & Google Cloud Platform

  • Python for readable, maintainable code (like clear SOPs)
  • GCP for enterprise reliability (like choosing proven vendors)
  • BigQuery for scale (understanding high-volume operations)

Frontend: React & TypeScript

  • Component-based architecture (modular operations thinking)
  • TypeScript for error prevention (like quality control systems)
  • Responsive design from customer experience principles

AI Integration: OpenAI GPT-4 & Vertex AI

  • API-first approach (vendor relationship management)
  • Cost optimization (P&L management experience)
  • Performance monitoring (fleet management principles)

Key Insights from the Unconventional Path

1. Operations Experience Accelerates Development

Understanding how systems work at scale—whether it’s a busy restaurant during dinner rush or a logistics network spanning multiple states—translates directly to architecting software systems.

Restaurant managers already think like systems architects:

  • Breaking complex processes into optimizable components
  • Monitoring multiple data streams simultaneously
  • Making rapid decisions based on incomplete information
  • Scaling operations while maintaining quality

2. Customer Service Principles Drive Better UX

Twenty years of customer-facing operations created an intuitive understanding of user experience:

  • Anticipating user needs before they’re expressed
  • Designing for stress and time pressure
  • Creating systems that work consistently under load
  • Building in graceful failure modes

3. P&L Management Informs Technical Decisions

Managing restaurant P&Ls taught cost optimization that directly applies to cloud infrastructure:

  • Understanding unit economics of API calls
  • Optimizing for performance vs. cost trade-offs
  • Planning for scale without over-provisioning
  • Monitoring metrics that actually impact business outcomes

The Competitive Advantage of Unconventional Backgrounds

Speed to Market

My “Speed DevOps” methodology—concept to production in 48-72 hours—comes from restaurant operations where being slow means losing money.

Real-World Problem Solving

Unlike developers who learned to code in academic settings, I learned to solve business problems first, then acquired the technical skills to implement solutions.

Systems Thinking

Managing complex operations with multiple stakeholders, real-time decision making, and performance pressure creates a systems thinking approach that’s invaluable in AI development.

Business Acumen

Understanding P&L, customer acquisition costs, unit economics, and operational efficiency isn’t an add-on skill—it’s foundational to building viable AI products.

Current Focus: Intent Solutions Inc.

Today, Intent Solutions Inc. specializes in rapid AI implementation for businesses that need solutions deployed fast:

DiagnosticPro.io Platform

  • 254 BigQuery tables processing millions of diagnostic records
  • $29.99 per analysis pricing model with proven unit economics
  • Multi-source data pipeline from YouTube, Reddit, and GitHub

Start AI Tools Platform

  • Rapid AI implementation showcase
  • Deployed and functional in under 24 hours
  • Demonstrates “Speed DevOps” methodology

Speed DevOps Consulting

  • 48-72 hour concept-to-production implementations
  • Operations-informed AI architecture
  • Business-focused technical solutions

Lessons for Other Career Changers

1. Your Experience Translates More Than You Think

Every industry teaches transferable skills. Restaurant management taught me:

  • Real-time system monitoring
  • Performance optimization under pressure
  • Team coordination and communication
  • Customer experience design
  • Data-driven decision making

2. Start Building Immediately

Don’t wait until you’re “qualified.” I started building AI platforms while learning the technology. The operations background gave me confidence to solve problems systematically.

3. Leverage Your Unique Perspective

My hospitality background gives me a different approach to AI development. Instead of trying to fit into traditional tech culture, I’ve built my own methodology that combines the best of both worlds.

4. Focus on Business Value

Technical skills can be learned, but understanding how to create business value is harder to teach. Lead with business understanding and support it with technical implementation.

What’s Next: The Evolution Continues

The journey from Marine Corps reservist to restaurant manager to AI founder isn’t finished—it’s evolving.

Current Projects:

  • Scaling DiagnosticPro.io to process millions of diagnostics monthly
  • Developing new AI platforms using “Speed DevOps” methodology
  • Building consulting practice around rapid AI implementation

Future Vision:

  • Creating a new category of “Operations-Informed AI Development”
  • Teaching other career changers how to leverage non-tech backgrounds
  • Building AI solutions that solve real business problems fast

Conclusion: The Power of Unconventional Paths

The most valuable lesson from this journey: your background isn’t a limitation—it’s your competitive advantage.

While others debate theoretical AI applications, I build practical solutions based on 20+ years of operational experience. While others optimize for technical elegance, I optimize for business outcomes.

The Marine Corps taught me discipline and systematic thinking. Restaurant management taught me operations at scale and customer focus. Logistics taught me system optimization and reliability.

AI development gives me the tools to amplify everything I’ve learned.

If you’re considering a career change into tech, especially AI development, don’t discount your current experience. The business world needs more technologists who understand operations, customer service, and real-world problem solving.

The unconventional path isn’t easier—but it might just be more valuable.

Want to learn more about applying “Speed DevOps” methodology to your AI projects? Connect with me on LinkedIn or explore our rapid AI implementation showcase at Start AI Tools.