Before I was deep into high-horsepower builds, I was in business leadership — scaling operations, solving process problems, and optimizing teams.
But it wasn’t until I got my hands greasy in the garage full-time that I realized: building cars and building systems aren’t that different.
Engineering Isn’t Just for Code
When I work on a 1,000+ HP Hellcat or prep a car for drag racing, I approach it like I would any complex system:
- Identify constraints (fuel flow, temperature, traction)
- Optimize inputs (timing, pressure, airflow)
- Test and iterate — always
- Use data, not assumptions
Just like code needs debugging, performance machines need diagnostics. Both worlds depend on feedback loops and fine-tuning.
From Executive Thinking to Engineering Execution
In my previous life, I was a Senior VP in the insurance space. We scaled to $620M revenue by making smart process moves. That same mindset now powers TG Motorsports — a Texas-based performance shop I founded where we build race-ready monsters with precision.
What changed? Just the tools.
The mindset? Still the same.
- Plan before you build
- Measure everything
- Fix fast, fail forward
- Deliver something that works under pressure
Tech Meets Torque
Here’s how our process at TG Motorsports mirrors dev workflows:
Software Dev Performance Build
CI/CD pipeline Dyno tuning + live track testing
Version control Build stages & documented upgrades
Monitoring & logging Sensor data, logs, diagnostics
Feedback loops Driver input + real-time testing
Whether it’s lines of code or fuel lines, you’re always managing complexity.
What I’m Working On
- A full Redeye drag build with zero electronic lag
- Race-day data logging systems to improve tuning
- Sharing knowledge with young builders entering the field
- Merging digital tools with mechanical workflows And yes, thinking about how AI and EVs will reshape everything we do in performance.
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