680 Hours, 4 Rebuilds, and Getting Fired: How I Built Software While Working Warehouse Shifts

Building software while working full-time in a warehouse requires more than technical skill—it demands relentless persistence. My journey spanned 680 hours of overnight coding sessions, four complete system rebuilds, and ultimately led to an unexpected career transformation.

The Warehouse Grind

Working 10-hour overnight shifts loading trucks left me physically exhausted but mentally restless. While my body recovered during daytime hours, my mind craved creative problem-solving. This became my development window: 2-3 hours of focused coding between shifts, often fueled by sheer determination rather than energy.

The physical labor provided unexpected benefits. Loading patterns optimized container space—a practical lesson in algorithm design. Warehouse management systems exposed me to real-world logistics problems that inspired my software's core functionality: inventory optimization for small businesses.

The Rebuild Cycle

First Build (Weeks 1-8)
Initial excitement produced a monolithic Python app. It worked locally but failed under real data loads. Lesson learned: Scalability isn't optional.

Second Build (Weeks 9-14)
Switched to microservices with Node.js. Improved performance but introduced deployment complexity. Discovered the harsh reality of distributed system debugging at 3 AM.

Third Build (Weeks 15-22)
Adopted containerization. Solved deployment issues but uncovered new latency problems. This iteration taught me observability principles through painful trial-and-error.

Fourth Build (Weeks 23-30)
The final architecture: Rust-based core services with JavaScript frontend. Combined performance with maintainability. Each rebuild taught me to value simplicity over cleverness.

The Turning Point

Management noticed my daytime fatigue. When they discovered I'd been coding during breaks (against company policy), termination followed. While devastating financially, this became my catalyst. The sudden availability of daytime hours accelerated development exponentially.

Within six weeks of getting fired:

• Completed the MVP
• Onboarded three beta clients
• Generated first revenue

Technical Insights

The warehouse environment directly influenced architectural decisions:

Warehouse Challenge	Software Solution
Physical space constraints	Memory-efficient algorithms
Time-sensitive shipments	Real-time processing queues
Fragile item handling	Error recovery systems

These parallels demonstrate how non-technical environments can inspire robust technical design.

Outcome

The software now helps 87 small businesses manage inventory with 98.7% forecast accuracy. More importantly, this journey proved that transformative work can emerge from unlikely circumstances—provided you're willing to rebuild when necessary, both in code and career.

Final note: Those warehouse-taught lessons in resilience? They're more valuable than any algorithm.