In the video below, I explain how I replaced the handheld trigger that originally came with my propeller with a phone-based controller.
There were two main reasons for making this change. First, I needed the ability to lock the propeller at a specific speed. Second, I wanted full directional control, both forward and reverse.
While the original trigger does support reverse movement, it places the neutral position in the middle of its range. This means I would have to constantly hold the trigger at the midpoint just to keep the propeller stationary. That setup is typically designed for applications like drones or skateboard motors, where continuous bidirectional control is required, but it wasn’t ideal for my use case.
Key Takeaways
1. Development Time
From start to finish, the project took about six hours. I used AI assistance throughout, which helped with troubleshooting bugs, finding drivers and formats from manufacturer sites, and making rapid adjustments to the workflow.
2. Traditional Effort Comparison
Without AI, this same project would likely have taken week, possibly even months, to complete.
3. Iterative Process
I went through multiple iterations, switching between UART and PPM, analyzing data between the VX3 receiver and the controller, and eventually settling on replicating the VX3 signal.
4. Productivity Gains
This experience suggests a potential 10–30× improvement in individual productivity when using AI assist effectively, compressing months of work into just a few hours.
5. Enterprise Perspective
However, research indicates that at the enterprise level, productivity gains are typically more modest, around 2–5× when implemented effectively. If implemented poorly, AI can actually introduce bottlenecks and slow processes down rather than improve them.