Customizations Implemented in VESC Through Vibe Coding
David Bloomfield, a technology enthusiast, sought to enhance an embedded system, specifically the VESC Telemetry Display created by Lukas Janky. With limited coding experience, especially for embedded systems like the Arduino Nano, he opted to explore a novel approach: vibe coding. He utilised Gemini 2.5 Pro to modify the display, aiming to introduce more colors, alter the data format, and tweak the EEPROM saving process.
The stakes were higher than usual, as changes to embedded systems could have tangible real-world consequences. Additionally, relying on an AI model to generate the code without fully understanding it presents obvious risks. It's essential to exercise caution when working with embedded systems.
Vibe coding has garnered attention, with Jenny List previously delving into its emergence as a contentious coding phenomenon. Expect discussions about its merits and challenges to persist.
When using AI for coding embedded systems, potential risks arise. For instance, AI-generated code might be incorrect, leading to hardware malfunctions or damage. Relying too heavily on AI could also erode a developer's deep understanding of the system, affecting long-term maintainability. Furthermore, AI-generated code could contain hidden vulnerabilities, such as malicious code or backdoors, from complex supply chains.
Despite these challenges, careful validation, security awareness, and expert oversight can mitigate these issues. It's crucial to review and test the AI-generated code extensively, use trusted AI tools and models, maintain developer expertise, implement security best practices, and monitor AI model integrity.
As David Bloomfield demonstrated, AI tools can accelerate development and modification of embedded systems like the VESC Telemetry Display for Arduino Nano. However, it remains essential to strike a balance between leveraging AI's benefits and minimizing associated risks to ensure the safe, secure, and reliable operation of these systems.
Data-and-cloud computing could potentially be integrated with the enhanced VESC Telemetry Display, given the Arduino Nano's capabilities. This integration might allow for real-time data monitoring and analysis, along with potential Artificial-Intelligence applications.
However, it's crucial to approach the integration of AI in embedded systems like the Arduino Nano with caution. While AI may speed up development and modification, it's essential to ensure the integrity of the AI-generated code to prevent hardware malfunctions, maintain system transparency, and safeguard against hidden vulnerabilities.
