AI-driven workflow for rapidly generating custom operating systems
This technology is a method for rapidly generating a custom operating system using a structured AI-driven workflow.
Unmet Need: Generating a custom operating system using AI
Custom operating systems are essential for a wide range of applications, including embedded devices, IoT platforms, and specialized hardware. However, developing these complex software systems is often slow, resource-intensive, and difficult to automate. While current AI-enabled coding assistants accelerate human task completion, they are limited to smaller, isolated tasks like function completion, and struggle with the scale and contextual demands of building an entire software system from the ground up.
The Technology: AI-driven workflow for rapidly generating custom operating systems
This technology describes a method called “Task Prompting,” which enables a human developer to effectively collaborate with a large language model (LLM) to generate a complete and functional operating system (OS) kernel. These prompts iteratively guide the LLM in creating all necessary C++ and assembly code for OS functionality on new hardware. This technology supports multi-process user application, virtual memory, systems calls, networking, and persistent storage.
This technology was successfully used to generate a high-performance OS kernel that can run on unmodified Linux applications with performance comparable to native Linux.
Applications:
- Rapid prototyping for IoT devices, robotics, and custom computer hardware
- Creation of custom operating systems for embedded systems
- AI-powered developer tools
- AI-tools for advanced educational platforms
- Enterprise software
- Computer engineering research model development
Advantages:
- Rapid generation of working OS kernel
- Iterative process for creating, refining, and debugging codebase with large language models (LLMs)
- Supports multi-process user applications, virtual memory, system calls, networking, and persistent storage
- Utilizes structured methodology for human-AI interactions
Lead Inventor:
Patent Information:
Patent Pending
Related Publications:
Tech Ventures Reference:
IR CU25381
Licensing Contact: Greg Maskel