With the rapid expansion of IoT technologies, edge computing has become essential for processing data closer to the source, reducing latency, and improving efficiency. However, developing and maintaining code, including requirements and testing, for diverse IoT devices can be time-consuming and complex. This thesis explores AI-driven techniques for automating code generation in edge computing applications, focusing on requirements definition, code creation, and automated testing. The principal contribution of this work is the design and implementation of a multi-agent chat system using Microsoft’s AutoGen-AgentChat framework. This system allows collaborative interactions between different AI agents, where each agent is responsible for a specific assignment in the software development pipeline, such as requirements interpretation, project organization, code generation, testing, and fixing code.