The rise of Software defined network-based containerized applications has driven the need for efficient resource management and network optimization, especially in constrained environments for Raspberry Pi. This paper highlights the AI driven approach in optimizing Raspberry Pi-based container setups using Strongly typed genetic programming (STGP). This generative AI driven approach is followed by the prompt engineering aspects for implementation of adaptive approach in SDN Network. The proposed approach improves task success rates, reduces latency, and minimizes resource contention based on real-time network metrics using CPU usage, Memory utilization and Network consumption. Experimental results demonstrate the effectiveness of STGP in maintaining optimal performance in highly dynamic network environments. The proposed model allows more precise and adaptable solutions for resource-constrained SDN environments on distributed systems of Raspberry Pi.