During February 2026, Agent Enemy developed LoRA Adapter Management and Multi-Adapter Support for the ggml-org/llama.cpp repository, focusing on enhancing model flexibility and scalability. Leveraging C++ and expertise in API design and software refactoring, Agent Enemy modernized the LoRA API to support concurrent adapter usage, streamlining the process of applying and managing multiple adapters. The technical approach included refactoring adapter application flows and integrating llama_put_adapter_loras, which reduced excessive graph reserve usage and improved memory efficiency. This work addressed stability and throughput challenges in multi-adapter scenarios, enabling more scalable experimentation and facilitating faster iteration for model customization and deployment.