This paper describes our initial efforts at implementing a new Choice-Adaptive Intelligent Learning Environment (CAILE) that combines multi-agent adaptive technologies and service architectures to provide a framework for designing extendible and reconfigurable learning environments. We describe the core components of the CAILE architecture, learning tasks that establish a situated context for learning, and a set of customizable agents that support student learning. We employ software engineering metrics to evaluate the system, and illustrate the reconfigurable and extensible properties of our design and implementation.