We aim to reframe how developers create LLM applications. Instead of iterating on verbose, complex prompts to achieve a desired complex behavior, we break down complex tasks into a series of standard computing elements that can be called by a developer in programmatic way. In this demonstration we will explore how leveraging a LLM trained with key intrinsic functions such as hallucination detection, uncertainty quantification, and topic scoping, could unlock a new way of building and working with LLMs.