This episode covers PDL (Prompt Declaration Language), a new language designed for working with large language models (LLMs). Unlike complex prompting frameworks, PDL provides a simple, YAML-based, declarative approach to crafting prompts, reducing errors and enhancing control.

Key features include:

• Versatility: Supports chatbots, retrieval-augmented generation (RAG), and agents for goal-driven AI.

• Code as Data: Allows for program optimizations and enables LLMs to generate PDL code, as shown in a case study on solving GSMHard math problems.

• Developer-Friendly Tools: Includes an interpreter, IDE support, Jupyter integration, and a live visualizer for easier programming.

The episode concludes with a look at PDL’s future impact on speed, accuracy, and the evolving landscape of LLM programming.

https://arxiv.org/pdf/2410.19135