Iterative Proof-Driven Development LLM Prompt

This paper introduces Iterative Proof-Driven Development, a novel prompt engineering method designed to take advantage of GPT-4 level models that are able to follow detailed instructions. Iterative Proof-Driven Development is a structured prompt that outlines a test-driven process for solving complex mathematics and programming tasks. The prompt provides an LLM with instructions to decompose a problem into sub-problems, generate test cases, verify results, and integrate sub-solutions. While Chain of Thought (CoT) reasoning remains central to individual steps, the structured process ensures consistency and reliability. This method takes advantage of embedded code interpreters within chatbot user interfaces, enabling immediate execution, debugging, and iterative refinement without external tools. We demonstrate this prompting technique by guiding an LLM through the development of a small CSV processing library, illustrating each step and highlighting how the method ensures well-tested, logically consistent, and reliable outputs. Finally, we explore potential use cases, future directions for automation with agent-based systems (e.g., Langgraph), and the broader implications of prompt engineering for larger software development projects.