We propose a novel architecture for integrating large language models (LLMs) with a persistent, interactive Lisp environment. This setup enables LLMs to define, invoke, and evolve their own tools through programmatic interaction with a live REPL. By embedding Lisp expressions within generation and intercepting them via a middleware layer, the system allows for stateful external memory, reflective programming, and dynamic tool creation. We present a design framework and architectural principles to guide future implementations of interactive AI systems that integrate symbolic programming with neural language generation.
@article{arxiv.2506.10021,
title = {From Tool Calling to Symbolic Thinking: LLMs in a Persistent Lisp Metaprogramming Loop},
author = {Jordi de la Torre},
journal= {arXiv preprint arXiv:2506.10021},
year = {2025}
}