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From Tool Calling to Symbolic Thinking: LLMs in a Persistent Lisp Metaprogramming Loop

Published: June 8, 2025 | arXiv ID: 2506.10021v1

By: Jordi de la Torre

Potential Business Impact:

AI learns to build and use its own tools.

Business Areas:
Natural Language Processing Artificial Intelligence, Data and Analytics, Software

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.

Page Count
8 pages

Category
Computer Science:
Programming Languages