July 7, 2025
Volume 23, issue 3
Unleashing the Power
of End-User Programmable AI
Creating an AI-first program Synthesis framework
Erik Meijer
As a demonstration of what can be accomplished with contemporary LLMs (large language models), this paper outlines the high-level design of an AI-first, program-synthesis framework built around a new programming language, Universalis, designed for knowledge workers to read, optimized for our neural computer (Automind; queue.acm.org) to execute, and ready to be analyzed and manipulated by an accompanying set of tools. We call the language Universalis in honor of Gottfried Wilhelm Leibniz, a 17th century German polymath who had an amazing vision long before our time. Leibniz's centuries-old program of a universal science (scientia universalis; wikipedia.org) for coordinating all human knowledge into a systematic whole comprises two parts: (1) a universal notation (characteristica universalis; oxfordreference.com) by use of which any item of information whatsoever can be recorded naturally and systematically, and (2) a means of manipulating the knowledge thus recorded in a computational fashion, to reveal its logical interrelations and consequences (calculus ratiocinator; wikipedia.org). Exactly what current day LLMs provide!
This may sound a bit abstract and academic, but it is extremely concrete and practical. Here is an example of a question that can be asked in natural language (the what):
Question
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