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Tables and AI
Learn how to use spreadsheet tables to define, prioritize, and evaluate LLM rules and prompts, enabling stakeholders to manage AI behavior without complex code.
In his classic book Code Complete, Steve McConnell dedicates a whole chapter to Table Driven Methods. A Table Driven method is the use of lookups in lieu of complicated algorithms. It offers simplicity as an alternative to complexity; immediate modifiability over hard coding. With AI, this paradigm is more relevant than ever before and in fact essential when prioritizing the role of people in defining the rules an LLM should follow. With tables, literally worksheets, stakeholders can manage, discuss, and evaluate rules for how an AI responds and the structure of the response(think JSON data structures). For a solo developer, tables offer a cell for every thought and an opportunity for every thought to be thoroughly thought through. Technically, tables allow us to categorize, weigh, engineer prompts, and then manage the execution of individual and grouped prompts. Because LLMs are imperfect in what they return, we can use a table to compare what was produced with what was expected. A lot of value in a near forgotten paradigm, whose time has come to shine.