A collection of useful insights (with hope).
Interdisciplinary perspectives on Generative AI from Wittgenstein, Lewis, Dennett, and Nagel.
đź“„ Download Paper (PDF)
A structured prompting model rooted in philosophy, cognitive science, and interdisciplinary design.
The CONTEXT Prompt Framework supports clarity, ethical alignment, and iterative refinement in human-AI interaction.
Grounded in best practices from design, education, governance, and communication, it helps users structure prompts for
high-quality, purpose-aligned AI outputs.
Unlike ad hoc prompting, CONTEXT now has empirical support: in a recent benchmark comparing CONTEXT to structured prompting
heuristics from OpenAI and Anthropic (HHH), CONTEXT outperformed both across three real-world tasks—in UX design, education,
and risk governance. It produced more complete, clearer, and board-ready outputs with fewer revisions required.
Whether you’re building chatbots, teaching AI literacy, or managing compliance-sensitive AI use, CONTEXT offers a practical,
tested structure for prompt design that reduces iteration and increases output quality.
This is a personal diversion. If you want to know more about my professional role, find me on LinkedIn.