Architectural informatics self-hackathon workshop — Reassessing professional essence through generic and generative artificial intelligence

Abstract

This paper presents a novel self-hackathon workshop methodology integrating Large Language Models (LLM) and Generative AI (GenAI) into architectural education. The study addresses the critical shortage of digital talent in the Architecture, Engineering, and Construction (AEC) industry by developing a time-efficient framework that enables participants to engage with multiple emerging technologies while maintaining focus on core architectural competencies. The workshop methodology, successfully implemented in two distinct settings, demonstrates its effectiveness in facilitating rapid technological adaptation within a condensed 1.5-h timeframe using standard equipment. Results indicate high participant satisfaction and successful integration of physical computing, AI-driven dialogue, and virtual-physical space transformation. The framework catalyzes meaningful dialogue between human creativity and artificial intelligence in spatial design while providing valuable insights into redefining professional competencies in an AI-augmented future. This research contributes to architectural education by offering a flexible, scalable methodology that bridges the digital skills gap while emphasizing essential human capabilities that complement AI technologies.