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The generative AI industry suffers from an overlooked but critical obstacle: engineering bias. Rather than adapting AI tools to match how most people naturally learn—through conversation, intuition, and incremental guidance—the industry overwhelmingly pressures mainstream users to think and behave like engineers. Certification programs, corporate training, and AI tutorials

Introduction Over the past five years, prompt engineering became nearly synonymous with effectively interacting with AI systems. Driven by necessity, early large language models (LLMs) such as GPT-2 and GPT-3 required carefully structured prompts to produce reliable outputs. Engineers and early adopters developed a quasi-formal discipline of prompt engineering, akin

Executive Summary Generative AI holds transformative potential—but its promise remains locked behind an invisible wall: engineering bias. By prioritizing complex prompt engineering over intuitive, human-centered design, current AI systems are alienating mainstream users and hindering mass adoption. Across industries, a growing body of evidence reveals deep frustration with prompt-driven

Preferred AI Communication Styles by Gender Research shows clear gender-based differences in how adult professionals prefer to interact with AI. Women tend to adopt a more conversational and cautious style, while men often take a direct, “tool-like” approach. For example, a Pew survey on voice assistants found 62% of women