The transition from printed format user guides to GPS-style step-by-step instructions is just beginning.
There's a major opportunity to apply AI tools to the long-neglected problem of product documentation.
Users want clear, step-by-step instructions tailored to their specific task, similar to GPS navigation.
Existing product manuals often lack connection to an underlying map, resulting in AI-generated content not being based on actual data.
A proposal for a dynamic system involving computer vision, LLMs, CCMS, and a knowledge graph is made to improve product documentation.
Product manuals stored as static PDFs need to be transformed into structured, searchable content for better user experience.
The development of a knowledge graph is suggested to organize product data and enable on-demand, tailored instructions.
The knowledge graph acts as a map, allowing tools like RAG and pathfinding algorithms to generate step-by-step instructions for any valid route.
The system aims at replacing static manuals with a dynamic, living system aligned with how users search, learn, and solve problems.
Adoption of AI tools like ChatGPT highlights the readiness of users to seek instructions from AI, emphasizing the need for accurate, high-quality data.