Beyond Code Generation: AI Across the Product Development Lifecycle
TL;DR
It is suggested that AI can support the entire product development lifecycle, helping lean startup teams work more efficiently while leaving key decisions and expert judgment to people.
Abstract
Artificial intelligence (AI) is becoming an important part of modern product development. However, most existing studies focus on software development or individual AI applications rather than the entire product lifecycle. This study explores how AI can support different stages of product development in a lean technology startup. A comparative case study was conducted using two similar product development projects completed by the same company. The projects had similar functionality, target market, technology stack, and development process, but differed in the level of AI adoption. The study combined quantitative analysis of labor effort with qualitative observations of how AI tools were used throughout the product lifecycle. The results show that AI supported activities from market research and hypothesis validation to software development, testing, release preparation, and post-release product improvement. The greatest benefits were observed in research, requirements preparation, documentation, and design, while software development and testing also became more efficient. Overall labor effort was reduced by 35.8% in the AI-assisted project. The findings suggest that AI can support the entire product development lifecycle, helping lean startup teams work more efficiently while leaving key decisions and expert judgment to people.