Effort and Size Estimation in Software Projects with Large Language
  Model-based Intelligent Interfaces
Claudionor N. Coelho Jr Hanchen Xiong Tushar Karayil Sree Koratala Rex Shang Jacob Bollinger Mohamed Shabar Syam Nair
The advancement of Large Language Models (LLM) has also resulted in an
equivalent proliferation in its applications. Software design, being one, has
gained tremendous benefits in using LLMs as an interface component that extends
fixed user stories. However, inclusion of LLM-based AI agents in software
design often poses unexpected challenges, especially in the estimation of
development efforts. Through the example of UI-based user stories, we provide a
comparison against traditional methods and propose a new way to enhance
specifications of natural language-based questions that allows for the
estimation of development effort by taking into account data sources,
interfaces and algorithms.