This research investigates how programmers interact with conversational AI coding assistants and identifies key factors influencing their adoption in software development workflows.

• Examines real-world usage patterns and interaction strategies with LLM-based coding tools
• Reveals both benefits (efficiency improvements) and challenges programmers encounter
• Identifies expectations and perceptions that shape adoption of AI coding assistants
• Provides insights for improving LLM tools for software engineering applications

For engineering teams, this research offers valuable understanding of how to effectively integrate AI coding assistants into development processes while addressing user expectations.

Original Paper: Conversational AI as a Coding Assistant: Understanding Programmers' Interactions with and Expectations from Large Language Models for Coding