On the Prospects of Dynamic LLM Conversations in Software Development

arXiv:2608.30756 · cs.SE, cs.AI · Submitted 2026-08-31 · Read on arXiv

cs.SE, cs.AI

Submitted: 2026-08-31

Updated: 2026-08-31

Terminology

• Frustration — 15× in this paper · explained in 2 episodes
• Alignment — 7× in this paper · explained in 1 episode
• Prompt Engineering — 4× in this paper · explained in 4 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Agent-Based Simulation — 1× in this paper · explained in 1 episode
• Generalizability — 1× in this paper · explained in 6 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Scaffolding — 1× in this paper · explained in 3 episodes

Sources

• Elicitron: An LLM Agent-Based Simulation Framework for Design Requirements Elicitation
• Understanding the Role of Large Language Models in Personalizing and Scaffolding Strategies to Combat Academic Procrastination
• The Impact of AI Tool on Engineering at ANZ Bank An Empirical Study on GitHub Copilot within Corporate Environment
• How Far Are We? The Triumphs and Trials of Generative AI in Learning Software Engineering
• Beyond Code Generation: An Observational Study of ChatGPT Usage in Software Engineering Practice
• Navigating the Complexity of Generative AI Adoption in Software Engineering
• Prompt Engineering or Fine-Tuning: An Empirical Assessment of LLMs for Code
• Developers' Perceptions on the Impact of ChatGPT in Software Development: A Survey
• Rocks Coding, Not Development--A Human-Centric, Experimental Evaluation of LLM-Supported SE Tasks
• Productivity Assessment of Neural Code Completion

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