# In-IDE Human-AI Experience in the Era of Large Language Models; A Literature Review

arXiv: https://arxiv.org/abs/2401.10739 · HTML: https://mlsanity.com/paper/2401.10739/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jan 2024.

## Built on by (most cited first, 6 of 6)

- [Natural Language Outlines for Code: Literate Programming in the LLM Era](https://mlsanity.com/paper/2408.04820/) (2024)
- [DEMO: Reframing Dialogue Interaction with Fine-grained Element Modeling](https://mlsanity.com/paper/2412.04905/) (2024)
- [Mind the Metrics: Patterns for Telemetry-Aware In-IDE AI Application Development using the Model Context Protocol (MCP)](https://mlsanity.com/paper/2506.11019/) (2025)
- [Curiosity by Design: An LLM-based Coding Assistant Asking Clarification Questions](https://mlsanity.com/paper/2507.21285/) (2025)
- [Humans are Missing from AI Coding Agent Research](https://mlsanity.com/paper/2608.12355/) (2026)
- [Rethinking IDE Customization for Enhanced HAX: A Hyperdimensional Perspective](https://mlsanity.com/paper/2501.02491/) (2025)

## Abstract (arXiv)

Integrated Development Environments (IDEs) have become central to modern software development, especially with the integration of Artificial Intelligence (AI) to enhance programming efficiency and decision-making. The study of in-IDE Human-AI Experience is critical in understanding how these AI tools are transforming the software development process, impacting programmer productivity, and influencing code quality. We conducted a literature review to study the current state of in-IDE Human-AI Experience research, bridging a gap in understanding the nuanced interactions between programmers and AI assistants within IDEs. By analyzing 36 selected papers, our study illustrates three primary research branches: Design, Impact, and Quality of Interaction. The trends, challenges, and opportunities identified in this paper emphasize the evolving landscape of software development and inform future directions for research and development in this dynamic field. Specifically, we invite the community to investigate three aspects of these interactions: designing task-specific user interface, building trust, and improving readability.