# AI Agent Pull Requests on GitHub: Frequency, Structure, and Merge Conflict Rates

arXiv: https://arxiv.org/abs/2607.04697 · HTML: https://mlsanity.com/paper/2607.04697/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use.
- Builds on 8 of its 13 references that are in the map.
- First posted on arXiv 6 Jul 2026.

## Placed in

- LLM agents and tool use / [Software engineering coding agents](https://mlsanity.com/agents/software-engineering-coding-agents/)

## Builds on (most cited first, 8 of 8)

- [AIDev: Studying AI Coding Agents on GitHub](https://mlsanity.com/paper/2602.09185/) (2026)
- [The Rise of AI Teammates in Software Engineering (SE) 3.0: How Autonomous Coding Agents Are Reshaping Software Engineering](https://mlsanity.com/paper/2507.15003/) (2025)
- [How AI Coding Agents Modify Code: A Large-Scale Study of GitHub Pull Requests](https://mlsanity.com/paper/2601.17581/) (2026)
- [Security in the Age of AI Teammates: An Empirical Study of Agentic Pull Requests on GitHub](https://mlsanity.com/paper/2601.00477/) (2026)
- [AgenticFlict: A Large-Scale Dataset of Merge Conflicts in AI Coding Agent Pull Requests on GitHub](https://mlsanity.com/paper/2604.03551/) (2026)
- [Analyzing Message-Code Inconsistency in AI Coding Agent-Authored Pull Requests](https://mlsanity.com/paper/2601.04886/) (2026)
- [Detecting Semantic Conflicts using Static Analysis](https://mlsanity.com/paper/2310.04269/) (2023)
- [Understanding the Rejection of Fixes Generated by Agentic Pull Requests -- Insights from the AIDev Dataset](https://mlsanity.com/paper/2606.13468/) (2026)

## Built on by (most cited first, 1 of 1)

- [Covert Assistance: Helpful LLM Agents Evade Oversight in Multi-Agent Systems](https://mlsanity.com/paper/2609.39050/) (2026)

## Abstract (arXiv)

AI coding agents may generate and submit Pull Requests (PRs) to the same repository at the same time. However, research concerning the extent of concurrent submission by AI coding agents to a common repository does not exist. This paper uses the AIDev-pop dataset (33,596 PRs in 2,807 repositories) to provide the first empirical examination of the prevalence of concurrent submission using PRs authored by agents. We report that when considering exact temporal overlap, 40.2% of repositories contain co-active agent-authored PR pairs; further, the co-active pairs account for 79.4% of all PRs generated by an AI agent. When we examine co-activity within a one week collaboration window, the percentages are increased to 53.4% and 95.0%, respectively. For the majority of the co-active PR pairs (underlying the vast majority of which are intra-agent authored), both PRs were authored by the same agent, while only 0.5% of co-active pairs were cross-agent, and occurred in only 122 out of 2807 total repositories examined (or approximately 4.3%). Additionally, we replayed actual three way git merges on 747 unique co-active pairs (one per repository), and computed the percentage of textual conflict encountered during the merge operation to combine the two PRs in each pair. We observed that the percentage of textual conflict encountered was significantly higher for cross-agent pairs compared to intra-agent pairs: 41.7% vs. 19.8%, respectively, with non-overlapping 95% confidence intervals. Lastly, we developed a classification system based on the detection of conflict reported by git, and determined that the majority of conflicts resulted from modifications to source code files (84.4% of conflicted files) and not dependency manifest files; further, nearly 42% of conflicts we observed were structural (i.e., modify/delete or add/add).