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# Paper: What Do AI Agents Actually Change? An Empirical Taxonomy of Mutation Patterns in Performance-Improving Pull Requests
---
type: paper
title: What Do AI Agents Actually Change? An Empirical Taxonomy of Mutation Patterns in Performance-Improving Pull Requests
authors: Illia Dovhoshliubnyi, Nima Soroush, Ashkan Sami, Alexander Brownlee
year: 2026
venue: arXiv
url: https://arxiv.org/abs/2607.05666
code_url:
source: arxiv
collected_at: 2026-07-08
published_at: 2026-07-06
updated_at: 2026-07-06
status: queued
relevance: high
topics:
- coding-agent
methods:
-
benchmarks:
-
models:
-
datasets:
- cs.SE
- cs.AI
related_concepts:
-
related_jobs:
-
related_experiments:
-
related_projects:
-
collection_score: 13
collection_queries: ai-agent, coding-agent
---
## One-line Takeaway
Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
## Why Collected
- matched queries: ai-agent, coding-agent
- inferred topics: coding-agent
- arXiv categories: cs.SE, cs.AI
- collection score: 13
## Review Checklist
- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
- Does it include a benchmark, dataset, code, or reproducible experimental setup?
- Should it be promoted from `queued` to `skimmed` or `summarized`?
## Links
- arXiv: https://arxiv.org/abs/2607.05666