Collaborator or Assistnat? How AI Coding Agents Partition Work Across Pull Request Lifecycles

2026-05-08

AI Summary

This study addresses the ambiguity in responsibility and agency between AI coding agents and human developers during pull request (PR) lifecycles, where proactive AI actions intersect with human-led merge governance. The authors propose an “Initiator × Approver” taxonomy and construct a collaboration–assistance spectrum alongside state-machine models of various tools. Through systematic log analysis of 29,585 PRs, they disentangle the distinct roles of AI and humans in the PR workflow. Their findings reveal that over 96% of PRs in collaborative tools are initiated by AI, yet merge decisions remain almost exclusively under human control. While automated merges record execution behavior, they do not engage with core governance functions. This work thus provides the first clear delineation of operational boundaries and governance demarcation for AI coding agents.

Abstract

When AI coding agents open branches and submit pull requests (PRs), two questions co-determine oversight design: who starts the work (operational agency) and who authorizes its completion (merge governance). We characterize tools along a Collaborator-Assistant spectrum in how they redistribute initiative, oversight, and endorsement, while merge governance remains predominantly human across five tools (OpenAI, Copilot, Devin, Cursor, Claude Code). We analyze 29,585 PR lifecycles using an Initiator x Approver taxonomy with six interaction scenarios; lifecycle reconstruction supplies the how behind those roles. Collaborator tools (Cursor, Devin, Copilot) concentrate operational initiative in agents that open and carry PR work forward, with humans retaining review and endorsement on the path to merge; Assistant tools (OpenAI, Claude) leave task direction primarily with humans and supply bounded support within human-led workflows. Across the spectrum, agency and governance decouple: Collaborator workflows are >=96% agent initiated, yet terminal merge authority remains almost exclusively human, with agent-classified approvers confined to a small fraction of PRs. Where automation executes a merge, logs record the executor but not the decision-maker, marking a boundary of observation. We contribute the taxonomy, per-tool state machines, and a replication package for research on automation, oversight, and governance in PR workflows.

Problem

• AI coding agents
• pull request lifecycle
• operational agency
• merge governance
• Collaborator-Assistant spectrum

Innovation

• AI coding agents
• pull request lifecycle
• operational agency
• merge governance
• human-AI collaboration