# From Assistance to Agency: Rethinking Autonomy and Control in CI/CD Pipelines

arXiv: https://arxiv.org/abs/2605.07062 · HTML: https://mlsanity.com/paper/2605.07062/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use.
- Builds on 14 of its 38 references that are in the map.
- First posted on arXiv 8 May 2026.

## Placed in

- LLM agents and tool use / [Agent threats, guardrails and governance](https://mlsanity.com/agents/agent-threats-guardrails-and-governance/)

## Builds on (most cited first, 14 of 14)

- [Large Language Models for Software Engineering: A Systematic Literature Review](https://mlsanity.com/paper/2308.10620/) (2023)
- [RepairAgent: An Autonomous, LLM-Based Agent for Program Repair](https://mlsanity.com/paper/2403.17134/) (2024)
- [Large Language Model-Based Agents for Software Engineering: A Survey](https://mlsanity.com/paper/2409.02977/) (2024)
- [Keep the Conversation Going: Fixing 162 out of 337 bugs for 0.42 each using ChatGPT](https://mlsanity.com/paper/2304.00385/) (2023)
- [Agents in Software Engineering: Survey, Landscape, and Vision](https://mlsanity.com/paper/2409.09030/) (2024)
- [You Name It, I Run It: An LLM Agent to Execute Tests of Arbitrary Projects](https://mlsanity.com/paper/2412.10133/) (2024)
- [Continuous Integration, Delivery and Deployment: A Systematic Review on Approaches, Tools, Challenges and Practices](https://mlsanity.com/paper/1703.07019/) (2017)
- [AIDev: Studying AI Coding Agents on GitHub](https://mlsanity.com/paper/2602.09185/) (2026)
- [How to Design a Program Repair Bot? Insights from the Repairnator Project](https://mlsanity.com/paper/1811.09852/) (2018)
- [LogSage: An LLM-Based Framework for CI/CD Failure Detection and Remediation with Industrial Validation](https://mlsanity.com/paper/2506.03691/) (2025)
- [Repairnator patches programs automatically](https://mlsanity.com/paper/1910.06247/) (2019)
- [Understanding the Challenges and Opportunities of Generative AI Apps: An Empirical Study](https://mlsanity.com/paper/2506.16453/) (2025)
- [When AI Agents Touch CI/CD Configurations: Frequency and Success](https://mlsanity.com/paper/2601.17413/) (2026)
- [AutoGuard: A Self-Healing Proactive Security Layer for DevSecOps Pipelines Using Reinforcement Learning](https://mlsanity.com/paper/2512.04368/) (2025)

## Abstract (arXiv)

AI agents are assuming active roles in Continuous Integration and Continuous Deployment (CI/CD) workflows, yet the research community lacks a shared vocabulary for describing what it means for CI/CD to be agentic, how much decision authority is delegated, and where control should reside. This paper presents a vision of agentic CI/CD in which the central challenge is not improving task performance but designing authority transfer, defined as the delegation of operational decisions from human-controlled pipelines to agent systems under specified constraints and recourse mechanisms. To structure this argument, we introduce a distinction between data-plane authority (localized interventions such as patch generation and test reruns) and control-plane authority (modifications to pipeline configuration, deployment policies, and approval gates). Drawing on research prototypes and industrial platforms, we show that current systems operate mainly at the data plane under bounded autonomy, with safety achieved through surrounding governance infrastructure rather than intrinsic agent guarantees. We identify three recurring patterns: constrained autonomy as the dominant design, external governance as the primary safety mechanism, and a widening gap between deployment momentum and evaluation methodology. We propose a research agenda in which control-plane safety and governance mechanisms represent the most urgent open problem, followed by formalization of autonomy boundaries, evaluation frameworks, and human--agent coordination.