mlsanityData to 7 Oct 2026

Human oversight of agentic systems in practice: Examining the oversight work, challenges, and heuristics of developers using software agents

arXiv 2606.05391 ↗First posted 3 Jun 2026cs.SE cs.AIcited by 6

On the map: LLM agents and tool use → Software engineering coding agents

Abstract (arXiv)

Autonomous software agents hold promise to increase developer productivity but make mistakes and exhibit novel failure modes, making human oversight central to successful human-agent collaboration. Existing research on agent oversight is largely conceptual; normative frameworks exist, but how users actually oversee agents is less known. In this paper, we bridge this gap by providing early empirical anchors for the theoretical discourse on agent oversight. Drawing on interviews with 17 experienced developers, we conduct an exploratory inquiry examining what forms of emergent oversight work developers perform, when, and how. We also document the oversight challenges developers face and the strategies they have started using to address them. We found at least four forms of emergent oversight work: a priori control, co-planning, real-time monitoring, and post hoc review. We show that oversight work is not only reactive and retrospective, as portrayed in existing research, but also preventative and proactive. We describe situated oversight challenges (e.g., difficulty reviewing agent-generated code) and outline heuristics developers adopt to address such challenges (e.g., using test results as guarantees for code correctness). We conclude with high-level takeaways, future research directions, implications for the human-centered design of software agents and for software engineering practice, and limitations of our research.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 88 of its 161 references that are in the map. First posted on arXiv 3 Jun 2026.

Builds on

88 of 161 references.

Closest ancestors · 14

Same direction, newest first

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  6. 2025Why AI Agents Still Need You: Findings from Developer-Agent Collaborations in the Wild14 Jun
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  8. 2025Beyond Final Code: A Process-Oriented Error Analysis of Software Development Agents in Real-World GitHub Scenarios16 Mar
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  10. 2024Agents in Software Engineering: Survey, Landscape, and Vision13 Sep
  11. 2024SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering6 May
  12. 2024RepairAgent: An Autonomous, LLM-Based Agent for Program Repair25 Mar
2 more
  1. 2024Executable Code Actions Elicit Better LLM Agents1 Feb
  2. 2024CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges14 Jan

Other references · 74

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  7. 2024Agent-as-a-Judge: Evaluate Agents with Agentscited by 223
  8. 2020Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthycited by 182
  9. 2024The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Surveycited by 164
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  11. 2023Harms from Increasingly Agentic Algorithmic Systemscited by 134
  12. 2024Black-Box Access is Insufficient for Rigorous AI Auditscited by 123
  13. 2021To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-makingcited by 118
  14. 2025Large Language Models Often Know When They Are Being Evaluatedcited by 105
  15. 2018Mapping Language to Code in Programmatic Contextcited by 104
  16. 2024MARG: Multi-Agent Review Generation for Scientific Paperscited by 98
  17. 2025Establishing Best Practices for Building Rigorous Agentic Benchmarkscited by 94
  18. 2024RedCode: Risky Code Execution and Generation Benchmark for Code Agentscited by 87
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  20. 2023Appropriate Reliance on AI Advice: Conceptualization and the Effect of Explanationscited by 80
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  22. 2024CRMArena: Understanding the Capacity of LLM Agents to Perform Professional CRM Tasks in Realistic Environmentscited by 69
  23. 2024"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trustcited by 67
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  25. 2024Spider2-V: How Far Are Multimodal Agents From Automating Data Science and Engineering Workflows?cited by 55
  26. 2023CodeLMSec Benchmark: Systematically Evaluating and Finding Security Vulnerabilities in Black-Box Code Language Modelscited by 52
  27. 2024(Perhaps) Beyond Human Translation: Harnessing Multi-Agent Collaboration for Translating Ultra-Long Literary Textscited by 49
  28. 2025Are "Solved Issues" in SWE-bench Really Solved Correctly? An Empirical Studycited by 47
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  30. 2021The Flaws of Policies Requiring Human Oversight of Government Algorithmscited by 44
  31. 2024WaitGPT: Monitoring and Steering Conversational LLM Agent in Data Analysis with On-the-Fly Code Visualizationcited by 38
  32. 2024Automatic Programming: Large Language Models and Beyondcited by 35
  33. 2024Towards Translating Real-World Code with LLMs: A Study of Translating to Rustcited by 35
  34. 2023Investigating and Designing for Trust in AI-powered Code Generation Toolscited by 34
  35. 2022Sensible AI: Re-imagining Interpretability and Explainability using Sensemaking Theorycited by 32
  36. 2024CodeHalu: Investigating Code Hallucinations in LLMs via Execution-based Verificationcited by 32
  37. 2023Unveiling Memorization in Code Modelscited by 29
  38. 2024On the Quest for Effectiveness in Human Oversight: Interdisciplinary Perspectivescited by 28

50 most cited of 74 All 74 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 6.

6 papers.

Similar, not cited

Close in wording, no citation either way

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  5. 2026Are We All Using Agents the Same Way? An Empirical Study of Core and Peripheral Developers Use of Coding Agents
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  7. 2026The Work Behind Delegation: A Framework for Supervising AI Coding Agents
  8. 2026Steerability via constraints: a substrate for scalable oversight of coding agents