mlsanityData to 14 Oct 2026

Can Coding Agents Be General Agents?

arXiv 2604.13107 ↗First posted 10 Apr 2026cs.SE cs.AI cs.LGcited by 2

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

Abstract (arXiv)

As coding agents have seen rapid capability and adoption gains, users are applying them to general tasks beyond software engineering. In this post, we investigate whether coding agents can successfully generalize to end-to-end business process automation. We identify gaps in current evaluations, and conduct a case study to evaluate a coding agent on practical business tasks in an open-core Enterprise Resource Planning system. We find that the agent reliably completes simple tasks but exhibits characteristic failures on complex tasks, suggesting that bridging domain logic and code execution is a key bottleneck to generalizability.

Key facts. Cited by 2 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 15 references that are in the map. First posted on arXiv 10 Apr 2026.

Builds on

8 of 15 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024Executable Code Actions Elicit Better LLM Agents1 Feb

Other references · 7

  1. 2021Evaluating Large Language Models Trained on Codecited by 8,320
  2. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
  3. 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?cited by 3,373
  4. 2024τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domainscited by 1,402
  5. 2021Unified Pre-training for Program Understanding and Generationcited by 366
  6. 2024Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Modelscited by 178
  7. 2024To Code, or Not To Code? Exploring Impact of Code in Pre-trainingcited by 47

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026SCATE: Learning to Supervise Coding Agents for Cost-Effective Test Generationcited by 1
  2. 2026Applying Anthropic Primitives at Large Enterprises: Harness Paradigm for Knowledge Workcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Beyond Generalist LLMs: Specialist Agentic Systems for Structured Code Workflow Execution
  2. 2026Terminal Agents Suffice for Enterprise Automation
  3. 2025A Comprehensive Empirical Evaluation of Agent Frameworks on Code-centric Software Engineering Tasks
  4. 2026AgentSWE: Can Coding Agents Build the Agent You Actually Want?
  5. 2026A Phased Workflow for Operating LLM-Based Coding Agents
  6. 2025Code with Me or for Me? How Increasing AI Automation Transforms Developer Workflows
  7. 2026General Agent Evaluation
  8. 2026Understanding the Architecture of Coding Agents: An Exploratory Study Using a Research Prototype