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Custom vs. General LLM Agent Harnesses for Automotive Testing

By PulseAugur Editorial · [1 sources] ·

A new paper from arXiv explores the trade-offs between developing custom LLM agent harnesses and adopting general-purpose ones, using automotive GUI testing at Volvo Group as a case study. The research found that while general-purpose harnesses like Claude Code and OpenCode incurred higher inference costs, they significantly reduced engineering effort, leading to lower overall monthly costs for nightly regression suites. These external tools also demonstrated better success rates on open-ended tasks and improved recovery from errors, though they offered less control over model inputs compared to in-house solutions. AI

IMPACT This research provides insights for organizations deciding between building custom LLM agent solutions or adopting existing ones, impacting development strategies and cost-efficiency in AI applications.

RANK_REASON Research paper published on arXiv discussing LLM agent harnesses. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Custom vs. General LLM Agent Harnesses for Automotive Testing

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Research paper published on arXiv discussing LLM agent harnesses. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Arsham Gholamzadeh Khoee, Ruyu Fu, Jiaqi Wei, Ruikun Deng, Robert Feldt, Dhasarathy Parthasarathy, Yinan Yu ·

    Build or Adopt? Custom-Built vs. General-Purpose LLM Agent Harnesses for Automotive GUI Testing

    arXiv:2610.33636v1 Announce Type: cross Abstract: As general-purpose LLM agent harnesses mature, organizations must decide whether to continue developing in-house systems or adopt existing alternatives. We study this decision at Volvo Group for GUI testing of Android-based in-veh…

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