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EngiWorld introduces a rigorous benchmark for evaluating autonomous agents in professional engineering contexts, revealing that current frontier models struggle significantly with complex geometric and physical constraints. The study highlights a critical capability gap where even the strongest models succeed in less than 4% of multi-software tasks, underscoring the distance remaining before reliable end-to-end automation is achievable in industrial design loops. This work provides an essential foundation for measuring progress in specialized AI applications beyond general-purpose computer use.
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EngiWorld: What Can Frontier Agents Deliver in Professional Engineering Environments?

arXiv2 min read

arXiv:2609.37686v1 Announce Type: cross Abstract: Autonomous agents have made rapid progress in general-purpose computer use, but reliable automation of professional industrial engineering remains out of reach, as engineering workflows demand reasoning over geometric and physical constraints and dependencies preserved across software and design stages. We present EngiWorld, the first benchmark structured around the complete design loop: 1,301 expert-curated tasks spanning 6 engineering domains (CAD, CAE, CAM, BIM, EDA, and 3D visualization) and 26 professional software platforms, with both GUI and CLI interfaces and 6 task types ranging from software-selection to open-ended tasks. We further introduce an artifact-centric evaluation methodology built on a unified domain-verifier suite, which programmatically checks the geometric validity, physical feasibility, and rule compliance of final and intermediate artifacts, and scores quantitative design tasks continuously by specification attainment rather than binary success. Evaluation of seven frontier models reveals a substantial capability gap: the strongest model achieves an EngiScore of only 44.3, and just 3.6% of multi-software attempts succeed. EngiWorld provides the first rigorous foundation for measuring progress toward agents that operate professional engineering software end to end.

Title:EngiWorld: What Can Frontier Agents Deliver in Professional Engineering Environments?

Abstract:Autonomous agents have made rapid progress in general-purpose computer use, but reliable automation of professional industrial engineering remains out of reach, as engineering workflows demand reasoning over geometric and physical constraints and dependencies preserved across software and design stages. We present EngiWorld, the first benchmark structured around the complete design loop: 1,301 expert-curated tasks spanning 6 engineering domains (CAD, CAE, CAM, BIM, EDA, and 3D visualization) and 26 professional software platforms, with both GUI and CLI interfaces and 6 task types ranging from software-selection to open-ended tasks. We further introduce an artifact-centric evaluation methodology built on a unified domain-verifier suite, which programmatically checks the geometric validity, physical feasibility, and rule compliance of final and intermediate artifacts, and scores quantitative design tasks continuously by specification attainment rather than binary success. Evaluation of seven frontier models reveals a substantial capability gap: the strongest model achieves an EngiScore of only 44.3, and just 3.6% of multi-software attempts succeed. EngiWorld provides the first rigorous foundation for measuring progress toward agents that operate professional engineering software end to end.

Artificial Intelligence (cs.AI); Computation and Language (cs.CL)

arXiv:2609.37686 [cs.AI]

(or arXiv:2609.37686v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2609.37686 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 282 words

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