Mercor

Mercor and Google's AI & Infrastructure research team released Physical-Engineering's Last Exam (PLE), 85 long-horizon tasks testing whether AI agents can do mechanical, electrical, civil and structural engineering work. Each task runs in a containerized project folder of about 61 files, including PDFs, spreadsheets, emails, 2D CAD drawings, 3D BIM models and planted outdated revisions, with no internet access and up to six hours. The best configuration, Claude Opus 5.5 in Claude Code, reaches 48.3% on the hidden test set at an average of 27 million tokens and 63 minutes per task; its designs met 91% of individual constraints on average, but only 41% cleared every hard check.

Mercor and Google's AI & Infrastructure research team released Physical-Engineering's Last Exam (PLE), 85 long-horizon tasks testing whether AI agents can do mechanical, electrical, civil and structural engineering work. Each task runs in a containerized project folder of about 61 files, including PDFs, spreadsheets, emails, 2D CAD drawings, 3D BIM models and planted outdated revisions, with no internet access and up to six hours. The best configuration, Claude Opus 5.5 in Claude Code, reaches 48.3% on the hidden test set at an average of 27 million tokens and 63 minutes per task; its designs met 91% of individual constraints on average, but only 41% cleared every hard check.

Google AI & Infrastructure, with Mercor, released Physical-Engineering's Last Exam (PLE), an 85-task benchmark and open competition spanning mechanical, electrical, civil and structural engineering that tests whether agents can complete real engineering work under a licensed engineer's review. Each task is a containerized project folder averaging 61 files, and an agent must find governing codes, run calculations and produce deliverables, earning points only after passing every hard safety check. On the private test set all 14 frontier models scored below 50%, with the top configuration reaching a mean of 48.3% on its native harness.

Google AI & Infrastructure, with Mercor, released Physical-Engineering's Last Exam (PLE), an 85-task benchmark and open competition spanning mechanical, electrical, civil and structural engineering that tests whether agents can complete real engineering work under a licensed engineer's review. Each task is a containerized project folder averaging 61 files, and an agent must find governing codes, run calculations and produce deliverables, earning points only after passing every hard safety check. On the private test set all 14 frontier models scored below 50%, with the top configuration reaching a mean of 48.3% on its native harness.

An occupational task catalogue for the US economy now has language models interview workers directly instead of relying only on fixed questionnaires. Standardized surveys like O*NET are slow to catch tasks that have just appeared, and human-led interviews are expensive to run at scale. The interviewer asks follow-up questions to clarify vague descriptions and confirms the resulting task bundles with the worker; on a holdout of 1,184 task reports from 57 workers, TaskNet's lists covered 89.3% of reported tasks on average across six occupations, against 78.6% for O*NET.

An occupational task catalogue for the US economy now has language models interview workers directly instead of relying only on fixed questionnaires. Standardized surveys like O*NET are slow to catch tasks that have just appeared, and human-led interviews are expensive to run at scale. The interviewer asks follow-up questions to clarify vague descriptions and confirms the resulting task bundles with the worker; on a holdout of 1,184 task reports from 57 workers, TaskNet's lists covered 89.3% of reported tasks on average across six occupations, against 78.6% for O*NET.