DAYJOB: Can Agents Survive a 9 to 5?

DAYJOB is a benchmark suite introduced to assess whether AI agents can perform realistic, long-horizon professional knowledge work in healthcare and finance, where tasks are often ambiguous, spread across many documents, and require judgment rather than simple execution. Its creators argue that existing benchmarks such as GDPval frequently provide overly detailed instructions, limited inputs, and tasks focused on formatting or routine document production, while DAYJOB uses shorter requests, roughly 20–26 supporting files per assignment, and assignments estimated to take professionals about 20 hours. The initial release includes 130 expert-designed tasks covering areas such as clinical decision support, patient safety, investing, banking, and corporate finance, with task-specific evaluation rubrics. Examples show agents missing a major currency-unit pricing error that overstated a fund position by $25.7 million and failing to challenge a potentially unsafe Bell’s palsy discharge plan despite concerning symptoms. The reported top model scores are below 25% in both healthcare and finance, suggesting that although current agents can handle well-specified calculations and writing tasks, they remain limited in independently identifying relevant information, resolving ambiguity, and making consequential professional judgments.

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