New CEO-Bench Benchmark Shows AI Agents Struggle with Long-Term Startup Management
A new arXiv preprint introduces CEO-Bench, a benchmark designed to test language model agents on managing a simulated startup over 500 days, requiring long-term planning, adaptation, and multi-task coordination. The study finds that only a few advanced models—Claude Fable 5, GPT-5.6 Sol, and Claude Opus 4.8—end with more than the initial $1M balance, but all perform worse than a simple rule-based baseline. This highlights a significant gap in current AI agents' ability to handle complex, sustained decision-making tasks.
Why it matters: The results suggest that even leading AI models are not yet capable of reliably managing complex, long-term real-world tasks, underscoring a key limitation for practical deployment.
Full story at: arXiv Software Engineering ↗