Smart contracts, the self-executing agreements at the heart of blockchain technology, promise a future of automated, secure transactions. But they're not immune to hacks. A new research paper explores how the subtle errors in smart contract logic—often overlooked by current security tools—can be exploited, leading to significant financial losses. Researchers have developed "Soley," an AI-powered tool that leverages large language models (LLMs) to detect these vulnerabilities. By analyzing real-world code changes from GitHub, Soley pinpoints nine previously unidentified logic vulnerabilities and proposes 15 mitigation strategies. The tool goes beyond simple pattern matching, delving into the intricacies of code semantics and context to catch errors like insecure oracle data validation, state manipulation via inline assembly, and inconsistent state transition checks during upgrades. The initial results are encouraging, outperforming existing security tools in accuracy. Soley isn't just detecting vulnerabilities; it's helping us understand why and how they occur. This understanding paves the way for more secure and reliable smart contract development. Soley demonstrates that AI can play a crucial role in preventing future smart contract exploits, ensuring the blockchain ecosystem's continued growth and stability.