This research describes Cicero, a novel AI agent that achieves human-level performance in the complex game of Diplomacy. Success in Diplomacy requires strategic reasoning and effective natural language negotiation, which Cicero accomplishes by combining a dialogue module trained on human game data with a strategic reasoning module using a novel KL-regularized planning algorithm. The dialogue module is designed to be controllable through "intents," or planned actions, enhancing its ability to cooperate with humans. Multiple filters are implemented to mitigate potential issues like generating nonsensical or strategically poor messages. Cicero's superior performance in a human online league demonstrates the potential of combining advanced language models with strategic reasoning for creating human-compatible AI.