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  "text": "Code isn't just what LLMs produce. It's also useful for reasoning.\n\nThe relationship between code and reasoning in LLMs runs deeper than it seems. It's not just about generating Python scripts. It's bidirectional: code enhances reasoning, and reasoning transforms code intelligence.\n\nThis new survey paper, \"Code to Think, Think to Code,\" maps this two-way street across the research landscape.\n\nIn one direction: code strengthens reasoning.\n\nCode is abstract, modular, highly structured, and has strong logic. When LLMs use code as a reasoning medium, they gain verifiable execution paths, logical decomposition, and runtime validation. The structure of code becomes scaffolding for thought.\n\nIn the other direction: reasoning elevates code intelligence. Basic code completion was just the beginning. With deliberate reasoning capabilities, LLMs evolve into agents that plan, debug, and solve complex software engineering problems. From autocomplete to autonomous engineer.\n\nThe survey synthesizes research across both directions, identifying key patterns: how structured code provides verifiable reasoning pathways, and how reasoning transforms simple code generation into sophisticated agent-based systems.\n\nUnderstanding this bidirectional relationship is essential for building more capable AI systems.\n\nCode and reasoning aren't separate tracks. They reinforce each other. The future of LLM capability lies at its intersection.\n\n🔖 (bookmark it)\n\nPaper: https://t.co/Ba8cbUOEYl\nLearn to build AI agents in our academy: https://t.co/zQXQt0PMbG",
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