AI Agents' True Intelligence Lies in Code, Not Just Output
A new review paper reveals that code is the backbone of AI agents' decision-making and actions, and that the surrounding software layer is crucial for their functionality. This shift in perspective has significant implications for developers, businesses, and everyday users of AI systems.
A new review paper argues that the real bottleneck for autonomous AI agents isn't the language model itself but the software layer wrapped around it. Tools, memory, testing, and permission boundaries turn a stateless model into a working agent. Deepseek is already building a dedicated "Harness" team in Beijing with a core formula that confirms the thesis: model plus harness equals AI agent. The article New review paper argues code is how AI agents think and act, not just what they produce appeared first on The Decoder.