字节前技术负责人创业，联手清华姚班校友，编程智能体世界登顶

Core Insights - InfCode is defining the "Engineering Era" of AI programming, moving beyond the "Vibe Coding" concept introduced by Andrej Karpathy, which focuses on generating code from simple prompts [3][7]. Group 1: InfCode's Performance - InfCode achieved a Pass@1 score of 79.4% on the SWE-Bench Verified benchmark, surpassing leading models like GPT-5 and Claude, which scored around 70% [6][13]. - On the Multi-SWE-bench C++ subset, InfCode reached a 25.58% resolution rate, significantly outperforming competitors such as Claude 3.7 Sonnet (8.59%) and DeepSeek V3 (7.75%) [6][13]. Group 2: Technical Innovations - InfCode employs a multi-agent system designed for enterprise scenarios, marking a shift from individual efficiency to organizational evolution in AI coding [6][9]. - The system integrates "Code Intent Analysis," allowing it to understand the functional intent behind natural language descriptions, enhancing its ability to locate issues in large codebases [18][19]. - InfCode features a structured search engine based on Abstract Syntax Trees (AST), improving code retrieval accuracy compared to traditional text search tools [21][23]. Group 3: Repair Process and Methodology - The repair process of InfCode consists of two phases: generation and selection, allowing for multiple iterations to produce diverse patch candidates [30][33]. - InfCode utilizes a dual-agent architecture for code patch generation and testing, enabling continuous improvement and robustness of the generated patches [25][29]. Group 4: Team and Vision - The core team of InfCode, referred to as a "startup dream team," combines technical expertise with commercialization capabilities, positioning them uniquely in the competitive AI coding agent landscape [35][38]. - The team aims to transform the AI coding landscape from mere tool efficiency to a comprehensive reconstruction of the software engineering lifecycle, focusing on end-to-end value delivery [38].