思码逸：2025研发效能红宝书2.0

Core Insights - The report "R&D Efficiency Red Book 2.0" focuses on enhancing software development efficiency in the AIGC era, compiling practical experiences from over ten industry experts, and establishing a comprehensive system covering collaboration mechanisms, data measurement, and AI applications [1][2]. Group 1: Collaboration Between Technology and Business - The report emphasizes the synergy between technology and business, breaking the dichotomy of "doing the right thing" and "doing things right," proposing that both are complementary [1]. - It advocates for practices such as demand value scoring and layered management to create a win-win model between business and R&D, while also fostering an organizational structure and culture conducive to lean thinking, agile principles, and DevOps practices [1][2]. Group 2: Data-Driven Efficiency Measurement - The report outlines the need to avoid single-metric traps in measuring R&D efficiency, recommending the GQM+MARI methodology, which integrates mainstream tools like DORA metrics and SPACE framework to build an automated data collection and analysis platform [1][2]. - It promotes the core metric of "code equivalent," which quantifies code complexity through syntax tree analysis, avoiding the limitations of traditional metrics like lines of code and story points, while also incorporating dimensions such as demand throughput and defect density for a multi-faceted measurement view [1][2]. Group 3: AI's Role in Reshaping R&D Efficiency - A key highlight is the transformative impact of generative AI across the entire R&D lifecycle, with notable efficiency improvements of approximately 17% in areas like code completion and test case generation, although quality improvements still face challenges [2]. - The application of AI in measurement is twofold: enhancing the accuracy of measurement data (e.g., identifying code vulnerabilities) and alleviating analysis burdens by assisting in generating efficiency reports and uncovering data trends [2]. - The report includes case studies from companies like Qunar, JD Technology, and Hello Chuxing, showcasing pathways from pilot projects to organization-wide promotion and from single-process optimization to systematic construction [2].