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优企派系统开发:以价值为核心的协同共创之路
Sou Hu Cai Jing· 2025-10-30 04:19
Core Insights - The essence of system development is to solve problems and create value through technology, rather than merely writing code [1] - A valuable system integrates business goals, user needs, and technical capabilities, avoiding the pitfall of becoming an unused tool after development [1] Value Anchoring: Focusing on Real Needs - The first step in system development is to clarify the value the system aims to create, rather than discussing technical frameworks [6] - Demand research should penetrate superficial requests to identify core needs, ensuring that the system addresses actual pain points [6] - Not all demands are worth developing; prioritizing based on value and cost is essential to focus resources on solving real problems [6][7] Consensus on Requirements - After determining requirements, all stakeholders must align on the value and acceptance criteria of each function to avoid misunderstandings [7] Role Collaboration - System development is a collaborative effort involving business, technical, design, and testing roles, rather than a solo endeavor by the technical team [8] - Clear role definitions and proactive communication among teams are crucial to ensure that all aspects of the project align with business needs [8] - Iterative development with frequent communication helps to identify and resolve issues early, avoiding the pitfalls of traditional waterfall methods [8] Tool Collaboration - Utilizing a unified collaboration platform for managing requirements, task assignments, and progress tracking is essential to avoid confusion [9] Quality Control: From "Usable" to "User-Friendly" - Quality control should be an ongoing process that encompasses functionality, user experience, and security [12] - Functionality must match requirements precisely to avoid operational issues, with thorough self-testing during development [12] - User experience should be prioritized by incorporating user feedback into the development process to simplify operations [12] - Security measures must be integrated from the start, including data encryption and vulnerability assessments before launch [13] Continuous Evolution: Adapting with Business Growth - System deployment marks the beginning of ongoing value delivery, necessitating a feedback and optimization loop [16] - A data-driven iteration mechanism should be established to monitor core metrics and identify areas for improvement [16] - Systems must be adaptable to changes in business models, ensuring they can support new functionalities as needed [16] - User feedback should be actively collected and incorporated into future iterations to enhance the overall experience [16]
专家谈车企AI大模型开发:构建理解行业的专属大脑
Zhong Guo Xin Wen Wang· 2025-07-17 01:45
Group 1 - The core concept presented is the transformation of employee roles in enterprises due to AI and digital thinking, where employees will evolve from executing processes to becoming operators and enhancers of intelligent systems [1] - China FAW Group introduced the concept of Enterprise Operation AI Agent (EOA) aimed at linking various business units through a large model for real-time optimization, breaking the constraints of traditional process governance [3][4] - EOA enables direct connection of strategic indicators to workshop sensor data, facilitating complex problem breakdown and creating a self-evolving capability within enterprises by modeling the entire supply chain from demand to channel [3] Group 2 - The traditional management model is being restructured through EOA, allowing for real-time verification and optimization of product development and manufacturing processes, thus eliminating intermediary steps and creating a data-driven closed-loop optimization [3] - There is a need for a new management paradigm that shifts from process governance to data-driven, intelligent autonomy, and continuous evolution in the automotive industry [4] - The company is developing a specialized large model that deeply understands industry knowledge, business processes, and proprietary data to maximize AI's value in the automotive sector [4]