如何打造可信可用的模型软件系统，从实验到生产全链路指南
The Hitchhikers Guide to Production-ready Trustworthy Foundation Model powered Software (FMware)
- 整合大模型构建系统级软件（FMware），解决选型、数据对齐、提示工程难题
- 揭示从演示到生产的关键瓶颈：测试、优化、部署与旧系统集成
- 面向工业界落地，提供可操作策略与技术路线图
基础模型（如大语言模型）正重塑软件产业，推动以模型为核心组件的FMware系统发展。本教程在KDD 2025上全面探讨了FMware面临的挑战，涵盖研究与实践现状。重点分析模型选择、高质量领域数据对齐、鲁棒提示工程及自主代理编排等难点。进一步梳理从惊艳演示到生产可用系统的复杂路径，包括系统测试、性能优化、部署策略及与遗留系统的集成问题。结合工业经验与最新研究成果，提供切实可行的应对策略与技术演进路线图，帮助从业者构建可信可靠的FMware系统。
原文摘要 · Abstract (English)
Foundation Models (FMs) such as Large Language Models (LLMs) are reshaping the software industry by enabling FMware, systems that integrate these FMs as core components. In this KDD 2025 tutorial, we present a comprehensive exploration of FMware that combines a curated catalogue of challenges with real-world production concerns. We first discuss the state of research and practice in building FMware. We further examine the difficulties in selecting suitable models, aligning high-quality domain-specific data, engineering robust prompts, and orchestrating autonomous agents. We then address the complex journey from impressive demos to production-ready systems by outlining issues in system testing, optimization, deployment, and integration with legacy software. Drawing on our industrial experience and recent research in the area, we provide actionable insights and a technology roadmap for overcoming these challenges. Attendees will gain practical strategies to enable the creation of trustworthy FMware in the evolving technology landscape.
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