编译：Grace、Haozhen 在过去十年里，Snowflake（SNOW）凭借云原生数据仓库的创新，成为企业数据平台领域最具代 表性的公司之一。2020 年 Snowflake 以 120 美元发行价完成约 34 亿美元的 IPO，成为当时软件行 业规模最大的上市发行。 但随着 AI 的迅速崛起，企业使用数据的方式、技术栈构建和产品演进节奏都出现显著变化。接任 CEO 的 Sridhar Ramaswamy 在过去 18 个月中推动 Snowflake 迎来重要转折：从以数据基础设施为 核心的公司，升级为以 AI 驱动、面向更广泛企业用户的 AI Data Cloud。 在最新访谈中，Sridhar 解释了为什么 Snowflake Intelligence 是公司战略转型的关键一步。从底层技 术到跨云生态，再到与主要合作伙伴的关系演进，Snowflake 通过 AI 不断放大企业在自身平台上沉 淀的数据价值。此外，他还分享了企业应该如何衡量 AI ROI、AI 对广告行业的影响，以及在大模 型不断进步的今天，传统搜索技术为什么仍然不可或缺。 01 . Snowflake 的"转型"：利用 AI 放大已有 ...

Product Development - Warp 发布新功能，旨在让用户更好地监督命令行编码代理 [1] - 新功能包括更广泛的差异跟踪和更清晰的编码代理行为视图 [1]

Acquisition & Talent - Google DeepMind acquired Windsurf AI, including founders Mohan Solo and Douglas Chen, and some engineering team members [1] - The acquisition aims to enhance Google DeepMind's Gemini efforts in coding agents and tool use [1] - Windsurf AI's team will contribute to advancing agentic coding within Gemini [1] Technology & Product Development - The acquisition is expected to "turbocharge" Gemini's capabilities in coding agents and tool use [1] - Google DeepMind is focusing on advancing its work in agentic coding within the Gemini project [1]

AI Coding Agents: Efficacy and Usage - Coding agents are substantively useful, though opinions vary on their best practices and applications [1] - The number one mistake people make with coding agents is using them the same way they used AI coding tools six months ago [1] - The evolution of frontier model capabilities drives distinct eras in generative AI, influencing application architecture [1] Design Decisions for Agentic LLMs - Agents should make edits to files without constant human approval [2] - The necessity of a thick client (e.g., forked VS Code) for manipulating LLMs is questionable [2] - The industry is moving beyond the "choose your own model" phase due to deeper coupling in agentic chains [2] - Fixed pricing models for agents introduce perverse incentives to use dumber models [2] - The Unix philosophy of composable tools will be more powerful than vertical integration [2] Best Practices and User Patterns - Power users write very long prompts to program LLMs effectively [4] - Directing agents to relevant context and feedback mechanisms is crucial [5] - Constructing front-end feedback loops (e.g., using Playwright and Storybook) accelerates development [6] - Agents can be used to better understand code, serving as an onboarding tool and enhancing code reviews [9][11] - Sub-agents are useful for longer, more complex tasks by preserving the context window [12][13]