我们从一年的LLM构建中学到了什么（第三部分）：策略

We previously shared our insights on the tactics we have honed while operating LLM applications. Tactics are granular: they are the specific actions employed to achieve specific objectives. We also shared our perspective on operations: the higher-level processes in place to support tactical work to achieve objectives.

我们之前分享了我们在运营LLM应用程序时磨练的策略。策略是具体行动，用于实现特定目标。我们还分享了我们对运营的看法：这是一种支持战术工作以实现目标的更高级别的流程。

Learn faster. Dig deeper. See farther.

学得更快。挖得更深。看得更远。

But where do those objectives come from? That is the domain of strategy. Strategy answers the “what” and “why” questions behind the “how” of tactics and operations.

但这些目标从何而来？这是战略的领域。战略回答了战术和运营背后的“什么”和“为什么”问题。

We provide our opinionated takes, such as “no GPUs before PMF” and “focus on the system not the model,” to help teams figure out where to allocate scarce resources. We also suggest a roadmap for iterating toward a great product. This final set of lessons answers the following questions:

我们提供了我们的观点，比如"在PMF之前不要使用GPU"和"专注于系统而不是模型"，以帮助团队确定在哪里分配有限的资源。我们还提出了一份逐步迭代实现出色产品的路线图。这组最后的课程回答了以下问题：

Building vs. Buying: When should you train your own models, and when should you leverage existing APIs? The answer is, as always, “it depends.” We share what it depends on.
建造与购买：何时应该训练自己的模型，何时应该利用现有的API？答案是，如常，"这取决于情况"。我们分享了它取决于什么。
Iterating to Something Great: How can you create a lasting competitive edge that goes beyond just using the latest models? We discuss the importance of building a robust system around the model and focusing on delivering memorable, sticky experiences.
迭代至伟大：如何创建一个持久的竞争优势，超越仅仅使用最新的模型？我们讨论了围绕模型构建强大系统的重要性，并专注于提供令人难忘、有吸引力的体验。
Human-Centered AI: How can you effectively integrate LLMs into human workflows to maximize productivity and happiness? We emphasize the importance of building AI tools that support and enhance human capabilities rather than attempting to replace them entirely.
以人为中心的AI：如何有效地将LLM整合到人类工作流程中，以最大化生产力和幸福感？我们强调构建支持和增强人类能力的AI工具的重要性，而不是试图完全取代它们。
Getting Started: What are the essential steps for teams embarking on building an LLM product? We...