总结与展望未来，智能体将会是我们在各行各业、各种场景应用人工智能的主要载体。可以预见，随着模型能力和智能体工程的进步，企业数据治理和组织适配的提升，智能体会逐步成为每家企业极有竞争力的数字员工，和我们人类员工竞争与协作。
Implementations have found ways to optimize transform pipelines by collapsing identity transforms, short-circuiting non-observable paths, deferring buffer allocation, or falling back to native code that does not run JavaScript at all. Deno, Bun, and Cloudflare Workers have all successfully implemented "native path" optimizations that can help eliminate much of the overhead, and Vercel's recent fast-webstreams research is working on similar optimizations for Node.js. But the optimizations themselves add significant complexity and still can't fully escape the inherently push-oriented model that TransformStream uses.
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