您过去构建的哪些应用可以迁移到Agentic架构？
最近，我一直在学习基于大型语言模型（LLM）的ReAct架构，以设计软件解决方案。我还参与了这一方法的高规模生产实施，这让我思考过去构建的所有应用程序。
理论上，任何一个应用都可以使用ReAct架构来实现，但我仍在思考何时使用这种架构是合理的，何时又不合适。一些应用显然受益于LLM支持的推理，特别是那些业务逻辑繁重且频繁变化的应用。在这些情况下，更新提示可能替代代码更改，从而使产品团队能够直接影响系统行为，而无需工程师的参与。
另一方面，静态数据处理管道似乎不适合这种架构。当逻辑稳定且确定时，LLM推理的开销和不可预测性并不会带来价值。最佳应用场景似乎是业务规则快速演变的应用，而维护传统代码的成本超过了提示工程的复杂性。
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Recently I've been learning about [LLM-powered ReAct architecture](https://arxiv.org/pdf/2210.03629) for designing software solutions. I've also worked on a high-scale production implementation of this approach, which got me thinking about all the applications I've built in the past.<p>Theoretically, any of them could be implemented using the ReAct architecture, but I'm still grappling with when this makes sense and when it doesn't. Some applications clearly benefit from LLM-backed reasoning—particularly those with heavy business logic that changes frequently. In these cases, updating prompts could replace code changes, potentially enabling product teams to directly influence system behavior without engineering involvement.<p>On the other hand, static data processing pipelines seem like poor candidates for this architecture. When the logic is stable and deterministic, the overhead and unpredictability of LLM inference doesn't add value. The sweet spot appears to be applications where business rules evolve rapidly and the cost of maintaining traditional code outweighs the complexity of prompt engineering.<p>https://www.sanathkandikanti.com/meditations