Unverified60% confidenceOpinionTime unknown
Large model application development can be divided into three progressive levels: prompt engineering, RAG retrieval-augmented generation, and model fine-tuning.
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60%
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Long-term
Relevance
6/1/2026
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Unverified大模型开发学习可拆分为五个递进阶段：大模型基础、RAG知识库开发、Agent智能体开发、模型微调进阶、项目实战79% similarUnverifiedThe article divides large model deployment into four stages: native large model, prompt engineering, RAG, and Agent, corresponding respectively to generation, expression, knowledge, and action.78% similarUnverifiedThere are three main technical approaches to injecting external knowledge into large language models: fine-tuning, retrieval-augmented generation (RAG), and structured semantic layer/ontology injection.77% similarUnverifiedPrompting, RAG and fine-tuning are composable: a fine-tuned model can still use prompts, retrieval and tool calls.76% similarUnverifiedFine-tuning is suitable for teaching a model a specific output style or domain tone, while RAG achieves immediate-update-ready results through an external knowledge base, and the two are often used in combination in engineering.76% similar
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