A Juejin article breaks enterprise AI into 3 layers: website expression, knowledge retrieval, and task execution; we argue that investment should be prioritized by business bottlenecks, not by how new the technology is.

What This Is

Website optimization helps outsiders understand what a company does and whom it serves. RAG (Retrieval-Augmented Generation: first retrieve specified materials, then let the model answer based on them) targets internal documents; against scattered files and repeated lookups, it can lift efficiency—but only if the knowledge is cleaned up first.

Enterprise-grade RAG is not the same as uploading every document to a large model. Part numbers and model codes rely on keyword matching; colloquial questions get answered by meaning. Hybrid search (combining both methods) is usually more reliable, but still requires real-world business testing. AI Agent (an assistant that lets the model call tools and execute multi-step tasks) corresponds to the action layer.

Industry View

If the product lineup, delivery model, and common questions are unclear, website optimization comes first; if materials are scattered across cloud drives and business systems, and customer service routinely cites outdated versions, evaluate RAG first. Our judgment is not a fixed sequence, but allocating budget by problem.

The article provides no go-live samples, timelines, or ROI data, so we cannot conclude that "website first, then RAG" fits every company. Neither build guarantees external AI search recommendation; if permissions and versioning aren't sorted out, RAG may just relocate the chaos into a new system.

Impact on Regular People

  • For enterprise IT: Knowledge base building isn't just software procurement—it also includes document cleanup, permissions, and maintenance; with limited budget, address existing efficiency bottlenecks first.
  • For working professionals: If the assistant shows sources and respects permissions, fact-checking gets easier; if answers come without grounding, the risk of recycled outdated documents persists.
  • For the consumer market: Corporate descriptions may become more readable, but AI search citation isn't the same as authoritative endorsement—prices, contracts, and delivery commitments still need verification.