Agents, automation, and RAG: what to build, and when

Three things people lump together

"AI automation," "AI agents," and "RAG" get used as if they are the same thing. They are not, and picking the wrong one is how projects stall. Here is the plain-language version, and a rule for choosing.

AI automation: speed up a repetitive cognitive task

AI automation is the broad practice of using AI to accelerate or fully run recurring workflows that need interpretation but not independent planning. Extracting and coding data from invoices, generating a meeting brief from your calendar, drafting routine copy or code. The task is well understood; you just want it done faster and cheaper.

Use it when: the work is high-volume and standardized, and the win is speed on a known task.

RAG: look up and synthesize your own facts, safely

Retrieval-augmented generation connects a language model to a search system over your private data. When someone asks a question, the system retrieves the exact, current documents first, then generates an answer grounded in that evidence. That grounding is what stops the model from making things up.

Use it when: factual accuracy is critical and the answer must come from your own information. Internal policy assistants, compliance and legal research, technical support over your documentation.

AI agents: take action across your systems

An AI agent is an autonomous entity that plans, decides, and uses tools to reach a goal. A chatbot answers; an agent acts. It can call APIs, query databases, and operate software to complete a real workflow with little supervision. Think of a support agent that checks order history and processes a refund in your commerce platform, or a booking agent that checks availability and makes the reservation.

Use it when: the task is multi-step and requires taking action in other systems, not just producing text.

The one-line rule

• Need the AI to safely look up and synthesize your internal facts? Build RAG.
• Need it to perform actions across your software? Build an AI agent.
• Need to speed up a repetitive cognitive task like summarizing or extraction? That is plain AI automation.

Most real systems combine them: an agent that uses RAG to ground its decisions, wrapped in automation that routes the work. Deciding the right mix for your case is what our Foundations and Build tiers are for.