RAG vs AI agents

RAG's job

Retrieve relevant passages and ground a response. Great for policy Q&A, runbooks, and internal search.

RAG does not own a case lifecycle. It should not silently update CRM fields because a paragraph looked related.

Agents' job

Execute a workflow: extract, validate, call tools, wait on humans, close or escalate.

Agents often use retrieval as one tool among many. Retrieval alone is not the product.

Choosing

If success is "correct answer with citations," start with RAG and evaluation.

If success is "case advanced with audit trail," design an agent system—and maybe use RAG inside it.

Combining them safely

Use retrieval as a tool inside an agent for policy text. Keep case state and writes outside the retrieval index.

Never let a retrieved paragraph authorize a write. Authorization is IAM and business rules, not semantic similarity.

Buyers' common mistake

Buying a chat-over-docs product and expecting underwriting or KYC outcomes. Those need case workflows, not better search snippets.

In practice

Map the workflow on a whiteboard before you open a framework: inputs, systems of record, humans, and irreversible writes. If that map is fuzzy, the agent will encode the fuzz.

Pick ten to fifty real historical cases as an eval set. Include the ugly ones. Run the agent offline against them until critical fields and hard rules are acceptable. Only then connect write tools.

Ship with a pause switch, a human queue, and a weekly review of override reasons. Promote repeated overrides into rules. That loop is how production systems improve—not another prompt brainstorm.

Common failure modes

• Treating a demo on clean samples as readiness for production volume.
• One shared service account with broad write access across systems.
• No owner for the exception queue, so failures pile up as noise.
• Changing prompts and models without regression gates on real cases.
• Measuring only model latency or thumbs-up, not completed-case cost and audit completeness.

What good looks like after ninety days

The first workflow is boring: stable override rate, known failure modes, operators who trust the queue. Config changes go through review. Traces answer "what happened to this case?" without archaeology.

At that point you can add a second document type or a second agent role. Expanding before the first path is boring is how programs stall with five half-built pilots.