RAG, agents, and workflows: choosing the right AI approach
Architecture should follow the job. If the product needs reliable access to changing knowledge, retrieval may be enough. If it needs a sequence of tool calls, an agent can help—but only with clear boundaries.
Use retrieval when knowledge is the problem
RAG is useful when users need grounded answers from a known collection of documents or records. Invest in source quality, permissions, chunking, and citations before adding more autonomy.
Use workflows when consistency matters
Deterministic steps with AI inside them are often easier to evaluate and operate. Let the model handle language or classification while the product controls the process.
Use agents for bounded action
Agents make sense when the system must choose among tools or steps. Define allowed actions, limits, approvals, and an audit trail from the beginning.