When Not to Use Agents

Not every problem benefits from an agentic approach: deterministic tasks, simple data operations, and well-defined algorithms run faster, cheaper, and more predictably with traditional software than with a language model in the loop. Reaching for agents when a regular expression, SQL query, or rule engine would suffice adds unnecessary cost, latency, and unpredictability to a problem that has a single correct answer derivable from a fixed algorithm. The clearest signal that you need an agent is when a task requires judgment, ambiguity resolution, or multi-step reasoning across unstructured information, where the problem space cannot be fully specified in advance.