Agents vs. Scripts: Choosing the Right Tool for Automation Tasks

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As AI agents grow popular, many developers are defaulting to them for tasks that simple scripts could handle more efficiently. A script follows a fixed control flow defined by the developer, while an agent lets the language model decide what actions to take and in what order at runtime. Using email triage as a case study, a basic regex script can sort support emails by keyword in microseconds at near-zero cost, but fails when customers use informal or unexpected phrasing. This limitation reveals where LLM-based approaches add value — understanding context and intent that cannot be captured by predefined rules. The core takeaway is that choosing between a script and an agent based on task complexity can save developers significant time, money, and debugging effort.

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