When should you not build an agent?

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Answer

$When the task has a known, fixed sequence of steps.$
$A deterministic pipeline that calls the model at two specific points is cheaper, faster, easier to test and far easier to debug than an agent deciding what to do each turn.$
$Agents earn their cost when the number and order of steps genuinely depend on intermediate results, such as open-ended research or multi-step debugging.$
$They are a poor fit where errors are expensive and irreversible, where latency budgets are tight, or where you cannot afford unbounded token spend.$
$The honest default is a workflow, escalating to an agent only when the branching is real.$

Check yourself — multiple choice

Always build an agent
When the steps are known and fixed — a deterministic pipeline is cheaper, testable and debuggable; agents only pay off when branching genuinely depends on intermediate results
Agents are always cheaper
Only when tools are unavailable

Fixed step sequences belong in a workflow; agents are for genuinely dynamic control flow.

#agents#production

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