Not every repetitive task needs a model. Deterministic steps—format checks, calculations, permissions and routing rules—are often better handled by ordinary code. AI is useful when the input is ambiguous or language-heavy and the task can be evaluated against clear criteria.
Map the process first
Write down the input, decision, action, output and exception path. Identify where judgment or interpretation is genuinely needed.
Define how quality will be measured
Use a representative test set and agree what counts as acceptable. Consider error types, latency, cost, privacy and the consequences of a wrong answer.
Keep deterministic guardrails
Use ordinary code for permission checks, data validation, required fields and irreversible actions. Add human review where consequences justify it.
Choose the simplest adequate design
Compare a rule-based baseline with the AI-assisted version. Adopt AI when it provides a measurable and maintainable benefit for the task.