Begin with predictability
A conventional workflow follows defined rules: when an event happens, validate the input, update a record, and notify an owner. When your process is stable and the rules are clear, this can be the simplest dependable solution.
Add reasoning where the inputs vary
Some tasks involve unstructured messages, changing context, or several plausible next steps. An AI component may help classify a request, find relevant information, or draft a response. That does not mean every step needs to be controlled by an agent.
Combine strengths deliberately
A useful pattern is a deterministic workflow around a bounded AI step. The workflow handles authentication, validation, logging, and delivery. The AI handles a task such as summarization, and a person reviews sensitive actions.
Design the failure path
Ask what happens when a tool is unavailable, an answer is uncertain, or the input is incomplete. Define timeouts, retries, and a human escalation route before the workflow becomes essential to daily operations.
Choose the smallest useful system
Start with the least complex design that meets the need. Add more autonomy only when it solves an observed limitation and can be evaluated reliably.
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