Why Chatbot Logic Should Be Layered, Not Left Entirely to AI or If-Else

As chatbots scale to handle order tracking, refunds, validation, and API calls, a simple if-else decision tree quickly becomes unmanageable. Relying entirely on large language models is not a reliable fix either, since probabilistic models should not be the source of truth for deterministic business decisions like payment state or refund eligibility. OWASP has flagged 'Excessive Agency' as a risk when LLMs are granted too much autonomy, potentially leading to unintended actions. A more effective architecture separates responsibilities across layers: AI interprets ambiguous user language, structured inputs capture exact values, backend systems own business truth, and deterministic logic controls predictable paths. This approach, explored in a developer series on messaging automation, argues that clear boundary-setting between layers matters more than the specific tools or language used to build the workflow.