By Start by choosing a specific, repeatable task. Then choose a model that can handle it. Before selecting a provider, define what the user supplies, what a useful response contains and what should happen when the response is incomplete.
Start with a bounded task
Classification, summarisation, extraction and assisted drafting are easier to evaluate than an open-ended assistant. A useful first feature may categorise a support request, prepare an excerpt from an approved article or turn form text into a known set of fields.
Keep business logic outside the prompt
The application should decide permissions, validation, publishing rules and record changes. The model can suggest content or return structured data, but it should not silently become the source of truth for important business decisions.
Prefer structured output
If WordPress needs a title, summary and category, request those named fields and validate them. Do not parse an unpredictable paragraph when a schema can describe the expected response. Validation also gives the interface a clear way to handle missing or incorrect values.
Make human review visible
When output affects published content, customers or stored records, review belongs inside the workflow. Show the proposed change, preserve the source material and let the user approve, edit or reject it.
Separate the provider from the product
Keep provider-specific authentication and request code behind a small internal layer. This makes testing easier and reduces the cost of changing models later. Log latency, failures and token usage without storing sensitive prompt content unnecessarily.
Design the failure state
Rate limits, unavailable services and invalid responses will occur. A useful WordPress feature should fail safely, explain what happened and allow the user to continue without losing their work. Practical AI is less about a dramatic demo and more about a carefully controlled improvement to an existing task.
