Get JSON back, not prose.
Describe what you want extracted or returned. Prompt Airchitect writes the prompt that makes the model answer with structured, parseable JSON — schema, types and rules included.
What the prompt you get back gets right
The schema lives in the prompt
Field names, types and nesting are stated explicitly, so the model mirrors the shape you asked for instead of inventing its own.
Required vs optional, spelled out
Which fields must always appear and which may be omitted — the ambiguity that usually produces half-filled objects.
Edge cases decided up front
Missing values, empty lists and date formats get a stated rule, so you are not patching nulls after the fact.
No wrapper to strip
The prompt asks for the JSON object alone — nothing to clean up before you parse it.
From a rough note to a working prompt
Your note
“pull the key details out of these support emails so I can drop them into a spreadsheet”
The prompt you get back
- Role
- the model is framed as an extraction engine, not a chat assistant
- Input
- where your emails or text go, clearly delimited from the instructions
- Output schema
- the exact fields, types and nesting you want — for example { customer_email, issue_type, priority, order_id }
- Rules
- null for missing values, ISO dates, no commentary, no markdown fences around the object
Every prompt is written for your exact request — this is the structure it comes back in, not a fixed template.
Common questions
Will the JSON always be valid?
Structured output is far more reliable than asking for JSON in passing, but no prompt can guarantee a model never errs. The prompt states the schema, the rules and a worked example so the model has every reason to follow it exactly.
Does it work with any model?
Yes. The structure is stated in plain instructions rather than a provider-specific feature, so it works with whichever model you name.
Try it with your own notes
One pass in, a structured prompt out — saved to your library so you can reuse it.
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