Create structured JSON prompts for better AI interactions
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Learn More at Madewell.aiJSON prompting is a structured way to interact with AI models by using JSON (JavaScript Object Notation) as the input format. This approach transforms your prompt into a clearly defined task with specific parameters, reducing ambiguity and improving consistency.
Rather than asking the AI in natural language (which can be vague), you act like a builder giving blueprints. The structure gives the model clarity on what to do, how to do it, and what output format to return.
Defines the task, structure, format, and tone up front
Models respond more reliably and predictably
Outputs can be reused as inputs for next steps
Works across models, tools, and environments
JSON = structure. Freeform = chaos.
Use JSON when your outcome requires structure, repeatability, and precision. Perfect for:
Keep nesting under 3 levels deep. Too many layers confuse the model.
Define exact formats, fields, and constraints.
Lower temperature = more deterministic, essential for structured output.
Use 3 retries with temp=0 before human review. This covers 99% of issues.
Schema validation acts like a contract. Invalid formats get rejected.
{ "task": "write content", "platform": "twitter", "structure": { "hook": "short, curiosity-driven", "body": "3 insights with smooth flow", "action": "1 strong question" }, "topic": "how to stay focused as a founder", "output_format": "text" }
{ "task": "write code", "language": "python", "goal": "build a script that renames all files in a folder", "constraints": ["must work on MacOS", "include comments"], "output_format": "code only" }
{ "task": "act as brand consultant", "client": "early-stage AI tool", "goal": "define clear positioning", "deliverables": ["1-liner", "target audience", "3 key differentiators"], "tone": "simple and strategic", "output_format": "bullet points" }
"Can you help me write a tweet about staying focused as a founder?"
Too vague, inconsistent results
{ "task": "write content", "platform": "twitter", "structure": { "hook": "short, curiosity-driven", "body": "3 insights with smooth flow", "action": "1 strong question" }, "topic": "how to stay focused as a founder", "output_format": "text" }
Clear, specific, consistent results
"Write me a Python script for files."
Too vague, inconsistent results
{ "task": "write code", "language": "python", "goal": "build a script that renames all files in a folder", "constraints": ["must work on MacOS", "include comments"], "output_format": "code only" }
Clear, specific, consistent results
"Help me figure out my AI brand."
Too vague, inconsistent results
{ "task": "act as brand consultant", "client": "early-stage AI tool", "goal": "define clear positioning", "deliverables": ["1-liner", "target audience", "3 key differentiators"], "tone": "simple and strategic", "output_format": "bullet points" }
Clear, specific, consistent results
Stop asking. Start specifying.
JSON prompting turns vague requests into production-ready instructions. Think like an architect, not a poet. Structure your prompts and watch your AI workflows become 10x more reliable, scalable, and useful.