In this video, we’ll explore how to generate structured output in JSON format using LLMs (Large Language Models).

We’ll start by discussing the benefits of structured data — how it ensures data consistency, enables easy software integration, and makes database storage and management more efficient. 

Next, we’ll take a real-world example by generating iPhone 17 details in JSON format and observe how the model sometimes produces inconsistent or varying structures.

To solve this issue, we’ll learn how to generate an exact JSON structure with only the properties we need — such as name, price, features, and specifications.

By the end of this video, you’ll understand how to guide AI models to produce clean, structured, and predictable outputs — ideal for API development, database storage, and real-world AI integrations.

Telusko

Learn how to get structured JSON output from AI models through effective prompt engineering. The guide demonstrates techniques for requesting specific data formats, validating JSON responses, defining custom schemas, and eliminating unwanted text from AI responses. Covers role prompting, context injection, and schema specification to ensure AI returns data in a format suitable for application integration.

Getting Structured Output in JSON format