Structured Output & Function Calling
Move from chat responses to reliable application behavior with schemas, validation, tool selection, and typed outputs.
Production project
Order Support Assistant
A support assistant must inspect order and refund information instead of inventing answers from conversation context.
Who this is for
- •Developers integrating LLMs into backend products
- •Engineers whose prototypes still parse fragile free-form text
How this helps
- •You can build LLM features that return application-safe data
- •You gain the key foundation for tool-using agents
What you will learn
The capabilities, not just the keywords.
- •Design structured model outputs that applications can safely consume
- •Validate and recover from malformed model output
- •Define tool contracts with clear inputs and outputs
- •Implement tool-selection and result-return loops
- •Separate model reasoning from business-side effects
Real production project
Order Support Assistant
A support assistant must inspect order and refund information instead of inventing answers from conversation context.
What we build
- •Intent extraction schema
- •order-status tool
- •refund-status tool
- •ticket-creation tool
- •tool result handling
Stack
- •Python or TypeScript
- •LLM API
- •Pydantic or JSON Schema
Production concerns
- •Schema validation
- •tool permissions
- •timeouts
- •invalid arguments
- •auditability
- •side-effect boundaries
Finished deliverables
- •Working tool-enabled assistant
- •tool schemas
- •test prompts
- •production checklist
Prerequisites
Required
- •Basic Python or TypeScript
- •Basic experience calling an LLM API is useful
Helpful, but optional
- •REST API experience
- •JSON Schema or Pydantic familiarity
Before the session
Come ready to build.
- •LLM API key or compatible local/provider setup
- •Python or Node.js
- •Git
What to expect
What you get
Something useful after the call ends.
- •Source code
- •tool contract template
- •test scenarios
- •next-step agent/RAG path
Where to go next
LLM APIs → Reliable Tools → Agentic Applications
Every session can be booked independently. If you already know the prerequisite material, skip ahead.
Useful before this
No earlier session is mandatory.
Teaching proof
Review the evidence first.
See workshop delivery, technical projects, and teaching proof before booking.
Ready?
Request AI03: Structured Output & Function Calling
Share your current level and what you want to build. The session can be adapted without changing its core outcome.
Request this sessionFAQ
Can I book only this session?
Yes. Every session is designed to work independently.
Can I bring my own project?
Yes, when it fits the session outcome. We can map the concepts onto your project instead of the default example.
What if I already know part of the topic?
We can move faster through familiar material and spend more time on implementation, failure modes, and production trade-offs.
Is the session recorded?
Recording is not promised by default. Confirm this before the session if you need it.
What should I install?
The preparation section above lists the default setup. You will receive any session-specific setup notes before the call.
Are API or cloud charges included?
No. Any third-party API or cloud usage is paid directly through your own account unless explicitly agreed otherwise.