LLM Interfaces & Structured Outputs

Context construction, prompt contracts, tool calls, schema validation, retries, and observable model APIs.

Not started3 min explanation

Visualize, practice, and deep-dive material are optional—use only what helps you learn.

Explanation

A focused 3-minute explanation using the topic's authored material.

Learning goals and prerequisites

After this lesson

Design a bounded model request contract
Validate structured outputs and tool calls
Implement safe retries, tracing, and side-effect controls

Helpful before starting

HTTP and JSON basics
LLM token and context-window concepts
Application validation and error handling

Start here

LLM Interfaces & Structured Outputs, in plain language

Context construction, prompt contracts, tool calls, schema validation, retries, and observable model APIs. Reliable AI applications treat model calls as typed, observable, failure-prone dependencies rather than magical text completion.

For a small example, convert a sentence into a typed event with date and location. Define a schema, request structured output, reject invalid values, and retry only with bounded, observable rules. This is the mechanism to keep in view as the lesson becomes more technical. Before moving on, identify the input, transformation, output, and one observation that would falsify your conclusion.

Key points

Message roles, context assembly, and token budgets.
Schema-constrained generation and semantic validation.
Tool descriptions, parameter schemas, and result envelopes.

Use it well

When LLM Interfaces & Structured Outputs helps—and where it breaks

A model chooses between search, calculator, and ticket creation. Describe tools precisely, validate arguments, separate read from write permissions, log outcomes, and require approval for side effects. A useful result still depends on checking the assumptions and evidence below rather than treating one successful output as proof.

Key points

Parsing free-form output with ad hoc regular expressions. Better approach: Use one explicit schema and reject invalid results.
Retrying every error. Better approach: Classify transient, invalid, unauthorized, and unsafe failures.
Letting the model enforce authorization. Better approach: Enforce identity and policy in application code.

Was this lesson helpful?

Submit to the team when server feedback is available; otherwise this browser keeps a local copy and tells you so.

Back to Topic Library