LLM application workflows: Generative AI worked examples

Validate outputs and handle failures at application boundaries.

• LLM tool calling with validated arguments and a bounded dispatcher

  Treat tool proposals as untrusted input, validate a read-only unit conversion and reject unknown tools, fields and nonfinite values.

  tutorial · 4 min read

• Prompt injection in a retrieval pipeline: keep documents from granting permissions

  Test a malicious retrieved instruction with deterministic proposal fixtures and enforce a read-only application capability boundary.

  tutorial · 4 min read

• Validate structured LLM outputs in Python: syntax, schema and evidence

  Test an extraction boundary with malformed JSON, wrong types and schema-valid mistakes, using an offline validator and explicit source facts.

  tutorial · 4 min read