Production & LLMOps · TRACK 04/05
Guardrails & Reliability
Validation, fallbacks, and the safety net between the model and your users.
// THE TRACK
01 · START HERELLM GuardrailsUnderstand what guardrails check before and after each model call, and how to add your first input and output validators.BEGINNERValidating LLM OutputsLearn the concrete techniques — structured parsing, schema validation, retry loops, content filters, and fallbacks — that turn unpredictable model text into safe, typed data your app can rely on.INTERMEDIATEFallbacks & RetriesDesign retries, fallback models, and degraded modes so LLM failures become minor annoyances instead of outages.INTERMEDIATESchema ValidationLearn to enforce structure on LLM output with Zod, Pydantic, and JSON Schema, plus repair loops for when parsing fails.INTERMEDIATEContent ModerationLearn how moderation filters and safety APIs keep harmful content out of your inputs and outputs, and where to place them.BEGINNERCircuit BreakersYou'll understand how a circuit breaker detects a failing LLM provider, stops sending doomed requests, and lets the system recover instead of piling up timeouts.INTERMEDIATEHallucination DetectionYou'll understand the practical, runtime techniques teams use to catch likely hallucinations before they reach the user, and how to react when one is detected.INTERMEDIATEPII Redaction in LogsYou'll understand how to strip personal data from prompts and responses before it lands in your logs and traces, without losing the ability to debug.INTERMEDIATE