Design a Validation → Retry → HITL Control Flow
Explore how to design a robust AI workflow control flow that enforces schema validation, manages retries driven by specific errors, and integrates human-in-the-loop fallback for safe automation. Understand how to ensure outputs meet structured contracts, avoid infinite loops, and create auditable results for reliable production use.
Automated workflows require deterministic branching, yet language models are inherently probabilistic. To bridge this gap safely, your pipeline must assume that invalid or schema-violating outputs will occur and enforce a strict control flow that fails safe. Instead of allowing downstream routers to consume raw AI text directly, a production architecture places a validator gate between generation and execution. In this lesson, we will design an end-to-end validation → retry → human-in-the-loop (HITL) control flow that enforces schema rules, limits retries with specific error signatures, and constructs auditable fallback packets when human intervention is required.
The diagram’s key behavior is that route() never consumes raw model text directly. The validator sits between generation and routing and produces two outputs: a parsed structured object when validation passes, or a list of violations when it fails. Each retry records the ...