Building AI Agents That Don't Hallucinate: Structured Workflows, Guardrails, and Per-Step Evaluation

Short summary

The author replaced fragile prompt-chained agents with structured workflows using Pydantic schemas, validation guardrails, explicit state machines, and per-step evaluation, improving task success from 60% to 94%. Each step has typed inputs/outputs, blocking guardrails that auto-retry on failure, and an evaluation harness for granular debugging. The approach gives full visibility into which step fails and why, eliminating the cascading-failure problem of naive prompt chains.

• •Structured workflows with Pydantic schemas and guardrails improved agent task success from 60% to 94%
• •Per-step evaluation and explicit state machines replace fragile implicit prompt chaining
• •Validation gates auto-retry failed steps, preventing cascading failures across the pipeline

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