Key Takeaways

My biggest learning is that AI understanding and business control should be separate concerns.

The LLM helps translate messy human language into structured candidate information. The deterministic workflow engine uses validated facts, explicit state, and predefined rules to determine the next permitted step. The application then executes authorized operations and records the result.

This architecture combines the flexibility of natural-language interaction with the predictability required for controlled business workflows.

In one sentence:

Use the LLM to understand the user, but use deterministic rules to control the business process.

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Topics covered: LLM-based information extraction, deterministic rule engines, workflow orchestration, state ledgers, graph execution, out-of-scope intent detection, guardrails, authorization, connectors, idempotency, auditability, golden-scenario testing, and reusable SDK architecture.