Don't Let LLMs Control Everything: Five Hybrid LLM + Rules Architecture Cases

On September 16, @goyalshaliniuk laid out a systematic argument across multiple posts: LLMs are powerful, but they shouldn't control every decision—the strongest AI systems are often a hybrid of "LLM flexibility + deterministic rules."

Confirmed

• The author offers five practical case studies (detailed in her long-form post), spanning customer service, document processing, fraud prevention, compliance, and workflow automation.
• AI customer service: the LLM understands user messages and handles natural conversation; a rules layer decides what the system is allowed to do—answering FAQs, checking order status, escalating angry customers to humans, and blocking unauthorized refunds.
• Document processing systems: the LLM extracts information from unstructured documents like invoices, contracts, and forms; the rules layer handles validation—checking required fields, verifying dates and amounts, flagging missing information, and rejecting invalid formats.
• Fraud prevention systems: the LLM handles messy data and ambiguous signals, while the rules layer makes deterministic decisions and serves as the fallback.
• AI compliance assistant: the model "explains policy"—summarizing policy text and interpreting regulations—while deterministic logic "enforces policy"—checking approval conditions, restricting sensitive operations, applying access controls, and escalating compliance risks.
• Workflow automation: the LLM understands requests, resolves ambiguity, and decides next steps; the rules layer governs flow and permissions to keep execution safe, classifying incoming tasks and routing them accordingly.

Why it matters

The core takeaway from this thread: LLMs bring natural interaction and the ability to make sense of unstructured data, while business predictability, safety, and compliance boundaries should be guaranteed by deterministic rules. For teams building production-grade AI systems, this division—"the model handles flexibility, rules handle the safety net"—is a reusable architectural design principle.

2026-09-16 ~ 2026-09-16 · 6 related posts

• [source] 5 AI Systems That Combine Deterministic Rules with LLM Flexibility — goyalshaliniuk · 2026-09-16
• [source] 5 AI Systems That Combine LLM Flexibility With Deterministic Rules — goyalshaliniuk · 2026-09-16
• AI Customer Support: LLM Understands Users, Rules Decide What It Can Do — goyalshaliniuk · 2026-09-16
• LLM Handles Flexibility, Rules Enforce Accuracy: Fraud and Document AI Patterns — goyalshaliniuk · 2026-09-16
• AI Compliance Assistant: LLM Explains Policy, Deterministic Logic Enforces It — goyalshaliniuk · 2026-09-16
• [source] Design pattern: LLMs handle ambiguity while deterministic rules enforce safe execution — goyalshaliniuk · 2026-09-16