AI Architecture · Deep Dive
Rule-Based Logic and LLMs: Use Each for the Job It Does Best
The useful question is not whether a business should choose a language model or a rules engine. They solve different problems. MyOpsAgent combines flexible language capabilities with controlled business logic so the user experience can be natural without making important decisions depend on generated opinion.
Where Language Models Are Strong
Large language models are well suited to tasks such as:
- understanding a user's intent from natural language;
- extracting structured information from a conversation;
- finding and organising relevant context;
- summarising documents or business information; and
- explaining a structured result in language a person can understand.
These capabilities make complex systems easier to use. They do not automatically make the model the correct authority for permissions, safety constraints or deterministic operational decisions.
Where Controlled Logic Is Strong
Structured rules and deterministic evaluation are better suited to questions such as:
- Is this user permitted to perform this action?
- Does this resource have the required capability?
- Does a proposed schedule violate a hard constraint?
- Which valid recovery plan causes the least governed disruption?
- Has the approved action actually been executed and verified?
How MyOpsAgent Combines Them
MyOpsAgent can use conversational AI to understand what the user is asking and to present the answer. Identity, permissions, connected business state, tools and deterministic decision components sit behind that conversation.
This means a user can ask a normal-language question while the final controlled outcome still comes from the organisation's approved data, rules and constraints.
A Practical Design Rule
Use AI for ambiguity, language and explanation. Use explicit controls for authority, access and repeatable business decisions. The boundary between those responsibilities is more important than the label attached to either technology.