The Problem with Raw LLMs
Large language models are incredible at generating text. They are not, however, inherently good at making decisions. When you send a user query directly to Claude or GPT, you're asking a text predictor to perform business logic — and that's a category error.
The Think Engine Layer
At Legenyx, we introduced a Think Engine between the user and the model. This layer:
- Classifies intent before the model ever sees the query
- Routes to the appropriate agent or workflow
- Enriches the context with structured memory
- Applies business rules, feature gates, and monetization logic
Results
By separating decision-making from generation, we reduced incorrect agent routing by 94% and improved response relevance scores by 40% across all deployments.
What's Next
We're expanding the Think Engine to support multi-agent orchestration, where decisions cascade across specialized agents for complex enterprise workflows.