Building the Agentic Core: STT to LLM to Intent Mapping

Wed, 06 May 2026 00:00:00 +0000

In this chapter, we’re building the brain of our on-device AI agent: the core pipeline that translates user speech into actionable intents. This involves taking transcribed text, feeding it into a tiny, local Large Language Model (LLM), and then extracting a structured understanding of what the user wants to do. This is a critical step towards enabling truly intelligent, privacy-preserving interactions on edge devices.

By the end of this milestone, you will have a functional Python script that can:

Intent Recognition on AI VOID

Building the Agentic Core: STT to LLM to Intent Mapping