Building AI Agents with Tool Use
Designing LLM-powered agents that can interact with external tools and APIs.
Overview
AI agents extend LLMs beyond text generation by giving them the ability to use tools, call APIs, and make decisions. This post covers the architecture of tool-using agents.
Agent Architecture
Core Components
1. LLM Brain: The reasoning engine. 2. Tool Registry: Available tools and their schemas. 3. Memory: Conversation history and state. 4. Orchestrator: Decision loop for tool selection.
Tool Definition
Each tool needs a clear schema defining its input, output, and description for the LLM to reason about.
Challenges
Hallucination in tool selection requires input validation. Infinite loops need maximum iteration limits. Cost management benefits from caching common tool results.