In this article, you will learn how to design, scale, and secure tool calling in AI agents so that the layer connecting model reasoning to real-world action holds up in production.
Topics we will cover include:
- How the tool calling protocol separates model reasoning from deterministic execution, and why that boundary matters.
- How to write tool definitions, error handling, and parallelization strategies that stay reliable as your agent scales.
- How to manage tool catalog size, secure agentic systems, and evaluate tool calls beyond end-to-end task success.
