Tool Safety, Permissions, and Error Handling
Learn how to engineer safe and resilient AI agents by implementing prompt-based permissions, confirmation steps, and error-handling logic.
In our previous lesson, we successfully gave our AI the capability to use tools and act in the world. This new capability immediately introduces a new set of critical engineering challenges. An AI agent that can take actions, such as sending an email, modifying a database, or deleting a file, is inherently more powerful and carries more risk than one that only generates text.
This introduces an important distinction between a capable agent and a responsible one. A capable agent can perform a task correctly. A responsible agent performs that task safely, predictably, and with the required level of user oversight. As engineers, our job is not just to enable actions but to build the guardrails that ensure those actions are safe and effective.
This lesson focuses on the three core responsibilities of an engineer building a tool-using agent:
Permissions: How do we define and strictly control the set of actions an AI is allowed to perform?
Confirmation: How do we prevent the AI from taking sensitive or irreversible actions without explicit user consent?
Resilience: How do we ensure the AI behaves predictably and gracefully when its tools inevitably fail or return unexpected results?
We will learn the prompt engineering techniques and architectural principles required to build these guardrails, transforming our capable agent into a responsible one.
The principle of least privilege (PoLP)
The most fundamental rule of system security is to never grant more permission than is necessary. This concept ...