HR workflows often involve highly sensitive information, making them one of the highest-stakes environments for AI agents. Building an HR agent for real-world use takes more than effective prompting. It requires a secure architecture that limits access, reduces data exposure, and makes agent behavior more predictable and auditable.
In this code-along webinar, Calen Bedford, Security Architect at Insight Global, will walk through how to build an HR-focused AI agent in Claude Code using security-first design patterns. You’ll learn key principles for designing agents that handle sensitive data, including permissioning, tool boundaries, and the safe handling of inputs and outputs. By the end of the webinar, you’ll leave with a practical blueprint for building agents that can operate responsibly in HR and other high-risk domains.
Key Takeaways:
- Learn how to build AI agents in Claude Code for real enterprise workflows, with a focus on context engineering to improve relevance, control, and reliability.
- Understand security-focused agent architecture patterns for handling sensitive data, including permissioning, tool boundaries, and context isolation.
- Build an HR AI agent prototype designed to minimize risk, limit data exposure, and produce useful, auditable outcomes.
