The LavaCon Content Strategy Conference | 25–28 October 2026 | Charlotte, NC
Brianna Stevens-Russell

Brianna Stevens-Russell has been a consultant at Comtech Services for ten years. She specializes in helping clients with their DITA implementations. From information modeling to DITA Open Toolkit publishing transforms, she works in all parts of a DITA environment. In addition to consulting with individual companies, she also enjoys training professionals to learn these skills and become the experts within their teams.

Welcome to the Company: Hiring, Managing, and Firing AI Employees

Co-presented with: Amanda Patterson

Stop Building Bots! Start Hiring AI Employees! Most organizations approach AI agents as tools. That mindset is already limiting scale, safety, and trust. By reframing AI agents as employees that you must hire, onboard, manage, review, and eventually retire, bots move to agents to integrated members of the team.

Participants will learn how to write clear “job descriptions” for agents, design onboarding prompts that encode organizational standards, and evaluate agent performance using measurable criteria. We will explore access control, escalation paths, probationary sandboxes, bias and compliance considerations, and the tradeoffs between specialist and generalist agents.

The workshop concludes with strategies for offboarding agents cleanly to preserve auditability and institutional knowledge. Attendees will leave with a practical, HR-inspired framework for building AI agent ecosystems that are governable, explainable, and scalable. Please bring laptops to this session.

 

In this workshop, attendees will learn how to:

  • Define and scope AI agents as accountable organizational roles, using job descriptions that clearly specify responsibilities, authority, and prohibited behaviors.
  • Evaluate and govern an agent’s knowledge and access, applying training-data review, and escalation paths to reduce risk.
  • Measure and manage AI agent performance over time, using practical metrics and review criteria to assess quality, cost, and trustworthiness.
  • Apply lifecycle management practices to AI agents, including role specialization decisions and clean offboarding with auditability.