An AI Agent is an assistant you set up for a specific job. The best agents are focused, grounded in your own knowledge, and connected to the tools they need. Here is how to build one that works for your team.
Start with one clear job
Resist the urge to build an agent that does everything. Pick a narrow, repeatable purpose, such as answering questions about how your team handles client onboarding or drafting a first pass of a recurring update.
A focused agent is easier to test, easier to trust, and easier for your team to adopt.
Define the role
Give your agent a clear purpose and responsibilities. Describe who it helps, what it is expected to do, and what a good answer looks like. The clearer the role, the more consistent the results.
Add knowledge
Train your agent on the documents, data, and resources it needs for its job. Start with the material your team already points people to: guides, policies, playbooks, and answers to common questions.
Grounding an agent in your own knowledge helps its answers reflect how your business actually works. For more on choosing and maintaining sources, see Bring your knowledge into Cohrt.
Set skills and behavior
Choose the expertise, tone, and working style your agent should bring. A support agent might be friendly and concise; an agent that helps with proposals might be thorough and formal. Match the behavior to the people it serves.
Connect tools
Integrate the systems your agent can use, so it can work with the information your business relies on. Connect only what the job requires.
Test with real questions
Before you share your agent, try it with the questions your team actually asks today. Note where answers are strong and where they miss, then refine the role, knowledge, or behavior. A few rounds of testing go a long way.
Share it with your team
When you are happy with the results, share the agent with the people who will use it. Ask for feedback in the first few weeks and keep improving it.
Ready to go further? Roll out AI to your team responsibly covers approved models, visibility, and cost control.