What is a Custom AI Agent?

General-purpose assistants are built to be broadly helpful across any topic a user brings; a custom agent is narrower and more capable at its specific job because it's given the exact tools it needs (a CRM connection, a specific set of file access, a defined escalation path) and instructions grounded in how a particular business actually operates, rather than generic advice. This specificity is what lets it complete a real multi-step task — like processing a refund request end to end — rather than just describing how one might do it. Building one well means defining boundaries as carefully as capabilities: what the agent is allowed to do autonomously versus what requires human approval, what data it can access, and what it should do when it hits a situation its instructions don't cover. An agent without clear boundaries either does too little (constantly asking for confirmation) or too much (taking consequential actions it shouldn't have autonomy over). The best custom agents are also observable — every action they take is logged in a way a human can review after the fact, since trust in an autonomous system depends on being able to verify what it actually did, not just what it claims to have done.