How to build AI agents
The hands-on directory of deployable AI agent patterns — capabilities, permissions, setup difficulty, and when to buy vs build with Ekofi Lyrae.
Most “AI agent” pages sell magic. OperatorRadar catalogs scoped systems you can actually run: trigger → tools → draft or action → human approval when it matters. Browse patterns below, then implement in-house or with Ekofi Lyrae.
An AI agent is a scoped system that takes a trigger, uses tools or context, and produces an action or draft — with a human approval gate when the stakes are high. It is not a chatbot you babysit all day.
Pick one painful workflow (support triage, lead qualification, churn signals). Define inputs, tools, and the approval step. Ship a thin version in a week, measure failure cases, then expand. OperatorRadar catalogs patterns; Ekofi Lyrae implements production agents.
Use deterministic automation when rules are stable. Use an AI agent when language, judgment, or messy inputs matter. Use a chatbot only for Q&A. Most operator wins are agents wrapped around clear CRMs and tickets — not open-ended chat.
Buy or copy a pattern when the workflow is common. Hire implementation (like Ekofi Lyrae) when the agent must live inside your stack, permissions, and evals — and you cannot afford weeks of DIY glue.
Clear scope, tool permissions, human approval on irreversible actions, logging, and an eval set of real examples. Without those, you have a demo — not an operator system.