Definition
AI agent
An AI agent is software that uses an AI model to pursue a goal across multiple steps, taking actions and reacting to results, rather than answering a single question and stopping.
A plain Large language model (LLM) responds once to a Prompt and stops. An agent wraps that model in a loop: it decides what to do next, calls a tool (looks something up, sends a message, writes a record), reads the result, and keeps going until the goal is met. The practical difference is between a model that tells you how to book a table and one that actually checks the book, offers a time, and writes the reservation.
Agentic behavior is what turns AI from advice into work done, which is where it earns its keep for a short-staffed team. A phone agent (Voice AI) that answers, confirms availability, and books is an agent. A marketing agent that finds lapsed guests and sends a win-back text is an agent. This is the direction restaurant software is moving, though adoption is still early: only 26% of operators report using AI at all today, so the operators who deploy it well have a real head start.
Be clear-eyed: an agent that can take actions can take wrong ones, so the useful ones run on rails. They get a fixed set of allowed actions, a human reviewing anything risky (a refund, a comp, a promise to a guest), and grounding through Retrieval-augmented generation (RAG) so decisions rest on your real data rather than a guess. An unsupervised agent is a liability; a bounded one is a force multiplier. See AI reservations.
See it in action
Your next service / Ready when you are
Less busywork. A better next shift.
Turn what you have learned into a focused brief. Start with the job that matters most, and keep the tools that already work for your restaurant.
Describe it. Review it. Keep improving it. Check connections and costs before going live.