Two Agents Are Better Than One: Our Multi-Agentic Approach to Review Response

Responding to online reviews at scale is harder than it looks. Every response needs the right tone, has to follow compliance rules, should feel personal, and ideally shouldn’t take a human hours of work to produce. Multiply that by hundreds of reviews a week, and the math gets ugly fast.

We tried the obvious solution first: hand the job to a single AI agent. Write a prompt, feed it the review, and get a response. Simple. It mostly worked. But “mostly” isn’t good enough when a bad response can damage a property’s reputation or violate a policy. So we rebuilt the system using a multi-agent workflow, and the results have been significantly better.

Here’s how it works, and why we think more teams should be thinking this way

What Are Multi-Agent Workflows?

A multi-agent workflow is exactly what it sounds like: multiple AI agents working together, each with a narrow, well-defined job. Instead of asking one agent to do everything, you break the task into stages and assign a specialized agent to each one.

Why does this work better than a single agent? A few reasons. Focused prompts produce focused outputs. Each agent can be evaluated and improved independently. And critically, separating tasks like “do the work” and “check the work” tends to surface mistakes that a single agent reviewing its own output will miss.

Common patterns include writer/reviewer setups, planner/executor pairs, and researcher/synthesizer chains. Our review response system uses the first of these.

Our Two-Agent System

Agent 1: The Writer

The writer has one job: draft a response to the review. It takes in the review content along with context about the business, then produces a reply.

But drafting a good review response isn’t just about writing something polite. The writer has to make real decisions on every pass:

• Should contact info be included, and if so, what kind?
• Are there business-specific instructions it needs to follow (certain phrases to avoid, a particular sign-off, escalation language for complaints)?
• What tone fits this specific review and this specific business?

We’ve put a lot of work into giving the writer the context it needs to make these calls well. But even a strong writer agent makes mistakes. Which brings us to the second agent.