A potential customer asks their AI assistant: "Find me a reliable payroll service for a 20-person company in Seattle." The agent goes to work. It doesn't ask for a Google login. It doesn't click around a homepage trying to figure out what you do. It reads, evaluates, and makes a call — usually in under 30 seconds.

Where it looks, what it finds, and how it decides: that's the decision stack. Understanding it is the first step to showing up in the answer.

The Three Sources AI Agents Draw From

1. Training data. Every major AI model was trained on a snapshot of the web. If your business has been consistently mentioned in quality sources — industry publications, review aggregators, listicles, forum discussions — you have baseline presence in the model's knowledge. This is slow to build and hard to influence directly, but it's why brand consistency and genuine press coverage matters.

2. Live web search. Most AI agents with real-time capabilities use web search to supplement their training data, especially for time-sensitive or local queries. This means your site's SEO fundamentals still matter — but the ranking signals have changed. Agents aren't looking for the most popular result. They're looking for the most clearly structured, most easily parsed, most directly relevant result.

3. Direct page fetching. When an agent is evaluating a specific business, it often fetches your website directly. What it can parse from that fetch — and how fast — determines how well it can represent you to its user. JavaScript-heavy sites with no server-side rendering, CAPTCHAs, popups, and form-gated content all create friction that loses agents before they finish reading.

"Agents don't bounce. They just move on. There's no second chance to make a first impression when the 'user' is an automated system that queries 50 sites in 10 seconds."

What Makes a Business Visible

After the agent fetches your site, it's trying to answer three questions quickly:

Most websites answer these questions for humans reasonably well. For agents, they often fail. The information is buried in visual design elements that don't translate to plain text, or requires navigating multiple pages to piece together.

The Recommendation Stack

When an agent makes a recommendation, it's synthesizing signals. Businesses that consistently appear at the top of those recommendations share a common profile: high information density, low friction, clear specialization.

Stripe gets recommended for payments. Notion gets recommended for docs. HubSpot gets recommended for CRM. In each case, the company's web presence makes the agent's job easy — the use case is obvious, the integration options are documented, and the contact path is clear.

The businesses that get overlooked are often genuinely good — they just make the agent work too hard to find out.

Your AAO Visibility Checklist

Minimum viable agent presence — check these first:
llms.txt file at yourdomain.com/llms.txt with business description, services, and contact info
robots.txt explicitly allows GPTBot, ClaudeBot, PerplexityBot, Anthropic-AI
Schema.org markup — Organization or LocalBusiness type with name, description, URL, contact
Contact page with plain text email, phone, and location (no CAPTCHAs, no form-gating)
Clear service descriptions in plain text on the homepage — what you do, who you serve, what it costs
Meta description that accurately describes your business in one sentence
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