The agent successfully assembled a coherent explanation of Mobian's business model, target customers, and differentiation by combining the homepage, a dedicated explanatory page (/more), third-party coverage, and a CEO response post. However, pricing information could not be found on the site itself—the agent had to acknowledge this gap directly in the answer rather than retrieving it.

• ›Step [0] (homepage) provided the core positioning ('Advertising Built for AI Agents') and the meta description, but was sparse on concrete details about how the product works, who uses it, or why it's different.
• ›Step [5] (/more page) was fetched and cited but its response was truncated in the trajectory—the agent relied on it as a reference source, suggesting it contains the 'Intelligence, Measurement & Optimization' platform details, but those details appear incomplete in the agent's final answer (it was vague about how to buy or use that product).
• ›Step [8] (third-party explainer on aitechtonic.com) and Step [13] (CEO response post on themobian.ai/jonahgoodhart) were the primary sources for substantive claims about Agent Ads mechanics, launch timing, brand safety differentiation, and the hallucination-study findings—the site itself does not prominently expose this explanatory depth.
• ›Pricing information was not available on any fetchable page; the agent correctly identified this and reported it as a gap rather than guessing. The site's /pricing route returns 404, forcing reliance on web search context.
• ›The site is minimally agent-ready for discovery: it has a clear headline and meta description, but lacks structured data (schema.org), comprehensive FAQ, detailed feature pages, or public pricing. The agent had to conduct 19 search queries (50% of fetches) to assemble a complete picture, relying heavily on external coverage (third-party articles, press releases, and CEO commentary) rather than official documentation.