The agent only successfully retrieved two pages from beneathatree.com (homepage and /our-people), with the homepage serving as the primary source. Unable to navigate the site's internal structure to find pricing, services, or detailed offerings, the agent assembled most of its final answer from prior knowledge (57% of sourcing) and web search results that did not contain BeneathATree-specific information. The site proved poorly navigable for machine discovery: no pricing page, no services page, no portfolio or case studies accessible, and limited structured content in the pages that did load.

• ›Step [1] (homepage fetch, 200 OK) appears to be the only content-bearing page fetch; it likely contained the core tagline ('Lean MVPs to enterprise-ready products'), team names (Sachin Shyam Phatak), and mission statements. Step [3] (/our-people) was fetched but not explicitly cited in the final response, suggesting it was retrieved but yielded limited usable content.
• ›Steps [4–8] all returned 404s (/pricing, /services, /work, /about, /contact), indicating the site's navigation structure is either not standard or not discoverable via common URL patterns. The agent had to guess at these URLs rather than follow internal links, suggesting the homepage does not expose a clear site map or navigation menu that would prevent these failures.
• ›The agent's final answer draws heavily on prior knowledge about what BeneathATree does (social enterprise, JavaScript stack, MVP focus, values-driven) rather than from fetched content. Web searches [10–20] returned generic industry articles or LinkedIn profiles, not BeneathATree-specific pricing or case studies. The 57% prior-knowledge sourcing and 43% previous-artifact sourcing indicate the agent relied on its training data, not the live website, for most factual claims.
• ›The site is not agent-ready for discovery tasks: no public pricing (acknowledged as missing in the final response), no detailed service descriptions, no case studies or portfolio, and no structured data (schema.org, meta tags) that would expose these details to an LLM. The agent had to recommend a Calendly link and Upwork profile as workarounds, neither of which are on the fetched pages.