The agent assembled a functional explanation of JMI Equity by combining content from the site's core pages (homepage, about, value, responsibility, companies) with external search results, since the site itself lacks transparent pricing and competitive positioning. The site is navigable but sparse—key pages exist and load, but the HTML responses were truncated and the agent relied heavily on prior knowledge and web search to fill critical gaps around deal terms, fees, and differentiation.

• ›Steps [1, 3, 20, 21, 22] returned actual page content (200 responses) that confirmed JMI's identity as a growth equity firm, its focus on software/AI, portfolio size (180+ investments), and value-creation claims, but the HTML was truncated and did not expose detailed narratives or structured data.
• ›The site's navigation structure proved weak: direct guesses for /pricing, /portfolio, /services, /blog, /approach all returned 404s; the agent discovered pages like /value, /responsibility, /companies only by fetching and parsing the sitemap, indicating poor discoverability.
• ›The agent filled critical gaps (fee structure, investment process, differentiation vs. competitors) using web search [24, 25] and prior knowledge—not from jmi.com—because the site does not publish this information; this is cited in the final response as 'missing' rather than sourced.
• ›The site is hosted on WordPress with XHTML 1.0 Transitional doctype and a 'noimageindex' robots meta tag, suggesting legacy infrastructure that does not expose structured data (JSON-LD, schema.org) that would aid AI parsing.
• ›The agent succeeded despite friction because it correctly identified that jmi.com alone cannot answer the full task (pricing, alternatives) and explicitly called out what was missing rather than fabricating answers.