The agent successfully assembled a comprehensive explanation of Prezi by combining direct site fetches with web search results and prior knowledge. The site's marketing pages (homepage, about, product pages) provided positioning and high-level product descriptions, but pricing details and feature comparisons were incomplete from Prezi's own pages—requiring external sources (TrustRadius, third-party review sites, Prezi's blog) to construct a full picture. The site's React-rendered pricing page did not serialize cleanly into static HTML, forcing reliance on external sources for accurate pricing and plan details.

• ›The homepage and product pages (Present, Video, Design) provided basic positioning but lacked substantive feature details—agent had to infer product scope from page titles and navigation structure.
• ›The official pricing page (prezi.com/pricing and prezi.com/gts/pricing) rendered as React SPA without semantic HTML, making it unreadable to the agent; all concrete pricing data came from external review sites (steps 13, 14, 16), not Prezi's own pages.
• ›The agent successfully accessed /about, /product, /business, /video, /design, and /learn pages (all 200s), but these returned minimal extractable content in the trajectory logs—most substantive claims in the final response cite external sources rather than Prezi's own content.
• ›Web searches (steps 13, 14, 16) were critical to completing the task; they surfaced pricing comparisons, competitor analysis, and AI credit details that Prezi's own site did not clearly expose in fetchable form.
• ›The site does not publish structured data (schema.org, JSON-LD) for pricing or product offerings in a machine-readable form, requiring the agent to either parse client-side rendering or rely on third-party aggregators.
• ›The agent correctly identified key confusion points—pricing plan limits, team vs. individual plan differentiation, AI credit mechanics, and lack of PowerPoint export—but these came from external sources, not from Prezi's documentation.