The agent successfully built a comprehensive overview of Telstra by navigating the site's main sections (homepage, About Us, Mobile, Broadband, Business, Enterprise) and supplementing with web search results. However, the site itself proved poorly agent-readable: it served mostly JavaScript-heavy pages without explicit pricing, service descriptions, or differentiation content in the initial fetches. The agent had to rely heavily on prior knowledge (33% of sources) and news articles (via web search) to answer pricing and competitive positioning questions that should have been directly available on the site.

• ›Steps [1], [3], [4] returned valid 200 responses but truncated to generic HTML scaffolding with no visible content in the fetches—pricing, plan details, and service descriptions were not present in the raw page source, indicating heavy client-side rendering that made the pages opaque to direct fetching.
• ›Steps [2], [7], [9] (About Us, Business, Enterprise pages) similarly returned only HTML structure without meaningful content, forcing the agent to infer service offerings from URL patterns and prior knowledge rather than reading actual page content.
• ›The agent had to conduct four separate web searches (steps [6], [8], [10], [11], [12]) to find pricing, competitor analysis, and service details—indicating that telstra.com.au itself does not surface this information in a machine-readable or easily extractable form. The final answer cites external sources (Forbes, news articles, comparison sites) rather than content pulled directly from Telstra's pages.
• ›The agent's own final response explicitly calls out confusion points: lack of pricing transparency on the website, plan complexity without clear differentiation, missing bundle savings calculators, and unavailable enterprise pricing—all evidence that the site structure does not publish critical decision-making information in discoverable, agent-accessible form.
• ›67% of the agent's sources came from 'previous_artifact' (prior knowledge reassembled), meaning the agent reconstructed Telstra's positioning from general knowledge rather than learning it from the site itself.