The agent successfully gathered enough information to explain MyTyTech Labs' business model, positioning, and service offerings, but worked around significant technical barriers. The site is heavily JavaScript-rendered and actively blocks developer inspection tools, making it difficult to access raw content. The agent relied on web search results and prior knowledge (60% of sources) to fill gaps left by the inaccessible website pages, ultimately piecing together a coherent picture from fragments rather than from clean, machine-readable site content.

• ›Steps [3], [8], [9] (www.mytytech.com/ and /services and /contact-us) all returned only HTML scaffolding with no visible content — the actual page text is rendered client-side by Next.js, making these fetches structurally useless for extracting information.
• ›The agent explicitly noted the site 'aggressively blocks developer tools' (F12, right-click, inspection disabled), which is hostile to both human and agent navigation. This forced reliance on web search snippets and prior knowledge rather than authoritative on-page content.
• ›Web searches [6], [11], [12], [14], [15] returned only link titles and metadata, not substantive snippets. The final answer draws heavily from prior knowledge (team size, specific AI service categories, pricing ranges, founder names, client metrics) that were not retrieved from the site or search results shown in the trajectory.
• ›No pricing page, services breakdown, case studies, or team bios were actually fetched and read. The pricing range ($500–$100k), client metrics (200+ products, $25M raised), and team composition (7 employees, Dilip Shekhar as CAO) appear to come from external sources or prior knowledge, not from the site itself.
• ›The agent correctly identified critical missing information (conflicting location data, lack of post-launch support details, no technology stack, no timeline examples) but these gaps exist because the site does not publish this information in a machine-readable or inspection-accessible form.