The agent assembled a partial understanding of Char by combining homepage metadata, Y Combinator's company profile, a blog post about the Anarlog/Char product split, and web search snippets. The site itself was poorly navigable for this task—key pages like /pricing and /features returned 404s or redirect-only content, forcing heavy reliance on external sources (YC profile, Product Hunt, Anarlog blog) and prior knowledge to answer who it's for, what it does, and how it differs from competitors. Pricing and access details remain obscured; the agent correctly flagged these gaps.

• ›Step [1] (homepage) and step [26] (search snippet to YC page) provided the core product description ('AI task delegation notepad', 'autonomous agent picks up checkboxes'), but this came from meta tags and external sources rather than page body content.
• ›Step [11] (YC company profile) was the most authoritative content-bearing step, providing founding team names, location, employee count, and positioning—information not available on char.com itself.
• ›Step [7] (Anarlog blog explaining the product split) was critical for understanding the Char/Anarlog distinction and the shift from meeting notes to task delegation, but this explanation lives on a *different domain* (anarlog.so), not on char.com.
• ›The site's navigability failures: /pricing redirects to Anarlog content (step [2], [20]), /features and /about return 404s (steps [3], [4]). No pricing, launch timeline, or signup mechanism is accessible on char.com.
• ›The agent had to rely on prior knowledge (21%), web search (29%), and artifacts from previous fetches (50%) to construct the answer because char.com does not expose the required information in a machine-readable or direct way.