The agent successfully assembled a comprehensive explanation of Postman by combining web search results with attempted direct fetches of the marketing site. The main postman.com pages returned only JavaScript-rendered HTML that was not readable by the agent, forcing heavy reliance on web search and prior knowledge (71%) to fill the gaps. The agent delivered a satisfactory answer despite the site's poor machine-readability, using search results, documentation links, and external comparisons to construct the final response.

• ›Steps [1]–[7] attempted to fetch postman.com directly but returned only truncated, JavaScript-heavy HTML boilerplate with no actual content rendered. The agent recognized this limitation at step [8] and pivoted to web search.
• ›Step [9] (search for 'Postman API platform what is it 2026') returned Gartner reviews and Wikipedia links that provided definitional and market-position data; step [10] (pricing search) pointed to postman.com/pricing and learning.postman.com/docs/billing/about-plans; step [11] (alternatives search) returned external comparison articles from Abstracta and Medium that structured the competitive landscape.
• ›Step [13] fetched learning.postman.com/docs/billing/about-plans from the search results but also returned unreadable JavaScript, so no new content was extracted there.
• ›The agent did not receive machine-readable pricing details, feature matrices, or use-case descriptions directly from the site; it reconstructed these from search result snippets, blog mentions, and external third-party analysis. The agent explicitly flagged uncertainties (free-tier request limits, AI credit mechanics, enterprise pricing) that were not publicly specified on the site.
• ›All eight sources cited in the final response's Sources section were either search results ([9]–[11]) or URLs surfaced by those searches. The site itself was not machine-traversable, so the agent had to rely on web search as a proxy for site content.
• ›The site's current structure (heavy client-side rendering without server-side HTML content) makes it nearly impossible for agents to extract facts directly; the agent defaulted to prior knowledge and search-sourced intelligence, achieving a satisfactory outcome despite poor site navigability for automation.