The agent assembled a comprehensive explanation of AWS by working around the site's JavaScript-heavy rendering. Direct aws.com fetches [1–7, 13] returned unintelligible HTML; the agent pivoted to web search [9–11] to find authoritative external sources (AWS whitepaper, Wikipedia, comparison articles) and fetched the AWS documentation whitepaper [14], which provided concrete service and positioning details. The marketing site itself was not navigable; the agent succeeded by treating it as a discovery signal and relying on off-site documentation and third-party comparisons.

• ›Steps [9–11] (web searches) returned URLs and snippets that pointed the agent to actionable resources: the AWS whitepaper, Wikipedia, and comparison articles. The search result snippets themselves did not contain full answers, but the links were the routing to content-bearing resources.
• ›Step [14] (AWS whitepaper fetch) returned structured documentation that directly answered 'what is AWS,' service categories, and who it's for—this was the primary content-bearing resource for the 'what' and 'who' portions of the task.
• ›Steps [1–7, 13] (direct aws.com marketing pages) returned only HTML scaffolding with no text content visible in the response. AWS's main website is heavily client-side rendered and not machine-readable; the agent could not extract marketing positioning, pricing detail, or differentiation directly from the site.
• ›The agent had to rely on prior knowledge and web search to assemble pricing models and competitive differentiation [10–11]; these were not comprehensively available in a single AWS-published source the agent could fetch.
• ›The final answer cites external sources (Wikipedia, third-party AWS pricing explainers, and comparison articles from Coursera, Google Cloud, DataCamp) more prominently than AWS's own marketing site, reflecting the site's poor agent-readiness.