The agent successfully assembled a comprehensive explanation of Temporal by combining fetches from the main site (homepage, pricing, product pages) with targeted web searches to fill gaps and validate understanding. The site's main pages rendered as JavaScript-heavy HTML without meaningful content in the fetches, forcing the agent to rely heavily on prior knowledge (50%) and search results (13%) to construct the answer. Despite this friction, the agent delivered a well-structured, accurate breakdown of what Temporal does, who it's for, pricing tiers, and competitive positioning—all the elements the user requested.

• ›The homepage and primary pages ([1], [3], [18]) returned JavaScript-heavy HTML that did not expose readable content in the fetch responses, making them non-content-bearing. The agent cited them as sources anyway, indicating it may have relied on prior knowledge or had inferred their structure rather than extracted facts from the responses.
• ›Web searches ([11], [12], [13], [15], [16], [21], [22], [24], [25]) were the actual sources of substantive information: pricing details ($100/mo baseline, consumption models), use cases (payments, order fulfillment, customer onboarding), differentiators vs. Airflow/Prefect/Dagster, and architectural concepts (event sourcing, deterministic replay). The agent had to search for what should have been prominent on the marketing site.
• ›The agent proactively identified gaps in what it found (customer count, performance benchmarks, migration details, feature parity tables) and called them out explicitly in the 'confusing or missing' section, showing honest boundary-setting about what the site did and did not expose.
• ›The site's IA appears to segregate key information: product positioning on temporal.io/product, pricing on temporal.io/pricing, and deep technical details on docs.temporal.io/. The agent had to stitch these across multiple domains to answer the user's integrated question ('understand well enough to explain').
• ›Polyglot language support, deterministic replay, and the workflow/activity split were well-documented in search results but not easily discoverable from the main site fetches alone—the agent had to search for architectural differentiation.
• ›The agent correctly diagnosed the site's main weakness: marketing pages are JavaScript-rendered without server-side content, making them opaque to fetch-based retrieval. This forced a 'light bridge' outcome where the agent had to compensate with search.