The agent partially fulfilled the task of explaining Walter to someone else. It successfully identified Walter's core concept (AI agents for construction documentation) and positioning from homepage metadata and navigation anchors, but the site's JavaScript-heavy design prevented full access to feature details, pricing, and competitive differentiation. The agent had to rely on prior knowledge and failed web searches to fill gaps, since critical information pages (pricing, about, detailed features) either returned 404s or required client-side rendering that the fetcher couldn't execute.

• ›Steps [1], [4], and [6] returned HTML with metadata (title, meta tags, navigation classes like #workflows, #how-it-works, #trust, #faq) that revealed Walter's positioning as a 'Construction Brain' for RFIs, submittals, change orders, and pay apps, but the actual content was hidden behind JavaScript rendering.
• ›The site's routing structure is minimal: /pricing, /about, /contact, /blog, /faq all returned 404 errors, indicating either a very new product with incomplete site structure or a single-page app that doesn't expose these sections as traditional URLs. The agent guessed these URLs rather than discovering them through navigation.
• ›The agent could not access detailed feature comparisons, pricing tiers, customer testimonials, or company background—all typical discovery-evaluation content. It had to synthesize positioning from navigation anchors and class names alone, then resort to web search, which returned results for unrelated products (Walter Writes AI, other construction tools) rather than buildwithwalter.com specifically.
• ›No structured data (schema.org, JSON-LD) was visible in the fetched responses, and the site does not appear to publish a public pricing page, API documentation, or competitive positioning guide in machine-readable form.