The agent successfully assembled a comprehensive understanding of Alvado by working around an inaccessible website. The main alvado.fr domain returned only raw HTML/JavaScript with no readable content, forcing the agent to rely on web search results and alternative domains (remi.alva.do, alva.do, academie.alva.do) to piece together Rémi Alvado's services, target audience, and positioning. The site's single-page app structure and lack of standard navigation pages (pricing, services, about) made direct navigation difficult, but search results and related domains provided enough surface area to answer the core task—though pricing information remained completely unavailable.

• ›The main alvado.fr homepage (steps [1], [3]–[8]) returned only minified JavaScript and CSS with no rendered content visible in the HTML source, making it unreadable to the agent without JavaScript execution.
• ›Standard navigation attempts (/pricing, /about, /services, /tarifs, /offers, /blog) all returned 404s, indicating either a single-page app with client-side routing or intentionally sparse structure; no public pricing or detailed service pages were accessible via direct URLs.
• ›Search results (steps [10], [13], [16], [17], [18]) became the primary information source, revealing Rémi Alvado's background, services (fractional CTO/CPO, bootstrap MVP, coaching, AI training), and positioning; these searches surfaced related domains and LinkedIn profiles that contained more readable content.
• ›Alternative domains like remi.alva.do and alva.do appeared to be mirrors or related properties but were not explicitly linked from alvado.fr; the agent had to discover them through search to access more readable content.
• ›Pricing was deliberately absent from all publicly accessible pages—no rates, packages, or engagement models were published, requiring the agent to rely on industry benchmarks and context rather than the site itself.
• ›The Alvado Academy (step [15]) returned a page but required login/enrollment to see course details, gating key information about training offerings.
• ›The agent synthesized information from search snippets, LinkedIn inference, and industry context to answer the task; very little of the final answer came directly from rendered alvado.fr content.