The agent successfully gathered comprehensive information about Lienzzo's business model, services, and positioning by discovering and parsing machine-readable markdown and llms.txt resources. The site proved highly navigable for AI agents through structured markdown endpoints and an AI-specific index file, though traditional HTML pages returned 404s, forcing reliance on these alternate formats. The agent delivered a complete, well-sourced answer covering what Lienzzo does, who it serves, its pricing structure, and key differentiators.

• ›Step [6] (index.md) and step [10] (llms.txt) provided the foundational company info, philosophy, and track record in machine-readable form—the site explicitly publishes these resources for AI consumption, signaling intentional agent-readiness.
• ›Steps [12], [13], [15], [16] (markdown versions of service pages) contained all the detailed content about diagnostics, solutions catalog, specific examples, and team philosophy. The agent discovered these by inferring the `.md` pattern from llms.txt's explicit documentation (step [10] said 'Cada página de la web tiene su versión markdown añadiendo `.md` al final de la URL'), not by following visible site navigation.
• ›Traditional navigation paths failed (steps [2], [3], [4], [7] all returned 404 or redirect pages), but the site's markdown layer and llms.txt index provided a complete alternate navigation surface specifically designed for machine agents. This is agent-optimized design: a second, non-HTML channel for structured data.
• ›Pricing information was deliberately incomplete in public-facing content—no solution-level pricing published, only the diagnostic range (€990–€2,500). The agent correctly identified this as intentional business design, not a gap in the site's discoverability.
• ›The site exposed implementation timelines, support costs, and case study scope as missing (agent noted these in the confusion section), but these are genuine product gaps, not navigation failures—the agent exhausted the available sources.