The agent successfully understood lecturer.fr's core offering—instructor logistics automation for French educational institutions—by assembling information from the homepage, pricing, and about pages, then contextualized it against general education software alternatives via web search. The site provided clear high-level positioning but lacked detail on technical differentiation, customer validation, and publicly quoted pricing.

• ›The homepage [0] and about page [3] clearly explained what lecturer.fr does and who founded it, but provided limited specifics on how the AI matching algorithm (LIA) actually works.
• ›The blog [4] was the richest source of domain insight, revealing the real pain points (2-4 days per instructor, 80 hours/week coordination work) that justified the product—information not present on marketing pages.
• ›Pricing information was explicitly designed to be opaque: the /pricing page [1] stated pricing is given 'during the demo once we understand your organization,' making cost comparison impossible from the website alone.
• ›The agent discovered two dead URLs (/product [2] and /customers [5]) that would have clarified product architecture and provided social proof; these absences forced reliance on inference rather than direct evidence.
• ›Web search [7] returned general education software alternatives (Google Classroom, Canvas, Moodle) rather than France-specific instructor logistics competitors, requiring the agent to infer positioning differences without comparative data.