I returned from Web Summit Rio 2025 a few days ago. This year, every track and session at the conference centered on AI. Previously, AI was discussed primarily as a helper, a tool to assist human experts. Now, the focus has shifted toward full automation of production cycles.
The Emergence of the AI-Methodologist
The core of this shift in EdTech is the emergence of the AI-methodologist. More than a vision, it is a functional role already implemented in multiple products. The AI-methodologist addresses the most time-consuming and expensive phase of building any educational program: developing methodology, content, and assessment systems. Historically, creating a high-quality course required months of work by teams of subject-matter experts, instructional designers, and editors. Today, several startups demonstrated at Web Summit Rio how this process can be reduced to hours or even minutes.
What the AI-Methodologist Does
The AI-methodologist operates on unstructured inputs such as webinar recordings, PDFs, draft notes, and diagrams, and outputs structured learning materials:
- Long-form articles and video scripts
- Exercises, slide decks, and flashcard sets
- Practical assignments: quizzes, open-ended questions, problems at multiple difficulty levels
- Case studies derived directly from source content
It also designs assessment logic, not just summaries or paraphrases.
Solving the Cold Start Problem
This resolves the cold start problem in EdTech product development. Launching a pilot course in a new IT discipline no longer requires assembling a team of methodologists upfront. One domain expert and a well-configured AI pipeline are sufficient. If market demand is confirmed, production-ready materials can be generated within days.
Startups Showcasing the Pattern
At Web Summit Rio, this pattern was visible across several startups:
- VideoHub AI extracts mind maps, e-books, and quizzes directly from video content, reducing content production time by 70%.
- LessonAI enables teachers to generate lesson plans and exercises tailored to a specific class and topic.
- Hands-on Creator allows visual course assembly where AI acts simultaneously as methodologist and designer.
What This Means for EdTech Operations
These tools reflect a broader operational shift: from a model where teams invest months in content creation before testing demand, to one where market hypotheses are validated quickly using AI-generated drafts, with scaling applied only to what demonstrates traction.
Practically, this means a radical reduction in the cost and time required to test new educational offerings. The bottleneck is no longer content production; it is expert input and validation. The industry is moving toward a workflow where human expertise defines direction, and AI executes the bulk of methodological and production work.
