ELVTR bets live classes from working pros beat university — 90% finish (interview)

Short, intensive, entirely online live courses across AI, product, design, data and creative industries, taught by industry practitioners and built around practical workflows, with hands-on assignments and direct feedback.

Roman Peskin grew up with ADHD, was kicked out of preschool, and hated university lectures. He founded ELVTR inside the LABA Group ecosystem; it has operated independently since 2020.

ELVTR builds courses by recruiting practitioners and training them: 'We have a strong instructional design team that helps extract their knowledge and turn it into a curriculum. Our instructors are not educators — they're professionals doing their jobs.' All classes are live: 'If it's Wednesday at 7 pm, you log in. That structure forces attention.'

As of March 2026 the company reports scaling to thousands of students across multiple industries and says it is starting to measure long-term career outcomes more systematically. Peskin's own verdict on universities: 'They must integrate AI. Otherwise, they risk becoming irrelevant.'

Live scheduling solves the attention problem that kills recorded courses — 'my own pace is zero if I'm not interested'.

Practitioner faculty give students current workflows and tacit knowledge 'that simply aren't in textbooks', plus industry credibility no academic can offer.

Niche careers with no degree path (game writing, UX for games) face zero competition from universities and scarce alternative instruction.

Completion rates near 90% are the product: outcomes depend on finishing, and finishing is what the format is engineered to force.

When content is free, structure becomes the product: scheduled live sessions and credible practitioners convert attention into completion in a market where recorded courses lose 85-90% of learners.

As of March 31, 2026, ELVTR reports 100+ courses, over 10,000 students trained in the past year, and is beginning to measure long-term career impact systematically. Peskin predicts education 'will change dramatically in the next five years' and argues universities still provide structure, network and signalling — but must integrate AI or risk irrelevance.