Anton Andrusenko
Senior Product Manager in Ai Lab @Semrush
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WORK HISTORY
Senior Product Manager in Ai Lab @Semrush
Berlin, DE
Built and lead a team designing AI-native products - systems that leverage agentic reasoning, multi-step orchestration, and LLM tool use to solve problems that weren\'t viable to tackle before these capabilities existed.Personally architected and shipped agentic applications across the full stack - from system design and prompt architecture to deployment and user iteration. This isn\'t oversight of engineers building AI; it\'s building alongside them with technical accountability for the decisions that matter.Established the frameworks our team uses to evaluate AI bets honestly: distinguishing genuine capability from demo performance, identifying where models break in production, and knowing when to build versus when to wait for the capability curve to move.
EDUCATION
Moscow State University of Civil Engineering (MSUCE)
Master's degree, Software Engineering
ABOUT ANTON ANDRUSENKO
AI does make existing solutions better. However, what’s more it makes entirely different problems worth solving. The opportunity isn\'t defending what you have with AI - it\'s seeing what was previously impossible and building toward it.Most AI product work today is defensive. Take an existing workflow, insert a model, measure the efficiency gain. It\'s useful. It\'s also the wrong frame.I think about AI differently. When a genuinely new capability exists: autonomous reasoning, persistent agent memory, multi-step tool use, real-time synthesis across large contexts - it doesn\'t just improve what you were already doing. It makes an entirely different set of problems worth solving. Problems you couldn\'t have justified attacking before. Products you couldn\'t have built. User experiences that weren\'t physically possible.That\'s the space I work in.At Semrush I lead a team at AI Lab - a small, fast team building AI-native products from scratch, not retrofitting AI into legacy workflows. I\'ve shipped agentic systems personally: designed the architecture, built the pipelines, put them in front of real users, and iterated on what actually works versus what looks impressive in a demo. That hands-on building isn\'t a side project. It\'s how I maintain the judgment to lead a team doing this work - knowing where models genuinely fail, where agent orchestration breaks down at scale, where the interface between human and system needs to be redesigned from first principles.Thirteen years of product leadership across B2B SaaS, enterprise, and consumer gives me the other half of what this work requires: I know how organizations actually adopt new capabilities, how to translate a frontier technical bet into a roadmap a team can execute, and how to make a case for building something that doesn\'t have a comparable reference point yet.The combination - strategic product authority, genuine technical depth, and a forward-facing thesis about where AI capability is taking us - is what I bring to teams building at the edge of what\'s currently possible.If you\'re building AI-native products and thinking about what becomes possible in the next two years, not just what\'s defensible today, I\'d like to talk.
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