SergeiMaslennikov
Hi, I'm Sergei. Navigator by degree, sports-data nerd by habit, AI builder by choice.
Grew up by the sea in Pärnu
Don't feel like reading all this? Ask my digital twin anything, it's more talkative than me.
It knows my background, projects and opinions, and speaks English, Estonian and Russian. If it gets stuck, it pings my phone and I can jump into the chat myself.
Ask the twin →Log 03 · About
I used to navigate ships. Then I spent ten years reading tennis matches like spreadsheets. These days I try to make LLMs do useful things and read the Stoics when the code won't cooperate.
I trust data more than my gut, mostly because sports data showed me how often my gut is wrong. I also think time and attention are the only things you can't buy back, so I like handing boring work to machines. That's how I ended up building with LLMs.
The route so far
Deck Officer
Watchkeeping on container ships.
Independent Quantitative Analyst — Sports Markets
Ten years of reading tennis and volleyball matches like spreadsheets.
A break
I decided to take a break and reconsider my views on life, because I no longer saw meaning or value in what I was doing.
Back to learning
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Building with AI
Projects
Avatar
A digital twin with a human in the loop: a chat where visitors talk to an AI version of me. It answers from my profile and FAQ, streams its replies, and sends a notification to my phone when a question needs me. From an admin dashboard I can join any conversation, which makes it a three-way chat between the visitor, the AI and me. Built with the OpenAI Agents SDK, a FastAPI backend, Supabase and a Vite/TypeScript frontend. It's deployed to Fly.io through GitHub Actions and embedded in my personal website.
Autonomous Trading Floor
An equity trading simulation where four autonomous LLM agents manage virtual portfolios: researching the market, executing trades, and rewriting their own strategies based on how their past trades performed. Built on the Model Context Protocol and the OpenAI Agents SDK, with a FastAPI backend and a Vite/TypeScript dashboard.
Tennis Match Research Dashboard
LLM agent engineering on a real domain. The dashboard renders four independent signals side by side for every upcoming ATP / WTA tour-level singles match — market consensus odds, a trained LightGBM probability, a surface-Elo baseline, an LLM-discovered news block — plus a deterministic “why model differs” panel whenever the model-vs-market gap exceeds 10pp. The purpose of the project is to demonstrate end-to-end ML + LLM engineering: data ingestion, feature engineering, model training, evaluation, LLM tool-calling integration, deployable interface.
Not a betting toolToolbox
Outside work
- Training
- 20 years, almost daily. Gym, HIIT, CrossFit.
- Diet
- Zero tolerance for alcohol, nothing sweet other than fruit.
- Time off
- Long walks in the forest, no phone.
- Interested in
- Fitness and sport, neurobiology, Stoicism.
- School
- Straight-A student. Not sure if that counts as a good thing.
- Film
- Interstellar, by Christopher Nolan.
- Sportsman
- Andy Murray.
- Role model
- Pavel Durov.