# About

_A bit more about Mykola Palamarchuk — how I approach engineering and what I'm into now._

## A bit about me

I've been building software for twenty-some years across a wide span of stacks — backend services, data pipelines, infrastructure, observability, the occasional frontend. Through all of it I've kept gravitating toward the same kind of work: figuring out how the parts fit together, where the leverage is, and how to keep the resulting system understandable to the next person who has to touch it.

That generalist streak is what pulled me into data engineering, then into architecture, and now into AI.

## What I care about

A few things that don't change much regardless of what I'm working on:

- **Understanding the problem before reaching for a tool.** Most engineering decisions get easier once you're honest about what you're actually trying to do.
- **Boring, well-named code over clever code.** I'd rather a system be obvious than impressive.
- **Treating data as a first-class citizen.** Whatever you're building, the shape of the data tends to dictate the shape of the solution.
- **Curiosity as a working tool.** I learn fastest when I'm building something I actually want to exist.

## What I'm into now

My current obsession is **machine learning, large language models, and agents** — the architectures that are starting to turn raw model capability into things people actually use. I care about the whole stack: how the models behave, how to ground them in real data, how to evaluate them honestly, and how to ship the resulting systems without losing your mind.

I also like building unrelated side projects with AI as a collaborator. That's part of why this site exists — somewhere to put the things that come out of that.

## Practical details

- **Education.** MSc in Computer Science, Taras Shevchenko National University of Kyiv.
- **Languages.** Ukrainian (native), English (fluent).
- **Location.** Ukraine.