About

About

Hi, I’m Danylo Yenikeiev. I’m a software engineer based in Warsaw, focused on systems, game engines, AI/ML, networking, developer tooling, and difficult debugging.

I genuinely enjoy building things and understanding how complex systems work. Rust is my main language today, with Python as a frequent second tool when it fits the problem better.

What I’m building

My main project is a modular, general-purpose game engine I’m building from scratch in Rust.

The work spans runtime and ECS architecture, rendering, assets and content, input, scenes, physics, plugins, voxel systems, task systems, developer tooling, testing, CI, performance, and API design. A core design goal is keeping high-level engine APIs independent from backend-specific details so engine users and plugins do not need to depend directly on graphics or windowing internals.

Freven is a voxel game built on top of the engine and acts as a real downstream consumer. I use it to pressure-test gameplay paths, voxel world and chunk management, rendering and collision updates, interaction, diagnostics, frame-time behavior, and engine API boundaries. You can follow the project and development discussion in the Freven Discord.

Most of this engine work is private while it is being prepared for a public release.

AI and simulation

I also work heavily on AI and simulation systems, including:

  • deterministic neural-network execution
  • recurrent and time-delayed network behavior
  • NEAT and neuroevolution
  • evolutionary algorithms
  • reinforcement learning
  • artificial life and ecological simulations
  • reproducible experiments and deterministic simulation tooling
  • LLM systems with memory, task workflows, and external connectors

Some of this work integrates with my engine, while other parts are intentionally engine-independent.

Background

I spent years working with Godot, including Rust through GDExtension, before moving deeper into lower-level Rust systems and my own engine architecture. I still work comfortably in Godot codebases and integrations, and I can get into Unity, Unreal Engine, backend systems, networking stacks, or unfamiliar codebases when the work calls for it.

I especially like problems where the difficult part is figuring out what is actually wrong: reproducing an issue, tracing the root cause across subsystem boundaries, implementing the smallest reliable fix, and adding validation so it stays fixed.

Selected public work

  • Quinn: Windows/Wine ECN compatibility - merged upstream contribution that keeps QUIC endpoint creation working when Wine/Proton does not provide optional Winsock ECN functionality.
  • Rune Companion - LLM companion framework with streaming model responses, SQLite-backed memory and tasks, injected service interfaces, and console/Matrix connectors.
  • Gridworld Learning Lab - reproducible Rust reinforcement-learning experiment with tabular Q-learning, seeded environments, persisted policies, evaluation metrics, and deterministic visual rollouts.

How I work

I care about clear ownership and dependency boundaries, reproducibility, performance that is measured rather than guessed, and focused regression tests around failures that actually occurred.

I enjoy both building systems from scratch and entering an existing codebase with very little context and working backward from a real failure.

Contact

I’m open to contract work and longer-term engineering collaboration, especially around systems, engines, integrations, networking, AI/simulation, performance, and debugging.