Vitalii Ivanov

Senior Software Architect / Tech Lead

Helsinki

Here you'll find tutorials on technologies I recently found fascinating, or simply wanted to brush up on.

Tutorials

The AI stack: how one claim crosses six layers

LangChain, LangGraph, Langfuse, Airflow and the Claude Agent SDK: which job each one owns, shown on one insurance claim.

Diffusion models: how noise becomes a picture

How a prompt and a grid of random numbers become an image, and why the network only ever predicts noise.

MCP: how one question becomes a tool call

How one question travels from your editor to a tool and back: the protocol every AI client now speaks.

Claude Code: how one prompt becomes a code edit

What a coding agent actually does between your prompt and the two lines it ends up changing.

Git worktrees: how three AI agents share one repo

How several agents work in the same repository at once without overwriting each other.

Interpreted vs compiled: how one line reaches the CPU

One line of code through Python, JavaScript, Java and Go, and why the split is a dial, not a dichotomy.

Reasoning models: how a model learns to think before it answers

What a model is really doing while it thinks, and why the thinking is what makes it right.

Concurrency: how Java, Node, Go & Python hold 10,000 clients

Four runtimes under the same flood of connections, and the two tricks all of them rely on.

Transformers: how five words become a sixth

How a handful of words becomes the next one: tokens, attention, layers, and a final vote.

LoRA: how to teach a frozen model in 8 megabytes

How to teach a frozen model a new skill by training a tiny patch instead of the weights.

Prompt injection: how a poisoned email hijacks an AI assistant

How an ordinary-looking email turns a helpful assistant against you, and the guardrails that stop it.

AI evals: how a one-line prompt change earns the right to ship

How a change to a prompt earns the right to ship, measured instead of guessed.

AI numbers every AI engineer should know

The handful of numbers that explain what a model costs, how fast it answers, and why.

AI agent patterns: how one support ticket gets closed

Every core agent pattern, shown on one real support ticket from open to closed.

How RAG works: retrieval-augmented generation

How a model answers from documents it never studied, and cites where the answer came from.

How a neural network reads a handwritten digit

Three kinds of network read the same hand-drawn digit, and each one sees it differently.

What happens when you type a URL and press Enter

Everything that happens between your keypress and the pixels: DNS, TCP, TLS, HTTP, rendering.