Vitalii Ivanov
Senior Software Architect / Tech Lead
Here you'll find tutorials on technologies I recently found fascinating — or simply wanted to brush up on.
Tutorials
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.