online

> ls -la /whoami

Hi, I am a fullstack developer with experience since 2006

I build web, desktop, automation and LLM systems. I care about clean code, hard problems and tools that expand what a developer can do.

2006 started the path
100+ projects
lines of code
LLM researching

Code is a way of thinking, not just a profession.

/projects

Selected work

all web desktop llm experiments

NeuralFlow

LLM Python FastAPI

A platform for working with LLM models and private data.

DataBridge

Web TS Next.js

A real-time monitoring and analytics system.

DevStudio

Desktop C# WPF

A cross-platform studio for development, automation and internal engineering processes.

/lab

Experiments and research

The lab is a working bench for LLM, RAG, AI planning, code intelligence and admin workflows. I document testable hypotheses, not shiny promises: what can be automated, where a human must stay in control and how to bring it to production.

> llm-playground

in progress

A shared bench for quick checks: prompts, system instructions, tool calling, JSON responses, streaming and model behavior on the same inputs.

ai-agent code-miner prompt-studio rag-lab
> run experiment.py loading model... gpt-4o building context... ok generating... ███████████ 78% result: useful
// principle

I am not looking for magic tools. I assemble working systems.

/notes research log

Field notes from the AI lab

LIVE BUILD NOTES
01

RAG pipeline without magic

How I assemble a retrieval layer: sources, chunking, pgvector, eval sets, tracing and honest quality checks.

lab: rag-lab / retrieval / evals
02

AI Factory task planning loop

How a planner should work: goal, decomposition, skill selection, checkpoints, execution trace and manual approval for risky actions.

lab: ai-factory-planner / skills / execution trace
03

Context mining for large codebases

How to extract not just files from a repository, but a useful context pack: entrypoints, dependencies, risk zones and decision history.

lab: code-miner / repo context / LLM handoff

/about :: senior fullstack operator

I build products where interface, data and AI model have to work as one system.

I cover the full cycle: architecture, prototype, production infrastructure, observability and careful UX. I like complex domains where a hypothesis needs to be tested quickly without losing engineering discipline.

TypeScript React Next.js Node.js Python Postgres Redis OpenAI API RAG Queues CI/CD Telemetry
INPUTcontext.md
VECTORpgvector index
MODELreasoning loop
TOOLSapi + workers
$ run senior-stack --mode=production
architecture: clean | telemetry: on | ai: assisted
output: systems that survive real users

/contact :: open channel

Need an engineer who can bring an AI product to production?

Write if you need a fullstack lead for an MVP, internal tool, AI integration or architecture audit. I get into context quickly, speak plainly and leave the system understandable for the team.

Write an email