Welcome to My Technical Blog (mock blog post)

October 27, 2025 2 min read

Introduction to this blog and what you can expect - deep dives into AI/ML, distributed systems, and software engineering.

Welcome to My Technical Blog (mock blog post)

Welcome to My Technical Blog

Welcome to my corner of the internet where I share insights, learnings, and experiences from my journey in AI/ML engineering and software development.

What to Expect

This blog will cover a wide range of topics that I’m passionate about:

AI/ML Engineering

I’ll be sharing my experiences working with:

  • Local LLMs and privacy-preserving AI systems [comment: Privacy-first AI is crucial in today’s landscape. Running LLMs locally ensures data sovereignty and eliminates cloud dependencies.]
  • Vector databases and RAG (Retrieval-Augmented Generation) architectures
  • Natural Language Processing applications
  • Model deployment and optimization techniques

Distributed Systems

Topics will include:

  • Microservices architecture patterns
  • Event-driven systems with message queues
  • Real-time communication with WebSockets
  • Load balancing and horizontal scaling strategies

Full-Stack Development

Covering both frontend and backend:

  • Modern JavaScript frameworks (React, Vue, Angular)
  • Backend development with Java/Spring Boot and Node.js
  • GraphQL and RESTful API design
  • Database optimization and design patterns

My Background

I’m currently a Software Engineer at Engineering Software Lab Serbia while completing my Software Engineering degree at Metropolitan University Belgrade. My professional focus has shifted towards AI/ML engineering, particularly in building local, privacy-first AI systems. [comment: The intersection of traditional software engineering and AI/ML is where I find the most exciting opportunities for innovation.]

Current Projects

I’m currently working on Project Aeon, a modular local LLM system that serves as a research, coding, and learning mentor. It’s built with:

# Example: FastAPI endpoint with ChromaDB integration
from fastapi import FastAPI
from chromadb import Client

app = FastAPI()
chroma_client = Client()

@app.post("/query")
async def semantic_search(query: str):
    # Perform vector search
    results = chroma_client.query(
        query_texts=[query],
        n_results=5
    )
    return {"results": results}

Why This Blog?

I believe in learning in public and sharing knowledge. Through writing, I solidify my own understanding while hopefully helping others navigate similar challenges. [comment: Learning in public has been transformative for my growth. Writing forces clarity of thought and invites feedback from the community.] Whether you’re exploring AI/ML, building distributed systems, or just curious about software engineering, I hope you’ll find value here.