Building production AI systems at one of the world's largest modern financial businesses.
Stratos Louvaris
Agentic AI Systems Engineer
Production, not demos
Security from day one
Documents what breaks
Stratos Louvaris
Agentic AI Systems Engineer
Production, not demos
Security from day one
Documents what breaks
About Me
Welcome!
I’m Stratos Louvaris – Agentic AI Systems Engineer
I build AI agents that work in production and I document what breaks along the way.
Most agent projects fail somewhere between the demo and the second user interaction. That gap is where I work: agent architecture, RAG pipelines, MCP tooling, and the failure handling every tutorial skips.
Right now I build production AI systems with the GenAI & Agentic AI team at XM. Before that I designed agentic workflows and RAG tools at Bizeli.
Security isn’t a phase I add before launch. Every tool an agent can call is an attack surface, every permission is a threat model. Before I expose anything, the first question isn’t “does it work?”, it’s “what’s the blast radius if an adversarial prompt gets through?”
I write the process up on my blog “Stratos on Tech”, the architecture decisions, the trade-offs, and the failures. The test before anything goes up: could a tutorial-writer have written this without shipping anything? If yes, it isn’t ready.
- Age 38
- Residence GR
- Address Thessaloniki, GR
My Passion
Clarity and Precision
Breaking down complex technical topics into clear, actionable steps. First principles, not hand-waving.
Agentic AI Systems
Designing AI agents that work in production, with proper guardrails, security, and reliability.
Self-Hosted Infrastructure
Building and maintaining secure server environments with Proxmox, Docker, and OPNsense. Full control, full ownership.
Production Failure Analysis
Documenting what breaks and why — context overload, prompt injection, state that doesn’t survive the second turn. The failures are the useful part.
Fav Companies - Tools
Fun Facts
100+ Audiobooks Listened
Pizza Lover
Tech Content Creator
Passionate Learner
Resume
Experience
2026 - Present
GenAI & Agentic AI team
XM
2022-2025
Agentic AI Systems Engineer
Bizeli LTD
-Build advanced AI models.
-Create and continuously refine RAG tools.
-Design and implement agentic AI workflows and MCP-based automation solutions for business process optimization.
2020 - 2026
E-commerce Optimization & Business Intelligence Specialist
E-smokers
-Engineered technical solutions to optimize the e-commerce platform.
-Developed comprehensive reporting systems.
-Leveraged data-driven insights.
2021-2023
Mobile App Development
App Development
Monitored technical aspects of the front-end & back-end delivery for projects.
Education
2026
Building AI - Advanced coding
University of Helsinki
Honors: "Advanced Coding"
2026
Claude Code in Action
Anthropic
Practical training on the architecture and safe implementation of Claude Code.
2025-2026
Artificial intelligence applications in organizations and businesses
Aristotle Certification Training & Assessment "ACTA"
This program bridges the gap between AI theory and real-world business use.
2024-2025
Generative AI Leader
Google Cloud Certified
Pioneering foundational models and strategic vision to lead the generative AI technological revolution.
2006
ATEI Automation Engineering
Thessaloniki
International Hellenic University - Sindos Campus
2003-2006
Computer and Network Engineering
Thessaloniki
Electronics and Network science
Skills
Hard Skills
-
Agentic Workflows90%
-
Reporting Tools75%
-
Advanced Workflow Automation85%
-
Server Infrastructure50%
Knowledge
-
Agentic AI Systems
-
Cloud Computing
-
Natural Language Processing
-
Data Engineering & Processing
-
Infrastructure & DevOps
-
Large Language Models (LLMs) & Vector Databases
-
Data Analysis & Visualization
-
Optimization Techniques
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Predictive Analytics
Soft Skills
-
Creativity
-
Problem-solving
-
Communication
-
Teamwork
Languages
-
Greek-Native
-
English
Pydantic AI
PostgreSQL
LangGraph
Model Context Protocol
Docker
⚛️
React
Supabase
Serverless
Quote
Hard-working person, that will do the extra mile to accomplish the goals.
Chris Savvakis
UX/UI Programmer
Arete — AI-Powered Resume Optimizer
Hackathon
Active
Hackathon submission for the AWS & Dynamous AI Hackathon — placed 15th in the competition. An AI agent that analyzes resumes against job descriptions, identifies alignment gaps, and generates optimized content. Handles real resume structures — parsing documents, scoring sections against role requirements, and suggesting targeted improvements grounded in actual job market patterns.
Key Skills:
Natural Language Processing, LLM Integration, Document Parsing, Prompt Engineering, Python
Artemis — Personal Productivity App
ActiveA web application built on proven productivity techniques, designed for users who want structure without complexity. Features task management, goal tracking, and workflow patterns — all in a clean, dark-themed interface built for daily use.
Key Skills:
Full-Stack Web Development, TypeScript, Modern UI Architecture, Productivity Systems
Athena — AI-Powered Knowledge System
Hackathon
Active
Hackathon submission for the Elasticsearch AI Hackathon — recognized as a well-crafted, thoroughly documented project by the judges. A second-brain system that uses the Elastic Agent as its reasoning engine and Elasticsearch as its long-term memory — capturing, indexing, and retrieving knowledge so nothing gets lost. Integrated with the Artemis productivity dashboard to prioritize and sequence daily tasks using proven productivity techniques, turning raw information overload into a structured, actionable workflow you can execute each day.
Key Skills:
AI Application Architecture, Knowledge Management, TypeScript, Information Retrieval, Data Processing
Digital Twin AI Chatbot
DevA personalized AI chatbot embedded on stratoslouvaris.gr that acts as a digital twin. Visitors ask questions about background, skills, projects, and experience — and get accurate answers grounded in a curated knowledge base of 47 entries across 9 categories. Built with a RAG pipeline, vector search, and real-time SSE streaming, self-hosted on personal infrastructure.
Key Skills:
RAG Architecture, Vector Search (sqlite-vec), SSE Streaming, FastAPI, Pydantic AI, Self-Hosted Deployment
Blog
July 23, 2026
Agent Skills Explained: What They Are, How to Use Them, and How They Differ From MCP
A first-principles guide to Agent Skills: how they work, how to build one with skill-creator, and how they differ from MCP servers.
July 20, 2026
Running MCP in Production: Where Demos Break and How to Harden It (Part 2 of 2)
What goes wrong when MCP meets real users — context overload, smelly tool descriptions, prompt-injection-as-RCE — and the infrastructure work that prevents it.
May 16, 2026
What MCP Actually Is: Architecture, Primitives, and Why It Exists (Part 1 of 2)
Large language models are brilliant but isolated. The Model Context Protocol (MCP) fixes this by standardizing AI integrations. Just as LSP did for IDEs, MCP lets you write a server once using three primitives, Tools, Resources, and Prompts, so any compliant AI assistant can seamlessly use your
February 24, 2026
11 Advanced RAG Strategies That Separate Demos From Production Systems (Part 3 of 3)
Basic RAG works for demos, but production demands more. Explore 11 advanced strategies, from re-ranking and multi-query to agentic and self-reflective RAG, that solve specific failure modes. Learn how to stack these techniques to build accurate, production-ready AI systems.