I build secure, production-ready AI agent systems.
Most AI demos look impressive. Most AI demos also break on the second real interaction. The gap between prototype and production isn't the model — it's the architecture, the security boundaries, and the failure handling that nobody talks about.
That's what I build: AI systems that actually work in the real world. No hype. No buzzwords. Just practical implementation, security-first thinking, and first-principles engineering.
Agentic AI Solutions — Tools, frameworks, and educational content for engineers who want to build reliable AI systems.
My work sits at the intersection of three things:
- Practical AI Implementation — Patterns that survive production
- Security-First Architecture — Every permission is an attack surface
- Developer Productivity — Tools that make engineers more effective
| Project | What It Does |
|---|---|
| Artemis | Personal productivity web app implementing proven productivity techniques with a modern, dark-themed interface |
| Athena | Athena - Second Brain Orchestrator Agent |
| Arete | Arete - AI-Powered Resume Optimizer for Tech Professionals |
These projects are in active development. Star them to follow progress.
I write at Stratos on Tech — breaking down complex AI and infrastructure topics step by step.
| Article | Topic |
|---|---|
| 11 Advanced RAG Strategies That Separate Demos From Production Systems (Part 3) | RAG, production AI |
| The RAG Foundation: Embeddings, Vector Databases, and Chunking (Part 2) | RAG, embeddings, vector DBs |
| What Is RAG and Why Your LLM Needs It (Part 1) | RAG, LLMs |
| How to Use Google's NotebookLM as Your Personal Learning Assistant | AI tools |
| Self-Hosting LLMs with Ollama (AI for Sysadmins Part 2) | Self-hosted AI |
| From Neural Networks to the MLOps Factory Floor (Part 1) | AI fundamentals |
| Building a Secure Home Network: From Chaos to Control | Networking & security |
| Building My Personal Server: A Complete Journey | Self-hosted infrastructure |
1. Security is a foundation, not a feature you add later.
2. If it doesn't work in production, it doesn't work.
3. Complexity should serve the user, never the architecture.
4. Document the messy middle, not just polished results.
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