I’ve spent two and a half decades in the trenches of IT. I was deep in the Computer Science labs when the web was still finding its legs, and I’ve spent the 25 years since then building, architecting, and scaling systems that actually work. I’ve seen technologies arrive with a roar and fade into a whisper, and I’ve survived every “revolutionary” shift by focusing on one thing: the fundamentals.
But I’ll be honest with you: This AI moment is the big one. The industry is currently flooded with “experts” who think an AI career is just about writing a clever prompt. But as someone who has lived through 25 years of production deployments, I know better. You can’t build a skyscraper on a foundation of sand. Real AI success isn’t just about the model; it’s about the engineering—the architecture, the hardened security gates, and the massive data pipelines that make intelligence reliable at scale.
I am currently taking my 25 years of experience and intentionally filling the gaps to become an AI Architect. I’m not just learning tools; I’m orchestrating them. I’m sharing my journey here—the architectural wins, the veteran perspective on modern tech, and the enterprise-grade realities that the hype-train usually ignores.
The Strategy: Awareness vs. Mastery
In an enterprise environment, you don’t need to be a “junior coder” in 50 different tools. You need to be a Master of Orchestration. My strategy for this blog is a two-tier approach:
- Landscape Awareness: We’ll discuss the heavy-duty enterprise tools. I’ve worked with many of these over the years, and you need to understand how Jenkins, Ansible, and Compute Fabric serve as the backbone for AI.
- The Deep Dive (Mastery): We will spend 90% of our hands-on time with a Core Stack—modern, AI-assisted tools that allow one veteran engineer to do the work of a whole team. These are the ones where I’ll build actual projects from scratch and share the code on GitHub.
The Enterprise Gauntlet (The “Adult” Version of IT)
In a real organization, your code doesn’t just go from your laptop to the world. It navigates a gauntlet of specialized environments designed to catch failures before they become headlines. We’ll be touching on how to manage these:
- SIT (System Integration Testing): The “handshake” tier. Does the AI actually talk to the legacy ERP?
- PERF/LOAD (Stress Testing): Will it explode if 10,000 users ask a question at once? (Using k6 or JMeter).
- HOTFIX & DR: How do we patch a bug quickly, and what happens if the cloud region goes dark?
The 12-Level Mastery Roadmap (The Build-Out)
Level 1: The Command Center (CI/CD Orchestration)
- Mastery: GitHub Actions.
- Awareness: Jenkins and Spacelift.
- The Project: I’ll be architecting an automated Security Guard—a CI/CD gate that scans code for leaked API keys and vulnerabilities before they ever reach a server.
Level 2: The Logic Engine & AI-Assisted Dev
- Mastery: Python and Cursor.
- The Plan: Leveraging the Cursor AI-native IDE to write Python at 10x speed, building automation agents that actually solve business problems.
Level 3: The Safety Net (Quality & Autonomous Testing)
- Mastery: Pytest and Playwright.
- The Plan: Building “self-healing” tests—the holy grail of maintenance for any veteran architect.
Level 4: The Foundation Vault (SQL & Security)
- Mastery: PostgreSQL and FastAPI.
- Awareness: HashiCorp Vault.
- The Plan: Designing a central AI memory bank secured with professional-grade JWT tokens.
Level 5: The Transporter (Docker & Compute Fabric)
- Mastery: Docker.
- Awareness: Kubernetes and Microsoft Fabric.
- The Plan: Containerizing our AI agents so they are “Cloud Ready” in one click.
Level 6: The Watchtower (Observability 2.0)
- Mastery: Honeycomb (AI Insights).
- The Plan: Using AI to watch our AI. If a model starts “hallucinating,” we want the dashboard to scream before the user does.
Levels 7-12: The AI Core (Big Data, Vector DBs, RAG, and Agents)
This is the endgame. We’ll move through Databricks, Vector Databases, and eventually, Multi-Agent Systems where digital workers collaborate autonomously.
Why follow me?
I’m a student of the future with 25 years of context in the past. I’m bringing a veteran’s eye for what actually works in production and applying it to the most exciting technology of our lifetime.
We will start with the “Level 1” Security Gatekeeper project. I’ll be documenting every step—from the initial repository setup to the YAML configurations that protect our code. When that first commit drops, it’s going to be built for the real world.
Are you ready to build the future of IT? Let’s get to work.