AI Experts We are seeing a massive push across the software industry right now. Senior developers are rebranding themselves as "AI experts," newer engineers are learning to code with an LLM by their side, and enterprises are eagerly buying up AI licenses, convinced they are purchasing pure engineering velocity. The reality on the ground looks very different. Enterprises are quietly losing control of their codebases. The 5-Iteration Trap The problem usually starts with a simple task. The developer prompts AI to fix or update an existing application. At first, they take the time to read through the generated code, inspect the syntax, and understand how it works. Then the iterations begin: Iteration 1: The business asks for a change. Instead of modifying the logic manually, the developer asks the AI to rewrite the block of code. Iteration 2: A new edge case crops up. Another prompt is thrown at the model to patch the issue. Iteration 3: Another feature request comes in, fol...
AI Isn't Magic. It's a Normalization Layer. As a technical architect for the last 22 years, I’ve seen technologies come and go, but one thing remains constant: the tech industry loves hype and jargon. My guiding principle has always been simple: ignore the buzzwords and understand the fundamentals. When you strip away the marketing around Artificial Intelligence, enterprise architecture reveals what AI truly is: a normalization layer. The Predictable Bucket Theory At its core, AI solves an architectural interface problem. Users provide messy, erratic, unpredictable input. AI’s true utility is taking that unpredictable input and categorizing it into a set of predictable buckets that your deterministic, reliable core code can execute. Voice development taught me this years ago. When handling spoken human language, you don’t let the raw voice command run your database. You extract intent and slots, validate them, and feed clean parameters to your backend. AI does this at scale....