In the early days of enterprise software, the dynamic between technical architects and leadership was built on a clear, unspoken contract: management understood the business, and architects understood the technology. While there were always negotiations about timelines or budgets, management rarely interfered with core architectural decisions. If a seasoned architect looked at a proposal and said, "We cannot do it this way," leadership usually deferred to that expertise. They simply did not have the technical vocabulary to argue the low-level implementation. Today, generative AI has completely shifted that dynamic, and it is quietly derailing technical alignment. The Illusion of Alignment Middle and senior management now have a powerful tool at their disposal. Before a technical review, a manager can plug a business requirement into an LLM and ask for the technical options to build it. Or, even worse, they walk into the meeting and announce: "I’ve figured out we can ...
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...