The promise of AI is speed. Code is written faster, agents automate workflows, and software teams can accomplish in hours what once took days. But as this InfoWorld article argues, that acceleration comes with a hidden cost: a new generation of technical debt that extends far beyond code itself. AI agents don’t just add software dependencies—they introduce dependencies on prompts, tools, MCP servers, external models, and complex chains of behavior that few teams fully understand or govern.
The article’s core insight is that AI isn’t eliminating engineering discipline; it’s making discipline more important. As organizations rush to adopt agentic systems, every new integration becomes another potential point of failure, security risk, or maintenance burden. The winners won’t be the companies that connect AI to everything. They’ll be the teams that keep their systems understandable, controlled, and intentionally designed. In many ways, AI is repeating a familiar pattern from microservices and cloud computing: greater flexibility paired with greater complexity. The productivity gains are real, but so is the debt if nobody is keeping score.