The infrastructure debt AI creates isn't in the code. It's in the operations
Enterprise DevOps teams have adopted AI faster than they have adapted the operational systems that support it. Large language models generate Infrastructure as Code, deployment pipelines, and configuration files in seconds.
Development teams are delivering infrastructure changes at a pace that would have been implausible five years ago. Production environments have simultaneously become harder to reproduce, more difficult to govern, and more expensive to operate.
CEO at Quali.
The problem is easy to miss at first, because AI looks like a clear win in the early stages. A team asks an AI tool to set up some infrastructure. It works. The team expands how much they rely on it. More teams follow. More infrastructure gets created for testing, demos, experiments, and development. The organization ends up with far more moving parts than it had before, but far less ability to track them.
Not the full picture
The tools generating this...
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