You can address technical debt in AI models for creative content by implementing modular architectures, automated testing, version control, and continuous monitoring.
Here is the code snippet you can refer to:

In the above code, we are using the following key points:
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Model Versioning: Uses MLflow to track and manage AI model iterations.
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Modular Architecture: Ensures easy upgrades without full redesigns.
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Automated Maintenance: Simplifies rollback and debugging of AI models.
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Scalability: Supports continuous monitoring and automated testing integration.
Hence, managing technical debt in AI models through version control, modularity, and automated tracking ensures long-term maintainability and performance consistency.