Part 5/10:

He showcased how LLMs can dynamically infer schema changes by analyzing incoming data. By crafting well-designed system prompts, data engineers can instruct AI models to:

• Detect new or altered fields in data sources automatically.

• Validate whether these changes are legitimate.

• Decide whether to update the destination schema or flag for review.

For example, if a new six-field dataset arrives where five fields were expected, the AI model can identify the anomaly, suggest schema updates, or log discrepancies seamlessly. This process reduces manual effort, minimizes errors, and accelerates adaptation to business changes.

Implementation Details

Mangjunad highlighted that this approach involves:

• Defining clear system prompts that set the role and behavior of the AI.