An AI model must copy directly from existing, approved examples. The AI model must not create new content from scratch. This ensures accuracy and proper sourcing.
By Pawan Nayar · from the LLOS AI Learning record
An AI model must copy directly from existing, approved examples.
The AI model must not create new content from scratch. This ensures accuracy and proper sourcing.
An AI model should always copy content from 'gold' files. These are approved, correct examples. The AI model must open these files and use their exact content. This prevents errors and ensures the content is reliable. Creating new content can lead to mistakes or incomplete information.
A developer asks an AI model to create a new website template. The AI model creates new CSS code instead of copying from existing, approved CSS files. The new CSS code is much smaller and misses important styles from the approved files. This causes the website to look wrong.
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An AI model should not use random generation for its data. A developer must build datasets using specific, planned steps.
Before a developer makes the first edit in any work session, a backup copy of the file must be made. The backup file name should include the date.
A specification often tells a developer to copy an existing file. The developer should open that file first.
A developer must estimate the token count of the AI model's output before making an API call. If the estimated output is more than 6000 tokens, the developer should split the request.
An AI model must copy directly from existing, approved examples. The AI model must not create new content from scratch. This ensures accuracy and proper sourcing.