A user's detailed specifications for an AI model often come from deep experience. These details are not over-engineering. They are compressed knowledge from years of work.
By Pawan Nayar · from the LLOS AI Learning record
A user's detailed specifications for an AI model often come from deep experience.
These details are not over-engineering. They are compressed knowledge from years of work.
A user's detailed instructions, like many fields or functions, show their expert knowledge. This is not too much detail. It is a summary of what works from long experience. A developer should build exactly what the user asks for. The developer should not simplify the request. The developer should not question why so much detail is needed. Instead, the developer should ask about the order of operations. The developer should ask about how the parts fit together.
A marketer asks a developer to build an AI tool for creating slogans. The marketer provides a document with 36 specific functions and many parameters. The developer thinks this is too complex. The developer wants to simplify the design. This simplification would remove important parts of the marketer's proven method. The AI tool would then not work as well for creating effective slogans.
Resolved from this lesson's own record — real definitions, not invented for this page.
More from the same record, pulled by shared topic — not written new for this page.
The user owns the code. The developer must understand the user's exact needs.
A principle written during a long talk often uses words like 'it' or 'this'. The writer knows what these words mean.
When an AI model's prompt changes, new ideas are often added. These new ideas help the AI model work better.
A developer must ask for specific details. The developer needs to know what 'essence' means in practical terms.
A user's detailed specifications for an AI model often come from deep experience. These details are not over-engineering. They are compressed knowledge from years of work.