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Prompt feedback highlights respected vs ignored elements

When AI generates outputs from prompts, showing which parts of the prompt were successfully executed versus ignored (e.g., through visual highlights) helps users refine their instructions. This feedback loop allows humans to learn how to communicate effectively with AI systems, improving future prompts and reducing trial-and-error.

HostY Combinator00:23:12

Supporting quotes

what did it index on from The Prompt and execute on and what did it sort like maybe your fail if there could be sort of like that feedback loop then it can help the human to refine their prompt and kind of learn how to you know interact with the machine and help the AI to figure out what it did well and should keep doing and what it didn't do well and should get more data to improve Host
the output generated what are the things the machine actually respected from your prompt and where did it sort of like ignore or struggle with kind of giving that feedback back to the human and the prompt maybe with like little squiggly lines or kind of things or with color kind of showing you know what did it index on from The Prompt and execute on and what did it sort like maybe your fail Rafael

From this concept

Iterative Human-AI Collaboration

Progressive fidelity (blurred previews) accelerates iteration by letting users confirm direction before full generation. Incremental updates preserve existing work, while prompt feedback highlights respected vs ignored elements to refine instructions and improve AI understanding.

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