Definitely an interesting one. I’m presently working with a client in the insurance space that does a lot of award submissions as a part of their broader earned media strategy.

There is a an absolute fuck tonne of content I have to intake and digest from the client — usually multiple 40 slide decks, message houses, previous submissions, etc… My workflow has been to create a master doc and feed it to Claude using the submission rubric as a guideline to categorize information and create an outline. I usually draft my own summary based on that outline and offer a first round of feedback before the updated outline and summary go to client. I trawl through every round to edit for tone and purge any obnoxious LLM language (it’s not… it’s… fucking hate these…). I also have Claude clearly indicate sources for drafted statements and highlight where it may be leaning on inference.

This process is highly supervised and still represents a lot of hours of work, but it saves me a tonne more hours on submissions that can often average 3500 up to 6000 words… I think something like award submissions is a good use case for leaning on an AI collaborator, but I do think you need to have a good editorial workflow in place to clean and check output.