I’ve been testing different ways to use AI for productivity without turning every task into an over-engineered automation. The workflows that have held up best for me are usually simple: Research summaries — turning long source material into structured notes, then checking the important claims manually. Content repurposing — taking one article or idea and adapting it into shorter posts, outlines, email drafts, or social content. Prompt refinement — using a second pass to critique the first output for missing context, weak assumptions, and unclear wording. Customer FAQ drafting — generating a first version from existing product or service information, then reviewing it before publishing. Marketing idea generation — brainstorming campaign angles, hooks, and content themes without letting AI make the final strategic decision. The pattern I keep coming back to is that AI works best as a structured assistant , not as the final decision-maker. The biggest gains come from reducing repetitive work while keeping human review for anything public-facing or important. I organized the prompt structures and workflows I’ve been using into a practical toolkit for productivity and marketing. Disclosure: this is my own resource/site. https://digitalworldpulse.com/ai-productivity-and-marketing-toolkit/ I’d be interested to hear which AI workflow has actually stayed useful for you after the initial novelty wore off. submitted by /u/No_Appeal_5223
Originally posted by u/No_Appeal_5223 on r/ArtificialInteligence