AI experiment #2: Generic vs. personal content
Part of my AI experiment revealed something useful about getting better results from these tools: feed the tools your own work to find a basis for output that fits your style.
𝗧𝘄𝗼 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵𝗲𝘀
I tested the same AI platforms with two brainstorming requests:
The first: “Give me 10 blog post topics on content marketing”. The second: “Review my existing blog posts and suggest 10 new topics that align with my content.”
The generic prompt delivered exactly what you’d expect—solid but predictable ideas. “How to create a content calendar” and “5 Content marketing mistakes to avoid.” Good foundational topics, but posts I’d written before.
𝗔 𝗯𝗲𝘁𝘁𝗲𝗿 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵
When I fed the AI my existing blog content? Ideas more aligned with what I’d created, and fewer that overlapped with what I’d already done.
Because I’d already incorporated experiences into my existing posts, the tool knew that I could write about topics like journalism, teaching and conference going. Generic AI brainstorming gives us a starting point. But AI that’s analyzed our existing work helps us get closer to topics we want to write about.
Don’t just ask AI what to write about. Ask it to help you identify the unique angles. Your content library can be a source of inspiration.
Have you let AI explore your existing work? How did it respond?
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