I Tried Having AI Summarize My Blog Posts, and It's Better Than I Expected
I collected around 30 posts and had AI automatically generate summaries and tags. Here's the prompt I used:
"Summarize the text below in 3 lines and extract 5 key keywords. Leave out promotional wording."
About 80% of the results were good enough to use as-is, and I revised the remaining 20% because they didn't match my writing style. Even so, it cut the time I spent on it in half.
If you have any tips for generating tags automatically more effectively, please let me know.
10 answers
I'll admit, it really does a great job with the summary.
Got a source? It doesn't say which model was used to run the 30.
Auto-tagging won’t capture the long tail if you just leave it to its own devices. I set a constraint like, "Pick only 5 from my existing tag list." If you let it create new ones, it mass-produces tags that don’t get searched lol. And you need to lock the count to 3–5 so it doesn’t fluctuate.
They say 80% was usable as-is, but once you factor in the time spent fixing up the remaining 20%, I'm not so sure about the claim that it cut the work in half... When there's a lot of variation from piece to piece, sometimes it actually takes even longer.
Oh, I didn't know that.
I found there's just no way to fix a mismatched writing style with prompting. But when I included 3–4 pieces I'd written as examples, the tone snapped right into place. That one line—"refer to the style in the examples below"—makes a huge difference. When the prompt gets longer, it does waste tokens, but if you think about summary quality, it's still a net win.
Same here lol. I can’t be bothered to tweak it, so these days I just use whatever comes out.
Isn't that old news? These days, models pick up the writing style pretty similarly even without examples. And if it's 80%, I can't help but feel that's basically half a failure. The key is which model it was run on, but that's missing, so there's no way to compare.
"Leave out any promotional language" — that’s a good one. I didn’t include it, so even sponsorship wording ended up in the summary, and I had to run it again a few times. However, if you run the same text twice, the results come out different every time, which is stressful. If there’s an option to lower the temperature, use it.
It's better not to leave tags up to AI. They're for search traffic, and no matter how well the model extracts them, it often picks words that have nothing to do with actual search volume. I just run a real-time search terms tool and pull them from there.