Why I built NativPost (and what I learned building an Anti-Slop filter for AI content)
Hey everyone,
NativPost is live on Product Hunt today, and I wanted to share a bit about why I built it the way I did.
Every AI content tool I tried before this followed the same pattern: generate content, publish it immediately, and hope it's good. That's why so much AI generated social content sounds the same. Nobody is actually reviewing the output before it goes live.
The core of NativPost isn't just content generation. It's a quality filter that runs before you ever see the content. Every piece of generated text is scored against the patterns that make AI writing feel artificial, such as generic openings like "In today's fast paced world," corporate buzzwords, and hollow enthusiasm. Anything that doesn't meet the quality threshold is automatically rewritten until it does.
The feature I'm most excited to get feedback on is the learning system. Every time you approve, reject, or edit a piece of content, that feedback is fed back into the system and influences future generations for your brand. The idea is that it should get better at sounding like you the more you use it, rather than simply producing more generic "good" writing.
I'd love to hear from anyone who's dealt with the problem of AI content all sounding the same. What's actually worked for you, and what hasn't?
If you'd like to check it out, here's the Product Hunt launch:
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