I
I built an AI Agent for WordPress
Hacker NewsI built an AI Agent for WordPress
Hey HN, I developed an AI Agent for WordPress, to generate titles, write articles, review them to improve quality, and post content to WP (with SEO best practices) in bulk or with a recurrent schedule. It can manage multiple websites. Relying on GPT4o-Mini, I have used it locally for 6 months and Google is quite happy. Now I released it as a Saas. If you can give it a try, I’d love your feedback. There's a 14-day money back if it doesn't work. Thanks
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Launch Intel predictions
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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, google · Missing: mac, agents, macos88%88% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month, google · Missing: mobile apps, ios, personal46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released33%33% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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