Browse Comments — Clean (de-noised)
Close reading of the corpus at each pipeline stage: raw → clean → relevant → coded.
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YT video walkthrough (setup-guide) :
huge 🔝
Automating the full content stack like this is next-level efficiency.
This is no longer “AI for content.” It’s content operations turning into software
yes thats were we are heading 🙌
Is this thumbnail made by KIE?
Enrique Marq not bad, if you share the journey of making this thumbnail, it will be very convincing
So Kanon yes I reference a thumbnail on YT I liked to my agent, the agent used image to image nanobana pro 2, putting the reference image, my reference headshot and inspiration from the video, like the process, Claude code + social media, and with all of that boom the thumbnail got generated
Enrique, Feels like we’re moving from content creation to content orchestration. The creator directs. The system produces
Hi Enrique Marq, thanks for making this available. How do I access that repo?
here ya go brother!
Awesome! Thanks for sharing this!
Nice automation. How do you prevent losing your authenticity and credibility with your followers if AI is doing all of this for you and you no longer personally contribute? And what value do social media platforms still have if AI agents start posting and replying?
This V2 setup is mind-blowing, Enrique! The "Voice DNA" feature for LinkedIn is a lifesaver.
Amaizing
Do try vibedoctor.io if you are using AI for generating code.
This is genuinely useful because it removes three major bottlenecks at once: editing, repurposing, and publishing. Enrique Marq
Turning a single input into full production output reflects a strong shift toward scalable content systems with minimal operational effort, Enrique.
Dilip Sapkota but it doesn't remove the final bottleneck: watching the whole stuff.
Great job! Now I'm waiting for somebody to build an AI system that consumes LinkedIn posts, so we all don't have to watch all these AI-generated posts. Just imagine how much time that would free up, what efficiency!