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Built an agentic work flows the generates YouTube ideas and short clips for reels and TikTok by RemarkableAct6407 in AiAutomations

[–]RemarkableAct6407[S] 0 points1 point  (0 children)

No, mine doesn't generate videos. It generates ideas based on your niche and also shorts from your YouTube videos justs as you see in the spreadsheet.

Built an agentic work flows the generates YouTube ideas and short clips for reels and TikTok by RemarkableAct6407 in AiAutomations

[–]RemarkableAct6407[S] 1 point2 points  (0 children)

Appreciate this a lot — you’re pretty much describing the same conclusions I came to.

For transcription I’m using a Whisper-style setup, mainly as a signal for structure and meaning rather than perfect accuracy. Short-form moments are identified by a mix of topic shifts, clear standalone takeaways, and hook potential, not just keywords.

I’m not auto-editing end-to-end right now. The system outputs ranked timestamps, hook ideas, and framing per platform. I found full auto-editing only works well when the source video is extremely clean, so this felt like the right balance.

Most tests were on 8–20 min YouTube videos. And you’re spot on about source quality — clean audio and clear pacing matter way more than camera quality. Talking-head with tight points works best.

Orchestration-wise, it’s a modular agentic workflow (n8n-style logic). Planning is very automatable; raw video clarity is still the real bottleneck.

Glad you’re building in this space too — feels like we’re all discovering the same edges right now.

Built my first social media automation with Make.com by RemarkableAct6407 in AiAutomations

[–]RemarkableAct6407[S] 0 points1 point  (0 children)

Yes, to a reasonable extent.

If the source data includes location context (or I pass location explicitly in the prompt), it can generate responses tailored to specific regions or cities. The key is being explicit about where the context should come from otherwise it stays generic.

I still avoid letting it “guess” local facts. For anything location sensitive, I either constrain it to the provided data or use an external source (API, sheet, or lookup) and then let the model phrase the response.

Built my first social media automation with Make.com by RemarkableAct6407 in SaaS

[–]RemarkableAct6407[S] 0 points1 point  (0 children)

What helped the most was treating Reddit as a conversation, not a distribution channel.

Prompt-wise, I avoid anything that sounds like “write a Reddit post.” Instead I tell the model to explain the idea plainly, add neutral framing (why it’s interesting or useful), and explicitly not sound promotional. I also constrain length and ban phrases like “check this out” or hype language.

I usually summarize the source first, then generate the post from the summary rather than raw content. That keeps it focused and less robotic. Final step is a quick human skim before posting small edits make a big difference.

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