DEV Community: tamay erdogdu

From Zero to Daily Content: My AI Automation Journey

tamay erdogdu — Sat, 30 May 2026 08:01:24 +0000

From Zero to Daily Content: My AI Automation Journey

The Problem I Was Facing

I’ve been trying to keep a steady flow of videos on YouTube, TikTok, and Instagram for the past year, but the reality was pretty brutal: I’d spend three to four hours brainstorming ideas, another two editing, and then the dreaded “what’s next?” panic set in. My side hustle felt more like a part‑time job, and the numbers weren’t growing fast enough to justify the hustle. I started Googling AI video automation and stumbled across a few buzzwords—AI Shorts, automated video production, content automation—but every solution seemed either too pricey or required a dev team I didn’t have.

That’s when I thought: what if I could stitch together a few free tools and an n8n workflow to do most of the heavy lifting? I was skeptical, but the promise of “passive income AI” was too tempting to ignore.

First Steps with n8n

Week 1 was all about research. I installed n8n locally (Docker made it painless) and started mapping out the steps a video needs to go from idea to published post:

Generate a script with an LLM.
Find royalty‑free images or short clips.
Convert the script to a voiceover.
Stitch everything together into a vertical video.
Upload to YouTube Shorts, TikTok, and Instagram Reels.

I found a few community nodes for OpenAI, Unsplash, and FFmpeg, but none of them were wired together. I built a content automation pipeline that took a seed keyword, called the OpenAI API for a 60‑second script, then passed that script to a text‑to‑speech service (Google Cloud TTS). The first run produced a garbled voiceover; I hadn’t set the language code correctly. That was my first mini setback.

Building the AI Shorts Pipeline

By the end of Week 2 I had a rough prototype that could create a short video in about 7 minutes—minus the human‑level polish. To reach the AI Shorts quality I wanted, I added a few more nodes:

Image Search: The Unsplash node fetched three relevant images based on each paragraph. I wrote a tiny JavaScript function to overlay captions on the images.
Video Assembly: FFmpeg combined the voiceover, images, and a background music track. I used the scale=720:1280 flag to force a vertical format.
Auto‑Posting: n8n’s YouTube API node handled the upload, while I used a third‑party TikTok API wrapper (still in beta) for the other two platforms.

All of this ran on my laptop, and the entire flow was saved as a reusable n8n workflow that I could trigger with a simple HTTP request. I set up a cron job to fire the workflow every 24 hours, feeding it a new keyword from a Google Sheet that I curated each night.

Setbacks and Tweaks

Even after the pipeline was live, I ran into a couple of hiccups that forced me to pause and rethink:

Voice Quality Issues: The first few voiceovers sounded robotic. I switched from the free tier to the premium “WaveNet” voice, which added about $0.02 per 1,000 characters—still cheap compared to hiring a voice actor.
Platform Rate Limits: TikTok’s upload endpoint throttled me after three videos in a row. I added a delay node and limited the daily output to two videos per platform, which meant I had to prioritize the best‑performing keywords.

These setbacks added roughly 2–3 extra hours per week, but the process became far more reliable.

Results after 30 Days

After a full month of automated video production, the numbers started to look promising:

Views: 12,800 total across all platforms, with YouTube Shorts delivering the highest CPM.
Followers: +1,400 Instagram followers and +800 TikTok followers, most of whom engaged with the daily uploads.
Time Saved: I went from ~6 hours of manual work per video to <15 minutes of oversight. That freed up evenings for my actual day job and a side hobby (learning guitar).
Passive Income AI: The ad revenue from Shorts averaged $3.50 per day, covering the modest cost of the OpenAI and TTS APIs and leaving a small profit margin.

I also noticed that consistency mattered more than perfection. The AI Shorts format works best when you post daily, even if a few videos are “good enough.” The algorithm rewards frequency, and my audience grew because they knew a new video was coming every morning.

My Takeaway and Recommendation

If you’re a solo creator or a small team looking to scale content without hiring a full production crew, an n8n workflow for AI video automation is a game‑changer. The learning curve isn’t zero—you’ll wrestle with API keys, rate limits, and some FFmpeg syntax—but the community around n8n is incredibly supportive, and the whole setup can be done for under $50 in monthly API costs.

I’m not a marketing guru, and I’m certainly not selling a magic bullet. I’m sharing this because I genuinely feel that the combination of content automation and a disciplined posting schedule can turn a side project into a modest passive income stream. If you’re willing to invest a few evenings to tinker, you’ll be surprised how quickly you can go from zero to daily content.

The tool I’m using is called AI Shorts Factory (https://8622430312019.gumroad.com/l/gujqfy) — it's an n8n workflow that costs $20 one-time and handles everything: AI script generation, image search, voiceover, video production, and auto‑posting to YouTube, TikTok, and Instagram.

I Automated YouTube Shorts, TikTok AND Instagram With One Click

tamay erdogdu — Fri, 29 May 2026 14:02:24 +0000

I Automated YouTube Shorts, TikTok AND Instagram With One Click

The Problem: Too Many Platforms, Too Little Time

I’ve been posting tech‑tips on YouTube for a couple of years, but when TikTok and Instagram Reels exploded, my schedule turned into a juggling act. Every week I’d spend at least three hours just repurposing the same 60‑second script into three different video formats. I was skeptical that any tool could handle the whole pipeline—script, voiceover, visuals, and posting—without a massive learning curve. My biggest fear? Losing my personal touch while trying to automate.

Week 1: Diving into AI Video Automation

My first step was to research “AI video automation” solutions. I stumbled on a community post about an n8n workflow that could stitch together OpenAI’s text generation, a free image search API, and a text‑to‑speech service. It sounded promising, but the documentation was thin and the example only produced a single MP4 file. I decided to give it a try anyway, because the alternative—manual editing—was already burning me out.

I spent the first three days setting up a local n8n instance on Docker. The UI felt like a visual flowchart, which made sense for a non‑developer like me. My goal was simple: feed a topic, get an AI‑generated script, fetch royalty‑free images, generate a voiceover, stitch everything into a short video, and finally auto‑post to YouTube Shorts, TikTok, and Instagram.

Building the n8n Workflow

1. AI Script Generation

I used the OpenAI Completion node with a prompt that asked for a 45‑second explanation of a tech concept (e.g., “What is a webhook?”). I tweaked the temperature to 0.7 to keep the tone casual yet informative. The output came back as plain text, which I saved to a variable called script.

2. Image Search & Download

Next, I connected the script to a Google Custom Search node. By extracting key nouns (like “webhook”, “server”), I built a query string that fetched the top three images. A small “download file” node saved them locally; I later learned that the image‑size limit mattered, and my first attempt failed because the API returned 5 MB files. Reducing the resolution solved that.

3. Voiceover with Text‑to‑Speech

For the voiceover, I tried a free TTS service, but the quality sounded robotic. Switching to ElevenLabs gave me a natural‑sounding voice, and the node returned an MP3 file that I stored as voiceover.mp3.

4. Automated Video Production

I used FFmpeg inside an “Execute Command” node to overlay the images, sync the voiceover, and add subtitles extracted from the script. The command took a few minutes to run, and the first video was a bit jittery because the frame rate of the images didn’t match the audio length. I added a small “delay” node to pad the timeline, which fixed the sync issue.

5. Auto‑Posting to Three Platforms

Finally, I linked the video file to three separate API nodes:

YouTube Shorts via the Google API (requires OAuth, which took a couple of hours to configure).
TikTok using a third‑party upload endpoint (I had to generate a signed URL).
Instagram Reels via the Facebook Graph API.

All three nodes shared the same video file, so the final step was just a “trigger” that posted everything with one click.

First Setbacks and Tweaks

The biggest hiccup came on day 5 when the YouTube upload failed with a “quota exceeded” error. I hadn’t realized that the API limits were per‑day, not per‑request. To work around it, I added a rate‑limit node that staggered the uploads: YouTube first, then TikTok 30 seconds later, and Instagram after another 30 seconds. This added a tiny delay but kept everything within the quota.

Another minor setback was the subtitles. The auto‑generated text sometimes contained line breaks in the middle of sentences, which made the subtitles look odd. I wrote a small JavaScript function inside an “Function” node to clean up the line breaks before feeding the text to the FFmpeg subtitle overlay.

These setbacks took about 12 hours total, but each fix taught me a new piece of the content automation puzzle.

Results After 30 Days – Content Automation Wins

After a month of running the n8n workflow, I’ve been able to publish three short videos per week with a single “Run Workflow” button. The numbers speak for themselves:

YouTube Shorts: 2,300 views per video on average, 15 % higher CTR than my manually edited uploads.
TikTok: 1,800 likes and 200 shares per video, with the algorithm favoring the consistent posting schedule.
Instagram Reels: 1,200 views and a steady increase in follower count (≈ 300 new followers in 30 days).

In terms of passive income AI, the ads revenue from Shorts grew by roughly $120 over the month, and I’ve started getting brand partnership inquiries because the reach feels “organic”. The workflow itself costs me only the $20 one‑time fee for the AI Shorts Factory package (see below), plus the usual API usage fees (≈ $5 / month). That’s a tiny overhead for a potential monthly return of $150–$200.

Is It Worth It? My Take on Passive Income AI

If you’re a creator who’s already comfortable with the basics of video editing, the learning curve for this automated video production setup is modest. The biggest investment is time—about 20 hours to get the workflow humming smoothly. After that, the maintenance is minimal: you only need to update API keys once a year and occasionally tweak the prompt if you change the content style.

I won’t claim this is a magic bullet that will replace all your creative work. The AI can generate scripts, but you still need to review them for accuracy and inject your personality. The voiceover quality is great, yet some creators prefer their own voice. Nevertheless, the time saved on repetitive tasks is real, and the consistency it brings to posting schedules can boost algorithmic favorability.

My Recommendation

For anyone looking to streamline short‑form content across multiple platforms, I highly recommend trying out the AI Shorts Factory workflow. It’s an all‑in‑one solution that removes the friction of switching tools and handling each platform separately.

The tool I'm using is called AI Shorts Factory (https://8622430312019.gumroad.com/l/gujqfy) — it's an n8n workflow that costs $20 one-time and handles everything: AI script generation, image search, voiceover, video production, and auto-posting to YouTube, TikTok, and Instagram.

Give it a spin, tweak the prompts to match your voice, and you’ll see how much more you can focus on the creative side of things while the automation takes care of the rest. Happy posting!