How did you find your first affiliates? Recurring commission offer, zero takers so far.

My friend and I built a small SaaS an AI chatbot for small business websites that answers visitors and captures leads after hours. He handles the tech, I handle marketing.

Since we have no audience and no ad budget, I figured affiliates would be our best shot at distribution. So I made the offer as strong as I could justify: 40% recurring commission, every month, for as long as the customer stays. On our pricing that's real money per referral, not pocket change.

The problem: an offer means nothing if nobody sees it. I put up an affiliates page, but obviously no one is stumbling onto it.

For those of you who got affiliates before you had traction where did your first ones actually come from? Cold DMs to niche YouTubers/bloggers? Affiliate networks? Communities? Existing customers?

Did the strong commission actually matter, or did people only promote once you had social proof?

Would love to hear what worked and what was a waste of time.

reddit.com
u/Jazzlike_Ad_3604 — 2 days ago

I spent a month building 10 AI agents that run a YouTube channel. Just open sourced the whole thing.

​

I have no audience and I am not a professional developer. I wanted a channel that could run itself, so I started building one agent, then it needed another agent to check its work, and about a month later I had ten of them.

Here is what it actually does. You give it a YouTube podcast link. It transcribes the episode locally, scores which moments are most likely to perform, cuts them to vertical 9:16 with face tracking, burns in captions, adds music and effects, then checks its own output and schedules the posts.

The agents:

- **Finder** transcribes and scores clip-worthy moments

- **Editor** cuts, reframes, captions, adds music and zooms

- **Uploader** writes the titles and hashtags, posts to YouTube Shorts

- **Manager** reads your real metrics and feeds what wins back into the Finder

- **Trend Scout** checks what is trending in your niche

- **Planner** decides the creative direction per clip

- **Community** drafts comment replies

- **Finishing Editor** watches every finished render and blocks broken ones (captions covering a face, dead air, frozen frames, bad audio)

- **Trainer** studies top performers weekly and updates the playbooks

- **Compiler** stitches the week's best moments into a long-form episode

The part I am most happy with is the Finishing Editor. Everything else generates, but that one is the only agent whose whole job is to say "no, that one is broken, do not post it." It caught more bad clips than I expected.

It runs on free AI providers (OpenRouter, Groq, Gemini), transcription is local with faster-whisper, and the music is synthesized so it is safe to monetize. So the running cost is basically zero.

It is MIT licensed. Use it, change it, sell whatever you build with it. Honestly, if someone takes this and actually makes money with it, that would make my month.

Fair warning: it is not perfect. The output quality varies, some parts are held together with duct tape, and I am sure there are bugs I have not hit yet. I am putting it out as it is rather than polishing forever. If people want to help fix it, that would be great.

Repo: https://github.com/krakonjac300-pixel/podcast-shorts-factory

There is a PDF setup guide in there. Install is a double click on Windows, one command on Mac and Linux, then a wizard asks you a few questions.

Happy to answer anything.

Bty: Here is the Chanel that its running

https://youtube.com/@moneymugshots?si=9ZeeL2gFy17\_ViIL

u/Jazzlike_Ad_3604 — 29 days ago
▲ 113 r/AIAssisted+1 crossposts

I spent a month building 10 AI agents that run a YouTube channel. Just open sourced the whole thing.

​

I have no audience and I am not a professional developer. I wanted a channel that could run itself, so I started building one agent, then it needed another agent to check its work, and about a month later I had ten of them.

Here is what it actually does. You give it a YouTube podcast link. It transcribes the episode locally, scores which moments are most likely to perform, cuts them to vertical 9:16 with face tracking, burns in captions, adds music and effects, then checks its own output and schedules the posts.

The agents:

- **Finder** transcribes and scores clip-worthy moments

- **Editor** cuts, reframes, captions, adds music and zooms

- **Uploader** writes the titles and hashtags, posts to YouTube Shorts

- **Manager** reads your real metrics and feeds what wins back into the Finder

- **Trend Scout** checks what is trending in your niche

- **Planner** decides the creative direction per clip

- **Community** drafts comment replies

- **Finishing Editor** watches every finished render and blocks broken ones (captions covering a face, dead air, frozen frames, bad audio)

- **Trainer** studies top performers weekly and updates the playbooks

- **Compiler** stitches the week's best moments into a long-form episode

The part I am most happy with is the Finishing Editor. Everything else generates, but that one is the only agent whose whole job is to say "no, that one is broken, do not post it." It caught more bad clips than I expected.

It runs on free AI providers (OpenRouter, Groq, Gemini), transcription is local with faster-whisper, and the music is synthesized so it is safe to monetize. So the running cost is basically zero.

It is MIT licensed. Use it, change it, sell whatever you build with it. Honestly, if someone takes this and actually makes money with it, that would make my month.

Fair warning: it is not perfect. The output quality varies, some parts are held together with duct tape, and I am sure there are bugs I have not hit yet. I am putting it out as it is rather than polishing forever. If people want to help fix it, that would be great.

There is a PDF setup guide in there. Install is a double click on Windows, one command on Mac and Linux, then a wizard asks you a few questions.

Happy to answer anything.

reddit.com
u/Jazzlike_Ad_3604 — 29 days ago