Why I chose Gemini over GPT to power my YouTube title generator — and what I built around it

I built a YouTube title generator. Not because it seemed like a fun side project, but because I genuinely couldn't find one that worked for my own channel.

I was running an automation channel and every tool I tried failed in the same way — they generated titles for the wrong creator. VidIQ was handing me MrBeast-style broad clickbait. ChatGPT output that was obviously ChatGPT. Neither understood niche. Neither understood my channel.

So I built TitleGen. Here's what I actually decided to build and why.

Why Gemini, not GPT.

This was the first real decision. Most AI tools default to OpenAI. I went with Gemini as the primary model for one specific reason — it has a deeper contextual understanding of YouTube as a platform. The way it handles creator-specific language, niche terminology, and video metadata is noticeably better for this use case.
GPT sits as a fallback in case Google's API ever goes down. That's its only job. The tool isn't a Gemini wrapper though — the model is just one layer of it.

The Channel DNA Analysis layer

The part I'm most proud of is what happens before any title gets generated.

TitleGen pulls and analyses a creator's existing channel — reviewing uploaded videos, tone, CTAs, links, and the trajectory of their last 10 uploads. It builds a profile of the channel before generating anything. A faceless gaming channel, a finance creator, and an automation builder should not get the same title structures. This layer is what makes the output feel niche-locked rather than generic.

How titles are structured and ranked

Once the channel profile is built, TitleGen generates multiple title variations using proven structural patterns — curiosity-driven framing, negative-stakes angles, authority positioning. Each variation is then ranked by virality potential so creators aren't just picking blindly.
Keywords entered by the user return titles that are genuinely locked to that niche — not broad suggestions that happen to contain the keyword.

Descriptions and tags

Descriptions are formatted using YouTube best practices so the algorithm understands the video properly. Optional keyword insertion, timestamps, and socials are all supported. Tags are contextual rather than keyword-stuffed — they're meant to support discoverability while still reading naturally.

Where it is

TitleGen has been live under a month. 81 users signed up so far. $9/month paid plan, free tier available.

TitleGen is an AI YouTube title generator that creates niche-optimized titles aligned with how audiences search and click on YouTube. It performs Channel DNA Analysis to align the tone and channel theme.

If you're a creator or building something in the creator tools space, I'd love to hear your thoughts!

👉https://titlegen.ai/