How I Used AI to Summarize Complex Content and Got My First 50 Users

A few days ago, I quietly launched a tool I initially built for myself, called Summizer. Honestly, I wasn’t planning on launching it at all — it started as a side experiment because I was drowning in endless PDF reports and unstructured meeting notes. The kicker? Most AI summarizers I tried either oversimplified the content or missed critical nuances. So, I decided to scratch my own itch.

I posted about Summizer in a couple of niche Discord groups and forums — no ads, no launch party, no Product Hunt. To my surprise, I got 50 signups in the first 72 hours.

Here’s what worked and what didn’t, in case you’re thinking about launching something similar:

1. Build for your own pain point — and say it plainly
I explained the exact problem I had: context-switching between text, visuals, and video was killing my focus. Instead of saying “I built an AI summarizer,” I wrote about how reading 20-page PDFs, toggling between Chrome tabs, and skimming videos to find that one insight felt like death by a thousand microtasks. That kind of honesty resonated more than any pitch ever could.

2. Let the product tell a story on its own
I recorded a 40-second Loom showing how Summizer can take in a long doc, extract key sections, run summaries through multiple LLMs (like GPT-4o, Claude 3, and Gemini), and highlight what each one got right, missed, or framed differently.

That “multi-model comparison” feature sparked the most DMs. Apparently, others had the same trust issues with AI summaries — and being able to see the differences side-by-side added a layer of transparency that folks appreciated. (It’s something I didn’t even realize was a hook until someone called it a “truth-checker for LLMs.”)

3. Focus on curiosity, not conversion
I didn’t drop a CTA like “Sign up now.” Instead, I shared a few real outputs — e.g., a messy video transcript compressed into 5 bullet points, with each LLM’s take compared. That made people ask for the link. Turns out, showing is still better than telling.

What didn’t work:

• Posting to large Reddit threads cold. It got flagged as self-promo even when I tried to frame it as a “what do you think of this?” post.

• Trying to explain too much upfront. I had a long paragraph on the tech behind Summizer’s full-modality engine (it handles PDFs, video frames, OCR on screenshots, etc.) — but most people just wanted to know: does it save me time?

The takeaway:
If you’re building an AI product, assume your early users care less about your backend stack and more about whether it makes their lives 1% easier. For Summizer, the combo of “just works” + “I can see what the AI missed” helped cut through the noise.

Curious to hear — if you’ve launched something recently, what worked best for your first batch of users?
And if you’ve ever doubted an AI summary’s accuracy… would being able to compare multiple models change that?

Let’s swap notes.