Matt St. Peter

Who it's for

People with overflowing watchlists who still don't know what to watch tonight. Cinephiles who've outgrown "Top 10 Crime Movies." Anyone who wants to find a film by mood, not by genre or popularity. Think "warm hug after a long week" or "neon-soaked stylized action" or "rain-soaked melancholy."

The problem

Recommendation engines mostly run on collaborative filtering. Netflix, Prime, the whole streaming layer. Same 200 films surface for everyone. A 120-year catalog of cinema never gets touched.

Hey PH mates!

I ve been tracking my own workflow lately while chatting around with ChatGPT and Gemini, and I noticed a painful pattern: I had the whole picture in my mind, but I constantly forget some edge cases or tiny technical constraints on my first try.

I hit send, wait 30 seconds, realise the AI guessed wrong, tweak it, and retry. It s an absolute token-waster and a massive productivity killer.

I'm trying to prototype a lightweight extension to intercept these "blind spots" in real-time right inside the input box before hitting send. But I'm curious about how you lot deal with this:

Last summer, the idea for my SaaS, Xolora, started to take shape. Around the same time, the concept of vibe coding was blowing up. As a non-technical founder, it sounded like a dream come true. No coding experience? No problem, just let AI handle it.

The beginning was incredibly promising. Using Emergent made me feel unstoppable. I was seeing my idea come to life.