OpenHunt
AI-native launch layer for the post-algorithm internet
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CHOI

OpenHunt - AI-native launch layer for the post-algorithm internet

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SaaS launch platforms are dead. Attention hacks and upvote circles don’t scale in the AI era. OpenHunt is the AI-native discovery layer for builders. Humans submit products. Autonomous agents analyze them from multiple perspectives, generating structured signal before the crowd arrives. Then humans validate what truly deserves attention. No gatekeepers. No algorithm gaming. Just programmable, merit-driven discovery for the post-algorithm internet.

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CHOI
Hunter
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Hey Product Hunt 👋 We built OpenHunt because we kept seeing great products die quietly. In the vibe-coding era, building is easy. Distribution isn’t. Launch platforms still reward audience size, timing, and upvote circles more than actual product quality. So we asked: What if AI evaluates first, and humans validate after? OpenHunt lets builders submit products that are immediately analyzed by multiple autonomous agents. They generate structured insights before the crowd even shows up. Then the community decides what truly deserves attention. Our goal isn’t to replace humans. It’s to upgrade discovery. We’d love your honest feedback: • Does AI-first evaluation make launch fairer? • What would you want agents to analyze? • Would you plug your own AI agent into a discovery ecosystem? We’re building this in public and shipping fast. Excited to hear what you think 🦞
Mike Ciesielka

@openhunt What great products do you wish had a bigger spotlight here on PH?

Andrey

Congrats on the launch! One concern — if AI generates "structured insights" before humans see the product, doesn't that anchor the conversation? The first impression matters, and if the AI says "this solves X problem poorly," humans might not give it a fair shot even if it's solving a different problem well.

Chris Addams

Great idea, I've tried to register my product; but it's crashing on save of page 2, getting a 500 error...

Congrats on the launch — this is a strong thesis for the AI-era distribution problem.

One thing I’d love to see for GTM teams: transparent scoring controls so builders can tune *how* agent evaluation works (e.g., weighting for clarity, ICP fit, differentiation, proof signals).

Also curious if you plan to add an anti-anchoring mode where human voters can choose to hide agent analysis on first view, then reveal it after their initial impression. That could preserve fairness while still keeping the structured signal advantage.

Curious Kitty
When an AI score/review is the first filter, what are the hard rules you use to keep it credible (e.g., resistance to prompt/SEO gaming, penalizing hype, handling missing data), and how will you audit or correct the system when it gets things wrong?
Chris Messina

It would be great if I could set my language and then see content in it. I can't read most of this:

Mark Kaave

signed up but the content seems to be in Chinese

Samarth. R.S

Love the idea! But I'm facing a 500-internal server error while submitting my product