Evan Sterling

A few weeks after launching @Velo , we noticed something interesting.
People weren't using it alone.
They'd clone a voice, generate a few videos, then immediately ask:
"Can my co-founder use this too?"
"Can my editor access these assets?"
"Can the whole team share credits?"
At first, we thought they were edge cases.
They weren't.
The more people used Velo, the more obvious it became that content creation wasn't an individual workflow anymore.
The AI could move at incredible speed.
The bottleneck was collaboration.
Assets lived in different accounts.
Brand kits got recreated.
Teams shared logins.
The same voice clone got uploaded again and again.
The technology was solving creation.
It wasn't solving coordination.
So for the last month, that's what we've been focused on.
Today we're rolling out Velo for Teams

• Shared workspaces for brand kits, resources, and pooled credits

• Clone your voice and face once, then make them available to the whole team

• Shared libraries to organise videos and assets in one place

• Admin controls and member roles without the usual account-sharing headaches

One person sets it up.

The whole team can start creating minutes later.
We're doing a bigger launch push next week, but the Product Hunt community has supported us since day one, so I wanted to share it here first.
Curious - if you had a shared AI video workspace for your team, what's the first thing you'd use it for?
Watch our demo

Just saw reports that SpaceX acquired Cursor in an all-stock deal valued at $60 billion.

This is one of the most insane startup outcomes we've ever seen:

• Cursor was founded only ~4 years ago.

• The reported price tag would make it one of the largest startup acquisitions in history.

• It went from "just a VS Code wrapper" jokes to becoming the default AI coding tool for a huge number of developers.

• SpaceX/xAI would instantly gain access to one of the most valuable datasets in AI: how millions of developers actually write, edit, debug, and ship code.

What a day. detectly officially launched on ProductHunt today.

Quick recap for anyone just finding this. detectly automatically detects near-miss incidents from dashcam footage. Tailgating, cut-ins, hard braking, pedestrian hazards, lane drift. Every incident gets an annotated clip and every driver gets a risk score. No new hardware needed.