Trust and safety requires about 40% of Whatnot's employees because the platform is analogous to running the police force and legal system for a city the size of two New Yorks.
Whatnot treats trust and safety as its highest-priority investment, dedicating roughly 40% of headcount to it. An automated rules engine processes billions of data points in under a second to detect harassment, late shipping, and other bad behavior — but human oversight remains essential. ✦ AI generated
Grant LaFontaine · a16z Podcast · 2026-08-19 · original ↗
starts at this moment · 33:28
“What are some of the things you encounter with that amount of scale that you constantly have to be on top of?”
Trust and safety on whatnot is about 40% of employees. The trust and safety team is basically the police force and the legal system of whatnot. You got to write your policies. You got to be people who enforce your policies. In a city that has 10, 20 million people, you're looking at a city the size of Tokyo — a couple New York cities. We have a rules engine in the background which takes in billions of data points at this point in sub 1 second to be able to take down or find any range of bad behavior on the platform.
verbatim transcript · starts at 33:28
33:28trust is measure everything. Um and uh we have a invest a lot in it. So I think um trust and safety particular on whatnot is about 40% of employees. Yeah. So, it's au it's a huge huge investment from us because it's it's a challenging one and you don't want to put your >> credit card in a place you you don't trust. You certainly don't want to buy
33:50fresh fish from a place you don't trust, >> right? >> Um and and so so so those you know I think lot of measurement, lot of user feedback um and then a big just people investment to get the thing done is is sort of what drives it. Um, and then you know the problems are are pretty diverse and you have to make sure you're building the right set of things for it.
34:16So as an example, [clears throat] we have a a system in the background um which is called our our rules engine and it um takes in billions of data points at this point in sub 1 second to be able to take down or find any range of bad behavior on the platform. So if you harass someone in a live stream, the LLM will detect it. It will get plugged into the our action
34:46rules engine will look at the history of the seller and based upon other signals programmatically take them down, suspend them, ban them, warn them. If you are not shipping on time, the the rules engine will do the same thing. If you have a high refund rate, the rules engine will do the same thing. And so, um, and look, these are ever changing, you know, problems and issues.
35:09>> Waiting of scoring and things like that will always change. Yeah. Um and and so you constantly have to uh be on top of these things. >> Yeah. Yeah. I mean, you know, if you think about just how many concurrent users you have and how many transactions you process per day. >> Yeah. I I always the the the analog I like for trust and safety is so you know
35:29tens of millions of people use whatnot every >> Yeah. Yeah. >> And so um the trust and safety team is basically the police force and the the legal system of of whatnot. You got to write your policies. You got to be people who enforce your policies. And you know, in a city that has 10, 20 million people, you're looking at a city the size of Tokyo or I mean, maybe a
35:51better analog would be like I mean, it's a couple couple New York cities. >> Yeah. Two New York cities. >> Two New York cities. And um uh you know, in in New York, um it's not not perfectly run. Uh and so there's going to be some bad things that happen. and people get arrested. But at at our scale, because of some of the systems we build, there's actually far far fewer
36:12Yeah. >> problems. And and then of course, look, if whatnot is a business for a small small business, everything's on video. So if you're so if you're a small business, you want to build a great business. >> Any good business knows you got to have repeat customers, you got to invest in a customer experience. So our sellers reinforce it. >> Then you're on live video. [laughter] So