Fiona Fung

is low but actually people are like people are finding items that they're looking for which is what we're aiming for like helping people find items that that they need and then i realized in that region it wasn't a large number of sellers but there were power sellers but our first gate before we expand would have just been like you know factoring heavily number of sellers and i remember that

quick conversation of, hey, and this goes back to that whole people will use things in ways you may not expect and shift, iterate, learn.

And so then we updated the metric to go, oh, you know, like it's not a number of sellers because it didn't factor in power sellers.

And so that's the advice I have to like whatever metric, whether for productivity or even for product, always keep an eye and make sure that you're not just having blinders on that's blindly following a metric that used to make sense because sometimes the landscape can change so fast.

even the metrics themselves might need to be adjusted.

I would say, and this is what honestly we want to keep doing more of and being better at it too, like the proactive quality.

So especially for quality, making sure that what are the experiences that are key and making sure you actually, you know, actually speaking of metrics, those are really good things that you make sure you can kind of like see trends over time.

And so like on the quality front, we found like, yeah,

And this is like the more proactive we can be of like making sure we can get an earlier detection into quality.

And so like that's been one thing that we've been paying a lot of attention to.

Like, you know, I started this, hey, let's have a concept of what's bad versus what's sad.

And bad is like a very bad irrecoverable error.

And sad is something that's kind of like a pain point recoverable.

But it's interesting when you stack up sads, it could, you know, generally go to bad.

But even having like starting with a high level framework like that, and because if not, like I think sometimes with dashboards, you can have, you know, like time to load or all these other.

But when you're dealing with a lot of different product surfaces, it's harder to go, wait, is that a good number or not a good number?

And so one thing that's helped us is versus just raw, you know, like performance or, you know, like reliability numbers.

Also having some framework of what we think is, you know, like a bad experience and making sure we're focused on addressing those and then also keeping an eye on where we're seeing in terms of the sad.

So for example, like we allow each team, like speaking of agency, so knowing that bad is like a really bad irrecoverable error, we enable each team a further surface areas or it could be services that, you know, they lead.

What is like, so for example, on CLI could be crash rates, like a crash is pretty bad, you lost work.