Switching gears a little bit, that was a behavioral question. Let's go to more of a strategy question. Again, you'll still notice that the way I carry this interview will still be framed around some of the leadership principles. Tell me about your favorite Amazon product, and how would you improve it? Yeah. My favorite Amazon product I would have to say is, I'm thinking here, there are a lot of great Amazon products. I will pick the Alexa. Then your second question essentially was, how would I potentially improve it? One of the biggest challenges as a user for the Alexa product is sometimes the voice recognition, isn't 100 percent accurate. I don't know if whether it's my voice, my intonation, or sometimes when I have a guest come over, even though they're not like an improved account, they'll always give commands as well. There are some security concerns that I may potentially have from that regard. One of the things I would look to improve would be around how can I improve voice recognition. Understood. Give me a use case of why would you want to improve upon it? Where are the gaps that you are seeing? The main thing I think I am concerned with is security. If I have a certain list of voices that I want to say, "Hey, these are the approved users of my device," I don't want a stranger to come over, might give certain security keys, even orders that's connected to my prime account, etc. How do you know they're not already working on this on their roadmap? They could be. I think voice recognition is probably one of this continuous improvements. I think the challenge that I have seen is that they're probably more incremental rather than something that I can see that has made a significant difference. Yeah. Taking a pause here, the question I asked Jenny in terms of how do you know the company is not already working on it? That's an example of a question where I wanted to see her really think on that field because it's a question that may not necessarily be a logical follow-up to the question that I asked before, which is, what aspect of this product or this experience she would have improved upon? Typically, you may find that sometimes in your bar raiser interviews. Just to give you a quick context on what is the bar raiser interview. It's a interview by someone outside of the direct team that you will be interviewing with if you were to interview for an Amazon position. The role of the bar raiser essentially is to ensure that Amazon as an entire organization and company, regardless of its Alexa as Jenny mentioned her favorite product was or the retail organization or Amazon Web Services, they continue raising the bar on hires. The rule of thumb typically is if someone, for example, does not raise the bar for half of the current population, then that person isn't a no hire. Typically, that's how that justification is made. Sometimes in debriefs, there can be questions asked such as, for example, would you rather hire this person or choose randomly from the current population? Whether that answer is a yes or no, will also determine how the interviewer loop as a whole decides on the fate of the candidate. In that case, I thought Jenny did a great job in her answer, she does not know which is the right answer, whether or not she is on the product roadmap. However, she also presented how she thought of it as a consumer. I really like that the way she gave that answer, and I'm going to dig a little bit further. The LP that she just demonstrated is customer obsession, which is thinking on behalf of customers and the specific angle she presented was security. For example, then if you were like a product manager on Alexa focused on security, and that was the potential customer privacy was what you were working on, how would you design a feature around that? Walk me through the steps. Yes. If I had to design a feature around customer privacy, the first things is, what is the problem that I'm trying to solve? Essentially, I could conduct a bunch of surveys going out to users, collect existing quantitative data that we have within the company to really pinpoint what that problem is. The instance in the example I'd use for when I was a user my main scenario was saying, hey, I am a user, I'm a female voice and say, my boyfriend come in, he's not an authorized user, and he has a male voice. That's a very strong indication of like hey, is there security issues. I could use some data to validate, maybe male voices, female voices based on pitch or what have you. To try and grasp for the size of the problem, then understanding that and trying to pinpoint saying, hey, it's apologies, I don't know a lot about voice recognition, but assuming like, hey, there's might be something around intonation or the way the syntax or the phrasing and the pacing of voices somewhere in that area. Perhaps then I can work with my designers, and work with the engineers to identify like, okay, well, if we adopt this new technology that we can integrate with, how could we push a little further in a certain different area. Understood. You bring up gender as one of the ways that you would use to authenticate. Making sure that you are who you are when giving voice commands to Alexa. How would you think about authorization? That's a great point. Obviously, there's challenges with authorization, it all depends on the structure of how you guys manage accounts and account IDs. If you think back to me as a single user, I am on one account, but I also share that with multiple users. You can typically offer what most other systems and other B2B products have, like role-based access controls. You can actually divide it and say, hey, based on different devices, based on different profiles or services that you're integrated with on Amazon, different almost access and permissions from the main account holder. Say if we are in a household with multiple people, I would have to individually grant maybe voice access to all the users. Understood. Those are great examples. We could have gone a lot deeper in that example, but for the sake of time, I also want to move on to perhaps the most important category of questions. But before we move on, just a few highlights. I walk Jenny through essentially a product design tips. Even through that case, as you've noticed, we touched upon several leadership principles such as customer obsession, such as dive deep, where understanding what details present authorization and what details present authentication, and how those are separate. Then lastly, one area where for the sake of time we will not touch upon, which is delivered results, and as well as insist on the highest standards is, how would Jenny, after she's designed this feature ensure that is accessible? Which KPIs which she measure as well as finally, how can she iteratively improve on this feature? For example, is it 100 percent accurate? Probably not on the MVP. How would she continually improve on its accuracy?
