01:23:11 · Luca Ferrari, David Senra
[01:23:11] S1: made a lot of changes. We rebuilt the org vastly. So it was roughly 350 team members. We made it substantially smaller, I think, a year, a year and a half after the acquisition closed. We were more around 50 to 60 team members. [01:23:32] S0: Hold on. So when you acquired it, they had three fifty people working on the product Approximately. The Okay. And you're cutting that down to, let's say, 50 to 60. This is what we were talking about before we started recording, which I think is really important. And this is why I like Adam from App eleven too, because his whole thing is like, if you factor in either his cash flow to employee ratio or market cap to employee ratio, it's just like, that's a very interesting metric, where his whole thing is like, I'm doing this with 400 employees. You mentioned previously, it's like, to see what can be done and how efficient a business could be run, it's very similar to like... It's a good example for other entrepreneurs in the same way that, like, other runners didn't crack four minute mile, for example, until somebody did it. And once they see somebody did it, then you just see it happen all the time. Yeah. So why could you do this with, let's say, 300 people less than they could have? [01:24:27] S1: I think there are different factors. One is the access to talent. We... We've been able to build a... An employer brand, a company that... Where some of us people wanna work. We got 800,000 job applications last year. We hired 300 people. So... And and if you're running Evernote, even if you're Steve Jobs
01:24:27 · Luca Ferrari, David Senra
[01:24:27] S1: I think there are different factors. One is the access to talent. We... We've been able to build a... An employer brand, a company that... Where some of us people wanna work. We got 800,000 job applications last year. We hired 300 people. So... And and if you're running Evernote, even if you're Steve Jobs [01:24:47] S0: 800,000 people are not applying to Evernote.
01:24:50 · Luca Ferrari
[01:24:50] S1: Yeah. Exactly. And it's not it's not anyone's fault. I mean, the... That that executive team was was doing the best they could with the with the resources they reasonably had available. So we had good fortune to be able to take advantage of an arbitrage in access to talent. We also have a massive advantage in that each of these businesses matters to us, but it's not everything. So we can take risks. For example, if you're running Evernote, and that's all you do, that's a standalone company. And you make the change I just described in terms of headcount. If something goes wrong, you're out of a job, as say, a CEO, and realistically, you're done because that will be the blemish on your CV that you can never clear, pretty much. It's not that we want something to go wrong if, say, Evernote is part of Bending Spoons, but we have... We can make bets that are... The expected outcome is highly appealing, but maybe they are a little bit more risky, and so not so appealing if that's all you do with your life. The upside of, again, it's almost like insurance. On average, we get it right and it's a great value. Occasionally, maybe we make a mistake that would be painful if it were... If that business was run as a standalone company. But, you know, net net, we do so much better, and we learn so much faster, and the good lessons we learn from our business, we can port them and apply them as relevant to all other businesses. Three, we had access to that technological platform. So talent levels, ability to take some risks that would be uncomfortable for that management team, given their boundary conditions. Three, the technological platform I discussed, it just enables us to do so much more with fewer people. But if you're running Evernote standalone, you're not going to have resources to develop those technologies. Also, you don't have the business case because we can amortize those investments over all of our businesses and increasingly more businesses is required. It's difficult to justify if all you do is Evernote.
01:26:52 · Luca Ferrari, David Senra
And then again, those perverse incentives I mentioned earlier, whereby if you're judged by Evernote and Evernote alone, making a change that would, for example, result in a smaller number of monthly active users or subscribers will get you so much hail, even though it's maybe the right thing to do for the business, could make some of those unpopular decisions more easily and take full advantage because the business has been thriving relative to previous trajectory and financially and in terms of customers. So these are some of the big reasons. The changes were sweeping. The org, we rebuilt it, I mentioned, was a lot smaller. By the way, today, Evernote, ran it with about 20 people. What? Yes, because in the meantime, you keep improving. I'll describe the improvements we made, but some are fundamental improvements in the underlying technology code base that enable the team to do more with with fewer resources because everything gets a little bit cleaner and more maintainable and manageable. Part of it is our operating system of technologies has gotten so much better in the following two, three years that we're so much more productive. Especially with AI, we have had some close to breakthroughs in productivity. Can you talk about that? [01:28:08] S0: Yeah, sure. Everybody's interested in this right now. There's a bunch of founders that have already been on the show that are coming back on, and we're just going to do an hour of how, literally, they're redesigning their entire organizations with AI.
01:28:19 · Luca Ferrari
[01:28:19] S1: Yeah, we've been using AI pretty aggressively for as long as I can remember. Certainly in 2018, I'd like to say we're using it to predict user lifetime, basically to inform our AB testing. But I would say over the past two years, with very rapid progress in LLMs we've been able to have some major breakthroughs in various areas, especially software engineering and data analysis and product design. I'll give you a couple of examples. For design, we recently actually deployed a tool we built in house called Diagram. Whether you're a designer, a product manager, a growth manager, you go to this tool, it looks a little bit like Cloud Design, just broadly speaking, but it's specialized in our particular context and fully integrated with everything else at Bending Spoons. You can just tell the tool to pull up screens for the app you're working on, so it's Evernote, for the relevant features, and then you guide it as it produces new versions of those interfaces. And it will do so by automatically following the design guidelines that the, say, the head designer for that tool has laid out in some documents somewhere. Don't have to know where they are, like the tool nodes. You just tell it what you need, and they'll give you work that the head designer would typically approve. It will automatically look into the code base to know how the different interfaces interact functionally, it will make proposals that make sense from that point of view. And then once you're happy with your proposal, it will develop the code for you, and then the lead engineer will be able to review and approve it if it's fine. Then automatically, because it's integrated with our AB testing system, you'll have a new segment where you're going to test that new onboarding flow or whatever. If you had the skills before, were a product designer, now you can do it sometimes in maybe 1% of the time. In many cases, it's actually a better result because it's so precise and in just few months we tend to miss things. But interestingly, it enables doing design work for people before who couldn't, like product managers, software engineers, growth managers. Now a lot of the inefficiencies stem from I'm a product manager, have an idea, I want to test something, but I need to wait for the product designer to be available. Then I need to explain to them what I have in mind.
01:30:37 · Luca Ferrari
I failed to explain it properly. Get three days later, I get work back and it's not what I meant. Need to explain. The inefficiencies stemming from this exchange of information, we humans are insanely inefficient at exchanging information. We're quite efficient at absorbing information. But when we have to articulate ideas, language is very... And it's better than not having language, it's very inefficient. And more so when it's with another human with whom the iteration cycle will be slow because they may not be able to do the task immediately. Even if they do, will take them time. But with the machine, we can tell it, it will do it right away, and it will take them a fraction of the time so you can actually iterate very quickly. So overall, you get to the result in a tiny fraction of the time, but interestingly, you can do it even if you can't design. So this overall makes our teams a lot more efficient. This is an example. Another example is something we call old spooner, or it stands for alter ego or alternative spooner. And it's basically an agent that lives in Slack. We use Slack for communications. That has, by design, the very same access you do as an individual in the company. So it has access to the same tools, to the same degree. If you have full access, partial access, it mimics you. It's meant to be you basically, but artificial. And you can instruct it to do pretty much anything you could do, it could do. Some things it will do better, some things it will do worse. So we have Evernote. We we have a channel on Slack where we can report feedback on things we think could be improved bugs or new features. And I was there to to provide input on something. I I was just using the tool the tool and it failed at something and I wanted to to to relay that. And I I saw live one of the best users of old Spoons by one of my colleagues. She runs Evernote and and she wrote, you know, she... In this channel, she tagged old Spoons and said, I noticed this bug. Could you please go to Moros, which is, again, back to the integration of our tools. It's it's our customer support tool that collects feedback from users to check whether it's just I got unlucky or if it's a a widespread phenomenon or issue, and then report back so we know how to prioritize it.