00:03:05 · Rahul Vohra
[00:03:05] S7: I think we started last year in February. And believe it or not, nobody really knew anything about AI. We didn't have a machine learning engineer on staff. We'd never needed one. It just didn't turn out to be important for what we were building. We hadn't really used large language models ever. We were sort of vaguely aware. I mean, how could you not be aware of what was going on? But it was around January, February when it became incredibly clear to me, as I think it did all of us, that it's an existential moment. And these moments don't happen particularly often in the history of of startups, but it was obvious that it was existential, that everything would change, and that this is something that had to become one of the core pillars. It's like a top three priority if if you... We have three priorities as one of them at the company. Now because we didn't really have anyone on staff who knew what they were doing, and we didn't have time to wait and hire for this, and also it was something that was going to be existential to the company, we actually approached it in a very different way than we do most new initiatives. And so for context, we, at the time, I think around a 100 people, around a 110 people. Even so, we didn't assign this project a product manager, as you might add a company of that size to run it. We decided that I would actually run it personally. And fortunately, I just hired a president, so I was able to hand over day to day operation and management of the company to Paul, our president, and we created a small tiger team, if you will, of myself, a designer, and a handful of engineers. And the idea was to essentially run it like a startup, devoidable process. We just get together regularly and build stuff, and we'd found a Fiat. I I think a lot of what a founder has to do sometimes is, in the absence of data, just say, this is what we're going to build. Trust me. I will own it if it's wrong. And if it's right, we'll move on and build the next thing. But you need to be able to short circuits the decision paralysis that can sometimes happen, especially as companies get a little bit larger and debating things becomes the way in which decisions are taken. And debating films is great. That's actually how many decisions should be taken. But for something brand new like this, I wanted to be able to get at it really, really quickly.
00:05:04 · Rahul Vohra, S0, S1
So it was small. It was fast. It was chaotic. It was stressful. We did it really, really quickly. And a few months later, I think it was June of last year, we launched Superhuman AI, the very first version, which lets you write with AI. So you can jot down a few notes, we'll turn it into a fully written email that's in your own voice tone. We match all the emails you've already sent. This feature that we're now all very familiar with in basically every application that we use. That was the very first thing that we built. I really captured the hearts and minds of our user base, of Silicon Valley. Was it was a really big deal at the time. And that's an example of what we call on demand AI, relatively easy to run, cheap to run as well. Ad[00:05:42] S0: This episode is brought to you by Google Chrome. You think you know a browser, but Gemini and Chrome, that's new. They can help you with practically anything on the web, like restoring a vintage motorcycle from a 50 page restoration block or finally break down that long article you've had open for weeks. Gemini and Chrome is here for it. Ready to make anything online make sense? There's no place like Chrome. Check responses, set up required compatibility, and availability varies 18 plus. Ad[00:06:07] S1: How do you guarantee your Jagermeister is always ice cold? Well, you could move to Antarctica. Sure. Frostbite is a thing. Your dating apps won't let you set your radius to 3,000 miles, And your neighbor is an emperor penguin who honks outside your igloo. Or you could just keep your Jagermeister in the freezer.
00:06:07 · S1, S9, S2, S3, S4, S5, S6
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00:07:22 · Rahul Vohra
[00:07:22] S7: Because it's only operating when people actually click the button or when they use the feature. But that gave us the confidence to move on to the next phase of AI, which we call always on AI. So you move from on demand to always on. And this is AI that is just constantly running in the background all the time. Much harder to build, much more expensive to run. And the very first example of that that we built was auto summarize. So imagine when you receive an email, a one line summary that is pre computed and always available on top of that conversation. And when new emails arrive, it instantly updates. If you wanna find out more, you just hit a shortcut, then you can see some bullet points about the conversation. People really love that, and that then gave us the confidence to build instant reply, which is also an always on feature. Imagine waking up to an inbox where every single email already has a draft reply. You would just hit edit and then send, and sometimes you wouldn't even need to edit. And that then gave us the confidence to build the next thing. So we've been increasingly working up this confidence ladder, I would say, taking on more ambitious, more expensive projects. And now I'm not an IC on that team. But for the first six months I was, and it was really to kickstart it. Now it's being run like a regular project at Superhuman. Well, is one of the great things about having a great leadership team. And as I mentioned, I just hired a president. So I was able to leave the explanation and the delegation and the authorization of this idea to Paul. So he explained to everyone what was going on. He figured out who the resourcing... I didn't really have to explain or sort of go through any difficult conversations to make this happen.
00:08:49 · Hannah Lee
[00:08:49] S8: There are all these other AI agents that are coming up that doesn't just deal with email. There are these... Everybody's building all these AI tools to help you answer emails, book a call, book calendars for you. And there are also other email softwares that are trying to emulate a lot of the features that have been popular with Superhuman as well. How do you see all these AI agents coming along and all this competition coming along? And with the AI, how are you seeing this landscape, and how do you see Superhuman sort of moving the next steps forward?
00:09:21 · Rahul Vohra
[00:09:21] S7: So this topic of competition has obviously come up so many times over the years at Superhuman. Every single time there's been a new email client, for example, in the early days, maybe some people in the company would panic, and I would talk about it. And, you know, we'd get on with building great software and delivering value to our customers. And every single time, it's just come and gone and come and gone and come and gone. And Paul Graham has a good piece of advice about this, which is don't obsess over the competition. It actually doesn't really matter. Just focus on making your own customers, your own users incredibly happy. So that's what we've always done. And I I think the the AI wave is no different. I think the agent wave is no different. We see Superhuman as a core part of this evolution of the productivity landscape. We are working really hard towards building AI agentic future. We believe in a world where one day you will have a Superhuman AI agent, and you can start to see if you use the product today, the the beginnings of that with features like Ask AI. You can imagine an AI that can triage your inbox on your behalf, that can schedule meetings on your behalf, that can write and one day even send fully written emails on your behalf. An AI agent that can work not just on tasks, but complex problems, break them down into sub problems and work on them in parallel or in... That can resolve ambiguity, ask you clarifying questions, go off and research things, interrogate internal systems, APIs, or even other agents. And I think that world isn't tomorrow's world, obviously. I've just described a lot. But over the next year or two, we will actually get that in some places faster than in others. But that is what we're building towards.