Ep 30: Superhuman CEO Rahul Vohra on the Future of Email with AI and the Role Agents Will Play

Superhuman recently launched AI-powered Summarize and Instant Reply features, and has since processed 4 billion emails. On this week’s episode of Unsupervised Learning, we sat down with CEO and Founder at Superhuman, Rahul Vohra. Rahul shared with us what email will look like in the future, the internal product design decisions in building Summarize and Instant Reply, why he’s bullish on the agentic future, and why and how startups should go after incumbents.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  I think if you were to go back a thousand years when we were subsistence farming, or we were hunter gatherers, or maybe even like 1500 years, those people would look at our jobs and go, that's not work. You're just playing.

• 0:11Jacob Effron?

  I think a lot of people today would look at Pat and my job and say, that's not work. But it's kind of you to go back a thousand years. This is Unsupervised Learning, Redpoint's AI podcast. I'm Jacob Effron. I'm joined by my co-host, Pat Chase. And today, we had an awesome guest in Rahul Vohra, the CEO of Superhuman. Superhuman is the lightning-fast email tool that has taken the tech world by storm. And we hit on a lot of really interesting things, including all the AI features Superhuman's building, how they think about the future of email, and especially the role agents will play.

• 0:35Speaker 00

  Journalists perennially claim the death of email, and of course, it never happens. And there's actually a pretty good reason that never happens.

• 0:42Jacob Effron?

  And we talked about some really interesting product considerations when it comes to taking on incumbents and getting people to use new workflows. What areas are you like most excited about? What areas are you not as excited about as you do on the investing side?

• 0:53Speaker 00

  Where I was bullish and continue to be bullish is...

• 0:57Jacob Effron?

  I think folks are really going to enjoy this one. In general, if you're enjoying the podcast, please make sure to like, subscribe, share with a friend. We're trying to get the word out. And definitely stay around for Pat and my debrief. Well, thanks so much for being here. Really appreciate it.

• 1:09Speaker 00

  Yeah, thanks for having me.

• 1:10Jacob Effron?

  I've been excited for this one for a while. As Pat and I were saying, I think everybody in Redpoint is a Superhuman user, and we're all beneficiaries of these AI features you've done. So it's exciting to get to dive into them. You know, I figured we'd start like in the most broad futuristic way we could, which is just, what do you think email is going to look like in five, 10 years?

• 1:28Speaker 00

  I love this question because I'm, I mean, you've been in the business long enough. I'm sure you've seen journalists perennially claim the death of email, and of course, it never happens. And there's actually a pretty good reason that never happens, and it's to do less with email and more with email addresses. So think about the very first thing that happens when you join a company. You get an email address. And why is that? It's because the company needs a way to address you in a way that is owned by the company. So some people say, well, couldn't you use your cell number as your unique identifier? Well, the problem is that belongs to you. Unless the company is provisioning the number, you're going to take that with you. But if you think about an email address like [email protected],

• 2:12Speaker 00

  there really isn't any more succinct, human-readable way to talk about me as a specific company in a way that's owned by the company. So it's given to us to identify us. It's the unit of authentication. Even if you're going to use something like an Okta or a Rippling or some other SSO solution, guess what? You're probably logging into that thing with your email address. So it's like this underlying piece of infrastructure. So email addresses aren't going anywhere. But what email is, is obviously going to change. And there are lots of themes that we can talk about, but I think two that are very top of mind today, of course, this being an AI podcast, one is AI. And we can get into all of the details on how email will change with respect to AI.

• 2:56Speaker 00

  But I think the the short summary is we're heading towards an agentic AI future. So you can imagine AI agents in and around your email doing things in your behalf. And then secondly, collaboration. So we were talking about this just before we started recording. You all at Redpoint, you superhuman, you've probably started to see some of our team features, team read statuses, team reply indicators, team snippets, team scheduling. These are some of the basic things and actually some of my favorite features because you don't have to remember to use them. So long as all of you have turned on read statuses, you can actually see when a founder has opened your colleagues' emails, which sometimes can make the difference in closing that deal. So really important stuff.

• 3:38Speaker 00

  Where we're getting to, actually pretty shortly, is going to be the ability to share a thread and then comment on that thread.

• 3:46Jacob Effron?

  I mean, I'm intrigued by this this notion of, you know, there'll be a bunch of agents running around our inbox, helping us do things like, maybe for our listeners, just paint the picture of what some of those might look like, you know, down the lawn.

• 3:56Speaker 00

  Yeah, so let's actually zoom out and I think it might be helpful to to share the context of AI in Superhuman. And there's a very particular phasing that we use that I think folks might find helpful. And then we can get to the sort of the futurism stuff of agents. So there are three flagship AI features in Superhuman. There's actually a bunch of ways we leverage AI, but three flagship AI features. And the first was write with AI. So you simply jot down a few words and then we'll turn those into a fully written email. And we match the voice and tone in the emails you've already sent. So it sounds like you. And once you've written it, you can then shorten it, you can lengthen it, you can improve your writing, you can fix all your mistakes, you can even change language. We built that, I think, last June or July. We then followed that up with our second flagship AI feature, which was Auto

• 4:41Speaker 00

  Summarize, which we launched last We love that one. Great feature, one of my personal favorites. I actually have it on my phone today. That hasn't released yet. Pat writes some really long emails and so it's very Always needs the auto. It's very helpful. The summary. It's honestly game changing. And so for folks that don't know about this, above your conversation, imagine a one-line summary that summarizes the entire thing. It updates instantly when new emails arrive. If you want more information, you can just hit a shortcut and then you can see a bullet point summary. And as you guys have probably seen, this changes the way that people work because you almost always read the one-line summary first. And sometimes you don't need to read the email because the one-line summary was enough so you can just mark done or hit snooze and come back to it later. Totally. So that was our second flagship AI feature.

• 5:25Speaker 00

  And then our third, that we released just a few weeks ago, is Instant Reply. So imagine waking up to an inbox where every email already had a draft reply. You would just edit and then send, and sometimes you wouldn't even need to edit. So that's the thing that we released a few weeks ago. It's blowing people away. Of course, you know, we consume DNA in our company. Everything is instrumented and we have metrics for everything so we can actually measure how long it takes for people to write and send emails. And users who use Instant Reply are writing emails twice as fast, i.e. in half the time as before. That's real business impact, right? This is actually blew us away. We were not expecting it to be that affected. Okay, so those are the things we built.

• 6:09Speaker 00

  In terms of roadmap strategy, and I think this sort of applies to any founder who has an application, has some distribution, they're thinking, okay, what do we do? Like, what's a sensible strategy for progressing through this? Phase one, what we started with was on-demand AI features, like RightWithAI. These are features that the user has to remember to use. They're pretty easy to build, generally speaking, and they're pretty cheap to run because, you know, unless the user's mashing the same key all day long, they're not going to keep using them all day long. So it's a good way to dip your toe into the water and to see, A, do you understand the technology, B, how good is it, and C, do users love it? For us, seeing how much users loved it, that gave us the confidence to move on to the next phase.

• 6:54Speaker 00

  And this is the phase of always on features. Features like auto summarize and instant reply. Now, these are a lot more ambitious. They're a lot more difficult to build. They are a lot more expensive to run because they're always on, always working for you. And they operate at massive scale. So to put this into context, you know, when you train an L L M based on emails, the corpus most people use is the N one corpus. That's 500,000 to 600,000 emails if you poked around with it. Since we've launched auto summarize and instant reply, we've already processed 4 billion emails. I don't know how many orders of magnitude more that is, but it's a lot.

• 7:32Speaker 02

  I won't ask how many of those were from.

• 7:37Speaker 00

  So that was the next phase. That was phase two. And that's the phase that we're in right now. We have more always on A I features coming. And it paves the way and creates the foundation for phase three, which we alluded to at the beginning, which is our agentic A I future. So I believe the future of A I is we'll all have agents, probably multiple agents each. And you can totally imagine an inbox or an email agent. These agents will be mostly autonomous. You can give them goals, not tasks. They'll be able to plan and break those goals down into subtasks, work on those subtasks serially or in parallel. They'll be able to handle and resolve ambiguity by asking you questions and maybe interrogating other systems, perhaps even internal A P I's or your C R M.

• 8:22Speaker 00

  They'll even be able to interact with other agents. So that kind of an A I, we think, is where we're heading towards. And that will free us all up to be more creative, strategic and impactful.

• 8:33Speaker 02

  That's amazing. I love that. And it's been really cool to see you guys ship instant replies and all of these new features. And instant replies was interesting. I love the product and use it every day. Even if I wasn't going to use the replies, just having the three options of, oh, those are kind of the three ways that I could answer this email. I found that helpful in getting to a decision faster. So it's cool that you're kind of seeing that already have real impact on your users.

• 8:59Speaker 00

  Yes, absolutely. And that was one of the things that doesn't come across in metrics, but obviously we qualitatively analyze every feature as well. And one of the things we keep hearing is, wow, you know, I was sitting on this email because A, I didn't know how to reply. Or B, it was just like, it was just below the threshold of doing, but it was still important, but just below the threshold. And the fact that it was an easy do it this way made the difference and people are actually now replying to things they otherwise wouldn't.

• 9:25Speaker 02

  Totally. Yeah, it's, it's, it's super cool to see. And I was thinking on, on mobile, it would be amazing too of like then being able to kind of draft or have the AI help you when you're on the road is, it was also really cool.

• 9:37Speaker 00

  I think it's the case that basically every AI feature you can imagine is 10 times more useful on mobile.

• 9:44Speaker 02

  Yeah.

• 9:44Speaker 00

  That was the case with, right with AI. Trust me, it's the case with auto summarize. Again, we only have it internally coming out probably in a few weeks. And I believe it will be the case with instant reply as well.

• 9:54Speaker 02

  Yeah, super cool. What's been the, the team structure that you guys have kind of put around AI? Or how have you approached structuring the team to ship all of these AI features so quickly? It seems like you guys are really moving incredibly fast and have pushed a lot of things into production faster than, than almost any company out there.

• 10:11Speaker 00

  Wow. Well, I'm glad it feels that way because to me it always feels way too slow. And many other companies had a head start, but you know, I think, I think one thing we do well, even if sometimes we start something late is when we do something, we take it really seriously and like it's full steam ahead. So we began our AI journey, specifically our generative AI journey last February. We were doing AI things before then, obviously, we'd released autocorrect in January of last year. And that doesn't use generative AI, but it is still the best autocorrect that you'll find on the planet.

• 10:45Speaker 02

  Was it like immediately apparent to you when ChatGPT came out like, hey, this is going to be, you know, this is going to change the product or this is an all hands on deck effort? Or was there some moment where you were like, yeah, this is now time to dedicate a bunch of resources?

• 10:57Speaker 00

  It wasn't immediately apparent and.

• 11:00Speaker 00

  You know, this is, I think this is one of those moments where I really had to step out of the office and just take some time out to zoom out and think, okay, this is a really big deal. And there's this conference that folks may be aware of, the lobby conference that David Huonik puts on. And it's beautiful conference takes place in Hawaii, three or four days. It's not very big, like a hundred or so people, like half founders, half VCs come and just basically hang out with each other and talk about the future. And obviously, the topic last, I think it was February or March, was AI. And being able to have that conversation in that environment without having to worry about running the business day to day was what gave me the perspective to realize how important this is. So I came

• 11:45Speaker 00

  back to the Bay Area and I was like, oh my gosh, we have to prioritize this. Everything is about to change very rapidly. But it was very hard to prioritize because we usually do prioritization in one of two ways. We either try and figure out how valuable is this feature going to be for the user, or how valuable is this feature going to be for the business. And it was hard to know how valuable this feature would be, or this collection of features would be for the user, because we couldn't predict how well they would work, or how they would feel. And it was hard to make a business case for them because we didn't know how much revenue they would bring in, or how quickly they would help growth. And it's very rare that you have something like that. Normally, you're able to, excuse me, reason about it on two dimensions. So what we did was instead, we

• 12:29Speaker 00

  took a philosophical stance. We stated our core belief, which is that LLMs would change everything. It wasn't going to be obvious how, and it wouldn't be overnight, but we knew that, or I knew that the way that we work was going to change. You know, my job at that point is then to basically use founder fiat and say, this is it, folks, like, we're going in this direction. Obviously, it's not that easy. You have to tell the story many, many times, but that's essentially what we did. Very fortuitously, in February, I had also just hired a president, Paul Tessier. Now, Paul is an amazing operator, an amazing leader, a chief product officer twice before working at Superhuman, and he's exactly the kind of person I brought in to make these kinds of changes possible.

• 13:13Speaker 00

  So he and I discussed, and we came up with a new operating model for getting AI off the ground. So we have two operating models. One is alpha mode, and the other is theta mode. Probably wondering why alpha mode, why theta mode? You've probably heard of alpha brainwaves. The alpha brainwaves are when your brain is most coherent and in the present, and theta brainwaves are observed when your brain is thinking about the future. And so when a team is operating in alpha mode, which should be the default, they operate mostly autonomously, you give them goals, and they're held accountable to the goals. That's normal business as usual for most Silicon Valley companies. When a team is operating in theta mode, it's quite different. It has an embedded executive, in which case was me.

• 13:56Speaker 00

  We all carry that goal together, and the executive is doing individual contributor work on a day-to-day basis, and the expectation is this project can't fail because it's existential, right? And it moves really, really fast. So starting in February, we went theta mode and AI, and I knew basically nothing. I mean, which is kind of ironic because I dropped out of an AI PhD, but that was a very long time ago, so I had to catch up.

• 14:21Speaker 02

  Well, I feel like everyone knew basically nothing because it was all so new, right? Even if you studied AI a couple of years ago, then everything changed with LLMs.

• 14:28Speaker 00

  Yeah, like my stuff is 20 years old, so I was like, at least I had that background. And I very quickly got up to speed. We staffed a team with one designer, one marketer, maybe two or three engineers, and we just sat down and knuckled. And at that time, no one knew anything. No one even knew from a product's design perspective what the user interfaces should be, right? Should we have a sidebar? Should it be conversational? Should it be built into the surface area of the product? Do you write the prompt, then select it, then say, "turn this into an email"? Or do you enter the AI mode first and then put your prompt there and say, "turn that into an email"? And, you know, these things, maybe they sound small, but they're actually very big decisions in terms of the usability and how these things feel.

• 15:11Speaker 00

  So we we knuckled through that for a few months and then we launched Right With AI, which at that time we called Superhuman AI, last summer. And I mean, this thing went viral in a way that Superhuman hasn't been viral for a few years. And it was just like, oh, my gosh, AI has the ability to, you know, just make a product, make a company top of mind for everybody again. And that's something that's continued to be true for us since the summer of last year until now. I post a thirst trap graph on Twitter yesterday.

• 15:48Jacob Effron?

  I was gonna ask you about it, because I saw the hobby stick.

• 15:51Speaker 00

  Yeah, that's AI. Like, that is growth that happened because of AI.

• 15:55Jacob Effron?

  Amazing. Is that AI usage, or I guess?

• 15:58Speaker 00

  No, no, it's even better than that. That is new monetized retained seats per week.

• 16:02Jacob Effron?

  Wow, amazing. Yeah, it was a good, that was a good graph. I liked your caption, too. Just keep going.

• 16:07Speaker 00

  Just keep going. I mean, yeah, startups are hard. I've been doing this for seven or eight years. And sometimes there are some months where you're like, oh, my God, this is so hard. We need a breakthrough. We need a breakthrough. But I am reminded of, I think Paul Graham puts it best, just don't stop typing. Because one of the ways that startups die, you run out of cash. OK, don't do that. Raise money, don't spend too much money, make revenue. Other people talk better about that. Co-founder fallouts, don't fall prey to that. And, you know, I'm not the guy to talk to about that. We've done fine, thankfully. But the thing that if you get through those two things, and if you've lasted seven or eight years, you've got through those two things, the thing that then gets you is you just run out of steam, right? It's just like, it's just too hard.

• 16:50Speaker 00

  And SaaS is especially prone to that because it takes a very long time to build a great SaaS business. You guys know this. And so just keep going.

• 16:59Jacob Effron?

  So interesting. And I think, you know, I mean, one, it's interesting, just the kind of the white space of design decisions you guys had early on. And, you know, to your point, there are so many different ways you can do it. Obviously, you know, finding an intuitive way to have it seamlessly fit into the product feels like the North Star, but there's, you know, it's all kind of untrodden territory. Like, I don't even, I guess you probably just tried a bunch of the different designs and figured out which, like, felt the most intuitive to your end user? Or how do you, how do you even come to the design decisions you guys reach?

• 17:27Speaker 00

  Well, why don't we take a specific Yeah. feature like Instant Reply, which is the one that we just launched. Again, very non-intuitive. No one has built anything remotely like this. Actually, that's not entirely true. I think there were precursors to this. You could argue Gmail's Smart Reply is a precursor. So this is the three little blue widgets it has under emails. All it does is it puts the text of that widget in the email. And I think Microsoft demonstrated in concept a co-pilot feature where there are some little widgets and you can click them and it writes a really long email. But there were many product decisions that we had to take to get Instant Reply feeling right. So for example, the first one was, should they be visible before you start replying?

• 18:12Speaker 00

  Or should they only be visible after you start replying? Or maybe they should be visible at both times? And my gut sense, for what it's worth, was they shouldn't be visible until you start replying. And I had a very logical argument for this. My logical argument was you don't actually reply to most emails. So why would we clutter an interface that we've tried so, so hard to keep minimal over these last seven or eight years with this thing that you're not going to use all the time? Surely we should wait until you actually start replying? And then I realized, oh, wait a minute. Half the value of this feature, obviously, is to make you reply really quickly. But it goes back to what we were saying before,

• 18:55Speaker 00

  which is sometimes the activation energy to hit Enter is the problem. Right? Sometimes you need a bit of goddamn inspiration. You like, you need to see the three ways to actually do the thing. And that wasn't obvious when we started building the feature. Right? I think it wouldn't have been obvious to really any product design team. Like, you look at it and you go, okay, Instant Reply. What's it going to do? You're going to reply instantly. But half the value is inspiration to reply, which wasn't obvious. So that was the first thing. I think the second thing was... How do we make it, from a visual design perspective, tucked away and minimal? We have this principle at Superhuman, there when you want it and out of the way when you don't. And that is hard. That's the dream for AI in general, right, in products?

• 19:40Speaker 00

  I know, which actually makes me feel super lucky, because that is the razor that I've been honing. Actually, since I was a kid. Like, I've been a designer since forever. And constantly making software and user interface has been my obsession all day, every day. And so, we were ready. We were ready to take on that challenge. And I wouldn't say we've got it perfect, but I think it's pretty dialed in. We've had so, so many bits of feedback on this feature. No one has said, "Oh, I think these things are too intrusive. Like, I wish they weren't there until I started replying." So we had to dial that in. The next thing was actually the length of the replies. So, RightWith AI, which is a thing that we launched last summer.

• 20:24Speaker 00

  If you've used it, you'll know it generates pretty medium-length replies, right? It probably does a few sentences to a paragraph per point that you give it. And that's by design. That's actually what people want. We thought that's what people would have wanted with instant reply as well. Or I guess we didn't really question it. We kind of started with the prompt that we designed last summer for instant reply.

• 20:45Speaker 00

  But it felt weird. Like, you'd hit Tab a few times, you'd hit Enter, and it would put the thing in. And it'd be like, "Oh, I..." There was like an impedance mismatch here. I'm going really fast. And the thing that was put in is actually kind of medium-sized. Something didn't connect. And then I realized, when you're moving really fast, you actually also want the messages you create to match that and be really short. So instant reply, by design, only puts in one, maybe two sentences, right? And often doesn't even wrap the screen. It's just a really quick, snappy response, which matches the impedance of you moving, which means you can continue to move quickly. Because what you don't want is to be moving quickly, hit Enter, and now you have to proofread a really long email.

• 21:31Speaker 00

  And then maybe edit it, right? You want to hit Enter, maybe change a word, and then hit Send and move on. The interaction design, you know, it's funny. I was at OpenAI yesterday and doing a talk for some A16Z founders, and...

• 21:46Speaker 00

  We talked, obviously, we're at OpenAI. We talked a lot about prompt engineering and fine tuning and RAG and model customization and all the other things that startups are doing today. What I realized was the reason why, or one of the reasons why instant reply is so effective isn't the prompt engineering and all of the stuff that we did on the AI side, oh, that's really, really important and that was very hard. It's actually the interface itself, right? The fact that you can mash tab and hit enter and that's it is key to making it work. And early versions of the feature didn't work that way. Early versions of the feature, you had to sort of, I think you had to hit down, then you had to hit left or right.

• 22:29Speaker 00

  And this, by the way, this is one of the things that I spend a lot of time watching out for. The arrow key motion is a shoulder motion. It's an elbow motion. And if you measure the time it takes for people to do it versus tab enter, it's like 10 times as long. It's also quite painful. You do it too much, you get RSI and for what it's worth, most people don't even bother doing it. So one of the changes we made was to switch from down and arrow keys to tab and enter, and it instantly became 10 times more usable and 10 times faster to use. Wow, so interesting. And obviously, this is just the story of superhuman, right? A lot of what we do is like really minor, seemingly minor UX tweaks like that, but you do 200 of them and you have this product that feels completely different to everything that came before it.

• 23:14Speaker 00

  And then, speaking of prompt engineering, that was the last thing that was really, really tough. The, if I were to show you the prompt for this thing, oh my God, like it would blow, it would blow your minds. It is so big. In fact, our partners at OpenAI were like, we think you're the partner with the biggest prompt.

• 23:32Jacob Effron?

  You were like really pumped for the longer context windows. You're like, all right.

• 23:35Speaker 02

  Like make Jacob sound more professional, just do it, do whatever you can.

• 23:39Speaker 00

  It was actually funny. We specifically say, avoid corporate jargon, like we apologize for the inconvenience.

• 23:45Speaker 02

  I actually really like this about the superhuman AI, and I don't know if that's what makes it sound, it sounds like something that I would have drafted or, you know, that it sounds like a human versus a bunch of the other things. You can kind of tell this was drafted with AI and then that has the worst. Effect if you're receiving it, right? If you're receiving one of those things that seems kind of extra verbose or whatever, and you know it was written by AI.

• 24:10Speaker 00

  Yeah. And I think this goes back to what LLMs are trained on. We just don't have great training data when it comes to emails, which I think puts any email startup, including Superhuman, in a great position because our customers actually do want the AI to sound like them. And that's a thing that they're willing to let us help them achieve.

• 24:34Speaker 02

  How do you actually make it sound like? I mean, does that end up being like, does that influence the prompt you do? Or do you actually end up like, kind of fine tuning to some extent like the output? Or, you know, how do you get it so that like, my emails would sound different than Pat's? Or how do you see that evolving over time? Hey, guys. This is Jacob. Hope you're enjoying the episode. We're trying to get the word out as much as possible, so please share this episode if you think others will find it interesting. Now, back to the show.

• 24:58Speaker 00

  We avoid fine tuning as much as we possibly can because it takes time, it costs money. Actually, the money's the less important side. It takes time. You have to assemble a data set. You have to tag it. The training takes a while. And most importantly, you don't really get to transfer that as the models update from one version to another, even successive versions of the same model or model generations. And so, avoid fine tuning. That's sort of been our mantra. And push prompt engineering as far as it will go. And yeah, I think this is why OpenAI were like, wow, what you guys have done with prompt engineering and multi-shot learning, like basically it's other emails that this person has written are like this.

• 25:41Speaker 00

  It's pretty interesting how far you can push that. I think you can push that really, really far.

• 25:46Speaker 02

  Have you guys found any of the tools for prompt engineering or evaluation? Any of those helpful? Or have you had to build those types of things in-house? Or like, how do you think about developing these prompts and iterating on them? I'm sure they change in version and, you know, there's a bunch of intelligence that goes into those.

• 26:04Speaker 00

  Yeah, that's actually been the hardest thing about working with LLMs as a technology. And the most surprising thing is how even successive versions of the same model break what we thought was a great prompt. So when we wrote the auto summarized prompt last November or so. I think there was a January version of GPT-3.5 Turbo, which just completely broke it.

• 26:27Speaker 00

  And we were like, why? You know, the prompt looks reasonable. It's, we weren't doing anything too weird, but it just didn't, you know, didn't work properly after that. So we've had to build a pretty robust regression testing and evals framework on top of it. We haven't built it in-house. You know, I fully believe it's, it's a startup to do, so we use BrainTrust. Okay. And we'd be very happy with that. Every time we change a prompt or we change the model, we have a battery of tests that runs. We know, did something break? Do we need to look at something? And the fun thing about these evals frameworks is you can, of course, use LLMs to assess themselves. So we did this with Instant Reply. Instant Reply, by the way, way, way harder to build than AutoSummarize, especially on really, really long threads.

• 27:12Speaker 00

  You know, a funny example is, let's say someone is joining the company or leaving the company. And these threads often get 20, 30, 40, 50 emails long, right? It's a big, long thread. What the first few versions of Instant Reply would do is, it would be like, hey, Bob has joined the company. And then it now says, Alice congratulates Bob on joining the company. And Instant Reply would be like, thank you, Alice, for congratulating Bob on joining the company.

• 27:45Speaker 00

  I reminded of the bad intelligence from Team America. The, what else did I do? Great reference. I know, right? Other examples would be not addressing the topic at hand. So it will, you know, the thread of the conversation will be about something else and it will go off on a side tangent. Another example would be not addressing the right person and replying to the wrong person. So.

• 28:14Speaker 00

  In the evals framework, we actually ask GPT to assess itself and answer the question, are you addressing the right topic? Are you addressing the right person? Is the response that you created as long as it should be? And a few other ones as well. So that's been the most surprising thing and we rely on brain trust to do that.

• 28:34Speaker 02

  How have you thought about which models to use? It sounds like you're building on top of OpenAI and maybe some of their different models. Have you thought about going down the open source path? Or like, how did you land on choosing the OpenAI models?

• 28:50Speaker 00

  When we started, I mean, it was tough. Like, we peeled off, like I said, maybe three, four, five of us at most. And we didn't have the luxury that some larger companies have, which I think is to sort of do multiple things in parallel. Like, maybe run OpenAI models, anthropropic models, or maybe even Mistral models as well and just see and have that luxury of choice upfront. When you don't have the luxury of choice, I think you have to be even more precise in calculating in the decision that you make. But that said, it wasn't a particularly complex decision. My belief was that, and this is still true, that OpenAI is about six to nine months ahead when it comes to model quality. They are a little bit further behind. They have a lead, but not quite as far ahead, I should say, when it comes to model speed.

• 29:35Speaker 00

  And both of those are super important for our use cases. Speed is actually tremendously important. And they've demonstrated their commitment to aggressively lowering costs. I mean, they don't have to do that, but they're doing it. And so, you know, every time we're thinking, well, you know, this thing is too expensive, I'm able to point to the fact that, well, it just keeps on coming down. And I have every reason to believe that the costs will keep on coming down going forwards. And if you run the clock all the way forwards, I don't think it's that long, maybe two, three years before we have edge LLMs and it's actually running on device. So I mostly see this as relatively short-term cost and the value is going to start accruing elsewhere.

• 30:19Speaker 00

  In this entire ecosystem. So that was one of the reasons we picked OpenAI. The other is they've just been so incredible to work with. So we have a deep collaboration with them. Our executives are talking a whole bunch. Our marketing teams are, our go to market teams are, our engineering teams are. When like we've ran into difficulty with engineering or prompts, they're like, okay, try this, try this, try this. And making instant reply work really was a collaboration between the two companies that that we've been very grateful for. And I think that's because they're a startup and they they they want to win. They want to build AGI before anyone else does. And for all the reasons that they want to do that, and they're very good at collaborating with startups to do that.

• 31:00Jacob Effron?

  When you mentioned cost, I'm curious, like, how does cost play into decisions today? Are there things you would do, you know, if OpenAI is good, like you said, consistently dropping prices? Like if prices came down like 100 times, is there stuff you would do differently? Or is it kind of like, that's not, you know, as much of a consideration today because you're providing so much value for the stuff you are doing?

• 31:19Speaker 00

  If prices came down 100 times, I think in some ways things would stay the same. You know, for example, we don't use GPT four for instant reply. Because GPT four reserved instances have a much lower tokens per minute limit than three, five instances. And actually, the problem with something like instant reply is less the intelligence of the model and more the peak throughput. The problem and the challenge with instant reply and auto summarize is it's a very, very bursty feature. And it needs to work in real time. And it turns out everyone queues up all their emails to send out at 8:55 on Monday morning, which is.

• 32:01Jacob Effron?

  Thought I was the only one.

• 32:03Speaker 00

  Folks, please stop sending your emails at 8:55 Monday morning. Because our queue just gets insane, like it's nuts. And then we have to like, so much of what we've built is queue management and like saying, okay, we have now another billion emails. Okay, let's generate all the summaries, let's generate all the instant replies. And it would be completely infeasible to do that with a model like GPT four turbo. But it is feasible to do it with three P three, five turbo. Now, if costs were to come down 10x or 100x. Could we do it from a cost perspective? Maybe. But I think even from just a throughput and a latency perspective, Fort Turbo isn't going to cut it. So it's not just cost that has to change. I think it's also the advent of massively accelerated hardware,

• 32:46Speaker 00

  things like Grok, that will pave the way for new use cases and new applications.

• 32:50Jacob Effron?

  It's interesting though, because obviously I imagine you're running the model to summarize and to draft an instant reply like, I assume adds up at some point, but the bet you're making basically is look, the stuff keeps coming down. Whatever the cost is today to do this is the highest it'll be for us.

• 33:05Speaker 00

  That and Superhuman was designed this way from the ground up. We do charge $30 a month retail price, a little bit less if you're buying Teams or a contracted account from us in order to do things like this. And in the early days of Superhuman, I'll use margin in air quotes because it's not actually margin, but like the extra revenue, so to speak, would go into things like onboarding and into training. And this was years ago, right? Remember when Andreessen Horowitz led the Series B? And you couldn't self-service into the product. Whereas nowadays, that ratio has flipped. So we went from 85, 15% concierge to self-service. To today, it's flipped around.

• 33:49Speaker 00

  85% self-service, 15% concierge. And what we've essentially done is we've shifted those dollars into AI. It still costs money to serve the business, but we are deploying the revenue into what we believe is our duty to our customers, which is to build the fastest, most powerful AI email experience ever.

• 34:09Jacob Effron?

  It was interesting you alluded to, obviously, I remember my Superhuman onboarding. Mr. Lee, I'm sure you knew too.

• 34:14Speaker 02

  I got the concierge treatment. It felt very important. Yeah.

• 34:19Jacob Effron?

  But I think that one thing that I find so interesting about your story and relevant to a lot of AI startups today is you obviously have been so successful at introducing people in new workflows and getting people to do things differently. And I think this is something that a lot of AI companies are thinking about right now. How do we, AI features look differently, AI workflows work differently? How do you kind of educate your users about that? And I'm wondering, one, you've obviously, the always on ones, I guess, maybe less relevant, but for some of the ones like the writing features, you've obviously had to teach people how to use them. And two, just any advice you'd have for these startups that are thinking about like, hey, yeah, we've got something, a really cool new workflow if you use it, but how do we convince or how do we get people to start using it?

• 34:57Speaker 00

  I believe that the core trick, if there is a trick, is actually to start with the always-on features like auto summarize, like instant reply, and then connect them to the on-demand features.

• 35:09Speaker 00

  In general, like in product management, my philosophy as a product person is 100% reach features are so vanishingly rare that when you have the opportunity to build them, you should build them. And sometimes it's not obvious. So for example, when we could have been starting with generative AI, so this was Q4, not of last year, but of the year before,

• 35:36Speaker 00

  we weren't. And the reason we weren't is because we were busy building autocorrect. And the reason we were building autocorrect is it's one of the very few opportunities to build a 100% reach feature. Whenever you have those, build those. They are so, so rare. Because the main reason startups don't make progress, one of the main reasons is you just end up building stuff and people don't use it, right? Like you probably see this all the time in your portfolio companies. Half the battle is getting people to even use the thing that you built. So we started building the always-on features. A trick is to connect those to on-demand features. Imagine you've just used instant reply, and that's a much easier problem because they're always visible underneath qualifying emails. You now have an instant reply inserted.

• 36:19Speaker 00

  We haven't done this yet, but what we're planning to do is connect it to write with AI. So after you've inserted instant reply, you can imagine a few little buttons in the reply form like lengthen, which is going to be a likely one. Shorten is probably very unlikely, but what would they be? I mean, I'm just thinking about this on the fly. Let's just say shorten, lengthen, and custom. And if you were to tab over to custom, you're now in the full write with AI prompt. When you enter that, you'll see something on the screen like "to get here faster next time, hit command J." And so I think that kind of connection between always-on features and on-demand features is the best way to teach people about on-demand features.

• 37:02Speaker 02

  Very cool. Yeah, I really love the UI that you guys have around giving people options and buttons. And it seems like that is kind of one of the best ways of interacting with AI today versus at one point, people were saying, hey, it's everything's going to be a prompt or chat or that sort of thing. And I think people want more control than that, right? And I just, I think you guys have done a really great job of kind of introducing those to users. One thing I was curious about on the on the pricing side, you talked about, you know, taking the budget that was for the onboarding and then moving that towards AI. And I was thinking about the cost when it came to things like the always on features, right? Then you need to run that model for every single email that each user gets, but

• 37:47Speaker 02

  you haven't charged anymore for Superhuman. And is that by design? Like, there's been other companies out there that have increased their prices, or, you know, I think Notion, they were charging more for Notion AI. Have you guys thought about that? Or how do you think about pricing for AI features going forward?

• 38:02Speaker 00

  I think at some point we will. But that's actually primarily the fact that it's been $30 a month for eight years.

• 38:09Speaker 02

  Yeah.

• 38:10Speaker 00

  It's a very, very different, much better product today than it was eight years ago, obviously. It's just hard to do. You know, we have a pricing project going on right now. And we've talked primarily about AI today. But at the same time, we're building Superhuman for Sales, which is a version of Superhuman designed specifically for salespeople. And it has a HubSpot integration and a Salesforce integration and a recent Open Feed. We've also find that founders love Superhuman for Sales.

• 38:35Speaker 02

  I love Superhuman for Sales. I love the, yeah, I toggled it on. And I love the recent Open Feed is great. Yeah.

• 38:42Speaker 00

  Yeah.

• 38:43Speaker 02

  It's super helpful.

• 38:44Speaker 00

  It's shocking. If you email someone within five minutes of them opening your email, assuming you don't make it weird.

• 38:53Speaker 00

  They're like 20x more likely to reply. Obviously, there's a limit to this. You don't want to be creepy or whatever. And good salespeople and good recruiters and good founders and good investors know how to play this game properly. But it is a superpower and we want people to have these. So there's that line of business. There's the enterprise line of business where it's really exciting. We've just closed a deal with a tier one strategy consulting firm. I can't say which one yet, but they bought Superhuman for 1,500 managing director partners. And the reason they're doing this is we've been able to show that the MDPs are replying to emails eight to 13 hours faster. If you're an MDP, you're running a book of business, you're selling projects, you're running a team, you live in emails. This is real business impact.

• 39:38Jacob Effron?

  Yeah, as a former lowly analyst, that would have been, that would have been nice when I was around.

• 39:42Speaker 02

  You're waiting for your boss.

• 39:43Jacob Effron?

  Yeah, exactly. Turn on your Superhuman, please.

• 39:47Speaker 00

  But this is enterprise. This is, you know, do you have an in tune integration? And I was like, what's in tune? And I was like, oh, my God, there's a whole bunch of other stuff. It's like, do you have data loss prevention? Can you please beef up your anti-phishing features and all of that kind of stuff?

• 40:01Jacob Effron?

  Yeah, not always the most, when I was at McKinsey, we were using Lotus Notes. So not always the most, yeah, not always the most progressive.

• 40:06Speaker 00

  You look way younger than that.

• 40:08Jacob Effron?

  It was like, it was a decade ago. They were.

• 40:12Speaker 00

  So, long story short, pricing is very, very difficult. And like, we have all of these streams of work that we're trying to figure out. How do we price enterprise? How do we price Superhuman for sales? How do we price like a platinum edition? I think like every founder would just buy the give me all the tools edition, right? How do we price AI? Hopefully in a few months, we'll have an answer, but I don't know right now.

• 40:34Jacob Effron?

  I mean, I guess, you know, shifting over, you obviously are quite an active investor. I'm sure you get your fair share of AI pitches as Pat and I do too. What areas are you like most excited about? What areas are you not as excited about, you know, as you do on the investing side?

• 40:49Speaker 00

  So Todd and I were actually quite bearish on most de novo AI companies. Because most of the pitches that we got from from scratch AI companies were, well, here's the app that we were gonna build anyway. Now we're gonna build it with AI. And at that point, you almost have two companies to build, right? You have building the thing and then you have making it amazing with AI. And that's really, really hard. I would not want to be building an email client today and also have it try and be the best AI email client. That sounds, frankly, impossible. Like, you'd have to raise hundreds of millions of dollars and basically run two companies, and it's just really, really hard.

• 41:31Speaker 00

  So I think I'm pretty bearish on those pitches. Where I was bullish and continue to be bullish is if you have some kind of distribution advantage. You know, perhaps it's contacts from your previous line of work, or it's some distribution insights that you've figured out, some kind of viral loop or viral mechanic that no one else has figured out. Or you just have a track record, like you're, you know, you're Nikita Byer, just really, really good at launching consumer teenage apps. Then, then sure, by all means. Because what you're actually investing in is the ability for the founder to create distribution and to retain users. AI is kind of incidental. AI might be a hook, but it's it's sort of incidental.

• 42:15Speaker 00

  Where I am really bullish is, as I mentioned, our agentic AI future. And I don't know what that ecosystem looks like. You know, clearly, we're gonna need some kind of service. This could be ChatGPT or it could be something else that federates all of the AI agents we have that has some kind of authentication handshake between them. You know, I imagine a world where I was going through, this is like a real example, where my partner and I are doing family planning. And we were going through the process, or we want to plan for a potential pregnancy. And I was thinking, oh, when's my, when's my next open enrollment? Because that's like the last thing on my mind, right? I don't even know.

• 43:00Speaker 00

  And should I change my health insurance plan? The way I actually had to do that was I had to ping head of HR. Head of HR said, okay, go and talk to this person, go talk to that person. Like, we'll go talk to our benefits advisor firm, Benny, who's great. But then that's now another phone call, it's like a meeting. And I'm just like, please, just very simple questions. I imagine a world where I fire up my executive AI and I'm like, yo, we're doing family planning. When's next open enrollment? And it knows the roster of my other agent AIs and it goes down the listing. It goes talk to the Rippling one. And it's like, hey, Rippling AI, I'm here on behalf of Rahul. And the Rippling AI is like, okay, prove it. And they have some kind of cryptographic handshake. And it then says, okay, the question is, when's open enrollment? And it says, May 24th.

• 43:45Speaker 00

  And then it says, okay, he's planning for pregnancy. These are the details. It probably goes, you know, what's the age of his partner? What their health insurance details? Okay, based on all of that, this is the plan that we recommend. And it comes back to me. And that whole thing is instantaneous, right? It doesn't take, which is actually crazy, given that they'll probably be interacting in natural language. It's like a natural language conversation that happens instantaneously. And it doesn't take meetings and days and phone calls.

• 44:14Speaker 02

  And do you think all of that, all of those agents will live inside of Superhuman? Or do you think then it will be a Superhuman agent talking to the Rippling agent? Or maybe people have some sort of AI API where they can connect into? Or I guess it, maybe it's very TBD.

• 44:31Speaker 00

  I think it's so TBD. This is the trillion dollar question, which is how does this? Ecosystem of AI agents come together. I mean, do they all live inside a superhuman? I think from the perspective of pane of glass, yeah. One of the strategic advantages we have as superhuman, and I think this is why it was such an easy investment decision for IVP, for A6 and Z for first round and everyone else, is it's one of the only three hour a day products, right? How 50% or more of our users are in superhuman for three hours a day because it's email. What else does that? WhatsApp, iMessage, email, Slack? It's basically chat messaging and email that are three hour a day products.

• 45:16Speaker 00

  Nothing else even comes close. And so, well, I guess maybe operating systems, but apart from that, you've got this pane of glass opportunity to be where people do work. Now, do we have to own the agents? I don't think so, and it probably isn't even good strategy for us to try and own every single thing that you might do. So I think the way that this probably proceeds is every company builds an agent that makes sense within their domain. So you could imagine an email agent that triages on your behalf, that drafts emails on your behalf, that schedules in your behalf, that maybe even sends emails on your behalf and is interacting with all the other agents.

• 45:58Speaker 00

  And you're interacting with that ecosystem in a sidebar inside of superhuman, or maybe even one day with your voice.

• 46:05Jacob Effron?

  I love that vision. And we'll notice send the emails at 8:54 on Monday to beat the 8:55 rush.

• 46:12Speaker 02

  I want my agents to start messing with Jacob's agents and then, you know, send them on wild goose chases to do crazy things and yeah.

• 46:19Jacob Effron?

  It's like your OpenAI bill from last month was massive because Pat's agent had you checking all sorts of things. You know, I think another, again, like as I just think about how relevant the lessons are from superhuman to a lot of these AI startups we meet, you know, another thing is everyone says, oh, the incumbents have such an advantage, you know, in AI, right? They have, you know, they're where you already are, they have all your existing data. You know, and I imagine this was, and it still is something you probably deal with, with like people moving over from Gmail or other email clients where, I mean, obviously you import your emails, but as I understand it, you know, you got filters, you have other things set up and it's like there's some. It would have been easy at the time to be like, oh, that's a space where incumbents are to advantage. And so I'm sure a lot of our listeners are hearing from folks, yeah, the incumbents are so well positioned. I mean, any thoughts on that general statement

• 47:02Jacob Effron?

  of like incumbent positioning in AI and then any lessons you've learned or would think about for these companies on how to take on the incumbents?

• 47:09Speaker 00

  I think it is generally more true than in previous cycles that incumbents have a greater advantage. But I don't think it's such a great advantage that you shouldn't try. They're still incumbents, right? They're still encumbered. They move really, really slowly and be limited by the fact that they have to build one-size-fits-all solutions. I was on a podcast recently, a founder podcast, and the host said, you know, one of the craziest things about Superhuman is you're one of the few companies in recent memory that has specifically gone after a space where really the only competition is an incumbent or two

• 47:47Speaker 00

  incumbents, namely Outlook and Gmail. Do you have advice for founders on like, it's scary. Do you have advice for founders on that whole strategy? And I said, as an investor, I specifically look for that. I specifically look for founders going after incumbents because in many ways, it's a really great strategy. First of all, incumbents have to do one-size-fits-all solutions. So Microsoft Outlook or Office 365 more generally has something like 400 million plus paid seats. Gmail has north of a billion users. Between the two of them, that's basically everyone who does email. And by definition, that's a one-size-fits-all

• 48:30Speaker 00

  solution. It's really easy, relatively speaking, for a founder to go into that and go, okay, what is a underserved, yet economically powerful subsegment of this market that I could simply build a better product for? And at that point, you've turned a problem from something you don't have control over into something you do have control over, which is build a better product.

• 48:53Speaker 00

  I'm basically saying get good, but you can actually get good and build a better product as opposed to, you know, like somehow figure out some unfair distribution advantage. So that is, that is very doable. The other thing is, and this ties in directly to the previous tactic, incumbents specifically struggle with things like product speed. So you'll recall that Superhuman launched on the platform of speed, the fastest email experience of all time. We say that you get through your inbox twice as fast, that you reply to emails one to two days sooner, that you save four hours or more every single week. And the features that were the foundation for that at the very beginning were simply how fast the app was, right? Instantaneous response, instantaneous search, sub 100 milliseconds user interactions.

• 49:37Speaker 00

  It is very, very hard for an incumbent to make that change. Superhuman looks like a web app if you use our web version, but it's actually not. It was the first email client to be entirely written in JavaScript. Now imagine how difficult that would be for an incumbent to make that switch after 20 years of being a client server application. The third thing is design, right? Like familiar with Conway's law, where the, um, the structure of a product actually tells you more about the structure of the organization and you're looking at how the org is structured than whatever is logical for the user. We had a funny moment a few days ago in Superhuman where we were in Gmail and we were looking

• 50:20Speaker 00

  down the left-hand side of Google Workplace and I think it's, if I remember correctly, it's mail and then chat or spaces and then there's one other icon. I don't, I don't remember the icon. And I actually was, I was like, why isn't calendar there? That's a really weird choice. And the PM I was working with was like, oh, well, calendar's up on the top right-hand side where you have like the little grid of nine squares and you click that and there's a whole bunch of other things there.

• 50:43Speaker 02

  I honestly don't even know. I'm usually in superhuman.

• 50:45Jacob Effron?

  Well, yeah. I feel like you were trying to bait us and have memorized. The only correct place to be.

• 50:51Speaker 00

  And I was like, holy crap, this is just the organization of Google, right? That there's a products manager who runs this. There's a products manager who runs that. This is not in the benefit of the user in any way, or at least I don't think it is. And it's understandable. Look, people have careers. They they come and do these tours of duty where they run a product for two or three years and it gets handed on and

• 51:13Speaker 00

  at least historically in Google, the the big criticism has been you just get rewarded for launching some stuff, no matter how well or badly it does, launching gets rewarded. So people keep on launching things. This is why we've had six or seven different versions of Google meet slash hangout slash, I don't know, whatever they've been called.

• 51:31Speaker 00

  That's the other thing that incumbents really struggle with. So there's actually so many reasons to go up against an incumbent.

• 51:36Jacob Effron?

  Yeah, it's super interesting. I feel like for a lot of these AI companies, the question is like, do you go, do you do you take off a vertical from the incumbent or go horizontal? And I think we had Arvind from Perplexity on, and I think he was saying this like tension early on of some folks were like, well, just build the best search for X thing or, you know, but he's obviously tried to build, you know, a broad product there to to compete. And I think that's that's something a lot of folks are thinking about right now. Do you start with like one specific user archetype or try and just go for go for glory?

• 52:02Speaker 00

  Well, I've been a very big fan of the specific user archetype, right? And initially it was founders and VCs and then it became leaders and managers. And now it's really what at LinkedIn, we had internal lingo for this. It's really any outbound professional, right? You could be a founder, you could be a VC manager, but you could be a salesperson, you could be a recruiter, you could be a BD person, a consultant, a community evangelist, so, so many different people. They're now you superhuman in every industry, in every vertical, in every possible way. So I think there is a path from one persona to multiple. But I had a very clear sense of what the progression would be. And as an investor, I think one of the key questions to ask, if this is what the founder is pitching is,

• 52:47Speaker 00

  can you just articulate the series of personas that it's going to be?

• 52:50Speaker 02

  Yeah, it's interesting too, because I think.

• 52:54Speaker 02

  VC funds and even people within VC funds have different biases on they like to invest in companies where there's a big incumbent or there's not a big incumbent or those different things and I think you know we always love markets where there is a big incumbent because it kind of shows that the market is enormous and then even by you know building a product for the superheroes of whatever that market is or for the even a small segment of that then you can build a really big product and I've never thought of speed as really a vector to compete with some of those folks on of you know if you're competing against the Microsoft or Googles of the world then it is hard for them to make their app faster because they've been building it over I don't know 20 years or that sort of thing and yeah I think it's

• 53:39Speaker 02

  really interesting.

• 53:41Speaker 00

  Yeah, so two thoughts on that. First, the market size thing. It's interesting because as an investor, that's usually the main thing that would cause Todd and I not to make an investment. It's often not the founder isn't good enough, the product isn't good enough or it doesn't solve a problem. It's like, oh, the market here isn't good enough. And I think about all of my experience pitching Superhuman and it was so different. Like, no one ever questioned the number of people that do email. And it's funny because in many ways, the pitches could be boiled down to a few really simple facts, which is there's a billion professionals in the world. On average, we spend three hours a day reading and writing email. That's three billion hours every single day. That's north of a trillion hours every

• 54:26Speaker 00

  single year. It is basically impossible to find something that people spend more time on. The only other thing people spend an equivalent amount of time on is team chat, right? Slack, Microsoft Teams, and there's great businesses to be built in that area as well. And if people ever wanted a bottoms up analysis, I'd be like, okay, how many subscribers do you need at $30 a month to be a $100 million run rate company? I assume this was Arvind's pitch as well. And you do the math and it's like, okay, you need 300,000. That's it. There are a billion people who do email professionally. And I actually remember being in the A16Z, this was Series B pitch for 2019, in the In the boardroom, and I just, I asked the GPs, I was like, does anyone not believe that we'll get to 300,000 subscribers at some point?

• 55:10Speaker 00

  And everyone was like, yeah, you'll get to 300,000 subscribers. It's like, this is okay. So it's like, okay, so we've agreed this is at least a several billion dollar company. Let's now talk about 10 billion dollar plus and how we get there. So that's my general, general thought on, on markets, yeah.

• 55:23Jacob Effron?

  We always like to end our interviews with a, with a quick fire round where we get your thoughts on probably overly broad questions that shouldn't be in quick fire, but they're standard, so we keep them there anyway. I guess first, you know, what's overhyped and underhyped in AI today?

• 55:36Speaker 00

  So my overhyped and underhyped is actually going to be the same thing for both, which is this idea that AI is coming for our jobs. So I think it's underhyped in the sense that the vast majority of people, and by people, I just mean like people in general, I think about my family who don't work in tech, don't yet see how quickly it's going to happen for certain specific roles. So I'm thinking about, for example, entry level customer support roles, or maybe entry level sales roles, where I think Jason Lemkin said this best, it doesn't have to be as good as a salesperson. It has to be only 80% as good, because if it's 10% of the cost or less, that's a trade off that many companies will happily, happily make. And if anything, it's going to be a better consumer experience, right?

• 56:21Speaker 00

  I think we all know how terrible today's robotic voice customer support things are. When those are good, it, you know, companies are going to adopt them en masse. So that is underhyped right now. I think what is overhyped, sorry, that's overhyped. What's underhyped is exactly the same thing, which is there is nothing unique about customer service and sales roles, except for perhaps by headcount, there's a lot of them. But it's coming for my job, and it's coming for your jobs, and it's coming for our friend 's his job as well. And that's fine. Like, at some point, AI will be able to do most of my CEO job better than I do it. And yeah, bring it on.

• 57:04Speaker 00

  I think if you were to go back 1,000 years, when we were subsistence farming, or we were hunter gatherers, or maybe even like 1,500 years. Those people would look at our jobs and go, that's not work. You're just playing like you're just having fun most days.

• 57:22Speaker 02

  I think a lot of people today would look at Patton My Job and say, that's not work. But it's kind of you to go back a thousand years.

• 57:27Speaker 00

  Right, yeah, well, you know, make it easy for everyone. But I think that will happen again, and I think it will be a lot faster than a thousand years this time. We'll probably look fifty years into the future and see people primarily doing what we perceive to be as leisure. And I think Bertrand Russell said this really well a while ago. To us, it will look like leisure. But you know what the funny thing is? To them, it won't feel like it because humans are just hardwired to work and to get stressed about stuff and to play silly games of status with each other and to be competitive and to try and amass power and wealth and all this, that, the other. But the actual stuff that they're doing is going to seem silly.

• 58:12Speaker 02

  That's super interesting. Besides Superhuman, what other company do you think would be most interesting to be building generative AI features at?

• 58:21Speaker 00

  I go back to this idea that Superhuman is one of the few products in the world where it's a three-hour-a-day product. So what are other products like that? It's basically chat and messaging. And, you know, I've built my career on doing things which are valuable in the workplace and for professionals because it's really fun and I'm obsessed with productivity and helping unlock human potential. And so it would probably be Slack or Microsoft Teams. And I actually wouldn't start with AI. I have a very clear vision for how I would build either of those products way better than they are today. I would do that, and it would be AI-enabled, but that wouldn't be the point of the product.

• 59:01Speaker 02

  Very cool. What's the top thing you'd do?

• 59:05Speaker 00

  Oh gosh, okay, cue Slack rants. You guys use Slack? Yeah, we do. Slack and Superhuman. Yeah, cool, cool. Okay, so there are some things that email does shockingly well. And this is actually the main reason why it has pervaded for so long. In email, conversations aren't ordered like they are in Slack by when people happened to start them. They're ordered by when people last replied. In email, you have an at-a-glance view of what a conversation is about. We call them subject lines. In Slack, you don't have those things unless you manually write them in. In email, you can mark things as done. You can snooze things. Soon, in next-generation email clients like Superhuman, you'll be able to assign those threads

• 59:50Speaker 00

  and share those threads and leave comments and so on. In Slack, you can't do any of those things. And so if I were to show you my Slack this morning, which I haven't looked at yet, dreading the thought just as I say it, it would be, without exaggeration, probably 100 to 150 unread channels, in each of which are multiple conversations. Some people have thread disciplines, some people don't. Some conversations meander in and out of threads. They're all interjumbled with each other. I wouldn't be able to tell where to start or where to finish. I'd probably look at it and go, "Fuck that, I'm gonna go do something else." Which is actually how I structure my day. I open it, I close it, then I look at my calendar. I'm like, "Calendar, what should I be doing?

• 1:00:35Speaker 00

  Review this document, yes, this feels like a much better use of my time." Which is why when people want to get work on my plate, they're like, "Put it on Rahul's calendar, because that's the only way it will happen. Slack is just so overwhelming." Now, there are some problems with email, right? Email is immutable. You can't change a subject line once you've set it. Messages are immutable. You can't change it once you've set it. It's fully decentralized, which is an insane architecture. Everyone stores every copy of every email, which, oh boy. Like, building shared threads and comments on top of that is hard. It's very complicated, but we figured it out. It's gonna be amazing. So what I would do is I would just combine the best of both worlds, right? I would build a workplace experience of the future.

• 1:01:21Speaker 00

  That is designed for thoughtful asynchronous discussion, where you can have subject lines, where you can archive things, where you can snooze things, where you can assign things, where you have an inbox, where you can hit inbox zero. Chat is also there as well, but you have the choice of modality. And it doesn't become a free for all. And you can actually, you can legitimately run a company. And there is a reason, again, why email hasn't died, and it's because Slack didn't capture, and neither has Teams for that matter. These products didn't capture the thing that email does so well.

• 1:01:59Jacob Effron?

  The whole time you're talking about your Slack, I just pictured you need a Slack agent, something that can just do this all for you.

• 1:02:05Speaker 00

  Yeah, I mean, it does beg the question. You need a Slack agent. I think there is a, I think there's like a future of work agents, right? And I don't know whether it's a Slack agent or not, but there is an agent that maybe somehow knows what's important to you and what's going on in your Slack and what's going on in your email and where the free spots are in your calendar and just tries to organize the stuff that you should do next. One of the biggest life-changing moments for me as a founder has been when I switched from having anxiety over what to do next to simply saying, I'm not going to worry about that. I'm going to worry about whatever my calendar tells me to do next

• 1:02:48Speaker 00

  and I'm going to tell my executive assistant, who is phenomenal at what she does and she tracks all the priorities in the company at all time, what kinds of things I want to work on. And she has a knowledge of my preferences, what I like to do on a plane, what I like to do in the mornings, what I like to do in the evenings, and in greater detail than that, too. And it's been amazing. I don't have any anxiety or stress. Yes, I have an infinite amount of work. Yes, I'm always behind everything. That's okay, because I'm still making consistent progress. And I still feel good about the number of hours I work. I'm like, okay, I worked a solid day. Yes, I could work more, but sleep's also really important. And I'm eight years in. There's another 10 years here at least. Like, let's keep going, right? Like, this is a marathon. And I think having a healthy attitude to work

• 1:03:33Speaker 00

  is actually more important than anything else, which is ultimately the vision of Superhuman. It's the mission, I should say. It's not about email. Our mission is to help professionals end every day feeling happier, more productive, and closer to achieving their potential. So that's what we spend all day thinking about.

• 1:03:50Jacob Effron?

  I love that. I feel like that's the perfect note to wrap on. I mean, I guess we'd just love to leave the final word to you. You know, where can people go to learn more about you, about Superhuman? This is your chance to plug anything you would like for our listeners.

• 1:04:02Speaker 00

  Okay. Okay. So here come the plugs. If you want more of my crazy ramblings, I'm on Twitter. Just my first name, last name, R A H U L V O H R A. Superhuman is just Superhuman as well. If you don't use Superhuman and you're a founder, I mean, what are you doing?

• 1:04:20Speaker 00

  If you're a VC and you don't use Superhuman, this actually you're just bad at your job. What's happening? So go to superhuman.com, sign up. Our customers legitimately get through their inbox twice as fast as before. They reply one to two business days sooner. They save four hours or more every single week. And we have team versions of Superhuman now. We talked about team read statuses, team reply indicators, team snippets. Soon you'll be able to share threads and comment on them in addition to all of the amazing AI stuff that we've just built. I think that's it.

• 1:04:49Jacob Effron?

  Amazing. Well, thanks. This has been an amazing conversation. Really, really appreciate it.

• 1:04:52Speaker 00

  Thank you.

• 1:04:54Jacob Effron?

  Well, Pat, I know we've both been big users for a while, but it was fun to meet the man who saved us a few hours or two in person.

• 1:05:00Speaker 02

  Really, really cool to hear how they think about building AI products and they've already shipped so many features. So it was a lot of fun.

• 1:05:07Jacob Effron?

  Yeah, I mean, I loved his point that like the average data set that folks train email features on is 500, 600,000 emails and he's got 4 billion. That combined with the fact that he's one of the few applications that folks spend, you know, three hours a day on. What a cool seat to have to build some of these features.

• 1:05:24Speaker 02

  You know how he was talking about how they designed the AI features and the distinction between the always on AI features and the kind of user activated AI features? And how they started with the user activated, then moved to always on, but it seems like in hindsight, he probably would have done the opposite and started with the always on because those are those bring people in and they're cool.

• 1:05:46Jacob Effron?

  You don't need to teach users how to use them.

• 1:05:47Speaker 02

  Yeah.

• 1:05:48Jacob Effron?

  It's interesting. I would have thought that would have been from a cost perspective. It's funny. I remember when we were talking with the Intercom, you know, co-founder Dez. He was like, look, we'd love to summarize all the conversations all the times, but that adds up pretty fast. But it seems like the, you know, obviously with the price point they have, they've been able to, you know, take every email and still run those.

• 1:06:05Speaker 02

  I liked when he talked about the thirst trap graph that he posted.

• 1:06:10Jacob Effron?

  I'm glad he told us what it was. I was wondering if, yeah.

• 1:06:13Speaker 02

  He does seem like, he does seem good at building hype for his, uh, his company. And you could even see, he's a really good marketer, even in how he talks about, uh, you know, what they're building in the future and, um, and all of that. So it was, uh, it was funny that he, I don't know, self-aware enough to call it a thirst draft, draft.

• 1:06:29Jacob Effron?

  Well, I love that also. I mean, I think another really interesting thing he said was, he was talking about how like all the AI features they build are like 10 times more relevant for mobile, which makes, I mean, mobile is like, you're kind of half paying attention, you're on the go. Um, and it, and it, and it makes sense that that's, you know, those features are even more valuable. Um, you know, I find often even with email, it's like, I'm like, well, do I try to do this on my phone? Okay, I'll just wait till I get home and like have a little more, you know, focused time. And it's amazing, uh, it's, it's, you're going to think about the context in which some of these features are most valuable.

• 1:06:59Speaker 02

  Totally. There's that meme that's like, I'm a millennial. I can't write any important email from my phone. And that really resonates with me. If it's important, I'm getting in front of a computer. But if, if AI is writing it, then maybe I'll write it, uh, from, uh, from my phone.

• 1:07:17Jacob Effron?

  To the end, we got a little philosophical there, but I loved his, uh, his, his quoting Burt and Russell that like, no matter how much progress we make, uh, we'll still find a way to work a lot and, uh, and, and, you know, play status games and, you know, uh, that, yeah, that, that I thought the point was really well taken that, you know, a thousand years ago, folks would think what we do now is, is not work. And I'm sure we'll think the same of, of whatever comes post, uh, AGI.

• 1:07:40Speaker 02

  Yeah, we'll, we'll find a way to stress ourselves out for sure. The, uh, I, I thought it was really interesting how much he's thinking about agents and building agents into superhuman. And that seemed like something that was really on their horizon for, uh, for how they think about the world is orchestrating these agents from superhuman and interfacing to different products via the, the agent that he launched from superhuman. And I just thought that was really interesting. I think it's really TBD on. Who runs the agents and how they authenticate and how they talk to one another? And I think email is a really good place to start for a lot of these workflows. And I thought that was fascinating to hear him talk about.

• 1:08:24Jacob Effron?

  I think there's a real battle brewing for, you know, what's the homepage for all your agents? Like what and who has context on you and memory of the things you've done. And I think, you know, it's the three hour a day apps that are probably in the best position to do that. And I think it's kind of still TBD, like, are they going to need some third party to help with a lot of these agent interactions? Because they're so hard to build and they need to be, you know, tailored perfectly. Like, we still haven't seen that many agent demos that work. So maybe each individual one will be really hard to build. Or do we get to a point where you actually do have more of a horizontal agent? Which was always the dream during the agent hype cycle of six, nine months ago, that they can kind of just plug into Superhuman. So it'll be interesting to see how it plays out. But yeah, I agree with you. Like clearly he's thinking, you know, a few steps ahead.

• 1:09:07Jacob Effron?

  And I feel like we've been through the full agent hype cycle and now we're back to the real, I forget what they call the end of a hype cycle. But wherever it is.

• 1:09:16Speaker 02

  Trough of disillusionment.

• 1:09:17Jacob Effron?

  Well, we were past that, I feel like now.

• 1:09:18Speaker 02

  Okay, now we're on the something to enlightenment?

• 1:09:21Jacob Effron?

  Oh, that sounds right. That sounds right. Enlightenment sounds right.

• 1:09:25Speaker 02

  Yeah, the trough of disillusionment.

• 1:09:28Jacob Effron?

  I feel like we only remember the trough of disillusionment, which is pretty negative on our part. But there's definitely a good part after that.

• 1:09:33Speaker 02

  Yeah, good part coming soon.

• 1:09:36Jacob Effron?

  You know, obviously the Mistral partnership with Microsoft was really exciting. And I think, you know, it really does feel like it's coalescing around the set of, you know, six or so model providers that are going to be.

• 1:09:46Speaker 02

  What about the Mistral partnership with Snowflake?

• 1:09:48Jacob Effron?

  We had to get the Snowflake mentioned as well. Of course, two Redpoint portfolio companies working together. But yes, I think, you know, it really does feel like it's cementing, you know, who the folks are. I feel like in the last, you know, few weeks, you know, there's been a bunch of buzzy fundraises. There's a new robotics company that came out that thrive and a bunch of other funds funded. And, you know, I just think the application of foundation models and scaling laws to spaces like robotics and biology. It's going to be super interesting to see. I mean, I think the big question in those spaces is you don't have the entire internet to train on. So what is the, what's the data source? And biology, a lot of these folks have to do wet labs and actually create their own data sets. But if people can find ways to, you know, to create large data sets in those spaces, it would be incredible to see the emerging capabilities that happen from those models.

• 1:10:34Speaker 02

  Yeah, I haven't looked at any, anywhere near the number of. Bio or healthcare companies that you have, are they full stack where they're building their own lab to get this data?

• 1:10:42Jacob Effron?

  A lot of them, a lot of them have to because there's just not enough existing data to throw into like a large model. And so there's different approaches and some are, you know, doing simulations and there's lots, you know, I think there's still an ongoing debate about how much you can do outside of actual, you know, what they call wet lab data. But a lot of them, you know, a lot of the big ones do have their own labs.

• 1:11:02Speaker 02

  Yeah. Wow. Fascinating.

• 1:11:04Jacob Effron?

  Well, Pat, that was a fun one. And I think we've got a, we've got a great lineup coming up. We've got a Arthur from Astral, Edo from Pinecone, some mystery guests to be revealed later. But it really, it's a lot of fun as always.

• 1:11:15Speaker 02

  It was a really fun episode. I hope you enjoyed it. If you found it helpful or interesting, please like, comment, share, subscribe. It would really help the channel. Until next time.