AI Agents That Work: Jason, Jeanne DeWitt Grosser (Vercel), Amjad Masad (Replit), Amelia Lerutte

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The world has changed. AI is the accelerant. The amount of disruption that the software industry is going through now is unprecedented and it's accelerating. Innovation's everywhere today. SaaS is all about being positive. It's all about helping. It's about doing it together. The reality is we have to move faster. It's what I'm telling every CEO I meet. You got to re-found your company. If we could start over, what would we build in our space? What would we build today? How can we do it twice as fast? And just go find a freaking way to build it.

Please give a warm welcome to the CEO and founder of SaaStr, Jason Lemkin.

Hey everybody, can you hear me? Okay. All right. Thanks everybody for coming. Who's been before? All right. Solid show of hands. Thanks for the committed. This is going to be... Hold on. Let me see if these slides work. Can you guys bring up the slides? Maybe. Hello. Always the first bug. Can you guys bring up the slides, please? Hello. Should I go back in? Come back out.

Hello, Freeman. Team Freeman in the back. Hold on. Give me... I'll be back. Hold on. Hello. Ah, okay. Good. Okay. Okay.

Oh, there's a few bumps. This is... well, everything's optional. This session is super optional. This is an extra... it's starting early. It's one if you are... if you have deployed 100 agents yourself. If you have eight Mac minis at home running OpenClaw, don't go here. Go have some lunch, meet some friends. Go to... or you can go in half an hour. The chief product officer Versell is kicking off the whole Deploy Summit on the other stage. It's all go-to-market for AI and agents. It's going to be great from there until... until the end until we have poker and prosecco. But if you haven't done it yourself, even if your company, your product has an agent, a chatbot or whatever, if you haven't done it yourself on the other side, if you haven't built an agent, a bot or something, that's all this is about. We're going to pick the simplest possible way so that if you have your laptop or even you can even do it on your phone, you're going to build the bot here while we're here before we leave and you can train it and what we're going to use as an experiment and then with whatever time we have left until 1:55 of folks I'll take any questions on this or anything really that you want to ask. But a lot if you haven't done it yourself, a lot of the products are so exciting. Go meet with all the vendors here. It's incredible what's changed since last year. It's incredible what's changed since December. We have products that will set up appointments for customers for you. We will have products that screen everything. We have an agentic CRM that will do everything for you. It's all here. I'm going to talk with Amjad, the CEO of Replit about how we built an AI VP of marketing and AI VP customer success. And Amelia is going to teach you today how to build one your own. I mean, since last year, but we started on our own AI agent journey last year. Last year, we had one, not 21 agents like we have today. We had one. And I use this product called Deli.ai. Fire up your browser on your phone or whatever. If you can go to deli.ai and set up a free account. It's... I picked this one. There are other ways you can do this. There's other products, but this one is free and easy. Okay? It's a good combination for SaaStr. Okay. And you're going to build what... what Deli builds clones. So there's a clone of me you can talk to. There's a clone of Lenny. There's a clone of John from TBPN. There's a clone of like sports enthusiasts and influencers. And it lets you do that. But actually you can put anything into this. And so a little maybe 14 months ago I built a clone of myself. And at first it was folks could just ask a digital version of me questions about SaaStr. What would you... you know who should I hire for my first SDR? What if my VP of marketing doesn't want to do events? What do I do? And it was fun to have a digital version of Jason. And then I started adding other content like our SaaStr annual website and our prospectus for sponsors. And I know this sounds captain and obvious like 15 16 months later, but I was shocked that the agent could answer better than most humans on... that were helping us could. It knew our perspectives. It knew what a gold sponsorship cost. It knew the difference how much tickets cost over time. It knew the basic questions. It knew what the Wi-Fi was. And so I didn't realize how easy it was to train an agent and then we even had a sponsor that bought a $50,000 sponsorship just interacting with Digital Jason. So all I want to do and then we can do all the questions in the world is have you build your own and then you can play with mine and then we can look at together and then we can talk about where... where it's going. And again, apologies for folks if it seems too basic. But I found a lot of folks are using tools, playing with tools, buying tools, watching what their team does, but they... but they haven't done this one step themselves. So this is all I want to do. So, I'll go to the next one first, but first just take a second. Go to again... go to deli.ai. It's better on your laptop, but honestly, you can do it on your phone. It's free. You'll put in... you can auth in with Google, and then I think you have to give your LinkedIn and it should be good to go. You should have a blank clone of yourself. And if you've done that, if anyone needs a minute, deli.ai. I'm going to teach you how to clone yours, but I want to show you mine on the other side. So the next thing I want you guys to do is I built a new version, a new Digital Jason, Digital Jason 2 Prime. So it is completely blank as you can see. There's nothing in it, okay? With... with except a little bit of SaaS content. So what I want you to do if you want go to deli.ai/jason-demo. It's a new one and you'll see me another version of me and just ask any question you want. Let's see how good it is. All this is is two days ago I... I would have done it live on stage but the... the I want to make sure it worked. All I did was two days ago was tell it to find all the content on saster.ai... I mean saster.com and my... my YouTube and social media and it... it ingests all that content with just three links which I'll show you. So go to saster... if anyone wants go to deli.ai/jason-demo and ask it any, you know, be nice. But ask any question you want and then we're going to go see them in just a minute. And we'll show you how it all works. And mainly I want you, we'll come back and I want you to play with your agent, but I want you to ask questions. And all I really want if you haven't done it is just to see how simple it is to make something pretty good. How simple it is to train an agent. How simple it is to ingest data. And if you haven't done this, a lot of this stuff sounds complicated. But once you've seen on the other side with your own, you're going to see that... that it's really not. So let me know if I'm moving too fast. We'll come back. Let me show you a few slides.

Actually I'm going to... if the... if the AV guys are listening, I'm going to jump back and forth... I think... to show them this. I'll... I'll do two more slides and then we'll do my laptop and then we'll come back to the slides. So again, just sign up. It should take if you... if you beyond asking me questions, we'll come to that. Sign up, create your own. Play with it. I'll show you how to do it. And then what you'll see is a training screen. And this is what you'll see. And then I'll show you mine in a minute. And what's pretty magical is if you do this, you're going to find you're going to build a pretty good version of you. And all you really have to do is connect your website like this. Go to the bottom. It says, 'What's your YouTube? What's your website?' I put in saster.com. Obviously, there's 7,000 pieces of content on SaaStr. You'll see it's going to take a minute to ingest it, to scrape it, to find it. Put in your YouTube. If you have a Twitter or a LinkedIn, put them in. And while we're here, it will start scraping and ingesting all that content. And you'll be able to talk to that content. Okay? Put your own website, put whatever you want. Put your own docs, put whatever you want, or just put your own stuff in. And you'll find it works fairly quick. It should work fairly quickly and fairly... fairly magical. And so I want to... I want to show you mine. So, let's switch over. Let's see how it works and then we'll play with a few other things.

Okay, let's see. Here's mine. First of all, let's see if anybody asked any questions. I think so. You're welcome to ask more. Okay, thank you. Some of you are anonymous. They're already here. So, again, it's... what did I say it was? If you want, I know we're jumping around between yours and mine. You know, stay focused, guys. Sorry. I apologize. But if you want to ask questions now or later, it's deli... JSON demo. And so what you can see here is folks are asking these questions. How do I get to 100 million in ARR? Love the ambition. Let me split it in. The math simpler than people think. Retiring to become a fine artist. Okay, that's a new one. Let's see if anyone else. Okay, this one didn't. What time is SaaStr? I'll show you. It isn't trained. Let's see if it got any good ones. I'm a founder. Hold on. How do I get rid of this thing? A little summary here. Hold on. Okay, let's see if this is me. I'm a founder of a SaaS B2B company. Bootstrap for seven years, raised 5 million, reaching 3 million. It's a pretty prof... I guess there wasn't a question. But that's okay. What's your growth rate? If you're growing 80 to 100% with strong net revenue retention, you're in great shape for a real round. If you're growing 30%, it's going to be tough. One thing I'd flag, if it's 3 million, you haven't... you probably need your first VP of sales. I mean, if you guys have read SaaStr, I wouldn't say this is perfect, but it's... it's a good start, right? It's got a lot of the classic stuff in it. I can show you some more, but let me show you all it took and then let's try one more thing. So, here's all it got. All of this by me putting SaaStr in the YouTube and Twitter... in one post and I'll... and I'll show you how simple it is. I actually I might get blocked because I have too many words, but let's check add knowledge. So I want to add another URL because it didn't know about what time this event was. So let's see. I'm going to put in... this is all I have to do to quote train it. And I know a lot of folks... a lot of folks say this isn't training. This isn't like training an LLM. Fine, different vernacular. But this is how you train an agent. And all I have to do is put in SaaStr annual or SaaStr AI annual. Oh, I got to upgrade my plan. Ugh. Well, if I can do it in real time, I will. Hold on. Okay, that's a bump I didn't expect. Well, we'll go back. But this is all I had to put in because watch what happened. Put yours. And I'll show you one sec.

Content type completed. Let's see. I should be able to click. Okay, so here's... I guess it didn't. Most people don't have the amount of content in it. So, it already ingested 8.3 million words. But let's see if this one works. Hold on one sec. Personal website. So, watch what it's done. Or it should have completed. Oh, I see. It ingested so many tweets and other pieces of content. Let's see if it got to our YouTube. Hold on one sec. YouTube. Okay, it... it starting to ingest all the YouTube videos. It's actually going back in time. Jeff, poor Jeff Lawson doesn't run Twilio anymore, but we can probably ask Digital Jason any questions that we want about all of this. So that's in essence, I guess. Sorry, if I had my credit card, I would upgrade to pay. So, you're going to have to... you're going to have to bear with me. But all you really have to do to add knowledge is stick it in. Stick a YouTube video, a podcast, or most importantly, any URL, and it's going to ingest this just like it just... all this content and ask... answer some decent questions. Let's see if we got any other ones. Let's see if this one's any good from our content. Okay. Hi, Jason. How can I start my agent? Pick something that isn't good today. From there, the most common agents are support and sales. Pretty good. Okay. So this is step by step with this Deli. First write a spec. You don't have to write a spec. Treat every function hook up the integrations. It's pretty good. I built this. Okay. So you can see already the questions are flowing. It already... it's been trained just by putting the URLs in. And now I want to show you if we can go back to the slides for a second. I know we're moving quickly. We can ask questions, but if we can go back to the slides for a second and then we'll jump back. Sorry guys. Can we go back to the slides? Hello Freeman. Can we go back to the slides? Oh, I might have to go back. Okay, good. Okay. The next thing I want... I want you to use yours, but I want to come back. I... I want to do one other thing to show you guys. Now, I want you to go to saster.ai if you can. You don't have to. You can watch. You can watch, but it'll help you. And then you're going to see two improved versions of this that's trained. The one on the right is that we've been using for 15 months. So, it just has more of the data than came in in five minutes that all answer all these questions. You can try the one on the right, but again, you need... you don't need any technical resources. You can put any of this stuff on your own website. You can go to Deli. It'll give you one piece of JavaScript. You can... you can... you can walk out of this event with potentially a better bot or a better digital clone than you had coming into it. And if you want, there's one... there's one on the left where you... I... we're actually probably no one is doing this. I'm doing it for an experiment. But the one on the right is this basic Deli product that has been automatically ingesting SaaStr content for 15 months. The one on the left I built myself. So it's stair-stepping. So first is building something today that's pretty good. Then it's letting it run for months, reading those answers, seeing... doing QA did and every single day. So when I launched it at first, it worked. And then for the first 100, 200, 500 messages, I would see if there's a mistake. Did it have a mistake? And then I would just put in a little bit of text, you got that wrong. and it would ingest it. But then I built my own on the left so that it would really... really sound like me. And you can try this one. The guy looks like me saying where is it going to go up? Bark it. And the meta lesson from all of this is just to stair-step it. So a basic... basic one you can see you can build it in five minutes while we're here. You can keep iterating over days and weeks so it gets better and better. And then I wanted to try something more complicated. And if you try the one on the left with a picture of me, I actually think it's the best of the three. But now it got complicated. Okay, I mean not... not that complicated, but here I wrote it all up and we'll put it up on the SaaStr website. You can see all this, but how did I make it even better? Well, all my questions, we had to build a vector database. We had to do this on a product that MongoDB built. Then it had to chunk all this content into chunks and it had to search it. And then... then each chunk gets converted into a vector embedding using Voyage AI from MongoDB. So it could be search rather than keywords. This is like not that complicated but it... it's... it's you know you could do this in an hour or two but it's getting complicated to be better. Okay so this is requiring vector database chunking... figuring out how to store this figuring out how to train it figuring out how to integrate Claude Haiku into it. Okay but you didn't have to do any of that to have a pretty good output before. So I know Amelia and I have talked about this a lot. It's stair-stepping, right? You can get a lot out of something by taking almost any commercial product, even including this free one in any vendor that's here, getting it going, training it with your content, then QAing it, and then when you're ready, you can rip it out and build something better and more complicated. But you don't have to do something this complicated. And I didn't even build this for a year. I... I did really didn't think I needed it. It was an experiment. And the other meta lesson is... I guess it's on the next slide. It's related to it. Don't... don't build, buy. Whether it's here or anyone here buy and I will tell you at a... at a high level for this... I built this... this... this second version. I think it... it you know it's got me... I like that better. It's faster. It... it embeds in saster.ai website better. It has a lot of advantages but it breaks. It needs maintenance. So I asked... I asked... Replit that I built it on is Digital Jason still chunking recent content right... sort of but it's... he forgot to do the YouTubes and we just showed you how I set up the YouTubes in Deli third party product in one second he forgot the knowledge is only blog only now the YouTube transcripts and SaaStr content were adjusted earlier but it stopped... it stopped inputting all of that content want me to add it so it's just a small example of, you know, we've got 21 agents running at SaaStr. Now, I don't even consider this one of the 21. It's not even on the list. Maybe it's 22. Maybe it's 25. Maybe if we had the agent that distributed 5,000 parking passes autonomously this event, it's 26 or 27. But who the hell... who... who knew that it stopped ingesting YouTube content, right? If this was mission critical, I would have caught it. If it stopped working, I probably would have caught it. But what happens is there's a lot of times there's just drift. There's just drift. Things get out of sync. it doesn't happen. So... So for me, I like this Digital Jason better than the version that I built on Deli in an hour 15 months ago, but I don't know if I like it enough more to maintain it. What if we're here and it breaks? Like I... I just don't know. It's a meta issue. So it's a reminder to me in this 101 session to like buy don't build because it's a... it's even if it's just a little bit of maintenance, things fall out. The... the a new LLM comes out and it doesn't work. It breaks. something breaks constantly in all of our agents and it's fun to fuss with it, but I... I'm not sure that that one's worth it. So yeah, that was my final point and then maybe we can go back to questions you have and I want to make sure you guys build one, but simple but trained I think is... is the key. Simple but trained and that's why I want you to try it of the... of the one I just built here... that you guys could play with. I know I've jumping around a lot saster.demo/jason. That one was built in five minutes. It's not as good as this one on SaaStr AI that has 15 months of in automated ingestion. And this third one's better, but simple but trained on the two by two I think is... is the best way to go. So with that, sorry I jumped around a little bit more so that I... we could get through it and you have time. I want to just make sure have you guys ask me any questions? Not that I can completely QA this remotely. You guys want to... we can open it up to any questions, but go back if you haven't had a chance, go back just to deli.ai and build a free one and just put in something your company's website or some training. It's free and just train it yourself. See how it goes. Add it. There's a little bit of flow. It literally shouldn't take more than 5 minutes to have. We can debate whether it's truly an agent. But let's call it a mini agent... running here if that's helpful. So that's mainly what I wanted to show you guys. We can... go back to my screen maybe if you guys hear... can hear me. But with that I can just take any questions on any of this stuff if it... if it's helpful as we kick off. Any... any questions on how this works or to build or anything like that? How much time?

Y.

It's a lot. It's a lot of time. It's a really good question. And I'll give you a longer answer. This is the first session than I otherwise would. If this was pre-AI software, I would give you a different answer and then I'm going to answer your question. How... how much time do we spend with these agents that the... the one is getting it going which literally you're going to... you can do one here today here. Two is the initial training maybe the first two weeks to 30 days to reading every output looking at it every forcing yourself every day. How did this agent work? How did Lightfield work? How did Monaco? How did Artisan? You've got to like number one mistake folks make is they buy and they... and they... and they go away. Okay. And then there's... and then I'm going to get it. Then there's maintenance mode. How often do I need to check in this agent more often than you need to make sure Salesforce is working. Salesforce doesn't break. Salesforce doesn't drip. Salesforce doesn't hallucinate. There's you have to check in more often. Salesforce doesn't really have any autonomy built into it unless you're using Agentforce. Okay. So I would say someone... and... and then I'm going to get to the meta point. Someone on your team probably is going to have to spend an hour or two every single day working on your agents if you want them to work. If you don't have that resource, it's going to be you, but you probably have to spend an hour or two a day getting humans to work, too. So, ultimately, if there's enough ROI in it, it pays off. the... the non-obvious thing at first is once you... if... if it's a... if it's a product that if it's a product you built yourself and again buy versus build if you build it yourself we are constantly adding features and functionality to our stuff too much even the SaaStr annual website every day we would go in and not just maintain things on it because it was all vibe we would add new features add new functionality new ideas like let's pop into the Visible API and add cool images of all the speakers. Let's... what Amelia did. What if we need to distribute 5,000 parking passes? What if instead of one human emailing 5,000 PDFs, we asked the website to do it, right? It's really cool. But now if we were going to hand out 365 days of parking passes, we would have to check it every day, right? Because it would maintain it. And so we keep building. Then, and I'm going to show this to Amjad. Then we asked the SaaStr annual website, could you be an agent? Could you send emails to people here? And it turned out the SaaStr annual website sent better emails than 10K, our SVP of marketing. So we started sending emails from the SaaStr Annual website had a lot of context and knew about who's coming and what the speakers are and what the sessions are and what... what's most popular. It could pull all that data through these... through... through APIs. And so you start futzing with these things and the futzing never ends, right? It... it never ends. So I would say someone's got to spend one to two hours a day managing a group of agents, but you... you'll get sucked in if you get good at... you'll get sucked in because you will continue to see more and more productivity you can add and you'll have to decide where the line is that... that... that you want to stop, right? But it's a good question. All right, anybody else... questions?

We have two microphones in the house, one on either side. If you have any questions, please approach the microphone so that everyone can hear the question. Thank you. Cool.

Everybody's agents work fine. Any questions? Yeah. Go ahead. Sorry.

Yeah. Well for this today...

Um, two answers. Who... the question is who should build these agents, right? First, do not build it. Do not... we're going to... we're going to show you all the cool things that we've built we're going to show you but don't... the only things we've built are stuff that we couldn't buy. We used maybe eight of the different vendors that are here. Okay. We... we use a lot of them. We use Artisan, we use Monaco, we use Qualified from Salesforce, we use Agentforce. We don't... we don't buy. So first... first... buy don't build. Then you still need the right person even to buy because you have to deploy. Okay. So you really want the person on your team deploying an AI SDR, an AI marketing tool. The person that is like the nerdiest software person on your... in your org. The nerdiest person. the person that complain that tells you, 'Hey, this lookup table in HubSpot doesn't work the way I thought' or the person that builds custom dashboards for you in Salesforce that you never asked them to build.' Okay, that's the person that you want doing it because a point that I missed slides that I meant to make is it like this was just software adding a URL for... for your website and your Twitter handle like this is not innovative, is it? The innovation is in many cases behind the scenes. It's the LLM, but all this stuff just looks like, you know, normal software. So, find the person that's just tool nerd. You're smaller. Find the person that's your tool nerd to do this stuff. In terms of building yourself, I mean, try all of it, right? We're here. That... that's part of the point of this event. Go to the Replit vibe coding stuff. Go hear all the stuff. Try all this stuff. But only, you know, it's got to be someone that really wants to maintain this stuff that you can't buy. But you simplify it. It's so disruptive that there's only so far you can go without a true a great developer and engineer today. But basically every application that's running this whole thing that $10 million all the people all the things was all built without a developer all running on agents. So you can go pretty far if you want to. The question is do you have the right resources to push it that far? But it is possible today to do all these things. But any... hopefully that's helpful. All right. Anybody else? Go ahead.

Yeah, I... I think we're learning. So the question is, have you seen any good examples of things like accounting or finance software? I think the question's a little bit confusing, right? So, let's step back. Obviously, it's a big deal. Ramp launched a bunch of agents. I haven't tried any of them yet. Everyone's going to add some sort of agentic workflow to their... to their finance stack, I think. We got to confuse... maybe not confuse a couple of things. You... you don't have to rebuild financial software if the tools you use have an agent-friendly API. Okay? So, for example, after when we're done with this event for next year, we're going to build a finance agent that does... that does collections where it's going to... it's going to reach out to sponsors for their booths and just say nicely, please pay the 60. Right now we have humans sending emails. Okay, it's gonna... and it's going to integrate. Well, right now we use Bill.com and QuickBooks. Okay, not... I mean maybe we'll move because of this and we use Brex. We use Brex, QuickBooks and Bill.com. Assuming those APIs are good enough, the agent can just integrate with the APIs. So one of the reasons our agents are AI VP of marketing, Amelia will show you customer success, all these things. One of the reasons they work so well is they're just pulling in Salesforce data. They're pulling in Bizible data. If it worked, they would pull in Marketo data. It's this very agent-hostile platform. But when you pull all of these things in rather than rebuilding down to the system of record or the APIs, you can do a lot and limit the amount of risk going into it. Right? So I don't have all the answers. I... but I don't think you can do a lot in areas with sensitive data with financial data as long as you're not building the system of record. Right? When you're building the system of record, it's... it's totally different risk and... and ballgame. And I mean a small number of people should build their own system... system... system record but I don't think so. I mean one of the questions... it's not exactly a question you ask but now we've talked about on our podcast one of the questions like a lot of folks ask on Twitter is like you built all these things you're so... you're so stupid to do them on Salesforce why don't you do it on Postgres why don't you just if... if you have all this data why don't you just do it in a database well we don't want to be a system of record we don't want to maintain our own database we... we don't want to figure out how to do the compliance and the safety and how to structure it and how to make sure the backups actually happen and the agents don't delete the data so but you can do a lot more with sensitive data if the APIs are Great. If it's helpful. Yeah. Anybody else I can help with? Have you guys finished building your agents? Got to... You're not allowed to get up until... until you finish building your agent. Cool. Go ahead. Sorry.

What's that?

Just shout. You're with friends.

When you do agent, you are for the good quality and like feedback. You want to give them more data than just public available data. And then how to balance the security and the internal let's say company privacy data to not let's say fill it too much.

It's a good question. How... how do you balance how much sensitive data to give to an agent? Right. Yep. Exactly. I mean, look, the... a couple of things. If you buy any product that's here, or you can even... and again, play with... play with deli.ai, set up your own, they're going to put a lot of effort into building guardrails. And guardrails are not perfect, but they get better and better every week and every month. They get better and better, right? So, for example, this Deli one, this Digital Jason, when we rolled it out 15 months ago, someone came in and said, give me Jason's email, give me his home address, set up a meeting on his calendar. And it turned out back then, Deli would actually set up meetings on my calendar. And I walked in one day there like four meetings set up. I didn't even know this could do it. I didn't even know this third party piece of supposed to be like, you know, synthesize your digital mind could set up appointments in the calendar. Obviously, that was an issue, right? that...

Not... not like only that when you do let's say when you want to have some analytics ask okay what is your market segment what is your customer what... what is your let's say funnels proportion yeah... that to give you better like say answers that you start to pull your internal like data to the agent to the AI and then you never sure what is inside what is outside.

So I... my... I'm agreeing with you so my point is this 15 months ago it... it... it even just with this limited data started giving out my... my... my calendar and my email address and contact information to people, right? It even said go to Jason's office to somebody next Tuesday and meet with them. Okay, so I reached out to the founders of Deli, I showed them this and they... they instantly patched it and removed it and increased the guardrails and it gotten better and the guardrails have gotten better and better and better and better. And so I'm going to answer I don't have all the answer. I'm just telling the learnings, right? So anyone here, this is why you should buy and not build. Anyone here that has been in market is going to have better guard rails than something you create and vibe yourself, right? The more you build it yourself, whether it's your team or yourself, the riskier it is. And agents are goal seeking. And agents will leak information. And prompt injections do work, right? And agents want to make you happy. And if they have access to data, they will ultimately share it. And it is a... it is the... the meta risk that once your agent gets good, it gives information to people that... that it shouldn't, right? So all you can do is that's why I not to be repetitive buy don't build and if you build it and I say this on everything stair-step it start with your least sensitive information add a little bit of sensitive information be very careful before you add detailed PII right do all these other things and the last thing I'll say is if you use something like Replit or Lovable or v0 like any these sort of vibe coding apps they've gotten a lot more secure over the last year and I can tell you I mean we use all three but in... in Replit if the... sites are private by default so it's pretty hard to leak data if it's private only your team can... can access into them so you can stair-step and get comfortable with the amount of data but it's always going to be more of an issue than just buying Salesforce it's... it's just a fact and so you've got... you've got to stair-step it get comfortable make sure you... you are comfortable with the guardrails and if you're not just buy it just buy it that... that's why OpenAI I just funded created what a hundred billion dollar consulting company that is just creating. Anthropic has one. That's why ultimately Agentforce is going to be huge because people shouldn't... it's really fun to build this stuff. 99% of people should be buying it if you can and only building what you can't buy. So it's a good question. All right. Anybody else got... question on anything even vaguely related?

Hey Jason, is... like do you use AI agents only to like scale, automate and optimize your GTM motion or can you also leverage it to actually figure it out like as an early stage startup founder?

You know there'll be... if that's what you're interested so on the... the stage in the other hall on the other side the so-called Deploy stage after this every single session will be on AI GTM agents for the rest of the day. So just go sit in them. You'll hear a lot of opinions from leaders, vendors, cos. You'll hear a lot of that stuff. I'll... I'll give you two answers. And the... and to rephrase the question is, do these AI agents work if you're super early stage and don't have something, right? And we get... we hear that a lot when we've been talking about our agents for year. Everyone's like, 'Oh, well, you're SaaStr. You have a brand. Of course it works for you.' Well, you know, most of the world has a brand. Okay? Okay. I mean, not everyone here has a brand, but like and if you... you don't have to be... you don't have to be Anthropic to have a brand. You will find even after a couple million of revenue, people in your industry have heard about you. You have a list. You have more of a brand than you think. Okay. So, as a caveat, you're right that brand... brands have always outbound cold outbound and other things. It's much nicer if they... than if they haven't, right? But and so I'll... I'll... I'll... I'll give you an answer that most of the tools we use, most of the workflows that we talk about and have built do work best if you have a brand, if you have an audience. Most of what you know, some of what we're doing might be considered cold outbound, but most of it isn't. Most of it is we have a database of 450,000 people that have interacted with SaaStr. We're segmenting it and we're using AI to talk to more of them to see if they want to do things with us. The good news is it's getting better. It's getting better and a lot of the 2024 and 2025 tools were just about taking sales off Outreach and Gong and automating it. And that's... that's great, right? But... but more and more folks here like if you go talk to Monaco that's here they're very focused on startups and filling pipeline for you if they think they can deliver if you... if you even are pre-brand. Okay. So you know you can't make people take meetings they don't want to take. You can't make them buy products they don't want to buy. That... that is... that should be obvious. But that frontier of doing colder and colder at scale and using more and more data it's getting better. But I would say 98% of the tools are not meant for magically writing a very small check and getting millions of revenue right from... from zero. It's... it's... it's early for that. But... but not too early. Talk other folks do. I don't mean to pick them out, but I know that you know it's one of the things Monaco does. They've got poker in there. So talk to them and have some fun with it and... and they'll be at... at some of these sessions and stuff too. Sam will be here.

Thank you.

Cool. Anybody else on anything related to this? No pressure, but if you want, I'm here. I've got the time. Other than the blinding lights in the face.

Yeah, we'll... we'll do more of it in the event. If you're still here, if you have the energy on Thursday morning, we're going to go through every... everything soup to nuts, right? That we use. But for folks that we have used that are here, it's all over SaaStr, but in a nutshell, we use... we've used at least five of the tools here for real. We've used Artisan, which has a nice booth here. That was the first one we used other than Deli. We use that to... so classic we use that to replace the classic cadence of a Salesloft or Outreach type tool work great for us. You got to make sure the pitch is good. You've got to work with it. You've got to iterate it. You got to train it. But it was an instant sort of level up from the classic cadence. We use that. Then to... to learn we added Agentforce, right, which is Salesforce. It's... it's... it's a bigger lift at least historically. But it's native. So we used Agentforce for winback. We had Agentforce just automatically talk to folks who have turned and got back to them. It worked very very well. The third one we did and sales bought them. It's not a total coincidence, but there's a company called Qualified that Salesforce bought. They're here too. We put Qualified. It's on the sasterual.com website. You can try it for inbound to audit and I think Qualified it was okay. But then when Claude got good, it got good, right? Just like a lot of tools. So we use that. We add Monaco to try it for sort of this cold outbound the first day. That was fun. And then there's two similar products Momentum and Attentive which are sort of... they listen watch and train everything. Okay guys hello can you hear this? And if you want to do some S-tier stuff ingesting every single thing that your sales team says every conversation every email using those APIs are pretty cool. this sort of Momentum or Attentive. I have... I should post this. I'm an investor in a company called Owner that... that just crossed a billion dollars in revenue for restaurants. It's an AI tool for... for restaurants like a next generation Toast. The CEO will be here on Thursday. But anyhow, their CTO took these tools Momentum plus the Salesforce API and built a thing so that they could automate every single one loss deal. So he... in... he took in they've got I don't know 200 300 sales reps a CRM... I'll be tomorrow they ingest every single call every single conversation and then he uses AI to exactly understand why they lose every single deal and then they summarize it in a dashboard for the whole team so no one's guessing anymore why we lose deals everyone knows in real time and you can track it over time just by taking you know Gong calls are great reading transcripts are great but this is using this... this company Momentum that Salesforce also bought taking all that data and analyzing it just through Claude in a cool dashboard board and literally every single person knows to the day why they lose deals. It's... it's pretty slick. So, but you can also see them at saster.ai/agents. They're... they're all I should have brought that up. They're all... they're all listed there for the most part. Cool. All right, we probably got five more minutes. Anybody else got anything? Feel free. Don't be shy. Be shy. It's all good.

One, two. Hey, quick question. Yes. So recently you... most companies are building 60% agents. So I'm just wondering what your advice is or key lessons for anyone looking to build agents into their product based on your experience and usage so far.

Yeah, I mean we have... I have talked about that a lot. I mean listen it's... I think my advice is... is simple although it may not be simple to execute, right? The advice is twofold. One, your job now for the next 12 months is to build that best agent in your space. Whatever vertical you're in, whatever you do, build the best agent because the customers are too smart. They're trying products side by side. And if your agent is crappy, they're going to know today. This isn't a year ago, right? They're going to know. So, you have to have the best agent in your space. It has to deliver demonstrable ROI so they'll pay for it. But if you do, people will often pay a lot of money. They'll often pay much more than for the product itself. So what is a 60% versus 100% versus 110% better than competition? I mean, listen, you... we all... you should know this like what... what do your competitors do? What do they use? Go play with their tools. How good are they? They're open, right? Or... or buy a seat if you have to. It's... it's okay. I give you permission to buy a seat of your competitor's product and play with it. I mean, they're all using the same LLMs. They're just building different scaffolding and software around it. And then you've got to be honest. I guess the part three is, is your team good enough to build a competitive LLM? Maybe they're good enough to build a competitive dashboard or workflow. Are they... are they good enough to build a competitive agent? Are they... do they want it badly enough? And the really annoying thing I'll say for the part four is if... if the team can't tell what's best of breed or they don't want to build it or they're too slow, as hard as it is, you got to go find someone that can move faster than that can do this, right? the I mean literally if you try again the Deli if only we... I could get the slides up again that would be great. It... you know you can build a mediocre bot here in this session right that's better than most people could have built 18 months ago but it's hard to monetize that the bar has gotten up. So I don't know if that... you can ask one follow-up question. And I don't know if that totally helps, but that's what I want. People are... people everyone uses Claude and Cloud and ChatGPT. They know what good is, right?

Yeah. No, I think that is helpful. I guess I feel like we're trying to figure out what that magic moment is where it feels like this is magical. I'm willing to pay anything for it. And it feels like everybody's trying to discover that at the moment. And I wonder whether you would put some of the companies here in that bracket of early...

I think so. Look, the simple answer is actually I would argue magic isn't enough in 20... in the... in the middle of 2026. Magic was great a year ago. It... it was great. Now the truth is most of the agents that are... that you can charge for are replacing humans. It doesn't mean we're laying people off. It might mean we're laying people off. It means, listen, if I will pay $50,000 a year for an AI SDR here, of which there are several, if it really gets me customers, but I might as... even as a tiny organization, but I'm not...

You're going to pay $50,000 for an email automation cadence tool. It feels like a ripoff, doesn't it? Let's say you're 10 people in your company. Do you really want to pay $50,000 a year for outreach? Feels like a bad deal, right? But what if it got you 10 customers, 10 $50k customers? It would feel like the best deal in the world. And how many SDRs on your team are actually great? Probably zero. So that's the kind of benefit of the bargain that you have to find for your customers. That's why Sierra, Decagon, all these CX stuff blew up when it was a small, very cheap, low-end space before because they couldn't really replace people. They could just make it easier to manage teams of human agents, right? And all the pre-AI customer success CX tools just let you automate humans with customers with issues talking with humans on the other side. The ROI was real, but it wasn't a game-changer in terms of cost savings or productivity like these things are. So, sorry, excuse me for some water. That's what you have to find. And look, I know my hands are full. I'm not saying this is easy. But if you can use an agent to replace a person, two or three people, four or five people, a percent of people, even the smallest company will have huge budget. They'll have huge budget. Yeah. Go ahead. Sorry.

The question is do you recommend pricing agents on token users or outcome? I'm going to give you a first answer that we'll wrap on this so that we have a minute to hear from Vercel how they're running AI GTM agents. So come here in just a minute. I'm going to tell you I don't think it matters, but I'm being a little facetious and a little cute when I say this. If your agent is great, just charge what it's worth and be fair. Charging per token, listen, there are some use cases where it makes sense. No one's really doing this today. They're charging on outcomes. Whether you price on outcome versus charge on outcome maybe aren't the same thing. Okay. Basically, no matter what anybody says, customers just want a product that really, really works with some certainty around pricing. What's it going to cost me? $50,000 a year, $25,000 a year, $2,000 a month. Just tell me if I have to pay some overage or extra fees because I use a lot of the products, so be it. But I don't want to be charged per token. That's not very customer-centric. And a lot of the thinking is a little bit dated. For example, if you look at the CX space support, it seemed revolutionary when Sierra, which was founded by the ex-CTO of Facebook and the ex-COO of Salesforce, said, 'Oh, we're just going to charge based on positive resolution, based on outcome.' It seems so disruptive. But actually, I think the other day, maybe just a week ago, HubSpot changed to that pricing. Why? Because the agents got so good, 90% of the tickets got resolved, so you might as well charge per outcome. So, I think as all these products have gotten better, don't worry about it. Just charge for success, right? I'll give you even a nerdier example and then we can break in a minute. Like a lot of this stuff here we've built on these vibe coding platforms and a year ago if you went on the internet and you looked at Replit and Lovable and v0, a lot of folks would be complaining, 'Man, I got overcharged, the darn agent put all these bugs in my software and it cost me $200 to rerun it.' And I don't really see those complaints anymore because the agents are better, right? The agents are better. So just charge a fair price that is tied to positive outcomes and force yourself to charge a lot so that you have to deliver a lot of value to the customer. But I don't think anybody wants to pay for tokens anymore, at least not in B2B.

You know, who knows what's more important in the AI era, distribution or product? Look, the reason I don't know the answer, we're in a weird world right now where the leaders in B2B for the most part screwed up the last 12 years. They didn't ship the best agentic products. So it created a massive opening for people here. You others, see, they have the customer bases, right? SAP, HubSpot, Salesforce, all of these folks at least in B2B should have built the best agents. I mean, I'm not being as critical as I sound, but they should have. They had the bases and the customers want to buy from a trusted vendor. They don't want to buy from somebody they never heard of. But some folks got there more quickly, right? Some folks bought their way more quickly. But ultimately, all things even remotely equal, I'd rather have an agent close to my system of record. I'd rather have an agent integrated native than have to kluge together with some third-party thing from a company I don't know of. Right? So distribution should trump product, but over the last 12 months, we've seen incredible growth because distribution was insufficient. Distribution did not have the products that delivered high enough value to the market. So product trumped distribution. And when we talk next year, I don't know where it's going to land. I hope everybody wins this disaster. I want everybody to win. But a lot of the incumbents will have a whole another year. They have a year to catch up. There's really no, the LLMs are open to everybody. There's really no excuse to not catch up. And so we'll see. The hyperscalers came back, right? Obviously Microsoft, Google, Amazon became big beneficiaries. The B2B leaders should be. They're not yet, but maybe they will be in a year, right? But right now, it's not distribution of an agent that isn't great hasn't driven topline growth for anybody. So, thanks for the question. All right, everybody. We'll keep going. We'll hear next from Vercel on building their AI sales team. So, which I want you to hear. We'll take a five-minute break and I think kick that off. So, thanks everybody. Appreciate it.

My career has been marked by basically two nearly decade-long tenures. I joined Vercel because it became clear to me that over time every pixel on the internet should be built on Vercel. Vercel really does employ inventors. I want to build a really different go-to-market. You're creating something choreographed to get someone to the aha moment. Different industries, different company sizes, all with a shared mindset. Move fast, experiment boldly, and redefine how things get built on the web. Please welcome to the stage the COO of Vercel, Jean-David Grosser.

All right. Well, I will do my best before we get them up here. So, thank you everybody for joining me today. I'm Jean, the COO for Vercel. We are best known as the creators and maintainers of Next.js, who helped power a lot of the front end for the last generation that we were all in. I joined Vercel because it was one of the most engineering-forward companies out there and one of the first things I did when joining about six weeks in was to establish a go-to-market engineering team. This was back in June of 2025 before that phrase started being common and the goal of that team was to bring AI and agents to everything we did across go-to-market internally. After 10 months of working with this go-to-market engineering team as well as with other teams across Vercel building agents, we now have automated actually a decent number of core functions within the company. For example, our customer support agent, and you can imagine at Vercel a lot of our cases are complicated and highly technical, now handles 93% of total case load. Similarly, our content agent is used heavily by the marketing organization and did 96% of our major content updates last quarter. One of the bigger things we shared was an initial impact within the go-to-market org on sales development. So we launched a lead qualification agent back in August of last year. We started that with about 20% of a single engineer working on that agent. And with a human in the loop over the course of six weeks, we're able to completely move all but one human, taking our team of 10 on that function down to one. We now still have one person running that in the US and then about 20% of a person doing all of Europe and all of APAC. And when this came out, people sort of decried the end of the knowledge worker. But for us, really what we did was to shift all of those people into more valuable roles.

So, I'll give you a little sense of what we did with the lead agent. This, what the working model that we've used for all of our internal agent development is basically a tripod. It's a GTM engineer, a data scientist, and then the best person, the best subject matter expert in that function. And they sit down shoulder-to-shoulder and document the best practice for that particular function and then encode that in workflows that ultimately form an agent. We then keep a human in the loop. So that human will basically QA the agent. The agent won't be allowed to autonomously execute its action. And then over time as the subject matter expert has less feedback for the agent, we finally pull that person. Last year was declared the year of agents. And I think reasonably speaking, we didn't quite get all the way there on that one, but I think we're now with the infrastructure available in 2026 able to finally get there. So 2025 really ended up being much more about assistance. It was great for co-pilots, personal productivity, good prototyping, things that looked sexy and new, but very little in the way of actual agentic capability at scale. Now, we're getting to the point where you can have agents that actually act, that can complete end-to-end complicated business outcomes. And we're moving towards a world where agents can work as sub-agents underneath a super agent to ultimately collaborate and complete much more complicated actions. What happens though is most of us have not started doing anything at scale and so you haven't hit all the rough edges when all of a sudden that agent is operating at a hundred or a thousand times the scale it was previously. When that happens, you start to have infrastructure problems, costs in places you didn't anticipate them. And it's because the cloud infrastructure that we've all grown up on for the last 20 years wasn't built for this era. It's built for a simpler world where you have a request and you go out and return an output. But that's not how agents function. Agents are much more complicated. Their thinking, talking to an LLM with long-duration execution and tool calling and all those things actually require different infrastructure to execute them effectively.

So Vercel along the way has built a bunch of new agentic primitives. We call this agentic infrastructure and we built it for ourselves because I think one, Vercel is one of the most effective kind of customer zeros out there, but two, you could not get this off the shelf. So what is agentic infrastructure? We think that this is the next era, like a set of SDKs to help you quickly build these agents at scale, an AI gateway to be able to connect to different LLMs and try the latest model when it gets updated on a Sunday, and new primitives like fluid compute that respond differently when you have an LLM off thinking to fulfill a request. On top of that, you want your infrastructure to do fundamentally different things. The first thing you want is an effective deployment target for agentic engineering. For Vercel, one out of three deployments from our customers was now generated from an agentic engineering offering like Cloud Code or Codex. So we've optimized the infrastructure to come from where code is being written today. Two is the primitives I just discussed. They're different in an AI world even if things like compute or sandbox have been around for a while. And last but not least, you want infrastructure that is itself agentic, that gives you solutions rather than alerts, dashboards, and problems.

So what are the three things to take away as you all think about building agents both within your own products but also what we call business agents, the internal ones that you will end up building to make your own teams more successful with their bespoke workflows. First, agents need headless composable architecture. Agents don't live in UIs. They call APIs. They hit MCP servers. If your product isn't composable and developer accessible, you're invisible to agentic workflows and you're simply not going to be in the stack. Second, agents require you to invest in your data foundation. You should obviously be using data to decide how to cut territories, set quotas, and run your business. A strong data foundation has always been critical to the success of your business. But now data is the fuel that powers your agents. Good data equals good agents. So if your semantic layer includes highly accurate customer enrichment, your lead agent qualifies better than any MQL framework could have and your copy sounds more natural than any SDR could have ever written. And three, agents change the build-by calculus. Teams no longer need to default to buying just because development is too costly or slow. So I'll show you how each of these showed up for us.

Let's start with Deal One. This is our meeting intelligence agent. Deal One ingests every call, generates notes with action items, and posts coaching suggestions directly to internal Slack channels. It proposes CRM field updates. It tracks competitive mentions and objections over time. And it runs postmortems on every closed-lost deal. And all of this happens where we already work. For us at Vercel, that's generally in Slack. When a rep goes into a channel and mentions @dealone with a question, the agent does a Slack real-time search, queries D0, another agent of ours for data as a sub-agent, pulls Gong transcripts, searches our internal knowledge base, and streams the answers back into the Slack channel. The rep never leaves Slack, and the agent never has a UI. For Deal One to work, Gong needed an accessible API. Salesforce needed webhooks we could actually compose into automated workflows because those external products had composable developer surfaces. Everything worked. If they didn't, we would have gotten rid of the tool.

Next, there's the playbook platform. We kept seeing a pattern in our best reps. They knew to reach out when a customer's usage spiked or when a high-value prospect ended up on our pricing page. They did this instinctively, but it didn't scale. It depended on which rep owned the account and whether they followed through on their signals in their dashboard. The playbook platform automates all of that. A signal fires like a usage spike or a high-intent pricing page visit and the platform matches it to a play, generates personalized outreach and surfaces it to the rep for a single-click review. The best reps' plays, available to everyone, are automatically triggered. The before: we should reach out when usage spiked, but it never happened consistently. The after: an 11 out of 10 experience on every account every time. Notice no separate UI to log into. Signals flow in, drafted outreach flows out. Reps review in their existing workflow. We built it all headless by design. The companies that win in the agentic era will be the ones whose products have headless composable architecture. You've seen this signal coming from the best enterprise SaaS companies out there. Box, Notion, Salesforce. They're all making major bets on their developer platforms right now. So, the to-do here is simple. Even if the work isn't, go build the developer surface areas now. MCP servers, webhooks, APIs.

Next, data. Probably the most popular agent at Vercel used by the entire company is DZero. DZero is a data analyst agent that everyone at Vercel can access via Slack. Questions that used to take a week to ticket and get an answer back from the data science team can now be answered in less than a minute. What it'll answer things like: what was our token volume through AI Gateway last week? What companies do we have logo rights for in the UK? Who are our highest revenue startup customers using sandboxes? DZero powerfully democratizes data across the company. To do this, DZero translates natural language questions into SQL queries against our analytics infrastructure, letting anyone on the team answer questions without writing code or waiting for the data team. To power DZero, we invested heavily in what we call the knowledge base. It's a structured queryable representation of our business that all our agents can reason over. Our head of data science built a semantic layer on top of a model of our revenue, breaking down the business into the smallest causal units enriched with third-party and first-party signals. That layer is what powers DZero. It's what makes Deal One's analysis actionable rather than just interesting and it's what makes the playbook platform contact the right companies with the right message. Every agent runs on top of it. Without it, agents hallucinate or give generic answers. With it, agents are grounded in our data.

Finally, agents changed the build-by calculus. With the rise of SaaS, enterprise software was a procurement exercise. But now, robust applications and agents can be built and run at scale in a matter of weeks. Companies are building for their own unique workflows. To give you some perspective, the lead qualification agent that I opened with costs us under $5,000 a year between infrastructure and tokens to run. It takes about 20% of one engineer to maintain it. That's a 32x ROI. We used to have 10 people and their salaries. It's now $5,000 and it operates 24/7 with faster speed to lead and all the quality of human-equivalent metrics. That said, building isn't automatically the answer. So, every quarter I ask the same question of my GTM engineering team. Has another company out there built something better, faster, or cheaper than we already have? And if the answer is yes, our agent's going to go.

So, how did we actually do all of this? We had a GTM engineer, as I mentioned, shadow one of our best SDRs for a few days, shoulder-to-shoulder, looking at their screen together, watching every single tab she opened, LinkedIn, BuiltWith, the company website, CRM, Slack history. The engineer converted each of those data sources into a step in a tool-calling workflow. We documented it, made the workflow leverable before touching any AI. After building our first version, the agent ran in production in shadow mode for six weeks. Our best SDR reviewed every single output to create a feedback flywheel. And then finally, she couldn't improve it anymore. The architecture reflects exactly what she was doing manually, but now it performs like the 90th percentile rep 100% of the time. We applied the same framework to 30 different SDR workflows from event follow-up to PQA flows to specific time-based campaigns. SDR quotas increased by 30% this quarter. And again, the lead agent was not hard to build. A single engineer prototyped this over the weekend and it was in production six weeks later.

Then there's Vertex. This is our customer service agent, sort of like our internal Sierra that powers vercel.com/help. Vertex costs us $300 a month in infrastructure plus $12,000 in tokens. It's $150k a year. It operates at significant scale handling thousands of technical cases a week and three engineers work on it. Three. We started with an off-the-shelf solution but weren't seeing enough results. We built something in-house in two months and had it in production. Compare that with some of the agentic support companies out there with 150 engineers running the equivalent workflows at dramatically higher costs. The difference isn't magic. It's that we used infrastructure built for agents from the start rather than discovering the cost problem after we'd already committed to an architecture. All of our agents, lead agent, the playbook platform, Deal One, DZero, run on fluid compute. The infrastructure that powers our internal agents is the same infrastructure that our customers deploy their own agents and applications to. You may have heard my colleague Tom Okino speak about this earlier today. Most rules of cloud infrastructure are broken by agents. Fluid runs high-performance multi-tenant compute only triggers when needed. Plus, it reuses existing resources before spinning up new ones. So, early adopters cut compute costs by up to 85%. When you hear us saying that we purpose-built infrastructure for this next generation of the web, fluid is a big part of that.

Everyone wants to talk about what agents can do. Fewer people want to talk about how complex it gets when they're running at scale. If your agentic product succeeds, usage goes up. If usage goes up, that profile matters. Infrastructure choices matter a lot more than many teams realize at the beginning. Go-to-market is getting closer to consulting than sales. The executives I'm talking to right now aren't asking me to pitch them on Vercel. They're asking me to help them figure out where to start with agentic AI, what best practices look like and what architecture should be, what breaks at scale. A lot of companies are still early enough that they haven't fully felt this yet. The MCP server gets nominal traffic. Their business agent is still in an experimentation phase. Their AI workflows are impressive but not yet heavily used. That's fine, but it can give you a false sense of readiness because production scale is what reveals whether your architecture is actually durable. That's one of the reasons we think there is a significant difference between building an agent demo and building something in production at scale.

So to recap, one, build your developer surface area now. APIs, MCP servers, webhooks, the things that let your product be composed into an agentic workflow without a human in the loop. The companies that win in the agentic era will be the ones whose products are in the stack. The ones whose composable API layer won't, the ones who aren't won't have the composable API layer to be called. Two, invest in your data foundation, the knowledge base, the clean data warehouse, the semantic layer. None of it is exciting to build, but all of it is load-bearing. The agents you build will only be as good as the data underneath them. And as we learn, putting that data in front of smart people will make the data better itself, not just the agent that uses it. And three, the average builder on your team today should be able to out-ship any vendor who's trying to sell you the same outcome. And if they can't, you can start experimenting today with a few hours carved out of the week. That's the new build versus buy. I truly believe that the companies that treat their go-to-market as a product, that document it, design it, iterate, and then automate it piece by piece are the ones that will end up on the right side of the shift to agents. That's what we're building at Vercel and we hope you build the same too.

Let's give a warm welcome to the Chief AI Officer of SaaStr, Amelia Laroo.

Hello, SaaStr. Excited to have you guys today. Give it up for our band, our house band. I think four years or five or 10 years in a row now. Who knows? Thanks, Michael. All right. So, Jason did an AI agents 101. I know some of you were here for it. I'm going to do a 201 if you will as a little AI agents university all together now. We are going to live build an AI VP of marketing. So I hope you're ready. I see you have your laptops out. So we're going to do a couple things to get you guys set up and then I'm going to go to my laptop. We'll demo. We'll do it together so that hopefully by the time you leave this session you have your very own version of what we call 10K who is our AI VP of marketing. So you guys already know this. We have I don't know almost 30 agents now at SaaStr that have been used almost a million times. But a few things to keep in mind as you're getting going and started with building your very own version of 10K. So 10K started as actually something that I was slightly lazy about. I was tired as many of you might be of taking all of our different dashboards across marketing, sales, go-to-market. Now we don't have that very many people but it was still a lot of tedious work every Sunday night to copy paste put it into Notion every Sunday night and then every Monday morning go through it every Monday and so I didn't want to copy paste anymore. I thought to myself, you know what, let me just vibe code a dashboard to help me do this. But then that was back in January and now 10K, you know, fast forward five months later has become our AI co-pilot in marketing. This is a screenshot of 10K. I'll show you him live as well. But all of that to say, he started as a dashboard. So if all you leave today is even a dashboard, just know we've been building with 10K literally every day between myself and Jason for the last five months. And so it might take you some time after this session if you leave with a basic one to build it to the full feature and functionality that we have at SaaStr. So just keep that in mind. Also keep in mind you may want to add things that are more nuanced to your company. So there are things, you know, like you may not care about ticket sales in the way that I do. Maybe you care about more self-served customers or enterprise customers or different nuance things like that that may only apply to you. So keep that in mind that it started out in January. We've stairstepped the whole thing to what 10K is now, which I'll show you today, where he is making some autonomous marketing decisions. He helps us send campaigns. He's literally our co-pilot. He told me this morning, 'Hey, don't forget to send the attendee newsletter.' I said, 'Oh, yeah.' He helped me build it and he can do a lot of things on his own. So, but again, I just want you guys to know he started as literally a dashboard so that I could just hook in my Salesforce and that even if my reps forgot to do something, if they remembered to do it in Salesforce, then at least it would be in 10K by the time we did our Monday morning team call. So keep that in mind.

The other thing I want you guys to keep in mind, it's a little nuanced. So it's okay if you don't quite get the hang of this until later, maybe after you leave SaaStr, but 10K, who is our AI VP of marketing, isn't just a chatbot. He's not a code generator. And also, it's kind of a niche usage of how we're using vibe coding, Replit in specific, that we talk to our agent and the agent is literally 10K. And we have a lot of different agents. We have the agent that is SaaStr Annual. We have got the agent that's powering 10K. We've got QB who we talk about a lot on the podcast. He's our AI VP of customer success. And how these all have different personalities is we're actually using the agent as the entity. So it's not that we built our own like other super agent or super connector. I know it's a little nuanced and niche, but just something to keep in mind that if you build one of these for your team, whoever is building the agent, yourself or your head of AI or if you hire an FTE, whoever is managing the agent eventually will be the one talking to the agent in the way that we talk to 10K. And there are pieces you can share outwardly, like we've got members of our sales team who interact with 10K, but they don't talk to 10K the same way that I do on a daily basis. So, I'll explain that a little bit more, but just something nuance to keep in mind. And if you want a live build with me, hopefully this code works, but you can use the code Replit to get some free credits while I'm doing this so that you guys can build yours while you're out there in the audience.

So, okay, a couple things here on what 10K can do internally versus externally. Because as I'm going through this, what I would love for you guys to do is like have your notepad, have your Claude out or your Whisperflow or Granola, whatever you prefer, whatever agent you want, take notes so that you can write, you can incorporate all your notes into your own custom spec to deploy your AI VP of marketing. So, just as I'm talking through these use cases of things we have our agent do, write down what you want your agent to do in either a similar or same fashion because then you're going to literally take it, put it into the spec in a few minutes and give that to the agent to deploy. So, I always like to start with a spec. The more detailed you are with your spec, the better. That means you'll get better inputs from the agents and also better outputs from the agents. So, I'll walk you through how to do all that now. So a few things that our external-facing 10K AI VP of marketing does. Yes, he has dashboards. That part is pretty basic as you'll come to see. But that was his origination. That's what he does. Data. I'll walk you through next what set of data we gave him to have an AI VP of marketing as we have it today. Biggest thing here, closed-won revenue pipeline. So we gave him access to Salesforce via the API. You guys are also probably on Salesforce. So you can achieve this with a custom object to get all of your real-time and historical closed-won revenue and pipeline data. That will also give you historical comparisons. It'll help you with projection. So again, the more you hook up, the more time you spend with it, the more you'll start to hook up to your AI VP of marketing things like we just hooked up all of our, all SaaStr.com is hooked up to it now. All of our social media, all of our analytics. We actually just built a newsletter builder in it. But there's a lot you could do in the agent.

So again, things that we do that were external-facing I just went through and then there's internal things you can do with the agent. So yes, once your agent has all this data, things you'll be able to do is build ongoing features. So every day that Jason and I are like programming our agents, you know, we think of something new we want to do. We're like, 'Hey, can you do a win-back campaign to maybe folks that came to SaaStr Annual last year but hadn't yet bought a ticket for this year?' He can run that whole list, see who hasn't, come back. You can hook it up to something like a Clay, find their new contact data, and then send an email campaign just like that. So, projections, it's really great for revenue projections. We use it every Monday just to keep us on track and honest, honestly. And then marketing campaigns, I'll show you guys in a little bit. This is one of my favorite things it does because it's all based in data. You know, I think sometimes I know marketing is pretty creative and people have different ideas of what they think will work and then certain people have like certain agencies they want to bring in when they come to your company. But the nice thing about building something like an agent is any ideas it's going to give you is only based in data. Like that's all it has. It's got all your data. It's got your numbers. It's got a goal. Hopefully, you give it a goal. Maybe write down your goal as I'm chatting for your AI VP of marketing. And that's all it's going to focus on 24/7 all the time. So, it's kind of crazy because we've actually said on our podcast like now we need people to report to our agent because it's gotten so advanced on how it does marketing.

So, that's a few things that it does. Again, what I want you guys to do, as you can see here, like this, these are the top five things our AI VP of marketing does. And I had it describe itself. So I was like, well, I could think of the top three things that our AI VP of marketing does, but why not let him tell you? So the number one thing he does is own the number. So this is super important as you're writing your spec, as you guys are taking notes. Make sure you give your agent one goal. So that's also why we have like multiple agents between our AI VP of marketing, our AI VP of customer success, our AI SaaStr Annual agent. Like they all have different brains. I don't like to overload them. I like to keep them specific. So, we gave this guy one goal of what to do. Campaign performance, you know, sometimes the data you put in is what you get out. So, I think that's super important. Content, yeah, I'll give it that number. He ranked daily marketing ideas number four. I would have probably ranked it number one. But this is one of the funnest things it does for me. And yes, honestly, it can write email copy. I know there's a lot of AI agents out there that can write email copy, but again because ours is based and grounded and foundationally built upon the data that we have and the goal we're trying to achieve, it's more goal-seeking to hit those outcomes specifically. So this is how our AI agent described himself. If you read Jason's post, he doesn't actually think of himself as a VP of marketing yet. He says he only does some of that functionality. But I would say he, outside of owning people, he does pretty good. So I'm gonna go over to my laptop so we can do some live building together. While I'm doing that right now, you guys can go to saastrannual.com/resources. I vibe-coded it for you last night and you can grab this very spec that I already built. So there's a screenshot of it. I'm going to go over to my laptop, but ideally what you're going to do is you're going to grab the spec that I've already pre-built for you. And as you were hopefully taking notes while I was chatting or if you do this later with your team or later when you have a quiet moment to think about it, you'll be able to literally take this like 20-page long document that I already made and pop it into your favorite vibe coding platform, Replit, whatever it is, and make and get your own agent. If you want to do it live, I did a recreation that I'll show you and it took about 15-20 minutes for the agent to build it. So if you do it now, I have like 40 minutes left in the session so that by the time I'm done you'll have an agent.

Okay. So, hopefully you will grab the spec and I'm going to just drive here. So, let me come out to where I am. Perfect. All right. Cool. You guys are following along. Cool. All right. So, hit this resources. You guys will come here. So, again, this is saastrannual.com/resources. Grab these two things. So, I'm going to grab it. That's the spec. It's really long, but it's there. What you're going to do with this spec, you're like, Amelia, what do I do with this really long document that you created me? So, take this, if you want to use it now in real time, you can use it as is to build your own version of an AI VP of marketing. What you really should do though after this session is take this and write a version that more so applies to your business. I wrote this as more of a generic AI VP of marketing again with goals that I thought were more prevalent to you guys all here today. But you might want, again the more specific you make it the better the outputs of your agent will be. So I would take this later again, you know, make it more unique to you. If you haven't used co-work yet I use co-work a lot. You can ask Claude like what you should include in your spec when you're building out, you know, say the goal is that you want to have an AI VP of marketing agent. Say you wanted to build, you know, marketing campaigns for you. I wanted to do projections. I wanted to use it as a co-pilot. Like part of it too is honestly a mentality of how you treat your agent. Like we, I treated it day one as a dashboard. I was like, 'You are dashboard.' But now he is very much a co-pilot and co-worker. Literally, I was talking to 10K this morning about stuff and like we were bouncing ideas and I was like, 'These are great ideas, but I got to go do SaaStr now.' So again, it's part of it is also a mind shift of how you use your agents and how you also think about incorporating them into your workflows.

So what you'll do, you'll grab the spec. Again, you can use it as is if you want to right now. If you want to just make an agent right now, you can grab the spec that I made on SaaStr. The other thing you can do that you can grab from the resources section is download this sample historical data. So, I'll walk you through what's in there, but basically what you want to do is give the agent some data to start off with. So, when I started off building this as a dashboard, again, we had a bunch of stuff on CSVs. Like, don't be embarrassed by that. It's totally fine. Like, we still had stuff on CSVs that wasn't anywhere else. And then we had some stuff on CSVs that was somewhat in Salesforce, somewhat in Marketo, somewhere in like a million different places. And so, I gave it some CSVs. It's okay to do that. If you're worried about the security aspect of that, you can always just, you know, hook up natively to your marketing automation platform via the APIs, hook up to your CRM, whatever you're using. Some of your major tools. Again, you don't have to add those all day one. Eventually, you will need to though if you want to reach the same level of like semi-autonomy that our agent has. But you can definitely start simpler. The goal is honestly just to deploy an agent and keep building with it. Like what you want to get on day one, maybe through this session or when you do it later, using this data and spec is to really think again, think through the spec, build it with the agent together so that you have something feasible where you feel comfortable talking to the agent, building upon him and bouncing ideas back and forth on what to do hopefully for your marketing at your company.

So a few things to start with. Again, it's okay if you don't have this all today, but just some steps to follow if you are, you know, rebuilding your own AI VP of marketing. So, again, revenue, even though some might argue that's kind of sales data, but if you know at all how much marketing-sourced revenue has brought in or marketing-touched revenue, however you measure it, if you have any sort of data around marketing's final goal on an impact on revenue, that's the very first thing you're going to want to give your agent. The second thing would be obviously this isn't a VP of marketing. Give it campaign data. So, give it, you know, what campaigns are working. Give it everything that's not working. Give it everything in the middle. Any ads that you've run, anything that you think didn't work, any agency spends, like I mentioned, like everything. The more you can give your agent, the better. Like, just trust that it will use that data to basically build a brain that is dedicated to marketing just for you. So that's a good way to think about it. Campaign data is great. Email data is really great. Like just even exporting like how many people are reading our emails or not. What are people clicking in our emails or not? These are all really great things to give your agent so that it can give you better outputs. I like to give it like a progress tracker. So say you're building your agent today, you can start to give it, you know, what have you done so far through May of 2026. And it will give you some feedback of, hey, maybe that campaign you run that you thought was gangbusters didn't actually work. So that's a good thing to do with it as well.

Okay, so hopefully you have that now. And then what you'll do if you're literally doing this from scratch, you would do something like this. Now this is our Replit. So I already have one, but I'll do it from scratch with you guys. I'm going to say, you know, create an AI VP of marketing as a co-pilot. Here is the data and here is the spec. And then what you would do is you would take those two assets that I literally have up for download on saastrannual.com and do that as a list here. Here's my data. And then I'm going to give it the spec. So, I'm just going to copy this, paste this into the agent hopefully. Oh, I can see it here. Okay. And then I'm going to let that fire. We will come back to that guy. Like I said, last time I did this live, it took about 15-20 minutes and we've got more than that. So, we'll come back to that guy. I'm going to let the agent percolate. I am hardwired into the internet. We'll see how long it takes. For now, I'll show you two things. So, this is the one that I rebuilt the other day. This is the one that I literally built in 15. I didn't do anything to it. I was like, I did the same thing you just saw me do. And then I said, make it purple to match the vibe and that was it. So, this is literally already what it spit me out. Even just with that spec, just with that sample data, this is what I got. So, I'll walk you through it. So, you can see here again, 10K started as a dashboard. Maybe you don't want your 10K to have a dashboard. I don't know. I like to have dashboards still as a person and a human being. But you can also take that out of your spec if you don't want a dashboard. I think most of you do though. I think you probably want a dashboard of like what's working in marketing, what's not, what are the campaigns I should run, what are the campaigns I shouldn't run. And that's what this does. So you can see here this is obviously fake data for Acme Corp, but it's giving me a dashboard. It's giving me, in this case I just rebuilt the spec. So it's like attendee information. It's got pipeline. It's got our sponsors, right? Who are all of our sponsors that we should be checking in on? It's got invites. So, this is all fake obviously because Pi Piper was not a real company, but it's giving me things of like, okay, who should I, who should I personally, it says I should personally reinvite these people to SaaStr again. I mean, that's even right there for 15 minutes. If all you get is one campaign where your agent told you people you should follow up with as customers, people you should win back...

Maybe it helped you identify some people on the website that you should email. I think that's a win. Your agent does not need to be our full-blown AI VP of marketing like ours is, and it certainly won't be in a day. Again, ours has taken about five months to get to this point. So, something important to keep in mind, even if you only use your new agent for something like daily ideas, I think it again because it's using data because it wants to hit one goal for you, it's going to give you some pretty good ideas of what you should be doing every day in marketing. So, the top three things, because even three is too many. You can say just give me the top one idea of what we should be doing in marketing to execute on the team today. And honestly, the ones our agent has given us again are pretty good. It's because we've put in some pretty good data. We gave it one goal. And you can also tell the agent and fine-tune it. Like the first time we got the daily ideas, they were okay. And then we're like, hey, no offense, but that idea kind of sucked. Like we wouldn't do it or that other idea was going to cost a lot of money. Why would we do that? And so you can tell the agent, give it that feedback so that every day the ideas that it generates are getting better and better for you.

So let me pop back to my slides for a sec so I can make sure I walk you guys through everything you need to do. So while that runs, a couple nuance things again as you're recreating this and building it yourself. So I did build a what is called a Salesforce connected app. Trust me, I had not done that. I'm not, I mean our friends at Salesforce are over there. I'm not Trailblazer certified. I have an agent blazer hoodie which I very much love but I don't even think I'm agent blazer certified or anything. So I just asked Claude how to do it. And it was honestly because I was like, hey, how do I hook up this new agent I just built to my actual pipeline and revenue data so that I could hopefully read all that data and now it can actually write back some of that data. So that was the very first thing I did. For many of you that will be the same first step. So even again you could say maybe that's too sales-related but I think for something where it's still marketing and revenue and go-to-market related, it's important to have these things incorporated. So that's probably the first thing you're going to do too, probably after this session because it might take longer than the 25 minutes we have left but this is something you can do. It doesn't take very long.

The other thing you'll want to do next is hook up all your major APIs. Right? So again, whatever you're using for CRM, marketing automation platform, you can hook up your social media if you wanted to do posts for you. We still like to write ours manually. Slack is a nice one to hook up. Google Calendar, I actually used the Google Calendar hook up to send all of our speakers their speaker times and profile information. I was like, that was literally a whole person's job last year. And now an agent did it. So again, there's a lot of little things where you're like, 'That sounds minor, and yes, it is, but that was literally a part of someone's job last year that the agent not only did perfectly, but did it in 10 minutes.' We're like, that used to take a week to send our hundreds of speakers a personalized Google Calendar invite saying, 'Hey, please show up to not your address, a different address at the San Mateo County Event Center. Here's how our team will work. Here's how we'll take you to the green room. Here's how you come back.' All those nuance details. And also we told our agent, make sure you include anybody else that should be on the invite. So like any press teams, any marketing teams, any executive teams, and it just did it for us in 20 minutes. So even if you think your victories are kind of small with an agent, they're still pretty big. So again, don't feel like your agent has to do everything all at once, even if you give it super menial tasks, it's great at super menial tasks like that. Like that is something that your time is better used building the agent and deploying these campaigns that only you can deploy versus spending all this time doing nuance things in marketing like writing tweets. Like there are things that are a better use of time or coming up with campaigns that you're like I'm not sure are going to work well. The agent has all the data, it will give you a pretty good understanding of what it thinks it will do.

So a few things you'll be able to automate while it's percolating. I'll check back in with it in a second. But again, these are daily ideas. I just took one from last week where this was actually from our real 10K. It gave me three ideas for the day of what I should do in marketing just to give you a sample again if you use my spec of something you can have your very own AI VP of marketing do. Which is again send you ideas of what to do. So if for instance you're behind on something or if you're trailing behind a goal, one, it'll probably tell you to adjust the goal and be realistic. Two, it will give you some ideas of how to get there. And again, are these groundbreaking? No. But they're pretty good. I mean, there are things I might have forgotten about because we're really busy leading up to SaaStr. There are things you might be forgetting or things that you're too busy for as founders to go and do yourself. And so, it's just a really great reminder of what to do and when to do it. We have it again as a daily frequency. We do three ideas. You can cut that up and down as you see fit.

Other things it does really well is not only just like ideas, but also it's a really great email marketer. It's kind of funny because like the last couple things I've been sliding you guys through is like that used to be part of my job, too. All of this I had to do manually back when I started at SaaStr and now I just have an agent do it. But one thing it does really well is something like triggered emails. So again, you can think of a workflow that is more unique to your company, but some people have universal workflows. Like if you want to do one to follow up on current customers when they hit a certain threshold, your agent can do that. Now whether you call that marketing or product marketing or customer marketing, it doesn't, you know what, your agent doesn't care what its title is. Like you can give your agent kind of different little things within marketing to do emails like this and it will do it for you. So, this is one where we took a screenshot of something 10K did and said, 'Okay, like Replit is obviously a sponsor of SaaStr. Here are all the great folks that are coming that are like them and we sent this to a competitor and said, Hey, you should probably be at SaaStr, too.' So that was a really great use case of, you know, we ran a light competitive campaign. It's a little bit of sales. I think it's a little bit of sales and marketing, but again something our agent could just autonomously do versus maybe you telling your SDRs, your sales team or your marketing team to go find out who your competitors are, then find the contact details at those companies, then figure out in your data, okay, what are those people doing with my company that I should highlight to those competitors? The agent can just do it for you. Again, if you give it the right data, if you give it the right inputs, the agent can just do that for you.

The attendee newsletters and reminders you guys got. So this is more of a universal email campaign you can do with your agent for running website action email. So when people take an action on the website. So, for instance, when some of you came to the website, you played little Agent Hexi, who's also here on the stage, you played little Agent Hex's briefcase game or other game or spin wheel or I don't know, he had a bunch of games or Easter egg on the website and you could get a code to get like a small discount on your SaaStr annual ticket. Well, 10K just emailed all of you your reminders. Like that wasn't, again that used to be my job like hey if somebody comes to the website and they don't buy a ticket make sure you know every Friday you remember to send those persons an email to buy their ticket if they didn't buy it yet. Well now the agent just does that. You can hook up third-party tools like Vector 2. We use it as well to like deanonymize website traffic if you want to go that far. Obviously there's some risk involved there. So do that at your own risk. But there's a lot of things you could just do on your website. This one collected emails when people put in for the code. So, it already had their email and then just started emailing them, I think only twice. If you didn't buy your ticket, it would email you like twice autonomously on its own. And then every time we saw it send out a daily reminder, we would see tickets spike. So, again, it's really good at doing these kind of seemingly mundane marketing tasks that seem simple. Again, like people visit the website, you want to send them the email, let the agent do that so that the humans don't forget that. Like let the humans work with the agents to build out that content together with the agent, but it's really great at doing stuff like that.

Okay. Another thing it can do really well is things like newsletter. So, hopefully the one that you guys all read this morning, the attending newsletter you guys got was also built by our agent. So, I was like, 'Hey, what should I include?' because usually this is me like really tired trying to figure out what to remind people when they come to SaaStr but also I forget honestly what I should be reminding people because I've been to a lot of SaaStrs now and I'm on the back side of the whole thing that I'm like I don't know, people already know that, haven't they already heard that? And so I just ask the agent what I should include versus my own biases of what I thought I should include in the attendee newsletter. And then again finally some things you'll start to automate is we did actually, we've done now so many of these emails with our agent that we actually built in a newsletter builder into our AI VP of marketing so that we wouldn't have to keep building emails on like different templates and different styles and like sometimes it would kind of forget this little agent guy at the top and sometimes this little countdown would break. Again simple things but for ease of use of how much we started to use our agent to help us send emails we actually just vibe coded a newsletter builder into our agent to help us keep sending these emails in perpetuity and that we could also test them along the way.

So, a few things to remember here and then we'll see how our little percolator did. Your new almost VP of marketing, but again remember if you started this exercise along with me almost however many 20-ish minutes ago and are taking notes, just remember this didn't happen as fast as we're doing it now. Like it did take, you know, since January to now, every day we've been building and working with our agents. So, we add new features, we add new functionality. Some days I just talk to the agent. I'm like, hey, what should I be doing today? Or what am I behind on? Or is there anybody I've forgotten to invite to SaaStr or are there customers that we forgot to follow up with? Did David remember to make that deal a closed one in Salesforce? Oh, he forgot. Hey, how about you just close the deal for him? He's busy. So, there's a lot of things you can do with your AI VP of marketing. And just remember, we hooked up a lot of stuff to it. So, the more you hook up, the better it will be, but don't expect that you will need to hook up everything overnight.

So, let's see how I... Oh, hold on. Here we go. Oh, it's cuz I left the window too long. So, let's see how our little buddy did. Okay, he's still percolating. So while he percolates... Okay, he's going. All right. I'll go back to the one that I already kind of pre-populated, but you'll see here like it's got like an email builder in here. It's got a Slack daily summary that it sends every day. It's top ideas. It's got some outreach and win-back campaign. So, again, yours will get better with time. And some things to remember as you are building your AI VP of marketing.

Is that we did what Jason and I call stairstepping. So, we only built out one agentic workflow at a time. I know you guys are taking notes and watching the session. You're like, 'Okay, I'm going to try this at home.' Don't try to hook up everything all at once. That would be my suggestion. That's kind of a lot. Also, it's kind of overwhelming if you fall into like a vibe coding doom loop a little bit where you're like, 'Oh, wait, what about this and what about that? And what if my agent did this and what if my agent did that in marketing?' Which is great and I think you should spec that all out with your agent and maybe write down ideas you have for future states of your agent. But again, at the end of the day, you want your AI VP of marketing to work first and foremost. So that's one of the most important things you could do is build out your agent workflows one by one. Again, our 10K started as a dashboard. He was not the dude that you see on the screen now. So another thing to remember is we use our built-in agent again as a co-pilot and a co-worker in the production environment. So basically what you see here where the agent is percolating our new agent, this is what I use to talk to 10K. So like I can talk to our live 10K here. I can just talk to him. This is the one that I built. You can also just talk to the agent and then give him things to do and tasks. And this is how you can build with the agent. So you can say whatever you want to do. So I made him wired. You can see I just wired him up two days ago. And then I said, I think I said somewhere in here, yeah, make it purple and name it HexiCorp. And then that was it. And so, that's literally all I did. So, even if you just take that spec that I built, maybe rewrite it, put it in, you'll get a pretty kind of basic, but you will get an agent that you can talk to. So, the goal would be that you get something like this where you can talk to this data and say, you know, okay, what are the three things we should run tomorrow? Like our 10K does. What is this campaign? Return on ad spend. You can hook up to your ads platforms. You can have it monitor spend for you. You can have it come up with, you know, agents are really good at ads because they have like endless ideas. Whereas I feel like as humans, if you want your ROAS to be really high, I mean, and some people will tell you you need to change it like every other day or so and change it like seven times over. And I'm like, how are you supposed to keep up with that? Well, your agent can do that. Your agent can come up with a plan for you of what should the copy be in the ads, what should the image be? Like I've literally given our 10K different images of SaaStr and I was like which one should be the ad and then we'll go test it and see which one works. So you can really use it as more of a co-pilot more than anything. So I think that's something important to again, it's super nuance but it's just something to learn where if you start to talk to the agent in this builder in the back end it will develop its own what I call personality or you can call it brain but it will develop its own personality to do it. So let me make sure he keeps going. Okay, there he goes. And then cool. All right, a couple other things to keep in mind about 10K.

Maybe you read this on saster.com, maybe not. So you can go to saster.com/is10k a VP of marketing. Where he answers this question for himself. He again he doesn't think he's replaced a VP of marketing but he has replaced about 60% of like a basic functionality. I think he's not giving himself enough credit here based on all the things I told you that he can just do slash does for us already. And again, the cost of building an agent, I think we said, is like 200 bucks a month or something crazy low like that versus obviously hiring a human would be way more than that. So, the thing is too, like I've said, like our agent runs truly as a co-pilot with us 24/7. When we tell it things, it doesn't forget it. I literally scheduled emails with it. I'm like, 'Hey, send that email at 5:01 tomorrow.' The only weird thing is the agents in UTC time, so I have to tell them the Pacific time equivalent, but other than that, we're golden. So, me and 10K get along really well. And here I asked our 10K agent, who is our AI VP of marketing to give me his top five takeaways for you all as you are rebuilding your own AI VP of marketing so that I wouldn't give you what I thought I should tell people and he would give you what he thought I should tell everyone. So number one, I've talked about it, but as you're writing and building a spec, pick one number. I think that's super good advice from 10K. Again, if you give it one goal and more data, the better it will be. So if you give it more data on day one, you know, again, our 10K was built as the first 10K attendees at SaaStr and the first 10 million of sponsorship revenue. We gave it a very clear goal and a very clear set of data so that it had the right parameters to then start to think for itself of okay can I use 10K as a dashboard? Sure I can use it as a dashboard but like oh there it goes. See, but you know again you'll see now so this is the one I just percolated whatever 15 minutes ago. This is the one I just percolated. You can see here it's got Acme. That's the default name here. But you can see you'll get things like a dashboard. Again, I think that's important. It's got social media analytics here. The more data you give it, the better it will be. It's already giving me ideas. So, I'm going to say generate ideas. Again, things like this that you can get out in just a few minutes here. So, it's saying I should optimize my paid ads. I mean, yeah, I was really behind on that. So, that's a good tip. Leverage your sales team's network. I mean that is a good campaign you could run with your agent almost in real time especially if you're hooked up to Salesforce. This is one of those things that I feel like your AEs will always tell you that they do like oh if you hire me I'll reach out to my whole network and my Rolodex and all my LinkedIn followers and then they don't do it. So maybe if your agent tells you and then you could just hook up your agent to their social media profiles. You can do it automatically. So that's one of those things that is a good call out. Or another thing you could do with your agent is go through all of your AE's LinkedIn networks. Say, 'Hey, go through their LinkedIn profiles, see who probably are the best lookalike customers for us that have the highest propensity to buy, get their data using something like a clay or whatever, and then start an outreach campaign that way or have them do it manually.' But again, there are some steps you can save there even on the sales side that this marketing AI agent just came up with. Email campaign to customers to upsell them. Again, that's a good one. Like many of you are probably in that boat where you have a lot of free customers and maybe you can't follow up with all of them because they're on free trials. An agent is a great way to follow up if you're using live product-led growth at all to keep following up with those customers and trying to convert them to paid customers versus you or your sales team having to do that yourself. So again, this we literally built this live and these are the ideas that I already came up with which again I don't think are bad. Like if you spend some time with your agent to make it even more nuanced and specific to you and unique to you, these ideas only get better, right? They compound because the thing is too, the agent sees all the data. So whenever you know one of the campaigns works that you guys came up with together, it will know that it worked and that you came up with it together. So it's a cool thing you can do. And cool to see that it worked live in the way I wanted it to. So that's fun.

All right. So then a couple last things and then I'll hit any questions. What are the last kind of two I guess three-ish takeaways from our 10K VP of marketing perspective? So yeah, pick a number. Again, that's I think one of the pitfalls of being able to vibe code and again I'm not like a technical person by any means that was able to do this is you know it will remember everything. So anything you correct it, anything where you're like I don't like that but do more of this it will do that instantaneously. Like there were a few times where in our email copy it would come up with it would say things weird and it would get like gross revenue mixed up with net revenue and I was like stop counting the Stripe revenue of the ticket fees as revenue because it's not actually revenue. But every time we did that and corrected it, it would remember all that. And so again, that's an important thing to remember with your agent is that it will remember everything for you. Yeah, and then I think this is a good takeaway as well. Building two layers. So we are very clear with our AI VP of marketing the things it should be doing autonomously and then the things it should still ask us permission for. So whether you call it human in the loop or orchestration or operator, we like our AI VP of marketing not to just instantaneously email the whole marketing database that would be a little bit scary for any of you for that to happen. And so we were very clear when we were building out our AI VP of marketing what it can start to do autonomously like pulling data, pulling dashboards, coming with campaign ideas like you just saw. That's all great to do autonomously. Some of the emails it does semi-autonomously. So some of the ones you just saw as like newsletters. Some of the ones you saw as like the website campaigns, it does that semi-autonomously. It'll send me like a test. It'll say, 'Hey, do you like it?' And then I'll say yes or no. And then it will send it. So I always have like a fail safe there to make sure that we can push the buttons and tell it to actually do the things without just, I don't want to say going crazy but just going a little zealously in marketing and trying to email the whole database on day one which sometimes when you know we've hired humans in the past they would get into our marketing database and you know what I'm going to do to boost the number I'm just going to email everybody. So it's a good in the same way you would tell a new human marketer on day one, you would have to tell your agent marketer on day one as well. So things to, and again it's a little bit of a mindset thing like anything you would tell a human marketer you should 100% tell your agents because agents are goal-oriented. So things like that where you're like hey don't email the whole database on day one. It's a good thing to tell your agent. If you're ever worried like you shouldn't worry about overloading your agent with too much data. It's got like the internet, so it's got one of the biggest brains on planet Earth and Claude and every and Replit and everything else hooked up into it. So, it will remember everything, but just remember that it will remember everything. And that sometimes you will need to rein it in probably more than anything else. So, that leads to 10K's number five top takeaway, which is guardrails. So, yeah. Guardrails is, you know, better than prompt engineering. I think sometimes I fuss with 10K too much and then he like won't load or he does something wrong or he does something weird or he comes up with weird... like I asked him to do a campaign to some of the VCs that I wanted to reinvite to SaaStr annual this year and it was like yeah here's how many like there's whatever 400 from last year that haven't come back this year and I said okay cool I'll do the email can you give me those names and it said oh hold on I made that up. So then I was like, 'How about you go look at the real data?' And they gave me the real data and I'll go email those folks. So it did that. But sometimes again, just make sure you, as weird as it is for some of you to be, like you do need to talk to your data, make sure you interact with it, and then read it, verify it. Like a lot of the times, you know, I think sometimes we see the outputs and we're like, 'Okay, that looks kind of good. Whatever.' Like hit send, fire it, go. Let's deploy. But sometimes, yeah, you do need to, you know, make sure because the agents are so fast, just double check everything. Especially the first few times you do things like I was extremely nervous the first time we sent an email directly from 10K. I was like, what email domain is it going to use? What is it going to reply to? What if it goes into a weird black box? What if it has too many images? And so I tested it a lot to make sure that everything would work. So I'll come out of full screen again real quick if I can. So here's our little co-pilot we built together. It wants me to publish it. I don't need to. I have my own. But hopefully this is helpful to see what you can do literally in the time that I've been yapping up here. That you can rebuild your own AI VP of marketing as well. And so with that, if you guys have any questions for me or 10K because I've got 10K up, we can ask 10K too. If you have any questions for me on the AI agent, AI 10K VP of marketing or maybe one of our other agents, you there's microphones out there and you can ask me or 10K your question.

Yeah. Thank you.

I don't know if you can see me from here.

I can hear you.

Hello.

Hello.

I'm wondering why you're using Replit. I've been trying to build an agent ever since I found out I can when I thank you for all the content by the way and I've been using Claude and it tells me nah you don't need Replit. So the stack is where I'm stuck. Yeah. Yeah, I just I've been and how to manage the data that you keep learning every day and like yourself, I'm not a technical person, but you have to be technical these days. So, I'm wondering about the stack and why you chose specific tools.

Yeah, it's a really good question. So, I actually use Replit a lot and I use co-work. I mean, you can see it down there in my browser tab that's exposed to everybody, but I use, I turned it off for this because they were like, 'Close all your tabs.' But usually co-work is always on. One, at least one or two of my Replit agents is always on. I think the thing about the agents is they're going to say what's better for them, right? So, of course, Claude is going to tell you that you don't need Replit. It's going to say use co-work. It's going to say, you know, use cloud code. It's going to say I have all those functions and features. Why do you need a new agent to do that? And so, that's just one like any agent is going to tell you that. And so it's one of those things where it actually does come down to like personal preference and nuance where like I like to bounce back and forth like cost aside right like I like to use both in tandem. The when I wrote the spec for this session like it output what it did in Replit I was like hey I said hey 10K describe yourself so that our audience at annual can make their own AI VP of marketing but then I took that and I honestly put it into Claude and then I put it on the website. Like there's just I just I think it's better to like, you know, bounce ideas off of each agent. It's kind of like having two people on a team, right? It's like, okay, see what one says. I like to take some ideas from some, put it into another. Co-work is good, I think, for like simpler things that I like to do, right? Like I just have like when I was setting up the Salesforce custom object, I was like, I don't know. I don't know how to do that. And like the built-in agent gave me the built-in instructions for Replit which I did but then it kept like expiring the token in all honesty. So then I was like okay I asked Claude I was like hey my Replit thing keeps expiring to Salesforce literally every day like how can I make sure that it sticks and that it remembers my Salesforce OAuth so that this doesn't keep happening and co-work instantly was like just make a Salesforce connected app and I did that once and it literally solved all the issues. So like I like to just put two agents together but beyond that like do you need more than two or three like to your point it does get hard to manage the agent stack because you have so much running through it. So, not to say that you can't just stay on co-work and like stick with Claude and like make it work, but I think because our agents specifically in how we use Replit, which is super niche and nuanced, right? Like as I said at the start of this, like because it has its own brain, it actually will remember a lot more things than Claude. So, I actually have a version of 10K on my Claude co-work that like Jason and David don't have, but it's not as good. Like, it doesn't remember as much stuff. He has other goals and then he'll start to like remember context from other conversations I had with Claude, you know, that's just Claude for you. Like he remembers too many things. And so the reason why I use both kind of like in tandem and parallel is because this one will remember everything specific to him and he kind of has like a brain and personality now that's 10K. Whereas like the 10K I had in Claude, honestly, it just got too long at one point too. Like I had it going for a couple months. I was like, 'Hey, give me marketing ideas. Give me campaign ideas.' and it was like too long, too long, too long. And then I had to start a new 10K in co-work before they like upgraded or whatever. So I still use it a lot and like there are things I spot check with it, but Replit just seemed to have better memory and so that's why I switched.

Just to confirm, you're talking to Replit when you talk to your agent, correct?

I'm talking to Replit. Yeah.

Thank you.

Thank you.

Thanks for the great presentation. I have a question specifically around the content. Yeah. The newsletters, the emails. I read a lot of your content. Amazing. I didn't capture here. Are you human in the loop writing these still or is this generating based on an MD file or are you training the content to look great, read well and automate it because it's something that I think we're all trying to solve for.

Yeah. So, we do both, right? So, like there's a lot of content that Jason still writes himself like even today. Like you'll see like sometimes he'll like grab the data with co-work like I'll see him kind of like co-writing with his like he has a version on his co-work that is like the SaaStr annual kind of like content or SaaStr builder like content builder with him. But like when I've done that to my it's not the same output you know what I mean like when I try and do it. So I'm like that's one of those things that you could do in something like a Replit where like if somebody has gotten something kind of specked out in their own Claude and you need other, that's another thing about Claude is like if you need other people to access it it's honestly easier to do it when you go to production if you don't if you want some people to use the internal agent cool. If you want some people to use the production site cool but that's another thing where it's kind of handy to trade off on. But yeah that is one of those things where we still write a lot of that content manually. Like that is one of those things.

Yeah. So you haven't solved the automation, marketing, content generation.

Not for I mean not for things like that, right? Where we're talking about our like this content other than asking 10K like what it should tell you guys. Like I built those slides sitting over there while they were building booths here. Like there's nothing on planet Earth today that will replace that. So yeah, whether you call it human in the loop or not, like we probably downplay too much how much time we spend on our agents, but yeah, we spend a lot of time on it.

Okay. Thank you. Thank you.

Thank you.

Thanks, Amelia. Hello. You and Jason have both talked about drift and so I'm curious to know now that you've run 10K for a while, how you're what you're monitoring as far as Drift and how you do you ever go back and update the spec? And then one really dumb question is, can you show the Replit code again for the credits?

Yeah, I think it's Replit SaaStr. Okay, so you got it. They're also doing vibe coding classes out there, too. The whole week. But yeah, so when it comes to drift again, it's one of those things where like we've built in so much functionality to 10K. I honestly will look for drift when we push new updates in. So, like if Jason, Jason actually built the email builder that you guys saw me show, he was like, 'You're getting busy leading up to SaaStr. Why are you writing these emails yourself? We could just build a builder so it's more consistent. You don't have to think about it when you're really tired.' And actually, it was a great gift. So, yeah, it's one of those things where I don't look for drift more so in like the content or the goal because he always knows his goal. It's more so I look if he gets too far off the playing field of like okay because Jason added that newsletter builder I'm like is he starting to like is 10K starting to think about other things he wants to build into the platform where I don't want him to build that like I just want him to focus on the things he already has and so that's where I really look for drift and then like I said you with like a human that you're managing you do have to manage your agents on whatever their outputs are right so it's very similar of how I treat it of any email that it writes of course I'm going to read it before I just hit send, right? So, I have that approval. You can just ask your agent directly like, 'Hey, before you send the first email, make sure you send me a copy. Make sure and then I click all I still click all the links because sometimes when I'm doing email marketing in particular, for some reason the agent sometimes in like the newsletters, it would make up the link and I was like, 'But you have the right one.' And it'd be like, 'Oh, yeah, I have the right one.' And then it would put the right one in there. So small again small seemingly small things like that but things you should just look out for are things that you would look out for with a person or yourself anyway like when I write the emails I have to check all my links anyway too and so same same with the agent.

And do you ever go back to update the spec is there any value in that because you said 10K's evolved a lot for you all.

Yeah, I personally don't. I think Jason probably has. I think there's value in it. If you want to make other 10Ks, right? So like if your marketing is a lot bigger than SaaStr's, then you may say, 'Hey, I've got a 10K that is just for email marketing. I've got a 10K that's just for social. I got a 10K that's just for ads.' And I do recommend you do that because again, the more unique you can make them, the better their brain will be on just that one thing it's trying to do. And so that's one of those things where like if you ever try to like split it and clone it, then yeah, there's value to updating the MD and having it up to date. But also if it, you know, Replit has really good roll back. We've rolled back a couple times where we've needed to, but I think it's good to still, you know, save a copy every now and then. I still do that just in case.

Thank you.

Thank you.

Uh, thanks Amelia. Great presentation. Very practical.

Thank you.

Um, I'm really curious about how you orchestrate between co-work and Replit. Just for context, like we do a lot of stuff in co-work and we have individual like skills created. So, I'm wondering your 10K in Claude. Is it just a skill MD file or is it...

It's not. It's just a chat. It's a very long chat that I'm having.

Okay. So, most of your stuff is done on Replit then.

Yeah, most of our stuff is done on Replit. I still have my parallel kind of 10K Claude version where sometimes I'm like, 'Hey, I'm making an email outside of Replit.' Like, I'm just doing a quick email thing that I came up with, not 10K. And I'm going to put it into our marketing. I'm like, I'm going to do the like heavy lifting and the backend part of the marketing campaign. Where I just ask our Claude 10K to do it because it's like a little bit faster to do it.

Got it. Thanks.

Thanks, guys.

Okay, with that I had like 20 seconds left. So hopefully this was helpful. Again, you can go to sasterannual.com/resources that will have all like the specs and things that I made for this. And then again, hopefully you guys can duplicate it. If you get stuck, I volunteer the Replit team as tribute because I will be here all week. So if you get stuck, you can go ask them for help. I'm sure they'll help you out so that you can get your own version of the agent going. But thanks guys for coming to this and thanks for coming to SaaStr.

Our revenue like 100x-ed over one year. I built my first business when I was 13, 14.

Thanks for coming. We'll let folks stream in for a minute, but if you've been to a bunch of sessions today, we're going to have some fun. Can you guys bring up the slides, please? Thank you. So most of this all as you guys know is built on Replit. So thank you for building this platform. It has been quite a journey. So much has changed. If you guys have been through this half day to kick off, I did this 101 on the first agent we ever built 14 months ago on Deli. Amelia talked about building your own 10K on Replit. And now I want to take advantage of Amjad who co-founded Replit back in 2016. AI was a twinkle in your eye back then, right? Yes. Was it even a twinkle in your eye in 2016?

Yeah. Yeah. So if we have time we'll go back to the beginning getting Replit started but I want to talk about the present. I want to talk and I want there aren't that many better futurists than Amjad but I don't want to talk about 2028. I want to talk about the agents we built on Replit and maybe a little bit into the future because I want to...

Yeah. Yeah, it is. We're living in the future and I think if people, it's a good point if people take anything out of it is that if you want you can live in the future too.

Yeah. That are actually employee-like and actually and I've heard you're going to have someone reporting to them pretty soon.

But everyone talks about agents. The only agents that work are software agents, marketing agents, sales agents, all that haven't really worked very well. And so 10K is an example of something that works.

That's rare.

So I want to, there's a bunch of stuff I want to chat with you, but first I want to get some of your reactions as one of the creators to all of this to a few things. So just a reminder, I know you know a little bit of we built two. Well, we've actually built a third you haven't heard about. So 10K was the first one. Becoming autonomous marketing, QB's customer success handled everyone out there better than a human. I want to show you. And then we have a third one. I know you're not going to like this. That manifested itself that created itself on Replit which I'll show you. Holy... Um so but I want to get your, we've talked a lot about this but I want to get your perspective and go deep. So first cheat code I want is that the beauty to it is it knows us cold. Amelia I think touched on this prior session but literally every piece of data you can find, some of it is pushed into the Replit database into Neon or whatever it is. A lot of it is pulled in real time out of APIs, Salesforce, niche apps you've never heard of like Bisbo and Marketo and others. But the amount of data the agent can access and process is more than any human.

Yeah.

Right.

Yeah, it's a massive difference.

And I want to show you why this chart's sort of interesting, but...

It's a million. Help me understand. I just want to get a little nerdy for a second.

When I'm running the agent in Replit, not refreshing it, which is my passion. Never reached in the old days when we started in Replit, you rebooted the agent three times a day. Now Amelia and my goal is never to refresh.

How long can that context window last at a practical level? Forever? And where's it going?

Are there two? Are they both running or only you're only running? You're not using any compaction from Claude? It's just Replit compaction?

Now you said, okay, let me get your insight. You said sometimes with the long context window, the agent will make more mistakes because it has more bugs. But let me give you, we haven't really talked about it much. If you go to saster.ai, we probably have 10 apps running in one codebase and one URL. We have a website. We have a fun tool to help you value your startups. Maybe folks have used it, been used over a million times, which is crazy. We have an AI that grades startup pitch decks 4,500 times. We now have one that grades how agent-friendly APIs are. All these different apps. When I go to build a new one, it remembers. It's like, 'Oh, we did that with the pitch deck grader. It didn't work that well. Let me do this new app a different way.' Maybe it gets confused on bugs. But the power of the agent remembering how it built other apps to build a new one, I find it kind of amazing.

I see.

Yes, a bit. Like the idea, I mean, the other day I was talking to a company fully bootstrapped, started on Replit, five, six people now, started with a couple people but they've grown and they have everything laid out on a canvas on Replit. They have their mobile app, their web app, their backend, their admin, their back office, their automations. I'm like, man, I wish I could run Replit like that, you know, because you can see everything in one place. And now with the new collaboration primitives that we have where you can start new tasks, new threads and so people can work simultaneously on the same projects. I think this idea of monorepo will become more and more important. You want the agent to have access to global context as much as possible. Not necessarily all in the context window at any given moment, but it will know, it will have enough pointers that it will know to go search the files and bring in the right context at the right time. So I recommend everyone here whether you're using Replit or not really think about providing these monorepos with all the information you want. We have a data agent at Replit built on Replit but because data at Replit is so big right now, we have terabytes of data across BigQuery and Databricks and all the other things and all the schemas are different. And so we created this repo that has all the information, all the fields and everything the agent learned about our data. Because you know there's a problem now when we talked about it earlier where agents can write bad queries that end up costing you millions of dollars in BigQuery or Databricks or Salesforce backend cost. So it's important especially when it comes to data to write out the information, have the agent continuously learn how to better query the database. Yeah, maybe just to summarize at a very lay level, the monorepo, if you're building on something like Replit, maybe it's a hack today, maybe it won't be a hack later in the year. The more you put in a single app, the more power you're going to get rather than breaking it up. It's very tempting to break things up into 20 apps, right? But I found and there are powers to it because in some ways you get the benefit of a clean database, separate, clean database, even a new Clerk instance. But you lose, but there's so much power. If you guys, Amelia talked about building 10K and we have 10K and QB, we'll chat about before we end. Our AIP customers, they're different. It'd be great in some ways if they were the same app, right? They communicate through APIs, yeah.

Yeah, they can't quite do it right. But just on this and maybe we can move on, but this is all of our social media numbers. 1.27 million social media followers for SaaStr. I can see it all over time. This is all built, 10K built this for me. We used to have an admin who spent 10 to 15 hours a week building this.

And she would go to, because a lot of these aren't even exposed APIs. She would manually put it in a Google sheet, collect it, forget to do it. Now 10K can do all of it between scraping and APIs and then I can talk to this data. It's a massive amount of data it's collecting. This isn't even all people that are here, 10 years of attendees. This is just social media data that was unable to be acted upon until it was inside of an agent and inside of an application.

Is that the rough numbers? Like an order of magnitude less headcount.

Yeah. Yes. But this one and then this person just quit after five years. She couldn't stand doing these Google sheets of how many Twitter followers I had after 5 years. It was that, you know, the agents don't mind numbing work, right? I mean, that's what doesn't get discussed in the job displacement discussion is that there's a lot of jobs that suck that agents are just better at.

Yeah. 10K is an application and it has a chat window and it can be accessed on the web, but we run it almost full-time in Replit and have the Replit agent talk to the app, right? It's smarter. And I asked 10K like you might a VP of marketing, are you sure all the VCs that came to SaaStr last year? Are you sure this is all the VCs that came last year that aren't coming this year for an email campaign? Sounds light. Fair concern. I screwed up. I missed some titles. I found 137 VCs that came before I forgot to invite. Right. Pretty interesting that. And is this weird us using the Replit agent to talk to because we're staying in dev mode?

This doesn't work in production, does it? Unless I'm missing something. Replit doesn't think it works in production. I don't think it works in. So, we're hacking the Replit. I know. I know I'm not supposed to personify it. I know it's an editor now, but we talk to the Replit agent to make the application work better.

Yes.

Okay so let me show you what happened next. So I talked to the agent. He said, 'You're right. I'm wrong. We forgot to invite these 137 VCs here.' And then here's something I don't really understand, Amjad. So, we've been playing with 10K for months and we have it draft emails. Okay. And it's using the application that we built and it's using some Claude and using whatever it is and the emails were okay. Yeah. Okay. That it drafted. Then I said, this is literally last week because everything's getting better, but I don't always know why. Then I said, 'Okay, draft me an email to these 137 VCs.' And it drafted one that one of your investors. Okay. And I was like, to Bloomberg Beta, I think they're one of your seed investors. And I said, write James isn't coming back. Write him an email. This is, I just said like you would say to a human, why the hell isn't James here this year? You know, he's been part of SaaStr. Why isn't he? Look at this email he wrote. It's next week. Not pitching you. Replit's here in serious for now. Think about the data pool. Here are 25 people coming from Replit. I'm Michelle. Why? Look at how good this email is. All these people, then everyone else, the competitors, the adjacent folks, they're all here. Think about what a crappy SDR AI email was 12 months ago. I mean, this is so good.

I mean, maybe it's a little hard for you to see. And how is it so good? This, if you did this like a couple months ago, it wouldn't have...

I'm not even talking about December and Agent 4 or 5. I'm literally saying, when I show this to Amelia, I did this last week.

Like what is this? May 8th, my jaw dropped because I'd never seen an email this good.

Right. Look, I think... and I got a lot of feedback from folks that got different versions of the email. I think that's the best one I've ever seen. But why? What changed? Or is it just getting better at because it's just pulling data, right? But this is such a good email. Why is it so good? No human could write an email. No human would even have the patience to pull every single person of Replit is here. Scan 8,000 registrants, figure out who they are, who's like them, create like... how? What happened two weeks ago. Amjad, what is 10K's AI? Is it OpenAI? Is it what is running 10K's AI? Not the Replit.

Okay.

But this was also the agent in the Replit agent working with 10K to craft this email. So you're using whatever is in Replit too, right?

It used to be 5.4 like a couple weeks ago.