In short
Summary of Podcast Episode: SaaStr 822
Overview In this episode of the Official SaaStr Podcast, SaaStr CEO Jason Lemkin and Chief AI Officer Amelia Lerutte explore the integration of AI agents in SaaStr's operations. The discussion outlines their journey from using no AI to incorporating over 20 AI agents, including 11 core ones, to enhance their operational capabilities.
Key Themes
AI Integration Journey
- Start Point: The year began with no AI, apart from basic tools like ChatGPT.
- Implementation: SaaStr now employs 20 different AI agents, with a focus on six core agents that are pivotal to their daily operations.
- Rapid Growth: The team has transitioned from zero to 20 AI agents in less than a year, highlighting a significant shift in operational strategy.
Core AI Agents Utilized
- Artisan: Used for outbound sales, capable of sending hyper-personalized emails.
- Qualified: Employed for inbound queries and managing sponsorship inquiries.
- Delphi: A general-purpose AI that handles various requests but is less specialized than other agents.
- Gamma: A tool for creating dynamic sales collateral.
- Momentum and Attention: AI tools focused on RevOps.
AI Training and Management
- Active Management: Both Jason and Amelia emphasize the necessity of ongoing training and management of AI agents, indicating that success requires continuous oversight.
- Employee Involvement: Initial testing of AI messages is done manually to ensure quality before full automation is implemented.
Use Cases for AI
- Sales Development: AI is employed to handle warm outbound efforts, personalize outreach, and manage leads.
- Example: Over 15,000 messages were sent by the AI in just 100 days.
- Customer Support: AI helps answer FAQs and manage inbound inquiries, improving response times significantly.
- Content Review and Evaluation: Custom-built AI tools help review speaker applications and startup valuation calculations.
Key Takeaways
- No Set and Forget: AI systems require dedication and training to be effective. Automated systems will fail without regular input and monitoring.
- Vendor Selection: Choosing AI tools should depend on their alignment with company needs and the vendor’s capability to provide support during onboarding.
- Hyper-Personalization: Sales strategies that focus on customer value and personalization yield better results.
Conclusion The episode emphasizes the transformative impact of AI on SaaStr's operations, showcasing practical strategies for other SaaS companies interested in leveraging AI. Jason and Amelia advocate for a hands-on approach to integrating AI, emphasizing the importance of continuous improvement and training in maximizing the potential of AI agents.
Recommendations for Bringing AI into Business
- Start with a versatile general-purpose AI tool and gradually transition to more specialized applications.
- Ensure that internal teams are committed to ongoing training of AI systems.
- Leverage AI for customer interactions to improve engagement and response times.
Future Events
- SaaStr AI London: A significant gathering of leaders and founders to discuss practical advice on using AI for business growth.
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This detailed summary captures the essence of the podcast episode, outlining key themes, insights, and recommendations discussed by the hosts.
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Transcript
Automatic transcript. May contain errors.0:01Welcome to the official Sastr podcast where you can hear some of the best Sastr speakers. This is where the cloud meets. Up today on the Saster Podcast. The other thing we've learned is you can't have a crappy sales team because we need the help. And I can tell you there's at least two leading vendors that we said no to, not because the software is not good enough, but because the sales team fought us. They didn't know the product. And this is always true in the old days. But when you're talking about an app with training and deployment in a new category and the rep fights you, no. I want to know how I'm going to get this deployed.
0:36And so just if this is you, listen to the sales calls, get momentum or attention hooked up, be relentless and just get rid of anybody that is not an asset to your prospects because they'll just leave for AI. They'll just leave. If they can't help you, can't answer the questions wrong or fight with you.
0:57Hey, everybody at Saster. FIN is the number one AI agent for resolving complex queries like refunds, transaction disputes, and technical troubleshooting, all with speed and reliability. See how FIN can deliver the highest resolution rates and highest quality customer experience at fin.ai.saster. That's fin.ai.saster. Hey, everybody. If you're serious about B2B and AI, if you want to know how to deploy AI SDRs, how to get AI to qualify leads to your site, how to use AI to manage your rev ops, how to use AI in GDM, you have to be in London this December 2nd and 3rd with us. Saster AI London is bringing together more than 2 ,000 leaders and founders for two days of practical advice on scaling with AI into the new year.
1:47That's all we're doing this year. how to use AI to grow faster and how to make this stuff actually work at your startup and your company. We'll have speakers flying in from around the world from OpenAI, Wiz, Clay, Intercom, all your favorite B2B companies, including yours truly and Harry Stebbings for a live 20 BC and Sastra podcast. It'll be fun all right in the heart of Sastra London with me and the entire Sastra team. You gotta be there. So get your tickets with my exclusive discount by going to podcast.sastralondon.com. That's podcast.sasterlondon.com. See you there.
2:26So welcome, everybody. We're going to do something that a lot of folks have asked for, which is a bit of a deep dive on what we're doing, how we're using AI at Saster. We've chatted a lot about it. We've got, as Amelia will show you, we've got about 11 core agents we use and about 20 total. But we're going to do a deep dive into like the six that we use the most and the six that are probably most interesting to you guys, core AI agents that we use every day, how they work and show you, show you the actual data. I can give you a little bit of an overview, but then Amelia can dive in on, on most of them.
3:01And then I'll help most of them we've bought and we'll show you who we've bought or what commercial apps we use, which is our recommendation. And then we've actually built some ourselves on Replit. And we can dive into that. The biggest takeaway I can tell you, I don't know if we put it in this deck. The biggest takeaway is there's a lot of vendors there. But on two of the ones we use, Artisan for outbound and qualified for inbound, of all their customers, this is the most important thing. We're the number one vendor. Number one results. Amelia will show you that. But the most important thing is going really, really deep with AI agents.
3:34There's no set and forget, no matter what anybody tells you in 2025, maybe in 2026. But there's no set and forget. This is our little journey. And hopefully you'll be on the same journey, just time shifted. But we came into the beginning of this year basically using no AI at Sastr other than ChatGPT and Claude. I could be wrong, using nothing. And the first thing we adopted, which some of you guys have seen, is we use an app called Delphi to do an AI agent on Sastr. We've done over a hundred thousand conversations. At first, we just used that, right? Going into Saster Annual this year. And we used it for everything.
4:12We used it for a little bit of sales, a little bit of marketing, a little bit of support. It's really just designed and we'll go over it to be a digital mind, a digital version of me. But what we quickly instantly saw was just having it was so much better than nothing. It was so much better than nothing. A general well-trained tool is better than nothing. Then we started adding marketing tools. We added Gamma and Higgs field we'll talk about. And then we added our GTM tools like Artisan and Qualified and Momentum and others, and we'll dig into it. And ultimately, the journey we're on, we've gone from zero agents at the end of the year to about 20 today and nine core ones.
4:50This should be you. And if you haven't started, it's okay, but it won't be okay soon. But you can do it. And as you see, our adoption has just skyrocketed. And frankly, as we've lost agencies or resources on our tiny internal team, we've done what everyone on the internet says, which is replace them with AI. And it's not without challenges. It's a higher load on me and Amelia because we have to manage these agents. We don't have, I mean, Amelia's title has changed to SVP and GM to cheap AI officer. It's not a joke because that's probably what she spends 30 % of her time on is managing these agents.
5:22It's not free from a soft cost perspective, but it's radically different. So we'll go through what we've done. we can go through the next ones just briefly and then dig in. Here's just one for fun for guys. I just did the one of our timeline, nothing to 20 in nine months. This is a night and day. We have a SAS University where I built a bunch of courses. They're free if you want to try them, sasuniversity.com. They're still good. I'm redoing them in the AI age, but I went to ask a question about it, a reply in a day. and I went around a lot of websites and a lot of them are terrible in terms of AI interaction.
6:06And again, on the right is our Delphi agent, the first one. It's not specialized. It is not specialized for sales. We've taken it off for sales and tickets and sponsors that we'll show you. We've put it in the buckets and the parts of Sastra that are general. But man, waiting a day to get my question versus here, I just asked him five minutes ago, when is Sastra annual? Who are the sponsors. It just tells you everything. There's no excuse to not have extremely high quality customer interactions instantly through AI in 2025. There's just no excuse. And we'll go through our, we'll go through our stack there.
6:36So just for fun, if this is anywhere in your product, just company, just like end it this week, just start. And maybe the next one, and then I'll let Amelia drive. We do have, depending on you count about 20 agents, We'll go through it. You know, our organization is tiny, but, you know, Sasser does do eight figures in revenue with a tiny team. So it's interesting to track us because we have a single digit amount of headcount doing eight figures of revenue. That's fairly extreme. It's not unique to us, but it means we really push the model here. But pretty much every single thing you can do with an agent we are doing.
7:16Roughly, you could kind of see it on the slide before. Roughly, we try to try something new about every two weeks. Would you say that's right, Amelia? Yeah. Yeah, we're talking about, we try to come up with a new agent idea each week and try one every two weeks. And then one and a half per month is about all our org can tolerate because it's just too much process change even today. But this is kind of the stack we've built up. We do have a lot of AI apps, but a lot of folks ask what our stack is. And this may be different in 90 days. It probably will be because Amelia did a version of this 45 days ago or something.
7:54In July. In July, our agent had already done 8 ,000 customer interactions. The stack's already somewhat different and it may be different later, but we'll go through it. We use an app called Artisan. We actually use three instances of it for AISDR. Amelia will show you. We just rolled out Qualified as BDR on our website to manage inbound, and it's already had a pretty strong impact. We've used Gamma almost since inception to automate sales collateral so that it's all dynamic, so that it's not the same old frigging deck that gets out of date and is embarrassing. We love it. We talked about Delphi as a general tool.
8:29We've added AI RevOps. I've blogged and talked about it. We've added both momentum and attention. They're both great. Amelia will show you why. And then we've built some stuff ourselves, and we'll briefly touch on it. We could do a different session. If you've followed me on Twitter, probably seen a lot about our journey with Replit, but now we're sending some bumps in the beginning. It's been pretty successful, and we've rolled out about five apps ourselves. The main learning is only do this if you can't buy it from 99 % of you. Like, it's cool, but we did this for content review and other things, and we'll show you where there is no off-the-shelf app.
9:03But don't roll your own. Buy, don't build, right? Use for B2B stuff. There's a lot of cool things you can vibe with Replit and Lovable and others. try it. We can do a whole nother session on it in the coming weeks. But if you can buy something that's bulletproof, don't build it. Don't believe the hype. But most important, none of these names are as important as putting in the reps and the work. And Amelia will show you the actual date in a second. These are all great apps. We stand behind them. We recommend them for sure. But you could pick another two. The most important thing is training them deeply and doing it every day.
9:40So many of the AI failures from late 2024 into early 2025 that you'll see all over social media are just folks that bought something and never trained it. Or they bought something and hired a mediocre agency that did nothing. You've got to train these. And you've got to do it every day. And not only does it take weeks. And Amelia, when you touch on some of these, you can talk about our training. We're pretty good at it because we're tiny. Everything is weeks of training, ingestion and training. And then every single day we're in these apps, monitoring the outputs, monitoring the interactions, monitoring the discussions and fixing things that are as often as wrong.
10:15And if you don't commit to that, you're going to have extremely mediocre outputs, just like any, frankly, just like any other tool you buy. If you don't put in the effort, you're not going to get much out of it. So many of the failures for AI agents, if you really peel back the layer of the onion, just someone on the team did it and there was no proper training or there was no data to ingest a combination of two. So that's far more important than which vendor to use, but we'll show you what we use. And maybe with that, Anil, you could transition into SDR and BDR. Okay. The first one we'll go through is our AI SDR.
10:49So for all and his purposes, what it does is we use it as warm outbound. We did a full deep dive on how to do AI specifically and use agents for sales, like Jason said in July. That one is still very relevant, though. So if you haven't watched that full one, that is a full-on deep dive. So we'll touch on a few most recent learnings, just because now we've had it fully deployed for 100 days or so. So how we've used it in our use cases, we use it as a warm outbound agent. So I have trained it on three different use cases, which you'll see here, which I'll walk you guys through, to do outbound in different ways.
11:27So the way that this is helpful or why you might think about using an ARS ER agent with some of our data is because it can do hyper-personalized emails and scale. So in the last 100 days, it's done about 15 ,000 messages. I've put a screenshot on the right of one that it's sent out to a prospect here to buy tickets. So this is from our direct ticket sales agent specifically. And you can see it's pretty good, right? It's talking about what they do. And this is part of the training we did with the AI agent is a lot of how we started up initially between ourselves and Artisan was to say we want every email to try and add value to whatever audience it is.
12:07So if it's our sponsorship agent, if it's our direct ticket sales agent or a VIP, it also looks at what they're doing on the website. It looks at what they're doing personally. And we've basically set the slider like all the way up on, you know, customize more on them versus on Zaster. So this is part of the hack of like, we try and make it as much about them and less about us as possible. When I've talked to other folks who have an AISDR, they have similar use cases that they're seeing success. The more you can make it about them and adding value to them, the better results you're going to see.
12:43And Amelia, how do we, I should know this, for both sponsors and attendees, how do we pull in historical data? Do we pull it in from Salesforce and Marketo? And how does that integrate with outbound messaging? Yeah, great question. So there's a couple of ways you can do it. You can pull in from automatic signals. So you can do like a search of, hey, who's talking about SaaS or who's interacting with SaaS or your company? How we've done or how I've done it is I do a direct pull from either Marketo or Salesforce. I'll combine it manually. So on the backend, that does take some time. and then you can do a straight up upload to artisan.
13:23So the most successful campaigns we've had are the ones that have been straight up uploads of our data. And then what it will do from there, it does take some time. So this is an interesting part too. Like the first time you set up anything like an artisan, so any AISDR, they're all going to tell you it needs two to three weeks to warm up. That's common. So keep that in mind. I don't know if we touched on that last time, but they all need time to warm up. And basically, they all need that time to warm up your mailboxes. So all of these are going to use... You don't want it to use your private email.
13:55You don't want it to use AmeliaSafster.com. You want it to use AmeliaGetSafster, AmeliaTriSafster.com. So every AISDR platform I talk to needs this two-week warm-up. So that's part of it. It's going to spend time just warming up those domains and mailboxes for you. Then if you do something like a CSV upload, as we've done numerous times, And it will take another day or two to ingest all those contacts. So again, if you're starting from scratch, this is already probably like week three in the jury. To do that, because it's going to take time to basically find those people and use all the data signals I've uploaded to make sure it identifies the right person.
14:35So it's going to find their LinkedIn. It's going to look at their email. It's going to check the deliverability of your email. It's going to look at their company signals. So it'll start to generate those messages. You can read through the messages, make sure it's the right person. make sure it's the right thing you want to say, and then you can automate the send from there. Just two questions, one tactical one on the data. So it cues them up before it sends in the beginning, what percent and how many messages did you read manually before you let the AI do it, mostly automated? In the beginning, I read all the messages.
15:08So it was, you know, hundreds and then thousands. Like, I wouldn't start with a huge list the first time you do this. I think I started with a list of like 600, that's a good mix because it's not going to find everyone. The match rate is fairly high, but it's not going to find everyone. So by the time it does that and identifies the right people, yeah, I did about 600. And then in the beginning, I would read because you can set the agent to say how many messages do I want to do? So for us, historically, we always knew like if we wanted to email somebody to come to Saster, an email from me or a human SDR would take about three actual human touches.
15:45And so we duplicated that in Artisan and said, okay, three touches in email and then one LinkedIn message to the person. And so your outbox would then have four messages per person. So 600 times four, you're looking at 1 ,200 messages. I would read all of them in the early days. Now I just spot check. You probably read the first thousand emails yourself, but now every day you're still spot checking for 20 or 30 minutes per day probably, right? Exactly. Yeah, I spot checked 20, 30 minutes today of what it's going out. And then I also spend probably more time now on the replies of like, how are people replying to our artisan emails?
16:22Is this what we want? How do we want to respond to them? That piece is a bit more manual. Now you can turn it on. So it's like automated in responses, but I still like the human responses. I feel like there is still a bit better. One last question. I don't want to spend all of our time on artisan, but this is helpful. So we've had probably 50 ,000 people over a decade come to our Sastra events in one form or another, and we have hundreds of LAP sponsors, right? Maybe 150. And that gets added to the text of the AISDR. Are you manually creating XLS files and manually uploading to Artisan? And how does that whole workflow use for LAPs to reactivation so that the email comes out great out of that process?
17:09I will actually show you guys the backend for one second. I think it'll be helpful. Okay. So you can see here is some of what I'm talking about, right? Like how many messages it's already sent in September, right? So again, I didn't read all thousand. In the early days, I would have read all thousand, whatever. Now I'm just spot checking. Honestly, mostly because sometimes we, because we don't have speakers for London, sometimes it will like pull speakers or speakers for manual. So I'm mostly checking that it didn't like hallucinate any speakers for London. But again, part of that is human error.
17:42Like I just haven't trained the AI yet on our current speakers for London because we haven't publicly announced them. It's got 207 messages in the queue. And then yeah, to your question here of like the inbox and the outbox, I spend most of my time now in the inbox. So this is where I can see who's engaged with us. I can see what it's sent. You can see if it's LinkedIn or email. So you can see I've stored some of these. These are ones I want to go back to. And then you can go to the pending messages here. This will be all of our scheduled messages at the moment. So right now there's 200 in this at any given time.
18:18But then to your question of how this works with reaching out to lapsed or churned customers and making sure. So you've got 200 folks that have responded to RAI that have a question. We've got more. So it's a pretty high risk just for folks. That's a pretty high response rate. yeah i mean i do think we have a response right here total it's a pretty high right so like this one's seven percent that one's high five percent you know jasper and arson who's the ceo has said like averages like two to four so if you do this well and the seven percent is you're trying to get folks to come back to saster that's probably who this batch is right correct yeah but if the emails actually you know people saying that email dead or stuff, if it's actually good, if it's adding value, helping them, 7.14 % is pretty good for an AI.
19:12Pretty good. Yeah. Pretty good, right? Pretty good. Yeah. And again, this is still in addition to the marketing emails we do. So it's not that we've stopped the marketing emails that come from Marquero and are fully designed and are still inviting you back to SaaS. We still do those too. It's just that you're getting those maybe two or three times a month. And then now you're also getting a sequence where you're getting a highly personalized invite from me also to london so it does help reinforce the fact as well yeah cool and then yeah to your point of like how do we make sure it's the right person that's where i go into the inbox right and you can check the messages of what it's sending making sure it's the right person you can change it at any point if you're like okay i want to say something specific to this person because i actually know them and i've worked with them a little bit more you can customize it and then the other thing you can do is you can upload a do not send list.
20:05So how we've used it is once we do have people who sign on. So if you want to drive new customers through this, once you get that new customer, so you can upload them to a list and say, stop emailing that entire company. But it can't today. And then maybe we can move on. It can't. So it doesn't sound like today it auto ingests our Salesforce or Marketo or other data in the same way that like Delphi auto-ingests our website, right? Not today. It takes training. So I'll go into one of our campaigns here. I'll pick you. Just pick this attendee one. So this is our ticket agent, right? And this is the one that sells more directly because again, I've empowered the AI to do more responses than I have for our sponsorships.
20:47This is pretty easy, right? If you say you want to come back to Saster, the AI gives you a code. You don't really need me for that. It's fairly low overhead low risk, right? The ACV on a ticket to London is like 300 bucks. So I've let it go a little bit more hog on this than others. But yeah, you can say, here's the lead. You can see I did a CSV. You can see it's already done 400 out of 800. Don't contact people. Much like a Mercado or a Salesforce or a Sales Loft, you can say, if they're in other sequences or campaigns, don't contact then like we only want to do one the pitch is where you can tune it right so this is where i spend a lot of time saying okay this is the offering here are the pain points this is where i put in like the speakers and you can just keep adding to this so it won't do it automatically today i do know gasper from artisan says that's coming by end of year but right now you just put it in yourself you know pick the best pain points improve points i continuously update this you know use saster london and the subject line people know saster so it's good to put the brand into the beginning break it up you know i've put in different things here as we've kind of got along be excited that this yeah the and doesn't even vote to get to tell it to get excited this is an event in london for us i always put like dates and locations because for events if you again if you don't specifically tell the ai sometimes it can make it up generally so that's where i put that there so that's where i do a lot of the tuning now again somewhat manually it does crawl like when you put in your website it will generate some of this i rewrote a lot of it just because it was better but you can you can tell it to do that and then i know yeah by end of year it'll automatically do a lot of what i'm doing now cool
22:42there's a lot of great vendors out there we're not saying these are the best vendors we are saying they work for us when they're trained that's what we're saying for what you'll find there are some apps that you could deploy on your own right with in few minutes and there are some apps if you have engineering resources you could probably deploy on your own we don't we don't have a lot of time at saster we have a lot to do with the small team we don't have any engineers so we We need tools and we have a lot of data. Okay. We have more data than almost, we have a decade of data. So there's like some sort of three by three matrix where we need tools that can support a lot of data that don't require engineers where the vendor will get us onboarded.
23:16And so to be honest, no one we've talked about yet, there are other vendors who wanted to work with Saster and they fought with us or they wouldn't help us or they wouldn't, you know, they said they couldn't ingest the amount of data we have, or they didn't want to do with their app what we wanted to do. So first try to figure out who's using what, which is probably why a lot of you here, but then use your spider sense when you talk to them. Do they work the way we want to work? Like, for example, at Clay, there's a massive ecosystem of agencies that help you deploy Clay, right? Yeah, exactly.
23:46Now, for us, we don't need a$100 ,000 agency to help us. We just don't have the bandwidth to do it. But that might be a huge advantage over Artisan. Like, they're not direct competitors and everything, but like, I don't think Artisan has that network, right? Once in a while, your own team can do this with engineering, but almost everyone needs help. And so you've got to decide, is this the type of help? Can this vendor provide you the type of help you need? And I would almost pick that vendor, the one that you have the most confidence you can onboard on, not the smoothest deck or sales process or best demo.
24:19Just talk. What's the onboarding process like? How does it match to how you work in your data? And if it doesn't feel right, pull the ripcord and bail and pick somebody else. artisan, qualified, momentum, attention. They've all been the same. Gamma now has all been the same way for us. And that they were not unique enough. They were like, oh, it's SaaS. Or we have to help them get set up. They're like, no, we do this for everyone. Like we want our AIs to be successful. We want it to work. See who you trust. And go with that if you're going with a out-of-the-box solution. The other thing I'll say, I want to stay on track.
24:50But good God, if you're in this space, the other thing we've learned is you can't have a crappy sales team. because we need the help. And I can tell you, there's at least two leading vendors that we said no to, not because the software is not good enough, but because the sales team fought us. They didn't know the product. And this is always true in the old days. But when you're talking about an app with training and deployment in a new category and the rep fights you, no, like you, I want to know how I'm going to get this deployed. And so just, if this is you, listen to the sales calls, get my number or attention hooked up, Be relentless and just get rid of anybody that is not an asset to your prospects because they'll just leave for AI.
25:31They'll just leave. If they can't help you, can't answer the questions wrong or fight with you. Okay, let's move on. So that's for outbound. Let's talk a bit about inbound. I'll preface this to a lot of folks we chat to say support and sales are their top two use cases. For agents, I think the data is out now on Salesforce and Agent 4 so that's their top two use cases too across all their agents that they've deployed on agent forces for sale or for support. So these are common use cases, right? Like that's not unique to Saster. I think where it became unique to Saster is because Jason's Delphi has now become a bit of a co-pilot for folks.
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26:09Like you can try it at sasterai.com, use the co-pilot. People use it for advice. Sometimes people use it for one-off questions, but when we looked at the data, most people come back to it. So they'll actually ask Jason's AI a question. Jason's AI will respond. Let's say, hey, I'm thinking about hiring this candidate for a VP of sales. Here's my high-level overview of them. What do you think? Jason's AI will say, hey, I think we should think about these XYZ things. And then if the founder says to them in the next instance of Delphi, I'm thinking about hiring that person that we talked about. What should their comp plan be?
26:42It'll come up with a comp plan with them. So again, it's becoming more of a co-pilot, which is kind of cool. and in that use case we really liked how folks use it for faster advice right faster style advice jason doesn't have time to talk to a thousand people a day but his delphi does but where i thought it kind of struggled a little bit honestly was in the sales and support side and the inbound side people would ask it going up to sas for annual questions about the annual questions about sponsoring and it did okay with the answers like it was still better to get an answer in real time the no answer, right?
27:16So it was still pretty good. But now it's just gotten a lot better that we use this mix of having a dedicated, right? Even though we have free on Artisan, like it just works better to have a dedicated agent working on outbound. And now we have a dedicated agent that works on inbound. So again, it's just that the level of output we've gotten to be used is just a lot better than what we originally had on Delphi being Jason's mind and used for like a little bit of everything. It also kind of led us to these use cases, right? I just saw that people were starting to struggle with things like that. And so that's where we wanted to add those next tools and agents to the mix.
27:55We use Qualified now. They've been in the Saster ecosystem, I would say, a long time. I know they've been attending a really long time. So we already knew of them, right? When I was starting to look for things that could do inbound for Saster as an AI, this is top of mind because I also knew a lot of folks who are already using it. So this was also one of those things where I could just back channel like what are people already seeing with Qualify and they were all positive on it. So that led me to chat with their team. But what it does for us specifically, which actually is a little bit different.
28:29So you can see it on our website. If you're on saster.com, you're going to mostly interact with Delphi. If you're however, on one of our Saster events pages. So if you're on Saster London, in, SaaS for annual, or you're on one of the sponsorship pages, media pages, basically anything that has to do with actual SaaS for revenue, this is where our qualified agent lives. This is where you'll see the Amelia AI. We strategically said that Jason Delphi is Jason's AI. We named it after Jason so folks know that they can ask it for advice. We named for this one the Amelia AI so that folks knew that there was a difference.
29:00It wasn't just like another Jason AI. This is the one that you specifically go to when you have a question about attending saster sponsoring saster and then what you should do about those two things or media right so that's how it's specifically trained um and honestly it's something where even like we don't have many sales folks here but they were a little steptic on in when i first deployed it because they're like okay our prior process to qualified was you would come to sasr annual or sasr one in any of our event sites and if you say were interested in a sponsorship you would fill out a form after sasr annual in may the sierra i was like that feels very antiquated that feels not very 0.25 where our conference is now all ai we're going all in on ai it feels very outdated to have a page where you fill out a form and that's the way to get a hold of Samster.
29:54So that was like a kick in the butt for me specifically too, to get away from that kind of old model of how we were doing things. So now our qualified does actually a lot of different things, but part of what it does is it, the form is on the website, but you won't actually ever complete it now. Like it's literally there as like a wrapper. And if you start to say, the moment you start typing in your first name, this qualified agent, the Amelia AI will pop up and say, hey, I saw you're interested in sponsoring faster. Just shoot me your email and then I'll automatically, on the back end, I'll round robin it to a sales rep here and it'll show the meeting booker instantly.
30:34Again, I know there's a lot of other things that do that. The magic though of Qualified that we've seen is that it does have all of our data. It does already have full integration with Marketo, full integration with Salesforce. It is so nice that it knows this. So like when they're coming to the site and people will come multiple times, usually to our website, it knows how many times they've been on the website. It knows if they've been to Sastre Annual and knows if they sponsored Sastre Annual. Literally, if they opened the Sastre newsletter from Tuesday, it knows all of this because our Salesforce and Mercado knows all of this.
31:08So that is actually, they call it Piper Dequalified. That's the magic of using a Piper agent. Ours is called Amelia. Is that it knows everything. So in that context for inbound, I actually like that it knows everything because these are folks that are obviously warmer leads, right? They're coming to the website. They're coming multiple times. They're on specific pages to either buy something or get involved in staffer. For all intents and purposes, they're high intent visitors. So in this scenario, I do want it to know as much data as humanly possible. And so in that reason, it's very nice that Qualify does that on the back end.
31:44So that's what it does. So it's, and it's, I mean, it's, it's ingesting our Salesforce and Marketo data like daily? I said it's a weekly because I'm like, you know, daily is a lot. I'm like, weekly is enough. Okay. So every, every week it's doing some sort of diff analysis and importing everything that's new from Salesforce or Marketo? Correct. Yeah. Okay. And that's automated. That's automated. Yeah. And that's automated. It also will crawl all of our websites once a week too. So like sastra.com, it will re-ingest once a week. So if you write something up about like you wrote, like you did the Vibe coding last week on Workshop Wednesday, it already saw that it adjusted it and knows how to reference it.
32:23This one will show up like next week, right? It's after annual, it'll recrawl once a week. So like, you know, when we add speakers or when we add them to London or make updates to the London pages, I don't have to worry about pushing it to that. It'll just do that automatically. Yep.
32:41So yes, that is where we've used it. part of it was like okay i want to you know bring our inbound into the whatever century this is into 2025 and so that was part of like okay let's replace the form with something that is a lot more intelligent than just a static form the other thing we've started doing is because it can do the meetings bookings it's obviously going to have a better response rate on meetings than we used to have manually right so if you filled out the form Previously, we would then, I would wrap Rob in it manually. Then I would send it to rep, the rep would reach out. And then, you know, they'd have to go back and forth on picking a time for the meeting.
33:20Now it just books the meeting. So literally, Dave and our team will wake up and he'll be like, yeah, I got like three new meetings from qualified. I'm like, that's great. That's what we want. I didn't have to touch it, but I do have all that data, right? I can see the conversations they had that led them to sponsoring. I could see who they were. I can also like, I'll go through with David kind of daily and say, okay, like, hey, who did you get from a qualified meeting like let's see what they said on the website website and then you can also see like what their company is doing so you can see if their company is on the website a lot right maybe they're taking it more seriously um you can see what pages they were on so again it just gives you like extra like buyer intelligence context for how they came inbound versus again static form you're just kind of getting their name and email you're not getting the context around it that piece has been really nice for us the other thing we've started it on there's like and then there's one like somewhat future use case which is literally in the next couple weeks is i started to train after we nailed the sponsorship piece which was the first piece we wanted to solve i started to train it on direct ticket sales so much like our origin this is a little bit different because it's a thin bound versus outbound it can again it can see when people are on like the sass or london site you can see if they've been a couple times now we'll preempt them and say hey are you thinking about attending you are okay great here's the discount code to attend and if they don't use it the next time they're on the site it'll remind them of the discount code so this is a new thing we've we literally adjusted that at the end of august worked really well so we're going to keep doing that and then we as you can see here we started a prompt for like do you want to inquire about group tickets my concern on that honestly with that if I turned that on, we were going to get too many spammers that were like, hey, your chat already gave me a promo code.
35:05And actually, I just didn't like it. So I'm inquiring about group tickets. But really, I've actually gotten the opposite. I've actually gotten highly qualified. I've gotten highly qualified leads, companies that actually need group tickets. So because how you buy tickets on sastra.com is usually good for a group of one to four. it's kind of tedious actually pass for people because you have to put in all their info you have to like do different things it's just easier to do it with an actual person so this has actually led to actual sales of of group tickets which has been nice because i actually thought it was going to be abused but it's been used properly that that was like the next we literally just rolled that out in the last two weeks so that was like the next use case we found it so now we're actually already up to like two slash three use cases of it the other thing it does is it does really get the port so if you ask it like people have asked the london one a lot for like the hotel block again it's like kind of buried on the website so that's a common thing it'll answer now like hey i forgot where the venue is also is there a hotel block it'll just answer that for them you gotta remember too like london time difference to california where SaaS is pretty staggering.
36:22So like I can't answer these questions in the middle of the night. And if they come to the website and they can't find it, it's much easier to just interact with the Amelia AI, ask it all the questions. The future use case, which we're going to do before London, and this is the goal with being qualified, is to turn this into even more of a co-pilot so that folks can ask it like, hey, if you come to the website again, it's going to know if you're already registered or not. So let's say you're attending, you come to the website in November, you haven't booked any networking meetings yet, or Amelia AI will be able to tell you like, hey, you haven't booked any meetings yet.
36:57Here's all the info on the SaaS for who do you want to meet program for London. You should start networking. Or hey, I saw you haven't booked any sessions yet. Here are some ones we recommend you should book and go to on Tuesday, December 2nd. So that is its next date. I'm also adding, like Jason's Delphi already has voice. So you can literally talk to it, which a lot of people do. They call it. So we're adding like poison video to this agent as well. Again, this is adopted a lot later than Delphi. So it's doing a little bit of catch up in that area. But I would say in the use cases we've printed on has been successful out the gate.
37:34And then, yeah, I would say too, like you can see here, like some of our much like artisan, like our performance. I think they're fine with me sharing this. our performance metrics is like higher than average. So like the black lines on each of these for like engagements and meetings for Sastra has been higher than average, but still really, again, their averages are still fairly high. Ours just happens to be above average. Again, I think that's part to do with like the brand that Sastra has and how people are coming to our website versus like a more common product website.
38:11i think it sounds like listen a lot of these behind the scenes these apps are a lot of mashups of other apis right they're api other services that can figure out who's on your website and figure out all these things but what's i think one of the things i don't know others can do this but that works for us for qualified is we have so much data about so many people over a decade right that we have so many returners yeah so many of the folks that come back to us And so that's why we do so well. But you might think if you're a newer startup, oh, I don't have folks that are returning. Of course you do.
38:41Everyone's, the newer you are, the more folks are in discovery. How many times do I have to come back to your website to do diligence, to think about it, to when a sales rep tells me something, when I hear a referral, they're all coming back multiple times. As Amelia said, we're shocked how many times, now that we track it more carefully, we could have done it before, how many times people come back, right? So you should leverage this, all the data, all the interactions, everything you have to get them, right? to personalize the experience and get them. There's one thing before we move. So I'll show you guys the backend of Qualified for a second.
39:15All right. So somebody asked, if you have a more enterprise ASP, can you still use a tool like Qualified versus having the customer directly connect with a rep? You can do both. I've literally done both on Qualified. Like one, are ASP for tickets? Yes, it's a couple hundred bucks for London, in slightly more for Sastra Annual, but our ASP for sponsorships is probably 85k. So I don't know if you consider that enterprise, but I would say that's more of an enterprise ASP. The nice thing about it is you can at any time, they call it pounds, you can start talking. I don't know who this is, so I'm not going to talk to them.
39:54At any point, if you see that they're typing, which it'll show you what they're typing in real time, it'll literally show me what page that they're on right now on sasher.com you can say hey it's like you can hit this and start talking to this person so for us it's on either or like i actually find it very addicting to have this just this is literally i have called what always on as one of my tabs and i'm continuously seeing what it's doing where people are going and it'll alert you it's got like a slack integration so it'll alert you like you can set it for certain signals but it'll alert you how you want so if If you want to jump in and have an actual rep, start a conversation with them, you can.
40:34It's meant to be fully automated. Most of the time people get our fully automated experience, but there have been instances where I see folks or maybe have a more nuanced question related to sponsorships, which is a higher ASP, and I jump in and I start talking to them. And then I get it to show the meeting book or et cetera. You can do both. Before we run out of time, Anything else you want to hit on Delphi, Jason? We've hit it a bunch, but. No, the only thing I would, listen, if you want to try our general chat, just go to saster.com and just click on the chat on the bottom right if you have, and a lot of you have, 139 ,000 conversations.
41:14It's really good. Just the one reminder from it, this is the first one we started, and there are other tools that do this that create digital clones, but what it does is it mostly automates ingestion. So it automates, you can automate, It'll crawl our website. It'll automate the RSS feed from our blogs. It ingests all my tweets. It ingests every YouTube video we've ever done. Then we got SaaS for that. It's a lot of content. So out of the box, it was really good. The quick thing we learned is then to quickly upload some very specific documents. So when this was the only tool we had, I'm like, well, let's upload the sponsor prospectuses for our sponsors.
41:47It became magical because all of a sudden it could answer those questions. And we get some stuff wrong, so you have to read it each day, but it would get pretty good. So we'd have to review it daily. The meta learning is, listen, to get the results that we've seen from the SDR and the BDR, you have to put in a lot of effort, but even just some general tools, man, this is so much better than get back to you in a day. It's so much better. So if you want to start, we started first with, or you could use qualified as a general tool. Like it's not a perfect support tool, but it could like these tools all can do more than you think.
42:21So pick a platform and just keep investing in it. It's so much better to get back to someone with a 90 % perfect answer in real time than any brutal other process. There's just no excuse. So my point is, listen, we started with one and now we have 20, right? And 11 core ones. So this general platform was not enough. But man, just having a versatile platform versus nothing is so much better. It's just so much better. There's no excuse to not have a super well-trained AI talk to your prospects or customers in real time if that's the way they want to talk without a human. So if nothing else, pick a general tool and run with it is the meta learning.
42:58All right. Two more, if we have time, and then Jason can chat about quickly as well as we live coded ourselves. Sales collateral, I'll touch on this one real quick. I actually don't remember how you found Gamma, Jason, but... I just knew. I just tried it. And it was great. But then I said to me, can we customize this so that every single sponsor prospect gets customized collateral? because it was driving me nuts and how crappy like our decks were pretty good but they were so uncustomized i wanted to cry yeah yeah and yeah so we use it that is our primary use case so like to jason's point we have right now this prospectus on our website which you can download you can talk to our ai and get it and see it and it's like a hundred pages i don't know it's crazy long because it has everything.
43:47So it's fairly long and hard to digest. So where we started to use a Gamma was, okay, if I wanted to talk to somebody who is a prospective customer, and I didn't want to send them this 100-page deck, I wanted to send them something more custom, I now just load it into Gamma. I tell it which slides I want to keep from our long prospective stack. And I tell it what the company is i tell at other points and it'll automatically spit out a more customized deck for them i send it to them it's a lot easier for them to not only use and reference but it'll get passed around right especially if you host it on gamut it'll give you like an alert of anytime somebody reads it or sees it these will get passed around because we've literally made it for them specifically so if it's the bp of marketing we're talking to and they need to run it up to the cml or the CEO.
44:39Send them an either pre or post sale, highly customized deck, they can share it around. A lot of the times we do these decks now and send to folks, the number one response I surprisingly get is like, oh, I was going to have to actually do that myself so I could show the rest of my team or I could show it to our decision maker or a buyer or actually legal need something for procurement. So a lot of times it will actually, not only does it look a lot better, it feels a lot better. it's more customized to them it will save your buyer a step and so obviously if you think about those implications you want to make your buying process as easy as possible and so now we like live and breathe by doing these decks again probably takes like 10 or so minutes to make one just depending on how customized you want to get with it and then it'll spit it out instantly the other thing i've done is i've used it for like our internal docs or docs i share with like certain VIP groups at faster.
45:33So like at sponsors, past attendees, if I want to make something, you know, we don't have a full-time in-house designer. I just do it on Gamma. I uploaded our brand guidelines. I said, here's our guidelines. Here's our colors. Here's our logo. Give me something that I can just, you know, use in 60 seconds to pass around because I already have all the content I need for this. So that's where it's been, again, highly well received when We send these because it saves folks to staff and also just super easy to use. Like it is as easy as Gamma to use in Gamma.
46:07Last ones we've added, I bring them away to my attention because they're good partners of chapters, but they help us do automation and we use Salesforce. So specifically, it's Salesforce. It will analyze all of our sales calls automatically. So now I just get a Slack. There's some stuff up there, right? It's not just going to be like, okay, David had a call with XYZ company. Here's the summary of the call. It does do that, but we've also tuned it on. There are certain things I want it to say. So I always wanted to do next steps, which you'll see in the screenshot. I always wanted to do it. Were there any objections?
46:41What help does either the person or does David need to get the deal to the next step? It will automatically attach the contacts to an opportunity. So we're really bad at doing this. Your sales team is probably bad at doing this too. We put a lot of accounts in Salesforce. Sometimes we forget to put the actual individual contact. It will just create the context for you when you have the call. Then you go back to Salesforce already there. You don't have to do anything. For us, we've also set it so that it will change our stage. So if this is a first step call, which for us is like a 0.5 step in Salesforce, it will move them to step one, like meeting held, anytime the meeting has been held, and then it's over.
47:20So for us, it's just nice because I have spent the last I don't know how many years pulling my teeth trying to get our sales reps to put things into Salesforce. So now instead of pestering them all day to do it, and they just don't. So they do have to, again, they do poke it up to Salesforce. It does give me reports of like how much activity they've had a week, how many calls, action items, red steps. It also has some like both of them have really good AI where you can automate like the next steps if you wanted to. with the ai but again there's a lot it does here even though maybe it seems simple to you guys there's a lot it does behind the scenes similar to like a qualified where it knows these accounts right it's hooked up to your salesforce data it knows who how the call went and automatically push all the notes right like we didn't have any call notes in our salesforce prior to this like we just had like loose information like if there was a close one deal it was in salesforce otherwise it was pretty much not in there, which means it did not exist.
48:24Part of this too is like the, I guess there's other learning on it of doing like the AI Red Vops tool is forever starting from when we implemented this. Now we have great Salesforce data, right? We have healthy data on all these accounts. So when it talks to, when qualified so you're up there on the website or artisans that were outbounding them, it can reference this, right? Because it's all pushing the Salesforce.
48:53okay we only have a few minutes left but if you want to go through do you want to go through like the bide code yeah i'll go we go a little a little bit over even if we lose people it's a new world but um anyhow there's a lot more that we do but we just wanted to give you the core gtm flow that we spend the most time in which is what you just saw the sdr bdr generic ai and rev ops but there's a lot more and it's a bigger topic. Certainly we've written about it and tweeted about it, but we have built a bunch of stuff ourselves in Replit. You could build it in other tools as well. I mainly picked Replit in the beginning because it was an end-to-end solution, but ultimately all the leaders in VibeCoding basically use Cloud Code and are more similar than they're different.
49:37But where there was nothing to buy, we built. And there's a bunch that are cool. This one is niche, but some niche apps are, can be pretty powerful. So for example, this is specific to us, but it is interesting. We get thousands of speakers submissions a year. Okay. And if we get a handwritten email from Larry Ellison saying they blew up the quarter on AI, I'd like to speak at Sastr. We'll just, we'll get that one. We'll see that one most likely, but we get thousands and there's gems and it's too many to process. It's way too many to process. And so what we did until, uh, through last year was we hired agency.
50:14They worked with three years. We paid them about$15 ,000 a month or more. And part of their job was to review all these inbounds. And it was okay for a while, but they got tired of doing it. And the volume was really high. And they might have heard of HubSpot or Salesforce, but they might not have heard of cool tools like Gamma or Replit or others. And so they'd miss things and it was a lot of volume. And then they would hold things and people wouldn't know if they were accepted and they get grouchy because it would take months to hear back from the agency. And so when the agency didn't want to do this anymore, after a while, I just vibe coded a speaker application.
50:48And it's pretty damn cool. You could don't do too many, but you can try it on sass or london.com. Do a speaker application yourself, put in it. And it's pretty good. It uses all the criteria that we want. And then it instantly grades you on the website. Here's one from 857 this morning, 54 out of 100. It tells you what your score is. It tells you why you might or might not be a good fit. It tries not to be triggering. and it sends us an email and a Slack notification of who they are and why. And it gives us actually much more brutal feedback on their pitch than it does to the candidate. But man, now everybody knows this is so much better and saves us so much time.
51:25And this did take iterations. This was not a 15 minute project. It probably only took me three or four hours to build this, but it was over multiple days. So it has to be at least a P2 priority to build it yourself. and then maintain it. But pretty damn cool to have an agent reviewing thousands of speaker submissions and content submissions rather than spending hundreds of thousand dollars a year and getting much lower output from humans that don't want to do this. They just don't want to do this work anymore. So I built an agent. So that one's pretty cool. You can try it and you can, that's kind of epic.
51:59That's an internal, mostly internal UGIS, but you can try it and do a submission. The next one, what's the next one we got, Amelia? and just a few others you can try that we built ourselves and again at the bottom buy where you can don't build we can do a follow-up session on this i know some of you have followed it we built this whole speaker review we do content review with ai agent we built a startup valuation calculator you can try it on saster.ai we've had 230 000 valuation calculations where you can value a startup we then once we did the speaker review of the 2000 submissions i'm like let's use a version of that to help founders review their pitch decks to VCs.
52:39I launched that this week. We've already had, I think, 450 bona fide DC decks go through the system. It gives you deep feedback and scores based on 4 ,000 recent VC rounds and 800 DCs that have come to Saster. It's pretty cool. We had our Saster AI London website built in Squarespace for years, but it was driving me nuts. I couldn't do what I want to do with this year, so I rebuilt it from scratch and replet. That's pretty cool. And then we built a whole new version of our Saster website, which you can try in sasara which has so much stuff and all this stuff is cool it's interesting when i look at the order i made this and they went i went from necessary to nice to have so probably anything below this line i would not vibe i would buy it there's no way you're going to build an artisan a salesforce a gamma you could build the little bits of it i mean there's just no way there's too many man hours but if you have nothing the beauty is you can vibe your own agent now.
53:32Just be patient. We've done a lot on it. So a quick look on other things. We've done a bunch on this. Maybe we'll do another in a couple of weeks on what we've really learned vibing. You can try them all here, but you really can do it. Just stay small, keep it simple, and buy if you can.
53:51Hey, everybody. It's Saster. Finn is the number one AI agent for resolving complex queries like refunds, transaction disputes, and technical troubleshooting, all with speed and reliability. See how FIN can deliver the highest resolution rates and highest quality customer experience at fin.ai slash saster. That's fin.ai slash saster.
From the publisher
SaaStr 822: SaaStr's Top 10+ AI Agents: AI SDR, AI BDR, AI RevOps + More: The How, The Who, The Why with SaaStr CEO Jason Lemkin
Join us in this comprehensive deep dive into the use of AI agents within SaaStr's operations, as requested by many of our followers.
Led by SaaStr CEO and Founder, Jason Lemkin, and SaaStr Chief AI Officer, Amelia Lerutte, we'll detail our journey from having no AI at the start of the year to utilizing 20 different AI agents, including 11 core ones that we rely on daily.
Learn from our insights on our most utilized AI agents, their workings, actual data, and how we manage them for optimal results. Discover specific tools like Artisan, Qualified, Gamma, and Replit, and understand how they're integrated into our outbound, inbound, and sales processes.
This episode also covers how we've internally developed AI-powered solutions for speaker application reviews, content review, startup valuation, and more. If you're interested in bringing intelligent automation to your business, this session offers practical advice and firsthand experiences to guide you on your AI journey.
--------------------- This episode is brought to you by Intercom:
Fin is the #1 AI Agent for resolving complex queries like refunds, transaction disputes, and technical troubleshooting—all with speed and reliability. See how Fin can deliver the highest resolution rates and highest-quality customer experience at fin.ai/saastr.
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