SaaStr 830: 6 Months Later, How Our AI SDRs Actually Work as AI Runs GTM with SaaStr's CEO and Chief AI Officer

21 Nov 2025 · 1 h 25 min

Ask about this episode

Ask anything about it. ChatGPT or Claude reads this page and answers with the times it was said.

Connect VO and ask about every podcast you hear, including the moments you saved. Add to ChatGPT · Add to Claude

In short

Podcast Summary: SaaStr 830 - 6 Months Later, How Our AI SDRs Actually Work as AI Runs GTM

Overview In this episode, SaaStr CEO Jason Lemkin and Chief AI Officer Amelia Lerutte discuss their journey of integrating AI into SaaStr's go-to-market (GTM) strategy over a six-month period. They share insights on the deployment of AI agents across various functions, including marketing, sales, customer support, and operations, analyzing their performance, challenges, and unexpected outcomes.

Key Topics Discussed

AI Implementation Journey

  • Initial Deployment: Started with one AI agent before SaaStr Annual in May 2023 and scaled to around 20 agents by November.
  • Oversight Requirement: The implementation of AI requires significant management and time, indicating that it is not simply set and forget.
  • Integration of Tools: Tools used include Artisan, Qualified, and Salesforce's AgentForce, with varied use cases across the organization.

Performance Metrics

  • Outbound Emails: AI agents facilitated sending nearly 20,000 outbound emails, achieving a response rate of almost 7%, which is double the industry average.
  • Revenue Contribution: AI agents contributed significantly to ticket sales and sponsorships, with 10% of ticket revenue attributed to AI efforts.

AI's Role in Sales and Marketing

  • Cloning Best Practices: AI agents can replicate and scale effective practices but require a foundational understanding of what works before effective scaling.
  • Nuances of Deployment: The effectiveness of AI is directly tied to human oversight, training, and context provided by the teams deploying these tools.

Challenges Encountered

  • Human-AI Interaction: Maintaining a balance between AI automation and human involvement is crucial for success.
  • Data Quality and Governance: Concerns about data governance and the need for quality data to train AI models were discussed.

Key Takeaways

  • AI vs Human Roles:
  • AI should not replace talented human roles but can enhance their productivity and capabilities.
  • The ideal approach is to empower top performers within teams by integrating AI to scale their efforts.
  • Best Practices for AI Use:
  • Ensure foundational processes are effective before deploying AI to avoid scaling poor practices.
  • Continuous training and oversight of AI tools can enhance their performance and ensure they meet organizational needs.
  • Cost and Budgeting Considerations:
  • Investing in AI tools can be cost-efficient when reallocating budgets from human roles or ineffective tools.
  • Anticipate annual costs ranging from $50,000 to $100,000 for effective AI tools, with an emphasis on the importance of data quality.

Future Directions The conversation will continue in part two, focusing on additional aspects of GTM strategies, including revenue operations (RevOps), customer success (CS), and further insights into AI applications across various teams.

Conclusion This episode highlights the transformative potential of AI in SaaS go-to-market strategies, emphasizing the importance of understanding both the capabilities and limitations of AI tools. Continuous engagement, training, and adaptation are crucial for maximizing the benefits of AI deployments in sales and marketing environments.

---

> Note: This summary captures the essential discussions and insights from the podcast episode, providing a structured overview of the integration of AI in SaaStr's business operations. For further details, refer to the full episode.

Written by AI. May contain mistakes. Listen to the episode to check what was said.

Hear the part that matters, and keep it.Open this episode in VO. Double tap your headphones to save a moment as you listen.
Get VO free

Transcript

Automatic transcript. May contain errors.

0:00Welcome 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 Sastra podcast. Don't fire anyone good to replace them with AI if you haven't learned anything. If someone's failed, if they can't close anything, or if your AI SDR hasn't set a single appointment, I mean, your human SDR, maybe just replace that budget with it. You know, if your SDR can't do anything, you know, you can't do worse than zero. But we'll track it. Many of you, if you're early stage folks watching this, you'll think that's expensive. and if you don't believe in the vendor, it will seem very expensive.

0:37It will, because you'll get quoted by a sales rep a lot of money and it will feel risky to you if the deployment doesn't work. You know, that's why we're not trying to be walking billboards, but we do share the vendors that we use. Others are good too, but if you get the right people, it's going to work, but it can feel risky. It's tough to start at 500 bucks a month today, but you got to take a little risk in life.

1:06Hey, everybody. It's Saster. Connect data, automate busy work, and empower teams like nobody's business with the one platform that grows with you every step of the way. Learn how Salesforce works for startups at salesforce.com slash SMB. That's salesforce.com slash SMB.

1:26Hey, Saster. Imagine having agents for every support task. One that triages tickets, another that catches duplicates, one that spots churn risk. That'd be pretty amazing, right? HappyFox just made it real with Autopilot. These pre-built AI agents deploy in about 60 seconds and run for as low as two cents per successful action. All that sits inside the HappyFox Omnichannel AI First support stack. Chatbot, Copilot, and Autopilot working as one. Check them out at happyfox.com slash faster.

2:01All right. Hello, everyone. Welcome.

2:06All right. Welcome to everyone in today listening or your agents that are also listening and you'll be reading the recap later. We thought it would be fun to do a deep dive into where we're at today in our AI journey. it's kind of crazy to think before saster annual this last may we really only had one agent that we had sort of just deployed and now we have about 20 or so core agents which we've gone through but i'll go through a little bit as well for context so it's crazy to see you know just kind of from may till november you know post annual now that we're fully in all the platforms we've added a lot more use cases across go to market which you'll see just to give an update of where we're at what's working there's some nuances on what hasn't worked and there's some maybe unexpected learnings there that we'll also go through but hopefully it's helpful for folks just to listen and hear and see where we're at share our learnings and our findings hopefully this helps you as well.

3:15But if you have any questions as we go along, put them into the chat. We'll try and do a bunch of questions at the end. I'll answer your guys' NET dev questions too. So with that, let's go through it. So what do I mean by six months of AI running our GTM? Now, it's not on full autopilot so it is not just that the ai is running amok with our gtm on its own it does require a lot of oversight and time and management which you'll see here today uh how we do that how we think about it and also how we are thinking about doing that going forward just because right now it does take literally the majority i would say of both mine and jason's time to run all these agents and use them successfully, right?

4:07If we could run more agents and they would fail if we didn't put in as much time, but since we do devote a lot of time to them, they've become quite time consuming. Now, none of that is to scare you. I don't think, you know, 20 is the right amount for everybody. So if you haven't seen the sassr.ai slash agents, you can see all the agents we use. there's a mix of ones we've five coded that Jason's talked about previously. And then there's ones that we are using third-party tools for. So that's all listed there. You'll see most of those here today too. We'll go through the metrics of them, just like in full disclosure, I've got screenshots of all of our metrics.

4:47And then also we're going to go through how we think about them in our day-to-day. So Jason, anything you want to add there? No, I think that's great. I think, And we'll go through all of it. I think most importantly, we'll give you an update on how all our AI SDRs slash BDRs of work outbound, inbound, the actual data, which I think will be super helpful when we put this together, which is great. Yep. And then, so why 20, right? So I'll kick this off to say 20 is not the right amount for most people. I think even like a few is maybe the right amount for most people. or even right now, if you're like, I have maybe, let's say, one agent kind of fully deployed, it's scaring me to go from one to 20.

5:32I don't think you should take this as like the gold standard of everyone needs to be on 20 apps or you're behind. Now, I do think you need to be, we've talked about this before, I do think you need to be on some version of this stack in GTM to not fall behind. And I'll show you why. But I don't think 20 is the right number for everyone. I feel like between myself and Jason, we're fairly technical, right? Some of the stuff we vibe coded, we've been thinking about for a long time. Some of the stuff you'll see that we've deployed across our go-to-market is where we had gaps and we had a need to fill them, right?

6:05So that's why we have 20. I just put a fun image of, you know, this is a real image of myself that then Reeves added a digital clone to. But I think there is a lot of talk and I want to get your thoughts quick, Jason, on this before we move on, you know, how much can AI clone yourself? How much can it do? I would say now, six months in, it is for us and for me, it's become a clone of all the best things we can do when we devote the time to it. It can do such a massively scale of output more than I could physically do or that Jason could physically do. There's just so much scale in getting these systems to actually work and go to market.

6:50That is a scale that no single human could achieve. right and so that's kind of the magic of it i think six months in it still does not cease to amaze me how much we can do with our ai together across all of go to market and i would say too in the last six months we didn't start with all of go to market right we started with basically a support use case and then we added in the we layered in the other places where people either left the org or we had gaps or we wanted to improve how we were doing these things and go market and so that's kind of how we landed on 20 that's why we have it all across the org but i think this concept now it's cloning the best parts of your best players right maybe your org isn't as small internally as samstra is um and you've got more folks but i think there is now i think a clear path to where i'm seeing in these platforms you can clone all your best a players right Take all the best A players on your team across marketing, sales, CS, sales, rev ops, and make them S tier with AI.

7:50I truly believe that's possible and you'll see it from our results. But yeah, what do you, any of you thoughts out there, Jason? I think that's a really great insight. Thinking about what we have learned since we've had some success. A lot of folks want agents, specifically AI SDRs, AI BDRs, AI marketing agents, others. is they want them to do magical work for them. They want to spend 20 grand, 50 grand, 100 grand, and all of a sudden get leads. That is, I didn't fully realize that, Chil just now. Chil just said, that's the wrong way to think about it. What your agents can do, and it is so powerful, is they can take your best practices and scale them out almost infinitely.

8:28Figure out what works, figure out what campaigns work, what messaging, whatever works is already working. You have to have something that's working. An agent can't today figure out, make something that isn't working work. But if you know what's working, and then this is important, you train the agent with it, then you get 24-7 infinite firepower backing up your best practices. And your best practices will change, and you'll run A-B tests and A-B-C-D-E-F tests and multivariant tests. But you've got to understand what is working in GDM before your agent can scale it up. And I think that is a fundamental mistake that confuses folks.

9:02It's not about buying a tool. but once you have something that works, which we have, and Amelia will show you the data, then you can scale in a way you can't with humans. Yep. Yep. I would say that's my biggest learning six months. And like we, we took things that were already, or some processes were broken, right? Like our RevOps process was pretty broken before we did this, but we figured out how to fix it. And then we basically put that on acid with the AI and the agents. So I do think it's a, it's an interesting nuance of how to approach it as people are in different states. Okay, this is just a quick fun one before you go into our data.

9:38This is from Jason's co-host, Rory Hitskin. That's their state of GTMAI. It's pretty good. It's actually fairly short but concise. I like it. You can just go over there so you can download it. It said a lot of interesting things that I used to kind of anchor how I wanted to present a lot of our data since we have a lot, right? So I think we're in this right now sort of paradoxical world in November of 2025, where a lot of folks have adopted at least one sort of AI or agent, but maybe to Jason's point that he just made, a lot of them aren't seeing the impact because either they're expecting too much or they're not putting in the time.

10:16So I think that's kind of where I see the paradox lie. In this report, you'll see, I'll write it up too. I'm just one of my learnings, but you'll see across go to market, which ties into this, most deeply the adoption has been in marketing. But if you read the whole report, it's on kind of what I consider base level adoption, right? Like they're using cloud to create content. Yes, so are we, but you'll see our more kind of like sophisticated 2.0 stack at the end of this. Sales dev, same thing. They're using it for sales messaging. Like the kind of middle ground is using it for starting to do things like rev ops or more intelligent emails.

10:59again consider that kind of baseline i feel like you can again if you take the best people give them an agent they get used to and they know how to train it i do think you can get them to blow by that fairly quickly so i think across the board even what they said in sales and cs is a lot of folks are still early right so a lot of still early adopters there across the board but some good stuff there i'll try and tie into what we're going to show i think just a quick one to tie into that data plus what Jason was saying as well. Here are my quick biggest learnings and then literally all the next slides are the data that we'll run through.

11:37I think again in a lot of early days and as you add more platform I think the expectation that it gets easier with each platform you add is false. So I wouldn't expect to have that expectation. I do think a lot of the platform whether you use what like one specialized one for each function the way we are or you end up on one platform that does kind of like a little bit of everything pretty good maybe in that case it gets a little bit easier as time goes on but it's never set in and forget it like the biggest thing is that our agents will ebb and flow oddly depending on how much time the humans put in right so the more time i've put in with our agent wow shocker the better the output is and sometimes that ebbs and flows, right?

12:19Like we get busy, we have faster London coming up. So I can't always spend the amount of time I would like to with the agents, right? And so that obviously does translate to the results. And so I think that's one of the biggest things. I think Jason's fine on like immediate ROI and headcount is a hugely false expectation that I hope nobody has on this call. But if you had a baby going into this, can kind of course correct on where you're going to see lift and there there have been cases in our data you'll see where we did get immediate lift but again it took our processes like it took us recreating some of our best processes that we're already working to get an immediate lift in these six months you know and then i think in the expectation on needing to staff like an ai expert i've talked to a bunch of cmos and cro's now as well as founders that are either at saster or participating in saster where you know they say hey, Amelia, what's your advice on my biggest problem right now is we're starting to onboard all these tools, but I don't have anybody to run it.

13:21I don't have a chief AI officer like I am now to help us figure all this out. What do I do? And most folks, I will say that have figured this out and started to deploy AI more across the GTM org have told me that their best success has been, again taking your a player take somebody that is the best person on your sales ops team your rev ops team your best marketer your best sdr your best ae sit down with them figure out what tools you want to use together don't just deploy it to them from you know the council and then go through that process with them together because it's very important too that you need to do the ai yourself in order to figure out how it works you know you can't expect the even your best sdr to know how to instantly use this.

14:10You got to help them out and help them figure it out a little bit. But everyone I talk to that says they go this route of using the best A-tier players and injecting AI and figuring it out with them, they have now changed their job role. Like in the way that my job role has changed into now chief AI officer, they're saying the same thing. This is like the best path I've seen work for people across. And these are founders and CMOs at different stages, different ops. Some of them are even AI native companies and they need to figure out AI too. They're just taking all their best people, figuring out, and these are the founders, figuring out AI with them in the trenches.

14:45And then you become this S tier team together with AI that can do this, again, great outputs that you'll see like ours with everything AI. I think this, like somebody else asked me yesterday, hey, I'm rolling out a few platforms. Some of them are ones that's asked for users. do you like recommend anybody to any other anybody or like an agency that can help me deploy all this i'm like that's the wrong way to go about it what you got to figure it out yourself to you know no i don't care who where anybody went in life or school or whatever no single person on planet earth will know how to do this better there's no agency that already knows how to do it there's no maybe there's a few like ester people at orgs that you can try and steal but outside of that i wouldn't you know vibe a snake oil of oh we're an ai native agency and we know how to do gcm across the entire org i'm like they probably haven't done it themselves i know maybe that's a little disheartening that you have to figure out yourself but that is the best path forward in the meantime until others catch up and then i would say too don't get too hung up on this data governance thing a lot of folks i talk to now especially at bigger org get very concerned.

16:02Okay, if I add so many agents, I'm going to need governance as a layer. I'm going to need to clean up all my data and cleaning up all my data or getting all the processes right. It's going to take two years before I can even think about implementing. I think too much data is too much data. And if you have things that are working, again, I would focus there first. So I wouldn't try and tackle, you know, bite off more than you can chew. It just, it didn't work pre-AI and it stuck work with AI. And then I think the last one, because the other ones we'll get into per department, is I hear this panic a lot from folks now.

16:37I don't know if it's because of how much content we post about AI or because of all the tweets, all the LinkedIn messages that they have to keep adding. Oh, I got to catch it. I got it. Sastra has 20. I got to get to 20. You don't. Like, actually, we have 20. I'm only adding one more tool for the rest of the year. That's literally it. I'm adding more use cases to our current agent. I'm adding a 2.0 agent to AgentForce. I'm adding a 2.0 thing to qualify. I'm going deeper on our current tools. I'm adding one more because I think it's cool. And that's probably it for the first seed. Like Q1, I don't really know what I'm going to add yet, actually.

17:14I feel like if our agents can just go a little deeper, I may not add anything new. I might add just deeper use cases on our current.

17:26okay let's start with outbound i'll try not to spend all the time here we i know outbound is near and dear to a lot of our hearts and we talk about it a lot but i'll start here and she's an all your input too so for outbound six months and now we have sent now almost 20 000 messages actually it would be 20 000 again if the human me had a little bit more time to spend with my agent it'd be over 20 000 but still 20 000 is like a lot overall our outbound with the ai is almost a seven percent overall response rate which is you know kind of double just overall averages across anything you'll see from all any you know tool that does sequences and outreach of four percent positive response rate which is higher than most now keep that in mine this is like higher than most folks on the platform but interestingly too now that it's been six months 10 of ticket revenue for sastra ai in london only on this agent so this is an interesting thing where i have seen our outbound agent it has different goals we've explained this previously but i'll just give you guys some context it has different goals and so it has like different agents in one platform because the training is different on all those agents.

18:51I have an agent basically for lap sponsors. I've got one for current sponsors. I've got one for people who previously attended Soundster. Now I have one for people who are opening our emails, but maybe not taking any actions with us. And then I have one purely for cold outbound. So all of those agents are trained and tuned in a slightly different way because those audiences are different, right? The messaging is different the collateral of what we want the agent to do and also the goal for the what we want the agent to do is very different across those five and so we've got about five core ones just within artism that are set up differently and this is i think is surprising because at the start i was like okay you know it's an outbound tool they were a sponsor of soundster this last may like i'm going to use it for sponsorships but then i quickly saw okay like it's not bad at bookie meetings like it's fine at bookie meetings and that's great and then you know capture that intent and it's a great way to do follow-ups again to like current or past or lapse customers it's a great way to do that using AI again at scale in a more consistent way that sometimes we can't physically do but then you know there was just this interesting learning of because tickets for London and then now for annual or you know less than a thousand dollars depending on which event you go to the ai got pretty good at selling the tickets itself like it got pretty good like at first i was nervous now six months in i'm like it's let let it go let it run free like it's gotten pretty good now with all the time we've put in that it is empowered to sell tickets to be bulk again it's a lower asp so maybe that's the most interesting learning and it is still booking meetings for us on like the higher ASP things but yeah these people know us and it's just it's giving us this scale and personalization in a way we couldn't pre yeah pre six months ago like every event after we have a saster event I struggle to you know send I'm like okay we should send out hyper personalized follow-ups to everyone to all the sponsors to all the attendees to all the speakers everybody think about London that's 2 ,000 people.

21:02Annual, that's 10 ,000 people. We could never do it. We had to literally cherry pick the people who got an actual human customized email, then who would the sales team send a somewhat customized email to you, and then who just got a templated email because we didn't have time to do the rest. We just can't send that hyper-personalization of scale before this. Now, we've sent 20 000 post london it'll easily send a highly customized email to all 2500 people that come that's crazy if you think just stop and think about that for a second it's doing all this for us and this also was something that took not just me it took you know different members of the sales team like everything that we did is now consolidated into this in a way where the output is obviously fairly for us positive at least right we've seen some good gains here but it's not without time right so our how will you think about using ours and specifically for outbound and you'll see here that's why i put the data like the positive response rates do vary right and so this is varied on agent this is showing just the so one's a website one you'll see a couple of these are attendee ones but different years and so they have slightly different training slightly different things that they're referencing here.

22:23But these are ones where, you know, these positive response rates do vary depending on how maybe recent they interacted with us. Again, that was probably true pre-AI and it's still true now. But because our outbound emails sent per rep, like this was a crazy sound I just looked into last night, our outbound emails per rep across the board. So across the things I just mentioned for us, you know, tickets, sponsorships, speakers, whatever. On the average band six months ago, with anywhere between 75, let's say at the low end, to 285 at the high end, depending on the birth. Some people were faster than others.

22:59Now our AI is blowing that scale out of the water. It does 3 ,000 on its own per month in one. This is just one platform. I have another one that's always... I have actually two more. Two more that's doing outbound. This is just one platform that's giving us this leverage. And so I think, again, what's working for us is using this to do hyper specialized, personalized messaging at scale has been working. There is a, which I fully believe it. I've talked to Jasper, the CEO of Artism. There is a two to three week warm up period with Artisan so that they can get your deliverability as close to perfect as possible.

23:41You want to do this. You don't want to skip this step. There's a reason they make everybody do it. At first, I was kind of annoyed. I'll be honest. Previous webinars would be like, it's kind of annoying. It takes two weeks. Or anytime I need to add new domains, it takes another year. I'm kind of a little frustrated. But then you wait and then you see why. Because you're like, okay, not only do your emails in this hit the inbox, they don't go to promotions. I can't even solve that in Marketo. So many of our newsletters end up in promotions. These actually go to the inbox. And so, again, just another point of, differentiation there of things that could do that we come do six months ago.

24:20And at the start, we had a review. I was nervous. I wanted to review all the emails myself. But now I just spot check, right? I spot check it. But I do mainly let the AI in or isn't draft a response. I don't let it send it fully yet, even six months in. I think it's still... And some of my other agents, I do empower to do full responses without me looking. But this one in particular, because of where Saster is, and maybe if you have multiple products, you might be the same way. Sometimes people ask multi-threaded questions, right? And so I think that's where the AI is pretty good. Let's just say in this scenario, it's to book a meeting and that person's like, yeah, I want to book a meeting.

25:01I'm like, cool, here's the calendar thing. I can do that. But if someone starts to ask about speaking and sponsorship, that's a common question we get it's multi-threaded it's not as good and i think because there's just some human nuance and okay do i feel like they're trying to ask me about speaking or free tickets because they want us they actually want to sponsor or do they just want free tickets they're kind of wasting my eyes and so there's still a little bit of that you know we do constantly monitor the human attention and responses specifically in this platform that we're using so again i do think it i think the unexpected learning is for artisan in particular probably any other outbound tool for ai for outbound it relies heavily on human consistency for training and iteration and quality of contacts like it's not a hundred percent it's not a hundred okay 90 of the contacts we've reached out to with our artisan agents are contacts we have they're not contacts i'm going at mining and lucia or apollo or clay or artisan has a way you can do it natively in the platform i just you know i trust our contacts more and so putting in all that data does require time and it requires consistency on our end.

26:22So when I've had more time, you know, the sequences and everything works better. When I've had less time, it still works on autopilot, but I see a drop off in the amount of responses we get. And that's because I just can't keep up with the AI. Six months in, I have to try and give it fresh context. It used to be I would do it once a week. Now I do it twice a week if I can, ideally, because it's gotten better. Jay Wright, like Empower Agents, has gotten better and so ideally twice a week would be better so that's i think the again unexpected learning there anything you want to add on outbound jason

27:02no i think i i that that i think that's a lot here is it's interesting i think there's a this is plenty i think the question i mean the conclusion obviously is that moving from the two human SDRs we had, the way we were doing it to AI, there was no downside in net, right? Yeah. Actually, not necessarily better. It looks like the open rates and response rates were roughly similar in the end, but we have 10 times the scale if I had to summarize it, right? Correct. Yep. I guess the one question that I might have in the audience is that's great, but what about like super high value prospects, the ones you would want to reach out to personally?

27:45How do you, how did we address that? How do you measure that? How do you think about that versus this is a broad swath of a lot of potential prospects? Yeah, it's a great question. Yeah, for super high value folks, I still put our AIs into draft mode across our agents, right? So there's different use cases where I want to hit different folks, different parties with a message that is maybe hyper personalized. or it's somebody who's actually met me and would know that you know my amelia get sasser.com is one of my artisan emails and not ameliasassdrink.com and so for those folks like no matter what platform i use artism does some of them some other platforms do others i pretty much put the agent's draft vote and i see what it says right but that still saves me time like having a draft that next email either next email or first email of you know whatever i'm trying to action with them as like the end goal is helpful versus me writing everything from scratch that's what's helpful i think i still spend probably the most time making sure the contacts are the right people i think where there's a gap right now is for a lot of these folks especially our high value ones i always have to find new people to cc which is manual like that no ai can do this yet trust me I've looked like no AI can do this yet.

29:10We're like, because we have so many CEOs and founders in our database, and maybe you sell to a lot of C-suite executives too. The biggest issue I have right now in the AI is not that it's not working or that we have high value contacts that it can't draft an email to pretty good and fairly customized. It's that you don't want to send it just to CEO, right? So if I'm going to email the CEO of Databricks, like I want to copy his press team, his chief of staff his cm if it's for something speaking probably the cmo too for visibility like i don't want to just send it to ollie like even though i have his email and he knows faster and there's no way to really do that in the like there's no good way right now in any ai to find those additional contacts and also include them in a in the sequence like right now across all across the board all of our platforms are one to one right so i think that's something where we're six months in i do think that will get better and the platforms will let you do that more so down the road but that part takes a lot of time right now that's kind of like one of my biggest pain points okay let's look to inbound because i want to try and go through all of go to market but i'm already 30 minutes i'll pick it up all right this is the inbound so there's some interesting numbers here on the right my zoom's a little bit in the way we actually have not had this for six months we've only had it since august so august september october a couple weeks of november three and a half months we have not had this one as long because i had it out on first and then i tackled it down again you got to stair step your use cases here on ai i wouldn't try and do everything in ggm all at once do one get it working and add another one if you want so then i added inbound we've had you could see it's had a lot of almost 700 000 sessions with people which we can never do physically and it's had a thousand conversations so like sessions versus conversation in this realm is that the sessions are either i think he counts it where it can answer itself whereas a conversation is something where the ai agent is actually conversing with the person more fully it's looking you know it's looking at his training it's answering it a bit more i think that's the nuance but don't take my word for it but it's still a lot of sessions and conversations and then when i took the screenshot it was 91 meeting bucks and then this morning it was close to 100 so we've had a lot of interactions with inbound now that's always going to be true right this is in now but this is the data i wanted to share because i will say i wasn't as hesitant as adding an outbound agent there's alternatives to artisan if you don't like that one i like that one because again it's highly specialized on outbound so i like that one because everything it does is to get the like similar results to what we're saying like that's literally its whole manifesto so i like to go specialize i know other people like to try and find one platform that can do like multiple agents and try and consolidate for a lot of reasons but i like to go specialize because i I do feel like the specialized ones for now still work a lot better because they go deeper.

32:24But anyway, so then when I added inbound, we've only had less, let's say, three months. The inbound agent has been responsible for already a million dollars of revenue. Now, you could say, OK, some of that revenue would have closed entry, right? It's inbound people are reaching out to SaaS or in this case, particular for sponsorships. you could say okay you know one that would in the old day six months ago that would have been routed to a rep somebody would have responded eventually gotten the meeting on the books and then you know hopefully i don't know i mean my data does show our win rates are better now with a on inbound than six months ago but assuming it was similar ish and still fairly high let's say you know 750 of that would have still closed the onus here is that it closes not only does it close a lot faster is what we're saying in our data it's also closing at a higher rate than previous to us six months ago so even though it is inbound and you could say okay there's obviously inherent demand because they're coming inbound this has given context to both the prospect and our sales team in a way that it's giving us speed so our inbound agent right now is definitely picking up speed.

33:45A crazy stat I just saw too, like 70 % of our October close one came from the AI. So you can see, right? There was a little bit of lag in August, September, and then most of that million came last month. But then we have like another 2.5 in Pi that is literally attributed to meetings and deals that came from the qualified agent. And that's magical in a couple of ways. Now, I know some people like to describe it as, okay, it's just a meetings booker. I could do the same thing with just a meetings booker. That's like round robining. And if I show that on the website with a little AI, maybe that's good enough.

Read the full transcript

34:22And maybe that is good enough for you. But I'll say the difference here of why I've become a fan of qualified for what we use on this tool is that it gives you so much context more than a meetings booker, right? Like even if you have an AI meetings broker that's doing round robin for inbound our agent is having conversations with people like it's okay well you know let me feel like let me book the meeting but first okay it puts the meeting instantly it used to be six months ago you had to fill out a contact form to start disaster then I would it would go to me I would round robin it so there's a delay like if it's overnight or on the east coast or a time I'm not awake there's a delay for me to round robin it then i send the round robin to the rep then the rep has to respond to that person and so that process is anywhere from within the same hour to a day later that's highly inconsistent six months ago now our agent is empowered to book meetings on its own and have a conversation so it's send it's not only booking the meeting instantly where this used to take up to a day at the worst gate scenario the meeting is instant but it's having a conversation with this person so that when i give into the sales team, like literally man damned, we'll go through, we'll be like, okay, what did they say to the agent?

35:39Did they say anything interesting? The agent can also show you other people who have been on the website. You could say, oh, hey, cool. Like this person actually booked the meeting with me, but I saw their CEO was on the site or I saw a lot of contacts from the same company were on the site. Let me see. And also what they were looking at. It'll show you directly. Okay. This is what they were reading on the website. This is what they were probably interested in and so that context just gives us a lot more like highly pre-qualified contextualized meaning right we don't really have to do discovery anymore because the ai has already done it the ai already knows what websites you are on it already knows who was on the site who was there how many times you visited the site and because we have ours on multiple domains it can also say hey they were also looking at xyz thing on saster.com like again we don't do discovery anymore we're like okay our agent already did it and already has the data we just use that to do like a theory of what we see like hey we saw you were looking at xyz thing is that actually one what you want to talk about today you know part of sales is still learning what their goals are just but we have it's so nice now to get on the club where we have that baseline with folks they appreciate it right that you're not doing you're not wasting 10 of their minutes on discovery you already kind of know what they're about you know what they're they've been doing or sometimes they're like oh i didn't know our ceo was on the site looking at speaking that's good to know maybe i should look at a sponsorship package on it when speaking the conversations of quality is anecdotally a lot better i don't have data around that but maybe we will now but it's just like that it can do that so that's an interesting context on selling something that is more of a higher asp right because for us i got tickets are like some$1 ,000 sponsorships.

37:27The most popular one is, let's say between the 50 to 100K range. There are more custom ones than that. But this is helping us with something that's at a higher price point. Closed one a lot faster and we're seeing a lot more of... I will say two interesting things before we move on to the next one. And then anything you want to hit Jason on this one, but I see a lot of folks who use Qualified that limit their agent, right? Like they limit it to talk to support or talk to sales and there's two buttons and that's kind of it. And then when I talk to other people's qualifies, I've seen it sometimes not as good.

38:05I'll be honest, it's not as good. And that's not a fault on the technology. That's a fault on the training. Again, if you take something that is A tier and make it even better, like we have, like I've empowered our qualified agent to ingest all of our websites. So across saster.com, which is 20 million words, saster AI London, saster annual, our YouTube channel, things I upload to it. I'm like, these meetings, I upload these meetings, I upload some of my sponsor meetings. I'll upload calls to it so we kind of know what we're saying on calls. because it can ingest all that. It does so much more than I think most agents do on qualified.

38:42And so ours in particular too is I think pretty good, but it's also pretty good because we've empowered it to be that way. There's a level of trust I have with my Amelia AI now that we've also, you know, I talked a little bit about the outbound piece of that's booking meetings for sponsorships, but it's also selling a lot of tickets. The inbound agent previously, right? You would fill out a form on the website. for sponsorships and then if you wanted to buy a ticket there was kind of nothing there was like you could email events at sastrink.com six months ago it wasn't great and it's you know the number one question our chat gets now related to tickets versus sponsorship is can i have a discount and so quickly oh i think a weekend when i saw it in the data with qualified we empowered the agent to sell tickets directly so what it does now and if you ask it that question or if you prompt it for that question, that you're looking, you're like seeking a discount.

39:39The agent's goal is to not only give you that discount, it will remind you. Because the agent lives on our website, it will know if you come back. And if you don't after a couple of days, it will actually, you know, like, hey, Jason, I gave you the code. We had this nice conversation as Amelia AI. You didn't use it. And then it reset to the code. Hey, are you still interested? And people then use that code. Again, I can't do that in scale just me. and it's something we didn't have prior to this so between our two agents it's now 20 of our ticket revenue for the upcoming london event we'll see where we net out for london and then where we net out for annual because it will have a lot more time but i think our ai just totally crushes it on this kind of stuff if you can empower it if you can get it to work in the same way man doesn't crush it so i love our ai i actually went to go film with qualified i mean i think it's called tavis to make our ai into a full-blown seller and supporter where it's gonna have my video and voice and so that will hopefully roll out by london and y 'all can play with it there in person too but i'm just letting it do more

40:59it's good yeah i want to keep moving because this data is so good we've said it before but when we look you know we're we're 100 days in here we're 125 days into using replet we're six or seven seven or eight months into using delphi if you're hands off with your agent not Not only will it not perform, not only will you not train it properly or iterate, you won't realize all the things it can do. It can do so. All of our agents, when you get good at it, if you just are really hands on with your agent, you work with it every day, you watch results, you're as quantitative and data driven as Amelia is here.

41:31If you get there, there is a pot of gold after that, because you will find your agent can do so much more than you thought it could. That is the magic. But you've got to push on. You've got to get really good at what you think it does and then open your eyes for other use cases. All these AIs get so powerful. They know all your data. They ingest everything out of you. And the underlying LLMs are so powerful. They can't help but do more. Yeah. You'll see, like, I'm reading some comments in the chat, too, where you're going. be you know our again my slash our theory is i like to go deep now with like specialized tools where i can just keep adding use cases and add agents within certain tools i don't use an all in one tool but i feel like the results are worth it and so that's why it's worth you know sometimes i have to put stuff in artisan and qualified separately and is it a little annoying of course it's a little bit annoying it's time consuming but am i going to do it because the response rates i think will be better in the long run for inbound versus outbound yeah so i'm still gonna do that for the foreseeable future it's gonna be a little bit annoying and painful that's true of anything outbound's always a little bit annoying and painful like it's not like the ai was gonna magically wave its wand and like glindify it like it's less painful and have more scale but i'm just still outbound you didn't like doing it before ai you're probably not gonna like doing it else okay a quick one here because i do think i don't want to all agree i have like more use cases but maybe i'll have to do a part two ai and gtm the there's this middle ground and i do want to spend some time on this because i feel like most people have a misconception about the next product which is asian force i do feel like like when i talk to people about it they're always shocked they're like what do you mean i've either they've never seen it so i put like more screenshot or like not sure how to use it because i don't know i think because it's from a and you know an existing company versus a it's an incumbent versus a startup i don't know but anyways i guess reaction but i'm like yeah part of our core stack now is asian force so i'll explain agent force i've gotten to know their team very well they're all fantastic humans let me say they are the nicest people on the planet they're like some of the best people and i now have also you know i love the qualified team i've gotten to know jasper and artism part of this is i do trust the human that are on the backside i think that's if you're going to pick an ai vendor i do think that's part of it like you should trust the humans like you should want to work with their human counterparts like i call replets team replets humans like replese humans like we went there this week i was like oh we're gonna go see replese humans i'm like but i like those guys and i trust them so same thing with any vendor you've said but we have this middle ground where i've gotten to know their team a lot and they you know i think publicly they say their number one their number one use case for agent force is support and i'm building a 2.0 agent that with somewhere between support and like personalization but our first agent that we've deployed and this was recently so this was just right at dream force which was like a month ago so it's only been live a month this is our newest agent right because i had ours and i had qualified and then i added a bunch of other stuff you'll see in marketing then i added agent force in we had a gap where it wasn't inbound in the way that call like qualified is it wasn't outbound and the way that artisan mostly is, I had this gap where, embarrassingly, post-SAS Reannual, I was like, we literally, just from this SAS Reannual, have about 1 ,000 people our sales team we never followed up with.

45:28These are people who literally filled out that form I was talking about earlier, said they wanted information about SAS Reannual. I routed it to a rep, and then the rep did nothing. I found 1 ,000 of these people, which is all the bond. Like, I can't kill, I'm not gonna go, I should email those people an apology one by one and email them but that again that would take me too much time I need to scale and so I thought okay this is probably the best first use case for an agent force agent because these people raised their hand meaning they're already in our sales force because that's how our forums used to work and I already have info about them in sales force whereas like artisan does a lot of personalization based on what they're posting this the magic i would say the agent course is that it knows everything your sales force knows which sometimes i say that to people and they're surprised i'm like what that's the beauty of it like it has all your sales force data if you like click a button and you want it to and then you can use that to then sense the context of the email so i'll show you what i mean next but this was our for SeizeCase.

46:36We had a thousand leads nobody wanted to follow up with. So it's now sending outreach to mainly those people. Like it's still working. Again, it's newer. So it's still working that list of a thousand. I also capped it, right? Whereas like ours is doing 300 ,000 a month. It's doing 3 ,000 a month on month six. Like agent forces very much on, I would say month one, at the end of month one, going into month two. So I've capped it. So it's still emailing those thousand people that we ghosted but then i also started adding people where if i have a conversation with them for a deal cycle it starts to email them a follow-up because sometimes i'm really bad at them between those two use cases what we've seen and this is early days is a higher response rate so far and a huge open rate like again the open rate is 72 it's freaking high you can't get that in marketo you can't get that with a human that doesn't send that email the open rate is zero at equals zero for an email that was never sent and even though it's early days i'm fairly bullish on this one because the early data is pretty good so i have liked it for that i think it's a good use case that more folks are getting into okay first you know forget support is their number one kind of like agents in the world most people deploy find whatever but are qualified to support so like i posted one that did sales and you'll see i put two sample emails here this was like a follow-up email to again somebody we ghosted and for this agent because it's early days i haven't empowered it yet to do bookings itself so that's why it's asking for a meeting versus like just showing a direct booker and kyle responded literally right away and said you know no thanks but all attend again never would have happened six months ago because our sales team nothing against that they just decided not to follow up with these thousand people and yeah you could say maybe i started with the use case that is low-hanging fruit sure but why also why wouldn't you i already have so many uses the other agents that we use that i wanted one that was near and dear to me because i was like if i inbounded to somebody and they never followed of salty well like maybe because the ai has data you know them being in our sales force and what their company has done with us they get some like a nice note like you know so i don't know that's where i went into it the other thing i'll say about asian force which was alerting is also there's two slides there so if we're flipping ahead on the deck because somebody asked this earlier actually about the setup of it like it is within the ux of salesforce right my biggest learning was like i am i will admit i am not the greatest sales force user on planetor i was not the greatest user six months ago i've definitely become a better user now in this process but i wouldn't by no means like you know i'm not even certified not even certified like i know that a lot of people i'm not mercantil certified either so i but i would say like in my rankings of tools in our stack six months ago, I would say I was a lot better at Marketo than Salesforce.

49:57And I pushed a lot of things from Marketo to Salesforce, just because that's what I was trained on in the early days of the marketer versus Salesforce, which was a sales tool. Only back in the day, they just wouldn't give you access. And so I didn't know all the nooks and crannies. I learned a lot of them in this process. And so I think there's a misconception on it's super technical and nobody can get it to work that's like the number one thing i hear but honestly one i had help with all these platforms artisan helped us help set up artisan qualified helped us set up qualified salesforce helped us set up asian for it like all of these it wasn't just me like we did a lot of the trading and tuning once we knew how it worked but they helped us with the setup that's not vendor agnostic right now and i think it's true any good vendor in AI right now.

50:45They do have to help you and they should want to help you get successful. They want you to have the same numbers on results we have. I think this misconception of, oh, I can't use agent port if you've been on Salesforce because it's probably too technical or it's going to be doomed to fail or I probably can't get, I'll need either a third-party agency or like a Salesforce admin. So come do this for me. I'm not a Salesforce admin. I figured this out with their help. so again i think it's for many tool where you'll need their help at the start for sure like now i need less help now i get how this works but you'll see too like a lot of things even though they don't look the same are kind of the same concepts so once you learn one tool because i learned artisan first like this is for reference the artisan setup where this is only two screenshots of a very long page and it's great but you're seeing like i'm putting in what is this one for this one's for london tickets i can tell because of what i put in my proof points and then there's coaching right here that i put in then there's other things you have to put in to the setup this is not dissimilar to that where i'm putting in instructions on the prompt builder similar to or actually copied my total page of course actually copied all the instructions i put into artisan i just put them into agent force and rewrote them for this use case of email people who haven't been reached out to and then it worked so like some of the training you do is again maybe not going to look physically the same but some of the same concepts i think are core across any ai tool you use where again between the ones i've shared so far artisan qualified now salesforce slash agent force like this logic that i had to learn six months ago okay this is how you tune an agent.

52:35This is how you train it. This is how you consistently update it. It does have this kind of universality to it, which I know seems a little funky. But once you kind of learn how to do it in one, it is easier to do the others. I don't think I could have gotten successful on having all these agents and now learning how to vibe, go to replet had I not taken the time to learn the foundations of one of them and go really deep so that I can basically speed through the other ones and say, okay, I kind of know a version of this. I kind of know the concepts. You just start to learn how to talk to AI and talk to the agents and the models with your data in a way that, again, no one can teach you.

53:14It's just something you've got to go through yourself of, okay, I've learned now how to talk to Repli. I've learned how to talk to our agent birth agent. I know how to talk to Qualified. I know how to talk to Repli. Again, certain universalities are there actually six months in where if you learn one, you can figure out the others because they're not dissimilar to one another.

53:36Okay, there's a lot of questions. There's eight minutes, but I haven't really gone to all these. What do you record, Jason? Should I keep going or should I just do questions and do a part two? You're on mute. Sorry, let's do questions. I think the SDR outbound and inbound is so important. Let's take questions and then let's break this up into a part two on the rest of GTM and AI agency. Okay. I can do part two next week, guys. It will not be long. I can do part two, but I haven't even touched on RevOps, CS, and like marketing. So there was a lot there. Let me go back to question. Oh, some people are like, keep going.

54:11Like, do you want to be here? Or let me go back to question. We go back to a few key questions and then I'll do a quick overview and we'll do a part two. So I'll meet you guys in the middle if that's the piece. Let me go back to the start. Let me go back to the start.

54:37Someone has asked, what are the tools you are using with success? Yeah, they're in this deck and then I don't, sorry, a lot of you asked for a link to the deck. So I'm going to put that in now. It wouldn't let me do it while I was talking. you have to refer

55:00sure

55:04order offensive to Jason hold on I do think this is important because if we're going to do part two you guys can also tell me what you want to see in the next one okay let me get you guys the link

55:27Megan it's not everything can be sold by something you have to do yourself like finding this link in a very roundabout way but I've got it and also you guys can keep asking questions I will all stay on I can go over so if you guys want to stay on and get your question answered or if you want to watch the replay later that is good by me so copy we can try okay slides there we go okay there's one first major question my thoughts but somebody else is asking what's our tools and stack as they join light so at the beginning of this presentation but if you also go to faster.ai slash agents we talked a lot about these tools so this has all the tools you can see I really didn't make it far.

56:22I only made it through 30. The ones I was going to go through today. But we have a few here. So you can go to saster.ai slash agent. There's a little bit more on all of them here. And then I'd link this deck where you can, we'll draw it on saster.com too. So that you can also see it there. There's a few good questions here I think on the earlier part of the session that was about inbound and outbound.

56:56some folks were asking what is our cost for each of these tools i think it's and how you should budget for it it's a good question i want to get your thoughts on this as well jason mainly on the budget side i would say for cost one it depends on what you're going to use it for and i'll give a quick antidote i literally spoke to a 15 million dollar arr cmo this week and he was like oh i have 10 betas going and i was like why do you have 10 betas right now because i'm in a bake-off with you know three different outbound aisdr tools like two for inbound a couple more from all-in-one tool i was like maybe don't do that maybe my advice is to stop all this i was like why you know i just want to see which one works the best before i spend money i'm like i think you got to make a bet here dude like i think in trying to save money you're actually spending a lot more time than you are really would just deploying these and getting the outputs of ai by doing these 10 different betas i was like just pick one and if you feel like the cost is prohibited work with the vendor on the cost see what they can do for you if not go to i can go to their competitor if you need to but i was like don't do 10 trials because you think it's going to magically save you money in the end on ai this is like the craziest thing i've ever heard i think and to be it is to first of all one i don't think you i mean it would be nice to have a bake-off but unless you're going to invest the effort to truly train all of them it'd be hard to do a bake-off than more than two vendors you should do a bake-off for a variety of reasons there's different flavors different ui ux different limit they all have limitations they all have limitations so i would bake but i wouldn't do 10 because you won't put the energy into training them the bake-off will fail with 10 i would do two just like in the old days the one thing i would say amelia you could add to it is what's the pricing they asked you can talk to the vendors yeah here's the tough part basically all the vendors that we're describing for this, for GTM sales type motions or marketing BDR, whatever you want to call it.

59:12They all require training. They all have a fair amount of data. And really they're mostly optimized kind of around a hundred K price point. Now, sometimes it's 60 or 70 K annual and 30 K to pay you for the onboarding and training. Some of the vendors absorb some of the onboarding costs. Some don't. There are lower end versions, but it is all in the tens of thousands of dollars a year or more, and probably more like 20, 30, 40 ,000. Artisan that we happen to use is launching the low end version, right? I think everybody will, and we will be on top of that. We will be on top of that and we will test out more of these cheaper versions and see how the more automated training works.

59:56I'm not skeptical with where LLMs and AIs are going today. I think I can guarantee you that the low-end cheap versions just, and this is true in support, which is further along, the low-end cheap versions aren't as good. And it's not that the software isn't as good. I just did a deep dive with G2 on the CEO of Zendesk and we talked about it. And Zendesk can support the low-end agents work. They just don't ingest as much data. They might ingest your wiki and a little bit of information. And so the low-end Zendesk AI agent is still good, but it may be only has 20 % of the power of the enterprise version.

1:00:27And I suspect that's what's going to happen. Instead of training this on every bit of data we have for a decade, every interaction, every customer action, it's just going to simplify what it trains. Maybe Amelia feels it differently. And so it won't be quote as good, but it may be plenty good. It may be plenty good for$299 a month or 10 grand or what. We don't know. We're going to be objective. And I think if we do nothing else, we're going to pilot the low, some low end versions of these, and we'll compare and contrast for you. But I am not aware of in right now, as this is recorded, I'm not aware of any cheap AI, SDR and BDR tool that works because of the training, ingestion and data.

1:01:03But I wouldn't rule it out for 2026, but I would budget 50 to 80 grand or more. And if you can't afford that, don't expect much. Just don't expect. No, it's a good point. And I think the bank off thing was interesting because that was something I was just kind of shocked when I'm like this. I was like, well, I know you're trying to save money, but I don't think this is the way to do it. It's just too many. I was like, it's just too many and too much. Like, you're either going to say that they all suck or you're going to kind of pick one and it's going to take you too long to actually implement it.

1:01:40This was a CMO. I was like, no, your CEO is going to get frustrated with you. There's a lot of problems in doing too many make-offs for all these AI tools in the vein of saving money, right? there's other reasons you should do it to jason's point but i think in the vein of saving money i like this is not the way to save money the other thing i'll say about budget i think the 100k range is right somewhere right below it somewhere maybe right above it depends on what you use it for pricing does fluctuate based on you know uses but the other thing i'll say about budget that i've come to learn from folks too and then like trials yeah a lot of these are going to be rolling out self-serve versions right where it's more of a paid to go or you know you can try it for a few months and see how it goes and see if you get some of the same results we do but i would say too like the thing that you should budget that is maybe more important than the direct cost is gonna be time so we also were able to reallocate budget right there's certain things you could do where this was not new budget i had for all these tools that i went to jason and said hey can't for Asian Forth Qualified Artisan.

1:02:50But also around the time of our event in May, a few people left semester after. And so I was like, okay, instead of replacing that headcount, which was already budgeted, I will replace it with the tool. And so that's another way to do it. Like, I'm not saying to fire someone and then hire this tool instead, but if somebody - No, but we replaced two human, the budget from two humans to support our agents. And we didn't fire anybody. I really think natural attrition is going to create your budget more than, you know, if you're going to fire someone because they don't perform, just fire someone. Like you don't fire anyone good to replace them with AI.

1:03:23If you haven't learned anything, if someone's failed, if they can't close anything, or if your AI SDR hasn't set a single appointment, I mean, your human SDR, maybe just replace that budget with it. You know, if your SDR can't do anything, you know, you can't do worse than zero. But we'll track it. Many of you, if you're early stage folks watching this, you'll think that's expensive. and if you don't believe in the vendor, it will seem very expensive. It will, because you'll get quoted by a sales rep a lot of money and it will feel risky to you if the deployment doesn't work. You know, that's why we're not trying to be walking billboards, but we do share the vendors that we use.

1:04:01Others are good too, but if you get the right people, it's going to work, but it can feel risky. It's tough to start at 500 bucks a month today, but you got to take a little risk in life. Yep. There's another question for, I think, related to Outbound for what this question would be. Let me ask, can I add one more thing on pricing? It's interesting. All of the vendors have too much demand, including Salesforce. They have too much demand. And so you're going to hear that manifested with some of them where they might not take your business. And the main reason, Amelia could maybe share other anecdotes she learned.

1:04:42I've seen it just a few ways. she's seen it more often because she interacts more with them. If you don't have enough data, if they don't think you have a rich enough data source to train these agents, they might just, even if you have the money, they may not take your business. We've sent a lot of business to our, the vendors we use directly, or just by doing this, we generate millions, we've generated millions of revenue, dollars of revenue for all these guys, just by sharing what we use. That's the nature of the beast, but they turned away a lot of business we've sent to them. a lot of business.

1:05:12So don't get flustered, but just be aware. Not only is it not dirt cheap, but if you're not an appropriate candidate, it's bad that they have too much business and that it's like everything in the eye, folks are overwhelmed with demand. But also if they tell you they can't support you, ask why and listen, and they're probably right. Yep. I agree. I think the biggest other thing I've seen is like, I either through this webinar our content we post, right? Folks will then reach out to these vendors or they'll ask me and I'll say, hey, I'll just make like an intro to you to the team because now I know them.

1:05:46And, you know, I'll be like, hey, did that ever work out? Did this person that I referred you actually sign? Some of them do, some of them don't. So they do have a lot of demand which shouldn't turn you off. But also they're going to go through with you and the way they did with us. Sastra is not unique to this because I saw another question in the chat. are we getting you know special upgrades from some of our vendors help on pricing that are public some okay now those three vendors i just focused on today have become sponsors of saster sure if artisan hadn't artisan actually sponsored saster before i became a customer so if they hadn't sponsored maybe i would be on a different my isdr tool talking about it but because they were a sponsor i did the classic thing if i just went to the founder jaffer and i said hey i want to use this post-annual can you help me get like the best person on your team to help me set it up because i didn't know as much at the time and can you help me figure out like yeah what is your pricing how does all this work and so we were i just went to the ceo but again i think if you know the ceo of a company you're going to do that anyway that hasn't changed in my life and i put it in the chat there are a few features specifically like beyond pricing we're in a lot of beta features i would say with all of these vendors across the board so we spent the most of the time today on sales but also in marketing most of the things you'll see next week because i'll come back and do a part two we're in beta features and i think that's partially because one this is not like a hubris thing but a lot of vendors have told us because we have so many agents were a lot faster now at adopting them than just maybe a typical sass company slash off the street company i think too because we spend so much time with them i think of more use cases right i'm like okay i started using it for one thing now i want to just pronounce it and i'm like wait can it i'm like maybe can it do this or that or maybe can it do xyz thing and so i just email you know the founders our cs rep whoever it is i'm like hey can the agent maybe do this if i have this use case of like the next use case and sometimes the answer is yeah that's usually the answer i would say is yeah that's already on the roadmap but we can give you access like we can have you guys test it break it and so i we do get access to things but also because we want to i want to test these things i have no comfortability with the ai where i want all those data features so i can be like okay if i break it or if it hallucinates i understand the risk there testing something that's not fully released but i will say that's my disclosure but we do have some features on each of those tools that are not publicly available yet but some of them are like either just launching in the new year or soon but i don't think that's unique maybe that's unique disaster but i also think it's there's a want there for there's a like i personally have a want to do some of those things and they have a want to test some of those things yeah but let me I think it's a good question because we do have a lot of success.

1:08:48Some folks think it's because we have so much data. We thought in the beginning it turns out to not to be true. You just need enough data for these tools to work. You don't need 10 years of data. Six months is enough. You need a volume of actionable data. You don't need to know who came to SAS or annual first meetup in 2012. That data really doesn't help. Okay. So it's not so much data. Do we get special treatment? I think we do. We get the best people at these vendors helping us, the best FDs, the best onboarding folks. And so I want to tell you a counter story just to help you qualify vendors.

1:09:19There's another vendor on this list that we thought about using. Great founders like them. We were routed to a very mediocre sales slash onboarding person who really didn't want our business. Told us we couldn't use certain features and was a pain to work with. And so we passed them by and we never used them. Do that yourself. Talk to these vendors. If you have a bad experience, don't use that one. And don't also in the age of AI is where I'm getting frustrated. Don't get bamboozled by a sales rep that doesn't know the product or isn't technical. Ask to talk to an FTE or a solution architect or an onboarding specialist.

1:09:59Don't waste your time with an idiot sales rep. I will tell you some of the very best AI companies across the globe, not just anyone's we're talking about. the best ones I know have really mediocre sales teams that do not understand the products they're selling. They just don't understand how AI coding tools work and how AI support tools are trained or how any of these tools are trained. Don't stand for that in the age of AI because a rep will tell you something that's just wrong or they won't understand it, bypass it and say, listen, if you want my real money, I want to talk to the person that's going to be onboarding me and own it.

1:10:32And if some blocker that last worked at, you know, a dated B2B company five years ago and doesn't know AI won't let you talk to that person, find another vendor. You deserve it. You deserve it. Assume the sales rep, unless they're technical or know their CRAP or have done a deployment. If they hesitate on an answer, talk to somebody else. And so we just didn't deploy one of these agents. It's probably as good as the ones on this list. It's probably just as good because we had the idiot sales guy that he lost all this PR revenue promotion friends and just ran the deal into the ground and you deserve to talk to an expert an FTE or whatever it is before you sign before you sign and we did with Harry and Rory we had Mark Benioff on about a month and a half ago and we talked about what's the number one thing you wanted at Salesforce he not only do they does he want to have thousands more forward deployed engineers on agent force and AI.

1:11:29He said he wished, obviously it's not practical at 44 billion in ARR. He wished every company could deploy their agent and have value before they sign their contract. Okay. And it's not practical for Salesforce. It's not even practical for the folks, the startups on this list, but you should demand as close to that as you can. You should demand that you at least talk to an expert who in 20 minutes can tell you exactly how successful your tool will be. They'll go, that he can just look, he or she can just look at your Salesforce data, look at your upspot data look at your marketo data do whatever data pop up a little bit and say yeah listen i did this with 20 other customers and clients this will work or no it won't work you deserve that you deserve that if you have to pay 20 grand for it for the training it's going to be your best 20 grand that you're going to pay this year yeah the other thing i'll say to add on to it and then we can answer a few more questions we're going to do two next week somewhat related to cost like i like i said we we replaced headcount spend so i reallocate i shouldn't say replace i reallocated headcount spend into some of these tools that will start to happen at your org as people naturally leave for no matter what the reason you can start to say okay can it is it a role where i can start to earmark that budget and move it into a bucket that would then be an AI tool that, again, I'm not saying you have to replace your entire SDR team with AI and get these three agents that we have.

1:12:54You can. We've done it, but we still have humans here too. I'm saying the magic of this is getting the best A-tier players on your team that are still there to become S-tier with AI. So I think there's some of that. And I think a lot of folks I talked to, which you have more common, you probably do too, Jason, just say they're not going to add headcount. so that they can empower their teams, either Q4 2025 or Q1 2026 with these tools. Like they're just, again, reallocating budget that they would have to say, okay, instead of growing the sales team from five to 10 humans next year, we're going to keep it at five, but we reallocate some of that spend to the tool so that those five people can be asked here.

1:13:36I think that's a good way to think about it. The other thing I'll say, we're not immune from people roasting our AI. And so I think how that kind of plays into cost, if you decide to roast an AI in the beta, because maybe it's not very good. I don't know. Listen, I don't know all the tools. I know a lot of them. I've seen a lot of them now. I can't say I know them all. There's so many of them. I do try. If we can't use it for ourselves, I do try to at least learn all the tools and their capabilities so that when folks ask me for recommendations, I can make at least an informed answer. So I don't know all the tools.

1:14:11But I will say there are instances where people roast our AI and they've roasted all of our inherent vendor because they roast our AI. I think to some degree, that's a little bit okay. And your team should be maybe a little bit skeptical. And maybe the outputs and the outputs are never going to be perfect, but the outputs with the human are never perfect either. So maybe if there's one final takeaway before we answer the last question, if it wasn't working pre-AI, it probably still won't work now. if it was working or it's working kind of good and ai can get you that leverage then as we've seen in our results then it's even better but it you know if you hated outbound pre-ai you're still going to hate outbound it's hated if you didn't have the best support or you still don't have the best support documentation for your ai to ingest then your support is still probably going to be b tier versus f tier there are times where our agent can't answer a question and it's a support question i'm like that's my feeling that's and they should i know people roast the ai in those times when you know it's happened i put it somewhere in a slide i think less than 10 percent of the time or i think three percent of the time well yeah we'll touch on it next week less than three percent of the time but when they do roast it i'm like you know what it's not even a failing on my ai's fault it's actually a failing on my fault like it's something they're asking the ai that i didn't train it on i didn't do it on even though it has 20 million words there are certain use cases and scenarios where you ask certain questions that are 20 million words you not have the answer to and they were not going to have the answer to pre-ai and they don't have the answer to now last couple questions then we'll wrap and we'll come back for part two next week there's a few specific questions that are fairly technical but i think they're good ones just so you guys are thinking through this as well so the first one's on artisan so i'll come back to here which we use for outbound there's two questions on it one someone has said have i played around with the legion contacts that it has related question is have i seen artisan engaging with duplicate contacts in a smarter way than maybe a human would is there anything built in to prevent bombarding inevitable dupes so on the first part have i experimented with their legion contacts yes i commented on the chat i just started so like to this point if we're six months in i is 99 of the contacts there are i just started using it to see how i i wanted to learn i wanted to see how it does on completely cold outbound contacts but that's a new experiment i'm running so it's really for me to say yet if the data was it's a contact data was good enough for us to keep outing but again i don't think you with the beauty of artisan is like even i used to train like the sub eight you can call it sub agents you can call it sub campaigns whatever

1:17:15separately the it's too early for me to see on you know outside contacts but i do want to assess it because there's other things we use when for instance i need to find a new email for a contact that existed in our ecosystem, which I think is a lot of people, but it's not there anymore. We have a lot of contact. We've got 12 years of Satsangl data, like six Europas now. People are not all at the same job. They may still be in Sats and they still may be at a company I want to reach out to. And that's where I use contact arrangements to get their new contact. A lot of people, we have Gmails, I will say.

1:17:50We've been very careful since the start to get Gmails to folks. So you're not going to change your Gmail. So I have those. But for context, I move on, which I think is a common occurrence for most folks. That's where I'm testing it. So it'll be interesting to see how that pans out. Now, on the question on dupes, a lot of the... I will say I don't get dupes within a single agent. So Artisan has... Artisan will de-dupe your list across multiple campaigns, multiple agents. Qualified does the same thing. Salesforce does the same thing. Where there's a gap is because I have three. I have to be super careful in saying okay this bucket of contacts going to artisan this bucket going to qualify that bucket going to salesforce and then inevitably all contacts yeah all contacts throughout the salesforce because we use work that are wishing to salesforce and so they're kind of all already in salesforce anyway and so I don't really see a lot of do for one vendor so So if you only use one vendor, you won't have the issue.

1:18:51I do. But my issue right now is I have to be super careful in manual oversight to make sure those contacts are not getting hit by three different agents. Those three agents as of right now mostly do not talk to them. They're getting there, though. I know Artisan just pushed an update where you could turn on a toggle and you can pick what Salesforce campaigns you want it to exclude. So that's great. So it's starting to solve for this problem if they know some of their customers, like us, have multiple agents that don't all live there. Qualified already syncs natively to Salesforce, so it kind of has that toggle by default.

1:19:28So again, because the backbone of all these three is that Salesforce is the common denominator, it works. But I do think it's an interesting nuance there. Like you may not have a problem if you just go deep on one, but I've got that problem now where trying to get data across different agents is sometimes right now a little bit manual, pushing it to a few different places. That's inevitable. But again, because we're getting good results, I think it's worth it for the interim.

1:20:03Last question and then anything you want to ask. Jason, in the end, let's do it. Somebody asked me about how to trigger all these, which I think is a good question. It's fairly technical, right? Let me stay here. So they're all, again, the underlying foundations and training are all a little bit the same, but particular to the vendor that you use. And so the way you can trigger in i'll just go to him for you real quick the way you can trigger in ardent in is you can upload a list that's the easiest thing you can do you can just export that that's what i do honestly i just export or again i don't want the contacts to be in the other two agents i export the contact i upload them that's the way i do it that's the easiest way to do it now you can't there's other ways you can do it you can like i said now you can kind of like cherry pick from certain sales for campaigns or contacts that you have.

1:21:00You can do just like a search, like an intent search on there and do it that way. I use CSV. It's the easiest trigger. Also because I don't, I've seen this, I don't know if this is like a, again, a platform thing or a me thing, but I've played different sizes in our design, really different campaigns and different audiences. But I see 800 to 1 ,000 as a sweet spot. So the other reason why I do CSV is I want to keep it in that band because it seems to perform better for whatever reason. I keep it in that band. Triggering on qualified is more so automatic. So also the user can just talk to the agent.

1:21:36So if you guys go on Sastra London right now, you could talk to my Amelia AI. That was something where in the early days, I used to, I still somewhat do it, but I used to monitor a qualified like a hawk in me. Like, what are people saying to Amelia AI? Is she giving the right response? Is she saying the right thing? Now I've obviously built some like trust and comfortability with it and I let it run. Yeah. And it will tell me if it needs help. Like it'll raise its hand and say, someone's interacting and needs your help. And then I'll jump in. But now if she doesn't say that, then I just let it go.

1:22:06We'll autopilot. So that's how that's triggered. I'll talk next week in part two, how I trigger some of the emails that it's doing. I made the earlier case of if our agent gives you a code, it sends you an email follow-up in a few days. I'll show that more so next week on the marketing side, because there's different ways you can think about using that use case that's relevant for you. and then in agent force the trigger is i'm a screenshot for it so to be pushing but the trigger is based on either the you can do it on a lead level contact level or like a campaign level it's i will say that portion of it i think i think they just pushed it i think you know as we were rolling this out we did it very manually just to make sure it wasn't like spamming a thousand people all at once but then since then i've been able to say okay i've got like a list of contacts already in salesforce i can put them into a campaign and then i can match this i then i could just have the entire campaign go live on the agent and it'll parse it out the way it thinks it should right okay you got a thousand people i'm looking at them all at once i'm going to see what time zone they're in i'll look at the times you want me to email those folks and i'll just start to queue them up you can do it either way it's actually gotten easier so i commend them on that it's gotten easier on how to, in our use case for this sales, this sales motion that we use it for, it's gotten easier to trigger this particular flow.

1:23:37Anything else I want to wrap on? Sorry, we have to do part two, guys.

1:23:44Good? Okay. Cool. Thanks, Amelia. Great job. Appreciate it. Yeah, you guys can keep, you can, I'm just, like I said earlier, I'm just Amelia's strengths. If you try and answer any additional questions, I'm not on LinkedIn that often, but I will add you in the week when I check it. And then we will do part two next week. So I'll send that as a follow-up to everyone so we can cover the rest of GTM. And then I'll do a much shorter version of this at SaaS for AI in London. If there's anything you want to see in particular for part two, I've already gotten some good ideas from this. Just let me know.

1:24:19I will put it into part two, and then we'll see you next Wednesday.

1:24:24Bye, everyone.

1:24:56Hey, Sasser, imagine having agents for every support task. One that triages tickets, another that catches duplicates, one that spots churn risk. That'd be pretty amazing, right? HappyFox just made it real with Autopilot. These pre-built AI agents deploy in about 60 seconds and run for as low as two cents per successful action. All that sits inside the HappyFox Omnichannel AI First support stack. Chatbot, Copilot, and Autopilot working as one. Check them out at happyfox.com slash daster.

From the publisher

SaaStr 830: 6 Months Later, How Our AI SDRs Actually Work as AI Runs GTM with SaaStr's CEO and Chief AI Officer

In this episode, SaaStr CEO and Founder Jason Lemkin and SaaStr's Chief AI Officer, Amelia Lerutte delve into their journey of integrating AI into our go-to-market strategy over the past six months. Starting with just one AI agent before SaaStr Annual in May, we've scaled to roughly 20 core agents by November, covering various use cases across marketing, sales, customer support, and operations.

Together they discuss the specifics of our AI implementations, the tools we have deployed, including Artisan, Qualified, and Salesforce's AgentForce, and share valuable insights on their performance, benefits, and challenges. Tune in to learn about the unexpected outcomes, the time and management required, and the significant impact on our efficiency and revenue. 

 ---------------------

This episode is Sponsored in part by Salesforce:

Connect data, automate busywork and empower teams like nobody's business with the one platform that grows with you, every step of the way. Learn how Salesforce works for Startups at salesforce.com/smb.

 

 ---------------------

This episode is Sponsored in part by HappyFox:

Imagine having AI agents for every support task — one that triages tickets, another that catches duplicates, one that spots churn risks. That'd be pretty amazing, right? HappyFox just made it real with Autopilot. These pre-built AI agents deploy in about 60 seconds and run for as low as 2 cents per successful action. All of it sits inside the HappyFox omnichannel, AI-first support stack — Chatbot, Copilot, and Autopilot working as one. Check them out at happyfox.com/saastr

More from The Official SaaStr Podcast: SaaS | Founders | Investors

All 68 episodes
SaaStr 830: 6 Months Later, How Our AI SDRs Actually Work as AI Runs GTM with SaaStr's CEO and Chief AI OfficerThe Official SaaStr Podcast: SaaS | Founders | Investors · 1 h 25 min
Listen in VO