SaaStr 830: 6 Months Later, How Our AI SDRs Actually Work as AI Runs GTM with SaaStr's CEO and Chief AI Officer
episode
The Official SaaStr Podcast: SaaS | Founders | Investors
1h 25m
3 speakers
8 chapters
transcribed 15 days ago
Transcript
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Transcript generated automatically by AI and may contain errors.
How did SaaS tr’s AI journey start and what were the first use‑cases?
Welcome to the official Saster Podcast, where you can hear some of the best Saster speakers. This is where the cloud meets. Up today on the Saster Podcast. Don't fire anyone good to replace them with AI if you haven't learned anything. If someone's fail 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 a you know, if your SDR can't do anything, you know, th you can't do worse than zero. But we'll track it. The 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 s because it 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, we 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 gonna work. But it it can feel risky. It's tough to start at five hundred bucks a month today. But You gotta take a little risk in life. Hey everybody at Saster, 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 slash SMB. That's Salesforce.com slash SMB.
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Alright. Hello everyone, welcome. All right, um, welcome to everyone in today listening for 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 of May, we really only had one agent that we had sort of just deployed. And now we have about twenty 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 has it 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. Um, but 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, help answer your guys's any deep dive questions too. So with that I try and keep the dingy patterns. Let's go through it. So what do I mean by six months of AI running RGTM? Now it's not on full autopilot. So it is not just that the AI is running amok with RGTM on its own. It does require a lot of oversight and time and management, which you'll see here today of 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? If 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 this is Sasser.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.
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Chapters
8 chapters
1
How did SaaS tr’s AI journey start and what were the first use‑cases?
0:01–11:12
2
What challenges and unexpected learnings emerged when scaling from 1 to 20 AI agents?
11:12–23:08
3
How do the different AI agents (outbound, inbound, support) work and what metrics show their impact?
23:08–32:59
4
Why is human oversight still essential for AI agents and how much time does it require?
32:59–43:06
5
How does SaaS tr measure ROI and revenue lift from AI‑driven outbound outreach?
43:06–53:51
6
What are the cost considerations and budgeting tips for adopting AI tools like Artisan, Qualified, and AgentForce?
53:51–1:04:05
7
How can organizations avoid common pitfalls when integrating multiple AI platforms into GTM?
1:04:05–1:15:10
8
What next steps and future topics will be covered in the upcoming part‑two deep dive?
1:15:10–1:25:25
Speakers
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