Nov 21, 2025 · 1h 25m · saastr
6 Months Later, How Our AI SDRs Actually Work as AI Runs GTM with SaaStr's CEO and Chief AI Officer
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions
SaaStr's Jason Lemkin and Amelia Ibarra provide an in-depth analysis of their six-month journey deploying twenty AI agents across outbound, inbound, and mid-funnel go-to-market motions. They share transparent performance data, procurement frameworks, and tactical lessons, highlighting that meaningful revenue gains require hands-on human optimization rather than reliance on passive autopilot.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Jason holds 16.2% of the talking time here. How this is scored →
Jason as informed peer 4.1 Guest teaching 2.8 Guest disagreement 0.3 Jason pushing back 0.5
speaking balance: gold is Jason, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 57:25 Guest rejects running ten concurrent vendor betas
Amelia strongly dismisses a CMO's approach of running ten simultaneous vendor trials, calling it the craziest thing she had heard and arguing it wastes time under the guise of saving money.
Hardest push from Jason ▶ 1:09:20 Host challenges reliance on non-technical AI sales repsJason forcefully warns buyers not to accept answers from sales reps who lack technical understanding of LLMs, urging customers to bypass them and demand forward-deployed engineers.
Biggest teaching moment ▶ 45:40 Guest demonstrates value extraction from ghosted leadsAmelia shows how deploying an agent across 1,000 neglected leads produced a 72% open rate and immediate conversions, proving the commercial value of mid-funnel automation.
Jason holds their own ▶ 58:55 Host breaks down enterprise agent economicsJason draws on executive discussions with CEOs across the ecosystem to explain why sub-$500 tools fail to match enterprise agents due to data ingestion limits.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | Jason as informed peer | Guest teaching | Guest disagreement | Jason pushing back | Why |
|---|---|---|---|---|---|---|
| Core Philosophy: Cloning Top Performers and Scaling Working Playbooks | 6 | 2 | 0 | 0 | Jason builds on Amelia's framing of cloning top performers by explicitly stating the fundamental principle that agents cannot fix broken playbooks, only scale working ones. Both colleagues are in full alignment, sharing their mutual operating philosophy. | |
| Industry Landscape: The Paradox in the State of GTM AI | 1 | 4 | 1 | 0 | Amelia leads a presentation on industry research and internal lessons, debunking the myth that AI deployments get easier with more platforms. Jason remains silent throughout this section while Amelia educates the audience on executive operational realities. | |
| Deep Dive: Outbound AI SDR Metrics and Multi-Agent Segmentation | 6 | 4 | 0 | 1 | Amelia breaks down outbound SDR statistics and multi-agent segmentation. Jason prompts her to clarify how high-value prospects are handled differently from automated broad outreach, demonstrating his strategic perspective on sales motions. | |
| Deep Dive: Inbound AI SDR Performance and Automated Meeting Qualification | 5 | 3 | 0 | 0 | Amelia explains inbound conversion improvements and automated discovery via Qualified, showing how inbound closing speed increased. Jason reinforces her points by emphasizing the importance of daily hands-on iteration. | |
| Mid-Funnel Reactivation: Deploying Salesforce Agentforce for Ghosted Leads | 1 | 4 | 1 | 0 | Amelia explains deploying Agentforce to reactivate 1,000 ghosted leads that human reps neglected. She reframes the common concern around Salesforce complexity by showing how prompting logic transfers between tools. Jason is largely listening. | |
| Audience Q&A: Structuring Tool Evaluations and Avoiding Evaluation Traps | 2 | 3 | 1 | 0 | Amelia answers audience questions and criticizes prospective buyers running ten simultaneous vendor betas as an inefficient evaluation trap. Jason agrees to pause the presentation and take questions. | |
| Financial Realities: AI Tool Pricing, Enterprise Costs, and Budget Reallocation | 8 | 1 | 0 | 2 | Jason delivers an extensive breakdown of AI tool pricing, onboarding costs, and low-end versus enterprise agent performance based on his conversations with SaaS CEOs. He corrects the assumption that cheap tools currently match enterprise ingestion capabilities. | |
| Vendor Selection: Managing High Demand and Demanding Technical Experts | 8 | 1 | 0 | 2 | Jason passionately warns buyers against non-technical sales reps at AI companies, advising customers to demand forward-deployed engineers or onboarding experts before signing contracts. | |
| Team Enablement: Upskilling Reps and Diagnosing AI Performance Failures | 2 | 3 | 0 | 0 | Amelia discusses turning A-tier reps into S-tier performers via AI enablement and diagnosing output failures as prompt or context gaps rather than tool defects. Jason listens attentively. | |
| Audience Q&A: Data Hygiene, Contact Enrichment, and Multi-Agent Deduplication | 2 | 3 | 0 | 0 | Amelia provides technical details on managing contact hygiene, list enrichment, and preventing multi-agent collision across Artisan, Qualified, and Salesforce. Jason wraps up the session. |
Statements from this episode (23)
SaaStr scaled from 1 to about 20 core AI agents in six months
“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”
Ibarra: Managing 20 AI agents takes the majority of our time
“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”
Ibarra: AI Lets Companies Clone A-Players and Make Them S-Tier
“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. I truly believ…”
Lemkin: AI Agents Cannot Fix Broken Playbooks, Only Scale Working Ones
“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 seven infinite firepower backing up your best practices.”
Ibarra: Most companies adopting AI agents fail to see impact
“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 ex…”
Ibarra: Expecting immediate ROI and headcount cuts from AI is false
“Jason's point on like immediate ROI and headcount is a hugely false expectation that I hope nobody has on this call, but if you had it maybe going into this, can kind of course correct on where you're going to see lift.”
Ibarra: AI-native GTM agencies are selling snake oil
“There's no agency that already knows how to do this. 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, buy the snake oil of, oh, we're an AI native agency and we know how to do GTM …”
Ibarra: SaaStr AI outbound hits nearly 7% response rate
“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 respons…”
Ibarra: Outbound AI agent generated 10% of SaaStr AI London revenue
“10% of ticket revenue for SaaS or AI in London only on this agent.”
Ibarra: SaaStr AI outbound sends 3,000 monthly emails versus 75-285 per human rep
“Our outbound emails per rep across the board. So across the things I just mentioned for us, you know, tickets, sponsorship, speakers, whatever. On the average band six months ago with anywhere between 75, you know, let's say at the low end to two 85 at the hig…”
Ibarra: SaaStr Inbound AI Agent Generated $1M Revenue in Three Months
“We've only had this, let's say three months. The inbound agent has been responsible for already a million dollars of revenue.”
Ibarra: 70% of SaaStr October Closed-Won Revenue Came From AI
“A crazy stat I just saw too, like, 70% of our October closed one came from the AI.”
Ibarra: SaaStr sales missed following up with 1,000 inbound event leads
“Post SaaS Riannual, I was like, we literally just from this SaaS Riannual, have about a thousand people our sales team we never followed up with.”
Ibarra: SaaStr's Salesforce Agentforce campaign achieved a 72% email open rate
“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, I can't, the open rate is 72%.”
Ibarra: Setting up Salesforce Agentforce does not require a Salesforce admin
“I think this misconception of, you know, oh, I can't use AgentPorth even on Salesforce because it's probably too technical or it's going to be deemed to fail or I probably can't get, you know, only either a third party agency or like a Salesforce admin to come…”
Ibarra: Running multiple AI vendor bake-offs wastes time instead of saving money
“Like, I think in trying to save money, you're actually spending a lot more time than you normally 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 It's prohibit…”
Lemkin: AI GTM and SDR tools are priced around $100k annually
“Basically all the vendors that we're describing for this. For GTM sales type motions or marketing BDR, whatever you want to call it. They all require training. They all have a fair amount of data and really they're mostly optimized kind of around a hundred K p…”
Lemkin: SaaStr funded AI agents by reallocating budget from two unreplaced headcounts
“No, but we replaced two human, the budget from two humans to support our agents. And we didn't fire anybody.”
Lemkin: AI sales agents only require six months of actionable data
“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.”
Lemkin: Top AI companies have mediocre sales reps who misunderstand their products
“Some of the very best AI companies across the globe, not just any ones 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 …”
Ibarra: SaaS leaders plan to freeze sales hiring to fund AI tools
“And I think a lot of folks I talked to, too, more common, you probably do too, Jason, just say they're not going to add headcount so that they can empower their teams, either Q four, 25 or Q one, 26 with these tools. Like they're just, again, reallocating budg…”
Ibarra: SaaStr AI support agent fails less than 3% of the time
“There are times where our agent can't answer a question, and it's a support question, and I'm like, that's my failing. 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…”