I know, I know. You’ve been hearing about “AI transforming B2B” for two years now. Your LinkedIn feed is drowning in it. Every vendor has slapped “AI-powered” on their homepage.
But here’s the thing: we’re actually just now getting to the starting line.
Really. Most of this stuff didn’t even work until early 2025.
2024: The Models Weren’t Good Enough (Until They Were)
That AI SDR tool you bought in early 2024? The one that sent embarrassing emails to your prospects and got turned off after two weeks?
I get it. We all tried them.
The models simply weren’t capable enough yet. Not really. Not for production B2B use cases where your brand and pipeline are on the line.
But then something changed. And it happened in stages.
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This edition of the SaaStr Daily is sponsored in part by Seamless.AI
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So in early 2024, Lenny Rachitsky invited us on to Lenny’s podcast for what became an iconic deep dive on sales and GTM. How and who to hire, the classic GTM and sales mistakes we all make, and more. It was great.
It was also … an entire era ago. The end of the pre-AI era, really. Everything in that classic GTM convo from Q1 2024 holds true today. But it also was about a world where all of sales, marketing, onboarding, support and success were done by humans.
So Lenny invited us back to talk about AI and GTM in 2026. His first show of 2026, in fact. HNY!!
And so much has changed, and more importantly, is just beginning to change.
At SaaStr, we’ve replaced nearly our entire go-to-market team with AI agents. The results? The same revenue with 1.2 humans instead of 10. Here’s what every founder and sales leader needs to know.
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2025 was our biggest year of transformation since launching in 2012.
We went all-in on AI. Not just talking about it—actually deploying it across our entire business.
Here’s what we shipped:
From Zero to 20+ AI Agents
We started 2025 AI-lean. By mid-year, we had 20+ AI agents running in production:
• AI SDRs sending 15,000+ messages at 5-7% response rates • AI BDRs booking qualified meetings while reps sleep • AI support handling 150,000+ community chats • AI RevOps syncing every call to Salesforce automatically.
Managing them takes 30% of our Chief AI Officer’s time. But the results? Eight-figure revenue with single-digit headcount.
SaaStr.ai Launched—And Took Off
We built a suite of AI-powered tools that founders actually use:
- 750,000+ startup valuations calculated
- 3,000 VC pitch decks graded •
- 600+ VC intros made (by AI)
- 500 founders used our free Real-time B2B benchmarking data •
- “Digital Jason” AI co-pilot trained on 20M+ words of SaaStr content
The Valuation Calculator hit 87% CTR on search. That’s product-market fit screaming at us.
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This edition of the SaaStr Daily is sponsored in part by Wistia
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Repurpose your videos and webinars into high-impact content with insights from marketing, content, and video production experts. Plus, learn how to produce content faster with AI, from clip creation for your social channels to dubbed content for your global audiences.
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One of the most common questions I get from seed-stage founders: “How much equity should I give my first hires?”
It’s a high-stakes decision. Give too little and you can’t attract talent. Give too much and you’ll regret it by Series B when you’re trying to recruit a CFO and your option pool is decimated.
Carta’s latest State of Seed report gives us real benchmarks from tens of thousands of startups. Here’s what the data actually shows.
The First 5 Hires: What They Actually Get
Let’s start with the headline numbers. These are fully diluted equity grants, typically vesting over 4 years with a 1-year cliff:
Hire #1: 1.50% (median)
- 25th percentile: 0.50%
- 75th percentile: 4.00%
Hire #2: 0.85% (median)
- 25th percentile: 0.30%
- 75th percentile: 2.00%
Hire #3: 0.50% (median)
- 25th percentile: 0.20%
- 75th percentile: 1.20%
Hire #4: 0.44% (median)
- 25th percentile: 0.18%
- 75th percentile: 1.00%
Hire #5: 0.33% (median)
- 25th percentile: 0.13%
- 75th percentile: 0.80%
The pattern is clear: equity drops fast. Your first hire gets nearly 5x what your fifth hire gets at median. By the time you’re making your fifth hire, you’re already in the “normal employee” range.
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Answer: try everything that just might work, even a little bit.
Then: double down on anything that works even a little.
That may sound obvious, but what I mean is, most start-ups scale roughly the same way after $1m-$2m in ARR or so, at a given price point. But they often get to $1m ARR different ways, and especially to the first $100k in ARR.
Some of the reasons companies get there differently are product-related, but others are founder-related (founders are good at some things, worse at others).
How did the best start-ups I’ve worked at $200m+ today … get to their first $1m-$2m ARR?
- 100% inside-driven outbound, for smaller deals, i.e., Cold Calling 2.0. One of the best startups I work with, the CEO had never done sales before. But he learned he was good at SDRs and outbound. So he hired 10 SDRs before he ever hired an AE or a marketing head.
- 100% field outbound, for bigger deals. Another I work with, where the price point was higher, the CEO convinced 10 senior execs to buy from him almost pre-launch. This is rare, but some founders trained in enterprise sales can pull this off. If you can commit to solving a big company’s big problem, and there is no other great vendor in the space, you can sometimes get a meeting. This is how I got my first start-up off the ground … but I failed miserably here the second time.
- PR. Mediocre PR alone rarely moves the needle, but if you are very good at it, it can. It helped me a lot. This is harder to predict today, and we expect too much. But especially if you have a viral product, good PR can move the needle — sometimes.
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Sometimes, yes. But just as often, the ones that complain are the ones that care. And oftentimes, their complaints help focus you on the gaps you really do need to fix.
One thing most SaaS companies get wrong in customer success is they don’t spend enough time surfacing customers that are truly at risk, but aren’t complaining.
The thing is:
- Somewhat and even very satisfied customers that still want more from you and your product often complain the most.
and
- Unhappy customers that are planning to leave often don’t complain at all. They just find another solution and leave. And …
- Once usage drops, it’s too late. You’ve already lost them. They’ve already gone somewhere else. So pure usage meters don’t really work.
So … #1 We all spend too much time on complaining customers and #2 We spend too much time looking at usage and even engagement metrics. They matter. But once they drop — it’s often too late.
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