Craig Rosenberg
In April, the Scale Venture Partners team put on our third annual Scale GTM Summit. The summit was a huge success, featuring 300 attendees, incredible NPS, and terrific discussions. While we came away with many insights and learnings, these 30 stood out under the two themes of AI and the GTM Founder.
Say hello to The GTM Founder
1. What is the “GTM Founder”? Founders who own go-to-market like they own product. It’s that simple. Three-time founder Scott Albro coined the phrase at our GTM Summit. (I checked ChatGPT to be sure, which is very “AI” of me.) The founder grasps market nuances and connects with customers in a way that others can’t. That’s what makes Scott’s concept so compelling: founders can do things others can’t. For example, see number 2 below.
2. Founders should build GTM from the ground up. The unconstrained, first-principles thinking of the GTM Founder allows startups to set past playbooks on fire. And we see that almost every day. Exhibit A: David Boskovic increased Flatfile’s outbound efficiency by a factor of five by re-architecting its pipeline strategy from scratch.
3. Founders should be deeply involved in early positioning & messaging decisions. As I said above, the founder grasps market nuances and understands the customer better than anyone. Even when you bring in the pros. Rick Schultz was a veteran CMO when he started at Databricks and spent his first quarter on the job collaborating with the founding team on messaging, positioning, etc.
4. Your founder is your #1 sales rep. Remember: the founder can say and do things that others in the organization can’t. That’s an advantage, both to winning deals and to helping inform #3 above. Scott Albro recommends founders set weekly first meeting targets with ICP prospects. Be aggressive here: 5 meetings per week. While the founder-led sales model gives way to more scale — the GTM machine — the founder/CEO will always be the #1 sales rep. When I asked Scale Entrepreneur in Residence (EIR) Tyler Harnish who the best sales rep was during his long tenure at Salesforce, he answered without hesitation: “Benioff”.
5. Great founders must tell great stories. The baseline expectation for the GTM Founder is to craft authentic stories based on their personal journey, a customer pain point, or a unique vision only they can see. Scott Albro highlights ServiceTitan founders “Born in the trades, built in the trades” as a model founder story.
6. Now let’s have some fun: founders should build a non-stop, “just launch” culture of GTM growth bets. If you haven’t figured it out yet, the GTM playbooks of the past 20 years are not working right now. Thus, the unconstrained thinking of the GTM Founder becomes an advantage. Scott Albro uses Anton Osika of Lovable’s Design Battle as a prime example: he armed a 19-year-old with his product, live streamed him battling a designer with 10+ yrs experience in front of 40,000 live viewers for 1 hour, and got 3M total views. Bonus points if you can incorporate your product.
Marketing in the age of AI: a blend of old and new
7. Messaging takes quarters, possibly even years, to truly penetrate the market. Rick Schultz recommends keeping with the core message for a while. Of course, there will sometimes be little tweaks or even a necessary pivot. But don’t overreact and pivot away from the message after one sales call or one bad analyst briefing.
8. Maintain maniacal targeting discipline. From the very beginning of his time at Databricks, Rick Schultz focused on a small subset of target personas, only later going after the C-suite. Yes, we are all faced with bigger and bigger stakeholder maps, but identify and optimize for the “entry point”: the 1-2 personas where your message and content will resonate most and get you in the door.
9. Poke the bear. Don’t shy away from provocation when creating a category. Rick Schultz and team faced initial skepticism from the analyst and influencer community around the “lakehouse” category but stayed with it and, eventually, won. Reminder: I worked at Gartner. The analysts take time to come around. If you are right, they will.
10. When the market shifts with AI, be prepared to disrupt yourself. The operative phrase here is “when the market shifts.” Yes, #7 above tells us to “stay the course,” and that’s right if the market context remains broadly similar. But when it’s changing dramatically, you have to be a first-mover. For inspiration, look to Tricia Gellman, who is overhauling Box’s marketing strategy–repositioning the brand, promoting enterprise AI education, and investing in partner marketing–to bring its new AI features to market.
11. Game change 101: optimize for “AIO.” Sydney Sloan presented 2025 G2 data that Gen AI chatbots are the #1 source for vendor shortlisting. That happened fast. There are two relevant acronyms emerging: AIO, artificial intelligence optimization, and GEO, generative engine optimization. I texted my most trusted SEO expert for AIO/GEO best practices. Here is what he said: “I am still just figuring this stuff out. Anyone who says they know how to get placed in LLMs is borderline grifting.” Best thing to do right now is to invest in GEO tools as best practices start to emerge.
12. Game change 101b: move resources to owned (community) and earned (influencers, podcasts). IMO, paid marketing is still on the list. While organizations are still getting excellent results from Linkedin and Meta ad spend, you can’t live off paid anymore. Lena Waters (formerly Grammarly and now Notion CMO) is seeing more ROI from community and user events than from her paid efforts.
13. Show that you’re AI native; don’t tell. I wanted to include some ode to the “tell me without telling me” party game but it didn’t quite hit. This is one of my favorite Maria Pergolino-isms: if you’ve done your job well, your campaigns and digital content will “look AI” even if you remove any specific reference to “AI”, “intelligence”, or “automation.” See 10Web’s homepage as an example of telling (before) and showing (after).
14. Align the GTM functions on one metric. Rick Schultz and his Databricks CRO agreed they would focus collectively on total pipeline created rather than who did what or where attribution should go. In last year’s keynote, Chris Degnan, CRO of Snowflake, said something very similar: the marketing and sales metric was on meetings created. If you are following at home, those are two of the most successful tech companies in the valley saying the same thing: focus on one metric and stay out of the attribution trap.
Selling in the age of AI
15. Sell the problem first, then the technology. Marc Wendling of Glean has his sales team focus their process on identifying concrete problems, specific use cases, and demonstrable ROI. This is the second time I’ve heard this in the last couple months. Dan Gottlieb also said, in reference to selling AI: “sell the work, then the tech.”
16. Don’t just sell the AI dream; help customers realize and measure value. Otherwise, turn on the churn machine. Stevie Case, CRO of Vanta, thinks the lack of attention most AI companies pay to educating and supporting customers is why they see high churn rates. It feels like #16 and #17 go hand-in-hand.
17. The Pete Giordano Cheat Code for identifying customer value: ask prospects how they earn their bonuses and what KPIs they track. Having this info on your customer enables you to deliver maximum value to them.
18. Selling AI to the enterprise will take time. Pear VC Investor Mar Hershenson has seen firsthand how data privacy and security concerns slow enterprise adoption. I have heard this for years from SMBs /mid-market players: “we are going to the enterprise.” It makes sense on paper, but execution is tougher than you think. Last year, Chris Degnan told the crowd that they purposely defined the ICP to not include the massive enterprise so they could avoid long sales cycles and cumbersome internal requirements.
19. At the end of the day, humans still need to sell and we need to teach them core sales skills. (For now.) According to Marc Wendling, AI hasn’t replaced the AE toolkit; rather, it’s optimized how the best AEs deploy it.
Pricing in the age of AI
20. You have to price AI software differently than traditional SaaS. For Pete Giordano, the fact that AI delivers value directly, instead of enabling users to deliver value, means it necessitates a bespoke pricing model. Think about this as the difference between an AI agent that automatically answers support questions without human intervention (e.g., Observe.ai or Bland) and software that helps human reps answer support questions. The fact that they create customer value in different ways implies that they need different pricing models.
21. Unlike traditional SaaS, AI products have substantial marginal costs. There can be a two-way bill shock: both customers and vendors can get hit with massive bills for compute costs. Pete Giordano recommends usage guardrails as the key to protecting both your company and the customer. This is why Everett Berry, Clay’s Head of GTM Engineering, and his team have implemented limits on the number of people/companies a customer can pull in one search
22. Hybrid pricing schemes are the gold standard for AI products. Hybrid pricing schemes typically feature a subscription/platform fee with some usage included. On top of that, there is a scalable usage- or outcome-based pricing component. For example, Clay’s hybrid pricing includes a) baseline subscription, which provides predictability to the customer and b) an option for customers to buy more searches.
23. AI pricing strategy is product strategy. In Pete Giordano’s words, if an outcome-based pricing scheme isn’t working for you, it’s probably because your product doesn’t directly produce that outcome. (And you might want to change that.) This is why AI content marketers like Jasper charge based on seats rather than on the engagement they drive or the pipeline they generate: they don’t directly produce those outcomes (yet).
Growing in the age of AI
24. AI is enabling a new era of “seed-strapped” growth. Pear VC Investor Mar Hershenson confirmed that this is a real thing they have seen. Tiny teams (<10 people) take their seed round and then use AI to build $10M+ ARR businesses.
25. In a world where everyone is building on top of the same foundation models, strong GTM execution and unique distribution are the key differentiators that investors like Jeremy Kaufmann are looking for. Efficient GTM is the new moat. In my world, that’s great to hear.
26. In AI, bottoms-up adoption = customer success. Marc Wendling gave a great analogy: with traditional SaaS, like CRM, management chooses the solution for their needs and end users come second. In AI, products tank if end users don’t get the “what” and “how.”
27. When it comes to your ICP, ditch broad verticals and craft hyper-personalized messaging for micro-segments. David Boskovic at Flatfile is using AI to identify these segments and create compelling, tailored messaging for each.
Driving tool adoption in the age of AI
28. Love this from Stevie Case: the internal “AI builder team.” Some people are calling these GTM engineers – dedicated, nimble teams that evaluate, build, and deploy AI tools in your GTM org. The builder team should include members of the GTM org (not just engineering types). For example, for prospecting, the builder team should include an SDR leader or volunteer SDRs.
29. Top-down initiatives drive AI adoption. Stevie Case and the Vanta GTM leadership team have set a baseline expectation that every employee, regardless of role, leverages AI in their work. There are many examples these days of CEOs mandating AI use, such as Shopify’s Tobias Lütke. Socure has a top-down mandate for AI and a goal of a 20% productivity gain. Their SDR team is already booking more meetings with fewer SDRs and their RevOps leader Colin Gerber has 9 AI projects in motion.
30. But so does bottom-up experimentation. Some of the best use cases we are seeing today come from individual contributors building their own stuff. Box CMO Tricia Gellman encourages team members to regularly swap ideas with peers as a low-risk, low-effort learning mechanism.
To summarize, the GTM Playbook is being rewritten every day. Most of the catchy LinkedIn headlines proclaiming “XYZ traditional GTM strategy or tactic is dead” (type in “cold calling is dead” if you want to see what I mean) are totally hyperbolic. At the same time, it is true that those strategies can no longer be relied upon to deliver it all. AI is changing both what we sell and how we sell. With everything back on the table, GTM is fun again, and this massive change has already inspired a pace of innovation I’m not sure I’ve seen before.