What world-class GTM looks like in 2026 | Jeanne DeWitt Grosser (Vercel, Stripe, Google)
Jean Grosser, COO at Vercel and former CBO at Stripe, discusses building world-class go-to-market teams. She shares insights on leveraging AI for sales, treating GTM as a product, effective segmentation, and fostering strong collaboration between sales, product, and engineering.
Deep Dive Analysis
16 Topic Outline
Defining Go-to-Market (GTM) and its Scope
Evolution of GTM Roles and Consultative Selling
The Rise of the Go-to-Market Engineer
Automating Sales Workflows with AI Agents
Defining Sales Development Representatives (SDRs) and Account Executives (AEs)
When to Hire a GTM Engineer and First Salesperson
Profile of an Ideal Go-to-Market Engineer
Leveraging Gong with AI Agents for Sales Insights
Changing Calculus of Building vs. Buying GTM Tools
Thinking About Go-to-Market as a Product
Effective Go-to-Market Tactics and Unique Insights
Understanding Customer Buying Motivations: Pain vs. Upside
Primer on Segmentation Strategies
Building a Sales Organization that Engineers Respect
Thoughts on Product-Led Growth (PLG) and Pricing Strategy
Hot Takes on Sales Compensation and Hiring Profiles
6 Key Concepts
Go-to-Market (GTM)
GTM encompasses any function that touches a customer or makes a dollar, including marketing, sales, technical sales, customer success, support, and partnerships. It's viewed as an integrated lifecycle, moving away from hyper-specialization towards a holistic orchestration of the customer journey.
Go-to-Market Engineer (GTM Eng)
A technical role that applies engineering prowess to GTM functions, building tools and AI agents to automate workflows, improve data utilization, and scale personalized customer experiences. This role aims to increase efficiency and allow human sellers to focus on deeper customer interactions.
Project Rosalind
An early (2017) initiative at Stripe to create a massive company database, mapping every company on the planet with attributes to enable highly targeted and personalized outbound prospecting emails. It was challenging to implement without AI but is now feasible with AI's capabilities.
Deal Bot / Lost Bot
AI agents built using sales call transcripts (e.g., from Gong) and other interaction data to analyze sales processes. The 'Lost Bot' identifies true reasons for lost opportunities, while the 'Deal Bot' provides real-time insights to sales teams, diagnosing GTM process 'bugs' and suggesting improvements.
Segmentation
The process of categorizing the market into distinct groups of companies based on attributes like size, growth potential, business model, website traffic, or workload type. This helps tailor sales strategies, content, and product development to specific customer needs and buying behaviors.
Go-to-Market as a Product
A mental model that views the entire customer buying journey—from initial awareness to long-term retention—as a series of unique, human, and personalized experiences. This approach aims to differentiate a company not just by its product, but by the quality and design of its sales and customer interactions.
15 Questions Answered
GTM encompasses all functions that interact with a customer or generate revenue, including marketing, sales, technical sales, customer success, support, and partnerships, ideally integrated into a cohesive customer lifecycle.
GTM has become more consultative due to consumption-based models and AI, requiring deeper customer understanding and leaning into 'the art of the possible,' leading to roles like forward-deployed engineering and the GTM engineer.
A GTM engineer brings technical prowess to GTM, building tools and AI agents to automate workflows like outbound prospecting or lead qualification, aiming to increase sales efficiency and allow human sellers to focus on customer interaction.
AI agents for GTM can be built very rapidly; for example, a lead agent at Vercel took one GTM engineer about six weeks (25-30% of their time), and a lost opportunity bot took only two days.
An SDR (Sales Development Representative) is typically responsible for generating pipeline by prospecting and qualifying leads, while an AE (Account Executive) is a closer whose job is to take an interested prospect through the sales process to a signed deal.
Founders should typically wait until they have around $1 million in ARR and a repeatable sales process, with a clear ideal customer profile (ICP), before hiring their first dedicated salesperson.
The ideal GTM engineer often has prior go-to-market experience, such as a sales engineer with a technical background, as they understand both the technical aspects and the nuances of effective sales processes.
AI agents can analyze Gong call transcripts and other sales interactions to perform tasks like lost opportunity reviews, identify reasons for wins/losses, provide real-time insights to sales teams, and diagnose 'bugs' in the GTM process.
When technical product differentiation narrows, the customer's buying experience becomes a key differentiator; treating GTM as a product means designing a unique, human, and personalized journey for the customer at every touchpoint.
Effective tactics include bringing unique insights to customers about their suboptimal state, investing in detailed implementation guides (like 'well-architected guides'), and practicing excellent discovery by listening more and asking probing questions rather than immediately problem-solving.
Approximately 80% of customers buy to avoid pain or reduce risk, rather than to gain upside, especially in enterprise settings where the focus is on avoiding negative outcomes like missing revenue targets or brand damage.
Segmentation involves carving up the market based on attributes that influence buying behavior (e.g., company size, growth potential, business model, website traffic, workload type) to tailor sales strategies and content, and it should be a company-wide strategy, not just a GTM function.
A sales organization builds trust by having deep product knowledge (so AEs can be mistaken for PMs), acting as an extension of the product management org by discerning and feeding customer signal into the roadmap, and thinking like general managers focused on building the business.
PLG is highly relevant for many products, especially those targeting startups, but it typically has a ceiling for deal size; companies often get stuck if they wait too long to layer in a sales-assisted or sales-led motion to sustain growth.
Pricing should be treated like a product, aligning value delivery with cost incurrence, avoiding underpricing, and carefully considering freemium strategies (e.g., Stripe Billings killed its free trial after realizing integration effort meant commitment).
18 Actionable Insights
1. Build Sales Org with Product Depth
Cultivate a sales organization where account executives possess incredible product depth, making them indistinguishable from product managers to engineers. This fosters credibility with product and engineering teams and enables sales to act as an R&D extension by translating customer feedback into valuable roadmap signal.
2. Treat Go-To-Market as a Product
Design the customer buying journey like a product, focusing on creating unique, human, and personalized experiences rather than transactional interactions. This differentiation becomes crucial when technical product differences narrow, driving buying decisions based on how customers feel about being sold to.
3. Leverage AI for Sales Automation
Utilize AI agents to automate rote sales tasks like research, follow-ups, and initial prospecting, aiming for salespeople to spend 70% of their time interacting with humans. This increases efficiency and allows sales teams to focus on deeper customer engagement.
4. Keep Human in AI Sales Loop
Implement AI agents for sales workflows with a ‘human in the loop’ approach, especially for critical tasks like lead qualification and crafting responses. Have humans review and send AI-generated outreach to ensure brand consistency and quality, while using agent feedback for continuous improvement.
5. Diagnose GTM Process with AI
Use AI agents to analyze Gong transcripts and other interactions to diagnose ‘bugs’ in your go-to-market process, such as poor objection handling or common sticking points. Run regular sprints to address these identified issues with new content, discovery guides, or demo changes.
6. Focus on Risk Reduction for Buyers
Understand that 80% of customers buy to avoid pain or reduce risk, rather than to increase upside. Frame your sales narrative around de-risking potential negative outcomes for enterprises and helping customers avoid not making revenue targets or being outdone by competitors.
7. Implement Collaborative Discovery Sessions
Replace traditional discovery calls with collaborative whiteboarding sessions where customers draw their architecture. This approach helps you learn about their stack and challenges, while providing customers with a valuable asset and a sense of partnership.
8. Add Value at Every Touchpoint
Strive to add value to customers at every touchpoint, even if they don’t buy immediately. Providing unique insights or helpful information builds trust and ensures that customers may return for future buying cycles.
9. Invest in Data for Unique Insights
Invest in data to uncover unique insights about a prospect’s current performance or suboptimal state. Share these data-driven insights immediately to pique interest, demonstrate value, and establish your company as a trusted, knowledgeable resource.
10. Create Well-Architected Guides
Beyond basic documentation, develop ‘well-architected guides’ or blueprints that outline best practices for implementing your product within specific customer setups. This is especially valuable for larger companies seeking detailed implementation guidance.
11. Practice Excellent Discovery Skills
Master the art of discovery by talking less than half the time in conversations, asking probing questions, and employing techniques like ‘five whys’ to go deep. Help customers arrive at conclusions on their own rather than immediately problem-solving.
12. Develop a Company-Wide Segmentation
Establish a clear segmentation framework that is understood across the entire company, not just go-to-market. This ensures product managers build with specific customer profiles in mind, aligning product and GTM strategies.
13. Use Data to Define Segmentation
Define your market segmentation by analyzing data to identify customer attributes that correlate with high revenue potential and repeated success. This helps you cluster winning customers and understand where your product resonates most effectively.
14. Build a General Manager Sales Org
Foster a sales organization that thinks like general managers, focused on building the business rather than just closing deals. This means understanding when to say no to feature requests and discerning market opportunities from mere objections.
15. Think About Pricing Like a Product
Approach pricing as a product, deeply understanding where customers derive value and where your company incurs costs. Align these factors smartly to avoid underpricing and ensure optimal revenue outcomes and customer experience.
16. Strategize Freemium Carefully
Do not default to a freemium strategy without a clear, intentional purpose. Evaluate if a free tier genuinely drives conversion or if the product’s integration effort means users are likely to stay regardless, potentially making a free trial unnecessary.
17. Diversify Sales Team Hiring
Build a diversified sales team by combining experienced salespeople with individuals from non-traditional backgrounds like consulting or banking. This mix fosters a richer learning environment where different skill sets (e.g., quantitative analysis, P&L understanding) are shared and developed.
18. Embrace ‘No’ as Data
Get comfortable with receiving ’no’ in sales, viewing it as valuable data rather than a setback. Use this information to understand why a deal was lost and inform future strategies or product improvements.
6 Key Quotes
80% of customers buy to avoid pain or reduce risk as opposed to increase upside, which is a good thing for startup founders to understand.
Jeanne DeWitt Grosser
The experience that you have of being sold to will increasingly actually differentiate a company and drive buying decisions if products are only different at the margin.
Jeanne DeWitt Grosser
The litmus test I have always given my sales team is if you are an account executive in my org and I put you in front of 10 engineers at our company, it should take them 10 minutes to figure out you aren't a product manager.
Jeanne DeWitt Grosser
No one, like, graduated from college and was like, yes, I just went to college for four years to become an SDR. It was more, okay, that's where you are forced to start.
Jeanne DeWitt Grosser
Company strategy is basically product strategy meets go to market strategy, right?
Jeanne DeWitt Grosser
Yeses are great, no's are great, maybe they'll kill you.
Jeanne DeWitt Grosser
3 Protocols
Building an AI Agent for GTM Workflows
Jeanne DeWitt Grosser- Have a GTM engineer shadow the highest-performing individual in the target function (e.g., SDR) to understand their human workflow, including tools and research methods.
- Encode the observed workflow into an agent, using code that is both deterministic and less so, to replicate human actions.
- Start with workflows that are legible (can be written down, relatively replicable, mostly deterministic) for initial agent development.
- Implement a 'human in the loop' review process where the agent makes calls (e.g., lead qualification) and crafts responses, but a human reviews and sends them.
- Continuously train the agent by incorporating feedback from human rejections or edits.
- Track key performance indicators (KPIs) (e.g., lead to opportunity conversion, number of touches, time to convert) to ensure the agent performs as well as or better than humans.
- Once confident in the agent's performance, redeploy human staff to higher-value tasks.
- For ongoing improvement, run the agent across calls and interactions to diagnose 'bugs' in the GTM process (e.g., objection handling, getting stuck) and then run sprints to address these issues with new content or demo changes.
Go-to-Market Strategy for Startups (Founder-Led to First Salesperson)
Jeanne DeWitt Grosser- As a founder, stay deeply connected to customers and lead sales until you reach a significant scale (e.g., $1 million ARR) with some repeatability.
- Ensure you have a clear Ideal Customer Profile (ICP) that can be written down, indicating where your product fits best (e.g., 'startups with less than 100 employees building SaaS applications').
- Document your effective sales practices, content, discovery questions, and objection handling strategies to transition knowledge.
- When hiring the first salesperson, empower them by handing over the reins, but founders should remain connected to customers for R&D insights and to understand scaling challenges.
- Consider bringing in revenue operations or GTM engineering earlier than traditionally thought to establish data-driven processes and leverage AI from the outset.
Building a Sales Org that Engineers Respect
Jeanne DeWitt Grosser- Set a high bar for product depth: Salespeople should be so knowledgeable about the product that engineers struggle to differentiate them from product managers.
- Recruit individuals who can think like general managers, focused on building the business, not just closing deals.
- Cultivate the sales org as an extension of the product management team, translating customer feedback into actionable signal for the roadmap.
- Develop the ability to discern true market opportunities from individual objections that can be overcome.
- Foster a culture where sales leaders lean into product and pricing strategy, understanding how these align with revenue goals.
- Diversify sales hiring profiles by pairing experienced salespeople with individuals from non-traditional backgrounds (e.g., consulting, banking) to enrich learning and analytical capabilities.