Sales In The Age of AI: The Playbook from The CROs of Databricks, Windsurf, Perplexity and Owner
"Your AI tools can get you to 80% of an expert level in a lot of fields”
We’re recently done A+ deal dives with the CROs / VPs of Sales from Perplexity, Owner, Databricks, and Windsurf. We brought together all their learnings on AI-driven selling to give you a playbook for AI-powered revenue growth.
Executive Summary: The 10 Game-Changing Insights
The AI revolution in sales isn’t theoretical—it’s happening right now, and the leaders who figure it out first are creating insurmountable competitive advantages. After analyzing deep conversations with four revenue leaders at the forefront of this transformation, here are the ten insights that will define the winners and losers in the age of AI sales:
AI Creates a Great Bifurcation: Elite performers become unstoppable while average reps become obsolete
AI-Native Hiring is Non-Negotiable: If candidates aren’t actively using AI tools, they’re unhireable
Speed Has Become the Ultimate Moat: Competitors using AI move faster than those who don’t
Technical Sales Teams Have a Massive Head Start: Deep product knowledge + AI = exponential advantage
The “People Person” Sales Rep is Dead: Product expertise and teaching ability matter more than schmoozing
AI Implementation Requires Continuous Investment: No tool works magically out of the box
Revenue Models Must Blend Human and AI: The future is seamless customer journeys, not siloed experiences
CROs Must Become Hybrid Team Managers: Leading both humans and AI agents is the new core competency
Attribution Models Will Break (And That’s Good): Focus on total business value, not commission allocation
Meeting Prep and Pipeline Analysis Are Just the Beginning: True transformation comes from AI handling direct customer interactions
Now, let’s dive deep into each learning with specific examples and tactical advice from leaders who are already living in the future.
Learning #1: The Great Bifurcation – Elite Performers vs. Everyone Else
“AI will contribute much more to elite performers… you’ll see the best get better and there become an even bigger bifurcation.” – Kyle Norton, CRO, Owner
The brutal reality: AI isn’t making average salespeople better. It’s making great salespeople unstoppable while leaving everyone else behind.
The Evidence:
Owner sees 3-4x productivity gains, but only from AI-native reps
At Windsurf, 7 out of 10 seasoned reps are already over their annual quota, with one rep closing $1.6 million in four months
Perplexity operates with 5,000+ enterprise customers using just 5 salespeople
Research shows AI raises the floor for simple tasks but amplifies the ceiling for complex knowledge work
Why This Happens: Graham Moreno from Windsurf explains: “The best sellers will have so much more leverage with all of these tools that the competitive dynamic will say they’re worth more.” The best salespeople are naturally curious, systematic, and committed to continuous improvement—the same traits that make them excellent at training and optimizing AI tools.
What This Means: If you’re managing a sales team, start identifying your top and bottom performers now. Invest heavily in making your A-players even better with AI tools. For your C-players, you have roughly 12 months to help them level up or transition them out.
Learning #2: AI-Native Hiring is Non-Negotiable
“I don’t care how good this person is—if they’re not in the tools and what I consider to be AI native, we can’t hire them.” – Kyle Norton, CRO, Owner
All four leaders have fundamentally changed their hiring criteria. It’s no longer enough to have great sales skills—candidates must demonstrate active AI fluency.
The New Interview Standard:
Owner: Every leadership candidate must explain their current AI usage and demonstrate tools proficiency
Windsurf: Graham Moreno requires “a component of the interview that’s now what are you doing with AI? What do you know about it? How are you using it today?”
Perplexity: Dmitry Shevelenko emphasizes that the entire company mandate is to move faster using AI superpowers
What “AI-Native” Actually Means: This isn’t about knowing ChatGPT exists. The bar is sophisticated usage across multiple tools and systematic integration into daily workflows.
The Tough Love Reality: “If your sales leader isn’t in the tools every day and genuinely curious, you’re cooked,” Norton warns. By mid-2025, any revenue leader not deeply engaged with AI tools should be transitioned out.
Tactical Application:
Add AI usage questions to every sales interview
Ask candidates to demonstrate specific tools they use
Test their curiosity about learning new AI applications
Look for evidence of systematic AI integration into their current workflow
Learning #3: Speed Has Become the Ultimate Moat
“Speed is the new moat. You have no excuse to not be moving faster. Your competitors are moving faster.” – Dmitry Shevelenko, CBO, Perplexity
Perplexity’s success story illustrates this perfectly: they hit the market at exactly the right moment when GPT-3 became powerful enough but before competitors could react.
How AI Enables Speed:
Meeting Preparation: Shevelenko notes that “every question you would ask in a meeting with an external party, you can be asking those questions of Perplexity or different AIs in advance”
Pipeline Analysis: Instead of subjective quarterly reviews, AI provides real-time deal risk assessment
Scaling Teams: Graham Moreno scaled Windsurf’s go-to-market from 3 people to 75 in under 12 months, largely through AI-enabled recruiting and onboarding
The Competitive Pressure: If you’re not leveraging AI for faster decision-making, faster customer response, and faster deal progression, your competitors who are will consistently out-execute you.
Practical Implementation:
Use AI for pre-meeting research on every prospect
Implement automated CRM updates to eliminate administrative lag
Deploy AI-powered proposal and deck generation
Set up real-time pipeline analysis instead of waiting for quarterly reviews
Learning #4: Technical Sales Teams Have a Massive Head Start Selling to Technical Buyers
“Most of our salespeople are more technical than most. They can code, they can do POCs, they can do pilots.” – Ron Gabrisko, CRO, Databricks
Databricks scaled from under $1 million to over $1 billion ARR with a predominantly technical sales organization. This technical foundation makes AI adoption natural rather than forced.
Why Technical Background Matters: Gabrisko explains: “If you’re not technically enough to understand the product and understand how it works, it’s hard to teach your customers how to get value from it.” Technical reps naturally understand how to train and optimize AI tools because they think in systems.
The Open Source Advantage: Databricks leveraged their open source community of millions of Spark users to identify prospects and validate market need. This data-driven, community-centric approach translates directly to AI implementation success.
For Non-Technical Teams:
Invest in technical training for your sales leadership
Hire sales engineers who can bridge the gap
Partner with technical team members for AI implementation
Focus on building systematic, process-oriented thinking
Learning #5: The “People Person” Sales Rep is Dead
“People think they’re people persons in sales, and I think they’re lazy and they’re smoozers.” – Kyle Norton, CRO, Owner
The old model of relationship-based selling is becoming obsolete. Customers want expertise, not friendship.
What Actually Matters Now: Ron Gabrisko emphasizes the importance of being able to “add value on the technical front” and knowing your stuff, because “technical buyers don’t really love talking with salespeople” unless they bring real expertise.
The Trust Factor: Dmitry Shevelenko identifies trust as “the scarce asset of the agentic internet.” Customers increasingly trust knowledgeable AI over uninformed humans. “It’s easy to create AIs that manipulate people, but that’s a very short-term strategy.”
The New Standard: Your sales reps need to be able to teach customers something they didn’t know, using AI to access perfect product knowledge and market insights instantly.
Learning #6: AI Implementation Requires Continuous Investment
“Every week there’s a QA meeting… We go through what needed to be escalated to a person and why.” – Kyle Norton, CRO, Owner
Every leader emphasized the same reality: AI tools don’t work magically out of the box.
The Implementation Reality:
Perplexity teams upload successful templates and continuously refine AI to “pull in all the real-time information about that company” while preserving winning styles
Databricks regularly refines AI-powered customer success processes based on their massive enterprise customer base
Windsurf’s Graham Moreno emphasizes that “you need to go do a bunch of the foundation work to create the content and tweak it every single day, every single week”
The Weekly Improvement Process:
Identify where AI failed or could perform better
Add new training content or adjust parameters
Test improved performance
Measure results and plan next improvements
Success Framework:
Pick platforms and expect 50% of what you hoped initially
Invest in making them better every single week
Treat AI optimization as a core business process, not a side project
Measure progress monthly, not daily
Learning #7: Revenue Models Must Blend Human and AI
“I’m trying to build what I call semi-self-serve—a consistent customer journey that has different channels, different experience channels.” – Kyle Norton, CRO, Owner
The future isn’t human vs. AI sales—it’s seamless integration where customers get the right level of assistance through the right channel at the right time.
Examples of Blended Models:
Perplexity: 5,000+ enterprise customers with just 5 salespeople
Windsurf: Graham Moreno is building “a unified platform that takes all of these disparate piecemeal processes and combines them” so customers can flow between AI and human interactions
Databricks: Ron Gabrisko leverages their massive community events where thousands of customers learn from each other, supplemented by targeted human outreach
The Customer Experience Advantage: Instead of forcing customers into rigid sales processes, let them choose their engagement level. “You should get whatever version from PLG to handheld sales that the buyer wants,” Norton explains.
Implementation Strategy:
Design systems that let customers move between AI and human interactions seamlessly
Don’t worry about attribution—focus on total business value
Train AI on your best sales conversations to maintain quality
Use humans for relationship building and complex problem-solving
Learning #8: CROs Must Become Hybrid Team Managers
“A lot of my job is managing the system and infrastructure of our business anyways. The same thing called by another name.” – Kyle Norton, CRO, Owner
The CRO role is evolving to include managing both human teams and AI agents. This isn’t optional—it’s essential for survival.
The New Management Reality: Graham Moreno at Windsurf is hiring a “GTM AI lead” who will do nothing but AI optimization within the RevOps organization. Meanwhile, Gabrisko at Databricks emphasizes that “hire the best, inspire them, motivate them, mentor them” now applies to both human and AI team members.
Perplexity’s Systematic Approach: Shevelenko describes how they “assume that using AI tools you can get to 80% of an expert level in a lot of fields” and then use humans for the crucial final 20% that requires judgment and intuition.
Core Skills for Hybrid Management:
Systems thinking about customer journeys
Understanding AI capabilities and limitations
Process design for human-AI collaboration
Performance measurement across both humans and agents
Learning #9: Attribution Models Will Break (And That’s Good)
“Is your job to hit your sales number or build enterprise value?” – Kyle Norton, CRO, Owner
Traditional sales attribution becomes meaningless when AI agents are closing deals independently or assisting in complex ways.
Why Attribution Breaks: Graham Moreno explains: “I’m very anti-attribution in general. We get into problems where we say ‘oh this is a marketing attributed sourced deal versus a sales attributed one’ and end up making local maxima decisions.”
The Databricks Example: Ron Gabrisko built a system where customers learning from customers is your best selling mechanism, making traditional individual attribution impossible but driving massive business value.
The Mindset Shift: “How do we maximize this entire system and not worry as much about the credit?” Moreno asks. The companies that figure this out will dominate those stuck in traditional commission structures.
Practical Changes:
Focus on team-based incentives rather than individual attribution
Measure customer satisfaction and business outcomes, not just closed deals
Design compensation around business growth, not activity metrics
Learning #10: Meeting Prep and Pipeline Analysis Are Just the Beginning
“We are building a PLG motion that will be heavily AI.” – Kyle Norton, CRO, Owner
While most companies are still figuring out AI for administrative tasks, leading organizations are deploying AI for direct customer interaction.
The Evolution Stages:
Stage 1 (Now): AI for research, preparation, and analysis
Stage 2 (6-12 months): AI for process automation and coaching
Stage 3 (12-24 months): AI handling direct customer interactions
Advanced Applications in Practice:
Perplexity uses AI that can “detect changes that are meaningful and surface that to you” proactively rather than reactively
Windsurf is implementing AI that joins Zoom calls and can “answer questions when called upon and also proactively jump in”
Databricks leverages AI to manage their massive community and identify the highest-value prospects from millions of open source users
Getting Ready: Graham Moreno emphasizes: “Much more of the success of the business will be predicated on finding product market fit and delivering customer value rather than being exceptional at developing and scaling go-to-market.”
The Bottom Line: Act Now or Get Left Behind
These ten learnings aren’t predictions—they’re observations from leaders already operating in the AI-powered future of sales. The window for adaptation is closing rapidly.
Your 90-Day Action Plan:
Week 1-2: Audit your team’s AI usage and curiosity
Week 3-4: Implement basic AI tools for meeting prep and CRM automation
Week 5-8: Deploy AI for pipeline analysis and deal risk assessment
Week 9-12: Begin building hybrid human-AI customer experiences
The Choice is Binary: As Dmitry Shevelenko puts it: “The imperative is to move faster because your competitors are moving faster.” You can either lead the AI transformation in your market or watch competitors who do take your customers, talent, and market position.
The leaders profiled here chose to win. What will you choose?
The future of sales belongs to those who build it. Start building yours today.