Tiki Bar with Justin Santilli | Turning technical curiosity into GTM advantage

We sat down with Justin Santilli, who leads Enterprise Go-To-Market at Cursor, for a straight-talk tour through his path from busboy shifts and 150+ cold-call days to helping advise executives on AI rollouts. Justin’s through line: lean into the hard, technical stuff, simplify it for buyers, and surround yourself with people you’ll want to work with again.

From Outback to 200 dials: building grit early

Justin’s first paid gigs weren’t glamorous: busboy at Outback Steakhouse (until they discovered he was 15) and front-of-house roles in Texas restaurants and retail. The value wasn’t the paycheck—it was the tolerance for late nights, odd problems, and serving people in unpredictable environments. That carried into his first professional sales role at SHI, where entry-level selling meant long hours and tedium under a firehose of new information.

His break came with SHI’s small “Black Ops” team focused on Microsoft licensing. The mandate: 150–200 dials a day and then run the meetings. The unlock: he realized he could translate complex licensing into simple, buyer-friendly decisions. That technical simplification muscle became a career-defining edge.

• Muscle built: high-volume prospecting paired with end-to-end meeting ownership
• Superpower spotted: turn complex technical/contract constructs into plain language
• Career lesson: early roles are tedious by design; the payoff compounds if you keep learning

Choosing inflection points: Sprinklr, Google Cloud, Databricks

Justin has a habit of picking companies right before they pop. At Sprinklr in LA, he discovered how much easier selling gets when the product resonates with your own experience. It was also his first exposure to formal enterprise rigor (Command of the Message/Force Management), working with brands like Sonos and Mattel. That stage taught him to match product-market fit with operational sales excellence.

Back in Texas, Google Cloud called. The pitch wasn’t just the brand—it was a chance to learn cloud while selling to Bay Area startups who already lived it. His territory luck mattered; many prospects arrived with deeper Kubernetes/GKE knowledge than some internal teams, which forced a collaborative, technical posture. The culture felt “Googly”: informal, highly collaborative pods, and customers appreciated the directness paired with technical depth.

Then came Databricks. The Lakehouse concept clicked for him—convergence of operational and analytical workloads—and the brand-new Digital Native segment offered that tight-knit, founding-team dynamic he thrives in. Pattern: he tracks technical trends he genuinely enjoys nerding out on, then joins when product-market fit is imminent but not yet saturated.

• Pick work you can explain simply and care about personally
• Look for teams at the moment before scale—tight founding groups teach fastest
• Let curiosity guide you to technical truths; that’s where conviction comes from

Cursor: talent density, PMF at full blast, and advising the C-suite

Moving to San Francisco for Cursor, Justin expected intensity—he still underestimated it. He calls the talent density the highest of his career across every role, and the product-market fit the most extreme he’s seen. Demand is such that executives aren’t just buying; they’re asking Cursor’s sellers what good looks like in AI rollout and operations, and how peers are winning.

The pace requires heavy use of AI internally just to operate. Capacity has been tight as the team scales. For Justin, this is the purest version of the job: meet buyers where they are technically, cut the fluff, and serve as a guide to outcomes.

• Signals of PMF: inbound pull from execs, requests for peer best practices, urgency on timelines
• Seller posture: technical advisor first, deal-runner second
• Operator reality: AI-augmented workflows to match market speed

How his approach evolved: champions over spreadsheets

Early on, Justin believed business decisions were strictly rational and data-first. Experience reframed it: decisions are human, then rationalized with data. Today, he prioritizes building champions and cohorts inside accounts while still backing the story with numbers. He also keeps the long view on relationships—colleagues, managers, and partners reappear across roles and companies.

Favorite deal story: at Databricks, while pursuing a land at Zoom, he texted a number he thought belonged to an exec—and reached Eric Yuan instead. Eric replied on a Saturday, and Zoom signed on Sunday. The lesson isn’t “spray texts to CEOs”; it’s that thoughtful persistence, paired with real alignment, can compress timelines when momentum is there.

• Decisions are human; arm your champion to rationalize them
• Persistence works best when you’ve already done the alignment work
• Your network is an asset you build by showing up well—over years

What he’s watching next

AI’s impact on the sales profession is top of mind. Cursor’s internal pace makes AI table stakes for execution, and Justin expects the broader sales motion to change materially over the next two years. He doesn’t claim certainty about the exact shape—only that capabilities are compounding, and teams that marry technical fluency with clear, human buying journeys will outperform.

Non-business rec he loves: God of War Ragnarök—an unexpectedly moving story about a father and son wrapped in an intense game.

Watch the full conversation: https://www.youtube.com/watch?v=kp6aYwwrd54

Closing thought: If there’s a Santilli playbook, it’s this—do the hard reps, get technically curious, simplify relentlessly, and choose teams where you’d bet your time again. The rest tends to follow.

Full episode: https://www.youtube.com/watch?v=kp6aYwwrd54