"How did they do that? How did they get there?" Companies succeed because of the people who build them - operating leaders who scale businesses to new heights and make decisions every day that can impact entire industries. Our Operator Spotlight gives you the inside track from one of our incredible operator Limited Partners (LPs) who are changing the game and operating some of the world's most successful companies. Read on for lessons learned and mistakes made, perspectives from the top, practical advice, and ideas on what's next.
We spoke with Ana Pinczuk, President of Product and Technology at SentinelOne, the autonomous cybersecurity platform now securing nearly one-fifth of the Fortune 500. Ana is an engineer-turned-executive who has led technology businesses from startups to $12B+ in revenue and 30,000 employees. She joined SentinelOne in 2022 as a board member and took on the President role in 2025, bringing oversight of the company's full product and technology organization. Before SentinelOne, Ana was COO at Dexterity (an AI robotics startup), Chief Development Officer at Anaplan, Chief Product Officer at Veritas, and President and GM of HPE Pointnext, HPE's $8B+ services business. She also spent 15 years at Cisco in senior sales and engineering leadership roles. She holds four master's degrees spanning robotics, MBA/technology management, software management, and cybersecurity risk and strategy. Ana also serves on the boards of Aptiv and SmartRent, as well as Cornell University and the Latino Donor Collaborative.
You've lived through the internet wave, mobility, cloud, SaaS, and now AI. Each of those shifts created new categories of risk. What makes the AI security moment fundamentally different from the ones that came before it?
ANA: Each prior wave created new risk categories, but the risks felt more containable, and companies could opt in at a reasonable pace, over a few board meetings. Now the half-life of any security defense is shorter than we’ve ever seen, and every prompt, every agent action, every model call is a potential attack vector. The asymmetry between attackers and defenders has flattened - both sides can move at the same speed, so escalation or de-escalation happens in near real-time. Risk mitigation has to match that.
On the business side, companies that don’t move fast can become structurally uncompetitive to an AI-first challenger. Our workforce is changing - we’re redefining the talent, roles, and skills we will need for the future. And when everybody is a builder, you execute faster, but you also have more places where guardrails can be missed. In prior waves, a slow adoption curve was a safer posture. With AI, the opposite can be true - slow adoption can kill your value proposition while fast adoption without guardrails creates real exposure. The art is finding the disciplined speed in between.
SentinelOne just crossed $1B in revenue and is building for the AI era, with 50%+ of annual bookings coming from Emerging Platform solutions. What does "building for the AI era" actually look like inside your product and engineering org day to day?
ANA: Within our team, three transformations are happening at once. We have been AI-focused for years and have accelerated AI-powered innovation. AI is also changing how customers buy, and we’ve introduced consumption models and new packaging that align with how AI-led value is consumed. Lastly, we are also changing how we work with AI internally. We are investing in our AI harness - the tooling that turns every product manager, designer, or engineer into a builder with agentic capabilities. We are extending our capabilities beyond our product and engineering teams so that our go-to-market teams can also quickly drive tailored solutions for our customers. We kicked off an AI Way of Working program that allows our teams to help exercise AI ways of working and, in so doing, help to shape our AI-enabled processes, roles, and tools. We aren’t bolting AI into the company - we are really rebuilding how we work - and how our customers consume value from us - with AI as a fundamental foundation.
You came to the President role from SentinelOne's board. How did that board vantage point shape the way you've approached leading the product and technology team? What did you see from the board seat that changed how you operate?
ANA: It's a unique position and a privilege to come from the board and step into the operating role at this moment in the company's life. I've approached leading the team with deep admiration for what's been built here and with the recognition that scaling SentinelOne beyond $1B requires considering different actions than those that got us to this point. I'm focused on three areas.
First, profitable growth. Being deliberate about the portfolio, doubling down on our runtime protection business, and defining the next growth vectors. Second, scale with an AI-first mindset. Executing at the pace and quality our customers expect, with AI woven into how we operate. Third, talent for the future. A significant share of my time goes into building leaders, bringing more of a GM mindset to product and engineering, and identifying how the team needs to shift for an AI-led world.
The board seat gave me an outside-in perspective I've kept — focused on what shareholders need to see: predictable performance, tight alignment between product, engineering, and our field teams, and strong financial discipline.
You've recently partnered with OpenAI on the Trusted Access for Cyber program. AI partnerships in security are moving fast. How do you evaluate which partnerships will actually compound your platform's value versus ones that are just noise?
ANA: I evaluate every partnership against three elements - whether it compounds our platform’s value over time, whether it provides customers something they can’t get any other way, and whether the partner is building towards the same future we are.
WIth OpenAI on Trusted Access for Cyber, we get early access to defender-specific frontier models and our deployment feedback shapes how those models continue to evolve for cybersecurity. Both sides get smarter quarter over quarter, benefiting our customers. As another example, we have a Google Cloud partnership where the compounding comes from distribution depth - every SecOps customer becomes a SentinelOne touchpoint, and integration deepens with every release. With our participation in Anthropic’s Glasswing effort, the compounding is at the ecosystem level - we get an early signal on the emerging AI-native security capability and more insight that can benefit our joint customers.
The partnerships that truly make a difference are those that are worth more to us in year two than year one. These are the ones that are more valuable to customers and that build platform differentiation every quarter.
How are you thinking about the dual challenge of AI as a threat vector and AI as a defense tool?
ANA: It’s a good question and I think about it as a three prong challenge, not two.
- Secure AI Itself: Agents are a new attack surface — prompts, agent actions, and the data they touch all need to be defended. That's what Prompt does for our customers.
- Defend with AI. Use frontier AI in our own defense — Purple AI, agentic detection, autonomous SOC. Defenders have to match attacker speed.
- Govern the agents. They're new actors with identity and access. The whole security model — who did what, when, on whose behalf — has to be rebuilt for a world where the actors aren't always human.
We're investing in all three on one platform. That's the bet.
On the governance side of AI in security, what's actually stuck? A lot of companies are writing AI governance frameworks, but the gap between policy and practice is wide. What has SentinelOne done that's moved past paper?
ANA: We’ve taken several concrete steps at SentinelOne. First, the Prompt acquisition gives our customers governance over their own AI agent usage — visibility, audit, control over what data flows to which model, and the ability to enforce policy at the prompt and agent level. We didn't just write a framework; we shipped governance as a product.
Second, we put trust under one executive. Our Chief Trust Officer owns AI risk, with the CISO and VP IT reporting to her. One accountable function, not three competing ones. And we run a weekly Governance Council with the authority to actually decide things — not a quarterly committee that drafts memos. Decisions in days, inside a defined risk envelope.
Third, we built the guardrails into the tooling itself. Model gateway, identity, audit, data classification all live at the platform level, not the policy level. If you want to use a model, you go through the gateway.
What I love about our model is that we’ve gone beyond a paper to embedding AI governance into the normal AI way of working and learning.
Describe one pivotal moment in your career that was truly defining for you - an opportunity that changed your life or a moment where you recognized defeat and changed course.
ANA: My most pivotal moment came earlier than most would expect. My family left Argentina when I was a teenager, and we had to start all over again as immigrants with virtually nothing besides my parents’ education. I saw my parents restart their lives, and recognized the importance of committing to a new country and rebuilding from scratch. This early lesson changed my life, as I now grew up in the US and had to rely mostly on myself to shape my future. It’s the reason I focus on continuous learning, take on new career challenges, and feel comfortable navigating change. Once you escape a country and have to start all over, there aren’t many experiences that rattle you - you feel like you can persevere and prosper no matter what comes your way.
You have an unusual career path for a CPTO: deep engineering roots, then sales, operations, services. How has that sales and go-to-market experience changed the way you build product?
ANA: The biggest gift of an unusual career path is appreciation. Having sat in many of these seats — sales, services, operations, engineering — I have real empathy for the customer and the seller. That experience has forced me to take a systemic view of how we build product. How will this be sold? How can it be monetized? How does it get supported in the field? Those questions belong inside the product conversation, not after it. Building product in isolation is the most expensive mistake a tech leader can make. Building it with the rest of the company in the room is how you ship things that actually win in the market. Being a strong collaborator has helped me build better products and become a better technologist.
What's a piece of advice you would give to yourself 10 years ago, if you had the opportunity?
ANA: I would tell myself to continue to stay hands-on. As you scale into bigger roles, the gravitational pull is to delegate everything and become "strategic." Resist it. Stay in customer conversations, stay in the product, stay in the technology. The best leaders I know still get their hands dirty — and it's not nostalgia. It's how you stay credible with your teams, how you keep your judgment sharp, and how you spot what doesn't show up in the dashboard. And this is particularly important in an AI-forward world.
What's a recent insight you picked up - from a book, a podcast, an article, a movie, etc - that made you really stop and think?
ANA: I have gone back to school every decade. Cornell years ago, programs along the way, and recently NYU's Cybersecurity Strategy Masters. It's a pattern — and the insight I've been sitting with is that going back to school isn't really about credentials. It's about testing my ability to be in the game and be a continuous learner. The half-life of any specific skill is shrinking. What made me valuable two years ago isn't what makes me valuable today. The way to keep up isn't reading about new things — it's getting back into the work yourself. Education for a leader at this stage isn't only an intellectual exercise. It's a posture and a mindset that means being proud of doing, not just delegating.
