Thank you so much for joining us in this interview series. Before we dive in, our readers would love to learn a bit more about you. Can you tell us a bit about your childhood backstory and how you grew up?
I was born in Israel but spent part of my childhood in Miami before moving back to Israel, where I now live in Tel Aviv. My life has often taken me back and forth between Israel and the U.S., whether for business, family, or personal travel.
Growing up, I had a deep love for music. I started playing the piano at nine years old and, over time, developed a passion for creating music, especially inspired by movie soundtracks and electronic trance. In 2011, I released a music album, which is still available on Spotify and Apple Music for those curious to listen.
In addition to music, I was always drawn to creating and innovating. Coding became a natural outlet for this passion early on. Over the years, this love for building and problem-solving has evolved into a focus on cutting-edge technologies like AI, where I continue to explore and innovate every day.
None of us are able to achieve success without some help along the way. Is there a particular person who you are grateful towards who helped get you to where you are? Can you share a story about that?
Absolutely. Early in my career, I was working at a startup that was going through a challenging time. The company’s ability to raise its next round of funding was uncertain, and that uncertainty cast a shadow over everything. At the time, I had an open role to fill, but I found myself questioning whether it was the right thing to do. How could I hire someone when I couldn’t guarantee the company’s future — or theirs?
I turned to my mentor, Ziv, for advice. I asked him, “How can I hire this person when I can’t promise what’s next for them or the company?” Ziv didn’t hesitate. He replied, “What’s your assumption? If your assumption is that the company has no future, then we should be having a different conversation. But if you assume there is a future, then what’s stopping you?”
That simple question reframed everything for me. Ziv’s advice taught me to approach uncertainty differently. Instead of getting stuck in the endless “what-ifs,” he showed me how to make decisions based on a clear assumption about the future. His words simplified what felt like a complex, overwhelming situation and gave me a practical framework to act confidently.
Even now, whenever I face tough decisions, I think back to that conversation. It wasn’t just about hiring someone; it was about learning to focus on the possibilities rather than the unknowns. That mindset has shaped how I lead and make decisions to this day.
Can you please give us your favorite “Life Lesson Quote”? Can you share how that was relevant to you in your life?
“Don’t grow up, it’s a trap.”
This quote resonates deeply with me because it’s a reminder to approach life with curiosity, playfulness, and an open mind. Growing up often comes with societal pressures to “be serious” or “play it safe,” but I’ve learned that keeping a childlike sense of wonder is key to innovation and resilience.
For example, early in my career, I chose to dive into AI when it was still a relatively niche and uncertain field. Many people hesitated, thinking it was too risky, but I treated it like an exciting new puzzle to solve. Life feels much more rewarding when you treat it like a playground rather than a rigid set of rules to follow.
You are a successful business leader. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?
- Communication:
Business is all about people, and communication is the bridge that connects them. You need to adapt to different communication styles to get your message across. For example, when we launched AI tools at monday.com, I worked closely with the Engineering, Design, and Marketing teams. Each team had different priorities, so I had to tailor how I communicated the vision to ensure everyone understood their role and how it contributed to the bigger picture. That alignment made all the difference in our success. - Beginner’s Mind:
This means staying curious and treating every problem as if you’re encountering it for the first time. Expertise can sometimes blind you to new ideas, but curiosity keeps you open. For example, when I worked on an early AI assistant, I questioned traditional methods and explored new approaches, which led to breakthroughs we wouldn’t have found otherwise. - Determination:
Staying focused on your goals, even when things get tough, is key. One example of determination was when we pushed boundaries in AI development. At monday.com, we took on the challenge of creating tools that could predict risks in complex workflows — something many thought wasn’t feasible. By staying focused, iterating relentlessly, and refusing to accept the limits of existing technology, we developed our Risk Analyzer. It proved that we can solve problems that once seemed out of reach with determination.
Ok super. Let’s now shift to the main part of our discussion. Share the story of what inspired you to start working with AI. Was there a particular problem or opportunity that motivated you?
My journey in AI started during the chatbot boom of 2015. I remember interacting with an AI bot that could understand intent — it felt like magic. It wasn’t just a novelty; it solved real problems like booking appointments or answering complex questions. That moment sparked my curiosity, and I began digging into how these systems worked. I realized how accessible AI had become, with tools and APIs that made it possible for developers to build powerful applications without needing a PhD in machine learning. The endless possibilities were exciting, and I knew I wanted to contribute to this transformation. Since then, I’ve been dedicated to building AI products that solve real-world challenges and improve people’s lives.
Describe a moment when AI achieved something you once thought impossible. What was the breakthrough, and how did it impact your approach going forward?
When DeepMind’s AlphaGo defeated Lee Sedol in the game of Go, it was a pivotal moment for me. Go is an ancient game with near-infinite possibilities, and I never imagined AI could master it, let alone surpass human champions. Watching AlphaGo employ deep learning to develop strategies that felt creative and intuitive — qualities we typically associate with human intelligence — completely shifted my perspective on AI. It showed me that AI isn’t just about automation or solving predictable problems; it can tackle challenges in ways we might not anticipate. This realization pushed me to think bigger in my work, focusing not just on efficiency but also on unlocking entirely new possibilities with AI.
Talk about about a challenge you faced when working with AI. How did you overcome it, and what was the outcome?
One significant challenge was building a personal assistant chatbot to manage reminders. Before large language models (LLMs), we used BERT for intent classification. While BERT was powerful, it struggled to handle the endless variety of ways users might phrase their requests. Manually training the system for every new intent was unsustainable, and users often ended up frustrated when their inputs weren’t understood. To tackle this, we introduced a fallback mechanism that gently guided users back to supported intents while collecting valuable data to improve the system over time. This iterative approach helped us refine the bot and ultimately deliver a smoother, more reliable user experience.
Can you share an example of how your work with AI has had a meaningful impact (on others, on business results, etc)? What was the situation, and what difference did it make?
One of the most impactful projects I’ve been involved in is the release of monday.com’s AI Blocks. These are atomic AI actions — such as summarizing content, extracting key information, or performing custom AI tasks — that can be seamlessly integrated into automations and workflows across the monday.com platform.
The goal was to address a key challenge: enabling organizations of all sizes and industries to unlock the potential of AI without requiring technical expertise. By designing AI Blocks as modular and accessible tools, we’ve empowered users to create meaningful AI-driven workflows and automations tailored to their specific needs.
For example, a team might use an AI Block to automatically summarize meeting notes or project status updates, extract deadlines from project briefs, or even customize unique AI actions specific to their industry. This streamlines workflows and democratizes access to AI, making it possible for anyone — regardless of their technical background — to leverage its benefits.
The impact has been significant. We’ve seen teams improve efficiency, reduce manual effort, and uncover new ways to solve challenges. Beyond business results, it’s been incredibly rewarding to see how AI Blocks have sparked creativity among users, enabling them to think of AI as a tool and a collaborative partner in achieving their goals.
