An Interview With Rachel Kline

Always have a customer and user centric approach. Get out there and talk with real customers and users. Understand their problems and how your product helps solve these problems. Build with empathy.

a world where the pace of change is faster than ever, the power of great ideas has never been more crucial. And yet, developing these ideas into impactful, market-ready products can be an immense challenge. The best products are not born overnight, they’re the result of dedicated ideation and innovation processes. These processes aren’t always easy, but they’re necessary and can be catalyzed with the right strategies and approaches. How do you foster a culture of creativity within a team? How can one rapidly translate ideas into prototypes and eventually finished products? How can roadblocks be anticipated and managed effectively to avoid unnecessary delays. In this series, we’re eager to explore insights, stories, and actionable tips from those at the forefront of ideation and innovation. As part of this series, we had the distinct pleasure of interviewing Babak Pahlavan, founder and CEO, NinjaTech AI.

Babak Pahlavan is founder and CEO of NinjaTech AI. He has been working on AI since 2008, when he was the founder and CEO of his first AI startup named CleverSense. CleverSense was acquired by Google in 2011, where it became an important personalization layer in Google Maps. Babak went on to spend 11 years at Google as a senior director of product management, where he led and scaled several large products and teams including Google Analytics, Enterprise Measurement Suite and others. He left Google in October of 2022 to found NinjaTech AI in partnership with SRI, which is the team’s original home of Siri. NinjaTech AI’s mission is to democratize access to AI-powered executive assistants, to give administrative time back to every professional and take the drudgery out of work.

Thank you so much for joining us in this interview series! Before diving in, our readers would love to learn more about you. Can you tell us a little about yourself?

Inmany ways I’m a textbook story of the American dream. I grew up in Iran, and my family immigrated to the USA just after I finished high school. Shortly after we arrived in California, I was fortunate to attend UC Berkeley for my Bachelor’s degree where I studied electrical engineering and computer science. After that, I jumped straight into my Masters program at Stanford, where I focused on data mining and my love of ‘assistants’ was born.

When I finished at Stanford, I quickly founded my first AI company — CleverSense — which was focused on creating an assistant for navigating the physical world; this was before Google assistant was born and while Siri’s team (that came out of SRI) focused on being an information assistant in your pocket. At CleverSense, we focused on “personalizing the world around you.” About 18 months after we raised our Series A, Siri was acquired by Apple and CleverSense was acquired by Google in 2011. We were a natural fit for Google, as they were especially interested in using our technology to make Google Maps personalized. In total, I spent 11 years at Google as a Senior Director of Product Management, where I had the opportunity to scale several large products and teams including Google Analytics and Enterprise Measurement Suite. It was an incredible & unforgettable experience; Google was and continues to be a very special company.

In the last two years, I studied BERT and Transformer architectures and started to dream about the next generation of assistants — with a special focus on understanding and taking care of tasks in the real world. I also re-established a relationship with my friends at SRI, where I quickly learned that they too are interested in building next-gen assistants. So, in October of 2022 I took the plunge: I left Google, I joined SRI as an Entrepreneur-in-Residence and I founded NinjaTech AI. My top priority was to build an exceptional team; only a few months later my good friend Sam — a senior AI engineering leader at Meta — joined me as my co-founder and we quickly started pulling in talent to make NinjaTech AI a reality. NinjaTech AI’s mission is to democratize access to autonomous AI assistants, to give administrative time back to every professional and take the drudgery out of work. We’re early into our journey, we have incredible investors, an amazing team of ex-Google, ex-AWS and ex-Meta leaders, and there are exciting things to come!

What led you to this specific career path?

I loved working with computers and technology from a young age, my parents worked incredibly hard to foster that passion and give me every opportunity to explore it. I’ve always been a product tinkerer and I’ve always had a passion for thinking about the next generation of technology. In-particular, I’ve been passionate about how robots can make our lives easier in solving complex everyday problems. As my career has developed, I’ve loved the engineering side of building these products, and equally loved interacting with the users who benefit from these products. Product management was a natural fit for me.

As I started building CleverSense, I became very passionate about AI assistants. At that time, the technology didn’t exist yet to build autonomous AI agents like the ones we’re building today at NinjaTech AI, but it was able to help immensely with personalization as search was taking off. Consumers were being overwhelmed with access to information and choices, Alfred (our CleverSense assistant) helped personalize what was relevant. The spark for solving everyday problems with AI was cemented during that era. Throughout my time at Google, I remained very passionate about this topic, I saw how AI was evolving, and I worked on products with similar themes as I grew into product leadership roles.

The decision to leave Google to start NinjaTech AI was very deliberate. I’d honed a skill set, knowledge base, a network of talented technologists and investors, and AI technology had evolved to a state where the stars were aligning to build a truly autonomous personal AI.

Can you share the most exciting story that has happened to you since you began at your company?

It is admittedly hard to pick only one! When you build a new company, in a new and rapidly-growing technology space like AI, there are exciting things happening every day. For example, when we closed our pre-seed investment in NinjaTech AI of $6 million, it was incredibly exciting to know that experienced investors and leaders felt conviction in the opportunity and in our team. When we opened our office and put up our logos it was an incredible feeling, and when we made our first hires I was overwhelmed by the number of applications and close colleagues that were ready to jump in. Today, we have over 30 talented Ninjas including full-timers and contractors.

From a technology perspective, the most exciting story I can share is when we first-connected our AI agent — named Atlas — to Google Calendar. It was the culmination of so many years of work, new technology, and team finesse. In an All-Hands meeting, our team asked Atlas to do three seemingly simple tasks: 1) to set up recurring 1:1 meetings with my co-founder, 2) to create space for a 30 minute walk everyday in my calendar, and 3) to analyze my calendar for where I could collapse meetings to save time. Within a few seconds, all three tasks were completed by Atlas and I’d saved real time in the process.

In that moment, we went from an “information” assistant, to a “task” assistant that could truly get tasks done for you in the real world. The look in our team’s eyes was unforgettable: we all watched the AI write a complex algorithm on-the-fly and execute it flawlessly. This is a unique technology that’s been primarily invented by our Chief Science Officer, Arash, who is a friend of over 20 years and a deep expert in artificial intelligence. We are now convinced that it’s now entirely possible to have robots that can think and take care of mundane tasks and everyone will eventually have one of these in their pockets soon.

What are some of the most interesting or exciting projects you are working on now? How do you think that might help people?

There are several exciting projects we’re working on, which we believe truly make NinjaTech AI’s technology next-generation.

  1. Autonomy: We’re hearing a lot about co-pilots in the AI world; Atlas is going to be an autopilot. Co-pilot accompanies you while you do tasks, autopilot takes over the tasks for you so you can get back to your real job. For example, if you’re looking to book a flight, the co-pilot will assist you while you do it, and the autopilot will do the research and the booking for you. Building autonomy into AI is very hard, but we think it is a critical step to humans achieving the maximum productivity outcomes from AI.
  2. Dynamic AI Agents: Inspired by DeepMind’s AlphaGo™, NinjaTech AI has gone beyond solving static games. The world operates dynamically, so we have built autonomous AI agents that continuously adapt to their environments. Rather than use playbooks and static decision trees, our agents dynamically adjust to complete complex tasks using multi-agent game theory and goal-oriented execution. This eliminates the need to learn every permutation of a game; our AI agents build a neural net of intuition which eliminates the need for expensive data sourcing and big LLMs.
  3. Real-Time Problem Solving and Learning: NinjaTech’s AI agents take an autonomous hierarchical approach to learning, by decomposing complex problems into digestible tasks that can be solved with existing skills and neural intuition. The AI agents formulate a step-by-step plan to solve each sub-task, self-validate the plan and solution before taking action, and then write their own validated code into the neural net of intuition. This breakthrough enables our AI agents to transfer learning and pick up new skills incredibly quickly, and it brings the barrier to entry for a user to essentially zero — you just start conversing with our AI agents and it will get real tasks done for you.
  4. State-of-the-Art Streaming Assistants: Users can talk live face-to-face with their digital assistants and even capture videos of them and share them. The assistants are created using state-of-the-art Unreal Engine 5 and are seamlessly delivered to users via NinjaTech AI’s proprietary cloud streaming technology similar to Microsoft Cloud Gaming or Nvidia’s Geforce or Amazon’s Luna. No fancy hardware is needed; as long as you have a good internet connection, you can interact with your CGI-quality digital assistant!

You’re a successful business leader. What are three traits about yourself that you feel helped fuel your success? Can you share a story or example for each?

  1. Curiosity — If you choose a career in technology, it means you are committing to a world that is constantly evolving — quickly! To be successful over time, I believe you need to have an unrelenting curiosity that drives you to become part of that evolution itself. Early in my career, my curiosity helped me catch up to the wave. As my career advanced, I felt I was able to spot the swell earlier and anticipate the waves more. As I became a leader of large teams, I always made it my goal to teach others to live with the same curiosity.
  2. Scrappiness — It is easy at big companies to find yourself constricted with processes, red tape and low velocity. A critical trait that I’ve always held from my first startup all the way through to NinjaTech AI, is the ability to get things done quickly. Some call this ‘test and iterate,’ for me it is equally about keeping things simple. Put differently, don’t create complexity, cut through it.
  3. Persistence — Every product, feature and launch is an experiment. Whether it is your core product, a marketing tagline or a customer presentation, you should expect to stumble and persistently adapt and try again. This persistent iteration will eventually lead you somewhere great, to produce something great, and to achieve great outcomes.

I look for these traits in everyone I hire — whether in a startup or on my teams at Google. These characteristics help build great products, do it in the fastest way possible and do it in a way that is driven by curiosity that drives real change and innovation. You need all three of these!

It has been said that our mistakes can sometimes be our greatest teachers. Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lesson you learned from that?

Plenty of examples come to mind, but there is one that stands out: Most product managers (myself included) tend to underestimate the importance of “delightfulness” in products; it’s especially overlooked for B2B products. The assistant that we made during CleverSense was called “Alfred.” We wanted to make it cute and fun, so we gave it a mustache that would start spinning if you touched it several times. This “easter egg’’ was something we only spent one or two hours on and didn’t think much of it. When we looked at our analytics, we quickly realized it was one of the most enjoyable features of our product! The lesson I learned: People enjoy using products that are easy to use; but they love products that are easy to use and are delightful.

Do you have any mentors or experiences that have particularly influenced your approach to product ideation and innovation?

I have been lucky to have tremendous mentors throughout my career. One of my best mentors and former managers of seven years is Paul Muret, who is the VP/GM of AI products at Google. Paul taught me how to build products at an immense scale, and he also taught me how to lead people with empathy, especially during tough times. His mentorship shaped the product leader I am today; I’ll be forever indebted to him.

In your experience, what is the anatomy of a strong product idea?

Strong product ideas come from thinking big and working backwards to solve user problems. For example, at NinjaTech AI, we’re building an AI-powered personal assistant for busy people. We’ve seen how powerful and helpful AI is and we know how much time busy professionals spend on administrative tasks. With NinjaTech AI’s new personal assistant, we’re solving real problems for busy professionals in a cutting edge, innovative way.

What approach does your team use for coming up with new ideas for products and features?

Leveraging AI to come up with new product and feature ideas is very experimental. There are essentially three components that need to align: 1) a need or problem that needs to be solved, and 2) dreaming up ways to solve that problem using AI, and 3) implementing experimental ways to solve it.

This is very much the process we went through when deciding on the core ‘skills’ for our NinjaTech AI first assistant. If you take an example like researching and booking travel, there are multiple problems you’re trying to solve for the users. The first is a research problem; they may not know anything about the location they’re traveling to. AI can help be an information assistant, this is a very solvable problem. The second is the overselection problem; there are so many flight options available that the consumers are overwhelmed with choice. AI can also solve that problem, by distilling the choices into a much smaller subset, without the user having to spend time on this — the AI can do it autonomously. The third step is the hardest problem, but is also immensely helpful — booking the flight! Perhaps the user has a preferred airline, a seat preference, a baggage preference. AI can also autonomously solve this problem if it knows the users’ preferences.

These three examples are graduating steps, but important ones that we go through when we come up with new ideas. Essentially, problem-led that are solved by increasingly complex AI resolution.

How does your product team manage new product and feature ideas?

Experimentation and iteration! The LLM and AI space is changing so rapidly. We’ve found that the best way to manage new product and feature ideas is to be constantly experimenting and iterating. This means everyone experiments and tries out new ideas quickly and cheaply, getting feedback from users, getting your hands dirty and making adjustments as needed.

Specifically, we’ve set up a few mechanisms to ensure we keep experimenting and iterating. First, we have a regular cadence of brainstorming sessions. This gives everyone on the team a chance to share their ideas, no matter how small or crazy they may seem. We’ve found that small or “crazy” ideas often end up being the catalyst for a much larger idea! Next, we ruthlessly prioritize! We make sure we’re focused on the key projects that fit with the long-term goals of the product and maximize the impact to our users and customers. Lastly, once we have prioritized our ideas, we start to develop prototypes. PMs get their hands dirty by doing quick proof of concepts, wireframes, etc. This allows us to test out the idea quickly and cheaply. Based on these proof of concepts or feedback we get, we iterate on the prototype and make adjustments as needed. We continue this process until we have a product or feature that we are happy with and that we believe our users will love.

We believe that this approach of experimentation and iteration is the best way to manage new product and feature ideas in the LLM and AI space. It allows us to be innovative and to quickly bring new products and features to market that our users will love.

What, in your view, is the biggest challenge with respect to innovation?

A combination of fearing failure and not thinking big enough. I’ve often found that the most successful product teams are the ones that “reach for the stars,” and welcome failure along the way. Many times I’ve seen product teams set extremely ambitious goals only to fail at hitting those goals. However, what they usually find is that, while failing at their original goals, they’ve been able to make considerable progress and launch products that delight their users. Another way I phrase it to my team is to “Shoot for Mars. Even if we fail, we’ll probably end up on the moon. And that’s pretty amazing in itself!”

Thank you for all of that. Here is the main question of our interview. Based on your experience, what are your “5 Tips for Accelerating Product Ideation & Innovation”?

Photo of the team behind Ninjatech AI

Here are 5 tips for accelerating product ideation and innovation:

First, always have a customer and user centric approach. Get out there and talk with real customers and users. Understand their problems and how your product helps solve these problems. Build with empathy.

Second, as product leaders, be deliberate about increasing and fostering cross-functional collaboration. Different perspectives at the table leads to more innovative ideas. Encourage open ideation without judgment. Some of the best products and services I’ve launched have come from one person having the courage to toss out an idea that’s been the catalyst to another’s even larger or impactful idea.

Third, focus on data-driven decision making. I was once in a meeting where we were deadlocked and the senior leader was listening to her lieutenants argue back and forth on a topic with their insights and views. She finally had enough and stopped them saying, “Do we have data on this issue? If we do, let’s go with the data. If not, and we’re going with opinions, we’re going with mine.” Let the data drive the decisions.

Fourth, shoot for Mars! Fall short. End up on the moon. Realize how awesome it is that you’ve reached the moon…then keep shooting for Mars!

Lastly, launch and iterate. Don’t let perfect get in the way of good and don’t be afraid to fail. Be quick but don’t hurry. Launch your product quickly, listen to feedback, iterate, and keep delighting your users and customers.

We are very blessed that very prominent leaders read this column. Is there a person in the world or in the US with whom you would love to have a private breakfast or lunch, and why? He or she might just see this if we tag them 🙂

Reid Hastings! I’m passionate about building high functioning diverse teams. NinjaTech AI shares a lot of the same values he implemented at Netflix — a high degree of transparency, a focus on talent density, and a willingness to experiment. I’d love to sit down and hear more about his journey in creating such a strong company culture building Netflix to a multi billion dollar company.

Thank you so much for this. This was very inspirational, and we wish you only continued success!