“From the Desk of” is a new editorial series focused on the members of Round and how they lead. From startups to some of the world’s biggest tech companies, follow along to see how some of tech’s most successful technologists think about leadership within the tech industry.
Zach Wentz helps others learn to be better tech leaders through his newsletter The Stoic Manager, where he shares his extensive experience leading product and engineering teams at both big tech companies and startups. Zach currently is a Software Development Manager at Amazon Music, previously working at Netflix and CrossFit. We sat down with Wentz for a conversation about how he leads.
Listen and adapt.
Everyone that I have reported to, and that has reported to me, has shaped me, but a few notables include:
Sabry Tozin taught me to lead like a stoic and the importance of psychological safety.
Chris Goss taught me that your team is a product, and treating it as such can lead to innovation.
Lauren Tan taught me to be humble and that your best hires are the ones you worry will take your job.
Gagan Hasteer taught me to earn trust and get into the details.
Todd Wynne taught me to inspire, think big, and make big bets.
Ryan Holiday taught me that my ego is my worst enemy and that tackling obstacles leads to growth.
Kelsea Wentz taught me that difficult conversations build understanding — don’t avoid them.
In my first six months as a Netflix leader, I struggled. I was stressed and overwhelmed. During our yearly 360s, where we write feedback for one another, I received feedback from 30 people, and 28 of them mentioned that I should "start delegating." But it wasn’t until a few weeks later, during a one-on-one with a team member that I understood what they meant. I still remember the moment: we were taking a walk for our one-on-one and as we returned to the building, just outside the door, I asked, "Are you bored?
"Their eyes lit up. They nodded yes.
I realized they wanted more responsibility, and I was standing in the way. I thought I was protecting my team, but I was inhibiting their growth. So I asked this person, “What are we not doing as a team that we should be?” And when they answered, I decided to bet on their proposal. I told them to go ahead and work with our product manager on completing the task. Looking back, it seems obvious to share responsibility with my team and delegate projects but it was uncomfortable early in my leadership career. I fell in love with leadership when I shifted my focus from managing stakeholder expectations to managing my team’s growth. (And, as it turned out, our stakeholders loved the new program). Nowadays, I seize any opportunity I can to bet big on someone. It's why I still lead today.
Too often, I see leaders seeking to empower their reports by pointing out company values like “we support a healthy work-life balance.” Sure, we all do… but reminding me of that is not empowering. What’s empowering is modeling. Describing how you, as a leader, achieve a work life balance by blocking your calendar at 5pm everyday.
It’s a trite example, but it applies to almost all leadership matters. You want your team to be open to feedback? Ask for feedback, and respond with a thank you. You want your leaders to admit failure? Be self-critical at your next team meeting.
Marcus Aurelius said it best in his book Meditations, “Waste no more time arguing what a good person should be. Be one.”
That’s my method: setting an example others can follow and be inspired by. One caveat: this works with peers and reports, meaning people who already see you as a leader. But if you want to elevate the leadership of those above you, your example might not mean much. I’ve found a good question to be a good substitute.
Whether it's a good question or a good example, we're trying to get our fellow leaders to reflect, to look inward because empowerment comes from within. How do you ensure you have good questions or that you're setting a good example? You need exposure to role models of your own and you also need someone asking you questions. My advice? Find a community of leaders working at your level or higher and join them.
Tech works at a faster pace than other industries and also offers the opportunity for outsized impact. As tech leaders, we need to know what our teams are talking about to measure, to coach, and to probe their thinking. No matter how high up the ladder we climb, we have to stay close to “the work”. We also have to establish a vision. Finally, Moore's Law has a consequence: your solutions get outdated. For example, designs that might not have made sense two years ago due to costs or physical constraints, might make sense today. To keep up in our industry, you have to maintain a beginner’s mindset and stay curious about what is happening in the industry.
In tech, a small team can have a big impact. It makes the work exciting and fulfilling, but also comes with ethical considerations. Privacy, data security, and the social impact of our products and services are not well understood when we build them nor in retrospect. The entities that are supposed to regulate the companies we work for don’t have the requisite understanding to know what or how to regulate. As such, it is incumbent upon tech leaders to consider ethical implications while trying to keep the pace — which is no small challenge.
I'm optimistic that the industry will prevent problems like the ones it created in the past and even unwind some existing problems. Why? As an industry, we are starting to benefit from time. For better or worse, we’ve had the opportunity to see how past choices have played out. As a result, we’re more aware of the consequences of our design choices.
Organizations like Round make me optimistic too. Its members are in tech and conscientious. And more importantly, they’re senior leaders with key decision-making responsibilities.
I’m also optimistic that the industry will deliver on the promise that got me into it: “solving big problems.” Why? Generative AI. Before LLM and stable diffusion, it seemed like we were trying to squeeze the last few drops out of the SaaS, retail, and social media lemons. Now? LLMs and stable diffusion have a clear application to the more complex problems we all share.
However, I’m also aware of the problems these two advancements present. Every conversation I have about the potential benefits includes a discussion about the potential issues as well. For example, a few of us stuck around to talk after a recent generative AI discussion at Round. We discussed how it will advance medical diagnosis and care. We then turned to the data that will train it — data that comes from our inequitable healthcare industry. How can we be sure we won’t train a model that produces the same outcomes of our current healthcare system more quickly? That we’re already having these conversations at this early stage gives me hope for the future. For optimism to produce positive outcomes, we need tech leaders across the industry thinking about their products’ impact as they build them.
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