Earlier this year, when I worked as the General Manager of a software engineering team, I faced a significant challenge in how to effectively understanding and communicating our technical needs based on the roadmap. Being a non-engineer, I lacked the lived experience to independently assess and validate the technology, which made it harder to ensure alignment and accuracy in our goals. Not only that, but I had never before been the only non-technical employee within an entire organization, which meant that in addition to quickly learning about the ecosystem surrounding our technology and product, I also needed to rely on other learning channels to help me quickly form opinions and navigate some of the more operational business concerns.

During that time, I'd often leave meetings with more questions than answers, and I realized at the start of my time with that team that I had a lot of leveling up to. I needed to grasp enough about the technology’s functionality and the basic operations of our business to understand the landscape and confidently navigate our strategic objectives.

In a world before AI, it would have taken me dozens of hours, long conversations, and possibly also strategic executive coaching. In a world with AI, I was able to strategically use AI to help me learn how to level up much more quickly, in addition to serving a role as a helpful translation and communication go-between.

Here’s what my process would have looked like before and after AI.

The process is the same. The tooling is more nuanced and complex. This is what it feels like to integrate AI into your workflow.

Along the way, I learned that there are some pretty nuanced, but high leverage ways that AI can support us as both a de-escalation and translation agent.

What I found most helpful about using AI to learn such a complex and unfamiliar set of topics was its endless patience. I could ask question after question without feeling judged, and the AI’s neutral tone made it easy to explore concepts without self-doubt or embarrassment.

When I didn’t understand something, I could ask for simpler explanations, analogies, or metaphors without hesitation—this was key to my progress. Although I’ll be the first to admit that I wasn’t doing my best work in that role (leading without deep technical knowledge is tough), I gained something invaluable: the confidence that in challenging learning environments, I could use AI as a bridge to understanding.

One of the most powerful ways I used AI during this time was to "lower the temperature" when emotions ran high—whether it was frustration with slow progress, confusion around complex topics, or defensiveness in response to feedback. I’ve realized that, left unchecked, these emotions can easily escalate. But AI helped me de-escalate.

Instead, when I felt myself growing upset or defensive, I could type out my initial reactions and ask AI to help soften them, creating a more balanced response. When I received critical feedback from peers, instead of reacting in the moment, I could input the feedback into AI, process it privately, and work out an action plan on my own terms.

This approach continued even when I left that job. I conducted a retrospective on my performance, taking extensive notes, and then used AI as a personal coach to outline ways to approach my next role and refine my leadership style.

While I primarily used AI for professional situations, its potential for navigating different group dynamics is broad. For example, as the new president of my block association on the Upper West Side, I’ve become an unexpected leader of a multi-generational community. Our group includes both long-time residents who’ve lived on the block for decades and newcomers like me, who’ve been here for just a year.

We will inevitably have disagreements. Already I’m starting to see a few of them play out in real time. For instance, at one of our first block events earlier this summer, at a picnic in the park, one of the neighbors who joined us brought a bunch of bird food to feed the pigeons, a task that brought him unbridled joy but frustrated many of the rest of us who spent all afternoon chasing pigeons away from our children and our food. 

There are two sides to every story, aren’t there? On the one hand, the helicopters that buzz over New York City all day and all night long? On the other hand, as the parent of a 2-year-old, we literally can’t get enough helicopters in our family, and we literally spent summer nights on our rooftop counting the flyover appearances with glee.

Tonight marks our very first planning committee meeting with a larger group of 10 participants. The energy is very strong and excited, but I’m also anticipating some disagreements. That’s okay. I’m building these varied perspectives into the process—today is framed largely as a listening session. Later, I can spend time with our notes, maybe with the help of AI, to help me consolidate the feedback and seek out potential compromises in areas where we disagree.

Is it possible that this quiet, but powerful, use case for technology is the bridge that could help many more of us find common ground? Who knows? But something tells me we’ll all have plenty of at-bat opportunities to figure it out in the years ahead.

Earlier this year, when I worked as the General Manager of a software engineering team, I faced a significant challenge in how to effectively understanding and communicating our technical needs based on the roadmap. Being a non-engineer, I lacked the lived experience to independently assess and validate the technology, which made it harder to ensure alignment and accuracy in our goals. Not only that, but I had never before been the only non-technical employee within an entire organization, which meant that in addition to quickly learning about the ecosystem surrounding our technology and product, I also needed to rely on other learning channels to help me quickly form opinions and navigate some of the more operational business concerns.

During that time, I'd often leave meetings with more questions than answers, and I realized at the start of my time with that team that I had a lot of leveling up to. I needed to grasp enough about the technology’s functionality and the basic operations of our business to understand the landscape and confidently navigate our strategic objectives.

In a world before AI, it would have taken me dozens of hours, long conversations, and possibly also strategic executive coaching. In a world with AI, I was able to strategically use AI to help me learn how to level up much more quickly, in addition to serving a role as a helpful translation and communication go-between.

Here’s what my process would have looked like before and after AI.

The process is the same. The tooling is more nuanced and complex. This is what it feels like to integrate AI into your workflow.

Along the way, I learned that there are some pretty nuanced, but high leverage ways that AI can support us as both a de-escalation and translation agent.

What I found most helpful about using AI to learn such a complex and unfamiliar set of topics was its endless patience. I could ask question after question without feeling judged, and the AI’s neutral tone made it easy to explore concepts without self-doubt or embarrassment.

When I didn’t understand something, I could ask for simpler explanations, analogies, or metaphors without hesitation—this was key to my progress. Although I’ll be the first to admit that I wasn’t doing my best work in that role (leading without deep technical knowledge is tough), I gained something invaluable: the confidence that in challenging learning environments, I could use AI as a bridge to understanding.

One of the most powerful ways I used AI during this time was to "lower the temperature" when emotions ran high—whether it was frustration with slow progress, confusion around complex topics, or defensiveness in response to feedback. I’ve realized that, left unchecked, these emotions can easily escalate. But AI helped me de-escalate.

Instead, when I felt myself growing upset or defensive, I could type out my initial reactions and ask AI to help soften them, creating a more balanced response. When I received critical feedback from peers, instead of reacting in the moment, I could input the feedback into AI, process it privately, and work out an action plan on my own terms.

This approach continued even when I left that job. I conducted a retrospective on my performance, taking extensive notes, and then used AI as a personal coach to outline ways to approach my next role and refine my leadership style.

While I primarily used AI for professional situations, its potential for navigating different group dynamics is broad. For example, as the new president of my block association on the Upper West Side, I’ve become an unexpected leader of a multi-generational community. Our group includes both long-time residents who’ve lived on the block for decades and newcomers like me, who’ve been here for just a year.

We will inevitably have disagreements. Already I’m starting to see a few of them play out in real time. For instance, at one of our first block events earlier this summer, at a picnic in the park, one of the neighbors who joined us brought a bunch of bird food to feed the pigeons, a task that brought him unbridled joy but frustrated many of the rest of us who spent all afternoon chasing pigeons away from our children and our food. 

There are two sides to every story, aren’t there? On the one hand, the helicopters that buzz over New York City all day and all night long? On the other hand, as the parent of a 2-year-old, we literally can’t get enough helicopters in our family, and we literally spent summer nights on our rooftop counting the flyover appearances with glee.

Tonight marks our very first planning committee meeting with a larger group of 10 participants. The energy is very strong and excited, but I’m also anticipating some disagreements. That’s okay. I’m building these varied perspectives into the process—today is framed largely as a listening session. Later, I can spend time with our notes, maybe with the help of AI, to help me consolidate the feedback and seek out potential compromises in areas where we disagree.

Is it possible that this quiet, but powerful, use case for technology is the bridge that could help many more of us find common ground? Who knows? But something tells me we’ll all have plenty of at-bat opportunities to figure it out in the years ahead.