I’ve had hundreds of conversations with leaders about workplace transformation, but few have been as wide-ranging and refreshingly candid as my recent interview with Bryan Power, Chief People Officer at Nextdoor. Bryan’s career stretches from the late 1990s dot-com era to Google, Yahoo, Square, and now a mission-driven platform focused on belonging. That arc gives him a unique vantage point on how the people function has changed and how leaders can navigate the most disruptive cycle of our working lives.
“Lots of things have changed,” he told me, recalling a time “before the internet was part of the equation,” and noting how today’s AI moment carries echoes of that earlier disruption. Yet the biggest shift he sees isn’t technological but rather the mandate for people leaders. For a long time, the job was seen as service delivery: recruiting, performance systems, compensation, and the operational plumbing that kept friction low. “No news is good news” used to be a compliment.
Then came a one-two-three punch in the 2020s: a pandemic that upended where and how we work, social and political polarization that walked straight into the office, and now AI overturning workflows and decision rights. As Bryan put it, those are problem sets with “not a lot of playbooks to copy,” which forces chief people officers to be far more creative, strategic, and central to enterprise decision making.
Consumer Expectations Don’t Stop at the Office Door
We talked about the pressure employees put on enterprise systems because their personal experiences are so seamless: food on demand, one-click checkout, algorithmic recommendations. Bryan’s seen this pattern before. When the iPhone arrived, employees wanted to use their personal devices for work. Many IT teams said no. Today, it’s unimaginable to block that completely. “That consumer pressure puts pressure on the enterprise to adopt these disruptions,” he said. The same thing is happening with AI tools. If people use them at home, they’ll expect to use them at work.
That expectation creates a practical implementation challenge. Enterprise buying cycles and integration projects move slower than the pace of AI innovation. Large language models leapfrog each other. “The hot thing from six months ago is already gone,” Bryan said. He admits it makes him anxious because you want to commit and build, but you also need to stay flexible. His answer: learn fast and learn together. “The goal right now is to be learning at a really high velocity.”
Training for Lift-Off, Then Training for Traction
At Nextdoor, Bryan didn’t wait for someone else to own the AI agenda. With the CEO’s support, he mobilized the people team alongside IS and IT in a cross-functional effort cheekily named Project Neighbor. The first three-month phase focused on ignition: get attention, raise energy, and lower the barrier to experimentation. He and a counterpart built an internal AI fundamentals course with help from ChatGPT, rolled it out to a handpicked cohort, then opened it up broadly. The crescendo was a hackathon.
Phase two raised the bar. It shifted from “what can you do with AI” to “how would you use AI to solve the problem in front of you.” That meant fewer optional experiments and more operational commitments, including enterprise tooling. “We’ve implemented enterprise-grade tools. We use Glean here,” Bryan said. Now the work is embedding those tools into daily flow and measuring where they truly accelerate work.
If you’ve tried to drive adoption yourself, you’ll recognize what he learned next: your busiest, most networked employees are exactly the ones you want to become power users, and they’re the least likely to have spare time to climb the learning curve. There’s also a short-term productivity dip. Bryan pointed to an engineering study he saw that found developers became less productive early on with AI copilots, then more productive later if they stuck with it. Many teams try, feel behind, and retreat to old habits. Leaders have to plan for that valley and create the space to climb out of it.
“Treat It Like a Teammate, Not a Tool”
I asked Bryan how he personally uses generative AI. His answer reframed my own calendar. “One of the first insights you learn in really leveraging AI is to treat it like a teammate, not like a tool.” He literally schedules one-on-ones with AI. He’s built custom GPTs with specific personas and meets them like he would meet direct reports. That shift altered how he spends time. He used ChatGPT as his L&D partner to design a leadership offsite. He uses it to synthesize inputs, pressure-test plans, and keep momentum on projects that might otherwise languish between meetings.
He also uses AI as a critic, not a cheerleader. Because these systems are powerful pattern matchers, they can subtly validate your thinking unless you prompt them to challenge you. Bryan asks questions like, “What am I missing? Where am I biased? How can you make this stronger?” You get a very different kind of help when you approach it that way.
On the mental health front, Bryan drew a hard line. “I don’t love ChatGPT as a therapist.” He worries when coaching substitutes for therapy, and he appreciates safeguards that reduce harm when conversations veer into clinical territory. Use AI for structured coaching prompts or critique, not as a stand-in for trained professionals.
People Decisions and Software Decisions Are Converging
Historically, headcount and software were different budget lines owned by different leaders. AI is collapsing that distinction. “What’s narrowing really fast is the question of who’s going to do this work. Is it going to be a tool or a person?” Bryan said. That’s a big reason he believes chief people officers must be in the room with technology leaders. Over the last six to nine months, he’s spent more time with IS and IT than ever before to reconcile choices that used to be separate. It’s about designing workflows where humans and tools complement each other and being honest about the tradeoffs.
Get Ready for Agents, and Manage Them Like Teammates Too
We’re all watching the rise of agentic AI with curiosity and caution. Bryan’s team is already experimenting with agents, and they’re learning that opportunity is massive, but governance can’t be an afterthought. “We already have the same number of agents as 20 percent of our workforce if you counted each agent as an employee,” he said. That raises real questions. Who grants permissions when an agent can trigger expensive data pulls? What oversight is practical when you can’t review everything? How do you “fire” an agent that spams people or goes stale? What happens when your best agent builder leaves and takes all the know-how with them?
Nextdoor is adopting a people-centric frame: hire agents thoughtfully, set expectations, collect feedback from collaborators, evaluate performance, and offboard deliberately. In other words, treat agents like you treat teammates.
Stay Close to the Front Line
One theme that runs through Bryan’s leadership philosophy is a frontline obsession. He told me to look up the book The Founder’s Mentality by James Allen, which influenced how Nextdoor reorganized when founder Nirav Tolia returned as CEO. The idea is simple to describe and hard to sustain at scale: keep senior leaders close to the employees who touch customers. As companies grow, information gets summarized, filtered, and reduced to dashboards. “Make sure the senior people don’t get so far away from the employees who are actually touching customers,” Bryan said. For people leaders, that means seeing for yourself what candidates experience, what new hires encounter in week one, and what messages are actually landing rather than relying on a chain of synthesis.
There’s a cultural payoff too. When leaders stay close to the action, employees feel purpose more clearly. Disconnection erodes meaning, but connection restores it.
Global Consistency, Local Sensitivity
Bryan has led globally dispersed teams and thinks the world has homogenized more than many assume, especially for younger employees. Still, leaders should be thoughtful about how values show up across cultures with different power dynamics. Tech often prides itself on flat structures, but some cultures value hierarchy. “You have to be thoughtful in how you apply what you want to be consistent,” he said. Sometimes you should export your cultural norms. Sometimes you shouldn’t. Even basic things like holiday calendars can signal whether you truly see and respect local context.
Don’t Abandon Early-Career Talent
In a tight market, many companies dial down entry-level hiring. Bryan thinks that’s a mistake for any firm that wants to innovate. Early-career employees bring fresh eyes. They ask why. They haven’t yet absorbed all the assumptions that come with experience. “What’s in their DNA is not knowing things,” he said with a smile. That’s a feature, not a bug, when you’re trying to break patterns.
He’s also watching a cohort effect. The college classes graduating in the next couple of years will have completed their entire university experience in a world where ChatGPT and similar tools existed. He calls them AI natives. They’ll arrive already wired for an AI-first approach. If you believe there’s a steep learning curve to productive AI use, the fastest way to gain advantage is to include people who never learned another way. The remaining open question is whether entry-level jobs evaporate as routine tasks get automated. If the bottom rung disappears, how do people get the experience they need to climb? Leaders will have to design new on-ramps.
Build Community Through Managers and Meaning
Nextdoor’s mission is about neighbors and belonging. Inside companies, that translates to managers who can form authentic connections with every person on their team and to leaders who make the work feel meaningful. Bryan sees many managers over-correct. Some go too deep with a few people and not deep enough with others. Some stay too shallow with everyone. The skill is building a balanced, real connection with each person. Pair that with a clear line of sight to purpose. “You have to make people feel like their job is going to mean something,” he said. When people see how their work fits into a bigger picture, connection and motivation rise together.
Read More, Scroll Less
We closed with books. Bryan recently reconnected with Tony Schwartz, author and founder of The Energy Project, whose message has shaped his leadership since 2006: you can’t create more time, but you can manage your energy. That principle is even more relevant in an AI-accelerated world. Bryan worries about a culture that outsources reading to influencers who summarize books into three talking points. “People should just read the book themselves,” he said. I couldn’t agree more.
What I’m Taking Back to My Team
Three practices from Bryan are already on my to-do list:
- Schedule one-on-ones with AI. Treat models like teammates with names, roles, and backlogs. Put those sessions on your calendar so exploration doesn’t get squeezed out by meetings.
- Design for the learning dip. Plan the time and support people need to go from initial slowdown to sustained lift. If you want power users, make space for them to become power users.
- Manage agents like people. Define how they’re hired, evaluated, permissioned, and offboarded. Avoid an unmanaged bot sprawl that creates noise and cost.
Bryan’s through-line is simple and actionable. He advises us to stay close to the work, wire teams to learn quickly, and use AI to strengthen human judgment rather than replace it. The nature of work is changing fast, but the core job of leadership hasn’t. Build trust, create meaning, and help people do the best work of their lives. The tools are new, but the responsibility is timeless.
If you haven’t yet, check out the rebranded Nextdoor. And if you want to follow Bryan’s ongoing experiments, he’s active on LinkedIn.
Brandon Laws is a workplace culture and leadership enthusiast, host of the Transform Your Workplace podcast, and VP of Marketing and Product at Xenium HR.