When I ask who's in the room on Mentimeter and the results start flying in, I'm not just gathering data. I'm telling people: you belong here, your presence matters, and this session was designed for you
When I ask who's in the room on Mentimeter and the results start flying in, I'm not just gathering data. I'm telling people: you belong here, your presence matters, and this session was designed for you
Ayla discovered Mentimeter during the COVID-19 pivot to virtual training, as her team scrambled to rebuild engagement in a world without conference rooms. What started as one person's experiment spread quickly, because attendees noticed the difference.
Today, Mentimeter is woven into the fabric of how Google Cloud trains at scale:
Confidence baselines: At the start of a multi-day summit, attendees rate their confidence in a strategy or skill. At the end, they rate it again. Ayla downloads those results and brings concrete confidence-increasing data to every business review.
Audience composition: Early in any session, Ayla asks attendees to share their role, not their job title, but what they actually do. Within seconds, she knows she has ten engineers, five finance leads, and three program managers, and she can adjust her delivery in real time.
Learner reflection: After a leader presents, instead of moving on, Ayla pauses and asks: what was your biggest takeaway? From a brain science perspective, that question alone signals the learner's memory systems to retain what they just heard.
Real-time feedback for leaders: Responses are captured live and exported. A leader who gave a keynote can receive a follow-up showing exactly what seven employees took from their message, word for word.
At a recent hybrid global event, Ayla had Mentimeter open during the opening keynote with a live word cloud capturing what attendees were hearing in real time. As the keynote wrapped, the CEO of Cloud Go-to-Market happened to walk past. Ayla called him over.
"He had just walked off the stage fifteen minutes earlier," she recalls, "and he could literally see, live on the screen, what hundreds of people had taken from his message."
It's the kind of moment that's impossible to manufacture, but entirely possible to design for.
Something unexpected happened as Ayla's internal training gained momentum. Customer-facing Googlers started attending sessions, watching Mentimeter in action and then quietly bringing it into their own customer meetings. One Googler ran dozens of external sessions before anyone formalized it. Recently, Ayla overheard two colleagues talking unprompted about using Mentimeter with clients.
"It just speaks to how it helps reinforce engagement," she says. "The most successful training, the ones that got requested again, that scaled, almost always had Mentimeter in them."
When asked what she'd tell an enablement leader starting from scratch, Ayla doesn't reach for tools first. She reaches for people. "Start with what they know, what they think they need, and what's been tried before, and why it did or didn't work," she says. "The system follows from that."
From there: build multiple levels of the same content for different audiences, lean into problem-solving over passive delivery, and find moments — even in a virtual, scaled environment — to make people feel seen. A word cloud that shows someone their colleague had the same exact thought? That's the connection. A confidence score that moves from 2.2 to 4.1 over two days? That's proof.
The future Ayla is watching closely is agentic AI; the possibility of training that adapts in real time to prior knowledge, role, and context. The principles that will make it work are the same ones she's been applying for years: start with the human brain, make it real, make it theirs.
For Ayla, scaling learning was never the goal on its own. Anyone can scale content. Few can scale confidence, clarity, and real behavior change.
That’s the difference.
At Google Cloud, training doesn’t end when the session does. It continues in the way people think, decide, and show up to their work. Every question asked, every response captured, every moment of reflection builds something bigger — a system where learning sticks because people are part of it.
And that’s what Ayla has built.
Not just a global training program, but a way of learning that adapts, responds, and improves in real time. One where people feel seen. Where leaders actually hear what lands. Where data doesn’t just report on learning, it shapes it.
The tools will evolve. AI will change the pace. But the principle holds.
Start with people. Make it relevant. Make it theirs.
That’s how you turn training into something more.
That’s how you make it matter.
Ayla discovered Mentimeter during the COVID-19 pivot to virtual training, as her team scrambled to rebuild engagement in a world without conference rooms. What started as one person's experiment spread quickly, because attendees noticed the difference.
Today, Mentimeter is woven into the fabric of how Google Cloud trains at scale:
Confidence baselines: At the start of a multi-day summit, attendees rate their confidence in a strategy or skill. At the end, they rate it again. Ayla downloads those results and brings concrete confidence-increasing data to every business review.
Audience composition: Early in any session, Ayla asks attendees to share their role, not their job title, but what they actually do. Within seconds, she knows she has ten engineers, five finance leads, and three program managers, and she can adjust her delivery in real time.
Learner reflection: After a leader presents, instead of moving on, Ayla pauses and asks: what was your biggest takeaway? From a brain science perspective, that question alone signals the learner's memory systems to retain what they just heard.
Real-time feedback for leaders: Responses are captured live and exported. A leader who gave a keynote can receive a follow-up showing exactly what seven employees took from their message, word for word.
At a recent hybrid global event, Ayla had Mentimeter open during the opening keynote with a live word cloud capturing what attendees were hearing in real time. As the keynote wrapped, the CEO of Cloud Go-to-Market happened to walk past. Ayla called him over.
"He had just walked off the stage fifteen minutes earlier," she recalls, "and he could literally see, live on the screen, what hundreds of people had taken from his message."
It's the kind of moment that's impossible to manufacture, but entirely possible to design for.
Something unexpected happened as Ayla's internal training gained momentum. Customer-facing Googlers started attending sessions, watching Mentimeter in action and then quietly bringing it into their own customer meetings. One Googler ran dozens of external sessions before anyone formalized it. Recently, Ayla overheard two colleagues talking unprompted about using Mentimeter with clients.
"It just speaks to how it helps reinforce engagement," she says. "The most successful training, the ones that got requested again, that scaled, almost always had Mentimeter in them."
When asked what she'd tell an enablement leader starting from scratch, Ayla doesn't reach for tools first. She reaches for people. "Start with what they know, what they think they need, and what's been tried before, and why it did or didn't work," she says. "The system follows from that."
From there: build multiple levels of the same content for different audiences, lean into problem-solving over passive delivery, and find moments — even in a virtual, scaled environment — to make people feel seen. A word cloud that shows someone their colleague had the same exact thought? That's the connection. A confidence score that moves from 2.2 to 4.1 over two days? That's proof.
The future Ayla is watching closely is agentic AI; the possibility of training that adapts in real time to prior knowledge, role, and context. The principles that will make it work are the same ones she's been applying for years: start with the human brain, make it real, make it theirs.
For Ayla, scaling learning was never the goal on its own. Anyone can scale content. Few can scale confidence, clarity, and real behavior change.
That’s the difference.
At Google Cloud, training doesn’t end when the session does. It continues in the way people think, decide, and show up to their work. Every question asked, every response captured, every moment of reflection builds something bigger — a system where learning sticks because people are part of it.
And that’s what Ayla has built.
Not just a global training program, but a way of learning that adapts, responds, and improves in real time. One where people feel seen. Where leaders actually hear what lands. Where data doesn’t just report on learning, it shapes it.
The tools will evolve. AI will change the pace. But the principle holds.
Start with people. Make it relevant. Make it theirs.
That’s how you turn training into something more.
That’s how you make it matter.
When Google Cloud releases a new product, the challenge isn't just the launch, it's everything that comes after. A product Ayla's team once trained their entire sales organization on was rebranded and re-optimized within months. The training wasn't wrong; it was just the beginning.
"Continuous learning is about building the foundational knowledge first," Ayla explains, "and then asking: how are we keeping things fresh? How are we building on those skills as the world changes?"
For a team that spans sellers, consultants, engineers, and program managers across the globe, that question is more than philosophical. It's a design challenge. The training that resonates with a cloud architect looks completely different to what lands for a strategic finance lead. At an organization the size of Google Cloud, one-size-fits-all is a fast track to disengagement.
Ayla's approach is grounded in the neuroscience of adult learning — what's often called andragogy. The adult brain doesn't absorb information the way a child does. Adults bring existing knowledge, experience, and opinions into every session. They need to understand why they're learning something. They need autonomy. And crucially, they need the learning to connect to their real world — not tomorrow, but right now.
"You can talk at adults for five hours," Ayla says, "but are they actually going to shift their behavior when they go back to their keyboards? That's the real question."
She structures her training around the SCARF framework — Status, Certainty, Autonomy, Relatedness, and Fairness, five social needs that, when met, move learners from passive recipients into active, engaged participants. When those needs go unmet, the amygdala fires and the brain checks out. Most people never notice it happening.
When Google Cloud releases a new product, the challenge isn't just the launch, it's everything that comes after. A product Ayla's team once trained their entire sales organization on was rebranded and re-optimized within months. The training wasn't wrong; it was just the beginning.
"Continuous learning is about building the foundational knowledge first," Ayla explains, "and then asking: how are we keeping things fresh? How are we building on those skills as the world changes?"
For a team that spans sellers, consultants, engineers, and program managers across the globe, that question is more than philosophical. It's a design challenge. The training that resonates with a cloud architect looks completely different to what lands for a strategic finance lead. At an organization the size of Google Cloud, one-size-fits-all is a fast track to disengagement.
Ayla's approach is grounded in the neuroscience of adult learning — what's often called andragogy. The adult brain doesn't absorb information the way a child does. Adults bring existing knowledge, experience, and opinions into every session. They need to understand why they're learning something. They need autonomy. And crucially, they need the learning to connect to their real world — not tomorrow, but right now.
"You can talk at adults for five hours," Ayla says, "but are they actually going to shift their behavior when they go back to their keyboards? That's the real question."
She structures her training around the SCARF framework — Status, Certainty, Autonomy, Relatedness, and Fairness, five social needs that, when met, move learners from passive recipients into active, engaged participants. When those needs go unmet, the amygdala fires and the brain checks out. Most people never notice it happening.