Growing Companies With Cutting-Edge Tech and Big Ideas

The tech industry is filled with buzzwords, but BAE Systems doesn’t care about them.

Director of Systems Engineering Jennifer Deppen said the company focuses instead on what’s tangible and impactful, a necessary approach to take in the aerospace and defense industry, where processes are complex, and projects can quite literally mean reaching for the stars. 

To ensure its people have the foundation to develop cutting-edge technologies, BAE Systems nurtures a culture rooted in experimentation and strategic objectives. 

“Using technologies like AI and digital engineering helps us innovate faster, reduce costs, and enable our engineers to focus on the toughest challenges,” Deppen said. “That’s when the impact happens.”

Having the right culture in place is critical to achieving tangible results, which is why marketing technology company Klaviyo treats its culture as a product.

“We’ve explicitly built it on rapid experimentation, fast learning and working autonomous-first,” Liang Zhang, vice president of engineering, AI and analytics, said. “This encourages innovation to happen on a daily basis.” 

With this emphasis on everyday innovation, Klaviyo’s technologists have been empowered to tackle a wide range of projects, such as a recent rollout of new AI agents, one of which has made it easier for teams to run more high-quality campaigns without needing to hire more team members. 

While every company takes a different approach to building cutting-edge tech, the end result is universal: real-world, measurable impact. Read on to see how Bose, BAE Systems, Klaviyo and other companies, such as Ahold Delhaize USA, Vantor and Squarespace, stay ahead of emerging tech trends while cultivating strong cultures, and learn about the recent product launches their teams are especially proud of. 

BAE Systems, Inc. specializes in building products for air, land and naval military forces in addition to developing solutions for use across a wide range of industries, including commercial transportation and aviation. 

 

How does your team stay ahead of emerging technology trends while scaling fast?

Staying connected with our customers, the professional community and advancements in areas like digital engineering and AI is key. These buzzwords are everywhere, but we focus on what’s tangible and impactful.

Scaling fast means prioritizing. In aerospace and defense, where processes are complex, we ask, “What’s the one thing we can do right now to benefit our teams, programs and customers?” We can’t do everything at once, but with a clear vision and smart independent research and development, we can make meaningful progress.

 

“In aerospace and defense, where processes are complex, we ask, ‘What’s the one thing we can do right now to benefit our teams, programs and customers?’” 

 

We also encourage our team to engage with industry groups and conferences. For example, one of our AI/machine learning leads runs and attends sessions at Institute of Electrical and Electronics Engineers conferences, keeping us at the forefront of advancements. Supporting our employees in these opportunities is a huge way we stay ahead of emerging technology and trends.

 

What recent product or feature are you most proud of — and what impact has it had?

I wanted to be an astronaut when I grew up, and that’s what got me into engineering. I may not be heading to space myself, but I’m proud that our BAE Systems team consistently delivers innovations that support mission success and advance space discovery, making a real impact both in orbit and here on Earth.

Systems engineering is exciting because it’s about how we bring everything together, connecting processes, tools and people to create something greater than the sum of its parts. One of our proudest team rollouts recently was an internal tool we developed to connect data from different sources of truth. Many tools from different vendors aren’t designed to work together, but this tool bridges those gaps.

We rolled it out last year internally, and the results were immediate. Producing artifacts for a review used to take weeks; now it takes an hour. It’s a time saver for our teams and a win for our customers. It’s ultimately about building a foundation for the future. This tool is scalable, and we’re exploring its use in modeling and simulation, and leveraging AI to conceptualize systems faster and develop initial requirements and architecture more efficiently.

 

How do you create a culture where innovation and experimentation are encouraged daily?

It starts with our strategic objectives. When we prioritize areas like digital engineering and AI, it creates opportunities for our teams to innovate. We also create roles and teams focused on these technologies, like algorithm development and AI/ML integration, which didn’t exist before. As a leader, I see my role as fostering creativity. I’m not an expert in every tool or technology, but I trust my team’s expertise. When someone comes to me with a great idea, I make sure they have the resources, freedom and support to pursue it. Even if it doesn’t work out, we learn and adapt.

Innovation is also about collaboration. Our team works across different domains and focus areas — from tactical systems to space vehicles to mission-level programs — bringing people together to solve complex problems. Systems engineering is about seeing the big picture and finding ways to make the process more efficient.

Using technologies like AI and digital engineering helps us innovate faster, reduce costs, and enable our engineers to focus on the toughest challenges. That’s when the impact happens.

 

 

ServiceNow’s AI platform enables enterprises to unify AI, data, and workflows through automation, so that enterprises can reinvent how people work across every corner of their businesses.

 

How does your team stay ahead of emerging technology trends while scaling fast?

We stay ahead by maintaining a “redshift” mindset, a commitment to high-velocity analysis and decisive action. A cornerstone of this is our weekly Redshift Forum, where we bring together top AI leaders to deep dive into the latest technical shifts. New technologies arrive in weekly waves, so it’s impossible for any one individual to see the full picture. These sessions allow us to collaboratively peer around corners and whiteboard proposals to build conviction about which trends are truly transformational.

Once that conviction is formed, we move instantly. We have built a technical environment specifically designed for rapid experimentation, allowing us to test new ideas as “probes” that can fail fast without systemic risk. By fostering a culture that encourages trying ideas with minimal friction and a heavy focus on high-level strategy over heavy preparation, we ensure our team isn’t just riding the AI wave but actively navigating it to deliver agentic solutions at scale.

 

What recent product or feature are you most proud of — and what impact has it had?

We’ve bridged the gap between information and action by unifying our Enterprise Search and Agentic Platform into a single system of intelligence. While Enterprise Search surfaces the right context from fragmented business software, the Agentic Platform provides the reasoning brain to act on it. Together, they allow our AI to not only understand complex enterprise needs but also execute multi-step workflows autonomously across the entire organization.

The addition of Agent Studio takes this further, allowing developers to extend our ecosystem with custom business logic. This transforms our AI into a programmable framework that enables developers to plug their systems into our reasoning engine.

 

How do you create a culture where innovation and experimentation are encouraged daily?

Innovation isn’t about having a perfect map of the future; it’s about the agility to navigate it. We recognize that it is impossible to always bet correctly in the next direction in such a volatile landscape. Therefore, our priority is building a technical foundation that enables rapid iteration and a culture where people feel safe to fail fast.

 

“Innovation isn’t about having a perfect map of the future; it’s about the agility to navigate it.”

 

AI is fundamentally changing how software is built, from the user experience down to the back-end systems. To meet this shift, we function as agile, virtual teams comprising product managers, designers, front-end, AI and back-end engineers. This cross-functional structure allows us to break down silos and make critical decisions quickly. By pairing this organizational speed with a flexible architecture, we ensure teams are positioned to build conviction and move from experiment to production-ready innovation.

 

 

Klaviyo’s platform combines marketing automation, analytics and customer service to enable B2C brands to deliver personalized, real-time customer experiences. 

 

How does your team stay ahead of emerging technology trends while scaling fast?

We stay ahead of emerging technology trends by combining continuous learning with disciplined execution.

First, we make learning a habit. Our team regularly reviews leading tech blogs, research, podcasts and open-source projects to spot meaningful shifts early. We also attend major AI and engineering conferences to hear directly from builders and researchers, then bring back practical ideas to test internally. This helps us evaluate new technologies before they become mainstream.

Second, we stay focused. We have a clear strategy to build an AI-driven product that can scale for large businesses. That focus guides our investments. We prioritize strong engineering foundations, reliable infrastructure and modern AI development tools so new technologies can be tested and deployed quickly without creating instability or technical debt.

 

“We have a clear strategy to build an AI-driven product that can scale for large businesses.”

 

Finally, we balance build versus leverage. For rapidly evolving areas like large AI models, we integrate best-in-class external solutions. At the same time, we concentrate our internal efforts on the features that uniquely differentiate our platform. That balance allows us to move fast, scale responsibly, and continuously bring innovation into the product.

 

What recent product or feature are you most proud of — and what impact has it had?

The recent product we are most proud of is the launch of our AI Agents, the Marketing Agent and the Customer Agent, which power our vision for an autonomous B2C CRM. We designed the platform to be open, so customers can use Klaviyo-built agents or bring their own, whether that is Claude through a Model Context Protocol server or ChatGPT through the Klaviyo App — any agent, any model, with full customer context from one platform. Our agents are grounded in insights from hundreds of thousands of businesses and trillions of data points, enabling specific, revenue-driving decisions rather than generic output.

The impact is clear and measurable. More than half of campaigns created with Marketing Agent are now AI-generated, often performing as well as or better than manually built campaigns, while taking a fraction of the time to launch. Teams can run more high-quality campaigns without adding headcount. Customer Agent is driving similar results in service. Resolution rates have increased by 20 percentage points, and the volume of issues resolved each month has grown by more than 50 percent. Businesses are also seeing meaningful lifts in sales and average order value from AI-driven recommendations.

 

How do you create a culture where innovation and experimentation are encouraged daily?

At Klaviyo, we treat culture as a product. We’ve explicitly built it on rapid experimentation, fast learning and working autonomous-first. This encourages innovation to happen on a daily basis. 

Our teams are anchored in clear outcomes, “Know the score,” and encouraged to run fast iterations that move those metrics. We optimize for short cycles and learning though “Move fast, no shortcuts.” In practice, that looks like lightweight experiment briefs, which include hypothesis, success metric and guardrails, shipping in days or weeks, and treating “What did we learn?” as the primary success criterion, even when the result isn’t what we hoped for. 

We also emphasize high agency and ownership. “Drivers wanted” means the people closest to the problem are expected to act, not wait. If you see something broken, you own fixing it or pulling in the right people. With a focus on working autonomous-first, we encourage teams to experiment with different AI tools to develop our own processes and internal tools. 

Lastly, we stay hungry, stay humble, and operate as if we are 1 percent done. This mindset enables us to learn from our mistakes, experiment with new things every day, and adapt very quickly.

 

 

Ahold Delhaize USA, a division of global food retailer Ahold Delhaize, is part of the U.S. family of brands, which also includes five leading omnichannel grocery brands: Food Lion, The GIANT Company, Giant Food, Hannaford and Stop & Shop.

 

How does your team stay ahead of emerging technology trends while scaling fast?

As a software engineering team, we stay ahead by embedding innovation into our development lifecycle. We monitor emerging trends through active participation in tech communities, open-source projects and continuous learning programs. Engineers regularly share insights via internal knowledge sessions, ensuring rapid adoption of new tools and frameworks. To scale fast without sacrificing agility, we leverage cloud-native architectures, continuous integration/continuous delivery pipelines and automated testing to integrate new technologies seamlessly. We also use modular design to enable quick iteration and deployment. We prototype and validate more complex ideas, so innovation moves from concept to production quickly and reliably.

 

“We monitor emerging trends through active participation in tech communities, open-source projects and continuous learning programs.”

 

What recent product or feature are you most proud of — and what impact has it had?

One of the recent achievements I am most proud of is building a fully automated, self-hosted GitHub CI/CD pipeline. This solution not only streamlined our development workflow but also delivered significant cost savings by eliminating dependency on third-party services. Another highlight was integrating Optimizely with Firebase Remote Config for A/B testing in our mobile app. This was a complex software development kit integration that enabled real-time feature experimentation and data-driven decision-making, improving user experience and accelerating product iterations. Finally, we addressed critical gaps in mobile app features to ensure a smooth go-live for a new app. That required rapid problem-solving and close collaboration across teams, ultimately delivering a stable, feature-rich product that met customer expectations.

 

How do you create a culture where innovation and experimentation are encouraged daily?

We create a culture of innovation by making experimentation part of our daily workflow, not an occasional event. Engineers are encouraged to propose ideas and validate them through rapid prototypes or A/B tests, supported by feature flags and automated pipelines. We treat every outcome as a learning opportunity, so the team feels confident trying innovative solutions. Regular knowledge-sharing sessions and open forums keep creativity flowing. Leadership reinforces this mindset by prioritizing time for research and analysis before coding, ensuring curiosity and collaboration are embedded in how we work.

 

 

Vantor leverages high-resolution satellite imagery and AI-powered software platforms to provide true information in near real-time.

 

How does your team stay ahead of emerging technology trends while scaling fast?

We process satellite imagery at scale, transforming raw sensor data into intelligence products for customers who need answers fast. Staying ahead means constantly finding ways to reduce latency while maintaining the precision and accuracy our customers depend on. 

Simplicity and portability are core to how we design. Our image processing service runs anywhere. The same codebase in our headquarters can deploy to regional nodes closer to where imagery is collected. Our next-gen Rapid Access Program initiative is fundamentally about processing data in-region to cut delivery times, so we minimize dependencies and keep our footprint small. Simpler systems are more robust, easier to troubleshoot and faster to deploy at the tactical edge. 

Automation is relentless. When we deploy to a new region, automation handles provisioning, deployment and validation. If something requires a human to remember to do it, eventually it won’t get done. We build systems that take care of themselves. 

Open, standard interfaces matter. Our services expose well-defined APIs that allow components, whether they’re built by us, other Vantor teams or partners, to integrate cleanly. When we added support for new sensor types, we extended existing services rather than rebuilding from scratch. 

The payoff of all this is time. When the foundation is solid, there’s time to be curious. We read papers, prototype new approaches, and share what we find across the organization. That’s how you stay ahead; not by chasing every trend, but by building a foundation solid enough that you can afford to experiment. 

 

“That’s how you stay ahead; not by chasing every trend, but by building a foundation solid enough that you can afford to experiment.” 

 

What recent product or feature are you most proud of — and what impact has it had?

I’m proud of our image quality and the effort we put into advancing it. Speed and simplicity matter, too, but imagery is only useful if you can trust it, so quality comes first. 

My background is in spatial and radiometric accuracy. Spatial accuracy is about using the best available ancillary data and resampling as few times as possible. Every resample loses information. We obsess over getting pixels to their true ground location while preserving as much of the original signal as we can. 

Radiometric accuracy is about calibration and atmospheric compensation. We tie radiometric calibration to real atmospheric measurements, so pixel values represent actual surface reflectance, not sensor characteristics or atmospheric effects.  

Both matter because this imagery feeds real decisions. Change detection, spectral analysis and object detection: These go to people and ML systems, and the quality of the input determines the quality of the output. 

Recently, I’m proud of bringing this precision to constrained deployment environments. Our next-gen Rapid Access Program initiative moves processing closer to where imagery is collected — smaller footprint and fewer resources. The challenge was achieving simplicity while making breakthrough quality improvements, without settling for incremental gains. 

This was a time when we collaborated deeply across the company, with system engineers, software engineers, quality assurance and ground systems team members all acting like owners. We had relentless design meetings focused on simplicity to hit tight timelines in what was genuinely new territory for us. With good planning, there were minimal late nights. People were excited to do things differently. The thrill was seeing a beautifully accurate image on screen 11 minutes from capture, from a satellite 400 kilometers up. When seconds count, that’s the work that matters. 

 

How do you create a culture where innovation and experimentation are encouraged daily?

Innovation happens when experimentation is low-risk and learning is valued as much as success. We’ve built a few practices into how we work that make trying new things feel natural. 

First, we make experimentation cheap. Because our system is portable and lightweight, we can spin up realistic test environments quickly. You can try a new approach against real data in a safe environment, gather actual performance numbers, and make informed decisions. No waiting for a release cycle to see if your idea works. 

Second, we question assumptions openly. In design reviews and code reviews, “Why do we do it this way?” is a real question, not criticism. Often, the answer is “Because it made sense when we built it, but things have changed.” These conversations surface opportunities that would otherwise go unnoticed. 

Third, we share what we learn. When an experiment teaches us something — whether it works or not — we share it broadly. This builds trust that the organization values learning, not just wins. Our leadership reinforces this. Our chief technology officer leads by example, approaching problems as a spatial intelligence problem, not just code to write. That means staying curious about how emerging techniques could help our customers. We read papers, prototype ideas, and bring findings back to the team. It’s not formal research and development time; it’s just part of how we work. 

The next-gen Rapid Access Program work showed what this looks like at its best: excellent engineers excited to do things new, a relentless drive to make it faster and the shared satisfaction when it actually worked. That energy doesn’t come from mandates. It comes from giving people room to own the outcome and experiment. 

 

 

Squarespace’s platform enables brands and organizations to build websites and promote their businesses through email marketing, SEO tools and more.

 

How does your team stay ahead of emerging technology trends while scaling fast?

We stay ahead of emerging technology by using it. Internally, we’re leaning on company-approved AI to help our teams research and prototype faster, which increases the pace of learning and execution. At the same time, we don’t chase technology for its own sake. We focus on where new capabilities can improve either the customer experience or the speed and quality of our product development.

 

“We focus on where new capabilities can improve either the customer experience or the speed and quality of our product development.”

 

What recent product or feature are you most proud of — and what impact has it had?

The recent product I’m most proud of is Blueprint AI, Squarespace’s AI-powered design partner. It was recognized by TIME as one of the Best Inventions of 2025. Blueprint AI provides customers with tailored recommendations for layouts, styling and starter content after a few simple prompts. I’m proud of the way it exemplifies our product philosophy of “design intelligence.” We think the best AI experiences combine technology with human design judgment. Blueprint AI doesn’t just generate something generic and leave the customer there. We give our customers a curated starting point that reflects both AI capabilities and Squarespace’s design point of view. The impact has been that we’ve made it much easier for customers to get past the blank page and get started, while still helping them create sites that feel distinctive and thoughtful.

 

How do you create a culture where innovation and experimentation are encouraged daily?

We work hard to establish a culture where experimentation is part of the work. A big part of that is making it accessible and fast to test ideas. We want teams testing rough ideas earlier, learning from them quickly and improving them collaboratively. Our goal is to reward curiosity and learning as much as we reward beautiful finished products.

 

 

Avant offers financial tools and solutions that are designed to help middle-income consumers reach their economic goals. 

 

How does your team stay ahead of emerging technology trends while scaling fast?

We stay ahead by being very intentional about where we experiment and where we standardize. As we scale, we invest heavily in strong technical foundations — clear architecture, shared platforms and disciplined engineering practices — so teams can move quickly without reinventing the wheel. On top of that foundation, we encourage small, focused bets on emerging technologies, whether that’s new data tooling, AI capabilities or developer productivity improvements. We learn fast, measure impact, and scale what works. Just as importantly, we stay close to real customer problems. Trends matter, but we only adopt new technology when it meaningfully improves outcomes for our users or our teams.

 

“We learn fast, measure impact, and scale what works.”

 

What recent product or feature are you most proud of — and what impact has it had?

One of the things I’m most proud of recently is how we’ve modernized and unified our customer and decisioning platforms. By simplifying complex systems and improving how data flows across the business, we’ve enabled faster product iteration, better risk decisions and a more seamless customer experience. The impact has been tangible: Teams can ship improvements more quickly, experiments reach customers sooner, and we’re able to personalize experiences at a much greater scale. It’s not a single flashy feature, but a set of foundational improvements that have unlocked speed, reliability and innovation across the organization.

 

How do you create a culture where innovation and experimentation are encouraged daily?

Innovation starts with psychological safety and clarity of purpose. We work hard to create an environment where teams feel empowered to question assumptions, test ideas, and learn from outcomes — good or bad. We set clear goals and metrics, then give teams autonomy in how they get there. Small experiments are encouraged, and learning is celebrated, not just success. We also prioritize strong feedback loops, so insights from customers and data quickly inform the next iteration. When people know their ideas are valued and that experimentation is part of the job, innovation becomes a daily habit rather than a special event.

 

 

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Achieve is dedicated to helping consumers build a better financial future for themselves by enabling them to find the right financial solution, such as a personal loan, a home equity loan, debt relief or online resources to help them more effectively control their expenses and save money. 

 

How does your team stay ahead of emerging technology trends while scaling fast?

Staying ahead of the curve isn’t about chasing every “shiny” new tech trend. At Achieve, we see innovation as a foundational mindset of empowerment. When you’re scaling fast, you realize it’s not just about hiring more people; it’s about amplifying the talent we already have. 

We view our team members as architects of experiences, not just operators of tools. By integrating AI and automation, we’re equipping our employees with the “enhanced capabilities” they desire, like perfect memory and instant data retrieval. This ensures that as we grow, our quality doesn’t just stay consistent; it improves. 

 

“We view our team members as architects of experiences, not just operators of tools.”

 

The way we do this is very collaborative. Members of our Center of Excellence identify repetitive and manual tasks and partner with our tech teams to automate those hurdles away. The resulting efficiency goes beyond simple gains. By eliminating the burden of manual data entry and routine compliance checks, we free up our employees’ mental capacity. This allows them to focus on solving complex problems and building deeper connections with our clients. For us, the true measure of innovation is the elevation of our employees.

 

What recent product or feature are you most proud of — and what impact has it had?

Our recent transformation involved integrating real-time agent assist with generative knowledge assistance, which is now deployed on every call to improve the frontline experience.

This generative knowledge assistance is key, as it proactively pinpoints crucial knowledge moments during a conversation. It then immediately provides agents with the exact answers and workflows they need, eliminating the need for manual searching or prompting. Previously, our agents suffered from “tab fatigue,” the stressful challenge of navigating multiple, disconnected systems to find essential policies or procedures while a customer waited.

This has been a game-changer for employee well-being. It removes the anxiety of “dead air” and the pressure of memorizing hundreds of variables. Our agents no longer feel like they’re being tested on their search skills; they feel supported by a digital partner. Because the tech handles the information retrieval, the human is free to focus on empathy and problem-solving. It’s a win-win: The employee stays in their flow state, and the client receives a seamless, expert experience without the wait.

 

How do you create a culture where innovation and experimentation are encouraged daily?

At Achieve, we create a culture of innovation by making it a daily habit, not a rare event. Our core driver is cognitive load management, using AI to take the “mental heavy lifting” off our employees’ plates. A perfect example is our real-time agent assist. Before this, agents acted like search engines, scouring databases while trying to talk to clients. Now, AI handles the data-hunting in the background, allowing our teammates to focus entirely on the human connection. 

When employees see that innovation gives them their “brainpower” back, they actively seek more ways to improve. We pair this experimentation with psychological safety. To maintain stability, we never “launch and hope.” We use a disciplined sandbox approach to stress-test every tool in isolation, hunting for bias or inaccuracies before they ever reach a live conversation. This balance allows us to be bold enough to experiment yet disciplined enough to ensure technology remains a powerful asset for our employees, never a liability. For us, innovation is measured by how effectively it elevates the human experience.

 

 

Sendbird’s AI customer experience platform enables brands to communicate with consumers via voice, video and messaging. 

 

How does your team stay ahead of emerging technology trends while scaling fast?

We don’t think of it as “staying ahead of trends;” we think of it as staying close to customers. We process over 7 billion conversations a month across our platform, so we see how real people interact with AI before it becomes a headline. That proximity is our advantage. When we noticed customers were frustrated by AI that couldn’t remember them from one conversation to the next, we didn’t wait for an industry report to tell us memory mattered. We built it. The best trend radar is just listening really carefully to what’s not working yet.

 

“The best trend radar is just listening really carefully to what’s not working yet.”

 

What recent product or feature are you most proud of — and what impact has it had?

Our Agent Memory Platform, and I’m proud of it because it solved a problem that most companies haven’t even named yet. Right now, the vast majority of AI in customer experience is stateless. Every conversation starts from zero. Customers repeat themselves, get generic responses, and the relationship never deepens. We built a memory layer that lets AI agents actually learn and remember each customer over time — their preferences, their history, the little details that make someone feel seen. It turns what used to feel like talking to a stranger every time into something that genuinely compounds. The shift from “chatbot” to “concierge” sounds like marketing until you watch a customer react to an AI that actually knows them. That’s the moment I’m most proud of.

 

How do you create a culture where innovation and experimentation are encouraged daily?

Innovation has been part of Sendbird’s DNA from day one, not as a buzzword, but as survival. We’ve reinvented ourselves multiple times: from a startup in 2013, to Y Combinator, to pivoting entirely to B2B, to becoming the world’s number one conversations API, to now building Delight, our branded AI concierge platform. Each of those transitions required the whole company to let go of what was working and bet on what could work better. When your people have lived through that kind of reinvention and thrived, experimentation isn’t something you have to encourage. It’s just how the company breathes.

That starts with who we hire. We look for people who are genuinely restless. The kind of person who sees how something works and immediately starts thinking about how it should work. That restlessness matters more than pedigree because you can’t teach someone to be uncomfortable with the status quo.

And we back it up by treating failed experiments as information, not failures. When something doesn’t land, the question here is, “What did we learn?” not “Whose fault is it?” That sounds simple, but most companies get it backwards.

 

 

Simply Business’s digital marketplace connects small businesses with insurance coverage solutions. 

 

How does your team stay ahead of emerging technology trends while scaling fast?

Our engineering organization does a really great job of encouraging us to use new tools and technologies like Microsoft Copilot/LLMs for development work. We have a dedicated Slack channel to talk about our experiences with AI native development. I personally have started tinkering with OpenCode and exploring how it can refine and refactor code that I’ve written, and even help me bypass blockers that I run into along the way. I do believe that collaboration between engineers will be the best way to adopt these new technologies, even as “vibe coding” increases in its commonality. 

Communication across development teams can’t boil down into “Claude did it” or “I just listened to Copilot” because that’s how we lose the craft of being software engineers. Discourse that starts with “Why did Copilot output this?” and continues across teams will lead us down a path of using these tools to their maximum potential by more efficiently crafting prompts and tickets to write readable and maintainable code. I’m encouraged by the care that our leadership has taken in rolling out these tools and giving engineers an open platform to discuss the insights gleaned from a very exciting technology.

 

What recent product or feature are you most proud of — and what impact has it had?

Our team recently launched a new insurer on our general liability panel, and while our team is no stranger to onboarding new carriers, a big focus of this implementation was the data and tracking point of view. We launched it as an A/B test because we wanted to be able to see how the new carrier would perform against the current panel of insurers for the general liability product. The process of implementing the test required heavy collaboration and learning between engineering, product and data engineering/analytics to make sure that everyone had what they needed to deliver a successful product launch. I’m really proud of the effort the team and I put in over the course of the project, which ended up being completed in a shorter time than originally estimated, leading to hundreds of new customers buying insurance through our platform that otherwise wouldn’t have been able to. We’ve recently had our biggest sales day in the U.S. market in large part due to this project.

 

How do you create a culture where innovation and experimentation are encouraged daily?

Simply Business does a really great job of encouraging engineers to take time out of their weeks to learn a new skill, level up their current skills, or expand features outside of the scope of refined feature work. This dedicated learning time gives engineers the opportunity to take advantage of tools that the company offers such as Spark courses to improve technical skills, or use the time to collaborate across the engineering organization with others who have different skills, experiences and perspectives. 

 

“Simply Business does a really great job of encouraging engineers to take time out of their weeks to learn a new skill, level up their current skills, or expand features outside of the scope of refined feature work.”

 

Since Simply Business has a lot of moving parts, I’ve been able to meet with and gain knowledge from more senior engineers and develop relationships with people that I wouldn’t typically work with during my day-to-day work. I believe that the best way to level up is through that collaboration and relationship-building; it builds a culture of asking questions and development of ideas with people that have entirely different contexts around their work. I’m happy to work at a company with people that I know are willing to answer questions and assist on projects, even if it isn’t directly related to their team’s work.

 

 

Circle’s platform is designed to help community-led businesses grow by supporting various capabilities, such as building a branded website, hosting virtual events and creating courses. 

 

How does your team stay ahead of emerging technology trends while scaling fast?

The AI landscape is evolving constantly, with new models, tools and techniques emerging faster than any organization can track. At Circle, we’ve leaned into that reality rather than try to manage it from the top down. We believe that the most successful engineering teams will be highly AI-leveraged, which means we’re working toward a model where we can scale our business with small, focused teams that can punch well above their weight. In practice, that looks like engineering leads who are expected to be hands-on with AI tooling themselves and a deliberate push to share what’s working across the org rather than letting learnings stay siloed.

 

“We believe that the most successful engineering teams will be highly AI-leveraged, which means we’re working toward a model where we can scale our business with small, focused teams that can punch well above their weight.”

 

What recent product or feature are you most proud of — and what impact has it had?

We launched Connect a few months ago. At its core, Connect helps community members find and build relationships with each other by using an AI-powered social graph. Rather than giving members access to the directory and hoping they figure it out, Connect surfaces personalized recommendations based on shared profiles, spaces and interests, and lowers the barrier to actually reaching out. The result is that meaningful member relationships can start forming naturally and at greater scale. Admins also have access to insights so they can see how relationships are forming, track engagement trends over time, and identify top connectors. Connect is a great example of how we are continually finding ways to enable our customers to build thriving communities. It’s also a good example of how we tackle genuine technical challenges, as it required the integration of a new graph database and AI alongside the existing relational database.

 

How do you create a culture where innovation and experimentation are encouraged daily?

Innovation isn’t just encouraged at Circle. In many ways, it’s expected, especially around AI. We hold regular show-and-tells in our engineering team meetings, where engineers demo whatever they’ve been experimenting with, no polish required: personal workflow improvements, novel MCP integrations and AI applied to places you wouldn’t expect. We share freely in Slack as well, from coding productivity wins to using automation to address sales questions and customer feedback.

What makes it work is that everyone, engineers and leaders alike, is genuinely learning and sharing those learnings publicly. Our co-founders constantly share how they keep up and experiment with AI, and when that kind of experimentation and curiosity is modeled at every level of the organization, it starts naturally feeling like it’s just how our work gets done.

 

 

VSCO’s platform enables creative professionals to edit photos and videos, connect with others across the industry and gain exposure to brands for hiring opportunities. 

 

How does your team stay ahead of emerging technology trends while scaling fast?

There are tons of creatives working at VSCO, and we tend to have a bias toward curiosity. We have a culture of sharing resources and making time for experimentation, so I feel like there’s an ambient, never-ending conversation around, “What’s next?” And that’s both about what we launch and what technology we’re using to empower our users’ creativity and businesses. 

 

“We have a culture of sharing resources and making time for experimentation, so I feel like there’s an ambient, never-ending conversation around, ‘What’s next?’”

 

What recent product or feature are you most proud of — and what impact has it had?

I’m the product manager on a new app, VSCO Galleries, which helps photographers impress clients when delivering photos. My favorite feature is the collaborative gallery. When enabled, others like wedding guests, party attendees and behind-the-scenes photographers can upload to their own gallery section.

I’m a bit obsessed with the goal of getting photographers paid, probably because I used to work in film and photography and know the grind firsthand. Whether I’m helping them book more clients or feel confident charging more, I try to make sure what I build at VSCO supports their career stability. Collaborative galleries aren’t just fun. They can be an add-on to a photographer’s package, helping them earn more.

I was on a call with a customer who’s using a collaborative gallery at a wedding for the first time. He told me he’s excited because it can be a real differentiator. It’s also been interesting to see the shifts in perception of VSCO, from it being seen as a photo editing app to a platform where photographers hone their craft, grow their network, and build a business on their terms. At a recent industry event, Wedding & Portrait Photographers International, you could feel that shift happen in real time, seeing people react to VSCO Galleries and our broader tool set.

 

How do you create a culture where innovation and experimentation are encouraged daily?

We’re very impact-driven, and we’re encouraged to take ownership and drive initiatives forward that work best to accomplish our goals. People are empowered to try new tools and new ways of working. There’s also a lot of trust on our team. If I, as a product manager, want to create a rough prototype of an idea for a feature, my design partner doesn’t see that as a threat. If an engineer spins something up in response to a feature request, I don’t feel like we’re in competition. We operate as one collaborative team, and we respect each other’s expertise while also recognizing we’re now living in a world where AI makes our crafts a little more accessible to each other.

 

 

GameChanger’s youth sports platform makes it possible to livestream games, schedule practice, review season statistics and more. 

 

How does your team stay ahead of emerging technology trends while scaling fast?

Maintaining a culture of learning and continuous self-improvement is foundational for us. We champion learning through multiple avenues, from grassroots forums like hackathons, lunch-and-learn sessions and focus guilds to more structured investments such as conferences and instructor-led courses.

When early adopters and innovators see potential in a new technology, they demonstrate its value through demos, tech talks and other knowledge-sharing forums. That peer-driven adoption model allows great ideas to scale organically before they ever become mandates.

Once we decide something should scale across the product, strong technical foundations are non-negotiable. You can’t move fast on the frontiers of technology if your platform is fragile. We continuously invest in reliability, observability and developer productivity so experimentation can happen safely and at scale, without compromising the customer experience.

 

“We continuously invest in reliability, observability and developer productivity so experimentation can happen safely and at scale, without compromising the customer experience.”

 

What recent product or feature are you most proud of — and what impact has it had?

I’m a big fan of many things within the GameChanger platform, but if I had to pick a recently shipped experience that stands out, it would be the Game Highlights feature.

This experience takes game data and broadcast video and automatically produces a professional-quality recap featuring key moments with contextual play information. The highlights are crisp, engaging and give fans a quick way to catch up — and hopefully see their favorite youth athlete featured.

What makes this especially meaningful to me is how many capabilities came together to power it: scorekeeping and stats, play-by-play analysis,1080p live video streaming and computer vision-based gameplay detection. It’s a great example of cross-team alignment creating something greater than the sum of its parts. The reception from users has been incredibly positive, and it reinforces how powerful it is when we connect our technical depth directly to an emotional user experience.

 

How do you create a culture where innovation and experimentation are encouraged daily?

Over my time at GameChanger, I’ve seen incredible learning and innovation translate into real impact for our users and business. Innovation requires two things: clarity and space. If you don’t give people clear goals, they drift. If you don’t give them space, you suffocate creativity.

We invest heavily in hiring great people, and when you hire great people, you have to trust them. That means allowing room for exploration, messy prototypes, and unconventional thinking. When something shows real potential, leadership’s role is to step in and ask: How do we turn this into something valuable at scale?

Daily innovation isn’t about grand gestures. It’s about empowering smart teams with clarity, trust and the freedom to build.