This as-told-to essay is based on a conversation with Chai Atreya, a 44-year-old chief product and technology officer at ActiveCampaign, who lives in Los Gatos, California. It has been edited for length and clarity.
I’m the chief product and technology officer at ActiveCampaign, an autonomous marketing platform powering end-to-end marketing across email, SMS, WhatsApp, and more.
Over the past decade, I’ve led product and AI teams at high-growth tech companies. From 2012 to 2015, I worked as a software development manager at Amazon, helping launch the first iterations of Alexa, building distributed systems, and optimizing performance for fast, intuitive voice experiences.
I left Amazon because I wanted to take the lessons of operating at an Amazon-level scale and apply them in a role where I could drive transformation more directly and visibly. After Amazon, I held leadership roles at Teradata and Alteryx before joining ActiveCampaign in May 2025.
Jeff Bezos had a clear vision for what would become Alexa
When I started at Amazon, Jeff Bezos shared his vision for an always-on, cloud-connected virtual assistant for the home (what would eventually become Alexa). He set the stage for an experimental and secretive design process, with roughly 50 different concepts, each exploring different use cases, voice domains, and form factors.
The environment was exhilarating — a mix of intense scrutiny, collaboration, and experimentation, where inventing and simplifying were core to our decision-making every day. In one meeting, latency was called out as too high, and Bezos challenged us to reduce Alexa’s response time. It challenged every team to rethink the architecture, caching, and system design.
What many people misunderstand about Amazon’s “frugality” leadership principle is that it isn’t simply about saving money. It’s about being frugal with resources like time, bandwidth, and complexity. Setting an aggressively low latency target was an act of frugality.
We had to accomplish more with fewer milliseconds, fewer dependencies, and less architectural overhead. Those constraints forced clarity, demanded resourcefulness and self-sufficiency, and fueled invention.
Two distinct principles from Bezos stayed with me well beyond Amazon
The first was the distinction between one-way and two-way doors. One-way doors are decisions that are hard or costly to reverse, so they deserve more rigor and patience; two-way doors are reversible, so these decisions should be made quickly, tested, and adjusted based on what you learn.
The second was the regret minimization framework, which is about stepping back from the noise of the moment and asking which path you will be proud to have taken over the long arc of your career. The Amazon leadership principles shaped how we operated day-to-day, but those two ideas shaped how I thought about bigger decisions over a longer arc.
Another lesson I learned is that speed builds trust
At Amazon, we learned that moving quickly to deliver meaningful value earned the confidence of customers and partners. Speed wasn’t just about reducing latency; it also meant anticipating needs, interpreting subtle signals, and acting decisively on feedback, both explicit and implicit, by leveraging insights from integrated systems to deliver real impact faster.
On Alexa, every decision, from which voice domains to prioritize (weather, music, etc.) to how the system handled errors, was driven by the question “what outcome does this create for the user?” In tandem, it required thinking big. We were redefining how customers interact with technology in their homes, and that ambition pushed us beyond incremental improvements.
I joined when Alexa was a handful of teams, and by its launch in 2014, it grew to thousands of people
During this hyper-scale phase, I conducted hundreds of interviews, consistently applying Amazon’s leadership principles and honing my ability to scale teams and processes effectively.
Amazon gave me rapid exposure to high-velocity execution, rigorous decision-making, and systems built for massive complexity. I was also increasingly convinced that AI, analytics, and data would define the next major era of enterprise software.
By the end of my time at Amazon, I felt ready to bring those lessons to a mid-cap company where I could have a direct, broad impact and help guide its own scaling phase.
The principles I learned at Amazon still shape how I lead product teams today
Although my Amazon experience was unique, the principles I learned there — simplifying the customer experience, treating speed as part of product quality, and rethinking systems end-to-end — can help almost any technology company.
Systems that respond quickly and intuitively earn trust, encourage experimentation, and let users focus on strategy instead of mechanics. At ActiveCampaign, it means pushing my teams to simplify workflows, remove unnecessary complexity, and ship improvements that customers can benefit from immediately.
Amazon’s leadership principles shaped me to see that every product decision comes back to a balance of speed, data, and clarity of intent. Product reviews constantly revolved around a simple question: “Does this serve a real user goal, and can it be iterated quickly?” The mindset of iterative learning allows teams to move quickly, test ideas in real contexts, and continuously improve.
I believe we’re in a pivotal moment for software as a service
SaaS companies that fail to innovate risk disappearing. Success now demands two things at once: improving quality and faster delivery. The only practical way to achieve both is through radical AI coding; supercharging how we build, design, and iterate, and multiplying productivity across the company.
Technology has changed dramatically since I worked on the earliest versions of Alexa, but the leadership principles haven’t. High stakes produce the most necessary, exciting products, and businesses that rise to meet market needs with something genuinely useful will define the future.
