Conversation with David Chen, Co-Founder of Sea and Chief Product Officer of Shopee.
In our Executive Function series, we highlight the perspectives of industry leaders driving the transformation of AI.
Sea Limited (Sea) is one of the world’s leading technology companies, headquartered in Singapore, with businesses spanning digital entertainment, e-commerce, and digital financial services. Its engineering teams build and operate products at scale across some of the most dynamic markets in the world.
Sea has been rolling out Codex across its developer organization, and internal data shows that 87% of users are weekly active users. For the company, AI-powered software development is more than just a productivity boost. It represents a deeper transformation in how engineering teams tackle complexity, build resilient systems, and turn ideas into implementation.
We spoke with David Chen, Co-Founder of Sea and Chief Product Officer of Shopee, Sea’s e-commerce business, to discuss why the company made this investment, how AI agents are changing the way developers work, and what AI-native software development could mean for Southeast Asia—and the broader Asia-Pacific region.
David, Sea’s businesses span many of the most dynamic markets in Southeast Asia. Why did you decide to roll out Codex across the entire engineering organization? What stood out most to you about the product?
At Sea’s scale, engineering is not just about writing code. It is about managing the complexity of large systems in fragmented, highly localized markets. We believe the ongoing evolution of AI is fundamentally changing how software is built, and how engineering teams operate at scale.
Agentic AI coding tools like Codex are not just about improving localized productivity. We see them as structural multipliers that help our engineering organization improve speed, responsiveness, and efficiency in an increasingly complex operating environment.
What has impressed you most about Codex?
What stands out most is its ability to go beyond simple autocomplete and demonstrate deep contextual awareness across a sprawling, distributed codebase. In a large microservices architecture, the real friction is not typing syntax—it is tracing dependencies, understanding legacy logic, and maintaining reliability under peak load.
Codex acts like a localized knowledge engine, significantly reducing the time engineers need to move across unfamiliar services. As a result, teams can direct their cognitive load toward higher-order work such as architecture design and product innovation.
We’ve heard internal feedback that Codex is being used heavily for code understanding, debugging, and feature development. What does that tell you about how developers are using Codex day to day? And how are AI agents starting to change software development at Sea?
The spread of Codex among developers, especially the rise in high-frequency users, is very encouraging. Many people have said it has improved the speed of experimentation and the overall development workflow. According to internal feedback, 73% of developers who gave Codex a 4 or 5 said they would recommend it to a colleague.
The biggest shift is that developers are using Codex not to “type faster,” but to “think better.” We are actively moving from treating AI as a passive autocomplete feature to building integrated agentic workflows.
In practice, AI agents are increasingly operating within CI/CD pipelines. That means they are reasoning about product requirements, autonomously suggesting test-driven implementations, identifying edge cases in distributed systems, and accelerating debugging iterations.
People often think of AI as only making things faster. At Sea, we are also using it to raise engineering discipline. By having AI rapidly prototype alternative implementations and generate comprehensive test coverage, we are moving faster while systematically paying down technical debt and delivering more robust systems.