Post by Mehmet Sinan Toktay

We are entering a phase where AI is not only changing what products do — it is also changing how engineering organizations operate. At Insider One, we are going through a broader transformation across engineering, knowledge, and product layers. On the engineering side, this shift is being shaped through AI Vanguard. Rather than improving a single step in the lifecycle, we are seeing change across the broader engineering landscape as AI starts to reshape how development, testing, security, debugging, and delivery work together. At the same time, we are addressing one of the biggest blockers for scalable AI adoption inside engineering organizations: fragmented knowledge. With 1,000+ repositories and dozens of internal tools, context is often spread across too many places. That is why we are investing in an Engineering Knowledge Base — built on Go and deployed on Kubernetes — to make knowledge more structured, contextual, and accessible for both engineers and AI systems. By centralizing and surfacing the right context at the right time, it enables teams and AI systems alike to operate with a shared understanding of how our infrastructure and services work. And on the product side, we are focused on how to enable products to move toward agentic capabilities — where software can go beyond static features and become more capable of understanding intent, working with context, and taking action. For us, this is not about a single AI feature or a single AI project. It is about building toward an environment where engineering, knowledge, and products evolve together with AI at the core. #InsiderOneEngineering #AITransformation #DeveloperExperience #EngineeringLeadership